bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamic Regulation of Vesicle Pools in a Detailed Spatial Model of the Complete Synaptic Vesicle Cycle
Authors: Gallimore Andrew R. , Hepburn Iain , Rizzoli Silvio , Schutter Erik De 
Published: August 2023

AbstractSynaptic transmission is driven by a complex cycle of synaptic vesicle docking, release, and recycling, and maintained by distinct vesicle pools with differing propensities for docking and release. However, the partitioning of vesicles into distinct pools and the conditions under which they are recruited from the reserve to the recycling pool remain poorly understood. Whilst computational modeling at the molecular level has progressed massively in recent years, modeling voluminous, dynamic, and heterogenous structures such as synaptic vesicles remains an unsolved problem. Here, we use a novel vesicle modeling technology to model the complete synaptic vesicle cycle in unprecedented molecular and spatial detail at a hippocampal en passant synapse, incorporating vesicle diffusion, the accumulation and diffusion of proteins on the vesicle surface, vesicle clustering, tethering, and docking, and regulated vesicle fusion and recycling. Our model demonstrates highly dynamic and robust recycling of synaptic vesicles able to maintain stable and consistent synaptic release over time, even during high frequency and sustained firing. We also reveal how the cytosolic proteins synapsin-1 and tomosyn-1 can cooperate to regulate the recruitment of vesicles from the reserve pool during sustained periods of synaptic activity in order to maintain transmission, as well as the potential of selective vesicle tethering close to the active zone to ensure rapid vesicle replenishment and enhance the efficiency of the vesicle cycle by minimizing the recruitment of vesicles from the reserve pool.
SpaRx: Elucidate single-cell spatial heterogeneity of drug responses for personalized treatment
Authors: Tang Ziyang , Liu Xiang , Li Zuotian , Zhang Tonglin , Yang Baijian , Su Jing , Song Qianqian 
Published: August 2023

ABSTRACTSpatial cellular heterogeneity contributes to differential drug responses in a tumor lesion and potential therapeutic resistance. Recent emerging spatial technologies such as CosMx SMI, MERSCOPE, and Xenium delineate the spatial gene expression patterns at the single cell resolution. This provides unprecedented opportunities to identify spatially localized cellular resistance and to optimize the treatment for individual patients. In this work, we present a graph-based domain adaptation model, SpaRx, to reveal the heterogeneity of spatial cellular response to drugs. SpaRx transfers the knowledge from pharmacogenomics profiles to single-cell spatial transcriptomics data, through hybrid learning with dynamic adversarial adaption. Comprehensive benchmarking demonstrates the superior and robust performance of SpaRx at different dropout rates, noise levels, and transcriptomics coverage. Further application of SpaRx to the state-of-art single-cell spatial transcriptomics data reveals that tumor cells in different locations of a tumor lesion present heterogenous sensitivity or resistance to drugs. Moreover, resistant tumor cells interact with themselves or the surrounding constituents to form an ecosystem for drug resistance. Collectively, SpaRx characterizes the spatial therapeutic variability, unveils the molecular mechanisms underpinning drug resistance, and identifies personalized drug targets and effective drug combinations.Key PointsWe have developed a novel graph-based domain adaption model named SpaRx, to reveal the heterogeneity of spatial cellular response to different types of drugs, which bridges the gap between pharmacogenomics knowledgebase and single-cell spatial transcriptomics data.SpaRx is developed tailored for single-cell spatial transcriptomics data and is provided available as a ready-to-use open-source software, which demonstrates high accuracy and robust performance.SpaRx uncovers that tumor cells located in different areas within tumor lesion exhibit varying levels of sensitivity or resistance to drugs. Moreover, SpaRx reveals that tumor cells interact with themselves and the surrounding microenvironment to form an ecosystem capable of drug resistance.
Revealing Shared Proteins and Pathways in Cardiovascular and Cognitive Diseases Using Protein Interaction Network Analysis
Authors: Zeylan Melisa E. , Senyuz Simge , Picón-Pagès Pol , García-Elías Anna , Tajes Marta , Muñoz Francisco J. , Oliva Baldo , Garcia-Ojalvo Jordi , Barbu Eduard , Vicente Raul , Nattel Stanley , Ois-Santiago Angel J. , Puig-Pijoan Albert , Keskin Ozlem , Gursoy Attila 
Published: August 2023

AbstractOne of the primary goals of systems medicine is detecting putative proteins and pathways involved in disease progression and pathological phenotypes. Vascular Cognitive Impairment (VCI) is a heterogeneous condition manifesting as cognitive impairment resulting from vascular factors. The precise mechanisms underlying this relationship remain unclear, which poses challenges for experimental research. Here, we applied computational approaches like systems biology to unveil and select relevant proteins and pathways related to VCI by studying the crosstalk between cardiovascular and cognitive diseases. In addition, we specifically included signals related to oxidative stress, a common etiologic factor tightly linked to aging, a major determinant of VCI. Our results show that pathways associated with oxidative stress are quite relevant, as most of the prioritized vascular-cognitive genes/proteins were enriched in these pathways. Our analysis provided a short list of proteins that could be contributing to VCI: DOLK, TSC1, ATP1A1, MAPK14, YWHAZ, CREB3, HSPB1, PRDX6, and LMNA. Moreover, our experimental results suggest a high implication of glycative stress, generating oxidative processes and post-translational protein modifications through advanced glycation end-products (AGEs). We propose that these products interact with their specific receptors (RAGE) and Notch signaling to contribute to the etiology of VCI.
Phenotype-based targeted treatment of SGLT2 inhibitors and GLP-1 receptor agonists in type 2 diabetes
Authors: Cardoso Pedro , Young Katie G. , Nair Anand T.N. , Hopkins Rhian , McGovern Andrew P , Haider Eram , Karunaratne Piyumanga , Donnelly Louise , Mateen Bilal A. , Sattar Naveed , Holman Rury R. , Bowden Jack , Hattersley Andrew T. , Pearson Ewan R. , Jones Angus G. , Shields Beverley M. , McKinley Trevelyan J. , Dennis John M. 
Published: August 2023

AbstractA precision medicine approach in type 2 diabetes (T2D) could enhance targeting specific glucose-lowering therapies to individual patients most likely to benefit. We utilised Bayesian non-parametric modelling to develop and validate an individualised treatment selection algorithm for two major T2D drug classes, SGLT2-inhibitors (SGLT2i) and GLP1-receptor agonists (GLP1-RA). The algorithm is designed to predict differences in 12-month glycaemic outcome (HbA1c) between the 2 therapies, based on routine clinical features of 46,394 people with T2D in England (27,319 for model development, 19,075 for hold-out validation), with additional external validation in 2,252 people with T2D from Scotland. Routine clinical features, including sex (with females markedly more responsive to GLP1-RA), were associated with differences in glycaemic outcomes. Our algorithm identifies clearly delineable subgroups with reproducible ≥5mmol/mol HbA1cbenefits associated with each drug class. Moreover, we demonstrate that targeting the therapies based on predicted glycaemic response is associated with improvements in short-term tolerability and long-term risk of new-onset microvascular complications. These results show that precision medicine approaches to T2D can facilitate effective individualised treatment selection, and that use of routinely collected clinical features could support low-cost deployment in many countries.
Exploring pleiotropy in Mendelian randomisation analyses: What are genetic variants associated with “cigarette smoking initiation” really capturing?
Authors: Reed Zoe E. , Wootton Robyn E. , Khouja Jasmine N. , Richardson Tom G. , Sanderson Eleanor , Smith George Davey , Munafò Marcus R 
Published: August 2023

AbstractBackgroundGenetic variants used as instruments for exposures in Mendelian randomisation (MR) analyses may also have horizontal pleiotropic effects (i.e., influence outcomes via pathways other than through the exposure), which can undermine the validity of results. We examined the extent to which horizontal pleiotropy may be present, using smoking behaviours as an example.MethodsWe first ran a phenome-wide association study in UK Biobank, using a genetic instrument for smoking initiation. From the most strongly associated phenotypes, we selected those that we considered could either plausibly or not plausibly be caused by smoking. We next examined the association between genetic instruments for smoking initiation, smoking heaviness and lifetime smoking and these phenotypes in both UK Biobank and the Avon Longitudinal Study of Parents and Children (ALSPAC). We conducted negative control analyses among never smokers, including children in ALSPAC.ResultsWe found evidence that smoking-related genetic instruments (mainly for smoking initiation and lifetime smoking) were associated with phenotypes not plausibly caused by smoking in UK Biobank and (to a lesser extent) ALSPAC, although this may reflect the much smaller sample size in ALSPAC. We also observed associations with several phenotypes among never smokers.ConclusionOur results suggest that genetic instruments for smoking-related phenotypes demonstrate horizontal pleiotropy. When using genetic variants – particularly those for complex behavioural exposures – in genetically-informed causal inference analyses (e.g., MR) it is important to include negative control outcomes where possible, and other triangulation approaches, to avoid arriving at incorrect conclusions.
Recent UK type 2 diabetes treatment guidance represents a near whole population indication for SGLT2-inhibitor therapy
Authors: Young Katherine G , Hopkins Rhian , Shields Beverley M , Thomas Nicholas J , McGovern Andrew P , Dennis John M 
Published: August 2023

AbstractRecent type 2 diabetes guidance from the UK’s National Institute for Health and Care Excellence (NICE) proposes offering SGLT2-inhibitor therapy to people with established atherosclerotic cardiovascular disease (ASCVD) or heart failure, or at high-risk of cardiovascular disease defined as a 10-year cardiovascular risk of >10% using the QRISK2 algorithm.We used a contemporary population-representative UK cohort of people with type 2 diabetes to assess the implications of this guidance. 93.1% of people currently on anti-hyperglycaemic treatment are now recommended or considered for SGLT2-inhibitor therapy, with the majority (59.6%) eligible on the basis of QRISK2 rather than established ASCVD or heart failure (33.6%). Applying these results to the approximately 2.20 million people in England currently on anti-hyperglycaemic medication suggests 1.75 million people will now be considered for additional SGLT2-inhibitor therapy.Given older people, those of non-white ethnic groups, and those at lower cardiovascular disease risk were underrepresented in the clinical trials upon which this guidance was based, careful evaluation of the impact and safety of increased SGLT2-inhibitor prescribing across different populations is urgently required. Evidence of benefit should be weighed against the major cost implications for the NHS.
Efficient and accurate sequence generation with small-scale protein language models
Authors: Serrano Yaiza , Roda Sergi , Guallar Victor , Molina Alexis 
Published: August 2023

Large Language Models (LLMs) have demonstrated exceptional capabilities in understanding contextual relationships, outperforming traditional methodologies in downstream tasks such as text generation and sentence classification. This success has been mirrored in the realm of protein language models (pLMs), where proteins are encoded as text via their amino acid sequences. However, the training of pLMs, which involves tens to hundreds of millions of sequences and hundreds of millions to billions of parameters, poses a significant computational challenge.In this study, we introduce a Small-Scale Protein Language Model (SS-pLM), a more accessible approach that requires training on merely millions of representative sequences, reducing the number of trainable parameters to 14.8M. This model significantly reduces the computational load, thereby democratizing the use of foundational models in protein studies. We demonstrate that the performance of our model, when fine-tuned to a specific set of sequences for generation, is comparable to that of larger, more computationally demanding pLM.
Molecular modeling of apoE in complexes with Alzheimer’s amyloid-β fibrils from human brain suggests a structural basis for apolipoprotein co-deposition with amyloids
Authors: Lewkowicz Emily , Nakamura Mari N. , Rynkiewicz Michael J. , Gursky Olga 
Published: August 2023

ABSTRACTApolipoproteins co-deposit with amyloids, yet apolipoprotein-amyloid interactions are enigmatic. To understand how apoE interacts with Alzheimer’s amyloid-β(Aβ) peptide in fibrillary deposits, the NMR structure of full-length human apoE was docked to four structures of patient-derived Aβ1-40and Aβ1-42fibrils determined previously using cryo-electron microscopy or solid-state NMR. Similar docking was done using the NMR structure of human apoC-III. In all complexes, conformational changes in apolipoproteins were required to expose large hydrophobic faces of their amphipathicα-helices for sub-stoichiometric binding to hydrophobic surfaces on sides or ends of fibrils. Basic residues flanking the hydrophobic helical faces in apolipoproteins interacted favorably with acidic residue ladders in some amyloid polymorphs. Molecular dynamics simulations of selected apoE-fibril complexes confirmed their stability. Amyloid bindingviacryptic sites, which became available upon opening of flexibly linked apolipoproteinα-helices, resembled apolipoprotein-lipid binding. This mechanism probably extends to other apolipoprotein-amyloid interactions. Apolipoprotein binding alongside fibrils could interfere with fibril fragmentation and secondary nucleation, while binding at the fibril ends could halt amyloid elongation and dissolution in a polymorph-specific manner. The proposed mechanism is supported by extensive prior experimental evidence and helps reconcile disparate reports on apoE’s role in Aβaggregation. Furthermore, apoE domain opening and direct interaction of Arg/Cys158 with amyloid potentially contributes to isoform-specific effects in Alzheimer’s disease. In summary, current modeling supported by prior experimental studies suggests similar mechanisms for apolipoprotein-amyloid and apolipoprotein-lipid interactions; explains why apolipoproteins co-deposit with amyloids; and helps reconcile conflicting reports on the chaperone-like apoE action in Aβaggregation.
Unilateral ephaptic program underlying sweetness dominance
Authors: Lee MinHyuk , Kim Seon Yeong , Park Taeim , Joo Kyeung Min , Kwon Jae Young , Kim Kyuhyung , Kang KyeongJin 
Published: August 2023

AbstractIn ephaptic coupling, physically adjacent neurons influence one another’s activity via the electric fields they generate. To date, the molecular mechanisms that mediate and modulate ephaptic coupling’s effects remain poorly understood. Here, we show that the hyperpolarization-activated cyclic nucleotide-gated (HCN) channel lateralizes the potentially mutual ephaptic inhibition betweenDrosophilagustatory receptor neurons (GRNs). While sweet-sensing GRNs (sGRNs) engage in ephaptic suppression of the adjacent bitter-sensing GRNs (bGRNs), HCN expression in sGRNs enables them to resist ephaptic suppression from the bGRNs. Such one-sided ephaptic inhibition confers sweetness dominance, facilitating ingestion of bitter-laced sweets. Flies with HCN-deficient sGRNs exhibited dramatically decreased attraction to sucrose mixed with moderate levels of caffeine, highlighting the behavioral significance that gustatory ephaptic inhibition promotes ingestion of carbohydrates buried in bitterness. Our findings indicate a role for the gating of ephaptic coding to ensure the intake of the essential nutrient despite bitter contaminants present in the feeding niche ofDrosophila, as the gating establishes a hierarchy of gustatory neuron excitation. Such refinement provides a previously unappreciated mechanism for controlling the activity of a neuronal network with potential implications in the mammalian brain, given the evolutionary conservation of the HCN genes.
TGFß/activin-dependent activation of Torso controls the timing of the metamorphic transition in the red flour beetleTribolium castaneum
Authors: Chafino Sílvia , Salvia Roser , Martín David , Franch-Marro Xavier 
Published: August 2023

AbstractUnderstanding the mechanisms governing body size attainment during animal development is of paramount importance in biology. In insects, a crucial phase in determining body size occurs at the larva-pupa transition, marking the end of the larval growth period. Central to this process is the attainment of the threshold size (TS), a critical developmental checkpoint that must be reached before the larva can undergo metamorphosis. However, the intricate molecular mechanisms by which the TS orchestrates this transition remain poor understood. In this study, we investigate the role of the interaction between the Torso and TGFß/activin signaling pathways in regulating metamorphic timing in the red flour beetle,Tribolium castaneum. Our results show that Torso signaling is required specifically during the last larval instar and that its activation is mediated not only by the prothoracicotropic hormone (Tc-Ptth) but also by Trunk (Tc-Trk), another ligand of the Tc-Torso receptor. Interestingly, we show that while Torso activation by Tc-Ptth determines the onset of metamorphosis, Tc-Trk promotes growth during the last larval stage. In addition, we found that the expression ofTc-torsocorrelates with the attainment of the TS and the decay of juvenile hormone (JH) levels, at the onset of the last larval instar. Notably, our data reveals that activation of TGFß/activin signaling pathway at the TS is responsible for repressing the JH synthesis and inducingTc-torsoexpression, initiating metamorphosis. Altogether, these findings shed light on the pivotal involvement of the Ptth/Trunk/Torso and TGFß/activin signaling pathways as critical regulatory components orchestrating the TS-driven metamorphic initiation, offering valuable insights into the mechanisms underlying body size determination in insects.
Identification of glucose-independent metabolic pathways associated with anti-proliferative effect of metformin, their coordinate derangement with cMyc downregulation and reversibility in liver cancer cells
Authors: Islam Sk Ramiz , Manna Soumen Kanti 
Published: August 2023

AbstractSeveral studies indicated anti-cancer effects of metformin in liver cancer. This was attributed to the activation of LKB-AMPK axis, which is associated with anti-hyperglycaemic effect and cytotoxicity. However, despite lack of evidence on cytotoxic effect of physiological metformin concentrations and ability of cancer cells to survive under glucose-deprivation, no study has examined the glucose-independent effect of non-cytotoxic metformin or metabolic reprogramming associated with it. In addition, no study has ever been conducted on reversibility of anti-cancer effects of metformin. Here, the dose-dependent effects of metformin on HepG2 cells were examined in presence and absence of glucose. The longitudinal evolution of metabolome was analyzed along with gene and protein expression as well as their correlations with and reversibility of cellular phenotype and metabolic signatures. Metformin concentrations up to 2.5mM were found to be non-cytotoxic but anti-proliferative irrespective of presence of glucose. Apart from mitochondrial impairment, derangement of fatty acid desaturation, one-carbon, glutathione and polyamine metabolism were associated with non-cytotoxic metformin treatment irrespective of glucose supplementation. Depletion of pantothenic acid, downregulation of essential amino acid uptake, metabolism and purine salvage were identified as novel glucose-independent effects of metformin. These were significantly correlated withcMycexpression and reduction in proliferation. Rescue experiments established reversibility upon metformin withdrawal and tight association between proliferation, metabotype andcMycexpression. Taken together, derangement of novel glucose-independent metabolic pathways and concomitant cMyc downregulation co-ordinately contribute to anti-proliferative effect of metformin even at non-cytotoxic concentrations, which is reversible and may influence its therapeutic utility.
Selective ablation of thymic and peripheral Foxp3+regulatory T cell development
Authors: Yilmazer Acelya , Zevla Dimitra Maria , Malmkvist Rikke , Bello Rodríguez Carlos Alejandro , Undurraga Pablo , Kirgin Emre , Boernert Marie , Voehringer David , Kershaw Olivia , Schlenner Susan , Kretschmer Karsten 
Published: August 2023

ABSTRACTFoxp3+Treg cells of thymic (tTreg) and peripheral (pTreg) developmental origin are thought to synergistically act to ensure immune homeostasis, with self-reactive tTreg cells primarily constraining autoimmune responses. We exploited tTreg-specific GFP/Cre recombinase activity to selectively ablate either tTreg (ΔtTreg) or pTreg (ΔpTreg) cell development. In contrast to the tTreg cell behavior in ΔpTreg mice, pTreg cells with a highly activated suppressor phenotype replenished the Treg cell pool of C57BL/6.ΔtTreg mice, preventing early mortality and fatal autoimmunity. Even with advancing age, pTreg cells largely maintained immune tolerance in C57BL/6.ΔtTreg mice. However, only two generations of (C57BL/6>NOD) backcrossing precipitated severe disease lethality associated with a distinct, partially overlapping pattern of organ-specific autoimmunity. Genetic association studies defined a small set of autoimmune risk loci sufficient to unleash a particularly severe form of diabetes, including genes known to impinge on Treg cell biology. Thus, pTreg cells exhibit an unexpectedly high functional adaptability, emphasizing their importance as mediators of bystander effects to ensure self-tolerance.SUMMARYThis study in complementary loss-of-function mouse models uncovers an unexpected functional plasticity of pTreg cells in constraining systemic autoimmune responses in the absence of tTreg cells and identifies tTreg cells as primary regulators of β-cell autoimmunity in type 1 diabetes.