Biology subjects

Kaminski Schierle, G. S.

Publications and source records attributed to Kaminski Schierle, G. S..

At least 19 recordsLinked to original sources

bioRxiv2026

A Dual-Gate OECT Platform for Drift-Suppressed and High-Sensitivity Real-Time Biosensing

Organic electrochemical transistors (OECTs) enable high transconductance at low operating voltages through the volumetric charging of organic mixed ionic/electronic conductors (OMIECs), making them attractive transducers for biosensing. However, the same ionic -electronic coupling makes OMIECs, such as poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) (PEDOT:PSS), sensitive to different ions and various environmental fluctuations, so drift and memory effects may compromise the quantitative readout in complex biofluids. In this work, we introduce a novel OECT-based sensor configuration that minimises drift by addressing a single channel with two gates: a functionalised sensing gate and a reference gate that allows real-time decoupling of environmental and channel-state fluctuations. A pulsed gate-biasing protocol is introduced to promote channel conductivity recovery and mitigate state accumulation. Using enzymatic glucose sensing as a proof of concept, the platform suppresses time-dependent drift by ~96%, eliminates temperature-induced variations up to 99% across the 20-70 {degrees}C range, improves calibrated sensitivity by 55% and reduces interferent-induced deviations under physiologically relevant conditions. By improving both signal stability and analytical reliability, this strategy addresses a central limitation of OECT biosensors and advances their use in high-sensitivity point-of-care biosensing in complex biological environments.

bioengineering↗

bioRxiv2026

α-Synuclein Facilitates Spontaneous Dopamine Release in a Calcium- and Phosphorylation-Dependent Manner

-Synuclein (aSyn) is central to Parkinsons disease pathogenesis, yet its native physiological role at the presynapse remain poorly defined. Here, super-resolution imaging in dopaminergic neurons reveals that endogenous aSyn localises within nanometres of L-type voltage-gated calcium channels (LTCC), with closer proximity under both spontaneous neuronal activity and stimulated conditions compared to when extracellular calcium is chelated. Blocking Ca2+/calmodulin-dependent kinase II (CaMKII) reduces aSyn clustering at LTCC under spontaneous activity, suggesting that calcium entry and downstream calcium-dependent kinase activity contribute to aSyn localisation. Moreover, quantitative single-molecule analyses indicate that calcium increases the abundance of both total and serine129 phosphorylated (pS129) aSyn in synaptosomes under spontaneous conditions, and NMR analysis reveals that both calcium and S129 phosphorylation increase the binding affinity of aSyn to synaptic vesicles. Functional assays further demonstrate that LTCC blockade elevates intracellular DA levels exclusively in the presence of aSyn under spontaneous but not stimulated conditions. Finally, biochemical fractionation and multi-colour single-molecule imaging reveal that aSyn preferentially associates with small vesicles that are not obligately coupled to full-fusion associated recycling pools. These results suggest that aSyn acts as a calcium- and phosphorylation-regulated modulator of spontaneous DA release through pathways that are largely independent of full-fusion recycling mechanisms, and that pS129 aSyn is not solely a pathological marker but may also reflects physiological regulation. Together, these insights provide a framework for understanding how therapeutic strategies targeting aSyn may impact its normal synaptic functions.

neuroscience↗

bioRxiv2026

Spatially Integrated Multi-Omics reveals the Multicellular Landscape of Progenitor-Driven Glioblastoma Progression

Glioblastoma is the most lethal primary brain tumor, driven by complex interactions between plastic malignant cells and a diverse tumor microenvironment. Despite advances in single-cell profiling, how genomic drivers and the tumor microenvironment interact to determine tumor progression and patient survival remains poorly understood. While cellular states have been cataloged, the multi-cellular logic coordinating these into lethal phenotypes remains unresolved. Here, we integrate whole-exome sequencing, bulk and single-cell RNA sequencing, spatial transcriptomics, and histopathology from the MOSAIC cohort (n = 89) to deconstruct this inter- and intra-tumoral heterogeneity. We identify a robust latent multi-omic program in glioblastoma that delineates a transition from homeostatic neural precursors to an aggressive, immunosuppressive progenitor phenotype. This high-risk state, which predicts poor survival in both the MOSAIC discovery and independent validation cohorts (TCGA, CGGA; total n = 598), is sustained by dense intercellular communication networks linking malignant progenitors with myeloid and endothelial compartments. Spatially, this program maps to hypoxic, perinecrotic niches, directly linking molecular signaling with microvascular proliferation and tissue necrosis. Our findings provide a spatially resolved, multi-omic blueprint of the multicellular logic driving glioblastoma progression, offering a robust molecular framework for patient stratification and targeted intervention.

cancer biology↗

bioRxiv2026

Discovery of TDP-43 aggregation inhibitors via a hybrid machine learning framework

TAR DNA-binding protein 43 (TDP-43) aggregation is a hallmark of several neurodegenerative diseases, including amyotrophic lateral sclerosis and frontotemporal dementia. Recent therapeutic efforts have highlighted the potential of small molecules capable of inhibiting TDP-43 aggregation; however, no effective treatments currently exist. Here, we developed a hybrid machine learning approach combining graph neural network (GNN) embeddings with traditional chemical descriptors and biological target annotations. Using XGBoost as the final classifier enabled model interpretability through SHAP analysis, allowing the identification of key chemical features and target annotations associated with TDP-43 anti-aggregation activity. Complementary Monte Carlo Tree Search analysis highlighted specific chemical substructures linked to predicted activity. By screening an external library of 3,853 small molecules, the model identified two compounds not previously evaluated against TDP-43 aggregation, namely berberrubine and PE859. Molecular docking analysis revealed that both compounds interact favourably with the TDP-43 RNA recognition motif (RRM) domain through distinct binding modes. Experimental validation showed that both compounds significantly reduced TDP-43 aggregation in HEK cells. Further testing in Caenorhabditis elegans expressing human TDP-43 demonstrated that PE859 significantly rescued locomotor defects, while berberrubine showed partial improvement. This work establishes a hybrid machine learning approach for accelerating small molecule drug discovery, yielding two promising therapeutic candidates for TDP-43 proteinopathies.

bioinformatics↗

bioRxiv2025

Impairment of neuronal activity occurs at the early stages of the aggregation cascade of Ab1-42 and mutant Tau

Alzheimers disease (AD) is a progressive neurodegenerative disease that is characterized by the accumulation of amyloid-{beta} (A{beta}) plaques and neurofibrillary Tau tangles, ultimately leading to brain atrophy and death. To elucidate the relationship between the aberrant folding and aggregation of A{beta} and mutant Tau and neuronal function, we monitored neuronal activity in C. elegans AD models across age. Our findings reveal that expression of both A{beta} and Tau lead to significant reductions in neuronal activity and function in young adult animals preceding the accumulation of amyloid aggregates. Notably, A{beta} expression and aggregation in muscle tissue produced comparable detrimental effects on neuronal activity as its expression in neurons, suggesting that proteotoxic stress in muscle can influence neuronal function. This may occur through the propagation of A{beta} from muscle to neurons or through retrograde signaling pathways. Further, our new sub-stoichiometrically labeled Tau strains highlight that TauP301L,V337M has a significant impact on neuronal activity throughout aging. These results enhance our understanding of the early functional effects of amyloid aggregation in Alzheimers disease.

neuroscience↗

bioRxiv2025

Brain cholesterol metabolites cause significant neurodegeneration in human iPSC-derived neurons

Disrupted cholesterol metabolism is increasingly recognised as a contributing factor in neurodegeneration; however, the specific effects of key brain-derived cholesterol metabolites, 24S-hydroxycholesterol (24S-HC) and 27-hydroxycholesterol (27-HC), remain poorly understood. Using human iPSC-derived i3 cortical neurons, we demonstrate that both 24S-HC and 27-HC significantly impair neuronal calcium signalling by elevating resting calcium levels, reducing spike amplitude, and disrupting network synchrony. These functional deficits are accompanied by widespread organelle dysfunction. Both oxysterols induce mitochondrial fragmentation, decrease spare respiratory capacity, and impair lysosomal degradation. Notably, 27-HC uniquely triggers lysosomal swelling and membrane permeabilisation. Additional signs of cellular stress, including axonal swellings and elevated endoplasmic reticulum calcium levels, were also observed. Furthermore, both 24S-HC and 27-HC were found to directly interact with alpha-synuclein (aSyn), promoting its accumulation in cellular models. In contrast, cholesterol itself had minimal impact, highlighting the distinct toxicity of its hydroxylated metabolites. Together, these findings reveal a mechanistic link between oxysterol accumulation and neuronal dysfunction, supporting the hypothesis that elevated levels of 24S-HC and 27-HC, commonly observed in Parkinsons and Alzheimers disease, may actively drive neurodegenerative processes. Targeting oxysterol metabolism may therefore represent a promising therapeutic avenue for intervention in neurodegenerative disorders.

neuroscience↗

bioRxiv2025

Deep learning for fluorescence lifetime predictions enables high-throughput in vivo imaging

Fluorescence lifetime imaging microscopy (FLIM) is a powerful optical tool widely used in biomedical research to study changes in a samples microenvironment. However, data collection and interpretation are often challenging, and traditional methods such as exponential fitting and phasor plot analysis require a high number of photons per pixel for reliably measuring the fluorescence lifetime of a fluorophore. To satisfy this requirement, prolonged data acquisition times are needed, which makes FLIM a low-throughput technique with limited capability for in vivo applications. Here, we introduce FLIMngo, a deep learning model capable of quantifying FLIM data obtained from photon-starved environments. FLIMngo outperforms other deep learning approaches and phasor plot analyses, yielding accurate fluorescence lifetime predictions from decay curves obtained with fewer than 50 photons per pixel by leveraging both time and spatial information present in raw FLIM data. Thus, FLIMngo reduces FLIM data acquisition times to a few seconds, thereby, lowering phototoxicity related to prolonged light exposure and turning FLIM into a higher throughput tool suitable for analysis of live specimens. Following the characterisation and benchmarking of FLIMngo on simulated data, we highlight its capabilities through applications in live, dynamic samples. Examples include the quantification of disease-related protein aggregates in non-anaesthetised Caenorhabditis (C.) elegans, which significantly improves the applicability of FLIM by opening avenues to continuously assess C. elegans throughout their lifespan. Finally, FLIMngo is open-sourced and can be easily implemented across systems without the need for model retraining.

biophysics↗

bioRxiv2025

Using a stable protein scaffold to display peptides that bind to alpha-synuclein fibrils

Amyloid fibrils are ordered aggregates that are a pathological hallmark of many neurodegenerative disorders including Alzheimers Disease and Parkinsons Disease. The process of amyloid formation involves a complex cascade by which soluble monomeric protein converts to insoluble, ordered aggregates (amyloid fibrils). Although inhibiting the aggregation pathway is a key target for therapeutic development, the heterogeneous collection of aggregation-prone species formed in this process, including oligomers, protofibrils and fibrils, represent other targets for modifying disease pathology. Developing molecules that can bind to amyloid fibrils and potentially disrupt the harmful interactions between the fibrils and the cellular components would be advantageous. Designing peptide modulators for -synuclein aggregation is of great interest, however effective inhibitory peptides are often hydrophobic and hence difficult to handle; therefore, developing strategies to display these peptides in a soluble scaffold would be very beneficial. Here we demonstrate that the ultra-stable consensus-designed tetratricopeptide repeat (CTPR) protein scaffold can be grafted with "KLVFF" derived peptides previously identified to inhibit protein aggregation and interact with amyloid fibrils, to produce proteins that bind along the surface of -synuclein fibrils with micromolar affinity. Given the ability to insert hydrophobic peptides to produce soluble, CTPR-based binders, this method may prove beneficial in screening for peptide modulators of protein aggregation. Short statementConsensus-designed tetratricopeptide repeat (CTPR) proteins can be endowed with additional functionality including specific client recruitment. Here we created stable, soluble CTPR-based binders that recognise -synuclein fibrils with micromolar affinity. The CTPR scaffold provides a facile way to test potential fibril-binding or aggregation-modulating peptides and to probe their mechanisms of action.

biochemistry↗

bioRxiv2024

FLIMPA: A versatile software for Fluorescence Lifetime Imaging Microscopy Phasor Analysis

Fluorescence lifetime imaging microscopy (FLIM) is an advanced microscopy technique capable of providing a deeper understanding of the molecular environment of a fluorophore. While FLIM data were traditionally analysed through the exponential fitting of the fluorophores emission decays, the use of phasor plots is increasingly becoming the preferred standard. This is due to their ability to visualise the distribution of fluorescent lifetimes within a sample, offering insights into molecular interactions in the sample without the need for model assumptions regarding the exponential decay behaviour of the fluorophores. However, so far most researchers have had to rely on commercial phasor plot software packages, which are closed-source and rely on proprietary data formats. In this paper, we introduce FLIMPA, an opensource, stand-alone software for phasor plot analysis that provides many of the features found in commercial software, and more. FLIMPA is fully developed in Python and offers advanced tools for data analysis and visualisation. It enhances FLIM data comparison by integrating phasor points from multiple trials and experimental conditions into a single plot, while also providing the possibility to explore detailed, localised insights within individual samples. We apply FLIMPA to introduce a cell-based assay for the quantification of microtubule depolymerisation, measured through fluorescence lifetime changes of SiR-tubulin, in response to various concentrations of Nocodazole, a microtubule depolymerising drug relevant to anti-cancer treatment.

biophysics↗

bioRxiv2024

Graphene microelectrode arrays, 4D structured illumination microscopy, and a machine learning-based spike sorting algorithm permit the analysis of ultrastructural neuronal changes during neuronal signalling in a model of Niemann-Pick disease type C

Simultaneously recording network activity and ultrastructural changes of the synapse is essential for advancing our understanding of the basis of neuronal functions. However, the rapid millisecond-scale fluctuations in neuronal activity and the subtle sub-diffraction resolution changes of synaptic morphology pose significant challenges to this endeavour. Here, we use graphene microelectrode arrays (G-MEAs) to address these challenges, as they are compatible with high spatial resolution imaging across various scales as well as high temporal resolution electrophysiological recordings. Furthermore, alongside G-MEAs, we deploy an easy-to-implement machine learning-based algorithm to efficiently process the large datasets collected from MEA recordings. We demonstrate that the combined use of G-MEAs, machine learning (ML)-based spike analysis, and four-dimensional (4D) structured illumination microscopy (SIM) enables the monitoring of the impact of disease progression on hippocampal neurons which have been treated with an intracellular cholesterol transport inhibitor mimicking Niemann-Pick disease type C (NPC) and show that synaptic boutons, compared to untreated controls, significantly increase in size, which leads to a loss in neuronal signalling capacity.

neuroscience↗

bioRxiv2023

Molecular mechanisms of liposome interactions with bacterial envelopes

Although fusogenic liposomes offer a promising approach for the delivery of antibiotic payloads across the cell envelope of Gram-negative bacteria, there is still limited understanding of the individual nanocarrier interactions with the bacterial target. Using super-resolution microscopy, we characterize the interaction dynamics of positively charged fusogenic liposomes with Gram-negative (Escherichia coli) and Gram-positive (Bacillus subtilis) bacteria. The liposomes merge with the outer membrane (OM) of Gram-negative bacteria, while attachment or lipid internalization is observed in Gram-positive cells. Employing total internal reflection fluorescence microscopy, we demonstrated liposome fusion with model supported lipid bilayers. For whole E. coli cells, however, we observed heterogeneous membrane integrations, primarily involving liposome attachment and hemifusion events. With increasing lipopolysaccharide length the likelihood of full-fusion events was reduced. The integration of artificial lipids into the OM of Gram-negative cells led to membrane destabilization, resulting in decreased bacterial vitality, membrane detachment, and improved co-delivery of Vancomycin--an effective antibiotic against Gram-positive cells. These findings provide significant insights into the interactions of individual nanocarriers with bacterial envelopes at the single-cell level, uncovering effects that would be missed in bulk measurements. This highlights the importance of conducting single-particle and single-cell investigations to assess the performance of next-generation drug delivery platforms.

biophysics↗

bioRxiv2022

Mutation of the ALS/FTD-associated RNA-binding protein FUS alters axonal cytoskeletal organisation

Aberrant condensation and localisation of the RNA-binding protein fused in sarcoma (FUS) occur in variants of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). ALS is also associated with cytoskeletal defects, genetically and through observations of compromised axonal transport. Here, we asked whether compromised axonal cytoskeletal organisation is an early feature of FUS-associated ALS/FTD. We used an ALS-associated mutant FUS(P525L) and the FTD-mimic hypomethylated FUS, FUS(16R), to investigate the common and distinct cytoskeletal changes found in these two reported Xenopus models. Combining a novel atomic force microscopy (AFM)-based approach for in vitro cytoskeletal characterisation and in vivo axonal branching analysis, we found that mutant FUS reduced actin density in the dynamically remodelling growth cone, and reduced axonal branch complexity. We furthermore found evidence of an axon looping defect for FUS(P525L). Therefore, we show that compromised actin remodelling is potentially an important early event in FUS-associated pathogenesis. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/510780v2_ufig1.gif" ALT="Figure 1"> View larger version (56K): org.highwire.dtl.DTLVardef@1e9a92aorg.highwire.dtl.DTLVardef@161076eorg.highwire.dtl.DTLVardef@12edf0forg.highwire.dtl.DTLVardef@365785_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2022

Intracellular FUS protein accumulation leads to cytoskeletal, organelle and cellular homeostasis perturbations

The molecular mechanisms that connect the formation of aberrant cytoplasmic FUS condensates to biological malfunction are incompletely understood. Here, we develop an approach to determine the intracellular FUS viscosity in live mammalian cells and find that ALS-related mutant P525L-FUS forms the most viscous condensates and has impaired cytoskeletal mechanoproperties and increased euchromatin formation. We further show that some of the main cellular organelles, e.g., actin/tubulin, lysosomes, mitochondria, the endoplasmic reticulum, are significantly functionally/structurally impaired in the presence of FUS. These may be related to defects in the tubulin network, as the latter facilitates transport, formation, fusion and fission of organelles. We observe significant increases in lysosomal biogenesis, size and pH; moreover, intracellular FUS accumulation significantly promotes cytoplasmic-to-nuclear translocation of TFEB, i.e., the master gene for inducing autophagy. However, despite these, increased autophagy needed for protein aggregate clearance is not observed to occur. Our study reveals that the formation of highly viscous FUS condensates significantly impacts cytoskeletal/organelle function and cellular homeostasis, which are closely associated with cell ageing. This raises the intriguing question as to whether mutant FUS activates similar cell processes as those during cellular senescence.

biophysics↗

bioRxiv2022

ERnet: a tool for the semantic segmentation and quantitative analysis of endoplasmic reticulum topology for video-rate super-resolution imaging

The topology of endoplasmic reticulum (ER) network is highly regulated by various cellular and environmental stimuli and affects major functions such as protein quality control and the cells response to metabolic changes. The ability to quantify the dynamical changes of the ER structures in response to cellular perturbations is crucial for the development of novel therapeutic approaches against ER associated diseases, such as hereditary spastic paraplegias and Niemann Pick Disease type C. However, the rapid movement and small spatial dimension of ER networks make this task challenging. Here, we combine video-rate super-resolution imaging with a state-of-the-art semantic segmentation method capable of automatically classifying sheet and tubular ER domains inside individual cells. Data are skeletonised and represented by connectivity graphs to enable the precise and efficient quantification and comparison of the network connectivity from different complex ER phenotypes. The method, called ERnet, is powered by a Vision Transformer architecture, and integrates multi-head self-attention and channel attention into the model for adaptive weighting of frames in the time domain. We validated the performance of ERnet by measuring different ER morphology changes in response to genetic or metabolic manipulations. Finally, as a means to test the applicability and versatility of ERnet, we showed that ERnet can be applied to images from different cell types and also taken from different imaging setups. Our method can be deployed in an automatic, high-throughput, and unbiased fashion to identify subtle changes in cellular phenotypes that can be used as potential diagnostics for propensity to ER mediated disease, for disease progression, and for response to therapy.

bioengineering↗

bioRxiv2022

Intracellular Aβ42 aggregation leads to cellular thermogenesis

The aggregation of A{beta}42 is a hallmark of Alzheimers disease. It is still not known what the biochemical changes are inside a cell which will eventually lead to A{beta}42 aggregation. Thermogenesis has been associated with cellular stress, the latter of which may promote aggregation. We perform intracellular thermometry measurements using fluorescent polymeric thermometers (FPTs) to show that A{beta}42 aggregation in live cells leads to an increase in cell-averaged temperatures. This rise in temperature is mitigated upon treatment with an aggregation inhibitor of A{beta}42 and is independent of mitochondrial damage that can otherwise lead to thermogenesis. With this, we present a diagnostic assay which could be used to screen small-molecule inhibitors to amyloid proteins in physiologically relevant settings. To interpret our experimental observations and motivate the development of future models, we perform classical molecular dynamics of model A{beta} peptides to examine the factors that hinder thermal disspation. We observe that this is controlled by the presence of ions in its surrounding environment, the morphology of the amyloid peptides and the extent of its hydrogen-bonding interactions with water. We show that aggregation and heat retention by A{beta} peptides are favoured under intracellular-mimicking ionic conditions, which could potentially promote thermogenesis. The latter will, in turn, trigger further nucleation events that accelerate disease progression.

biophysics↗

bioRxiv2022

A unified in vitro to in vivo fluorescence lifetime screening platform yields amyloid β aggregation inhibitors

Inhibiting the aggregation of amyloid {beta} (1-42) is a promising strategy for the development of disease-modifying Alzheimers disease therapeutics. To date, however, no sufficiently efficacious inhibitors have been identified, despite the best efforts of >200 advanced drug development campaigns. This failure can be attributed to limitations in current compound screening and in vivo validation assays. Here, we report an in vitro to in vivo screening platform based on the use of a fluorescence lifetime aggregation sensor. The microfluidic "nanoFLIM" assay developed circumvents issues that plague conventional assays, such as lack of reproducibility, high cost and artefactual false read-outs. The fluorescence lifetime sensor can also dynamically monitor peptide aggregation in cellular and Caenorhabditis elegans disease models, providing directly comparable aggregation kinetics, which is not achievable by any other method. The power of this unified system for accelerating hit-to-lead strategies, lowering attrition rates and expediting in vivo screening, was demonstrated with a pilot screening campaign of 445 compounds, revealing a new inhibitor that can inhibit amyloid {beta} self-assembly in vitro as well as in cellular and whole organism disease models.

molecular biology↗

bioRxiv2022

Local structural dynamics of alpha-synuclein correlate with aggregation in different physiological conditions

In Parkinsons disease and other synucleinopathies, the intrinsically disordered, presynaptic protein alpha-synuclein misfolds and aggregates. We hypothesise that the exposure of alpha-synuclein to different cellular environments, with different chemical compositions, pH and binding partners, alters its biological and pathological function by inducing changes in molecular conformation. Our custom instrumentation and software enable measurement of the amide hydrogen exchange rates of wild-type alpha-synuclein at amino acid resolution under physiological conditions, mimicking those in the extracellular, intracellular, and lysosomal compartments of cells. We characterised the aggregation kinetics and morphology of the resulting fibrils and correlate these with structural changes in the monomer. Our findings reveal that the C-terminal residues of alpha-synuclein are driving its nucleation and thus its aggregation. Furthermore, the entire NAC region and specific other residues strongly promoted elongation of fibrils. This provides new detail on our current understanding of the relationship between the local chemical environment and monomeric conformations of alpha-synuclein.

molecular biology↗

bioRxiv2021

Label-free characterisation of amyloids and alpha-Synuclein polymorphs by exploiting their intrinsic fluorescence property

Conventional in vitro aggregation assays often involve tagging with extrinsic fluorophores which can interfere with aggregation. We propose the use of intrinsic amyloid fluorescence lifetime probed using two-photon excitation and represented by model-free phasor plots, as a label-free assay to characterise amyloid structure. Intrinsic amyloid fluorescence arises from structured packing of {beta}-sheets in amyloids and is independent of aromatic-based fluorescence. We show that different amyloids (i.e., -Synuclein (S), {beta}-Lactoglobulin and TasA) and different polymorphic populations of S (induced by aggregation in salt-free and salt buffers mimicking the intra-/extracellular environments) can be differentiated by their unique fluorescence lifetimes. Moreover, we observe that disaggregation of pre-formed fibrils of S and {beta}LG leads to increased fluorescence lifetimes, distinct to those of their fibrillar counterpart. Our assay presents a medium-throughput method for rapid classification of amyloids and their polymorphs (the latter of which recent studies have shown lead to different disease pathology), and for testing small molecule inhibitory compounds.

molecular biology↗