**4. Rodent LRRK2 models**

While invertebrate LRRK2 models have been and will continue to be highly informative, it is important to remember that the LRRK genes are not true orthologues of LRRK2 (Marin, 2008). In addition, physiological limitations include not only the lack of basal ganglia but also their short lifespan, leaving the effects of aging impossible to determine. Given that age is the biggest risk factor for development of LRRK2 parkinsonism, the development of mammalian LRRK2 models is key for understanding pathophysiology and for drug screening.

To date a number of rodent models have been published in the literature, with experimental approaches Including knock-out of LRRK2, over-expression of human wild-type and

Studies have been performed utilizing double transgenic hLRRK2 flies concomitantly expressing human PINK1, DJ-1 or Parkin. These fly models exhibited various eye abnormalities and some had decreased DA neuron survival (Venderova et al., 2009) whereas coexpression of Parkin with mutant LRRK2 provided significant protection against DA neuron degeneration that occurs with age or in response to rotenone (Ng et al., 2009) Also, loss-of-function dLRRK suppressed Parkin and PINK1 pathology in flies (Tain et al., 2009). Thus, this data further supports the observations that wild-type *d*LRRK negatively regulates DA neuron survival and provides evidence that there is some sort of relationship between

*Drosophila* models have been utilized for the search and characterization of LRRK2 substrates and/or interacting proteins (Imai et al., 2008; Lee et al., 2010b; Tain et al., 2009; Venderova et al., 2009). Imai and colleagues showed that both *Drosophila* and human LRRK2 phosphorylate 4E-BP (a negative regulator of translation and mediator of stress response), and that pathogenic mutations caused hyper-phosphorylation of 4E-BP, which led to reduced resistance to oxidative stress and increased dopaminergic neurodegeneration in flies (Imai et al., 2008). Likewise, loss-of-function e03680 flies had a decrease in the amount of phosphorylated 4E-BP (Tain et al., 2009). This association was confirmed in a study that not only showed that LRRK2 interacted with 4E-BP at the postsynaptic compartment, but also found that hLRRK2 phosphorylated Futsch (MAP1b homolog) and possibly interacted with Tubulin (Lee et al., 2010b). Another study found that dLRRK/hLRRK2 phosphorylated FoxO (a transcription factor involved in cell metabolism and oxidative stress which regulates 4E-BP), which subsequently activated downstream cell death regulators and resulted in neurodegeneration (such as eye defects and DA neuron loss) in dFoxO overexpressing flies (Kanao et al., 2010). However, it has been found that LRRK2 phosphorylates itself and other substrates more strongly than 4E-BP in mammals (Kumar et al., 2010), so the negative effects may be *Drosophila* specific. Another study recently reported that dLRRK/hLRRK2 targeted microRNA pathways and that pathogenic LRRK2 antagonized these miRNAs, which negatively affected cell cycle and DA neuron survival (Gehrke et al., 2010). Additionally, the group found that LRRK2 associated with and negatively regulated Argonaute (dAgo1/hAgo2) RISC proteins and LRRK2 mutants promoted the association of phospho-4E-BP1 with hAgo2. Thus, it appears that WT LRRK2 can regulate protein expression by targeting microRNA silencing pathways, and mutations

While invertebrate LRRK2 models have been and will continue to be highly informative, it is important to remember that the LRRK genes are not true orthologues of LRRK2 (Marin, 2008). In addition, physiological limitations include not only the lack of basal ganglia but also their short lifespan, leaving the effects of aging impossible to determine. Given that age is the biggest risk factor for development of LRRK2 parkinsonism, the development of mammalian LRRK2 models is key for understanding pathophysiology and for drug

To date a number of rodent models have been published in the literature, with experimental approaches Including knock-out of LRRK2, over-expression of human wild-type and

**3.2.3 Fly interactor studies**

LRRK2 and these other PD-associated genes.

in LRRK2 can upset a delicate balance.

**4. Rodent LRRK2 models**

screening.

mutant LRRK2, over-expression of mouse wild-type and mutant LRRK2 and targeted knock-in of human mutations into the murine genome.

#### **4.1 Murine LRRK2 knockouts**

Several groups have reported LRRK2 knockout mice in varying detail. In 2009, Andreas-Mateo et al reported that mice with partial knockout of exon 39 and complete knockout of exon 40 are viable, grossly normal and have completely intact dopaminergic system in terms of dopamine levels and neuronal number up to 2 years of age and show no altered sensitivity to 1-methyl-4 phenyl-1,2,3,6-tetrahydropyridine (MPTP) (Andres-Mateos et al., 2009). Around the same time Lin et al also reported that no pathological or behavioral abnormalities were observed in their knockout mice that lack LRRK2 exon 2 (Lin et al., 2010). Interestingly, when they crossed the LRRK2 knockout to conditional A53T mice, a complete amelioration of α-synuclein mediated neuropathological abnormalities was observed. The third report which described two lines of knockout mice (one with ablation of exon 1, the other ablation of exons 29/30) also reported a lack of any dopaminergic phenotypes or brain neuropathology (Tong et al., 2010). Surprisingly, a major renal phenotype was found in these mice which included dramatic morphological changes and shrinkage, accumulation of alpha-synuclein and pSer 129 alphasynuclein, impaired ubiquitin degradation, impaired autophagy, apoptosis and inflammation. Interestingly, in a different exon 1 knockout model, yet to be fully described, decreased phospho-tau levels and concurrent increased soluble tubulin levels were reported, implying a role for LRRK2 in regulation microtubule dynamics (Gillardon, 2009).

Our group has also created LRRK2 KO mice, which are in the final stages of characterization. Microdialysis in these mice has revealed that while the dopamine release following KCl stimulated is not different in magnitude to the wild-type controls, it appears to be slightly delayed. Starting from about 4 months we have also seen progressive darkening of the kidneys and histopathological analysis reveals severe inflammation.

#### **4.2 Over-expression of LRRK2**

The first rodent over-expression models were described by McLeod et al in 2006 (MacLeod et al., 2006), whose group investigated both embryonic cDNA electroporation and adult adeno-associated viral expression of WT and mutant LRRK2 kinase domain constructs in rats. A reduction in neurite outgrowth and branching was observed in the embryos expressing mutant G2019S and Y1699C in periventricular layer neural progenitors. In adult rats, viral expression of WT and G2019S in the nigra resulted apotosis in nigral neurons and striatal abnormalities including phospho-tau increases.

Three years later, Chenjian Li's group published the first bacterial artificial chromosome (BAC) mouse models, using human WT and ROC domain mutant R1441G BACs (Li et al., 2009). The mice showed an expression pattern of transgenic LRRK2 that mirrored endogenous expression patterns at levels around 5–fold on an FVB/N background. Striking phenotypes were reported including progressive levodopa-responsive slowness of movement associated with ~33% decreased dopamine release following nomifensine treatment and axonal pathology of nigrostriatal dopaminergic projection. While nigral neuronal loss was absent, the R1441G mice displayed a marked reduction in the number of tyrosine hydroxylase–positive nigral dendrites and accumulation of microtubule associated protein tau pathology in the striatum. Extensive characterization of their expression matched human WT BAC model model was not presented, however no overt phenotypes were noted.

Modeling LRRK2 Parkinsonism 79

In a different transgenic approach Lin et al generated hemagglutinin tagged conditional human WT and G2019S using cDNA fragments inserted into the mouse prion protein expression vector controlled by the tetracycline-responsive promoter (tetP) (Lin et al., 2009). Expression levels were between 8-16 fold for the human WT and G2019S lines and mice were on a C57BL/6 background. Human WT mice were behaviorally normal, but G2019S mice were found to gain less weight than controls and had increased ambulatory and rearing activities. One month old human WT and G2019S and mice were also reported to have perturbed microtubule dynamics, evidenced by a dramatic shift of β-tubulin from soluble to insoluble fractions prepared from brain lysates. Finally, ubiquitin staining increased in cortical neurons of 6 month old human WT and G2019S mice and by 20 months this increase became more pronounced and was clustered with LRRK2 staining, which the authors suggest may hint to inhibition of ubiquitin-proteasome activities. Interestingly, both the human WT and G2019S mice enhanced α-synuclein pathology when crossed with inducible A53T mutant mice. Curiously, double A53T/ kinase dead G2019S mice also exhibited similar enhanced phenotype, suggesting that kinase activity was not involved in α-synuclein mediating toxicity. The authors instead attributed the synergistic effects to impairment of golgi function, microtubule transport and the ubiquitin-proteasomal pathway, which occurred when LRRK2 was co-expressed, regardless of the transgene type

Two recently described viral models are the only LRRK2 models to date that document dopamine neuronal loss. Lee et al (Lee et al., 2010a) developed herpes simplex virus (HSV) amplicon-based mouse models expressing either human WT, G2019S and G2019S-D1994A (kinase dead) LRRK2, in which up to 75% of nigral neurons were infected after injection. HSV amplicon–mediated delivery of LRRK2 G2019S induced significant loss (~50%) of tyrosine hydroxylase–positive neurons 3 weeks after stereotaxic injection into the ipsilateral striatum of mice compared to control viruses expressing WT LRRK2 and eGFP and G2019S-D1994A. This model is the first model that directly implicates kinase activity being responsible for toxicity *in vivo* in a mammalian model, supported by the lack of effect in the kinase dead model, as well as attenuation of the neuronal loss by kinase inhibitors GW5074 and indirubin-3′-monooxime. The second viral model, the only published rat model to date, used a second generation adeno-viral serotype 5 vector, with transgene expression driven by the neuronal-specific human synapsin-1 promoter to express human WT and G2019S LRRK2 in rat brain (Dusonchet et al., 2011). Injections were delivered to the striatum and retrograde expression in the nigra was around 2 fold expression level overall, although with only 30% of all neurons transduced, this suggested very high levels in individual neurons. G2019S, but not WT mice exhibited a progressive neuronal loss that reached ~20% by 42 days as well as a 10% decrease in tyrosine hydroxylase fiber density. No alpha- synuclein pathology was observed but the authors noted some transient abnormal phosphorylation of tau for both WT and G2019S which did not correlate with neuronal cell death in G2019S.

For large proteins such as LRRK2, the over-expression approach is not without caveat and within the field there has been much concern about over-expession artifacts. To circumvent this, targeting the models' own genome, known as "knockin" is an alternative and potentially more physiological approach, since gene expression is recapitulated in the correct temporal, anatomical and quantitative manner and under the endogenous

or expression level.

**4.3 Targeted knockin of LRRK2**

Two groups have since published data on BAC models expressing the kinase domain mutant G2019S. Li et al expressed a murine wild type and mutant G2019S BAC on a C57BL/6 background, with expression levels around 6 fold over endogenous LRRK2 (Li et al., 2010). Total dopamine content in the striatum was normal in WT BAC mice and G2019S mice at 6 months but declined by 25% in G2019S BAC mice by 12 months, suggesting an age related decline. Despite normal striatal dopamine levels, voltammetry in brain slices derived from 12 month old wild-type BAC transgenic mice showed a 25% increase in evoked dopamine release following a single pulse, whereas the decline in DA release following repeated stimulation was comparable to non-transgenic controls, as was their dopamine transporter (DAT)-mediated uptake. Conversely, the G2019S BAC mice displayed a 35% decrease in dopamine release by voltammetry, poorly sustained evoked dopamine release after repeated stimulation and a lower rate of dopamine uptake, presumably as a compensatory mechanism. No dopamine neuronal loss was seen in either model. Behaviorally the wild-type transgenic mice displayed enhanced ability on the beam test and increase spontaneous activity, whereas the G2019S BAC mice did not display any abnormalites. While no overt pathological lesions were reported, the authors did reveal that phospho- tau was decreased in the WT transgenic mice.

Our group (Melrose et al., 2010) also reported WT and mutant G2019S BAC mice, utilizing a human LRRK2 BAC rather than a murine BAC. Using *in vivo* microdialysis we demonstrated that basal extracellular dopamine levels were reduced by ~33% in G2019S BAC mice at ~8 months and an enhanced response to amphetamine challenge was noted. Total striatal dopamine, dopamine neuronal number, DAT levels and D1 and D2 receptor density were all unchanged up to 22 months. Behaviorally, the G2019S mice displayed some abnormal open field behavior but no motor deficits. Surprisingly, and in contrast to Li et al, we found that our human WT BAC mice also displayed reduced basal dopamine levels, even more pronounced (~66% versus 33%) than in our G2019S BAC mice. While this is likely attributed to differential expression levels in the two lines (WT BAC mice around 3.5 fold overexpression in half brain extracts and 2.5 fold in G2019S mice) it nevertheless supports a gain of function mechanism. Interestingly, D1 receptors were slightly upregulated in aged human WT BAC mice, although no changes were found in D2 receptors or DAT levels. Pathologically we did not detect any alpha-synuclein pathology in either line, but we did see changes in the phosphorylation of tau. Modest phosphorylation changes, detected by immunohistochemistry, were restricted to the hippocampus in the human WT BAC mice (the area of highest expression). In the G2019S mice however, tau alterations were much more pronounced and widespread. Biochemical analysis of tau revealed enhanced phosphorylation at several phospho-epitopes and upon dephosphorylation the tau species distribution was still different from the non-transgenic controls, suggesting that other post-translational modifications may be altered in G2019S mice and we hypothesize that these processing changes may increase the likelihood of abberant phosphorylation. One final observation worth noting is that we recently showed that neurogenesis is altered in our G2019S mice (Winner et al., 2011). Proliferation and migration of new neurons was impaired in the subventricular zone/rostral migratory stream and in the subgranular zone of the hippocampus. Furthermore, new neurons in the hippocampus had impaired outgrowth and a diminished number of spines. Curiously, exercise was found to partially recover the neuroblast deficit in the hippocampus, which may suggest that exercise induced signaling can at least partially compensate abberant LRRK2 activity caused by the G2019S mutation.

Two groups have since published data on BAC models expressing the kinase domain mutant G2019S. Li et al expressed a murine wild type and mutant G2019S BAC on a C57BL/6 background, with expression levels around 6 fold over endogenous LRRK2 (Li et al., 2010). Total dopamine content in the striatum was normal in WT BAC mice and G2019S mice at 6 months but declined by 25% in G2019S BAC mice by 12 months, suggesting an age related decline. Despite normal striatal dopamine levels, voltammetry in brain slices derived from 12 month old wild-type BAC transgenic mice showed a 25% increase in evoked dopamine release following a single pulse, whereas the decline in DA release following repeated stimulation was comparable to non-transgenic controls, as was their dopamine transporter (DAT)-mediated uptake. Conversely, the G2019S BAC mice displayed a 35% decrease in dopamine release by voltammetry, poorly sustained evoked dopamine release after repeated stimulation and a lower rate of dopamine uptake, presumably as a compensatory mechanism. No dopamine neuronal loss was seen in either model. Behaviorally the wild-type transgenic mice displayed enhanced ability on the beam test and increase spontaneous activity, whereas the G2019S BAC mice did not display any abnormalites. While no overt pathological lesions were reported, the authors did reveal that

Our group (Melrose et al., 2010) also reported WT and mutant G2019S BAC mice, utilizing a human LRRK2 BAC rather than a murine BAC. Using *in vivo* microdialysis we demonstrated that basal extracellular dopamine levels were reduced by ~33% in G2019S BAC mice at ~8 months and an enhanced response to amphetamine challenge was noted. Total striatal dopamine, dopamine neuronal number, DAT levels and D1 and D2 receptor density were all unchanged up to 22 months. Behaviorally, the G2019S mice displayed some abnormal open field behavior but no motor deficits. Surprisingly, and in contrast to Li et al, we found that our human WT BAC mice also displayed reduced basal dopamine levels, even more pronounced (~66% versus 33%) than in our G2019S BAC mice. While this is likely attributed to differential expression levels in the two lines (WT BAC mice around 3.5 fold overexpression in half brain extracts and 2.5 fold in G2019S mice) it nevertheless supports a gain of function mechanism. Interestingly, D1 receptors were slightly upregulated in aged human WT BAC mice, although no changes were found in D2 receptors or DAT levels. Pathologically we did not detect any alpha-synuclein pathology in either line, but we did see changes in the phosphorylation of tau. Modest phosphorylation changes, detected by immunohistochemistry, were restricted to the hippocampus in the human WT BAC mice (the area of highest expression). In the G2019S mice however, tau alterations were much more pronounced and widespread. Biochemical analysis of tau revealed enhanced phosphorylation at several phospho-epitopes and upon dephosphorylation the tau species distribution was still different from the non-transgenic controls, suggesting that other post-translational modifications may be altered in G2019S mice and we hypothesize that these processing changes may increase the likelihood of abberant phosphorylation. One final observation worth noting is that we recently showed that neurogenesis is altered in our G2019S mice (Winner et al., 2011). Proliferation and migration of new neurons was impaired in the subventricular zone/rostral migratory stream and in the subgranular zone of the hippocampus. Furthermore, new neurons in the hippocampus had impaired outgrowth and a diminished number of spines. Curiously, exercise was found to partially recover the neuroblast deficit in the hippocampus, which may suggest that exercise induced signaling can at least partially compensate abberant LRRK2 activity caused by the

phospho- tau was decreased in the WT transgenic mice.

G2019S mutation.

In a different transgenic approach Lin et al generated hemagglutinin tagged conditional human WT and G2019S using cDNA fragments inserted into the mouse prion protein expression vector controlled by the tetracycline-responsive promoter (tetP) (Lin et al., 2009). Expression levels were between 8-16 fold for the human WT and G2019S lines and mice were on a C57BL/6 background. Human WT mice were behaviorally normal, but G2019S mice were found to gain less weight than controls and had increased ambulatory and rearing activities. One month old human WT and G2019S and mice were also reported to have perturbed microtubule dynamics, evidenced by a dramatic shift of β-tubulin from soluble to insoluble fractions prepared from brain lysates. Finally, ubiquitin staining increased in cortical neurons of 6 month old human WT and G2019S mice and by 20 months this increase became more pronounced and was clustered with LRRK2 staining, which the authors suggest may hint to inhibition of ubiquitin-proteasome activities. Interestingly, both the human WT and G2019S mice enhanced α-synuclein pathology when crossed with inducible A53T mutant mice. Curiously, double A53T/ kinase dead G2019S mice also exhibited similar enhanced phenotype, suggesting that kinase activity was not involved in α-synuclein mediating toxicity. The authors instead attributed the synergistic effects to impairment of golgi function, microtubule transport and the ubiquitin-proteasomal pathway, which occurred when LRRK2 was co-expressed, regardless of the transgene type or expression level.

Two recently described viral models are the only LRRK2 models to date that document dopamine neuronal loss. Lee et al (Lee et al., 2010a) developed herpes simplex virus (HSV) amplicon-based mouse models expressing either human WT, G2019S and G2019S-D1994A (kinase dead) LRRK2, in which up to 75% of nigral neurons were infected after injection. HSV amplicon–mediated delivery of LRRK2 G2019S induced significant loss (~50%) of tyrosine hydroxylase–positive neurons 3 weeks after stereotaxic injection into the ipsilateral striatum of mice compared to control viruses expressing WT LRRK2 and eGFP and G2019S-D1994A. This model is the first model that directly implicates kinase activity being responsible for toxicity *in vivo* in a mammalian model, supported by the lack of effect in the kinase dead model, as well as attenuation of the neuronal loss by kinase inhibitors GW5074 and indirubin-3′-monooxime. The second viral model, the only published rat model to date, used a second generation adeno-viral serotype 5 vector, with transgene expression driven by the neuronal-specific human synapsin-1 promoter to express human WT and G2019S LRRK2 in rat brain (Dusonchet et al., 2011). Injections were delivered to the striatum and retrograde expression in the nigra was around 2 fold expression level overall, although with only 30% of all neurons transduced, this suggested very high levels in individual neurons. G2019S, but not WT mice exhibited a progressive neuronal loss that reached ~20% by 42 days as well as a 10% decrease in tyrosine hydroxylase fiber density. No alpha- synuclein pathology was observed but the authors noted some transient abnormal phosphorylation of tau for both WT and G2019S which did not correlate with neuronal cell death in G2019S.

#### **4.3 Targeted knockin of LRRK2**

For large proteins such as LRRK2, the over-expression approach is not without caveat and within the field there has been much concern about over-expession artifacts. To circumvent this, targeting the models' own genome, known as "knockin" is an alternative and potentially more physiological approach, since gene expression is recapitulated in the correct temporal, anatomical and quantitative manner and under the endogenous

Modeling LRRK2 Parkinsonism 81

tau and LRRK2 protein, there appears to be an indirect link that warrants further investigation. If LRRK2 regulates tau physiology, this could have important implication for

Less consistent/investigated *in vivo*, but nevertheless still compelling are the changes in the inflammatory, autophagy/lysosomal, apoptotic, mitochondrial and proteosomal pathways observed in some models. These pathways may be particularly important in unraveling how LRRK2 leads to α-synuclein pathology in humans. While studies in invertebrates are suggestive of a potential role for LRRK2, more mammalian studies are needed into the role of LRRK2 in mitochrondrial/stress pathways. As it stands, there is no evidence for a direct interaction between LRRK2 and α-synuclein and the only instance of *in vivo* α-synuclein pathology in a LRRK2 model is in the kidneys, but not brain, of the LRRK2 knockout model (Tong et al., 2010). Notably, accumulation was accompanied by autophagic, proteasomal and inflammatory changes. Furthermore in double LRRK2 and α-synuclein A53T mice, enhancement of α-synuclein pathology was attributed to impairments in microtubule dynamic, golgi organization, mitochondrial toxicity and ubiquitin-proteasomal pathway (Lin et al., 2009). What is difficult to resolve though, is that double LRRK2 KO/ A53T mice have ameliorated α-synuclein brain pathology (Lin et al., 2009). These complex findings reiterate the notion that LRRK2 is likely a multi-faceted protein, which may have distinct

Intense pharmaceutical interest has surrounded LRRK2 since its discovery and many companies are developing inhibitors of LRRK2 and screening is already underway in many of the models described above. It is still not clear exactly what function of LRRK2 mediates its toxicity and data attributing it to enzymatic kinase activity is conflicting. Although the general consensus appears to be that LRRK2 pathogenicity is a toxic gain of function, the kidney phenotype in LRRK2 KO mice suggests that peripheral effects may be an important loss-of-function consideration. A highly selective LRRK2 inhibitor (LRRK2-IN1) was recently developed by Nathaniel Gray and colleagues (Deng et al., 2011) which abolished Ser910 and Ser935 phosphorylation of LRRK2 in the kidney of mice after 1 hour. No changes were observed in brain because the compound is unable to cross the blood brain barrier. Once CNS drug delivery issues are overcome, it will be interesting to see the effects

Aasly, J. O., et al., 2005. Clinical features of LRRK2-associated Parkinson's disease in central

Abeliovich, A., et al., 2000. Mice lacking alpha-synuclein display functional deficits in the

Adams, J. R., et al., 2005. PET in LRRK2 mutations: comparison to sporadic Parkinson's disease and evidence for presymptomatic compensation. Brain. 128, 2777-85. Andres-Mateos, E., et al., 2009. Unexpected lack of hypersensitivity in LRRK2 knock-out

mice to MPTP (1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine). J Neurosci. 29,

LRRK2 therapies in Alzheimer's disease.

**4.5 The future for LRRK2 therapeutics**

of LRRK-IN1in in vivo LRRK2 models.

Norway. Ann Neurol. 57, 762-5.

nigrostriatal dopamine system. Neuron. 25, 239-52.

cellular specific roles.

**5. References**

15846-50.

transcriptional and translational controls. Nevertheless, many would still argue, justifiably, that over-expression models and their phenotypes, even if exaggerated, often give vital clues to normal and pathological functions. Equally, the risk with the knockin approach is that the relatively low mutant expression levels, within a species that doesn't normally develop the disease, may yield no or very subtle phenotypes.

To date only one knockin model has been published, by Tong et al, who created a ROC domain R1441C mutant (Tong et al., 2009). Whilst the homozygous knockin mice were grossly normal and did not exhibit dopamine neuronal loss, amperometric recordings in chromaffin cells derived from the R1441C, stimulated with high KCl, revealed significant reductions in the total catecholamine release per cell, quantal size and the frequency of release events. Slice recordings from dopaminergic neurons in the nigra of R1441C mice also exhibited smaller amplitude and duration of hyperpolarization after dopamine application, as well as slower recover times, and reduced responses to amphetamine and the D2 agonist quinpirole, compared with WT controls. Locomotor testing in the open field also revealed the knockin mice had a reduced behavioral response to amphetamine and quinpirole, providing *in vivo* evidence that dopamine release and D2 autoceptor feedback mechanisms may be impaired. No neuropathology was noted in these mice.

#### **4.4 What do the models tell us about LRRK2?**

At first glance, the success of the LRRK2 models appears to be nominal, with not a single model recapturing all the key features desired for a PD model – dopamine cell loss, motor impairment and alpha-synculein pathology. However, independent of the approach, a unifying theme is emerging from both invertebrate and vertebrate LRRK2 models, suggesting an important role for LRRK2 in dopaminergic neurotransmission, even in the absence of dopamine neuronal loss. Several other genetic PD mouse models also have abnormalities in dopamine transmission without neuronal loss including PINK1, parkin, DJ-1 and SNCA knockouts and SNCA WT over-expression mice (Abeliovich et al., 2000; Goldberg et al., 2003; Goldberg et al., 2005; Kitada et al., 2009; Nemani et al., 2010). Imaging studies have long established that in asymptomatic PD, the earliest detectable changes occur in the dopamine transporter and the same holds true for asymptomatic LRRK2 (Nandhagopal et al., 2008; Sossi et al., 2010) and SNCA patients (Bostantjopoulou et al., 2008; Perani et al., 2006; Samii et al., 1999). Thus, the data evolving from LRRK2 models (and other PD genetic models) may be recapturing early preclinical events. In reality this may make the models more valuable because the onset of motor symptoms in PD is only after 50- 70% of the dopamine neurons are lost, by which point neuro-protective therapy would be futile. Understanding these early events in disease is key to allow us identify biomarkers to detect at risk patients and design neuro-protective therapies.

Aside from the effects on dopamine neurotransmission, the other consistent theme arising from LRRK2 *in vivo* data appears to be the impairment of cytoskeletal function, evidenced by the alterations observed in tau phosphorylation and perturbed microtubule dynamics. Although tau pathology is rare in LRRK2 brains, there is mounting evidence of the involvement of tau in PD in general, with over 15 genetic studies in small populations implicating variability in the tau gene with Parkinson's disease and a recent study of a large number of European PD samples unequivocally showing that tau gene (MAPT) variability is a major risk factor for PD, along with the alpha-synculein gene (SNCA) (Simon-Sanchez et al., 2009). Even though it has been proven already that there is no direct interaction between

transcriptional and translational controls. Nevertheless, many would still argue, justifiably, that over-expression models and their phenotypes, even if exaggerated, often give vital clues to normal and pathological functions. Equally, the risk with the knockin approach is that the relatively low mutant expression levels, within a species that doesn't normally

To date only one knockin model has been published, by Tong et al, who created a ROC domain R1441C mutant (Tong et al., 2009). Whilst the homozygous knockin mice were grossly normal and did not exhibit dopamine neuronal loss, amperometric recordings in chromaffin cells derived from the R1441C, stimulated with high KCl, revealed significant reductions in the total catecholamine release per cell, quantal size and the frequency of release events. Slice recordings from dopaminergic neurons in the nigra of R1441C mice also exhibited smaller amplitude and duration of hyperpolarization after dopamine application, as well as slower recover times, and reduced responses to amphetamine and the D2 agonist quinpirole, compared with WT controls. Locomotor testing in the open field also revealed the knockin mice had a reduced behavioral response to amphetamine and quinpirole, providing *in vivo* evidence that dopamine release and D2 autoceptor feedback mechanisms

At first glance, the success of the LRRK2 models appears to be nominal, with not a single model recapturing all the key features desired for a PD model – dopamine cell loss, motor impairment and alpha-synculein pathology. However, independent of the approach, a unifying theme is emerging from both invertebrate and vertebrate LRRK2 models, suggesting an important role for LRRK2 in dopaminergic neurotransmission, even in the absence of dopamine neuronal loss. Several other genetic PD mouse models also have abnormalities in dopamine transmission without neuronal loss including PINK1, parkin, DJ-1 and SNCA knockouts and SNCA WT over-expression mice (Abeliovich et al., 2000; Goldberg et al., 2003; Goldberg et al., 2005; Kitada et al., 2009; Nemani et al., 2010). Imaging studies have long established that in asymptomatic PD, the earliest detectable changes occur in the dopamine transporter and the same holds true for asymptomatic LRRK2 (Nandhagopal et al., 2008; Sossi et al., 2010) and SNCA patients (Bostantjopoulou et al., 2008; Perani et al., 2006; Samii et al., 1999). Thus, the data evolving from LRRK2 models (and other PD genetic models) may be recapturing early preclinical events. In reality this may make the models more valuable because the onset of motor symptoms in PD is only after 50- 70% of the dopamine neurons are lost, by which point neuro-protective therapy would be futile. Understanding these early events in disease is key to allow us identify biomarkers to

Aside from the effects on dopamine neurotransmission, the other consistent theme arising from LRRK2 *in vivo* data appears to be the impairment of cytoskeletal function, evidenced by the alterations observed in tau phosphorylation and perturbed microtubule dynamics. Although tau pathology is rare in LRRK2 brains, there is mounting evidence of the involvement of tau in PD in general, with over 15 genetic studies in small populations implicating variability in the tau gene with Parkinson's disease and a recent study of a large number of European PD samples unequivocally showing that tau gene (MAPT) variability is a major risk factor for PD, along with the alpha-synculein gene (SNCA) (Simon-Sanchez et al., 2009). Even though it has been proven already that there is no direct interaction between

develop the disease, may yield no or very subtle phenotypes.

may be impaired. No neuropathology was noted in these mice.

detect at risk patients and design neuro-protective therapies.

**4.4 What do the models tell us about LRRK2?**

tau and LRRK2 protein, there appears to be an indirect link that warrants further investigation. If LRRK2 regulates tau physiology, this could have important implication for LRRK2 therapies in Alzheimer's disease.

Less consistent/investigated *in vivo*, but nevertheless still compelling are the changes in the inflammatory, autophagy/lysosomal, apoptotic, mitochondrial and proteosomal pathways observed in some models. These pathways may be particularly important in unraveling how LRRK2 leads to α-synuclein pathology in humans. While studies in invertebrates are suggestive of a potential role for LRRK2, more mammalian studies are needed into the role of LRRK2 in mitochrondrial/stress pathways. As it stands, there is no evidence for a direct interaction between LRRK2 and α-synuclein and the only instance of *in vivo* α-synuclein pathology in a LRRK2 model is in the kidneys, but not brain, of the LRRK2 knockout model (Tong et al., 2010). Notably, accumulation was accompanied by autophagic, proteasomal and inflammatory changes. Furthermore in double LRRK2 and α-synuclein A53T mice, enhancement of α-synuclein pathology was attributed to impairments in microtubule dynamic, golgi organization, mitochondrial toxicity and ubiquitin-proteasomal pathway (Lin et al., 2009). What is difficult to resolve though, is that double LRRK2 KO/ A53T mice have ameliorated α-synuclein brain pathology (Lin et al., 2009). These complex findings reiterate the notion that LRRK2 is likely a multi-faceted protein, which may have distinct cellular specific roles.

#### **4.5 The future for LRRK2 therapeutics**

Intense pharmaceutical interest has surrounded LRRK2 since its discovery and many companies are developing inhibitors of LRRK2 and screening is already underway in many of the models described above. It is still not clear exactly what function of LRRK2 mediates its toxicity and data attributing it to enzymatic kinase activity is conflicting. Although the general consensus appears to be that LRRK2 pathogenicity is a toxic gain of function, the kidney phenotype in LRRK2 KO mice suggests that peripheral effects may be an important loss-of-function consideration. A highly selective LRRK2 inhibitor (LRRK2-IN1) was recently developed by Nathaniel Gray and colleagues (Deng et al., 2011) which abolished Ser910 and Ser935 phosphorylation of LRRK2 in the kidney of mice after 1 hour. No changes were observed in brain because the compound is unable to cross the blood brain barrier. Once CNS drug delivery issues are overcome, it will be interesting to see the effects of LRRK-IN1in in vivo LRRK2 models.

#### **5. References**

Modeling LRRK2 Parkinsonism 83

Higashi, S., et al., 2007a. Localization of Parkinson's disease-associated LRRK2 in normal

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**5**

*Slovenia*

**Alpha-Synuclein Interactions with Membranes**

Synucleinopathies are a group of neurodegenerative disorders that share common pathological intracellular deposits that contain aggregates of the protein α-synuclein. Substantial evidence suggests that fibril formation by α-synuclein is a critical step in the development of Parkinson's disease (PD). Indeed, *in vitro*, α-synuclein forms fibrils with morphologies and staining characteristics similar to those extracted from disease-affected brains. Also, three single-point mutations and duplication or triplication of the α-synuclein

However, the function of α-synuclein remains unknown. A significant portion of αsynuclein is localized within membrane fractions, and especially synaptic vesicles associated with vesicular transport processes. These observations suggest that α-synuclein has a role in vesicular trafficking. Although α-synuclein belongs to a group of natively unfolded proteins, there is strong evidence that the membrane affinity of the protein induces an αhelical conformation. A large number of studies have investigated α-synuclein–lipid interactions in the search for a physiological function, as well as to understand this potential membrane involvement in the pathogenesis of α-synuclein. In this review, we will predominantly focus on current opinion about the native wild-type α-synuclein–lipid interactions and the structure of α-synuclein that is established at the membrane surface. However, it should be noted that membranes have been reported to both accelerate and inhibit the fibril formation of α-synuclein, although this will not be the focus of the present

A significant number of proteins involved in protein deposition diseases have been seen to be intrinsically disordered proteins. Well-known examples include amyloid β-protein and tau protein in Alzheimer's disease, prion protein (PrP) in prion diseases, exon 1 region of

It has been estimated that more than 30% of eukaryotic proteins have disordered regions that are greater than 50 consecutive residues (Dunker et al., 2001). This term "disordered protein" refers to proteins that in their purified state at neutral pH, have been either shown experimentally or predicted to lack an ordered structure; such proteins are also known as natively unfolded, or intrinsically unstructured. Disordered proteins, or disordered regions

huntingtin in Huntington's disease, and α-synuclein in PD (Fink, 2005).

**1. Introduction**

review.

locus correlate with early onset of PD.

**2. Intrinsically disordered proteins**

Katja Pirc1 and Nataša Poklar Ulrih1,2 *1University of Ljubljana, Biotechnical faculty*

*2Centre of excellence CIPKeBiP*


**6. Conclusions**

The crystallization of PLLA is one of the key factor for analyzing structure– property relationships of PLLA-based blend, block copolymer and nanocomposites. The presence of solid state additives (SFN and CNC) increased the nucleation of PLLA, thus influences the whole crystallization process, however the spherulite growth of PLLA was not significantly changed by loading SFN or CNC. For the case of liquid-state additive i.e. OMG, nucleation and spherulite growth rate both were found to be increased which improves the crystallizability of PLLA. The presence of SFN enhanced the SC crystallization while it suppressed the HC crystallization. It is noteworthy for this particular case that the spherulite growth rate was suppressed by the addition of 1% SFN whereas the nucleation density was much increased by SFN. For the case of PLLA/PEG(50/50) blend, a two-step temperature-jump was conducted as 180.0°C ! 127.0°C ! 45.0°C. For this particular condition, it was found that PEG can crystallize only in the preformed spherulites of PLLA. The confined crystallization of PEG can be accounted for as follows. Upon the PLLA crystallization at 127.0°C, the PEG content in the amorphous region inside the PLLA spherulite is increased because of the formation of the pure solid phase of PLLA (crystalline phase). Then,*Tf* of PEG increases so that PEG can crystallize but this crystallization is only allowed inside the PLLA spherulite. The direct evidence of the PEG crystallization was obtained by the bright-field optical microscopic observation and WAXS measurements. For the case of PLA and PCL block copolymers, the poor mechanical property of PDLA (which is poor elongation at break) was reported to be much improved by the presence of extensible PCL block component even in case of a short PCL chain in the block copolymer, which may be ascribed to the confined crystallization of PCL in the microdomain structure. Furthermore, the formation of SC crystal in the enantiomeric blend of PLLA-*b*-PCL and PDLA-*b*-PCL have been examined by changing the block length of PLLA and PDLA components.


**1. Introduction**

Aflatoxins (AFs) are a group of mycotoxins that are toxic, carcinogenic, and mutagenic. Amongst them, aflatoxin B1 (AFB1) is the most potent carcinogen found in nature and thus is classified as a group 1 carcinogen to humans by the International Agency for Research on Cancer (IARC) [1,2]. AFs are produced mainly by a common fungus *Aspergillus flavus*in fields, transportation, and storage conditions. AFs consistently and increasingly contaminate both human food and animal feed, and thus have been strictly regulated by the government authorities in over 100 countries in the world [3–5]. Trace levels of AFs, 4–20 parts per billion (ppb), can be considered hazardous, and foods with higher amounts are not fit for human consumption [6]. As global warming progresses, AF-producing molds will expand their growing regions, leading to an increased burden of AF contamination in the world [7–9].

AFs are fluorescent heterocyclic secondary metabolites with molecular weights of 286 to 346 Da. Although more than 13 types of AFs have been discovered, AFB1, AFB2, AFG1, AFG2, and AFM1 (in milk) are particularly hazardous to humans and animals, as they have been commonly present in food and feed. The "B" and "G" refer to the blue and green-blue fluorescent colors emitted under ultraviolet (UV) light (Figure 1A), and the numbers represent the travelled position from the front line

on the thin layer chromatography (TLC); moreover, AFB2 and AFG2 are the dihydroxy derivatives of AFB1 and AFG1, respectively [10,11]. Due to their oxygenated pentaheterocyclic structure, which is known as coumarinic nucleus, AFs have natural fluorescence properties (Figure 1A,B). This ability to fluoresce has paved the way for most analytical methods for the detection and quantification of these toxins [12]. Because of the absence of a double bond in the furan ring, AFB2 and AFG2 have a higher fluorescence quantum yield of fluorophore than the unsaturated compounds AFB1 and AFG1 [13]. derivatives of AFB1 and AFG1, respectively [10,11]. Due to their oxygenated pentaheterocyclic structure, which is known as coumarinic nucleus, AFs have natural fluorescence properties (Figure 1A,B). This ability to fluoresce has paved the way for most analytical methods for the detection and quantification of these toxins [12]. Because of the absence of a double bond in the furan ring, AFB2 and AFG2 have a higher fluorescence quantum yield of fluorophore than the unsaturated compounds AFB1 and AFG1 [13].

line on the thin layer chromatography (TLC); moreover, AFB2 and AFG2 are the dihydroxy

**Figure 1.** Aflatoxin (AF) thin layer chromatography (TLC) and structures. (**A**) A thin layer chromatograph of standard aflatoxin mixture containing AFB1, AFB2, AFG1, and AFG2. Note the color and the separation order. The photo was taken in a UV chamber at 365 nm. (**B**) Chemical structure of AFB1, AFB2, AFG1, and AFG2. **Figure 1.** Aflatoxin (AF) thin layer chromatography (TLC) and structures. (**A**) A thin layer chromatograph of standard aflatoxin mixture containing AFB1, AFB2, AFG1, and AFG2. Note the color and the separation order. The photo was taken in a UV chamber at 365 nm. (**B**) Chemical structure of AFB1, AFB2, AFG1, and AFG2.

*Aspergilli* residing in field soil of *A. flavus* specifically, is considered as the main source of AF contamination of agricultural products; however, not all strains of *A. flavus* produce AFs [14]. Communities of AF-producing fungal residents in varying agricultural environments are complex groups of diverse individuals. Thus, knowing the AF-producing potential of *A. flavus* populations is an important factor for the predicting the incidence and severity of AF contamination. On the other hand, although it was thought that *A. flavus* only produced B type AFs, recent reports have *Aspergilli* residing in field soil of *A. flavus* specifically, is considered as the main source of AF contamination of agricultural products; however, not all strains of *A. flavus* produce AFs [14]. Communities of AF-producing fungal residents in varying agricultural environments are complex groups of diverse individuals. Thus, knowing the AF-producing potential of *A. flavus* populations is an important factor for the predicting the incidence and severity of AF contamination. On the other hand, although it was thought that *A. flavus* only produced B type AFs, recent reports have demonstrated that several *A. flavus* strains can also produce the G type AFs [15–18].

demonstrated that several *A. flavus* strains can also produce the G type AFs [15–18]. To detect and differentiate aflatoxigenic and non-toxigenic *Aspergilli*, several methods have been developed including molecular marker-based methods and fungal culture methods [19,20]. Currently, in most cases, aflatoxigenic fungi are being identified by culture methods coupled with thin layer chromatography (TLC) or high-performance liquid chromatography (HPLC). However, to the best of our knowledge, no methods have been optimized and validated for simultaneous quantifications of aflatoxin cocktail (AFB1, AFB2, AFG1, AFG2) in the fungal cultures. Gell and Carbone have used HPLC-FLD (fluorescence) for quantification of AFB1 from fungal mycelium culture after sample purification by solid phase extraction tubes (SPE), and they were able to achieve a limit of detection (LOD) and limit of quantification (LOQ) of 2 and 3.9 ng/mL, respectively [21]. Culture method has a number of advantages over others, including it being inexpensive, rapid, available in most labs, and requiring minimal technical skills. However, due to the lack of verifications of these methods, they are generally regarded as being less precise than the other methods. Here, we report a new method for a rapid, sensitive, and simultaneous detection of AFB1, AFB2, AFG1, and AFG2 produced in laboratory culture conditions using HPLC equipped with a To detect and differentiate aflatoxigenic and non-toxigenic *Aspergilli*, several methods have been developed including molecular marker-based methods and fungal culture methods [19,20]. Currently, in most cases, aflatoxigenic fungi are being identified by culture methods coupled with thin layer chromatography (TLC) or high-performance liquid chromatography (HPLC). However, to the best of our knowledge, no methods have been optimized and validated for simultaneous quantifications of aflatoxin cocktail (AFB1, AFB2, AFG1, AFG2) in the fungal cultures. Gell and Carbone have used HPLC-FLD (fluorescence) for quantification of AFB1 from fungal mycelium culture after sample purification by solid phase extraction tubes (SPE), and they were able to achieve a limit of detection (LOD) and limit of quantification (LOQ) of 2 and 3.9 ng/mL, respectively [21]. Culture method has a number of advantages over others, including it being inexpensive, rapid, available in most labs, and requiring minimal technical skills. However, due to the lack of verifications of these methods, they are generally regarded as being less precise than the other methods. Here, we report a new method for a rapid, sensitive, and simultaneous detection of AFB1, AFB2, AFG1, and AFG2 produced in laboratory culture conditions using HPLC equipped with a conventional diode array (DAD) and a fluorescence detector (FLD) without using any pre- or post-column derivatization reagents, SPE and

conventional diode array (DAD) and a fluorescence detector (FLD) without using any pre- or post-

immune affinity column (IAC), or fluorescent enhancers. Moreover, we have optimized and validated the method through a series of experiments to meet the research laboratory needs for a robust, fast, easy to use, cheap, and environmentally friendly protocol with minimum organic solvents waste.


**3. Criteria for action in large courses**

Between April 2016 and July 2017, 15 universities throughout Chile were contacted to participate in the study, identifying and convening the best teachers of each institution. Each university selected their representing teachers using two key criteria. The first criterion is that teachers had the recognition of quality and excellence in teaching through different mechanisms, such as the evaluation of students, recognition among peers, and awards given to the best teachers at the institutional level. The second criterion of selection was related to the number of students in the course and the teacher or teaching team. In this sense, it was considered as selection criteria that the number of students per teacher doubled the overall average of the institution. This last criterion was adopted in this way, because the available evidence is not conclusive about what "large courses" mean, ranging from 50 to 1000 students, or under the criteria of "low visual contact" between the teacher and the students [10].

monitoring that teachers develop in different modalities and situations, ranging from the use of clickers through one-minute papers to brief quizzes, are key actions. Some representative quotes were "*…I am permanently concerned about student learning. I ask them a lot in class. And when I see what they are not understanding, I change the teaching strategy…*"; "*…in all classes I try to use clickers or brief questions … with these results, I start the next class. When I realize that the answers are not what I expect, I modify the class to try to get my students to learn*"; "*With the results of the partial assessments, I have sometimes had to adjust the syllabus…it is essential that my students learn*"; "*For several years until now I have been trying to invest more time on the essentials of the course content, to generate spaces of time to reinforce what students cannot learn…*"; *and* "*After I finish each class, I send a small online survey with the topics that were reviewed. I ask them two things: what you learned most strongly and what you have the most doubts…at the beginning of each class, I start with a brief synthesis with those weakest elements detected…when problems persists, I organize an activity especially to strengthen those points…*". Not all the teaching work will be determined from the beginning; probably during the development of the course, adjustments must be made from the feedback received by the students.

Large Courses at Universities: Criteria for Teacher Action http://dx.doi.org/10.5772/intechopen.72674 165

This aspect should always be considered within the administration of any class.

**3.3. The use of examples or analogies originated from reality is able to link**

Not always the topics of the course are liked by all students, especially in areas that may be more abstract and less motivating. A relevant fact is how teachers select and use examples and situations of contingency in order to promote motivation, linkage, and meaningfulness with the content or learning that is being intended in students. The above not only at an intellectual level but also at an emotional or empathic level with the situation being exemplified and its intrinsic link with learning. Some representative quotes were "*…in the day-to-day I am always looking for examples to use in my course. For me it is key to choose good examples not only able to cover the content that I am delivering, but also to engage students to learn*"; "*Students respond not just because they want to learn. They need to know how knowledge can be used in everyday life…*"; "*My students are not alien to reality and to the contingency…of what is happening around them. In one way or another, it affects their lives…so choosing good examples of reality will help them understand their environment and make learning meaningful…*"; "*When I start the course I realize that students are not able to relate contents to reality…it is as if they lived in parallel realities. When I gradually explain using everyday examples, they discover a new world and commit to the course. Hence, the importance I give in selecting good examples…*"; *and* "*Several years ago, in the evaluations that I applied in the course, rather than asking the students to answer questions, I gave them topics that they should exemplify, relate and analyze with facts of national and international contingency…it has given me very good results…*". This represents better communication skills not only over the average of teachers but also in the effective and relevant selection of examples capable of linking students' motivation with

**3.4. Promotion in the generation of networks of support and collaboration intra- and extracurricular (both between students and teachers) favors the quality of learning**

Teachers use the positive effect of collaborative networks, both in and out of the course. Within the course, there are multiple actions, but some stand out, such as peer instruction, collaborative

**cognitively and emotionally more effectively**

the contents and learning of the course.

Under these criteria, 32 teachers were identified who taught classes in large courses comprising between 62 and 246 students. Interviews were scheduled, informed consent validated by the faculty ethics committee, and interviews conducted according to the predefined protocol for this purpose. Interviews were recorded in audio files, and field notes were generated. Then, each interview and field notes were analyzed and codified, identifying and relating effective self-reported teaching practices, using the ATLAS.ti® software. Then, codes were integrated and optimized, generating five large groups of codes. Finally, a process of conceptualization or theorization of the categories with greater concurrence began.

The qualitative methodology described above [40–42] allowed the identification of the five criteria that teachers frequently use—consciously or unconsciously—within their teaching practice in large university courses. The criteria identified in their totality are methodological/ pedagogical and are presented from the highest degree of concurrence (22) to the minor (8). Each of the criteria was then reviewed and conceptualized.

#### **3.1. The ubiquitous interaction between student-teacher-student propitiates a better environment for learning**

Communication seems to be a relevant factor in the learning experience of large courses. This communication, however, has a particularity. It is present at all times, everywhere and in various formats or devices. Teachers use various ways to be "always connected" with their students. In other words, it is to offer an "always available" training experience through various media and formats, beyond the formal classroom spaces. Some representative quotes were "*…I have a special mobile phone for my courses. There, I set up a Whatsapp®-volunteer group with my students from the beginning of the course. They ask me questions and I respond at any time of the day, wherever I am*"; "*Since I discovered Facebook® a few years ago, I set up a closed group where my students participate in a very natural way. It was a good experience. It is relevant to observe how students interact, often responding to their doubts among themselves*"; and "*…in my strategic communication course, I use a lot Twitter®, because it allows me to exemplify with everyday cases the contents of the course…the students participate by commenting, allowing me to make corrections about certain errors that they may be making in their analyses*".

The use of communication technologies and social networks seems to be a great strategy to improve the interaction between teachers and their students. In this sense, the use of social media or Web 2.0 has become an interesting resource for student learning.

#### **3.2. Dynamic decision-making based on student learning achievement throughout the process should be the north in classroom management**

Size is not a sufficient justification for teachers to not orient their practice toward student learning outcomes. Most interviewees stated that they take short- and long-term measures when they do not achieve the syllabus objectives or in a particular activity or generation of evidence. In a way they empathize and take responsibility for the results that their students achieve, but above all, they manage to reorient their actions. In this context, the processes of feedback and monitoring that teachers develop in different modalities and situations, ranging from the use of clickers through one-minute papers to brief quizzes, are key actions. Some representative quotes were "*…I am permanently concerned about student learning. I ask them a lot in class. And when I see what they are not understanding, I change the teaching strategy…*"; "*…in all classes I try to use clickers or brief questions … with these results, I start the next class. When I realize that the answers are not what I expect, I modify the class to try to get my students to learn*"; "*With the results of the partial assessments, I have sometimes had to adjust the syllabus…it is essential that my students learn*"; "*For several years until now I have been trying to invest more time on the essentials of the course content, to generate spaces of time to reinforce what students cannot learn…*"; *and* "*After I finish each class, I send a small online survey with the topics that were reviewed. I ask them two things: what you learned most strongly and what you have the most doubts…at the beginning of each class, I start with a brief synthesis with those weakest elements detected…when problems persists, I organize an activity especially to strengthen those points…*".

Not all the teaching work will be determined from the beginning; probably during the development of the course, adjustments must be made from the feedback received by the students. This aspect should always be considered within the administration of any class.

#### **3.3. The use of examples or analogies originated from reality is able to link cognitively and emotionally more effectively**

as selection criteria that the number of students per teacher doubled the overall average of the institution. This last criterion was adopted in this way, because the available evidence is not conclusive about what "large courses" mean, ranging from 50 to 1000 students, or under the

Under these criteria, 32 teachers were identified who taught classes in large courses comprising between 62 and 246 students. Interviews were scheduled, informed consent validated by the faculty ethics committee, and interviews conducted according to the predefined protocol for this purpose. Interviews were recorded in audio files, and field notes were generated. Then, each interview and field notes were analyzed and codified, identifying and relating effective self-reported teaching practices, using the ATLAS.ti® software. Then, codes were integrated and optimized, generating five large groups of codes. Finally, a process of concep-

The qualitative methodology described above [40–42] allowed the identification of the five criteria that teachers frequently use—consciously or unconsciously—within their teaching practice in large university courses. The criteria identified in their totality are methodological/ pedagogical and are presented from the highest degree of concurrence (22) to the minor (8).

**3.1. The ubiquitous interaction between student-teacher-student propitiates a better**

Communication seems to be a relevant factor in the learning experience of large courses. This communication, however, has a particularity. It is present at all times, everywhere and in various formats or devices. Teachers use various ways to be "always connected" with their students. In other words, it is to offer an "always available" training experience through various media and formats, beyond the formal classroom spaces. Some representative quotes were "*…I have a special mobile phone for my courses. There, I set up a Whatsapp®-volunteer group with my students from the beginning of the course. They ask me questions and I respond at any time of the day, wherever I am*"; "*Since I discovered Facebook® a few years ago, I set up a closed group where my students participate in a very natural way. It was a good experience. It is relevant to observe how students interact, often responding to their doubts among themselves*"; and "*…in my strategic communication course, I use a lot Twitter®, because it allows me to exemplify with everyday cases the contents of the course…the students participate by commenting, allowing me to make corrections about certain errors that they may be making in their analyses*". The use of communication technologies and social networks seems to be a great strategy to improve the interaction between teachers and their students. In this sense, the use of social

criteria of "low visual contact" between the teacher and the students [10].

164 New Pedagogical Challenges in the 21st Century - Contributions of Research in Education

tualization or theorization of the categories with greater concurrence began.

media or Web 2.0 has become an interesting resource for student learning.

**the process should be the north in classroom management**

**3.2. Dynamic decision-making based on student learning achievement throughout**

Size is not a sufficient justification for teachers to not orient their practice toward student learning outcomes. Most interviewees stated that they take short- and long-term measures when they do not achieve the syllabus objectives or in a particular activity or generation of evidence. In a way they empathize and take responsibility for the results that their students achieve, but above all, they manage to reorient their actions. In this context, the processes of feedback and

Each of the criteria was then reviewed and conceptualized.

**environment for learning**

Not always the topics of the course are liked by all students, especially in areas that may be more abstract and less motivating. A relevant fact is how teachers select and use examples and situations of contingency in order to promote motivation, linkage, and meaningfulness with the content or learning that is being intended in students. The above not only at an intellectual level but also at an emotional or empathic level with the situation being exemplified and its intrinsic link with learning. Some representative quotes were "*…in the day-to-day I am always looking for examples to use in my course. For me it is key to choose good examples not only able to cover the content that I am delivering, but also to engage students to learn*"; "*Students respond not just because they want to learn. They need to know how knowledge can be used in everyday life…*"; "*My students are not alien to reality and to the contingency…of what is happening around them. In one way or another, it affects their lives…so choosing good examples of reality will help them understand their environment and make learning meaningful…*"; "*When I start the course I realize that students are not able to relate contents to reality…it is as if they lived in parallel realities. When I gradually explain using everyday examples, they discover a new world and commit to the course. Hence, the importance I give in selecting good examples…*"; *and* "*Several years ago, in the evaluations that I applied in the course, rather than asking the students to answer questions, I gave them topics that they should exemplify, relate and analyze with facts of national and international contingency…it has given me very good results…*".

This represents better communication skills not only over the average of teachers but also in the effective and relevant selection of examples capable of linking students' motivation with the contents and learning of the course.

#### **3.4. Promotion in the generation of networks of support and collaboration intra- and extracurricular (both between students and teachers) favors the quality of learning**

Teachers use the positive effect of collaborative networks, both in and out of the course. Within the course, there are multiple actions, but some stand out, such as peer instruction, collaborative work, and projects, among other initiatives. In the case of courses that have more than one teacher, they generate actions of reciprocal collaboration with students in smaller groups, especially in learning experiences where they demand the resolution of professional challenges. Outside the course, teachers commonly promote collaboration with former students of the course or simple contact with professionals of the same or other disciplines, with the purpose of broadening the look beyond the course and the generation of networks that facilitate the initial labor insertion. Some representative quotes were "*The work done by the students through collaboration, both inside and outside the classroom, has been vital … I notice it when interacting in the social media of the course and when jointly solving the work that I request. I usually organize groups randomly and reconfigure them two or three times during the course. This way I assure they generate networks, collaborate and are able to cope with the course…*"; "*My class is in a large auditorium…and although it seems difficult, what I do most is instruction between peers. Even on some occasions, I have placed themselves in different positions inside the auditorium so that they rotate the work-groups … I see how students' motivation, engagement and achievement increases…*"; "*…at the end of each topic, I ask students to interview professionals from their own discipline to compare the contents of the course and to generate professional links that promote understanding of how to insert themselves in the professional context…this helps the students to be responsible with their own learning and collect experiences or situations to be shared during the class*"; *and* "*When my students understand and realize that we are a learning community during the course, there are really significant changes in their performance…it is interesting to see how their behavior changes and how they take more responsibility for learning, especially in moments that I make them interact with key stakeholders outside the course…*".

Active learning must be one of the central pillars in class planning in large courses. To make

Large Courses at Universities: Criteria for Teacher Action http://dx.doi.org/10.5772/intechopen.72674 167

All the criteria that have been identified in this chapter are possible to apply in small courses and are not exclusive to large group activities. So, what must be especially considered in

It seems to us that the relevance lies in when, where, and how the teaching and learning process is implemented and managed. Consequently, the problem is not in size, but in the choice of strategies to use and how they are managed in the classroom to raise the quality of learning

Another issue to be considered is related to the use of technologies and its usefulness to tackle large courses. Above all, the use of everyday applications or those easy to access—such as social media—can cause significant differences when developing environments that promote effective learning. It should be noted that technologies do not solve all the challenges that come with large courses, but they manage to solve a significant group of them, such as interaction, communication, and individual monitoring that can be developed with these tools.

First, it should be remembered that large courses are common in institutions of higher education. Therefore, before continuing to renege on the disadvantages and drawbacks of this real-

However, the role of educational research is vital, especially in the understanding of how to make these kinds of classes more effective, considering the current and future cultural characteristics of students who will enter higher education. Increasingly, the demands for quality education and teaching encourage us to have better and greater tools to meet this challenge. Finally, it is the task of the whole university community to face the challenge of making the classroom, the teaching, and the learning processes of the twenty-first century more meaningful in higher education. The problem is not the size of classes, but how we are supporting the current and future generation of students who attend our universities for a training that effectively prepares them to face their professional future and the challenges of society.

This work was supported by the National Commission for Science and Technology (CONICYT)

of the Chilean Ministry of Education, under Grant FONDECYT No. 11150794.

ity, it is necessary to innovate on how it is possible to better assume this challenge.

learning happen, the student must do more than just listen to the teacher.

classes where the size becomes more of a problem than a challenge to be faced?

**4. Conclusions**

in the vast majority of students.

**5. Final thoughts**

**Acknowledgements**

As part of any course, the interaction between students, through various methodologies or extracurricular activities, must be planned and strengthened, in order to positively impact their learning.

#### **3.5. Promotion of permanent cognitive participation of students during class improves achievement in learning**

Beyond the course size, these teachers permanently ask their students' involvement and not just to attend as passive listeners. Usually, they ask students small but permanent actions that imply them to respond, think, propose, or elaborate, which is manifested in some type of evidence or learning product. These actions are permanently generated within the same class session and throughout the period in which the course is dictated. This is based on the perception of these teachers in maintaining students' attention as long as possible, which leads to better results. Some representative quotes were "*…or via clickers or One Minute Paper session-by-session, I have my students constantly mobilizing what we review in class, otherwise, what purpose has that they just sit and listen?…*"; "*In several sessions I use Flipped Classroom. Therefore, they already know that they must come to classes to apply or to solve exercises that will be part of their assessment. Many times I also do it to integrate several contents. The idea is that they are in constantly aware and attentive to learn…*"; *and* "*The traditional idea of going to class to sit and listen simply does not respond to the current needs in the development of skills. By having a large group of courses, I want to involve the vast majority of students, and not everyone can speak at the same time. That's why I integrate activities where they have to connect with what I expose in classes…*".

Active learning must be one of the central pillars in class planning in large courses. To make learning happen, the student must do more than just listen to the teacher.