bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cloud-enabled Scalable Analysis of Large Proteomics Cohorts
Authors: Guturu Harendra , Nichols Andrew , Cantrell Lee S. , Just Seth , Kis Janos , Platt Theodore , Mohtashemi Iman , Wang Jian , Batzoglou Serafim 
Published: September 2024

AbstractRapid advances in depth and throughput of untargeted mass-spectrometry-based proteomic technologies are enabling large-scale cohort proteomic and proteogenomic analyses. As such studies scale, the data infrastructure and search engines required to process data must also scale. This challenge is amplified in search engines that rely on library-free match between runs (MBR) search, which enable enhanced depth-per-sample and data completeness. However, to-date, no MBR-based search could scale to process cohorts of thousands or more individuals. Here, we present a strategy to deploy search engines in a distributed cloud environment without source code modification, thereby enhancing resource scalability and throughput. Additionally, we present an algorithm, Scalable MBR, that replicates the MBR procedure of the popular DIA-NN software for scalability to thousands of samples. We demonstrate that Scalable MBR can search thousands of MS raw files in a few hours compared to days required for the original DIA-NN MBR procedure and demonstrate that the results are almost indistinguishable to those of DIA-NN native MBR. The method has been tested to scale to over 15,000 injections and is available for use in the Proteograph™ Analysis Suite.
Unlocking cross-modal interplay of single-cell and spatial joint profiling with CellMATE
Authors: Wang Qi , Zhang Bolei , Gong Luyu , Guo Yue , Li Erguang , Yang Jingping 
Published: September 2024

AbstractA key advantage of single-cell multimodal joint profiling is the modality interplay, which is essential for deciphering the cell fate. However, while current analytical methods can leverage the additive benefits, they fall short to explore the synergistic insights of joint profiling, thereby diminishing the advantage of joint profiling. Here, we introduce CellMATE, aMulti-headAdversarialTraining-basedEarly-integration approach specifically developed for multimodal joint profiling. CellMATE can capture both additive and synergistic benefits inherent in joint profiling through auto-learning of multimodal distributions and simultaneously represents all features into a unified latent space. Through extensive evaluation across diverse joint profiling scenarios, CellMATE demonstrated its superiority in ensuring utility of cross-modal properties, uncovering cellular heterogeneity and plasticity, and delineating differentiation trajectories. CellMATE uniquely unlocks the full potential of joint profiling to elucidate the dynamic nature of cells during critical processes as differentiation, development and diseases.Graphical abstracts
Semaglutide Administration in Healthy Mice Alters Behaviour Related to Stress and Motivation
Authors: Moreno Andrea , Ansarifar Sanaz , Mosqueira Alejo , Nabavi Sadegh 
Published: September 2024

SUMMARYSemaglutide, a GLP-1 receptor agonist used primarily to regulate blood sugar and appetite, has been studied mostly in models of obesity and diabetes. Yet, little is known about its effects on healthy animals. In this study, daily dosing of semaglutide (0.1 mg/kg) in healthy C57BL/6JRj male wildtype mice led to noticeable changes in behavioural tests commonly used to evaluate stress and motivation. The mice showed increased jumping in the open field, reduced shredding of nestlets, less interest in sniffing female urine, and heightened activity in the forced swim test. These behavioural shifts may indicate potential side effects of semaglutide in healthy animals, providing a crucial baseline for understanding how the drug could affect conditions like obesity, addiction, or cognitive decline.
Receiving information on machine learning-based clinical decision support systems in psychiatric services increases staff trust in these systems: A randomized survey experiment
Authors: Perfalk Erik , Bernstorff Martin , Danielsen Andreas Aalkjær , Østergaard Søren Dinesen 
Published: September 2024

AbstractBackgroundClinical decision support systems based on machine learning (ML) models are emerging within psychiatry. To ensure their successful implementation, healthcare staff needs to trust these systems. Here, we investigated if providing staff with basic information about ML-based clinical decision support systems enhances their trust in them.MethodsWe conducted a randomised survey experiment among staff in the Psychiatric Services of the Central Denmark Region. The participants were allocated to one of three arms, receiving different types of information: An intervention arm (receiving information on clinical decision-making supported by an ML model); an active control arm (receiving information on standard clinical decision process without ML support); and a blank control arm (no information). Subsequently, participants responded to various questions regarding their trust/distrust in ML-based clinical decision support systems. The effect of the intervention was assessed by pairwise comparisons between all randomization arms on sum scores of trust and distrust.FindingsAmong 2,838 invitees, 780 completed the survey experiment. The intervention enhanced trust and diminished distrust in ML-based clinical decision support systems compared with the active control arm (Trust: mean difference= 5% [95% confidence interval (CI): 2%; 9%], p-value < 0.001; Distrust: mean difference=-4% [-7%; -1%], p-value = 0.042)) and the blank control arm (Trust: mean difference= 5% [2%; 11%], p-value = 0.003; Distrust: mean difference= -3% [-6%; - 1%], p-value = 0.021).InterpretationProviding information on ML-based clinical decision support systems in hospital psychiatry may increase healthcare staff trust in such systems.
Investigating the Causal Relationship Between Sleep-Related Traits and Self-Reported Diabetes: A Mendelian Randomization Study
Authors: Nisamudheen Nismabi A , Velayutham Dinesh , Jithesh Puthen Veettil 
Published: September 2024

AbstractObjectiveSelf-reported data can be a valuable resource for understanding health outcomes, behaviors, disease prevalence, and risk factors, yet underutilized in epidemiological research. While observational studies have linked sleep traits with diabetes, evidence using self-reported diabetes data for causal connection is lacking.MethodsWe performed a two-sample Mendelian randomization (MR) analysis using Inverse Variance Weighting (IVW), IVW with multiplicative random effects (IVW-MRE), Maximum Likelihood (ML), MR-Egger regression, and Weighted Median models, with genetic variants linked to five sleep traits (sleep duration, insomnia, snoring, daytime dozing, and chronotype) and self-reported diabetes from the UK Biobank dataset. The study utilized MR-Egger and MR-PRESSO regression to evaluate pleiotropy and outliers, IVW Q statistics to detect heterogeneity, the MR-Steiger test to assess directionality, and leave-one-out sensitivity analysis to ensure the reliability.ResultsML provided positive causal associations between genetically predicted insomnia (p = 0.002, OR = 1.021, 95% CI: 1.008–1.035) and daytime dozing (p = 0.014, OR = 1.029, 95% CI: 1.006–1.052) with diabetes, while IVW and IVW-MRE analysis showed a trend towards significance. Snoring showed mixed evidence, while genetically predicted sleep duration was marginally associated with diabetes (p = 0.053, OR = 0.992, 95% CI: 0.984–1.000) with the weighted median method, indicating a potential small protective effect. No causal association was found between chronotype and diabetes.ConclusionThis exploratory MR study provides evidence for the effect of insomnia, daytime dozing, sleep duration and snoring on diabetes risk. These findings underscore the importance of considering self-reported health outcomes in epidemiological research.Article HighlightsWhy did we undertake this study?We undertook this study to explore the causal relationships between sleep-related traits and diabetes using self-reported data, as previous prospective, retrospective or other observational studies have shown associations but lacked causal evidence using self-reported data.What is the specific question(s) we wanted to answer?We aimed to answer whether sleep-related traits, such as sleep duration, insomnia, snoring, daytime dozing, and chronotype, have a causal impact on diabetes which is self-reported.What did we find?Our two-sample Mendelian Randomization (MR) analysis found that genetically predicted insomnia and daytime dozing have a positive causal association and sleep duration was marginally associated with diabetes.What are the implications of our findings?These findings suggest that certain sleep traits may contribute to diabetes risk, highlighting the importance of considering sleep in diabetes prevention and treatment strategies. The results also emphasize the value of using self-reported health outcomes in epidemiological research and clinical interventions.
Harnessing non-standard nucleic acids for highly sensitive icosaplex (20-plex) detection of microbial threats
Authors: Kawabe Hinako , Manfio Luran , Pena Sebastian Magana , Zhou Nicolette A. , Bradley Kevin M. , Chen Cen , McLendon Chris , Benner Steven A. , Levy Karen , Yang Zunyi , Marchand Jorge A. , Fuhrmeister Erica R. 
Published: September 2024

AbstractEnvironmental surveillance and clinical diagnostics heavily rely on the polymerase chain reaction (PCR) for target detection. A growing list of microbial threats warrants new PCR-based detection methods that are highly sensitive, specific, and multiplexable. Here, we introduce a PCR-based icosaplex (20-plex) assay for detecting 18 enteropathogen and two antimicrobial resistance genes. This multiplexed PCR assay leverages the self-avoiding molecular recognition system (SAMRS) to avoid primer dimer formation, the artificially expanded genetic information system (AEGIS) for amplification specificity, and next-generation sequencing for amplicon identification. We benchmarked this assay using a low-cost, portable sequencing platform (Oxford Nanopore) on wastewater, soil, and human stool samples. Using parallelized multi-target TaqMan Array Cards (TAC) to benchmark performance of the 20-plex assay, there was 74% agreement on positive calls and 97% agreement on negative calls. Additionally, we show how sequencing information from the 20-plex can be used to further classify allelic variants of genes and distinguish sub-species. The strategy presented offers sensitive, affordable, and robust multiplex detection that can be used to support efforts in wastewater-based epidemiology, environmental monitoring, and human/animal diagnostics.
NR2F2 Reactivation in Early-life Adipocyte Stem-like Cells Rescues Adipocyte Mitochondrial Oxidation
Authors: Das Snehasis , Varshney Rohan , Farriester Jacob W. , Kyere-Davies Gertrude , Martinez Alexandrea E. , Hill Kaitlyn , Kinter Michael , Mullen Gregory P. , Nagareddy Prabhakara R. , Rudolph Michael C. 
Published: September 2024

ABSTRACTIn humans, perinatal exposure to an elevated omega-6 (n6) relative to omega-3 (n3) Fatty Acid (FA) ratio is associated with the likelihood of childhood obesity. In mice, we show perinatal exposure to excessive n6-FA programs neonatal Adipocyte Stem-like cells (ASCs) to differentiate into adipocytes with lower mitochondrial nutrient oxidation and a propensity for nutrient storage. Omega-6 FA exposure reduced fatty acid oxidation (FAO) capacity, coinciding with impaired induction of beige adipocyte regulatory factors PPARγ, PGC1α, PRDM16, and UCP1. ASCs from n6-FA exposed pups formed adipocytes with increased lipogenic genes in vitro, consistent with an in vivo accelerated adipocyte hypertrophy, greater triacylglyceride accumulation, and increased % body fat. Conversely, n6-FA exposed pups had impaired whole animal13C-palmitate oxidation. The metabolic nuclear receptor, NR2F2, was suppressed in ASCs by excess n6-FA intake preceding adipogenesis. ASC deletion of NR2F2, prior to adipogenesis, mimicked the reduced FAO capacity observed in ASCs from n6-FA exposed pups, suggesting that NR2F2 is required in ASCs for robust beige regulator expression and downstream nutrient oxidation in adipocytes. Transiently re-activating NR2F2 with ligand prior to differentiation in ASCs from n6-FA exposed pups, restored their FAO capacity as adipocytes by increasing the PPARγ-PGC1α axis, mitochondrial FA transporter CPT1A, ATP5 family synthases, and NDUF family Complex I proteins. Our findings suggest that excessive n6-FA exposure early in life dampens an NR2F2-mediated induction of beige adipocyte regulators, resulting in metabolic programming that is shifted towards nutrient storage.
Extracellular vesicles regulate metastable phenotypes of lymphangioleiomyomatosis cells via shuttling ATP synthesis to pseudopodia and activation of integrin adhesion complexes
Authors: Kalvala Anil Kumar , Silwal Ashok , Patel Bhaumik , Kasetti Apoorva , Shetty Kirti , Cho Jung-Hung , Lara Gerard , Daugherity Beth , Diesler Remi , Pooladanda Venkatesh , Rueda Bo R , Henske Elizabeth Petri , Yu Jane J. , Markiewski Maciej , Karbowniczek Magdalena 
Published: September 2024

AbstractPulmonary lymphangioleiomyomatosis (LAM) is metastatic sarcoma but mechanisms regulating LAM metastasis are unknown. Extracellular vesicle (EV) regulate cancer metastasis but their roles in LAM have not yet been investigated. Here, we report that EV biogenesis is increased in LAM and LAM EV cargo is enriched with lung tropic integrins, metalloproteinases, and cancer stem cell markers. LAM-EV increase LAM cell migration and invasion via the ITGα6/β1-c-Src-FAK-AKT axis. Metastable (hybrid) phenotypes of LAM metastasizing cells, pivotal for metastasis, are regulated by EV from primary tumor or metastasizing LAM cells via shuttling ATP synthesis to cell pseudopodia or activation of integrin adhesion complex, respectively. In mouse models of LAM, LAM-EV increase lung metastatic burden through mechanisms involving lung extracellular matrix remodeling. Collectively, these data provide evidence for the role of EV in promoting LAM lung metastasis and identify novel EV-dependent mechanisms regulating metastable phenotypes of tumor cells. Clinical impact of research is that it establishes LAM pathway as novel target for LAM therapy.
Ventral tegmental area dopamine neural activity switches simultaneously with rule representations in the prefrontal cortex and hippocampus
Authors: Ding Mingxin , Tomsick Porter L. , Young Ryan A. , Jadhav Shantanu P. 
Published: September 2024

AbstractMultiple brain regions need to coordinate activity to support cognitive flexibility and behavioral adaptation. Neural activity in both the hippocampus (HPC) and prefrontal cortex (PFC) is known to represent spatial context and is sensitive to reward and rule alterations. Midbrain dopamine (DA) activity is key in reward seeking behavior and learning. There is abundant evidence that midbrain DA modulates HPC and PFC activity. However, it remains underexplored how these networks engage dynamically and coordinate temporally when animals must adjust their behavior according to changing reward contingencies. In particular, is there any relationship between DA reward prediction change during rule switching, and rule representation changes in PFC and CA1? We addressed these questions using simultaneous recording of neuronal population activity from the hippocampal area CA1, PFC and ventral tegmental area (VTA) in male TH-Cre rats performing two spatial working memory tasks with frequent rule switches in blocks of trials. CA1 and PFC ensembles showed rule-specific activity both during maze running and at reward locations, with PFC rule coding more consistent across animals compared to CA1. Optogenetically tagged VTA DA neuron firing activity responded to and predicted reward outcome. We found that the correct prediction in DA emerged gradually over trials after rule-switching in coordination with transitions in PFC and CA1 ensemble representations of the current rule after a rule switch, followed by behavioral adaptation to the correct rule sequence. Therefore, our study demonstrates a crucial temporal coordination between the rule representation in PFC/CA1, the dopamine reward signal and behavioral strategy.Significance StatementThis study examines neural activity in mammalian brain networks that support the ability to respond flexibly to changing contexts. We use a rule-switching spatial task to examine whether the key reward-responsive and predictive dopamine (DA) activity changes in coordination with changes in rule representations in key cognitive regions, the prefrontal cortex (PFC) and hippocampus. We first established distinct rule representations in PFC and hippocampus, and predictive coding of reward outcomes by DA neuronal activity. We show that the rule-specific DA reward prediction after a rule switch develops in temporal coordination with changes in rule representations in PFC, eventually leading to behavioral changes. These results thus provide an integrated understanding of reward prediction, cognitive representations of rules and behavioral adaptation.
Biomolecular condensation of ERC1 recruits ATG8 and NBR1 to drive autophagosome formation for plant heat tolerance
Authors: Chung Ka Kit , Zhao Ziwei , Law Kai Ching , Ma Juncai , Chiang Cheuk Him , Leung Kwan Ho , Shrestha Ruben , Wu Yixin , Li Chaorui , Lee Ka Ming , Feng Lei , Li Xibao , Wong Kam Bo , Xu Shou-Ling , Gao Caiji , Zhuang Xiaohong 
Published: September 2024

AbstractMacroautophagy (hereafter autophagy) is essential for cells to respond to nutrient stress by delivering cytosolic contents to vacuoles for degradation via the formation of a multi-layer vesicle named autophagosome. A set of autophagy-related (ATG) regulators are recruited to the phagophore assembly site for the initiation of phagophore, as well as its expansion and closure and subsequent delivery into the vacuole. However, it remains elusive that how the phagophore assembly is regulated under different stress conditions. Here, we described an unknownArabidopsis (Arabidopsis thaliana)cytosolic ATG8-interaction protein family (ERC1/2), that binds ATG8 and NBR1 to promote autophagy. ERC1 proteins translocate to the phagophore membrane and develop into classical ring-like autophagosomes upon autophagic induction. However, ERC1 proteins form large droplets together with ATG8e proteins when in the absence of ATG8 lipidation activity. We described the property of these structures as phase-separated membraneless condensates by solving thein vivoorganization with spatial and temporal resolution. Moreover, ERC1 condensates elicits a strong recruitment of the autophagic receptor NBR1. Loss of ERC1 suppressed NBR1 turnover and attenuated plant tolerance to heat stress condition. This work provides novel insights into the mechanical principle of phagophore initiation via an unreported ERC1-mediated biomolecular condensation for heat tolerance inArabidopsis.
Use of the non-paretic arm reflects a habitual behaviour in chronic stroke
Authors: Sporn S. , Bonyadin E. , Fathana R. , Tedesco L. Triccas , Coll M. , Bestmann S. , Ward N. S. 
Published: September 2024

AbstractBackgroundA proportion of stroke survivors use their affected arm less than might be expected based on their level of impairment. The resulting non-use of the affected arm has a negative impact on participation in neurorehabilitation and functional independence. However, non-use remains poorly understood. One possibility is that prioritising the non-paretic arm reflects a habit, despite residual functional capacity in the paretic arm.Methods30 chronic stroke survivors (Mean FM: 28.9 ± 11.3) participated in a simplified version of the forced response paradigm, which reliably identifies the presence of a habit. Participants were asked to choose which arm to use to maximise points scored during a reaching task. During half of the trials, the presumed habit of using the non-paretic arm yielded more points, whereas in the other half using the non-paretic arm incurred a loss of points. Participants completed two versions of this task, once with unlimited response time available and once without.ResultsParticipants scored fewer points in the limited response condition compared to the unlimited response conditions. This difference was driven by a selective increase in the use of the non-paretic arm in trials where the paretic arm yielded more points. The results were not mediated by former hand dominance.ConclusionsOur results demonstrate that not using the non-paretic arm may reflect a habit response that is more readily triggered in demanding (e.g. time-limited) situations. This may explain why successful neurorehabilitation does not always result in a more functionally useful arm. Our results pave the way for targeted interventions such as habit breaking techniques to be included in clinical practise.
The Role of Cholesterol in M2 Clustering and Viral Budding Explained
Authors: Kolokouris Dimitrios , Kalenderoglou Iris E. , Duncan Anna L. , Corey Robin A. , Sansom Mark S. P. , Kolocouris Antonios 
Published: September 2024

AbstractThe proton-conducting domain of the influenza A M2 homotetrameric channel (M2TM-AH; residues 22-62), consisting of four transmembrane (TM; residues 22-46) and four amphipathic helices (AHs; residues 47-62), promotes the release of viral RNA via acidification. Previous studies have also proposed the formation of clusters of M2 channels in the budding neck areas in raft-like domains of the plasma membrane,1,2which are rich in cholesterol, resulting in cell membrane scission and viral release. Experiments showed that cholesterol has a significant contribution to lipid bilayer undulations in viral buds suggesting a significant role for cholesterol in the budding process. However, a clear explanation of membrane curvature effect based on the distribution of cholesterol around M2TM-AH clusters is lacking. Using coarse-grained molecular dynamics simulations of M2TM-AH in bilayers, we observed that M2 channels form specific clusters with conical shapes, driven by attraction of their amphipathic helices (AHs). We showed that cholesterol stabilized the formation of M2 channel clusters, by filling and bridging the conical gap between M2 channels at specific sites in the N-terminals of adjacent channels or via the C-terminal region of TM and AHs, the latter sites displaying longer interaction time and higher stability. Potential of mean force calculations showed that when cholesterols occupy the identified interfacial binding sites between two M2 channels, the dimer is stabilized by 11 kJ/mol. This translates to the cholesterol-bound dimer being populated by almost two orders of magnitude compared to a dimer lacking cholesterol. We demonstrated that the cholesterol bridged M2 channels can exert lateral force on the surrounding membrane to induce the necessary negative Gaussian curvature profile which permits the spontaneous scission of the catenoid membrane neck and leads to viral buds and scission.Significance StatementA key role of influenza A M2 channel, a prototype viroporin, is the generation of curvature in the host cell membrane to form budding necks leading to scission and release of the virions. It has been shown experimentally that this process is mediated through the amphipathic helices of M2 and that cholesterol enhanced lipid bilayer undulations in viral budding. Here, using coarse-grained molecular dynamics simulations we revealed that M2 channels form clusters in membranes, induced in an additive manner by both the AHs and cholesterol, which in turn increase local membrane curvature. We showed that both cluster formation and the induced membrane curvature are enhanced by cholesterol by bridging the conical area between M2 channels.