*1.5. Organization of This Paper*

This manuscript is organized as follows: After a short introduction of the spectroscopic basics of laser absorption spectroscopy, a discussion of some specific details such as line selection, and the used fitting approach, a detailed outline is given of the experimental setup, including sending, auxiliary, receiving, free-beam guiding unit, and burner. Finally, the initial demonstration of the setup is described by presenting measurements on a standard McKenna burner to validate temperature and species-concentration values (CO, CO2, and H2O) for literature-known operating conditions.


**9. Acknowledgment**

The author wants to recognize the help of the following people: Miss Patricia Karlsson of the National Pension Institution of Helsinki, who was instrumental in revealing Aalto's mastery of light; the kindness and assistance of Professor Mojita Navvab of the University of Michigan are deeply appreciated. Among many other favours, he granted access to MacAllister's original papers. Karma, my research group of the University of Seville was extremely supportive, especially Professors Jesus Pulido and Viggo Castilla; and in Japan, Professor Tetsushi Okumura of the University of Nagoya has always been helpful.

Finally, it is the author's wish to praise the Japanese people for their tenacity and profound respect of Nature, regardless of the tragic blows that She may inflict on this beloved land.


**1. Introduction**

In line with the contemporary literature [1–5], we have identified community and youth work (CYW) as a critical and optimistic practice for 'people and practitioners to work together in order to achieve the kind of social change that is needed for improved equality and social justice" ([6], p. 172). Yet, there is a gap in understanding the extent to which 'equality work' is practiced, and authenticated, in higher education (HE) professional degree programmes that espouse critical pedagogy [7,8] as a bedrock of practice. Building on Biggs' [9] conceptualisation of constructive alignment, and the idea of sustainable assessment as learning for the longer term [10], we question whether practices within higher education embody social justice values and principles. Our research sought to understand how working at the interface between formal and informal education, could help to create knowledge and develop more sustainable teaching, learning and assessment practices in HE. This offered scope to consider more widespread use of alternative methods to bring learning, teaching and assessment practice into constructive alignment with our theorising and teaching of critical pedagogy for social justice [6,11,12].

Antonovsky's [13] work on salutogenesis sought to understand what makes a good healthy life possible and reminded us of what we truly value: spending time with family and friends, and having a sense of community, coherence and freedom. As university

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**Citation:** Gormally, S.; Coburn, A.; Beggan, E. Idealistic Assertions or Realistic Possibilities in Community and Youth Work Education. *Educ. Sci.* **2021**, *11*, 561. https://doi.org/ 10.3390/educsci11090561

Academic Editors: Pam Alldred and Frances Howard

Received: 9 June 2021 Accepted: 16 September 2021 Published: 18 September 2021

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

lecturers, taking time to pause and reflect on our practice, we are able to re-theorise our world and assess if higher education (HE) contributes positively to society. This article considers the impact of HE values and approaches to learning that are pertinent to providing students with a positive educational experience.

CYW degree programmes are designed to facilitate student learning that is aligned with informal education with a clear democratic purpose. Critical pedagogy is portrayed as key to professional learning and is noted as offering an alternative to neoliberal frames that seek to regulate, reduce and standardise students' university experience. According to Taberner [14], the student experience has become fragmented and reduced to marketable outcomes, rather than advancing democracy. Yet, the application of critical pedagogy [15] offers a transformative learning process [16] that aims to help non-traditional students gain a professionally approved degree qualification, whilst becoming an emancipatory practitioner. Such programmes are required to meet both internal institutional scrutiny and external professional approval. This involves negotiation across educational boundaries, in order to mitigate distinctions in the expectations of formal education requirements at HE level and in the expectations of informal education methodologies as the focus of CYW practice. While joint validation processes appear coherent in facilitating synthesis to complete programme approval, this article examines student perspectives that show the extent to which this coherence persists across qualifying programmes, where their specific focus for qualification is located in their professional roles as informal educators in CYW contexts.

This article also examines current contexts in higher education and professional CYW practices. It explains our research methodology and results that offer insights into student experiences of studying CYW. The discussion considers the extent to which CYW students' experiences were constructively aligned with institutional and professional community practices [9]. This helped us to draw conclusions on how learning, teaching and assessment in HE are aligned with critical pedagogy in helping students to articulate their practice and its emancipatory purpose.

### **2. Materials and Methods**

Knowledge was created from a constructo-interpretive epistemological standpoint [17] as a means of interpreting how students come to know and understand their HE experiences. Our ontological position was grounded in the equality of capabilities and conditions [18] to understand how student perceptions were aligned or at odds with assertions of CYW lecturers in HE. Thus, our aim was to undertake a survey of teaching, learning and assessment practices in CYW programmes to consider the veracity of these assertions. Holding a mirror up to HE practice, we expected this survey to inform understanding of the complexities and challenges we face in crossing practice boundaries as informal educators within formal educational contexts.

Data were collected through an online questionnaire (via Microsoft Forms, MF). This offered a rich dataset of evidence that underpinned this article. The questionnaire asked a mixture of closed and open questions. This provided quantitative data that were analysed to produce numeric percentage calculations (generated by MF) and open questions that were analysed to produce qualitative themes, which were generated by an inductive thematic coding process to produce robust and trustworthy results. This involved using highlighter pens to code raw data, which were then grouped together to create themes [19], which enabled us to make sense of participant ideas rather than introducing existing theories or pre-established codes.

Participants were recruited through open invitation distributed via social media, relevant professional bodies and CYW higher education institutions. An open 'link' to access the questionnaire was circulated and posted on social media, which meant that our sample was opportunistic, comprising those who were able to access the link. This process gained 136 responses from graduates (112) and current (24) students on CYW HE programmes. Of the 136 participants, 128 completed a professionally approved programme, 3 completed a non-qualifying programme and 5 were unsure of their programme status. The majority of respondents (73) graduated between 2011 and 2020, while 27 respondents graduated between 2001 and 2010, 11 between 1991 and 2000, 2 between 1981 and 1990, and 1 graduated pre-1981.

The geographical split was UK-based, with only 1 participant from Zambia, who was studying with a UK institution. Despite seeking to recruit a broad range of participants, of the 135 in the UK, 86 were from Scotland, 22 were from England, 22 were from Northern Ireland and 5 were from Wales. The higher rate of Scottish students most likely reflects the fact that all three researchers are from Scottish higher education institutions. Despite this, we argue that so long as participants were studying or had studied CYW at this level, their perspectives were important within a whole country (UK) view, but not geographically representative of each of the four discrete parts of the UK. Our focus was on their headline experiences of learning, teaching and assessment, rather than being overly concerned about the distinctions in devolved governments and funding councils across all four UK nations. We may consider whether these distinctions are important in creating a more nuanced interpretation of praxis, but for now, our findings were analysed at the UK level. Further, as the focus of our research was grounded in CYW programmes as a practice cohort, we did not collect data on specific identifiers such as age or ethnicity. We believed that specific sociodemographic profiling was not applicable to this research, as our focus was on students' experiences in higher education on the CYW programmes without breaking into routine demographics.

Ethical approval for this project was gained from The University of the West of Scotland ethics committee. Questionnaires were fully anonymised, with no names, identifying features, or locations collected. Consent information was communicated in the introduction section of the questionnaire, and taken as given by submitting the form. Only the researchers had access to the results via the MS Forms responses table. All electronic files and documents related to the research were stored on password-protected computers, and any paper documents were securely stored in a locked location. There were no potentially or obviously upsetting questions, and as the subject of this research was their experiences of a programme that they were not responsible for, the risk of being harmed was mitigated.

### **3. Results**

The results for this paper are centred on three areas. The first relates to the understanding of theories that underpinned CYW programmes, questioning whether they align to emancipatory practice. The second is the alignment of teaching and learning with critical pedagogy to create powerful and professionally relevant learning, and the third is analysing assessment methods in professional development, questioning the role of traditional and sustainable approaches as learning for the longer term.

Figure 1 shows that the core selected subject area was 'critical/radical pedagogy and social pedagogy' (75 respondents). This was closely followed by youth work/youth studies (66), ethics/values/self-care (59), groupwork/collaborative and partnership working (57), power and empowerment (56) and community development/activism (55).

As shown in Figure 1, this indicated that the theoretical focus of CYW programmes was aligned with non-traditional pedagogical ideas that were driven by critical or radical theories that were prioritised over more traditional theories. To see these areas of critical, radical and social pedagogy at the forefront of degree programmes that routinely claim this area of educational expertise was heartening.

Building on such theories, it was unsurprising that values and group work or working collaboratively and in partnerships were key subject areas in theorising practice that works across professional boundaries and in a range of contexts. The focus on youth work and youth studies as key was also unsurprising, given that many HE programmes across the UK have an explicit 'youth' focus. The slightly lesser focus on community development/activism may demonstrate that whilst youth work is a central focus for many programmes across the UK, theorising community development principles, community activism and questioning what community is and how community is differently theorised remain important areas for study in CYW programmes. Unpacking the way in which these key subject areas were explored in CYW programmes is vital in understanding how students translated theory into practice and vice versa.

**Figure 1.** Student perspectives on theorising emancipatory practice.

### *3.1. Critical Pedagogy*

Freire [20] advocated for education to be reflective of societal issues. It was therefore affirming to see critical pedagogy as a focus for theorising practice in CYW programmes:

*'Critical pedagogy was a huge influence* ... *[it]* ... *really changed my thinking* ... *how I seen power dynamics* ... *I became much more critically aware'*. (Participant 6)

When asked about theories that opened their minds to new ideas, 25 participants specifically noted Freire's work, which was summed up by one participant as 'Genius', while another stated that 'Freire blew my mind' (participant 29). Critical pedagogy was useful in shaping students' thinking specifically in relation to education and educational institutions,

*'Critical pedagogy in particular was an important aspect* ... *it helped my understanding education, and power relations. This helped me reframe my understanding and emotional relationship to education and learning'*. (Participant 99)

Two participants explicitly connected theory in critical pedagogy to emancipatory practice which challenges injustices,

*'It's recognising rights* ... *Who has them and who doesn't. Who's excluded and why? What kind of world do we want and how nurturing it is'*. (Participant 58)

This form of 'transformative praxis' [21] was key for students' capacity to see direct relevance in a theory they engaged with, and putting it into action:

*'Studying Freire* ... *was incredibly useful on a theoretical level that can be very directly applied into practice. The emphasis on trying to help people to see their contexts in a new way has helped me also open doors to new possibilities in my work and my own learning* ... *the emphasis on seeing* ... *overlapping oppressions and dehumanizing systems, helped me put in more concrete terms what I had been feeling about the world through years of working internationally'*. (Participant 83)

That students have identified critical pedagogy as a core theoretical positioning on CYW programmes demonstrates the capacity to adopt critical pedagogies in formal HE institutions. Critical pedagogy focusses on the interplay between power and knowledge [22], which participants also noted.

### *3.2. Power/Empowerment*

Fifty-six respondents specifically discussed power and empowerment.

*'Paulo Friere and Saul Alinsky opened up my thinking* ... *It's about the ideas of knowledge and power and the acknowledgement of how these are essential in everyday life'*. (Participant 58)

Another participant noted uncomfortableness in reflecting on power differentials but subsequently had a positive impact,

*'Power and Empowerment stood out I felt really uncomfortable at the time doing the activities* ... *it pushed me out of my comfort zone* ... *It irks me to hear colleagues from across the partnership say they 'empower' communities. I believe that we could all do more in this area'*. (Participant 116)

Highlighting key theories on power and the importance of language, the challenging of tokenistic inclusion and dialectical teaching [23] were articulated as key lessons for CYW lecturers involved in educating informal educators.

### *3.3. Ethics and Values*

Explicit links between theories attached to ethics, standards, benchmarks and the capacity to be a good practitioner were noted,

*'Some of these subjects were about shaping what kind of* ... *[practitioner]* ... *we would be and our values—empathy, believing in and understanding equality, ensuring that young people know their rights'*. (Participant 54)

Participants clearly aligned areas of critical pedagogy, power and CYW practice. Additionally, the theorising of ethics, values, and self-care was also important,

*'Our ethics and values were drilled into us... Most CLD practitioners know these off by heart and I think that is important as it should underpin all work and always be our starting point'*. (Participant 11)

The fact that CYW is explicitly a value-driven profession [24,25] may explain why ethics/values and self-care featured so prominently. For others, this process facilitated a thinking of the world they wanted and the type of practitioner they would be,

*'* ... *working in an emancipatory way for social justice and built on CLD ethics and values'*. (Participant 87)

*'* ... *exploring ethics and values to allow yourself to see how you are coming across to others'*. (Participant 31)

The highlighting of the key subject areas on CYW programmes provides some headlines that are important for our community of practice. It is positive that students articulate critical pedagogy as a key focus of our programmes and demonstrates that theoretically, at least, our degree programmes do align with a view of the world which we strive for. However, despite this theoretical positioning, student responses on teaching and learning did not align so strongly with critical pedagogy.

### *3.4. Student Perspectives on: Alignment in Teaching and Learning*

Martin [26] posited that within the neo-liberal environment that currently permeates the educational system, a lack of programmes offering students the opportunity to engage in alternative ways of learning and thinking is troubling. As CYW educators within higher education, we feel that it is imperative that a variety of teaching and learning methods are implemented as a means to creating an equally viable education journey for the varied skill sets of students. Lynch and Baker [27] identified a need for equality of conditions within education and rather than social processes being the same for everyone, this is "about equalizing what might be called people's 'real options', which involves the equal enabling and empowerment of individuals" (p. 132).

From personal experience, we acknowledge that our pedagogy and practice reflect a blended or hybrid approach that uses a mix of face-to-face teaching, synchronous online engagements and asynchronous online engagements. We align our practice and pedagogy with CYW values to developing an informal and socially constructed and trusting relationship with students [23,28,29]. This is not simply about achieving a minimum level of learning, knowledge and understanding required to graduate, but is explicitly connected to the development of ongoing learning, continuous reflection and professional development within and beyond the programme.

From this perspective, it was important to gain a deeper understanding of how students are engaging with the different teaching and learning methods that are offered on the CYW programmes.

Above, Figure 2, shows the response from participants regarding teaching and learning methods on the programmes they attended. These were interesting, in that it came as no surprise that the top three picks were practice/placement (104), group work exercises (103) and collaborative/peer group learning (100). These were fairly typical expectations for a practice-based programme, which showed that the programmes the research participants engaged with offered a pedagogically sound learning experience, indicative of the field of practice. Exposing students of CYW programmes to community-based work in practice seem obvious as a teaching method in this field, where Jakubowski and Burman [30] stated that '[t]here are many reasons pedagogically for bringing classroom and community together' (p. 165), where students have an opportunity to develop ongoing relationships with community members over time.

However, it was interesting to note, that other choices featured in the middle ground. Methods such as critical pedagogy/social pedagogy (48), informal/creative/alternative methods (35) and peer teaching/peer support (22) were less frequently selected. This suggested that while some programmes clearly offered these options, they did not do so as often as those in the top three picks. This is noteworthy to the extent that we routinely see ourselves as advocates of alternative, informal methods in practice, yet this evidence suggests that practices within higher education may not be modelling these methods.

**Figure 2.** Five methods for teaching and learning that were most often used in your degree programme.

### *3.5. Powerful Learning Environments*

Being advocates for alternative methods in teaching and learning is not without complexity. Combining alternative informal methods with the more traditional formal notions of education requires creative thinking. Steffes [31] considered alternative approaches and made reference to 'powerful learning environments' for students which incorporate a 'view of learning that integrates their real world experiences with classroom lectures and discussion' (p. 49).

There were some interesting responses from participants to suggest that a broad range of learning was (and still is) happening.

*'The methods employed ensured total immersion in the subjects and a critical understanding of our place and views- personally and professionally in relation to everything'*. (Participant 32)

*'These areas helped my learning because it was a multi-faceted approach, covering a range of learning styles and scenarios, from reading assignments, to personal study to peer group work, this allowed me not only the time and space to form my own conclusions about the work and topics, but when working with peers it allowed me to see and discuss the similarities or differences between our approaches and mindsets allowing me to take those into consideration, improving my overall practice'*. (Participant 37)

*'I found it difficult to understand the creative methods of assessment in an academic course but it actually worked to ensure everyone had the chance to showcase their learning styles. The placements are where most learning takes place for me'*. (Participant 63)

*'A good mixed variety was used which pushed students out of comfort zones at times which would happen in the workplace so readied me for that again after years away from the field; new ideas and theories from workshops and reading from recommended reading lists or watching suggested videos etc stretched my mind and offered more knowledge and insights into topics and areas I had none or little in. More class time was what I and most fellow classmates said we would have liked more of. Sometimes group work was a hindrance when other group members would or could not make themselves available to meet and work together leaving others carrying them or when personalities clashed too much'*. (Participant 87)

These responses provided insight into how participants felt about the teaching and learning methods in the programmes attended. The above comments show the importance of the variety in methods used as a means to create critical understanding, accommodate different learning styles, facilitate peer learning and dealing with situations that require negotiation and compromise.

However, the results do suggest that there is a heavy reliance on the top three picks, and without these, the programmes would suffer. Modules such as practice placement are vital to the learning experience on CYW practice-based programmes, which is also common-place in most higher education programmes [32–34]. So, if we are to hold a mirror up to our own practice as critical pedagogues, and practice what we preach, we have to find a way of pushing through the other alternative methods that we argue to be so valuable. The difficulty lies in how that might be implemented.

### *3.6. Student Perspectives on: Assessment as Learning for Now, and the Longer Term*

Traditionally, assessment practices were engineered to ensure congruence between instruction and alignment with the curriculum [9]. Formative feedback was provided to improve and guide learning, and summative feedback was given at the end of the learning process to determine grades or award credit on the summation of the student's work [9,35]. Advances in formative assessment have accelerated learning, optimised the quality of learning, and have also raised individual and collective attainment [36,37]. However, Boud and Falchicov [38] noted that higher education assessment practices had not reflected a need for students to develop learning for the longer term.

The findings in Figure 3, show that essay (118 respondents), presentation (101) and reflective accounts (80) were selected as most prevalent, followed by research dissertation (62), course work (62), and practice portfolio (57), which included practice-based tasks and practice observation. The middle-ground assessment methods comprised case study (35), debate (32), academic posters (29), and peer-led seminars (18). Finally, the less frequently selected assessment methods included creative output (14), which included short film- and image-based methods, a capstone project (12) and critical incident analysis (12), game design/training exercises (9), designing learning materials (9), problem solving (7), contribution to the VLE (4), and web-based assessment (4), which included website development/blogs and podcasts.

When asked if assessments did more than simply help to achieve a particular grade, 87% said yes, and typically offered short answers on predictable areas of added value, such as: prompting critical or deeper thinking; creating or consolidating knowledge; and developing understanding of a specific subject area. Typical responses from the remaining 13% who answered 'no' included because the assessment was fit for purpose in achieving a pass grade or was viewed as a 'tick-box exercise', 'the questions had not been changed for years', or 'they were a means to an end'—these answers were indicative of traditional associations with assessment in awarding credit as an immediate or short-term means of grading student work.

**Figure 3.** The top 5 assessment methods featured in your programme.

Routinely, written work underpinned all or most student grades, due to the exclusion of other forms of assessment. While all written assessments were graded, formative assessments or coursework were viewed as facilitating feedback that was not graded. This privileging of written essay-type assessments was assumed, rather than considering alternative methods, for example:

*'I don't really understand this question? Other than the e-portfolio, all of my assessments were written'*. (Participant 108)

*'It was a distance learning programme and the assessments were written'*. (Participant 91)

In not being familiar with alternative assessment methods, participant 108 did not understand the question, and participant 91 believed that a distance learning programme, by design, necessitated written assessments. Yet, where more creative and varied assessment methods were available, participants noted:

*'Critical pedagogy module was in the format of showing it* ... *[Critical Pedagogy]* ... *in use by an assessment that involved us* ... *[students]* ... *in teaching the class and in facilitating learning'*. (Participant 79)

*'While written work was required at times, there were assessments to be completed in the form of presentations, debates, posters and games'*. (Participant 71)

*'I felt just as scrutinised during other means of assessments and got just as critical feedback compared with written work'*. (Participant 35)

These comments show why 41% believed that written work was not privileged over other forms of assessment. Responding to questions on assessment methods, the findings show balance, in that essays and written assessments were beneficial in grading and requirements for formal reporting, while creative or alternative methods were beneficial in widening student learning and enhancing capacity for different intelligences to shine. Thus, the findings clarify that assessment methods were varied and could be used or adapted for assessment and learning beyond the immediate purposes of academic credit [35,38], which included aspects of professional development.

The prevalence in the selected methods gave a total of 671 responses. It is concerning that 71% of this total showed persistence in the use of traditional formal methods comprising written essays, dissertations, presentations and reflective accounts, while 18% of responses showed middle-ground assessments comprising case study, debate, academic posters and peer-led seminars and 11% of respondents selected methods, such as webbased assessment, creative outputs, capstone projects or learning design. This imbalance suggests that assessment practice in HE was inconsistent with critical pedagogy.

### **4. Discussion**

CYW practitioners in the UK work with the most excluded and vulnerable in society, many of whom have borne the brunt of austerity measures and the negative impacts of COVID-19, which intensified levels of poverty and human suffering. Austerity measures were described as 'a harsh and uncaring ethos' by Alston [39] who, as UN Special Rapporteur on extreme poverty and human rights, also noted a 're-discovery of social protection in a global pandemic' [40] (p. 5). Yet, Alston [40] asserted the need for longer term social change where, 'economic recovery...contributes to poverty eradication and the reduction of inequalities' (p. 21). This connects directly to our HE role in teaching informal educators, as preparation for a career in striving for equality and social and structural change within CYW.

This aligns with perspectives that emphasise a role of higher education Institutions (HEIs) as a catalyst for social change, whereby:

*'Community—university engagement* ... *[creates]* ... *a two-way discourse that engages the community and the students to produce socially relevant contemporary knowledge based on active participation* ... *to make the world a better place to live'*. ([41], p. 4)

This discourse on civil society and social responsibility in higher education is consistent with CYW practices, in our aspirations for professional learning in which critical pedagogy connects to both community development and the emancipatory educational purpose that:

*'* ... *relates to a wider conception of education that connects matters of politics and to matters of powerful learning within and beyond the institutions* ... *[that]* ... *explicitly encourages* ... *boundary crossing in which community and institutional values coalesce'*. ([12], pp. 143–144)

While much has been written about the influence of critical pedagogy on formal and informal educational practices [8,15,42], there was a gap in the understanding of CYW student perspectives on whether this knowledge was influential in changing and authenticating practices in HEIs across the UK.

These research results provide robust evidence that, in preparing students for professional practice, CYW students are provided with a solid grounding in theoretical perspectives that are aligned with emancipatory praxis. Helping students to understand critical theory was articulated by students as transformative in facilitating a deep understanding of why CYW practice is important.

The prevalence of critical, radical and social pedagogy, and the analysis of power in theorising practice, was aligned with results that established grassroots practice-based learning and group or peer learning as the most highly selected methods for teaching and learning. This confirmed our expectations for professional grassroots practice that resides in a conceptualisation of critical pedagogy where education is proposed as the practice of freedom [7,8]. In critical pedagogy, education is understood as praxis, where a fusion of theory with practice engages people in 'action and reflection upon the world in order to change it' ([43], p. 206). Aligning critical theory with a strong focus on the practical application of alternative and creative teaching methods was shown by students as key to facilitating social change. Thus, the findings are consistent with Biggs' [9] ideas on constructive alignment, as the results are directly aligned with professional competences for working with people to enable them to engage in learning and to take action that brings change for themselves and their communities [44].

Furthermore, according to Lynch [45], who raised concerns about education as 'being incorporated into the market as an instrument of capitalism and profiteering' (p. viii), there is a requirement for resistance, as a moral imperative, against social and educational injustice. Our findings show that being grounded in ethical practice values and powerful learning environments was useful in creating authentically aligned teaching and learning methods in CYW programmes. These were different from traditional educational theories and methods and thus, we suggest, enacted the kind of resistance called for by Lynch [45]. Yet, evolving circumstances emphasise a need to challenge the marketisation and individualisation of education, in order to emerge from it in a world where all people, not only those who can afford it, have an increased chance of making a good life within a fairer economy that is driven not only by the market but also by well-being [46].

As the first whole-country empirical research of student perspectives specifically on their experiences of CYW programmes, this research adds to the work of Seal [42] to assert that across the UK, HEIs are already engaged in practice that is resistant to traditional theories and methods in education. This suggests that in educating informal educators, alternative, critical and radical theories and a range of teaching and learning methods are routinely, and in some instances strongly, applied in CYW programmes. Yet, this constructive alignment in teaching theory and modelling practice was not so obvious in assessment practices. Here, there was less evidence of alternative or sustainable practices. Despite results that show that some HEIs did use assessments that were constructively aligned [9] to professional roles and values, by utilising a full range of assessment methods, this was often not the case.

The imbalance of formal and traditional assessments, compared to the use of innovative, technologically, or varying from written assessments, was at odds with critical pedagogy and CYW values for emancipatory practice. The utility and scope for aligning assessment practices in HE resides in the evolution of alternative assessment methods that can assist in developing student dispositions as lifelong learners and as assessors of their own and others' learning [10,47,48]. Increasing creative and technological methods for face-to face and web-based assessment needs further consideration in the evolution of assessment in HE, as part of the wider contribution of a civic university.

Rather than simply measuring progress within the curriculum, as a means of grading coursework, assessment has been proposed as a means of 'equipping students to learn in situations in which teachers and examinations are not present to focus their attention' ([10], p. 3). If we aspire to achieve more sustainable assessment for CYW students, lecturers and students will be required to reflect on how assessment might be more usefully aligned with CYW praxis. How can assessment be reconfigured, enhanced and developed sustainably as a means of creating an authentic constructive alignment on the boundaries of informal and formal education?

Our analysis of student perspectives on educating informal educators has thus raised more questions than answers, particularly in areas that were not selected by respondents. For example, the lack of focus on international development/international perspectives is

concerning, as many programmes pride themselves on the international links they try to forge. Yet, within this predominantly UK context, it seems that students and graduates do not see international perspectives at the forefront of their curriculum. Other examples of low selection areas (less than five responses) included psychological perspectives, project and people management, culture/cultural planning/cultural contexts and academic study. These responses make us reflect on the future progression and focus of CYW professional HE programmes.

Analysis confirms that we can claim to apply critical pedagogy as an emancipatory practice which 'offers a powerful device for enabling us to challenge mainstream representations' ([42], p. 40) within the context of a power-laden university environment. However, this is not without its challenges. As Seal [42] noted, 'we teach it in universities, which are formal, rule bound, with distinct hierarchies and often elitist and reinforce multiple hegemonies' ([42], p. 24). This work, drawing on case studies from academics around the world, about teaching critical pedagogy exemplified the applied nature of civic education in Finland, where graduates were identified as community educators as part of an aim to 'educate experts for professional working life' ([42], p. 59). However, it did not offer empirical evidence or case study examples on how these theories were applied to the HE teaching practices of their home institutions. Thus, in considering the extent to which critical pedagogy is modelled in teaching emancipatory practice in CYW programmes, our analysis offers insights on a kind of civic education of professional CYW practitioners. In turn, this aligns with the idea of a civic university, where more effective engagement between HEIs and local communities is key to enabling institutions to meet their social responsibilities and 'to act as catalysts for social change with the potential to address and mitigate a variety of social problems' ([41], p. 4), where it is argued that 'critical pedagogy ... offers not just a framework for action, but a set of guiding principles that might inform aspects of teaching, research, citizenship and knowledge exchange' ([12], p. 142).

### **5. Conclusions**

Reflecting critically on student perceptions regarding teaching, learning and assessment in CYW programmes demonstrates a resistance to mainstream representations of institutional power. Our assertion is that boundary crossing persisted at the interface between the formal and informal paradigms. Furthermore, there was evidence of a more holistic and critical pedagogical approach in areas of teaching and learning that was aligned with methods from CYW practice. To a lesser extent, there was some evidence of shifting assessment practices in HE that did model critical pedagogy, but more traditional methods persisted. This showed that across a range of professionally qualifying degree programmes, critical pedagogy was theorised and taught as an emancipatory practice that operated on the boundaries between formal and informal learning within HEIs and was constructively aligned with CYW professional praxis.

Having held a mirror up to our own HE practices, the results of our analysis of student and graduate views inform our understanding that we are effective as informal educators within formal educational contexts. The discussion showed that in theorising, and in many teaching and learning contexts, CYW students provided evidence of an experience that was clearly and constructively aligned with critical pedagogy. This finding aligns with recent work from Seal [49] in advocating for hopeful pedagogies and celebrating those pedagogies in HE that challenge dominant discourses and strive for a more utopian reading of the world.

Yet, when it came to assessment, this alignment was less obvious, particularly in relation to assessment methods. Our focus on the application of critical pedagogy in HE practice as a catalyst for institutional change suggests that there is much to celebrate in the research results, as CYW programmes do prepare students as experts in critical pedagogy that can be applied in CYW practice. However, the results also show that many programmes seemed to be constrained in shifting pedagogic and assessment practices to fully embrace and model this alignment with emancipatory practice. There remains a challenge in bringing about more widespread change within HE institutions to enhance the experiences of our students and their emerging role as community practitioners. The idea of social responsibility in HE creates an opportunity for working within our various institutions to change practices. Our research confirms that we are already working at the interface between formal, informal and professional education within many HEIs. In seeking to promote social responsibility as a framework for equality and social justice, our CYW programmes are well-placed to drive institutional change forward in the interests of our students, our profession and the communities we serve.

**Author Contributions:** Writing—original draft, S.G., A.C. and E.B. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** The study was approved by the School of Education and Social Sciences Ethics Committee, University of West of Scotland.

**Informed Consent Statement:** Informed consent was obtained from all subjects involved in the study.

**Conflicts of Interest:** The authors declare no conflict of interest.

### **References**


*Pre-Sports Participation Cardiac Screening Evaluation – A Review DOI: http://dx.doi.org/10.5772/intechopen.102942*

two branches, namely the left anterior descending (LAD) and circumflex. The LAD continues in the same course as the left main CA and traverses in the interventricular groove. The circumflex traverses perpendicular to the axis of the left main CA and keeps on going in the posterior atrioventricular groove. The left CA perfuses the LV and interventricular septum [14, 15]. The right CA originates from the right sinus of Valsalva and continues in the right atrioventricular sulcus and does not branch out similar to the left CA. The right CA supplies the RV [14, 15]. The site of origin and the course of the CAs proximally can easily be demonstrated in echocardiographic studies (**Figures 10** and **11**). Color flow mapping of the CAs (**Figures 11** and **12**) should also be undertaken concurrently to ensure that the parallel lines of the transverse sinus of the pericardium are not mistaken for CAs [16].


power of haloacetates has been enhanced by incorporating DCA and other derivatives in phospholipid nanoparticles [69]. Increasing the local concentration of the inhibitor through the nanoparticle ensured efficient delivery. Although the doses used for Thio-DCA treatment are still high, they are lower than those employed in recent reports on the use of DCA, usually reaching up to 50 mM [44,70,71], and are similar to DCA concentrations used in sensitive cell lines [72]. The most important observation of our work is, however, that mitochondrial accumulation, promoted by a neutral carrier, enhanced the effect of the drug in several DCA-resistant cell lines. With this proof-of-concept, there is still plenty of room to improve drug efficacy by incorporating it in delivery nanoparticles [69] or supramolecular caging agents [73] and improving drug selectivity by reducing thiophene-associated toxicity by adding substitution radicals to the thiophene ring [38].

It is also informative to consider previous reports on anticancer drug design that involve thiophene cores. These drugs exhibited higher activity than previous inhibitors [74]. Likewise, thiophene-containing natural products, such as the bithiophenes arctinal and arctinol-b, have been shown to have antifungal and antimicrobial activity [75], as well as other cytotoxic effects on tumor cell lines [76]. Thiophene-modified coumarins also exhibit enhanced cytotoxicity towards cancer cell lines, whereas normal fibroblast cells are less affected [77]. In a recent report, Lisboa et al. described a chimeric drug of acridine andmodified thiophene with promising antitumoral activity [78]. We hypothesize that, in some cases, the primary cause of this activity may be inhibitor accumulation in the mitochondria, which is influenced by the thiophene core and enhances the inhibition mechanism by directly targeting where the metabolic reaction occurs.

Our current research lines aim to determine whether different subtypes of breast cancer cells display differential metabolic phenotypes [15,61]. Gaining knowledge about key metabolic features in breast cancer and their functional, molecular and genetic interrelationships could pave the way for a novel clinical classification, revealing potential therapeutic antimetabolic targets, and diagnostic approaches. The thiophene moiety as a noncharged neutral carrier for targeting mitochondria may represent a considerable advantage to overcome synthetic problems, paving the way to the rational design of new metabolism-targeted anticancer hybrid drugs [78,79]. The full potential of such drugs will be accomplished by incorporating additional substituents to the thiophene ring, aiming for improved selectivity in localization, activity and toxicity.

#### **4. Materials and Methods**

*4.1. Synthesis Reactions of New Compounds*

#### 4.1.1. General Details

All reagents and solvents (CH2Cl2, ethyl acetate (EtOAc), hexane, CH3CN, and methanol (MeOH)) were purchased from standard chemical suppliers and used without further purification. To ensure the dryness of tetrahydrofuran (THF), it was freshly distilled over Na/benzophenone. Anhydrous solvents (dimethylformamide (DMF), CH2Cl2 and diethyl ether (Et2O)) were purchased from standard suppliers. Thin-layer chromatography (TLC) was performed on aluminum-backed plates coated with silica gel 60 (230–240 mesh) with the F254 indicator. The spots were visualized with UV light (254 nm and 360 nm) and/or stained with phosphomolybdic acid (10% ethanol solution) and subsequent heating. All chromatographic purifications were performed with silica gel 60 (230–400 mesh). NMR spectra were measured at room temperature. 1H NMR spectra were recorded at 300, 400, or 500 MHz either in a Varian Direct Drive (Varian Inc., Palo Alto, CA, USA) or Bruker Avance NEO (Bruker BioSpin GmbH, Rheinstetten, Germany). Chemical shifts are reported in ppm using the residual solvent peak as a reference (CHCl3: δ = 7.26 ppm, CH3OH: δ = 3.31 ppm, and (CH3)2SO: δ = 2.50 ppm). Data are reported as follows: chemical shift, multiplicity (s: singlet, d: doublet, t: triplet, q: quartet, quint: quintuplet, m: multiplet, dd: doublet of doublets, dt: doublet of triplets, td: triplet of doublets, and bs: broad singlet), coupling constant (*J* in Hz) and integration. 13C NMR spectra were recorded at 75, 101, 126 or 151 MHz using broadband proton decoupling, and chemical shifts are reported in ppm using the

residual solvent peaks as a reference (CHCl3: δ = 77.16 ppm, CH3OH: δ = 49.00 ppm, and (CH3)2SO: δ = 39.52 ppm). Carbon multiplicities were assigned by distortionless enhancement by polarization transfer (DEPT) techniques. High-resolution mass spectra (HRMS) were recorded by EI at 70 eV on a Micromass AutoSpec mass spectrometer (Waters Co., Milford, MA, USA) or by ESI on a Waters VG AutoSpec mass spectrometer (Waters Co.). For the synthesis of the compounds described herein, several precursors were required to be prepared, including 2-[3-(4-bromo-3-methyl-phenoxy)propoxymethyl]thiophene (precursor **VII,** Scheme S4 in the SM) and 2,7-di-[*tert*-butyldimethylsilyloxy]-xanthone (precursor **VIII**, Schemes S4 and S5 in the SM). Compounds **1** (Schemes S1–S3) and **4** (Scheme S6) were prepared as previously described, isolated as pure samples and showed NMR spectra identical to reported data [40,51]. Further details on the synthesis and characterization of all the precursors and compounds **1**–**4**, including 1H NMR and 13C NMR spectra (Figures S1–S16), are compiled in the SM.

4.1.2. Synthesis of 6-hydroxy-9-(2-methyl-4-(3-(thiophen-2-ylmethoxy)propoxy)phenyl)- 3H-xanthen-3-one (compound **2**, Scheme S4)

*t*-BuLi (1.7 M in hexane, 0.96 mL, 1.64 mmol) was added dropwise to a solution of compound **VII** (279 mg, 0.82 mmol) in freshly distilled THF (4 mL) under an Ar atmosphere at −78 ◦C. After keeping the reaction at that temperature for 20 min, a solution of compound **VIII** (187 mg, 0.41 mmol) in THF (2 mL) was slowly added. Then, the mixture was stirred at −78 ◦C for 15 min and allowed to reach room temperature. The reaction was monitored by TLC. After consumption of compound **VIII**, 10% HCl (1 mL) was added, promoting a color change from light yellow to orange. Finally, the solvent was removed, and the residue was purified by flash chromatography (SiO2, CH2Cl2/MeOH 9:1) to yield compound **2** (130 mg, 66%) as an orange solid. 1H NMR (400 MHz, MeOD) δ 7.36 (dd, *J* = 5.1, 1.2 Hz, 1H), 7.12 (d, *J* = 8.4 Hz, 1H), 7.08 (d, *J* = 9.7 Hz, 2H), 7.05–7.03 (m, 1H), 7.00 (d, *J* = 2.5 Hz, 1H), 6.9–6.94 (m, 2H), 6.68–6.64 (m, 4H), 4.72 (s, 2H), 4.17 (t, *J* = 6.2 Hz, 2H), 3.72 (t, *J* = 6.1 Hz, 2H), 2.09 (quint, *J* = 6.2 Hz, 2H), 2.02 (s, 3H). 13C NMR (101 MHz, MeOD) δ 179.0 (C), 161.5 (C), 159.7 (C), 156.5 (C), 142.5 (C), 138.9 (C), 132.3 (CH), 131.5 (CH), 127.59 (CH) 127.58 (CH), 126.8 (CH), 126.0 (C), 123.4 (CH), 117.6 (CH), 115.5 (C), 113.3 (CH), 104.5 (CH), 68.3 (CH2), 67.4 (CH2), 66.0 (CH2), 30.7 (CH2), 20.0 (CH3). HRMS (ESI): *m/z* [M+H]+ calculated for C28H25O5S: 473.1417 found: 473.1416.

#### 4.1.3. Synthesis of 6-hydroxy-9-(thiophen-3-yl)-3H-xanthen-3-one (compound **3**, Scheme S5)

*t*-BuLi (1.7 M in hexane, 0.66 mL, 1.12 mmol) was added dropwise to a solution of 3-iodothiophene (118 mg, 0.56 mmol) in freshly distilled THF (2 mL) under an Ar atmosphere at −50 ◦C. After keeping the reaction at that temperature for 20 min, a solution of compound **VIII** (128 mg, 0.28 mmol) in THF (2 mL) was slowly added. Then, the mixture was stirred at −50 ◦C for 15 min and allowed to reach room temperature. The reaction progress was monitored by TLC. After consumption of compound **VIII**, 10% HCl (1 mL) was added, promoting a color change from light yellow to orange. Finally, the solvent was removed, and the residue was purified by flash chromatography (SiO2, CH2Cl2/MeOH 8:2) to yield compound **3** (48 mg, 59%) as an orange solid. 1H NMR (500 MHz, DMSO-*d*6) δ 7.93–7.87 (m, 2H), 7.32 (dd, *J* = 4.7, 1.4 Hz, 1H), 7.22 (d, *J* = 9.3 Hz, 2H), 6.64 (bs, 4H). 13C NMR (126 MHz, DMSO-*d*6) δ 145.4 (C), 132.2 (C), 130.5 (CH), 129.3 (CH), 128.0 (CH), 127.7 (CH). Several carbons are not observed. HRMS (EI): *m/z* [M]+ calculated for C17H10O3S: 294.0351 found: 294.0339.

#### 4.1.4. Synthesis of Thio-DCA

4-dimethylaminopyridine (DMAP, 429 mg, 3.51 mmol) was added to a solution of 2-thiopheneethanol (0.26 mL, 2.34 mmol) in CH2Cl2 (5 mL). After 5 min, dichloroacetyl chloride (0.27 mL, 2.81 mmol) was added dropwise. The mixture was stirred at room temperature and monitored by TLC until consumption of starting materials occurred (5–10 min). Celite was then added, and the solvent was removed. The crude material was purified by flash chromatography (SiO2, hexane/EtOAc 9:1) to yield Thio-DCA (512 mg, 91%) as a light yellow liquid. 1H NMR and 13C NMR spectra are shown in the SM. 1H NMR (400 MHz, CDCl3) δ 7.19 (dd, *J* = 5.1, 1.2 Hz, 1H), 6.96 (dd, *J* = 5.1, 3.4 Hz, 1H), 6.90 (dd, *J* = 3.4, 1.2 Hz, 1H), 5.95 (s, 1H), 4.49 (t, *J* = 6.7 Hz, 2H), 3.25 (t, *J* = 6.7 Hz, 2H). 13C NMR (75 MHz, CDCl3) δ 164.5 (C), 138.7 (C), 127.2 (CH), 126.1 (CH), 124.5 (CH), 67.6 (CH2), 64.3 (CH), 29.0 (CH2). HRMS (ESI): *m/z* [M+Na]+ calculated for C8H8O2Cl2SNa: 260.9514 found: 260.9513.

#### *4.2. Instrumentation*

Absorption spectra of the different dyes in aqueous solutions were obtained on a Lambda 650 UV–visible spectrophotometer (PerkinElemer, Waltham, MA, USA). The steady-state fluorescence emission and excitation spectra were collected using a Jasco FP-8300 spectrofluorometer (Jasco, Tokyo, Japan). Time-resolved fluorescence decay traces were obtained on a FluoTime 200 SPT spectrofluorometer (PicoQuant GmbH, Berlin, Germany). The concentration of dyes in spectroscopic measurements was between 0.5 × 10−6 and 5 × 10−6 M.

Colocalization studies using dual-color confocal microscopy were performed on a Fluoview FV1000 laser scanning microscope (Olympus, Tokyo, Japan). For imaging compound **2**, compound **3** or MT, the sample was excited with a 405 nm, 488 nm or 635 nm laser line, respectively. Emission from compounds **2** (between 410 and 490 nm) and **3** (between 500 and 580 nm) was collected using a grating, whereas emission from MT was collected with a BA655-755 bandpass filter. Dual-color FLIM experiments were performed on a MicroTime 200 microscope (PicoQuant GmbH, Berlin, Germany) equipped with 440 nm, 470 nm, and 635 nm pulsed diode lasers as excitation sources. Emission from fluorophores **1**–**4** was separated from that of MT using a 600DCXR dichroic mirror. Different bandpass filters were used for the collection of the fluorescence of **1** (465/30), **2**–**4** (520/35) and MT (685/70). Further experimental settings for each instrument can be found in the SM and Table S1. The concentration of dyes in the fluorescence imaging experiments was 3 × 10−7 M.

The effect of 2-(3-thienyl)ethanol, DCA or Thio-DCA compounds on cell viability was examined using the CellTiter BlueTM viability assay (Promega Corp. Madison, WI, USA). Cells were plated in quadruplicate in black, cell culture-treated, 96-well, optical, flatbottom plates at a density of 8 × 104 cells/well. The viability results of different treatments were compared to those of the control (cells in the presence of deuterated DMSO) at both 99% or 95% confidence using the Holm-Bonferroni and Holm-Sidak tests and the nonparametric Kolmogorov-Smirnov and Mann-Whitney tests in Origin 9.0 (OriginLab Corp., Northampton, MA, USA).

Further details about all the experimental methods, procedures and instrumentation can be found in the SM.

#### *4.3. Cell Culture*

For the imaging and viability experiments in this work the cell lines 143B (CRL-8303), HeLa (CCL-2), MCF7 (HTB-22), MDA-MB-231 (CRM-HTB-26), and SKBR3 (HTB-30) were acquired from the American Type Culture Collection (ATCC, Manassas, VA, USA), and the lines MDA-MB-468 (ACC 738) and ZR751 (ACC 8701601) were obtained from the Leibniz-Institut DMSZ, German collection of microorganisms and cell cultures GmbH (DMSZ, Braunschweig, Germany). Further details about culture protocols and procedures can be found in the SM.

**Supplementary Materials:** The following are available online at https://www.mdpi.com/1999-4 923/13/2/254/s1: Scheme S1. Synthesis of compounds I and II from 1,3-propanediol.; Scheme S2. Bromination of 2-thiophenemethenol.; Scheme S3. Synthesis of compound 1 from 2-methoxyacridin-9(10H)-one.; Scheme S4. Synthetic route for the preparation of compound 2 starting from 4-bromo-3 methylphenol.; Scheme S5. Nucleophilic addition of 3-iodotiophene to ketone VIII to obtain xanthene 3.; Scheme S6. Synthesis of BODIPY derivative 4.; Figure S1. 1H-NMR (500 MHz) spectrum of compound II in CDCl3.; Figure S2. 13C-NMR (126 MHz) spectrum of compound II in CDCl3.;

Figure S3. 1H-NMR (500 MHz) spectrum of compound 1 in MeOD.; Figure S4. 13C-NMR (126 MHz) spectrum of compound 1 in MeOD.; Figure S5. 1H-NMR (400 MHz) spectrum of compound V in CDCl3.; Figure S6. 13C-NMR (101 MHz) spectrum of compound V in CDCl3.; Figure S7. 1H-NMR (400 MHz) spectrum of compound VI in CDCl3.; Figure S8. 13C-NMR (101 MHz) spectrum of compound VI in CDCl3.; Figure S9. 1H-NMR (400 MHz) spectrum of compound VII in CDCl3.; Figure S10. 13C-NMR (101 MHz) spectrum of compound VII in CDCl3.; Figure S11. 1H-NMR (400 MHz) spectrum of compound 2 in MeOD.; Figure S12. 13C-NMR (101 MHz) spectrum of compound 2 in CDCl3.; Figure S13. 1H-NMR (500 MHz) spectrum of compound 3 in DMSO-d6.; Figure S14. 13C-NMR (126 MHz) spectrum of compound 3 in DMSO-d6.; Figure S15. 1H-NMR (400 MHz) spectrum of compound Thio-DCA in CDCl3.; Figure S16. 13C-NMR (75 MHz) spectrum of compound Thio-DCA in CDCl3.; Table S1. Dual-color FLIM instrumental settings for colocalization studies of each dye.; Figure S17. Absorption (**A**, **C**) and fluorescence emission (**B**, **D**) spectra of dyes 1 (**A**, **B**) and 4 (**C**, **D**) at different pH values. The excitation wavelength for the emission spectra was 375 nm for compound 1 and 495 nm for compound 4.; Figure S18. Absorption and fluorescence emission dependence with pH of dyes 2 (**A**–**C**) and 3 (**D**–**F**) in aqueous solution. **A** and **D**) Absorption spectra at different pH values of dyes 2 (**A**) and 3 (**D**). B and **E**) Global fittings of the A vs pH data to the general equilibrium equations [15,16] to obtain the ground state pKa values of dyes 2 (**B**) and 3 (**E**). (**C** and **F**) Fluorescence emission spectra (λex = 490 nm) of dyes 2 (**C**) and 3 (**F**) in aqueous solution at different pH values.; Figure S19. Average fluorescence lifetime, τ, of dye 3 in methanol:glycerine mixtures of different viscosity at 20, 30 and 40 ◦C.; Figure S20. Photostability of dyes 1–4 during 2 h of continuous irradiation.; Figure S21. Representative dual-color FLIM images of compound 1 in 143B cells and ρ0206 cells after 20 min of incubation with MT. Panels (**A**) and (**B**) show FLIM images on a pseudo-color scale (between 0 and 17 ns) of the dye's detection channel (left) and the MT detection channel (right). These examples were performed on human osteosarcoma 143B cells (**A**) and ρ0206 cells (**B**). The latter are tumor cells depleted of mitochondrial DNA, thus displaying an extreme metabolic phe-notype due to the absence of respiration [10]. Panels (**C**) and (**D**) show the colocalization images of 1 (green) and MT (red) in 143B cells (**C**) and ρ0206 cells (**D**). Scale bars represent 10 μm. Panels (**E**) and (**F**) show intensity traces in both channels for the depicted lines in images in panels C (for 143B cells) and D (for ρ0206 cells), respectively.; Figure S22. Representative dual-color, super-resolution optical fluctuation imaging (SOFI) of 1 (green channel) and MT (red channel) in formaldehyde-fixed HeLa cells, and intensity plots of the profile lines. Scale bars represent 5 μm.; Figure S23. Mitochondrial localization of compound 1 in 143B cells, after 20 min of incubation with MT, from dual-color FLIM images. Left panels represent the raw intensity images in the 1 channel and the MT channel. Central panels represent the selected region of interest, in cyan for compound 1 and red for MT. Rightmost panels are the overlaid images, with colocalized pixels represented in white color. Scale bars represent 10 μm.; Figure S24. FLIM imaging of compound 1 in 143B cells. The images show the fluorescence lifetime of 1 depicted on a pseudocolor scale between 13 and 16 ns. The leftmost column of images shows colocalized pixels with mitochondria. The central column of images shows non colocalized pixels. The rightmost column of images shows the overall images. Scale bars represent 10 μm. The plots on the right panels represent the pixel distribution of fluorescence lifetime of 1 in each image, localized in mitochondria (black lines) or in other cellular subcompartments (red lines), and the overall lifetime distribution (green lines). Given that the acridone core has a lifetime that depends on the polarity of the microenvironment [18], these data clearly show that the mitochondria matrix is a less polar environment than cellular cytoplasm.; Figure S25. Representative dual-color FLIM images of compound 2 in 143B (**A**, **C**, and **E**) and ρ0206 cells (**B**, **D**, and **F**), after 20 min of incubation with MT. In the FLIM images (**A** and **B**), the dye's detection channel (left) and the MT detection channel (right) are shown separately. The colocalization images (**C** and **D**) of the dye (green) and MT (red) are also shown. Intensity traces in both channels (**E** and **F**) are shown for the depicted lines (marked as 1, 2 and 3) in the colocalization panels. Scale bars represent 10 μm.; Figure S26. Mitochondrial localization of compound 2 in ρ0206 cells, after 20 min of incubation with MT, from dual-color FLIM images. Left panels represent the raw intensity images in the 2 channel and the MT channel. Central panels represent the selected region of interest, in cyan for compound 2 and red for MT. Rightmost panels are the overlaid images, with colocalized pixels represented in white color. Scale bars represent 10 μm.; Figure S27. Mitochondrial localization of compound 3 in MDA-MB-231 cells, after 20 min of incubation with MT, from dual-color FLIM images. Left panels represent the raw intensity images in the 3 channel and the MT channel. Central panels represent the selected region of interest, in cyan for compound 3 and red for MT. Rightmost panels

are the overlaid images, with colocalized pixels represented in white color. Scale bars represent 10 μm.; Figure S28. FLIM imaging of compound 3 in MDA-MB-231 cells. The images show the fluorescence lifetime of 3 depicted on a pseudocolor scale between 3 and 6 ns. The leftmost column of images shows colocalized pixels with mitochondria. The central column of images shows non colocalized pixels. The rightmost column of images shows the overall images. Scale bars represent 10 μm. The plots on the right panels represent the pixel distribution of fluorescence lifetime of 3 in each image, localized in mitochondria (black lines) or in other cellular subcompartments (red lines), and the overall lifetime distribution (green lines).; Figure S29. Representative dual-color FLIM images of compound 4 in 143B (**A**, **C**, and **E**) and ρ0206 cells (**B**, **D**, and **F**), after 20 min of incubation with MT. In the FLIM images (**A** and **B**), the dye's detection channel (left) and the MT detection channel (right) are shown separately. The colocali-zation images (**C** and **D**) of the dye (green) and MT (red) are also shown. Intensity traces in both channels (E and F) are shown for the depicted lines in the colocalization panels. Scale bars represent 10 μm.; Table S2. Pearson's correlation coefficient (PCC) and Manders' colocalization coefficient (MCC) values for the colocalization of dyes 1–4 with the mitochondria tracker MT.[a].; Figure S30. Representative dual-color fluorescence images of compound 1 (green) and the MT tracker (magenta) in 143B cells after 20 min of incubation with BAM15. Scatter plots represent the corre-lation of the intensity values in the green channel vs the red channel. Scale bars represent 10 μm.; Figure S31. Cell viability of SKBR3 breast cancer tumor cells treated with 2-(3-thienyl)ethanol at different doses. Error bars represent standard deviations. Line represents the fit to a dose-response function.

**Author Contributions:** Conceptualization, M.J.R.-R., M.M., J.M.C. and A.O.; formal analysis, C.R., P.H.-F., V.P.-M., M.C.G.-G., J.M.P., E.G.-F. and A.O.; funding acquisition, M.J.R.-R., J.M.C. and A.O.; investigation, C.R., P.H.-F., V.P.-M., M.C.G.-G., D.M., S.R., E.G.-F. and A.O.; methodology, C.R., D.M., J.M.P., M.J.R.-R., M.M., M.R., S.R., H.De K., J.H., J.M.C. and A.O.; project administration, A.O.; resources, P.H.-F., D.M., S.R., M.R., S.R., H.De K., J.H. and J.M.C.; Supervision, D.M., J.M.P., M.J.R.-R., E.G.-F., M.M., M.R., S.R., H.De K., J.H., J.M.C. and A.O.; visualization, D.M., J.M.P., E.G.-F., S.R. and H.De K.; writing–original draft, C.R. and A.O.; writing–review & editing, C.R., P.H.-F., V.P.-M., M.C.G.-G., D.M., S.R., J.M.P., M.J.R.-R., E.G.-F., M.M., S.R., J.H. and J.M.C. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research: including APC charges, was funded by the Spanish Agencia Estatal de Investigación (Ministry of Science and Innovation) and the European Regional Development Fund [grant numbers CTQ2014-56370-R, CTQ2014-53598, and CTQ2017-85658-R]; Fundación Ramón Areces; and the initiative Solidaridad Entre Montañas. J.H. acknowledges financial support from the Flemish government through long-term structural funding Methusalem (CASAS2, Meth/15/04).

**Data Availability Statement:** The data presented in this study are openly available in University of Granada repository, Digibug at http://hdl.handle.net/10481/66449, reference number 10481/66449.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

60. Ayyanathan, K.; Kesaraju, S.; Dawson-Scully, K.; Weissbach, H. Combination of Sulindac and Dichloroacetate Kills Cancer Cells via Oxidative Damage. *PLoS ONE* **2012**, *7*, e39949. [CrossRef] [PubMed]

## *Article* **CancerGram: An Effective Classifier for Differentiating Anticancer from Antimicrobial Peptides**

**Michał Burdukiewicz 1,2, Katarzyna Sidorczuk 3, Dominik Rafacz 2,4, Filip Pietluch 3, Mateusz B ˛akała 4, Jadwiga Słowik 4 and Przemysław Gagat 3,\***

Received: 14 October 2020; Accepted: 29 October 2020; Published: 31 October 2020

**Abstract:** Antimicrobial peptides (AMPs) constitute a diverse group of bioactive molecules that provide multicellular organisms with protection against microorganisms, and microorganisms with weaponry for competition. Some AMPs can target cancer cells; thus, they are called anticancer peptides (ACPs). Due to their small size, positive charge, hydrophobicity and amphipathicity, AMPs and ACPs interact with negatively charged components of biological membranes. AMPs preferentially permeabilize microbial membranes, but ACPs additionally target mitochondrial and plasma membranes of cancer cells. The preference towards mitochondrial membranes is explained by their membrane potential, membrane composition resulting from *α*-proteobacterial origin and the fact that mitochondrial targeting signals could have evolved from AMPs. Taking into account the therapeutic potential of ACPs and millions of deaths due to cancer annually, it is of vital importance to find new cationic peptides that selectively destroy cancer cells. Therefore, to reduce the costs of experimental research, we have created a robust computational tool, CancerGram, that uses *n*-grams and random forests for predicting ACPs. Compared to other ACP classifiers, CancerGram is the first three-class model that effectively classifies peptides into: ACPs, AMPs and non-ACPs/non-AMPs, with AU1U amounting to 0.89 and a Kappa statistic of 0.65. CancerGram is available as a web server and R package on GitHub.

**Keywords:** anticancer peptide (ACP); antimicrobial peptide (AMP); anticancer peptides; antimicrobial peptides; host defense peptides; prediction; random forest

#### **1. Introduction**

There are many health care issues that challenge the welfare of humankind; among them, cancer and antimicrobial resistance are of ever-growing concern. According to the World Health Organization, cancer is a leading cause of death globally, responsible for about 9.6 million deaths in 2018 [1], and antimicrobial resistance threatens our ability to treat an increasing number of infectious diseases, with a death toll of tens of thousands of people in Europe and the United States [2,3]. Interestingly, both these challenges could be approached with cationic peptides, antimicrobial peptides (AMPs) and anticancer peptides (ACPs), respectively.

AMPs, also known as host defense peptides, constitute a diverse group of bioactive molecules that provide multicellular organisms with protection against bacteria, fungi, protozoans and viruses [4,5], and microorganisms with weaponry for competition [6,7]. Some AMPs can target cancer cells; this particular group of AMPs is called anticancer peptides (ACPs). AMPs, including ACPs, are short peptides, generally with fewer than 50 amino acids, that are rich in positive and hydrophobic residues, and, consequently, have amphiphilic properties [4,8]. Due to these characteristics, they preferentially interact with negatively charged components of biological membranes, which are typical of the bacterial cell wall and the plasma membrane of cancer but not healthy cells. As a result, AMPs and ACPs lead to membrane micellization and/or permeabilization by forming pores [9–12]. By definition, AMPs target microbial membranes, especially bacterial envelopes, but ACPs, apart from their antimicrobial activity, also exhibit anticancer properties due to slightly different amino acid composition (for details, see [13] and Section 3.1).

One of the promising targets of anticancer therapies are mitochondria, cytoplasmic organelles derived from an ancestor of *α*-proteobacteria [14–16]. Mitochondria not only provide the energy and building blocks for new cells, but they are also the regulatory centers of redox homeostasis and apoptosis [17]. Interestingly, ACPs can bind to and affect the integrity of the plasma membrane of cancer cells; however, they preferentially disrupt mitochondrial membranes—specifically, they do so at concentrations hundreds of times lower than the concentrations for plasma membrane disruption [18]. The preference is due to the difference in membrane potential that is generated during oxidative phosphorylation at the inner mitochondrial membrane by proton pumps [19]. The membrane potential drives cations and cationic peptides into mitochondria, but because it is steadily increased in cancer cells, it provides even greater killing capacity in the cancerous environment [19–21]. Some preference for targeting mitochondria is also attributed to the fact that mitochondrial membranes still resemble, in terms of composition, the envelope of Gram-negative bacteria, and, therefore, attract AMP-like molecules [22,23]. Moreover, proteins imported into mitochondria carry an N-terminal targeting signal known as the mitochondrial transit peptide, which actually could have evolved from AMPs [24,25]. Since mitochondrial transit peptides show considerable similarity to their presumed progenitors, AMPs might also use the traditional Tom/Tim-dependent pathway to enter mitochondria [26].

Taking into account the therapeutic potential of ACPs, i.e., high target specificity, good efficacy, low toxicity, easy chemical modification and synthesis, it is of vital importance to find new cationic peptides that could target cancer cells [12,27]. Unfortunately, the experimental procedures to identify novel ACPs are time-consuming and expensive. Consequently, there is a demand for efficient and accessible bioinformatics tools that could help indicate potential ACP candidates with high accuracy for further research.

A number of computational approaches have been adopted for ACP prediction; however, there are serious concerns about the quality and quantity of sequences that were used for their development [13]. As a result, these algorithms have problems to discriminate between peptides with similar composition but different activity, i.e., between AMPs and ACPs. Some do not also provide web servers, and, therefore, have limited utility for biologists not well acquainted with bioinformatics ([13] and citations therein).

Our goal was to create a robust three-class model, CancerGram, for differentiating ACPs from AMPs and sequences that are neither ACPs nor AMPs. CancerGram uses *n*-grams (continuous or discontinuous sequences of *n* elements) and random forests (a machine learning method) for the classification algorithm. *N*-grams represent short motifs that are relevant to anticancer, antimicrobial and non-anticancer/non-antimicrobial properties of peptides, and they allow us, in an easily interpretable way, to discriminate between the three classes of molecules. This methodology has already been used with success in our previous projects to develop software for predicting AMPs [28], amyloid proteins [29] and signal peptides [30], and to assess the optimal growth conditions for methanogens [31]. CancerGram addresses the above-mentioned shortcomings of other ACP classifiers using verified data sets from AntiCP 2.0, which is the top-ranking ACP predictor [13]. However, compared to AntiCP 2.0, the decision making process of CancerGram is performed at the same time

between three classes of sequences, i.e., ACPs, AMPs and non-ACPs/non-AMPs; therefore, it is convenient from the point of view of the user.

#### **2. Materials and Methods**

#### *2.1. Data Sets*

The data sets used to develop CancerGram were acquired from Agrawal et al. [13]. The training and validation data sets contained, respectively, 689 and 172 experimentally verified ACPs, 689 and 172 AMPs without anticancer activity and 776 and 194 non-ACP/non-AMP sequences (the negative data set). After the removal of peptides shorter than 5 amino acids, the data sets were used for CancerGram training and validation of its performance. The final numbers of sequences in each class are presented in Table 1. Since we could not repeat the benchmark analyses for AntiCP 2.0 [13], to compare its performance with CancerGram, we downloaded 2952 experimentally verified ACPs from CancerPPD [32], APD3 [33] and DRAMP [34] database and 4118 AMPs from dbAMP database [35]. We removed the most similar sequences using CD-HIT [36], assuming 0.95 and 0.60 identity threshold for ACPs and AMPs, respectively. Next, we removed sequences that were already contained in the training and validation data sets of CancerGram and AntiCP 2.0 [13]. As a result, we obtained an unbiased data set, termed independent, containing 57 ACPs and 769 AMPs (Table 1).

**Table 1.** Data set sizes used for training and validation of CancerGram.

#### *2.2. Cross-Validation*

We divided the ACP, AMP and non-ACP/non-AMP training data sets into five groups (folds), ensuring approximately the same sequence length distribution in each group for each data set. Next, we performed the fivefold cross-validation on both the mer and peptide layers of the model (for details, see Section 2.4 and Figure 1). The results of the cross-validation are presented in Table 2 and Figure 4.

#### *2.3. Extraction of Encoded N-Grams*

In order to create the three-class model, we divided each sequence from the training data sets into overlapping subsequences of 5 amino acids (5-mers); the length of 5 amino acids represents the shortest ACPs in our data sets. Consequently, we obtained 11,496 ACP, 15,826 AMP and 18,587 non-ACP/non-AMP 5-mers. From each 5-mer, we extracted *n*-grams, i.e., sequences of *n* elements. We analyzed continuous and discontinuous *n*-grams of size ranging from 1 to 3. In the case of discontinuous *n*-grams, bigrams (*n*-grams of size 2) could contain a gap of length from 1 to 3 (e.g., L\_N, C\_ \_G, K\_ \_ \_K), whereas in trigrams (*n*-grams of size 3), there is only a single gap between the first and the second and/or the second and the third amino acid (e.g., K\_L\_L, AK\_F, L\_SA). The gap corresponds to the presence of any amino acid. The *n*-gram presence was then counted and binarized for each 5-mer. The binarization of *n*-grams means that if an *n*-gram is present (at least once) in the 5-mer, it obtains the value of 1, and 0 if it is absent (Figure 1A).

**Figure 1.** Schematic representation of *n*-gram extraction (**A**) and decision-making procedure in CancerGram (**B**). The training data sets include ACP (shaded in red), AMP (shaded in yellow) and non-ACP/non-AMP sequences (the negative data set, shaded in blue). Each peptide from the training data sets was divided into subsequences of 5 amino acids (5-mers). For each 5-mer, we extracted continuous and discontinuous *n*-grams of size ranging from 1 to 3, and exemplary *n*-grams are presented in boxes shaded in colors respective to the data sets. The informative *n*-grams for CancerGram training were selected by Quick Permutation Test for all combinations of the data sets, and they are shaded in: (i) red-yellow for the ACP/AMP data set, (ii) red-blue for the ACP/Negative data set, and (iii) yellow-blue for the AMP/Negative data set (**A**). To make a prediction, CancerGram first divides a peptide into 5-mers and then, for each 5-mer, makes a prediction if it is an ACP, AMP or non-ACP/non-AMP (the first model). To scale the prediction from 5-mers to the level of a peptide, numerous statistics are calculated, and on their basis, CancerGram makes the final prediction (the second model) (**B**).

#### *2.4. Model Training with Random Forests*

To select the informative *n*-grams, we performed Quick Permutation Test (QuiPT) [37] on each combination of classes (ACP/AMP data set, ACP/Negative data set and AMP/Negative data set) with *p*-value threshold 0.0001. We obtained 1883 informative *n*-grams and used them for CancerGram

training. We trained the first random forest model on binarized occurrences of informative *n*-grams in 5-mers using the ranger R package [38]. The number of trees was set to 2000 and mtry parameter, i.e., the number of variables randomly sampled as candidates at each split, to the default value.

In order to scale the information found in 5-mers to the level of a peptide, we calculated numerous statistics for each peptide and for each class (Figure 1B) according to the methodology used in our previous projects [28]. These statistics were subsequently used to train the second random forest model predicting the class of a given peptide (ACP, AMP or non-ACP/non-AMP). In this case, both the mtry parameter and number of trees (500) were set to the default values. Consequently, the model is composed of stacked random forests [39], where the first one evaluates the probability of each 5-mer derived from a peptide as ACP, AMP or non-ACP/non-AMP, and the second considers statistical results for all mers from the given peptide and decides whether the whole peptide is ACP, AMP or non-ACP/non-AMP (Figure 1B).

#### **3. Results and Discussion**

#### *3.1. Composition and Properties of ACPs and AMPs*

The amino acid composition that characterizes both ACPs and AMPs (Figures 2 and 3) defines their properties, such as positive charge, hydrophobicity and amphipathicity, and they, in turn, determine their propensity for damaging bacterial and cancer cell membranes [40]. First, the positively charged molecules are driven electrostatically to the negatively charged membranes, and then their hydrophobicity and amphipathicity allows them to penetrate into the membrane and destabilize it in a detergent-like manner (carpet model) and/or by forming pores (barrel-stave or toroidal model) [9–12].

From the three above properties, only the positive charge differentiates the ACP group from AMPs because the upper limit of the positive charge is elevated for ACPs (Figure 2). This is the result of a high frequency of lysine (K), which is a predominant amino acid component of ACPs [13]. Interestingly, arginine (R), which is another basic amino acid, is slightly depleted in ACPs in comparison with AMPs and peptides from the negative data set (Figure 3). The decrease in arginine residues may, however, be beneficial for ACPs as its side chain, compared to lysine's, exhibits higher affinity for zwitterionic (neutral) membranes of healthy cells, and, therefore, is much more toxic [27].

Apart from its positive charge, lysine is also hydrophobic in nature and, as stated above, the hydrophobicity is another important property of both ACPs and AMPs. Peptides with higher hydrophobicity could be able to penetrate deeper into the hydrophobic core of the cell membrane, and, consequently, exhibit stronger propensity to permeabilize it [41]. ACPs are much richer in lysine (K), leucine (L), alanine (A) and phenylalanine (F) compared to AMPs and the peptides from the negative data set (Figure 3) [13]. In addition to its rather weak hydrophobic properties, alanine is also a good helix-forming residue; ACPs are known to form *α*-helical structures [40]. The last hydrophobic amino acid that deserves attention, tryptophan (W), is generally rare in proteins, but there seems to be more of it in ACPs compared to the other analyzed data sets though it is not statistically significant (Supplementary Tables S1–S3). Tryptophan serves an important role by helping peptides enter cancer cells via the endocytic pathway, thereby traversing the plasma membrane [42,43].

**Figure 2.** Distribution of the hydropathy index and net charge for anticancer peptides (ACPs), antimicrobial peptides (AMPs) and non-ACP/non-AMP sequences (Negative).

**Figure 3.** Amino acid composition of ACPs, AMPs and non-ACP/non-AMP sequences (Negative).

The other two amino acids that are abundant in ACPs, but not as much as in AMPs, are glycine (G) and cysteine (C) (Figure 3). The former is known to provide peptides with conformational flexibility and the latter to stabilize and maintain their proper motif and domain structure [43].

Although ACPs and AMPs are generally considered to be similar in terms of properties and the mode of action, the differences in their amino acid composition are significant enough (Supplementary Tables S1–S3) to find informative motifs that characterize them and non-ACPs/non-AMPs, thereby training an effective model for predicting ACPs.

#### *3.2. CancerGram Performance*

In order to evaluate the performance of CancerGram, we have chosen three measures: (i) accuracy, (ii) mean AUC (area under the ROC curve) for binary comparisons of each class against each other

(AU1U) and (iii) Kappa statistic (KapS) [44]. Accuracy is the simplest and the most common measure to evaluate the performance of a classifier. In the case of CancerGram, it simply provides the fraction of well-predicted ACPs, AMPs and non-ACPs/non-AMPs. A better measure is AU1U, the approximation of AUC for multi-class models. It informs the user of how much the model is able to distinguish between the three classes of peptides, i.e., ACPs, AMPs and non-ACPs/non-AMPs. A more general interpretation is that AU1U represents the probability that, e.g., a randomly selected ACP will be ranked higher in the ACP class than a random AMP or non-ACP/non-AMP. The values of both accuracy and AU1U range from 0 to 1, where 0.5 means a useless, i.e., a random classifier [45]. The last measure used to evaluate CancerGram is KapS, and it contains the information about how much better the model performs compared to the classifier that simply guesses at random according to the number of elements in each class. KapS evaluates the degree of agreement between CancerGram predictions and the true labels [46]. It takes values in [−1, 1], where 0 means a random classifier and values above 0.80 indicate an excellent one [47]. All measures were calculated using the measures R package [48]. The results of CancerGram validation are presented in Table 3 and the results of the fivefold cross-validation are presented in Table 2 and Figure 4.

**Figure 4.** Results of fivefold cross-validation for the peptide layer of the model. Each dot corresponds to a single fold.

CancerGram is a robust model with AU1U amounting to 0.89. The value of KapS 0.65 (0.64 for fivefold cross-validation) informs us that CancerGram is a good model [47]. The least informative measure for the three-class model is the accuracy because, among other things, it does not take into account the distribution of the misclassification among classes, and it is equal to 0.77 (0.76 for fivefold cross-validation). From the point of view of the researcher interested in screening for ACPs, the most important issue is the restrictiveness of the model in terms of false ACP predictions. Accordingly, CancerGram falsely identifies only 1.5% of the non-ACPs/non-AMPs as ACPs (3 out of 194 from the validation data set) and less than 16% AMPs (27 out of 170 from the validation data set).

**Table 3.** Results of predictions on the validation data sets.

CancerGram is not only an effective model for ACPs prediction but also the only three-class model available at present. The other ACP classifiers represent binary models, and they have problems with distinguishing between sequences with similar amino acid composition but different activity, i.e., ACPs and AMPs [13]. AntiCP 2.0 has overcome the problem; however, the greatest disadvantage of AntiCP 2.0 is that the biologist may become confused about which model they should use from the ones available on the AntiCP 2.0 web server. The first one is a binary model that differentiates between ACPs and AMPs, and the second between ACPs and non-ACPs [13].

In order to compare the CancerGram and AntiCP 2.0 [13] performance, we decided to test their predictive power towards classification of ACPs and AMPs, which is most challenging for ACP predictors [13]. Interestingly, we could not use the validation data set bacause the final version of AntiCP 2.0 [13] was possibly trained not only on the training but also the validation data set; we were not able to repeat their benchmark analyses. Therefore, we constructed an independent data set containing 57 ACP and 769 AMP sequences. Since CancerGram is a three-class model, we had to binarize its prediction, i.e., the prediction results for AMPs and non-ACPs/non-AMPs were summed and represent the AMP class. CancerGram outperformed AntiCP 2.0 [13] in terms of AUC, accuracy, specificity and the Matthews correlation coefficient (MCC) (Table 4). Sensitivity and specificity indicate the proportion of ACPs and AMPs that were correctly identified as ACPs and AMPs, respectively. Precision reflects the proportion of predicted ACPs that are truly ACPs, and MCC represents a reliable metric for binary classifiers, i.e., a balanced measure of correlation coefficient between predictions and true labels. We also compared the performance of CancerGram with mACPpred [49] because it has recently been published but not included in Agrawal et al. [13] as the benchmark on the validation data set. The mACPpred model, similarily to AntiCP 2.0 [13], is also not as robust as CancerGram and, moreover, compared to AntiCP 2.0 [13] and CancerGram, it tends to predict AMPs as ACPs, i.e., it generates numerous false positive results (low specificity) (Table 5).

**Table 4.** Comparison of CancerGram and AntiCP 2.0 [13] performance on the independent data set. AntiCP 2.0 predictions were obtained using model 1 of the standalone version with default values of threshold (0.5) and window length (10). CancerGram predictions were binarized. The low values of the Matthews correlation coefficient (MCC), precision and sensitivity are due to the large number of AMPs (769) and low number of ACPs (57) in the independent data set.

**Table 5.** Comparison of CancerGram and mACPpred [49] performance on the validation data set, from which sequences used for mACPpred training were removed. The final data set contained 128 ACPs and 170 AMPs. CancerGram predictions were binarized.

#### *3.3. Prediction of Mitochondria-Targeted ACPs with CancerGram*

We also wanted to check the predictive power of CancerGram toward ACPs that have been experimentally verified to target mitochondria of cancer cells. By searching the literature, we did find 12 ACPs that were not included in our training data sets (Table 6). The results of the analysis are presented in Table 7. As expected, CancerGram correctly identified most of them, i.e., eight sequences, although it identified GW-H1, lactoferricin B and pleuricidin NRC-03 as AMPs, and A9K as a non-ACP/non-AMP.

**Table 6.** Experimentally verified ACPs targeting mitochondria of cancer cells.

**Table 7.** Prediction results for experimentally verified ACPs targeting mitochondria of cancer cells.

#### **4. Conclusions**

Based on data sets from Agrawal et al. [13], we have compared ACPs, AMPs and non-ACP/ non-AMP sequences in terms of their amino acid composition. In the case of ACPs, the upper limit of the positive charge was elevated, mostly due to the high content of lysine, which is not only basic but also hydrophobic. The other residues that are overrepresented in ACPs, compared to AMPs and non-ACPs/non-AMPs, are all hydrophobic and include leucine, alanine, phenylalanine and tryptophan [13]. The positive charge, hydrophobicity and amphipathicity are responsible for AMP and ACP selectivity towards microbial membranes and, in the case of ACPs, also for targeting the cancer plasma and mitochondrial membranes. The latter are derived from *α*-proteobacteria and, due to their bacterial inheritance [22,23] and the potential generated during oxidative phosphorylation [18–20], should be preferred over the plasma membrane.

ACPs and AMPs are generally considered to be similar in terms of properties and the mode of action; however, we did find informative *n*-grams (amino acid motifs) that well differentiate them from each other and non-ACPs/non-AMPs, thereby allowing us to train an effective random forest model for ACP prediction. CancerGram is the only three-class model available at present and, moreover, it is better at discriminating between anticancer and antimicrobial peptides than other top-ranking predictors, including AntiCP 2.0 [13] and mACPpred [49]. The benchmark results also indicate that our methodology has an advantage over the methodology of Agrawal et al. [13] because, despite training our model on the same data sets, CancerGram outperformed AntiCP 2.0 on the independent data set. CancerGram is easy to use and does not require any other action other than pasting a sequence or sequences into the query box of the web server (see Appendix A). CancerGram does not predict

sequences shorter than 5 amino acids, and the user should remember that it was trained on sequences up to 50 amino acids in length, i.e., it was not designed for predicting anticancer proteins.

Since new anticancer agents are desperately needed, CancerGram can be used for ACP screening to identify the best candidates for further experimental procedures. Short cationic peptides represent good antitumor agents because they are small, relatively cheap to produce and easy to modify in order to further increase their anticancer properties and stability or to lower their toxicity to healthy cells [12,27].

**Supplementary Materials:** The following are available at http://www.mdpi.com/1999-4923/12/11/1045/s1, Table S1: Average amino acid percentages for ACPs and AMPs. The differences in amino acid composition between ACPs and AMPs were statistically evaluated using the Mann–Whitney U test with Benjamini–Hochberg correction. Table S2: Average amino acid percentages for ACPs and the negative data set. The differences in amino acid composition between ACPs and the negative data set were statistically evaluated using the Mann–Whitney U test with Benjamini–Hochberg correction. Table S3: Average amino acid percentages for AMPs and the negative data set. The differences in amino acid composition between AMPs and the negative data set were statistically evaluated using the Mann–Whitney U test with Benjamini–Hochberg correction.

**Author Contributions:** Author Contributions: Conceptualization, M.B. (Michał Burdukiewicz) and P.G.; formal analysis, M.B. (Michał Burdukiewicz), K.S. and P.G.; funding acquisition, M.B. (Michał Burdukiewicz), K.S., F.P. and P.G.; investigation, M.B. (Michał Burdukiewicz), K.S. and P.G.; methodology, M.B. (Michał Burdukiewicz), K.S., D.R., F.P., M.B. (Mateusz B ˛akała), J.S. and P.G.; project administration, M.B. (Michał Burdukiewicz) and P.G.; software, M.B. (Michał Burdukiewicz), K.S., D.R. and F.P.; supervision, M.B. (Michał Burdukiewicz) and P.G.; validation, F.P. and P.G.; visualization, K.S.; writing—original draft preparation, K.S. and P.G.; writing—review and editing, M.B. (Michał Burdukiewicz), K.S., F.P. and P.G. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was supported by National Science Centre grant 2017/26/D/NZ8/00444 to PG and MB, National Science Centre grant 2018/31/N/NZ2/01338 to KS and National Science Centre grant 2019/35/N/ NZ8/03366 to FP.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **Abbreviations**

The following abbreviations are used in this manuscript:

#### **Appendix A. Availability and Implementation**

The code necessary to reproduce the analysis presented in this paper is available in the repository: https://github.com/BioGenies/CancerGram-analysis.

The CancerGram prediction web server is available at: http://biongram.biotech.uni.wroc.pl/ CancerGram/.

#### **References**

64. Law, B.; Quinti, L.; Choi, Y.; Weissleder, R.; Tung, C.H. A mitochondrial targeted fusion peptide exhibits remarkable cytotoxicity. *Mol. Cancer Ther.* **2006**, *5*, 1944–1949. [CrossRef]

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**2. MR fluid damper analysis**

## **2.1. MR fluid damper**

386 Smart Actuation and Sensing Systems – Recent Advances and Future Challenges

moderate complexity and is widely applied in building controls. Once the characteristic parameters of the Bouc-Wen model are determined, the model can obtain the linearity and the smoothness of the transition from the pre-yield to the post-yield region. One of the major problems in the Bouc-Wen model is the accurate determination of its characteristic parameters which is obtained by using optimization or trial error techniques. Consequently, these techniques demand high computational cost to generate the model parameters. Moreover, the fact that each set of constant parameters is valid only for single vibration conditions makes the Bouc-Wen model inappropriate for varying excitation environments. Therefore, many researches on how to develop a MR fluid damper model for higher accuracy and higher adaptability in estimating the behavior of the damper have been done. Spencer *et al* [21] successfully developed a phenomenological model to improve the model accuracy with an additional internal dynamical variable. Choi and Lee [22] designed a hysteresis damper model based on a polynomial and a curve fitting to predict better the damping force when compared with conventional models. Dominguez *et al* [23] proposed a methodology to find out the characteristic parameter of Bouc-Wen model and then designed a new non-linear model to simulate the behavior of the MR fluid dampers. Kwok *et al* designed a hysteretic model based on a particle swarm optimization [24] or using GA technique [25] to modify the Bonc-Wen model and identify the characteristic parameters of the models. The effectiveness of these models with their identification process was proved through the experimental test data. However, the parametric modeling methods require assumptions regarding the structure of the mechanical model that simulates the system's behavior. These approaches could be divergent if the initial assumptions for the model structures are flawed or if the proper constraints are not applied to the parameters [24,25].

Unrealistic parameters such as negative mass or stiffness may be obtained [29].

high precision, the model architectures and the training methods were complex.

Once an accurate model for the MR fluid damper is built, it is very useful to investigate the damper characteristics before applying to suspensions. In addition, the well-done model can effectively function as a virtual sensor to estimate the damping force which is used for closed-loop damping control systems with a self-sensing behavior. Self-sensing describes the technique of using a transducer to both actuate and sense concurrently [30,31]. Compared to typical self-sensing damping control systems using separated or integrated actuators and sensors [32], this technique can offer several advantages. A reduction in the

On the contrary, non-parametric methods could avoid these drawbacks of the parametric approaches for modeling both the linear, nonlinear, and hysteretic systems with high adaptability. For modeling MR fluid dampers, some researches have been done. Chang and Roschke [26] proposed a non-parametric model using multilayer perceptron neural network with optimization method for a satisfactory representation of a damper behavior. Schurter and Roschke [27] investigated the modeling of MR fluid dampers with an adaptive neurofuzzy inference system. The fuzzy structure was simple for modeling; nevertheless, the training model process relied on input and output information on MR fluid dampers and took much computation time. Wang and Liao [28,29] explored the modeling of MR fluid dampers by using a trained direct identification based on recurrent neural network. Although, the designed models could predict the dynamic responses of the dampers with

> For later discussions on modeling and control of MR fluid dampers, a MR fluid damper of the small size damper series, RD-1005-3, manufactured by LORD Corporation was used. The damper RD-1005-3 can be adapted to a wide variety of applications because of its simple design, quiet operation, and compact shock absorption with low voltage and current demands that allow for damping control. Specifications of this damper are displayed in Table 1.

The purpose of this research is to investigate the characteristics of the damper RD-1005-3 which are then used to derive the accurate damper models as well as to design the forcesensorless controller for damping systems using this damper. Therefore, a test rig employing the damper RD-1005-3, named as TR01, is needed for following tasks:

The optimized BBM model as well as the proposed force-sensorless control system based on BBM and IBBM models might be applied not only on this system but also on other damping systems using the same dampers. Consequently, the ability of using these models for modeling and damping control needs to be verified. Therefore, a second damping system, which is named TR02, is indispensable for following purposes:

**Table 1.** Technical data for the MR fluid damper RD-1005-3

Based on the dimensions and characteristics of the damper RD-1005-3 as well as the design purposes, the two testing systems were designed and set up as described below.