bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sex-specific Associations Between Traumatic Experiences and Resting-state Functional Connectivity in the Philadelphia Neurodevelopmental Cohort
Authors: Wang Shiying , Malins Jeffrey G. , Zhang Heping , Gruen Jeffrey R. 
Published: December 2020

AbstractBackgroundTraumatic experiences during childhood or adolescence are a significant risk factor for multiple psychiatric disorders and adversely affect cognitive functions. Resting-state functional magnetic resonance imaging has been used to investigate the effects of traumatic experiences on functional connectivity, but the impact of sex differences has not been well documented. This study investigated sex-specific associations between resting-state functional connectivity and traumatic experiences in typically developing youth.MethodsThe sample comprised 1395 participants, ages 8 to 21 years, from the Philadelphia Neurodevelopmental Cohort. Resting-state functional connectivity was characterized by voxel-wise intrinsic connectivity distribution parameter values derived from resting-state functional magnetic resonance imaging. Traumatic experiences were assessed based on a structured psychiatric evaluation. Sex, the number of traumatic events, and their interaction were regressed onto voxel-wise intrinsic connectivity distribution parameter values. Brain regions that passed cluster correction were used as seeds to define resting-state networks.ResultsAfter quality control, the final sample included 914 participants (mean (SD) age, 14.6 (3.3) years; 529 (57.8%) females; 437 (47.8%) experienced at least one kind of traumatic event). Four discrete anatomical clusters showed decreased functional connectivity as the number of traumatic events increased. The resting-state networks defined by using these four clusters as seeds corresponded with the somatomotor network. Sex-specific associations were identified in another four clusters for which males showed increased connectivity, and females showed decreased connectivity as the number of traumatic events increased. The resting-state networks defined by the four sex-specific clusters corresponded with the default mode network.ConclusionsTraumatic experiences are associated with an alteration of resting-state functional connectivity in the somatomotor network in youth without psychiatric diagnoses. The associations differ in direction between males and females in the default mode network, suggesting sex-specific responses to early exposure to trauma.
KLF17 promotes human naïve pluripotency but is not required for its establishment
Authors: Lea Rebecca A. , McCarthy Afshan , Boeing Stefan , Niakan Kathy K. 
Published: December 2020

AbstractCurrent knowledge of the transcriptional regulation of human pluripotency is incomplete, with lack of inter-species conservation observed. Single-cell transcriptomics of human embryos previously enabled us to identify transcription factors, including the zinc-finger protein KLF17, that are enriched in the human epiblast and naïve hESCs. Here we show that KLF17 is expressed coincident with the known pluripotency factors NANOG and SOX2 across human blastocyst development. We investigate the function of KLF17 in pluripotency using primed and naïve hESCs for gain- and loss-of-function analyses. We find that ectopic expression of KLF17 in primed hESCs is sufficient to induce a naïve-like transcriptome and that KLF17 can drive transgene-mediated resetting to naïve pluripotency. This implies a role for KLF17 in establishing naïve pluripotency. However, CRISPR-Cas9-mediated knockout studies reveal that KLF17 is not required for naïve pluripotency acquisitionin vitro. Transcriptome analysis of naïve hESCs identifies subtle effects on metabolism and signalling following KLF17 loss of function, and possible redundancy with the related factor, KLF5. Overall, we show that KLF17 is sufficient, but not necessary, for naïve pluripotency under the givenin vitroconditions.Summary statementInvestigating KLF17 in human pluripotency reveals that it is sufficient, but not necessary, to establish naïve hESCs. We posit that KLF17 is a peripheral regulator, like KLF2 in the mouse.
The Hard Limits of Decoding Mental States: The Decodability of fMRI
Authors: Jabakhanji R. , Vigotsky A.D. , Bielefeld J. , Huang L. , Baliki M.N. , Iannetti G.D. , Apkarian A.V. 
Published: December 2020

SUMMARYHigh-profile studies claim to assess mental states across individuals using multi-voxel decoders of brain activity. The fixed, fine-grained, multi-voxel patterns in these “optimized” decoders are purportedly necessary for discriminating between, and accurately identifying, mental states. Here, we present compelling evidence that the efficacy of these decoders is overstated. Across a variety of tasks, decoder patterns were not necessary. Not only were “optimized decoders” spatially imprecise and 90% redundant, but they also performed similarly to simpler decoders, built from average brain activity. We distinguish decoder performance when used for discriminating between, in contrast to identifying, mental states, and show even when discrimination performance is strong, identification can be poor. Using similarity rules, we derived novel and intuitive discriminability metrics that capture 95% and 68% of discrimination performance within- and across-subjects, respectively. These findings demonstrate that current across-subject decoders remain inadequate for real-life decision making.
Machine Leaning-based Determination of Sampling Depth for Complex Environmental Systems: Case Study with Single-Cell Raman Spectroscopy Data in EBPR Systems
Authors: Li Guangyu , Wu Chieh , Wang Dongqi , Srinivasan Varun , Kaeli David R. , Dy Jennifer G. , Gu April Z. 
Published: December 2020

ABSTRACTRapid progress in various advanced analytical methods such as single-cell technologies enable unprecedented and deeper understanding of microbial ecology beyond the resolution of conventional approaches. A major application challenge exists in the determination of sufficient sample size without sufficient prior knowledge of the community complexity and, the need to balance between statistical power and limited time or resources. This hinders the desired standardization and wider application of these technologies. Here, we proposed, tested and validated a computational sampling size assessment protocol taking advantage of a metric, named kernel divergence. This metric has two advantages: First, it directly compares dataset-wise distributional differences with no requirements on human intervention or prior knowledge-based pre-classification. Second, minimal assumptions in distribution and sample space are made in data processing to enhance its application domain. This enables test-verified appropriate handling of datasets with both linear and non-linear relationships. The model was then validated in a case study with eight SCRS phenotyping datasets each sampled from a different enhanced biological phosphorus removal (EBPR) activated sludge community located across North America. The model allows the determination of sufficient sampling size for any targeted or customized information capture capacity or resolution level. For example, an approximated sampling size of 50 or 100 spectra for full-scale EBPR-related ecosystems at 5% or 2% OPU cluster resolution. Promised by its flexibility and minimal restriction of input data types, the proposed method is expected to be a standardized approach for sampling size optimization, enabling more comparable and reproducible experiments and analysis on complex environmental samples. Finally, these advantages exhibit the capability of generalizing to other single-cell technologies or environmental applications, provided that the input datasets contain only continuous features.TOC
SARS-CoV-2 escapes CD8 T cell surveillance via mutations in MHC-I restricted epitopes
Authors: Agerer Benedikt , Koblischke Maximilian , Gudipati Venugopal , Smyth Mark , Popa Alexandra , Genger Jakob-Wendelin , Endler Lukas , Florian David M. , Mühlgrabner Vanessa , Lercher Alexander , Gattinger Pia , Torralba-Gombau Ricard , Penz Thomas , Fae Ingrid , Wenda Sabine , Traungott Marianna , Walder Gernot , Fischer Gottfried , Hoepler Wolfgang , Pawelka Erich , Zoufaly Alexander , Valenta Rudolf , Bock Christoph , Huppa Johannes B. , Aberle Judith H. , Bergthaler Andreas 
Published: December 2020

AbstractCD8+ T cell immunity to SARS-CoV-2 has been implicated in COVID-19 severity and virus control, though direct evidence has been lacking so far. Here, we identified non-synonymous mutations in MHC-I restricted CD8+ T cell epitopes after deep sequencing of 747 SARS-CoV- 2 virus isolates. Mutant peptides exhibited diminished or abrogated MHC-I binding, which was associated with a loss of recognition and functional responses by CD8+ T cells isolated from HLA-matched COVID-19 patients. Our findings highlight the capacity of SARS-CoV-2 to subvert CD8+ T cell surveillance through escape mutations in MHCI-restricted viral epitopes. This provides evolutionary evidence for CD8+ T cell immunity controlling SARS-CoV-2 with consequences for COVID-19 vaccine design.
Reliability of neural entrainment in the human auditory system
Authors: Cabral-Calderin Yuranny , Henry Molly J. 
Published: December 2020

AbstractAuditory stimuli are often rhythmic in nature. Brain activity synchronizes with auditory rhythms via neural entrainment, and entrainment seems to be beneficial for auditory perception. However, it is not clear to what extent neural entrainment in the auditory system is reliable over time – a necessary prerequisite for targeted intervention. The current study aimed to establish the reliability of neural entrainment over time and to predict individual differences in auditory perception from associated neural activity. Across two different sessions, human listeners detected silent gaps presented at different phase locations of a 2-Hz frequency modulated (FM) noise while EEG activity was recorded. As expected, neural activity was entrained by the 2-Hz FM noise. Moreover, gap detection was sinusoidally modulated by the phase of the 2-Hz FM into which the gap fell. Critically, both the strength of neural entrainment as well as the modulation of performance by the stimulus rhythm were highly reliable over sessions. Moreover, gap detection was predictable from pre-gap neural 2-Hz phase and alpha amplitude. Our results demonstrate that neural entrainment in the auditory system and the resulting behavioral modulation are reliable over time, and that both entrained delta and non-entrained alpha oscillatory activity contribute to near-threshold stimulus perception. The latter suggests that improving auditory perception might require simultaneously targeting entrained brain rhythms as well as the alpha rhythm.
Early IFNβ secretion determines variable downstream IL-12p70 responses upon TLR4 activation in health and disease
Authors: Posseme Celine , Llibre Alba , Charbit Bruno , Bondet Vincent , Rouilly Vincent , Saint-André Violaine , Boussier Jeremy , Bergstedt Jacob , Smith Nikaïa , Rotival Maxime , Kobor Michael S , Scriba Tom , Mottez Estelle , Pol Stanislas , Patin Etienne , Albert Matthew L. , Quintana-Murci Lluis , Duffy Darragh ,   Milieu Intérieur Consortium
Published: December 2020

SummaryThe IL-12 family of cytokines comprises the only heterodimeric cytokines mediating diverse functional effects. We previously observed a bi-modal IL-12p70 response to LPS in healthy donors of theMilieu Interieurcohort. Herein, we demonstrate that IFNβ expression serves as an upstream determinant of variable IL-12p70 production. Integrative modelling of proteomic, genetic, epigenomic and cellular data confirmed IFNβ as key for regulation of LPS inducedIL12Aand IL-12p70 variability. The clinical relevance was supported by reduced and variable IL-12p70 responses in individuals infected with the hepatitis C virus (HCV), and findings that IFN-based therapy for HCV is more likely to fail in those patients with dysregulated pre-treatment IL-12p70 responses. In sum, our systems immunology approach has defined a better understanding of IL-12p70 and IFNβ in healthy and infected persons, providing insights into how common genetic and epigenetic variation may impact immune responses to bacterial infection in health and disease.
LungAI: A Deep Learning Convolutional Neural Network for Automated Detection of COVID-19 from Posteroanterior Chest X-Rays
Authors: Gulati Aryan 
Published: December 2020

AbstractCOVID-19 is an infectious disease caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). As of December 2020, more than 72 million cases have been reported worldwide. The standard method of diagnosis is by Real-Time Reverse Transcription Polymerase Chain Reaction (rRT-PCR) from a Nasopharyngeal Swab. Currently, there is no vaccine or specific antiviral treatment for COVID-19. Due to rate of spreading of the disease manual detection among people is becoming more difficult because of a clear lack of testing capability. Thus there was need of a quick and reliable yet non-labour intensive detection technique. Considering that the virus predominantly appears in the form of a lung based abnormality I made use of Chest X-Rays as our primary mode of detection. For this detection system we made use of Posteroanterior (PA) Chest X-rays of people infected with Bacterial Pneumonia (2780 Images), Viral Pneumonia (1493 Images), Covid-19 (729 Images) as well as those of perfectly Healthy Individuals (1583 Images) procured from various Publicly Available Datasets and Radiological Societies. LungAI is a novel Convolutional Neural Network based on a Hybrid of the DarkNet and AlexNet architecture. The network was trained on 80% of the dataset with 20% kept for validation. The proposed Coronavirus Detection Model performed exceedingly well with an accuracy of 99.16%, along with a Sensitivity value of 99.31% and Specificity value of 99.14%. Thus LungAI has the potential to prove useful in managing the current Pandemic Situation by providing a reliable and fast alternative to Coronavirus Detection given strong results.
From SARS-CoV-2 infection to COVID-19 disease: a proposed mechanism for viral spread to the lower airway based on in silico estimation of virion flow rates
Authors: Basu Saikat , Chakravarty Arijit 
Published: December 2020

ABSTRACTWhile the nasopharynx in the upper respiratory airway is the dominant initial infection site for SARS-CoV-2, the physiologic mechanism that launches the infection in the lower airway is still not well-understood. Based on the rapidity with which SARS-CoV-2 infection progresses to the lungs, it has been conjectured that the nasopharynx acts as the seeding zone for subsequent contamination of the lower airway via aspiration of virus-laden boluses of nasopharyngeal fluids. In this study, we examine the plausibility of this proposed mechanism. To this end, we have developed computational fluid mechanics models of the inhalation process in two medical imaging based airway reconstructions and have quantified the nasopharyngeal liquid volume ingested into the lower airspace during each aspiration. The numerical predictions are validated by comparing the number of projected aspirations (approximately 2 – 4) during an eight-hour sleep cycle with prior observational findings of 3 aspirations in human subjects. Extending the numerical trends on aspiration volume to earlier records on aspiration frequency for the entire day indicates a total aspirated nasopharyngeal liquid volume of 0.3 – 0.76 ml per day. We then used sputum assessment data from hospitalized COVID-19 patients to estimate the number of virions that are transmitted daily to the lungs via nasopharyngeal liquid boluses. For mean sputum viral load, our modeling projects that the number of virions penetrating to the lower airway per day will range over 2.1 × 106 – 5.3 × 106; for peak viral load, the corresponding number of penetrating virions hovers between 7.1 × 108 – 17.9 × 108. These findings fill in a key piece of the mechanistic puzzle of the progression from SARS-CoV-2 infection of the nasopharynx to the development of COVID-19 disease within a patient, and point to dysphagia as a potential underlying risk factor for COVID-19. The findings also have significant practical implications in the design of COVID-19 prophylactics and therapeutics that aim to constrain the pathogenic progress of the disease within the limits of the upper airway.
Anti-cancer Potential ofMoringa oleiferaon BRCA1 Gene: Systems Biology
Authors: Balogun Toheeb A. , Buliaminu Kaosarat D. , Chukwudozie Onyeka S. , Tiamiyu Zainab A 
Published: December 2020

ABSTRACTBreast Cancer has always been a global challenge that is prevalent among women. There is a continuous increase in the high number of women mortality rates as a result of breast cancer and affecting countries at all levels of modernization. Women with high-risk factors including hereditary, obesity, and menopause have the possibility of developing breast cancer. With the advent of radiotherapy, chemotherapy, hormone therapy, and surgery in the treatment of breast cancer, there has an increased number of breast cancer survivors. Also, the design and development of drugs targeting therapeutic enzymes are helping to effectively treat the tumor cells at an early stage. However, long term use of anti-cancer drugs has been linked to severe side effects. This research aims to develop potential drug candidates fromMoringa oleiferawhich could serve as anti-cancer agents.In silicoanalysis using Schrödinger Molecular Drug Discovery Suite and SWISS ADME was employed to determine the therapeutic potential of phytochemicals fromM. oleiferaagainst breast cancer via molecular docking, pharmacokinetic parameters, and drug-like properties. The result shows that Rutin, Vicenin-2, and Quercetin-3-O-glucoside have the highest binding energy of −7.522, −6.808, −6.635kcal/mol respectively in the active site of BRCA1. The essential amino acids involved in the protein-ligand interaction following active site analysis are ASN 1678, ASN 1774, GLY 1656, LEU 1657, GLN 1779, LYS 1702, SER 1655, PHE 1662, ARG 1699, GLU 1698, and VAL 1654. Thus, we propose that bioactive compounds fromM. oleiferamay be potential hit drug candidates against breast cancer.
TWO CLASSES OF MYOSIN INHIBITORS, BLEBBISTATIN AND MAVACAMTEN, STABILIZE β-CARDIAC MYOSIN IN DIFFERENT STRUCTURAL AND FUNCTIONAL STATES
Authors: Gollapudi Sampath K. , Ma Weikang , Chakravarthy Srinivas , Combs Ariana C. , Sa Na , Langer Stephen , Irving Thomas C. , Nag Suman 
Published: December 2020

ABSTRACTIn addition to a conventional relaxed state, a fraction of myosins in the cardiac muscle exists in a newly-discovered low-energy consuming super-relaxed (SRX) state, which is kept as a reserve pool that may be engaged under sustained increased cardiac demand. The conventional and the super-relaxed states are widely assumed to correspond respectively to a structure where myosin heads are in anopenconfiguration, free to interact with actin, and aclosedconfiguration, inhibiting binding to actin. Disruption of the SRX population in different heart diseases, such as hypertrophic cardiomyopathy, results in unwarranted muscle contraction, and stabilizing them using myosin inhibitors is budding as an attractive therapeutic strategy. Here we examine the structure-function relationships of two myosin ATPase inhibitors, mavacamten, and blebbistatin, and found that binding of mavacamten to myosin at a site different than blebbistatin populates myosin into the SRX state. Blebbistatin, and para-nitroblebbistatin, binding to a distal pocket to the myosin lever arm near the nucleotide-binding site, does not affect the usual myosin SRX state but instead appears to render myosin into a new, perhaps non-functional, ‘ultra-relaxed’ state. X-ray scattering-based rigid body modeling shows that both mavacamten and para-nitroblebbistatin induce novel conformations that diverge significantly from the hypotheticalopenandclosedstates and furthermore, mavacamten treatment causes a greater compaction than para-nitroblebbistatin. Taken together, we conclude that mavacamten and blebbistatin stabilize myosin in different structural states, and such states may give rise to different functional energy-sparing SRX states.
Identification of NPC1 as a novel SARS-CoV-2 intracellular target
Authors: Garcia-Dorival Isabel , Ángel Cuesta-Geijo Miguel , Barrado-Gil Lucía , Galindo Inmaculada , Urquiza Jesús , del Puerto Ana , Gil Carmen , Campillo Nuria , Martínez Ana , Alonso Covadonga 
Published: December 2020

AbstractNiemann-Pick type C1 (NPC1) receptor is an endosomal membrane protein that regulates intracellular cholesterol trafficking, which is crucial in the Ebola virus (EBOV) cycle. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) enters the cell by binding of the viral spike (S) protein to the ACE2 receptor. This requires S-protein processing either by the surface transmembrane serine protease TMPRSS2 for plasma membrane fusion or cathepsin L for endosomal entry. Additional host factors are required for viral fusion at endosomes. Here, we report a novel interaction of the SARS-CoV-2 nucleoprotein (N) with the cholesterol transporter NPC1. Moreover, small molecules interfering with NPC1 that inhibit EBOV entry, also inhibited human coronavirus. Our findings suggest an important role for NPC1 in SARS-CoV-2 infection, a common strategy shared with EBOV, and a potential therapeutic target to fight against COVID-19.
Placing ancient DNA sequences into reference phylogenies
Authors: Martiniano Rui , De Sanctis Bianca , Hallast Pille , Durbin Richard 
Published: December 2020

AbstractDuring the last decade, large volumes of ancient DNA (aDNA) data have been generated as part of whole-genome shotgun and target capture sequencing studies. This includes sequences from non-recombining loci such as the mitochondrial or Y chromosomes. However, given the highly degraded nature of aDNA data, post-mortem deamination and often low genomic coverage, combining ancient and modern samples for phylogenetic analyses remains difficult. Without care, these factors can lead to incorrect placement.For the Y chromosomes, current standard methods focus on curated markers, but these contain only a subset of the total variation. Examining all polymorphic markers is particularly important for low coverage aDNA data because it substantially increases the number of overlapping sites between present-day and ancient individuals which may lead to higher resolution phylogenetic placement. We provide an automated workflow for jointly analysing ancient and present-day sequence data in a phylogenetic context. For each ancient sample, we effectively evaluate the number of ancestral and derived alleles present on each branch and use this information to place ancient lineages to their most likely position in the phylogeny. We provide both a parsimony approach and a highly optimised likelihood-based approach that assigns a posterior probability to each branch.To illustrate the application of this method, we have compiled and make available the largest public Y-chromosomal dataset to date (2,014 samples) which we used as a reference for phylogenetic placement. We process publicly available African ancient DNA Y-chromosome sequences and examine how patterns of Y-chromosomal diversity change across time and the relationship between ancient and present-day lineages. The same software can be used to place samples with large amounts of missing data into other large non-recombining phylogenies such as the mitochondrial tree.