bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mapping individual differences across brain network structure to function and behavior with connectome embedding
Authors: Levakov Gidon , Faskowitz Joshua , Avidan Galia , Sporns Olaf 
Published: January 2021

AbstractThe connectome, a comprehensive map of the brain’s anatomical connections, is often summarized as a matrix comprising all dyadic connections among pairs of brain regions. This representation cannot capture higher-order relations within the brain graph. Connectome embedding (CE) addresses this limitation by creating compact vectorized representations of brain nodes capturing their context in the global network topology. Here, nodes “context” is defined as random walks on the brain graph and as such, represents a generative model of diffusive communication around nodes. Applied to group-averaged structural connectivity, CE was previously shown to capture relations between inter-hemispheric homologous brain regions and uncover putative missing edges from the network reconstruction. Here we extend this framework to explore individual differences with a novel embedding alignment approach. We test this approach in two lifespan datasets (NKI: n=542; Cam-CAN: n=601) that include diffusion-weighted imaging, resting-state fMRI, demographics and behavioral measures. We demonstrate that modeling functional connectivity with CE substantially improves structural to functional connectivity mapping both at the group and subject level. Furthermore, age-related differences in this structure-function mapping are preserved and enhanced. Importantly, CE captures individual differences by out-of-sample prediction of age and intelligence. The resulting predictive accuracy was higher compared to using structural connectivity and functional connectivity. We attribute these findings to the capacity of the CE to incorporate aspects of both anatomy (the structural graph) and function (diffusive communication). Our novel approach allows mapping individual differences in the connectome through structure to function and behavior.
Evolutionary Perspective and Expression Analysis of Intronless Genes Highlight the Conservation on Their Regulatory Role
Authors: Aviña-Padilla Katia , Ramírez-Rafael José Antonio , Herrera-Oropeza Gabriel Emilio , Muley Vijaykumar , Valdivia Dulce I. , Díaz-Valenzuela Erik , García-García Andrés , Varela-Echavarría Alfredo , Hernández-Rosales Maribel 
Published: January 2021

AbstractEukaryotic gene structure is a combination of exons generally interrupted by intragenic non-coding DNA regions termed introns removed by RNA splicing to generate the mature mRNA. Thus, eukaryotic genes can be either single exon genes (SEGs) or multiple exon genes (MEGs). Among SEGs, intronless genes (IGs) are a subgroup that additionally lacks introns at their UTRs, and code for proteins essentially involved in development, growth, and cell proliferation. Gene expression of IGs has been proposed to be highly specialized for neuro-specific functions and linked to cancer, neuropathies, and developmental disorders. The abundant presence of introns in eukaryotic genomes is pivotal for the precise control of gene expression. Notwithstanding, IGs exempting splicing events entail a higher transcriptional fidelity, making them even more valuable for regulatory roles. This work aimed to infer the functional role and evolutionary history of IGs using the mouse genome. Intronless protein-coding genes consist of a subgroup of ~6 % of a total of 21,527 genes with one exon. To understand the prevalence, biological relevance, and evolution, we identified and studied their 1,116 functional proteins. We validated differential expression in transcriptomics data of early embryo stages using mouse telencephalon tissue. Our results showed that expression levels of IGs are lower compared to MEGs. However, strongly upregulated IGs include transcription factors (TFs) such as the class 3 of POU (HMG Box),Neurog1, Olig1, andBHLHe22, BHLHe23,among other essential genes including the beta cluster of protocadherins. Most striking was the finding that IG-encoded BHLH TFs qualify the criteria to be referred to as microprotein candidates. Finally, predicted protein orthologs in other six genomes confirmed a high conservancy of IGs associated with regulating neurobiological processes and with chromatin organization and epigenetic regulation inVertebrata. Moreover, this study highlights that IGs are essential modulators of regulatory processes, as Wnt signaling pathway and biological processes as pivotal as sensory organs developing at a transcriptional and post-translational level. Overall, our results suggest that IG proteins have specialized, prevalent, and unique biological roles and that functional divergence between IGs and MEGs is likely to be the result of specific evolutionary constraints.
Using Deep Learning to Predict Human Decisions, and Cognitive Models to Explain Deep Learning Models
Authors: Fintz Matan , Osadchy Margarita , Hertz Uri 
Published: January 2021

AbstractDeep neural networks (DNN) models have the potential to provide new insights in the study of human decision making, due to their high capacity and data-driven design. While these models may be able to go beyond theory-driven models in predicting human behaviour, their opaque nature limits their ability to explain how an operation is carried out. This explainability problem remains unresolved. Here we demonstrate the use of a DNN model as an exploratory tool to identify predictable and consistent human behaviour in value-based decision making beyond the scope of theory-driven models. We then propose using theory-driven models to characterise the operation of the DNN model. We trained a DNN model to predict human decisions in a four-armed bandit task. We found that this model was more accurate than a reinforcement-learning reward-oriented model geared towards choosing the most rewarding option. This disparity in accuracy was more pronounced during times when the expected reward from all options was similar, i.e., no unambiguous good option. To investigate this disparity, we introduced a reward-oblivious model, which was trained to predict human decisions without information about the rewards obtained from each option. This model captured decision-sequence patterns made by participants (e.g., a-b-c-d). In a series of experimental offline simulations of all models we found that the general model was in line with a reward-oriented model’s predictions when one option was clearly better than the others.However, when options’ expected rewards were similar to each other, it was in-line with the reward-oblivious model’s pattern completion predictions. These results indicate the contribution of predictable but task-irrelevant decision patterns to human decisions, especially when task-relevant choices are not immediately apparent. Importantly, we demonstrate how theory-driven cognitive models can be used to characterise the operation of DNNs, making them a useful explanatory tool in scientific investigation.Author SummaryDeep neural networks (DNN) models are an extremely useful tool across multiple domains, and specifically for performing tasks that mimic and predict human behaviour. However, due to their opaque nature and high level of complexity, their ability to explain human behaviour is limited. Here we used DNN models to uncover hitherto overlooked aspects of human decision making, i.e., their reliance on predictable patterns for exploration. For this purpose, we trained a DNN model to predict human choices in a decision-making task. We then characterised this data-driven model using explicit, theory-driven cognitive models, in a set of offline experimental simulations. This relationship between explicit and data-driven approaches, where high-capacity models are used to explore beyond the scope of established models and theory-driven models are used to explain and characterise these new grounds, make DNN models a powerful scientific tool.
Using ICD-10-based Social Determinants of Health Categories to Assess Patients Risk for Acute Care Utilization
Authors: Nguyen Peter H. , Wang James , Garcia-Filion Pamela , Dominick Deborah , Abbaszadegan Hamed , Hernandez Graciela Gonzalez , O’Connor Karen , Rehman Shakaib U. , Panchanathan Sarada S. 
Published: January 2021

ABSTRACTBackgroundThere has been an increasing recognition of the influence of social, behavioral, economic, and environmental factors on overall patient health. The purpose of this project was to leverage the ICD-10 codes to identify and link social determinants of health (SDoH) to patients with a high probability of utilizing acute care services and to determine if social service intervention reduced care utilization.MethodsWe analyzed retrospective data for active patients at a Department of Veterans Affairs Medical Center (VAMC) from 2015-2017. Eleven categories of SDoH were developed based on existing literature of the social determinants; the relevant ICD-10 codes were divided among these categories. Emergency Room (ER) visits, hospital admissions, and social work visits were determined for each patient in the cohort.ResultsIn a cohort of 44,401 patients, the presence of ICD-10 codes within the EHR in the 11 SDoH categories was positively correlated with increased acute care utilization. Veterans with at least one SDoH risk factor were 71% (95%CI: 68% - 75%) more likely to use the ED and 71% (95%CI: 65%-77%) more likely to be admitted to the hospital. Utilization decreased with social service interventions.ConclusionThis project demonstrates a potentially meaningful method to capture patient social risk profiles through existing EHR data in the form of ICD-10 codes, which can be used to identify the highest risk patients for intervention with the understanding that not all SDoH codes are uniformly used and some SDoHs may not be captured.
Posttraumatic Stress Disorder and the Nature of Trauma in Patients with Cardiovascular Diseases: A Case-Control study
Authors: Cyr Samuel , Marcil Marie-Joëlle , Long Valérie , De Marco Corrado , Dyrda Katia , Brouillette Judith 
Published: January 2021

AbstractIntroductionA large body of evidence indicates a significant and morbid association between posttraumatic stress disorder (PTSD) and cardiovascular disease (CVD). Few studies, however, have addressed the range of trauma in this medical population, from massive heart attack, to defibrillator shock to previous interpersonal aggression.ObjectiveThe main objective of this study was to examine the nature of trauma associated with the development of PTSD in CVD patients. More precisely, we were interested in knowing if trauma was medical in nature and whether cumulative trauma resulted in PTSD.MethodsWe performed a 1:3 case-control study. The authors compared CVD patients diagnosed with PTSD (n=37) to those with adjustment disorder (n=111) in terms of trauma/stressor types and medical and demographic characteristics.ResultsHalf (51%) of CVD patients suffering from PTSD had endured a medical trauma, 35% an external (non-medical) trauma, and 14% both. There were no significant differences with CVD patients diagnosed with adjustment disorder, 40% of them having experienced a medical stressor, 40% an external (non-medical) stressor and 20% both. Cumulative trauma was seen in only 19% of CVD patients suffering from PTSD. Traditional risk factors (female sex, younger age) were not prominent in CVD patients with PTSD as compared to those with adjustment disorder. Cases were, however, significantly more likely to have psychiatric antecedents and recent surgical interventions.ConclusionsBy uncovering characteristics of PTSD patients/trauma in CVD patients, this work will serve future research and clinical initiatives to better screen at-risk patients or at-risk medical situations.
Susceptibility vessel sign as a predictor for recanalization and clinical outcome in acute ischaemic stroke: A Systematic Review and Meta-analysis
Authors: Tang Si Zhao , Sen Jon 
Published: January 2021

AbstractT2*-weighted MRI using GRE and SWI sequences can potentially prognosticate the recanalization rate and clinical outcomes in patients with acute ischaemic stroke, using susceptibility vessel sign (SVS) and prominent hypointense vessel sign (PHVS).A literature search on PubMed, EMBASE databases and other sources from inception up to 01 February 2020 was conducted. 15 studies which reported SVS and PHVS were included in qualitative synthesis. 9 studies on SVS were included in quantitative synthesis i.e. meta-analysis.Meta-analysis did not show any significant difference in the recanalization rate between SVS (+) group and SVS (-) group (RR = 0.95, 95% CI = 0.87–1.05, p = 0.33). Treatment subgroup analysis (intravenous thrombolysis, IVT- or mechanical thrombectomy, MT-only) does not show significant association between the SVS and IVT-only (RR = 0.73, 95% CI = 0.51-1.05, P=0.09); or MT-only groups (RR = 0.99, 95% CI = 0.90-1.09, P=0.90). No significant association between poor clinical outcome at 3 months and presence of SVS (RR = 1.42, 95% CI = 0.79–2.57, p = 0.24). Treatment subgroup analysis revealed significant association of the SVS and poor clinical outcome at 3 months in the MT-only (RR = 0.67, 95% CI = 0.55–0.82, p = 0.0001) or no thrombolytic treatment (RR = 2.83, 95% CI = 1.69-4.75, p < 0.0001).In conclusion, there is a significant association between the presence of SVS and poor clinical outcome in patients who underwent MT or without treatment, and no definitive association between the presence of SVS and recanalization rate for acute ischemic stroke.
The Use of Procalcitonin as an Antimicrobial Stewardship Tool and a Predictor of Disease Severity in COVID-19
Authors: Drewett George P , Smibert Olivia C , Holmes Natasha E , Trubiano Jason A 
Published: January 2021

AbstractIn our study, procalcitonin was associated with both antibiotic use and duration in patients with COVID-19, as well as established biochemical markers of COVID-19 disease severity and oxygen requirement, suggesting a potential role for procalcitonin in COVID-19 antimicrobial stewardship.
S. Typhimurium impairs glycolysis-mediated acidification of phagosomes to evade macrophage defense
Authors: Gutiérrez Saray , Fischer Julia , Ganesan Raja , Cildir Gökhan , Wolke Martina , Pessia Alberto , Frommolt Peter , Desiderio Vincenzo , Velagapudi Vidya R , Robinson Nirmal 
Published: January 2021

AbstractRegulation of the cellular metabolism is now recognized as a crucial mechanism for the homeostasis of innate and adaptive immune cells upon diverse extracellular stimuli. Macrophages, for instance, increase glycolysis upon stimulation with pathogen-associated molecular patterns (PAMPs). Conceivably, pathogens also counteract these metabolic changes for their own survival in the host. However, despite this dynamic interplay in host-pathogen interactions, the role of immunometabolism in the context of intracellular bacterial infections is still unclear. Here, employing unbiased metabolomic and transcriptomic approaches, we investigated the role of metabolic adaptations of macrophages uponSalmonella entericaserovar Typhimurium (S. Typhimurium) infections. Importantly, our results suggested thatS. Typhimurium abrogates glycolysis and its modulators such as insulin-signaling to impair macrophage defense. Mechanistically, glycolytic enzyme aldolase A is critical for v-ATPase assembly and the acidification of phagosomes uponS. Typhimurium infection, and impairment in the glycolytic machinery eventually leads to decreased bacterial clearance and antigen presentation in macrophages. Collectively, our results highlight a vital molecular link between metabolic adaptation and phagosome maturation in macrophages, which is targeted byS. Typhimurium to evade cell-autonomous defense.
Two novel loci underlie natural differences inCaenorhabditis elegansmacrocyclic lactone responses
Authors: Evans Kathryn S. , Wit Janneke , Stevens Lewis , Hahnel Steffen R. , Rodriguez Briana , Park Grace , Zamanian Mostafa , Brady Shannon C. , Chao Ellen , Introcaso Katherine , Tanny Robyn E. , Andersen Erik C. 
Published: January 2021

AbstractParasitic nematodes cause a massive worldwide burden on human health along with a loss of livestock and agriculture productivity. Anthelmintics have been widely successful in treating parasitic nematodes. However, resistance is increasing, and little is known about the molecular and genetic causes of resistance. The free-living roundwormCaenorhabditis elegansprovides a tractable model to identify genes that underlie resistance. Unlike parasitic nematodes,C. elegansis easy to maintain in the laboratory, has a complete and well annotated genome, and has many genetic tools. Using a combination of wild isolates and a panel of recombinant inbred lines constructed from crosses of two genetically and phenotypically divergent strains, we identified three genomic regions on chromosome V that underlie natural differences in response to the macrocyclic lactone (ML) abamectin. One locus was identified previously and encodes an alpha subunit of a glutamate-gated chloride channel (glc-1). Here, we validate and narrow two novel loci using near-isogenic lines. Additionally, we generate a list of prioritized candidate genes identified inC. elegansand in the parasiteHaemonchus contortusby comparison of ML resistance loci. These genes could represent previously unidentified resistance genes shared across nematode species and should be evaluated in the future. Our work highlights the advantages of usingC. elegansas a model to better understand ML resistance in parasitic nematodes.Author SummaryParasitic nematodes infect plants, animals, and humans, causing major health and economic burdens worldwide. Parasitic nematode infections are generally treated efficiently with a class of drugs named anthelmintics. However, resistance to many of these anthelmintic drugs, including macrocyclic lactones (MLs), is rampant and increasing. Therefore, it is essential that we understand how these drugs act against parasitic nematodes and, conversely, how nematodes gain resistance in order to better treat these infections in the future. Here, we used the non-parasitic nematodeCaenorhabditis elegansas a model organism to study ML resistance. We leveraged natural genetic variation between strains ofC. eleganswith differential responses to abamectin to identify three genomic regions on chromosome V, each containing one or more genes that contribute to ML resistance. Two of these loci have not been previously discovered and likely represent novel resistance mechanisms. We also compared the genes in these two novel loci to the genes found within genomic regions linked to ML resistance in the parasiteHaemonchus contortusand found several cases of overlap between the two species. Overall, this study highlights the advantages of usingC. elegansto understand anthelmintic resistance in parasitic nematodes.
Novel Thyroid-Specific Autoantibodies in Patients with Immune-Related Adverse Events Involving the Thyroid Gland
Authors: Yamauchi Ichiro , Yasoda Akihiro , Hakata Takuro , Yamashita Takafumi , Hirota Keisho , Ueda Yohei , Fujii Toshihito , Taura Daisuke , Sone Masakatsu , Inagaki Nobuya 
Published: January 2021

AbstractAimsProgrammed cell death-1 (PD-1) blockade therapy frequently results in immune-related adverse events involving the thyroid gland (thyroid irAEs). Although clinical features of thyroid irAEs are known, the mechanisms remain unclear. Here, we conducted a pilot study to investigate mechanisms of thyroid irAE development from the perspective of autoantibodies.MethodsWe performed immunoprecipitation-based assays using sera of 3 patients who developed thyroid irAEs with PD-1 blockade therapy by nivolumab and HEK293T cell lysates, including overexpressed proteins of interest (NKX2-1, PAX8, FOXE1, and HHEX; thyroid-specific transcriptional factors). The pellets were analyzed by western blot to detect the HiBit tag attached to the C-terminus of the proteins.ResultsRelevant changes to NKX2-1 bands were not seen in all 3 patients, but PAX8 bands were augmented in patient 2 with lung cancer and patient 3 with renal cell carcinoma. In addition, FOXE1 bands were augmented in patient 1 with malignant melanoma and patient 3, and a HHEX band was augmented in patient 3. Thus, we revealed novel thyroid-specific autoantibodies, PAX8Ab, FOXE1Ab, and HHEXAb. Expression patterns of the antigens recognized by these antibodies were not identical to the primary sites, so autoimmune responses in thyroid irAE may originate from the thyroid gland, and not the malignancy. Considering that TPOAb rather than TgAb is often negative in patients with thyroid irAEs, other mechanisms such as cytotoxic T cell and antigenicity of thyroglobulin may be involved.ConclusionsAlthough the significance of these novel autoantibodies needs further examination, the present study provides new insights for thyroid autoimmunity.
An enhancer sequence in the intrinsically disordered region of the essential cell division protein FtsZ promotes conformation-guided substrate processing by ClpXP inEscherichia coli
Authors: Viola Marissa G. , Perdikari Theodora Myrto , Trebino Catherine , Rahmani Negar , Mathews Kaylee L. , Pena Carolina Meija , Chua Xien Yu , Xuan Botai , LaBreck Christopher J. , Fawzi Nicolas L. , Camberg Jodi L. 
Published: January 2021

AbstractThe essential bacterial division protein inEscherichia coli, FtsZ, assembles into the FtsZ-ring at midcell and recruits other proteins to the division site to promote septation. A region of the FtsZ amino acid sequence that links the conserved polymerization domain to a C-terminal protein interaction site was predicted to be intrinsically disordered and has been implicated in modulating spacing and architectural arrangements of FtsZ filaments. While the majority of cell division proteins that directly bind to FtsZ engage either the polymerization domain or the C-terminal interaction site, ClpX, the recognition and unfolding component of the bacterial ClpXP proteasome, has a secondary interaction with the predicted intrinsically disordered region (IDR) of FtsZ when FtsZ is polymerized. Here, we use NMR spectroscopy and reconstituted degradation reactions in vitro to demonstrate that this linker region is indeed disordered in solution and, further, that amino acids in the IDR of FtsZ enhance the degradation by conformationally-guided interactions.
Dissociable developmental trajectories of Orbitofrontal subregion grey matter volume
Authors: Gibbons S. G. , Noonan M. P. 
Published: January 2021

AbstractAdolescence is a period of development which is characterised by distinct differences in decision-making strategies relative to adults. While it is broadly established that there are relative differences in the structural maturation of the prefrontal cortex (PFC) and subcortical reward nuclei, such as the amygdala and ventral striatum, heterogeneitywithinthe PFC is often neglected. In particular very little is known about the fine-scale gray matter (GM) development of the Orbitofrontal Cortex (OFC), itself critical to a number of learning and decision-making mechanisms which show delayed development trajectories. Here we applied voxel-based morphometry to examine subregional differences in OFC grey matter in high-quality structural MRI scans of 125 subjects aged 11-35yrs from the Human Connectome Project. First, we examined fine-scale GM maturation in 5 anatomically dissociable OFC subregions and identified the best-fitting polynomial model. Next, we directly compared developmental trajectories across 3 functionally dissociable subregions, revealing a complex topological developmental profile from medial to lateral subregions. Collectively, the two complementary analyses suggest that while unequivocally the phylogenetically younger lateral OFCs showed the greatest shift in GM volume across adolescence, with maturation continuing well into young adulthood, the differences between the medial and central OFC subregions suggested a more complex pattern of maturation than a simple graded medial to lateral topological development. We argue that knowledge of these fine-scale anatomical differences in maturation could explain precise mechanistic differences in goal-directed behaviours.