**3. Face**

Malformations of the facial structures are often minor anomalies, therefore, they do not cause any functional impairment. However, they can suggest chromosomal abnormalities or other, more severe congenital anomalies (malformations of the heart or brain) so diagnosing these minor anomalies is important.

 The efficacy of prenatal ultrasound is low in case of these malformations and they are often left undiagnosed. As ultrasound techniques develop, the detection of anomalies such as cleft lip and palate (**Figure 4**) before birth is getting more accurate, reaching a sensitivity of 14–25% [19, 20]. 3D technique proved to be more effective in assessing the facial structures of the fetus [21].

**Figure 4.** Cleft lip. The detection of anomalies such as cleft lip and palate before birth is getting more accurate.

In our study, only 43 out of 135 face malformations were diagnosed prenatally (31.85%). We found that cleft lip and palate was detected with the highest sensitivity (53.33%), while no choanal atresia cases and only 9.09% of micrognathia cases were found.


*5.7. Weaning*

The transition to more varied, solid food is an important step in the development of the early-life gut microbiota; infants begin to be exposed to a much larger array of substrates and non-digestible carbohydrates that promote the survival and proliferation of more various bacterial taxa. As a consequence, the alpha diversity increases; moreover, *Proteobacteria* and *Actinobacteria* are replaced by *Firmicutes* and *Bacteroidetes* as the dominant phyla, in a more adult-like compositional structure. The cessation of exclusive milk feeding correlates with the decrease of saccharolytic bacteria as *Bifidobacteriaceae* (phylum: *Actinobacteria*). The increased protein intake is thought to be associated with an increase of *Lachnospiraceae* (phylum: *Firmicutes*), while the ingestion of fibers with that of higher levels of *Prevotellaceae* (phylum: *Bacteroidetes*) [39].

In general, the relative abundance of our intestinal microbes is highly influenced by dietary patterns and habits [11], that should therefore be taken into account in clinical studies targeting microbiota.

#### **6. Minor Factors A** ff**ecting Gut Microbiota**

Various minor factors can a ffect and modify the gut microbiota, which can occur at any stage of life. Insomnia and circadian rhythm disruption, latitude with time zone shift and intercontinental flights (with the consequent jet lag), household siblings, and companion animals as well as seasonal changes can modify gut microbiota and determine di fferent microbiota profiles with high inter-individual variability to responses to the di fferent factors [40–42]. All of these factors can influence the results and should be carefully considered before starting a clinical study and accurately reported in the metadata to then be considered later in the downstream bioinformatics and statistical analyses. Other similar confounder factors such as bowel movement preparations, evacuants or laxatives, or any microorganism-supplemented food (such as probiotics) can act as deep and long-time gut modifiers, thus a plot-to-plot variation needs to be addressed with nested statistical tests.

## **7. Sample Collection**

Donors/patients to enroll, their genetic or disease phenotypes as well as the expertise of the clinician in methodology used for collecting samples are very relevant in designing a correct study. The number of samples and patients to be enrolled is an intriguing and still hotly debated topic. Sample stability as well as shipping and storage requirements need to be more appropriate and will surely be improved and standardized in the future. Researchers may find some procedures at http://www.microbiome-standards.org or at https://www.hmpdacc.org/resources/metagenomics\_ sequencing\_analysis.php and other papers [43–45].

Concerning the practical aspects, an important question is how often to collect samples because the microbiome ecology is intrinsically dynamic. This largely depends on what question one is trying to answer. If, for gastrointestinal disorders, remarkable changes can be observed between one day and the next (e.g., in times surrounding surgery or in correspondence with periods of activity or remission of the pathology), changes induced by other factors (e.g., diet) often take place on a longer timescale. Collection of multiple samples from the same patient is preferred to allow for better standardization on the basis of the type of patients, centers involved, and statistical power. Whether or not samples collected from the same individual can be pooled before analysis is another topic to be standardized. An important point is that sampling and storage do a ffect microbiota composition in healthy as well as in diseased subjects. The most widely accepted protocols include immediate homogenization and freezing either with dry ice or in liquid nitrogen, followed by storage at −80 ◦C. However, this approach is not always practical, particularly for stool samples, or in the case of stool collection from a large scale cohort or remote/rural areas. Whether samples must be immediately frozen (and at what temperature) or whether they can withstand a period of room temperature remains controversial. The above-mentioned studies showed that the e ffects of short-term storage conditions on the structure and diversity of communities are quite small in general. In particular, storage at −80 ◦C, −20 ◦C for a week, or 4 ◦C for 24 h were found to not significantly a ffect the ecological indexes of between-sample diversity or the abundance of major taxa [45]. In contrast, the number of freeze–thaw cycles seems to have an e ffect on the composition of the microbial community, thus it is strongly recommended to aliquot samples at the beginning. Of course, some DNA stabilizers can be used to prolong the stability of samples. In the study of Choo et al. [46] Omnigene Gut and Tris EDTA appeared to show the same performance as storage in an ultrafreezer (−80 ◦C). In addition to feces, swabs can be an alternative starting material for DNA extractions, especially within hospital settings, even if some studies have shown that the stool swabs of some subjects had limited and not detectable bacterial DNA. A recent study by Christine M. Bassis [47], by comparing stool versus rectal swab samples and their storage

conditions, demonstrated minor di fferences in the bacterial community profiles between the stool and swab from the same subject as well as when samples were stored up to 27 h at +4 ◦C before freezing at −80 ◦C. Interestingly, this study also concluded that it was possible to thaw and refreeze samples a limited number of times under particular conditions (i.e., immediately frozen at −20 ◦C, first thaw cycle, refrozen at −80 ◦C; immediately frozen at −20 ◦C, first thaw cycle, refrozen at −20 ◦C, second thaw cycle and frozen at −80 ◦C) without strong e ffects on the community composition. A word of caution is, however, due on this point, as the consensus recommendations are di fferent, as detailed above. Finally, it is to be underlined that as the collection of stool can be di fficult from some subjects under certain experimental conditions, swab collection may be useful in such cases, which also has the advantage that they are more easily shipped and handled. A further recent study confirmed that swab samples reliably replicate the stool microbiota bacterial composition when swabs are processed quickly (≤2 days) [48].

Finally, special considerations are needed if addressing peculiar samples such as the newborn's first intestinal discharge (meconium). The debate about "when" the neonatal microbiota begins has been previously mentioned. Recently, several scientists have underlined that, even if it is possible that not all healthy babies are born sterile as previously thought, particular caution is due when working on samples bearing low microbial biomass such as meconia because of the contamination issues connaturated with molecular approaches based on PCR amplification and next-generation sequencing [17,49,50]. The presence of contaminating DNA in laboratory reagents (so-called "kitome") is a serious challenge in these cases; low levels of target bacterial DNA in a sample have been reported to correlate with a high proportion of sequences being attributable to contamination [51,52].


*2.8. Statistical Analysis*

Physicochemical analyses data were statistically analysed using the generalised linear model procedures of SAS software (Version 9.4; SAS Institute Inc., Cary, NC, USA) in a completely randomised block design with the fat type as the main effect. Observations over time were combined in a split-plot analysis of variance with production stage (raw batter and finished product) as a sub-plot factor. For DSA data, judges (n = 12) were considered as block replicates for each sample (backfat type × replicate). A Shapiro–Wilk test was performed on the standardised residuals from the model to test for normality. In cases where there was significant deviation from normality, outliers were removed when the standardised residual for an observation deviated with more than three standard deviations from the model value. The data for consumer acceptance were analysed using mixed model repeated measures of ANOVA. Fisher's least significant difference was calculated at the 5% significance level to compare treatment means.

**Table 1.** Sensory attributes description, scale and reference standards used for the descriptive sensory analysis of two cabanossi treatments.

a Low, moderate and high intensity were made using 1, 2 and 3 drops of liquid smoke solution in 100 mL water; b Roasted pork/mutton loin was roasted to an internal temperature of 75 ◦C and surrounding fat was used; c Fried bacon, pan fried bacon; d Wood sawdust solution, a cup-full (250 mL) of pine wood saw dust was soaked in water overnight and filtered; e Low, moderate, high intensity salt solution was made using 0.2%, 0.5% and 1% salt solution; f Dry cabanossi, a batch of cabanossi produced with no additional fat.

**Table 2.** Demographic variation of the sample population according to gender and age group.

\* Proportion expressed as a percentage of the total population size.

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


**7. Biological control of whitefly using natural enemies**

About 115 species of whitefly parasitoid belonging to 23 genera in five families (Aphelinidae, Azotidae, Signiphoridae, Encrytidae, and Platygastridae) have been reported [73]. The two most important genera of whitefly parasitoid are *Encarsia* and *Eretmocerus.* These two parasitoids significantly reduced the population of whitefly [74–76]. Apart from these two parasitoids, about 150 predators of whitefly have been reported from different parts of the world. Some of the important predators are ladybird beetles, predaceous bugs, lacewings, and spiders. It has also been reported that *Euseious scutalis* and *Typhlodromips swirskii* can significantly reduce the whitefly population on a single plant.


**Table 3.**

*Biocides used in cooling water [71].*

subject to strict regulations of use [10]. These rules are increasingly restrictive, so that the situation can be reached and that the concentration of allowed biocide is lower than the effective, which requires the search for other alternatives.

Biocides used in industrial refrigeration systems must have a broad spectrum, as they must limit the growth of a wide variety of microorganisms including bacteria, fungi, and algae. In addition, they must be effective in a wide range of specific conditions of equipment operation (**Table 2**).

There is a wide variety of chemical products that have been used as biocides to inhibit the formation of biofouling deposits in heat exchange systems that use seawater as a cooling fluid. According to their general principle of action, they are classified as oxidants or as non-oxidants.

They act by oxidizing the organic matter (cellular matter, enzymes, proteins, etc.) of the microorganism, and as a consequence they cause its death [68]. Its use is widespread, and its effectiveness as a widely demonstrated antifouling agent [69, 70].

In industrial refrigeration systems, different chemical compounds are employed that have the function of drastically reducing the number of cells present in the seawater-surface interface of heat exchange and minimizing their activity, having the capacity to limit the growth of a wide variety of microorganisms (bacteria and algae) and to be effective in a wide range of equipment operating conditions (**Table 3**).

#### **6. Biological treatments antifouling**

Biological antifouling biocides are active principles created by the agencies themselves (algae, batteries, fungi, etc.) as self-defense against other organisms in their natural environment. These substances are usually of a protein nature and are called enzymes.

Biological biocides are in the initial phase of research and development. Its use requires an in-depth analysis of the organisms that are intended to be eliminated and the environment in which they are found. The most recent research has shown the inhibition of marine biofouling by different types of bacteria, cyanobacteria, and marine fungi. Recent experiments have shown the antifouling properties of some organic compounds [72, 73], marine larvae of epibiotic bacteria [74–76], and various natural chemical compounds [77]. Dobretsov et al. [78] studied the microbial interference as a mechanism to control marine biofilms, focusing on the mechanisms of altering the biofilm by bacteria, algae, and various larvae.

#### **7. Physical antifouling treatments**

They represent an alternative to the use of biocides and an emerging research channel. They can be applied with the installation in operation (online systems) or with the installation in technical stop (offline systems) [5].

#### **7.1 Online systems**

#### *7.1.1 Taprogge system*

Mechanical cleaning system by sponge balls or elastomer material abrasives is a biofouling treatment which periodically introduce balls by the water flow to clean tubes in heat exchangers. The balls of suitable roughness are introduced into the water box of the condenser from where they pass into the tubes. Balls have a diameter greater than that of the tube which pass through tubes to clean inner surface avoiding the settlement of organic or inorganic matter.

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*Fouling in Heat Exchangers*

*7.1.3 Heat treatment*

repetition [40].

to 3 ms−1

compact.

*DOI: http://dx.doi.org/10.5772/intechopen.88079*

*7.1.2 Cleaning brush system housed in baskets*

*7.1.4 Variation in cooling water flow rate*

pumping capacity of the system can be increased.

nitrogen) at very high speed (3 ms−1

*7.1.5 Streams current antifouling*

lengthening its useful life.

*7.1.6 Ultraviolet radiation*

the cooling water flow is minimized.

At the ends of the tubes, there are baskets containing a brush that moves in both directions through the interior of the tube by reversing the flow of the cooling water. The investment of flow is made with a valve system that enables this action, not being necessary more than three daily cycles to maintain good conditions of the plant.

It consists of heating the cooling water by recirculating it in a closed circuit without renewing cold water or by installing a secondary hot water supply circuit from an internal combustion engine, for example. The water recirculates until reaching temperatures between 50 and 70°C, which produces the death of microorganisms [5]. The periodicity of this treatment is established taking into account the biological activity of the water. Its effectiveness depends mainly on the temperature of the water, the time of exposure, and the frequency of

The speed of water flow through the tubes of the exchanger is a determining factor in the growth of biofouling. In addition to influencing the contribution of nutrients that determine the growth of organic matter that is part of the biofouling film, deposits adhered to the inner surface of the tubes can be detached as a result of the greater cutting effect on the surface are exerted to higher water flow rates. The heat exchanger can be designed to work at high flow rates (from 1 to 2 ms−1

or so that the water flow rate can be varied for a short period of time (e.g., from 1

Pulsed injections can also be made by introducing a gas (compressed air or

and 60 minutes). The effect is to increase the turbulent regime, creating pressure fluctuations inside the tube and higher shear stresses on the surface. As a consequence, a greater detachment of biofouling is obtained than that obtained by simply increasing the speed of water flow [5]. However, according to Mussalli and Tsou [79], the effectiveness of this system decreases as the biofouling film becomes more

The principle of operation of this system is based on the generation of a voltage between the copper anodes (Cu) and the integrated steel cathodic plates so that when the Cu dissolves, the medium is contaminated by repelling the marine organisms. The level of Cu dissolution is regulated by a control unit adapting the system to the factors that influence biofouling growth (e.g., the season of the year) and

The sterilization of water by ultraviolet radiation (UV) is a potentially useful method to avoid the formation of the biofouling film and as a cleaning technique. Its principle of operation is based on attacking the deoxyribonucleic acid (DNA) of the cells, causing their death. In this way, the amount of microorganisms present in

) at regular intervals. This increase in flow velocity is only possible if the

) periodically at short intervals of time (5, 10,

)


*4.5. Additional Analysis*

To check the performance difference between different types of family firms, we did further analysis following the Saito (2008) approach. Accordingly, we separated the family firms into two groups: family firms run by founders and founding family members. The results are shown in Table 9.  This result is in line with the findings of Saito (2008). However, we found that family ownership reduces the performance of founder run family firms as far as the ROA is concerned, but Tobin's Q does not evidence the same. By contrast, family ownership significantly improves the performance of family firms run by the founder's descendants when Tobin's

Q is taken into account. However, such evidence is not pronounced with ROA. Similarly, factors such as institutional ownership and government shareholding encourage the performance of both types of family firms (founders and founders' descendants).

**Table 8.** Random effect regression results in controlling for time and industry effects.

Note: \*\* meaning *p*-value is less than 0.01; \* meaning *p*-value is less than 0.05.

**Table 9.** Regression results for family firms run by founder and founding family members (fixed-effect model).

Note: \*\* meaning *p*-value is less than 0.01; \* meaning *p*-value is less than 0.05.

However, as opposed to the firms run by founders' family members, foreign ownership is not found to be a significant factor for firms run by founders. This means that firms run by founders' descendants can utilize foreign shareholdings to boost firm performance following Japan's recent financial policy that encourages foreign ownership. Besides, we found that factors such as board independence and board meetings appear to be the significant factors for inhibiting the performance of firms run by founders' descendants. In contrast, such evidence is not pronounced for family firms run by founders. Moreover, we did not find any significant performance differences between these two types of family firms for the remaining cases.

 Furthermore, foreign ownership encourages the performance of firms run by the founders' descendants. However, we note that further studies incorporating management strategies are required to reveal the performance difference between these two groups of family firms. Moreover, more studies with longer time and multiple angles are warranted to generalize our findings.


**3. Factors influencing the diagnosis**

The diagnostic process is considered to be a complex transition process which begins with the illness of the patient and ends into a result which serves as a data for reference that can be categorized. The diagnoses start from the doctor asking the patient about signs and symptoms of a disease/illness. A doctor's treatment specific to a patient's symptoms and its outcome is important for both the doctor and the patient to see the efficacy of the treatment provided.

The diagnoses are an amalgamation of various processes that broadly depends on three main factors:

### **3.1 Doctor's knowledge**

*"The eye sees all, but the mind shows us what we want to see." -Shakespeare.*

The doctor's knowledge serves as data set for the human brain to process the likes and similarities from the previous acquired data. This helps in differentiating the two processes. And thus helps to form an opinion regarding a process. This is really critical for diagnosis.

For example, while diagnosing a Central Giant Cell Granuloma of the jaw, the doctor must also be aware of the differential diagnoses, and their appearance to rule those out.

#### **3.2 Doctor's experience**

The experience of a doctor plays an important role in the diagnosis of a disease. These experiences contribute in enriching the quality of the data and help in refining the data set and recreating subsets in the data. It is here that heuristics step into the picture. These subsets help in simplifying the data and make it comprehensible. The experiences can also be governed by the amount of different cases seen by the doctor, which in turn is greatly influenced by the geo-fencing of the same.

For example, the diseases that are predominant in some areas of the world, like Lyme's disease in the North Eastern American region, the physicians practicing there will have more experience of those cases and will form a more accurate diagnosis in comparison to the physicians in any other part of the world. Basically the age old dictum at work here is that—if you hear hooves think horses, not zebras.

**79**

superior algorithms [3].

*Computer Simulation and the Practice of Oral Medicine and Radiology*

Human brain is a complex structure which plays a pivotal role in making a diagnosis. According to Charles Sherigton (c. 1920), some of the deepest mysteries facing science in the twenty-first century concern the higher functions of the central nervous system: perception, memory, attention, learning, language, emotion, personality, social interaction, decision-making, motor control, and consciousness. Nearly all psychiatric and many neurological disorders are characterized by a dysfunction in the neural systems that mediate these neural processes. In fact, all aspects of human behavior and hence human society are controlled by the human brain: economics and decision making, moral reasoning and law, arts and esthetics, social and global conflict, politics and political decision making, marketing and preference, etc. These functions are greatly altered by the level of stress and the mood that the person has. Thus, a diagnosis is also greatly influenced by the doctor's

**4. Computer simulation: understanding AI (artificial intelligence) in**

AI and how to use it in CAD has become one of the hottest research topics in medical radiology both in imaging and diagnostics. Although, research in CAD is pretty much established and growing but most radiologists do not as yet, use CAD in their daily routine. The basics of AI and how to use it in CAD for detection and for quantification is defined by the various requirements such as performance, regulatory compliance, reading time reduction and cost efficiency are even today not as sophisticated/dependable as the human mind. Overall the performance of the CAD systems is still a major bottleneck for adaption. However, the usual machine learning and AI strategy can be used to improve CAD by using past and public databases for training and validation. This will create cognitive AI that will help tackle corner cases in CAD and eventually create

Yet all said and done, there is a global consensus that the advent of computer simulation is a crisis in the making for radiology. Not only has the number of imaging studies gone up, but also the number of images per study has drastically increased [4]. Radiology is becoming a victim of its own success, i.e., the disparity and the gap between the overall workload and the number of radiologists has increased dramatically which has resulted in a cost increase. Therefore, new

*DOI: http://dx.doi.org/10.5772/intechopen.90082*

**3.3 Influencing factors**

*Diagnostic paradigm.*

**Figure 1.**

state of mind, and stress level (**Figure 1**).

**computer-aided diagnosis (CAD)**

*Computer Simulation and the Practice of Oral Medicine and Radiology DOI: http://dx.doi.org/10.5772/intechopen.90082*

**Figure 1.** *Diagnostic paradigm.*

*Numerical Modeling and Computer Simulation*

in the diagnostic process, is an impending reality [1].

patient to see the efficacy of the treatment provided.

*"The eye sees all, but the mind shows us what we want to see." -Shakespeare.*

**3. Factors influencing the diagnosis**

on three main factors:

**3.1 Doctor's knowledge**

really critical for diagnosis.

**3.2 Doctor's experience**

those out.

"therapeutic intervention" and the response is studied to show characteristics of a particular disease [2]. For example, the dentist might prescribe antibiotic for 1 week to a patient with decayed tooth and tooth pain. The antibiotic resolves the infection and pain which shows that the patient had secondary infection going on in the carious tooth. The ultimate feature in the diagnosis of disease is to see if the planned therapy is working or if the disease is getting better or getting worse over a period of time, and have there been considerable side effects to the therapy [2]. Evaluation of the diagnoses is not only limited to living individuals. Post-mortem and autopsy examinations have proved to be a great tool in designing the diagnostic parameters. Artificial intelligence and computer learning have cashed upon the complex series of diagnosis in these days to assist humans in coming up with a module for diagnostic processes. In the current scenario, the possibility that artificial intelligence (abbreviated henceforth as AI) and computer aided systems may supersede humans

The diagnostic process is considered to be a complex transition process which begins with the illness of the patient and ends into a result which serves as a data for reference that can be categorized. The diagnoses start from the doctor asking the patient about signs and symptoms of a disease/illness. A doctor's treatment specific to a patient's symptoms and its outcome is important for both the doctor and the

The diagnoses are an amalgamation of various processes that broadly depends

The doctor's knowledge serves as data set for the human brain to process the likes and similarities from the previous acquired data. This helps in differentiating the two processes. And thus helps to form an opinion regarding a process. This is

For example, while diagnosing a Central Giant Cell Granuloma of the jaw, the doctor must also be aware of the differential diagnoses, and their appearance to rule

The experience of a doctor plays an important role in the diagnosis of a disease. These experiences contribute in enriching the quality of the data and help in refining the data set and recreating subsets in the data. It is here that heuristics step into the picture. These subsets help in simplifying the data and make it comprehensible. The experiences can also be governed by the amount of different cases seen by the

doctor, which in turn is greatly influenced by the geo-fencing of the same.

For example, the diseases that are predominant in some areas of the world, like Lyme's disease in the North Eastern American region, the physicians practicing there will have more experience of those cases and will form a more accurate diagnosis in comparison to the physicians in any other part of the world. Basically the age old dictum at work here is that—if you hear hooves think horses, not zebras.

**78**

### **3.3 Influencing factors**

Human brain is a complex structure which plays a pivotal role in making a diagnosis. According to Charles Sherigton (c. 1920), some of the deepest mysteries facing science in the twenty-first century concern the higher functions of the central nervous system: perception, memory, attention, learning, language, emotion, personality, social interaction, decision-making, motor control, and consciousness. Nearly all psychiatric and many neurological disorders are characterized by a dysfunction in the neural systems that mediate these neural processes. In fact, all aspects of human behavior and hence human society are controlled by the human brain: economics and decision making, moral reasoning and law, arts and esthetics, social and global conflict, politics and political decision making, marketing and preference, etc. These functions are greatly altered by the level of stress and the mood that the person has. Thus, a diagnosis is also greatly influenced by the doctor's state of mind, and stress level (**Figure 1**).


To identify the influence of the identified variants on PTK7 protein function, we evaluated overall protein expression and sub-cellular location of the variants of PTK7 compared to the WT. Western blotting analysis identified the immunoreactive-specific band for flag-tagged WT PTK7 at 150kDa and β-actin at 42kDa. The overall expression level was quantified by estimating bands from PNGase-treated samples and normalizing to WT. As anticipated, the overall expression of the frameshift variant (c.464\_465delAC, p.H155Pfs\*16) was significantly decreased compared to that of WT (*p* < 0.0001) (Figure 3A), indicating the loss-of-function effect of this variant. The expression level of two missense variants (p.S118F and p.D764N) were partially reduced (*p* = 0.0061 and *p* = 0.0293, respectively) (Figure 3A). Interestingly, these two variants were both identified in patients with AIS but not CS. There were no significant differences in the overall protein expression of the other missense variants (p.K465R, p.G627R, p.R562L, p.L17F, p.R795H) compared with the WT.

We also performed immunocytochemistry (ICC) assays and found there was a faintest signal from the frameshift variant of the PTK7 protein (Figure 3B), which supported the results of Western blotting assays. However, the sub-cellular location of all missense variant PTK7 protein did not change compared to WT (Figure 3B). *Cells* **2021**, *10*, x FOR PEER REVIEW 10 of 13

**Figure 3.** Western blot and ICC analyses. (**A**) HEK293T cells transiently transfected with WT or variant *PTK7* constructs revealed diminished PTK7 protein expression levels of p.H155Pfs\*16, p.S118F and p.D764N. \* *p* value < 0.05, \*\* *p* value < 0.01, \*\*\*\* *p* value < 0.0001. (**B**) ICC assays showed a faint signal of the frameshift variant PTK7 protein. No difference in PTK7 protein sub-cellular location was detected. **Figure 3.** Western blot and ICC analyses. (**A**) HEK293T cells transiently transfected with WT or variant *PTK7* constructs revealed diminished PTK7 protein expression levels of p.H155Pfs\*16, p.S118F and p.D764N. \* *p* value < 0.05, \*\* *p* value < 0.01, \*\*\*\* *p* value < 0.0001. (**B**) ICC assays showed a faint signal of the frameshift variant PTK7 protein. No difference in PTK7 protein sub-cellular location was detected.

Here, we performed WES on the genomes of 885 scoliosis patients, including 583 CS patients and 302 AIS patients, and identified seven missense variants and one frameshift variant in *PTK7*. Loss-of-function of PTK7 resulted in skeletal phenotypes in both zebrafish and mice. In zebrafish models, embryos with the *PTK7hsc9* variant (a mutant allele harboring a 10bp deletion that results in a frameshift and the incorporation of multiple

and axial mesoderm tissues, and abnormal three-dimensional spinal curvature with growth and development [2]. In 2016, Grimes et al. reported that mutated *ptk7* zebrafish exhibited spinal curvature as well as hydrocephalus, ependymal cell (EC) ciliary dysfunction and abnormal rate and pattern of the cerebrospinal fluid (CSF) flow [20]. The *chuzhoi* mutant mice embryo showed several congenital abnormalities including neural tube, heart and lung defects caused by the disruption of PTK7 protein expression [21]. In human, LoF mutations in *PTK7* and the double-heterozygous mutation of *PTK7* and *VANGL2* were associated with spina bifida and increased the genetic risk of NTDs [19]. However, only one case of scoliosis with a *PTK7* mutation has been previously reported [11], and our identification of these eight variants expands the variant and phenotypic

The PTK7 protein consists of an extracellular continuous immunoglobulin domain, a transmembrane domain and an intracellular PK domain [1]. PTK7 interacts with several molecules in both canonical and non-canonical Wnt signaling as a co-receptor. These molecules include Wnt ligands, Wnt receptors as well as intracellular components such as Dvls and β-catenin [22]. According previous studies, the extracellular domains and intracellular domains of PTK7 play distinct roles. By constructing and studying *PTK7* with

**4. Discussion**

spectrum of *PTK7*.

### **4. Discussion**

Here, we performed WES on the genomes of 885 scoliosis patients, including 583 CS patients and 302 AIS patients, and identified seven missense variants and one frameshift variant in *PTK7*. Loss-of-function of PTK7 resulted in skeletal phenotypes in both zebrafish and mice. In zebrafish models, embryos with the *PTK7hsc9* variant (a mutant allele harboring a 10bp deletion that results in a frameshift and the incorporation of multiple premature termination codons) had defects in the convergence of both neuroectoderm and axial mesoderm tissues, and abnormal three-dimensional spinal curvature with growth and development [2]. In 2016, Grimes et al. reported that mutated *ptk7* zebrafish exhibited spinal curvature as well as hydrocephalus, ependymal cell (EC) ciliary dysfunction and abnormal rate and pattern of the cerebrospinal fluid (CSF) flow [20]. The *chuzhoi* mutant mice embryo showed several congenital abnormalities including neural tube, heart and lung defects caused by the disruption of PTK7 protein expression [21]. In human, LoF mutations in *PTK7* and the double-heterozygous mutation of *PTK7* and *VANGL2* were associated with spina bifida and increased the genetic risk of NTDs [19]. However, only one case of scoliosis with a *PTK7* mutation has been previously reported [11], and our identification of these eight variants expands the variant and phenotypic spectrum of *PTK7*.

The PTK7 protein consists of an extracellular continuous immunoglobulin domain, a transmembrane domain and an intracellular PK domain [1]. PTK7 interacts with several molecules in both canonical and non-canonical Wnt signaling as a co-receptor. These molecules include Wnt ligands, Wnt receptors as well as intracellular components such as Dvls and β-catenin [22]. According previous studies, the extracellular domains and intracellular domains of PTK7 play distinct roles. By constructing and studying *PTK7* with deletion of different domains, Hayes et al. found that the plasma membrane-tethered *Ptk7* extracellular domain (*Ptk7*∆ICD) was sufficient to promote normal PCP as well as the inhibition of canonical Wnt signaling [2], while the intracellular domains may play a specific role in oriented cell division, radial intercalation and cilia orientation [23–26]. The intracellular PK domain of PTK7 may act as a scaffold promoting the binding of intracellular proteins and other receptors. In *Xenopus*, the ptk7 intracellular domain was stimulated by Wnt5A and induced its translocation into the nucleus, which promoted cell and tissue movements [27]. Additionally, the C-terminal PTK7 species up-regulated cadherin-11 expressed in the mesoderm-derived tissues, and which regulates osteogenesis. It is possible that PTK7 and Cadherin-11 might interact in embryogenesis and regulate similar developmental processes [28,29]. In our study, the frameshift variant and three missense variants (p.L17F, p.S118F, and p.K465R) were located in the extracellular domains of the PTK7 protein, while the other four missense variants (p.G627R, p.R652L, p.D764N, and p.R795H) were mapped to the intracellular portion, with p.D764N and p.R795H variants being located in the pseudokinase domain. In our expression assay, one variant in the extracellular domain and one variant in the intracellular domain were shown to alter the expression of *PTK7*, suggesting that both domains are critical for the integrity of PTK7 protein.

Interestingly, the frameshift variant that caused almost no expression of PTK7 was found in the CS patient, while the two missense variants that resulted in the significant decreases in protein levels were both found in patients with AIS. The patient carrying the truncating variant was diagnosed to have a mixed subtype of CS, with failure of formation (T12 butterfly vertebra) and segmental disorder (T9-T10) and no other developmental malformations. The two patients with the missense variants (p.S118F and p.D764N) did not have congenital developmental deformities of the vertebral body or other systems, presenting simple thoracolumbar scoliosis. However, due to the complex etiology of AIS, the role of PTK7 in AIS still warrants further validation and investigation.

Taken together, we hypothesize that the pathogenesis of vertebral deformities and the onset time of spinal curvature may be due to the effect of *PTK7* variants on the protein expression. In other words, congenital and adolescent idiopathic scoliosis may have a common genetic basis. Although some missense variants in our study did not show

abnormalities in protein expression or sub-cellular location, it is possible that the altered amino acids can affect the structure of the protein and subsequently affect downstream signaling pathways. Therefore, it is necessary to further explore the possible downstream pathways of PTK7, such as the canonical and non-canonical Wnt pathways.

### **5. Conclusions**

In conclusion, we identified eight *PTK7* variants in our mixed scoliosis cohort, including one frameshift variant (c.464\_465delAC) and seven missense variants (c.49C>T, c.353C>T, c.1394A>G, c.1879G>A, c. 1955G>T, c.2290G>A, c.2384G>A). The frameshift variant resulted in a depleted expression of PTK7 protein, and two of missense variants caused reduced expression of PTK7. Our study extended the variant and phenotype spectrums of *PTK7* and suggested a common genetic basis of CS and AIS.

**Author Contributions:** Conceptualization, Z.S., N.W. and S.Z.; methodology, Z.S., S.Z. and H.Z.; software, S.Z. and Y.N.; validation, Z.S., S.W., S.Z. and X.L.; formal analysis, Z.S. and Y.Y.; investigation, Z.S.; resources, S.W., Y.Y. and Deciphering Disorders Involving Scoliosis and COmorbidities (DISCO) Study Group; data curation, Z.S., S.Z. and H.Z.; writing—original draft preparation, Z.S., Y.Y.; writing—review and editing, S.W., S.Z., X.L. and N.W.; visualization, Z.S.; supervision, N.W., Z.W., G.Q. and T.J.Z.; project administration, N.W., Z.W., G.Q. and T.J.Z.; funding acquisition, N.W., Z.W., G.Q. and T.J.Z. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded in part by the National Natural Science Foundation of China (81902178 to S.W., 81972037 and 82172382 to J.Z., 81822030 and 82072391 to N.W., 81930068 and 81772299 to Z.W., 81772301 and 81972132 to G.Q.), Beijing Natural Science Foundation (No. L192015 to J.Z., JQ20032 to N.W., 7191007 to Z.W.), Capital's Funds for Health Improvement and Research (2020- 4-40114 to N.W.), Tsinghua University-Peking Union Medical College Hospital Initiative Scientific Research Program, Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences (No. 2019PT320025), and the PUMC Youth Fund & the Fundamental Research Funds for the Central Universities (No.<PHONE_NUMBER> to Shengru W.).

**Institutional Review Board Statement:** Approval for the study was obtained from the ethics committee at Peking Union Medical College Hospital (JS-098).

**Informed Consent Statement:** Written informed consent was provided by each participant.

**Data Availability Statement:** Data are available upon reasonable request. The datasets analyzed during the current study are available from the corresponding author on reasonable request.

**Acknowledgments:** We thank the patients and their families who participated in this research. We also thank the Nanjing Geneseq Technology Inc. for the technical help in sequencing, the Ekitech Technology Inc. for the technical support in database and data management. The members of the DISCO study group are provided in http://discostudy.org/.

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

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**About the Editors**

**Nikolaos Koukouzas** holds a BSc degree in Geology with MSc and PhD degrees in Industrial Mineralogy from the University of Leicester, UK. He received his bachelor's degree in Geology from the National University of Athens in 1987. He continued his postgraduate studies in the UK, receiving a 4-year grant from the State Scholar-ship Foundation of Greece, and completed his PhD in 1995. Dr. Koukouzas is Director of Research at the Centre for Research and Technology Hellas (CERTH) and Director of the Laboratory of the Solid Fuels at CERTH, supervising a team of scientists with offices in Athens, Thessaloniki, and Ptolemais, Greece. He is Member of the Executive Committee of the Monitoring and Assessment Exercise of the Research Fund for Coal and Steel, National Delegate in the Government Group of Zero Emission Power Plant Technology Platform (ETP-ZEP), and National Delegate in the Policy and Technical Group of the Carbon Sequestration Leadership Forum (CSL) coordinated by the US DoE. His research expertise is focused on coal geology, industrial mineralogy, coal geochemistry, fossil fuel characterization, coal combustion by-products, coal slope stability, waste and mine water treatment, and CO2 storage and monitoring. Dr. Koukouzas has been Project Manager and had scientific responsibility of several re-search projects with over 25 years' experience on energy and environment issues. He has 250 publica-tions, 1650 citations, and an h-index of 21.

**Pavlos Tyrologou** is a research fellow at CERTH, holds a BSc (4 years Hons) degree in Geology and Applied (engineering) Geology from Glasgow University, an MSc in Applied Environmental Geology from Cardiff University, and a PhD in Environmental Geotechnical Engineering from Imperial College London, fully supported by a scholarship award from The Institute of Materials, Minerals and Mining, UK. He is professionally accredited in the UK both as a Chartered Geologist and Eurogeologist in the field of Engineering Geolo-gy. Pavlos has 15 years of consultancy experience in various public infrastructure design/works in Greece, United Kingdom, Madagascar, and Sint Maarten. He is an expert witness for both the Athens Public Prosecutor's Office and Athens Court of Justice. He has evaluated more than 65 research and business projects as an independent evaluator for both the European Commission and Greek Govern-ment. Due to his expertise, Pavlos serves as Coordinator in the European Federation of Geologists (EFG) on the panel Natural Hazard and Climate Change and is member of the panels of experts on soil pro-tection. On the same note, he is the Greek representative within the EFG council through the Associa-tion of Greek Geologists. He is a member of the Greek Society for Soil Mechanics and Geotechnical En-gineering, Geological Society of London, International Society for Rock Mechanics, and Member of In-ternational Society for Soil Mechanics and Geotechnical Engineering, at which he serves on the tech-nical committee of the Engineering Practice of Risk Assessment and Management. He also has exten-sive research experience in several European H2020 projects, including proposal writing, inception, and execution (CHPM30, UNEXMIN, SLOPES, KINDRA, INTRAW, COALTECH2051, StrategyCCUS, LEILAC2, RECPP) of various tasks such as project management and research activities. His current re-search interests are focused on climate change and related activities and how these are related to securi-ty issues such as state fragility and vulnerability.

**Petros Koutsovitis** is Assistant Professor at the University of Patras, Department of Geology. He holds a PhD in the fields of Mineralogy, Petrology and Geochemistry from the University of Athens, Greece. Dr. Koutsovitis has been a Post-doctoral researcher at the University of Vienna (under an FWF-funded project) and was later employed at the Greek Institute of Geology and Mineral Exploration, within the frame of ESTMAP (Horizon 2020) and YPOTHER (NSRF-funded) projects. He continued his research activities at the Centre for Research & Technology (CERTH), participating in EU-funded Horizon2020 and RFCS project's (STRATEGY-CCUS, COAL2GAS & COALBYPRO), as well as at the University of Athens as an Academic Educational Fellow. Dr. Koutsovitis has also participated in the INTRAW Horizon 2020 programme, in cooperation with the European Federation of Geologists (EFG). He has published several papers in peer reviewed Journals and has been awarded by the Academy of Athens for his research.