bluuebunny/crossref_metadata_2025_split huggingface dataset:
Learning directed acyclic graphs for ligands and receptors based on spatially resolved transcriptomic analysis of ovarian cancer
Authors: Chowdhury Shrabanti , Ferri-Borgogno Sammy , Calinawan Anna P , Yang Peng , Wang Wenyi , Peng Jie , Mok Samuel C , Wang Pei 
Published: August 2021

AbstractTo unravel the mechanism of immune activation and suppression within tumors, a critical step is to identify transcriptional signals governing cell-cell communication between tumor and immune/stromal cells in the tumor microenvironment. Central to this communication are interactions between secreted ligands and cell-surface receptors, creating a highly connected signaling network among cells. Recent advancement in in situ-omics profiling, particularly spatial transcriptomic (ST) technology, provide unique opportunities to directly characterize ligand-receptor signaling networks that powers cell-cell communication. In this paper, we propose a novel statistical method,LRnetST, to characterize the ligand-receptor interaction networks between adjacent tumor and stroma cells based on ST data.LRnetSTutilizes a directed acyclic graph (DAG) model with a novel treatment to handle the zero-inflated distribution observed in the ST data. It also leverages existing ligand-receptor regulation databases as prior information, and employs a bootstrap aggregation strategy to achieve robust network estimation. Application ofLRnetSTto ST data of high-grade serous ovarian tumor samples revealed both common and distinct ligand-receptor regulations across different tumors. Some of these interactions were validated through a MERFISH data set of independent ovarian tumor samples. These results cast light on biological processes relating to the communication between tumor and immune/stromal cells in ovarian tumors. An open-source R package ofLRnetSTis available on GitHub athttps://github.com/jie108/LRnetST.
A flux-based machine learning model to simulate the impact of pathogen metabolic heterogeneity on drug interactions
Authors: Chung Carolina H. , Chandrasekaran Sriram 
Published: August 2021

AbstractDrug combinations are a promising strategy to counter antibiotic resistance. However, current experimental and computational approaches do not account for the entire complexity involved in combination therapy design, such as the effect of pathogen metabolic heterogeneity, changes in the growth environment, drug treatment order and time interval. To address these limitations, we present a comprehensive approach that uses genome-scale metabolic modeling and machine learning to guide combination therapy design. Our mechanistic approach (a) accommodates diverse data types, (b) accounts for time- and order-specific interactions, and (c) accurately predicts drug interactions in various growth conditions and their robustness to pathogen metabolic heterogeneity. Our approach achieved high accuracy (AUC = 0.83 for synergy, AUC = 0.98 for antagonism) in predicting drug interactions forE. colicultured in 57 metabolic conditions based on experimental validation. The entropy in bacterial metabolic response was predictive of combination therapy outcomes across time scales and growth conditions. Simulation of metabolic heterogeneity using population FBA identified two sub-populations ofE. colicells defined by the levels of three proteins (eno, fadB and fabD) in glycolysis and lipid metabolism that influence cell tolerance to a broad range of antibiotic combinations. Analysis of the vast landscape of condition-specific drug interactions revealed a set of 24 robustly synergistic drug combinations with potential for clinical use.SignificanceWorldwide, 700,000 people die each year from drug-resistant infections. Drug combinations have great potential to reduce the spread of drug-resistant bacteria. However, their potency is impacted by both the pathogen growth environment and the heterogeneity in pathogen metabolism. The metabolic heterogeneity in a pathogen population allows them to survive antibiotic treatment. Here we present a flexible machine-learning framework that utilizes diverse data types to effectively search through the large design space of both sequential and simultaneous combination therapies across hundreds of simulated growth conditions and pathogen metabolic states. Our approach can serve as a useful guide for the selection of robustly synergistic drug combinations.
The amyloid concentric β-barrel hypothesis: Models of amyloid beta 42 oligomers and annular protofibrils
Authors: Durell Stewart R. , Kayed Rakez , Guy H. Robert 
Published: August 2021

AbstractAmyloid beta (Aβ) peptides, a major contributor to Alzheimers disease, occur in differing lengths, each of which forms a multitude of assembly types. The most toxic soluble oligomers are formed by Aβ42; some of which have antiparallel β-sheets. Previously, our group proposed molecular models of Aβ42 hexamers in which the C-terminus third of the peptide (S3) forms an antiparallel 6-stranded β-barrel that is surrounded by an antiparallel barrel formed by the more polar N-terminus (S1) and middle (S2) portions. These hexamers were proposed to act as seeds from which dodecamers, octadecamers, both smooth and beaded annular protofibrils, and transmembrane channels form. Since then, numerous aspects of our models have been supported by experimental findings. Recently, NMR-based structures have been proposed for Aβ42 tetramers and octamers, and NMR studies have been reported for oligomers composed of ~ 32 monomers. Here we propose a range of concentric β-barrel models and compare their dimensions to image-averaged electron micrographs of both beaded annular protofibrils (bAPFs) and smooth annular protofibrils (sAPFs) of Aβ42. The smaller oligomers have 6, 8, 12, 16, and 18 monomers. These beads string together to form necklace-like bAPFs. These gradually morph into sAPFs in which a S3 β-barrel is shielded on one or both sides by β-barrels formed from S1 and S2 segments.
Synaptic plasticity is predicted by spatiotemporal firing rate patterns and robust to in vivo-like variability
Authors: Dorman Daniel B. , Blackwell Kim T. 
Published: August 2021

AbstractSynaptic plasticity, the experience-induced change in connections between neurons, underlies learning and memory in the brain. Most of our understanding of synaptic plasticity derives from in vitro experiments with precisely repeated stimulus patterns; however, neurons exhibit significant variability in vivo during repeated experiences. Further, the spatial pattern of synaptic inputs to the dendritic tree influences synaptic plasticity, yet is not considered in most synaptic plasticity rules. Here, we address the sensitivity of plasticity to trial-to-trial variability and delineate how spatiotemporal synaptic input patterns produce plasticity with in vivo-like conditions using a data-driven computational model with a calcium-based plasticity rule. Using in vivo spike train recordings as inputs, we show that plasticity is strongly robust to trial-to-trial variability of spike timing, and derive general synaptic plasticity rules describing how spatiotemporal patterns of synaptic inputs control the magnitude and direction of plasticity. Specifically, a high temporal input firing rate to a synapse late in a trial correlated with neighboring synaptic activity produces potentiation, while an earlier, moderate firing rate that is negatively correlated with neighboring synaptic activity produces depression. Together, our results reveal that calcium dynamics can unify diverse plasticity rules and reveal how spatiotemporal firing rate patterns control synaptic plasticity.
The decoy SNARE Tomosyn sets tonic versus phasic release properties and is required for homeostatic synaptic plasticity
Authors: Sauvola Chad W. , Akbergenova Yulia , Cunningham Karen L. , Aponte-Santiago Nicole A. , Littleton J. Troy 
Published: August 2021

SummarySynaptic vesicle release probability (Pr) is a key presynaptic determinant of synaptic strength established by cell intrinsic properties and further refined by plasticity. To characterize mechanisms that generate Pr heterogeneity between distinct neuronal populations, we examined glutamatergic tonic (Ib) and phasic (Is) motoneurons in Drosophila with stereotyped differences in Pr and synaptic plasticity. We found the decoy SNARE Tomosyn is differentially expressed between these motoneuron subclasses and contributes to intrinsic differences in their synaptic output. Tomosyn expression enables tonic release in Ib motoneurons by reducing SNARE complex formation and suppressing Pr to generate decreased levels of synaptic vesicle fusion and enhanced resistance to synaptic fatigue. In contrast, phasic release dominates when Tomosyn expression is low, enabling high intrinsic Pr at Is terminals at the expense of sustained release and robust presynaptic potentiation. In addition, loss of Tomosyn disrupts the ability of tonic synapses to undergo presynaptic homeostatic potentiation (PHP).
A pathogenic DYT-THAP1 dystonia mutation causes hypomyelination and loss of YY1 binding
Authors: Yellajoshyula Dhananjay , Rogers Abigail E. , Kim Audrey J. , Kim Sumin , Pappas Samuel S. , Dauer William T. 
Published: August 2021

AbstractDystonia is a disabling disease that manifests as prolonged involuntary twisting movements. DYT-THAP1 is an inherited form of isolated dystonia caused by mutations in THAP1 encoding the transcription factor THAP1. The phe81leu (F81L) missense mutation is representative of a category of poorly understood mutations that do not occur on residues critical for DNA binding. Here, we demonstrate that the F81L mutation (THAP1F81L) impairs THAP1 transcriptional activity and disrupts CNS myelination. Strikingly, THAP1F81L exhibits normal DNA binding but causes a significantly reduced DNA binding of YY1, its transcriptional partner that also has an established role in oligodendrocyte lineage progression. Our results suggest a model of molecular pathogenesis whereby THAP1F81L normally binds DNA but is unable to efficiently organize an active transcription complex.
Pediatric SARS-CoV-2 seroprevalence in Arkansas over the first year of the COVID-19 pandemic
Authors: Boehme Karl W. , Kennedy Joshua L. , Snowden Jessica , Owens Shana M. , Kouassi Marianne , Mann Ryan L. , Paredes Amairani , Putt Claire , James Laura , Jin Jing , Du Ruofei , Kirkpatrick Catherine , Modi Zeel , Caid Katherine , Zohoori Namvar , Kothari Atul , Boyanton Bobby L. , Forrest J. Craig 
Published: August 2021

ABSTRACTBackgroundSARS-CoV-2 seroprevalence studies have largely focused on adults but little is known about spread in children. We determined SARS-CoV-2 seroprevalence in children and adolescents from Arkansas over the first year of the COVID-19 pandemic.MethodsWe tested remnant serum samples from children from 1–18 years who visited Arkansas hospitals or clinics for non-COVID19-related reasons from April, 2020 through April, 2021 for SARS-CoV-2 antibodies. We used univariable and multivariable regression models to determine association between seropositivity and participant characteristics.ResultsAmong 2400 participants, seroprevalence rose from 7.9% in April/May 2020 (95% CI, 4.9-10.9%) to 25.8% in April 2021 (95% CI, 22.2-29.3%). Hispanic and black children had a significantly higher association with antibody positivity than white children in multiple sampling periods.ConclusionsBy spring 2021, most children in Arkansas had not been infected with SARS-CoV-2. With the emergence of SARS-CoV-2 variants, recognition of long-term effects of COVID-19, and the lack of an authorized pediatric SARS-CoV-2 vaccine, these results highlight the importance of including children in SARS-CoV-2 public health, clinical care, and research strategies. These findings are important for state and local officials as they consider measures to limit SARS-CoV-2 spread in schools and daycares for the 2021–2022 school year.
Strategies to Estimate Prevalence of SARS-CoV-2 Antibodies in a Texas Vulnerable Population: Results from Phase I of the Texas Coronavirus Antibody REsponse Survey (TX CARES)
Authors: Valerio-Shewmaker Melissa , DeSantis Stacia , Swartz Michael , Yaseen Ashraf , Gonzalez Michael O. , Kohl Harold W. , Kelder Steven H. , Messiah Sarah E. , Aguillard Kimberly A. , Breaux Camille , Wu Leqing , Shuford Jennifer , Pont Stephen , Lakey David , Boerwinkle Eric 
Published: August 2021

AbstractIntroductionSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and immunity remains uncertain in populations. The state of Texas ranks 2ndin infection with over 2.71 million cases and has seen a disproportionate rate of death across the state. The TX CARES project was funded by the state of Texas to estimate the prevalence of SARS-CoV-2 antibody status in children and adults.Materials and MethodsThe TX CARES (Texas Coronavirus Antibody Response Survey) is an ongoing prospective population-based convenience sample from the Texas general population that commenced in October 2020. Volunteer participants are recruited across the state to participate in a 3-time point data collection TX CARES to assess antibody response over time. We use the Roche Elecsys® Anti-SARS-CoV-2 Immunoassay to determine SARS-CoV-2 antibody status.ResultsThe crude antibody positivity prevalence in Phase I was 26.1% (80/307). The fully adjusted seroprevalence of the sample was 31.5%. Specifically, 41.1% of males and 21.9% of females were seropositive. For age categories, 33.5% of those 18-34; 24.4% of those 35-44; 33.2% of those 45-54; and 32.8% of those 55+ were seropositive. In this sample,42.2% (89/211) of those negative for the antibody test reported having had a COVID-19 test.ConclusionsIn this survey we enrolled and analyzed data for 319 participants, demonstrating a high survey and antibody test completion rate, and ability to implement a questionnaire and SARS-CoV-2 antibody testing within FQHC clinical settings. We were also able to determine our capability to estimate the cross-sectional seroprevalence within Texas’s FQHC clinical settings. The crude positivity prevalence for SARS-CoV-2 antibodies in this sample was 26.1% indicating potentially high exposure to COVID-19 for FQHC clinic employees and patients. These methods are being used to guide the completion of a large longitudinal survey in the state of Texas with implications for practice and population health.
Perceived racial discrimination and eating habits: Systematic review and conceptual models
Authors: Rodrigues Ylana Elias , Fanton Marcos , Novossat Ricardo Suñé , Canuto Raquel 
Published: August 2021

AbstractContextthere is no systematic organization of the available evidence about the relationship between racial discrimination and eating habits. Also, there is no consensus about its causal mechanism.Objectivesa systematic review was conducted to synthesize evidence on the association between perceived racial discrimination and eating habits (eating behavior and food consumption). A conceptual model was developed to depict the most common mechanisms used to explain this association.Data Sourcesarticles and dissertations were retrieved from the PubMed, EMBASE, Lilacs, and PsycINFO databases from inception to January 2021.Data Analysis19 studies were included. The assessment of methodological quality was conducted using the Newcastle-Ottawa Scale. On average, the studies showed a methodological quality of 66%. Forty-six associations were evaluated. There were 38 associations between perceived racial discrimination and negative eating habits, 29 concerning eating behavior, and 17 regarding food consumption.Conclusionsperceived racial discrimination negatively affects eating habits. A broader conceptual framework based on ecosocial theory is suggested to guide future research that would include different racial discrimination dimensions, such as internalized and structural.
Distinctive neural correlates of phonological processing and reading impairment in fetal alcohol-exposed adolescents with and without facial dysmorphology
Authors: Yu Xi , Dunstan Jade , Jacobson Sandra W. , Molteno Christopher D. , Lindinger Nadine M. , Turesky Theodore K. , Meintjes Ernesta M. , Jacobson Joseph L. , Gaab Nadine 
Published: August 2021

AbstractBackgroundPrenatal alcohol exposure (PAE) has been linked to atypical brain development and a wide range of cognitive and behavioral impairments, including poor reading performance in childhood and adolescence. However, little is known about how structural and/or functional teratogenesis in the brain mediate reading impairment in fetal alcohol spectrum disorders (FASD) and whether neural correlates of reading and phonological processing differ between FASD subtypes with different clinical presentations in facial morphology.MethodsThe current study utilized functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) to characterize functional and structural mechanisms mediating reading deficits in 26 syndromal adolescents with PAE-related facial dysmorphology (i.e., fetal alcohol syndrome (FAS) or partial FAS (PFAS)) and 30 heavily exposed (HE) without this dysmorphology, in comparison with 19 typically developing controls. Importantly, the levels of PAE and reading ability were comparable between the FAS/PFAS and HE groups in the current study.ResultsCompared to the nonsyndromal HE and control groups, the syndromal adolescents showed greater activation in the right precentral gyrus during an fMRI phonological processing task and rightward lateralization in an important reading-related tract (inferior longitudinal fasciculus, ILF), suggesting an atypical reliance on the right hemisphere during reading. By contrast, in the HE group, better reading skills were associated with increased neural activation in the left angular gyrus (LAG) and higher fractional anisotropy in the white matter organization of the left ILF. However, the brain function-behavior relation was weaker in the HE than among the controls, suggesting less efficient function of the typical reading neural network that may contribute to the observed reading impairments.ConclusionsOur findings provide the first evidence for the distinctive functional and structural mechanisms underlying atypical reading and phonological processing in PAE adolescents with and without FAS facial dysmorphology.HighlightsPrenatal alcohol exposure is associated with altered neural reading networksFASD subtypes exhibit distinctive neural correlates of phonological processingGreater right-hemispheric reliance was observed in FASD with facial dysmorphologyNon-syndromal FASD showed deficits in the typical left-hemispheric reading network
Specific telomere protection ensured by FOXO3a upon genotoxic stress and during aging
Authors: Burbano Maria Sol Jacome , Robin Jérome , Bauwens Serge , Martin Marjorie , Donati Emma , Martínez Lucia , Sacconi Sabrina , Magdinier Frédérique , Gilson Eric 
Published: August 2021

AbstractLongevity is determined by diverse signaling pathways including telomere protection and homeostasis master regulators like FOXO3a. We previously showed that the telomeric repeat binding factor 2 (TRF2) expression decreases with age in human skeletal muscle and that, surprisingly, its loss in myofibers does not trigger telomere deprotection. We reveal here that inTERF2-compromised myotubes, FOXO3a is recruited to telomeres where it acts as a protective factor against ATM-dependent DNA damage activation. Moreover, we show that FOXO3a-telomere association increases with age in human skeletal muscle biopsies. In mitotic fibroblasts, the telomere protective properties of FOXO3a are operative if the cells are treated with bleomycin. The telomere function of FOXO3a does not require its Forkhead DNA binding domain but the CR2C. Overall, these findings demonstrate a direct connection between two key longevity pathways, FOXO3a and telomere protection. This unveils an unexpected higher level of integration in the regulation of longevity signaling pathway.
The role of Musashi-1 in CEP290 c.2991+1655A>G cryptic exon splicing in Leber Congenital Amaurosis
Authors: Ottaviani Daniele , Lane Amelia , Jovanovic Katarina , Gardner Jessica C. , Sladen Paul E. , Hau Kwan L. , Panes Anna Brugulat , Guarascio Rosellina , Hardcastle Alison J. , Cheetham Michael E. 
Published: August 2021

SUMMARYHuman photoreceptors maximise alternative exon splicing to generate a unique set of gene isoforms. Conversely, the inclusion of a cryptic exon caused by the c.2991+1655A>G deep intronic change in CEP290 occurs in the human retina leading to Leber Congenital Amaurosis (LCA10). The RNA-binding protein Musashi-1 (MSI1) is a key component of alternative splicing in the developing mouse retina. Here we investigated the role of MSI1 in human photoreceptor-specific splicing and its potential role in CEP290 aberrant splicing disease. Alternative splicing was studied using human induced pluripotent stem cell derived 3D retinal organoid and RPE RNA-seq datasets and several photoreceptor gene isoforms were identified. Their temporal expression was resolved in control 3D retinal organoids in comparison to development and differentiation markers. Morpholino knockdown of MSI1 in control retinal organoids reduced the expression of several photoreceptor differentiation markers and the inclusion of photoreceptor-specific exons. Nonetheless, MSI1 knockdown in homozygous CEP290 c.2991+1655A>G LCA10 retinal organoids did not affect the inclusion of the LCA10-associated cryptic exon. These results show that while MSI1 is important for photoreceptor alternative splicing and homeostasis, it is not a major driver of the recognition of the CEP290 cryptic splice site and the manifestation of LCA10.HIGHLIGHTS▪The human retina expresses a unique set of gene isoforms▪Musashi-1 regulates alternative splicing in 3D human retinal organoids▪Musashi-1 knockdown in 3D retinal organoids affects gene splicing and homeostasis in photoreceptors▪Musashi-1 may regulate alternative splicing of cryptic exons in retina but not in LCA10