bluuebunny/crossref_metadata_2025_split huggingface dataset:
Immunosequencing of the T-cell receptor repertoire reveals signatures specific for diagnosis and characterization of early Lyme disease
Authors: Greissl Julia , Pesesky Mitch , Dalai Sudeb C. , Rebman Alison W. , Soloski Mark J. , Horn Elizabeth J. , Dines Jennifer N. , Gittelman Rachel M. , Snyder Thomas M. , Emerson Ryan O. , Meeds Edward , Manley Thomas , Kaplan Ian M. , Baldo Lance , Carlson Jonathan M. , Robins Harlan S. , Aucott John N. 
Published: August 2021

ABSTRACTLyme disease, the most common tick-borne illness in the United States, is most frequently caused by infection withBorrelia burgdorferi. Although early antibiotic treatment can prevent development of severe illness and late manifestations, diagnosis is challenging in patients who do not present with a typical erythema migrans rash. To support a diagnosis of Lyme disease in such cases, guidelines recommend 2-tiered serologic testing. However, 2-tiered testing has numerous limitations, including ambiguity in interpretation and lower sensitivity in early disease. We developed a diagnostic approach for Lyme disease based on the T-cell response toB. burgdorferiinfection by immunosequencing T-cell receptor (TCR) repertoires in blood samples from 3 independent cohorts of patients with laboratory-confirmed or clinically diagnosed early Lyme disease, as well as endemic and non-endemic controls. We identified 251 public, Lyme-associated TCRs that were used to train a classifier for detection of early Lyme disease with 99% specificity. In a validation cohort of individuals with early Lyme disease, TCR testing demonstrated a 1.9-fold increase in sensitivity compared to standard 2-tiered testing (STTT; 56% versus 30%), with a 3.1-fold increase ≤4 days from the onset of symptoms (44% versus 14%). TCR positivity predicted subsequent seroconversion in 37% of initially STTT-negative patients, suggesting that the T-cell response is detectable before the humoral response. While positivity for both tests declined after treatment, greater declines in posttreatment sensitivity were observed for STTT compared to TCR testing. Higher TCR scores were associated with clinical measures of disease severity, including abnormal liver function test results, disseminated rash, and number of symptoms. A subset of Lyme-associated TCRs mapped toB. burgdorferiantigens, demonstrating high specificity of a TCR immunosequencing approach. These results support the clinical utility of T-cell‒based testing as a sensitive and specific diagnostic for early Lyme disease, particularly in the initial days of illness.
An age-depth model and revised stratigraphy of vertebrate-bearing units in Natural Trap Cave, Wyoming
Authors: Lovelace David M. , Redman Cory M. , Minckley Thomas A. , Schubert Blaine W. , Mahan Shannon , Wood John R. , McGuire Jenny L. , Laden Juan , Bitterman Kathleen , Heiniger Holly , Fenderson Lindsey , Cooper Alan , Mitchell Kieren J. , Meachen Julie A. 
Published: August 2021

ABSTRACTAlmost a half-century ago excavations at Natural Trap Cave (NTC) began to yield evidence of the steppe paleoecology along the western slope of the Bighorn Mountains in north central Wyoming. The first decade of fieldwork led to the discovery of a diverse fauna that existed at the end of the Last Glacial Maximum. Stratigraphic deposits below the entrance of the cave were studied soon after excavations began, but never formally published. Although stratigraphy, taphonomy, and depositional circumstances were briefly discussed over the following years, little has been done to correlate the numerous stratigraphic schemes used by various authors. In this study, four stratigraphic sections were measured and analysed to establish an easily modifiable lithostratigraphic system of nomenclature. We provide the first correlations of all stratigraphic nomenclature used throughout excavations at NTC to facilitate comparisons with current and previous collections and publications. By leveraging more than 100 radioisotopic dates we developed an age-depth model and chronostratigraphic framework to further interrogate spatiotemporal relationships between strata, paleoenvironmental proxies, and fossil assemblages. Deposition is shown to be discontinuous; sediment accumulation in the study area is restricted to the buildup through peak penultimate and Last Glacial maxima. More recent (<10 ka) Holocene deposits unconformably cover the eroded surface of underlying Pleistocene strata. There is active reworking of sediments with transport and deposition of reactivated sediments within the Lower Chamber. We note that the two hiatuses coincide with interglacial periods and may reflect changing depositional circumstances within the cave such as extended periods of non-deposition, erosion, or bypass (possibly leading to deposition in the Lower Chamber). Contrary to previous reports, we demonstrate that it is unlikely a prominent snow cone existed or contributed to the pattern of sediment and fossil distribution within the study area, furthermore, we do not observe a continuous Pleistocene-Holocene transition in the study area. Further stratigraphic work will be needed to better understand the interrelationship between Main and Lower chamber deposits and the evolution of sediment accumulation in NTC.
A new single-cell level R-index for EGFR-TKI resistance and survival prediction in LUAD
Authors: Xie Xiaohong , Li Lifeng , Xie Liang , Liu Zhentian , Gao Xuan , Xia Xuefeng , Deng Haiyi , Yang Yilin , Yang MeiLing , Chang Lianpeng , Yi Xin , He Zhiyi , Zhou Chengzhi 
Published: August 2021

ABSTRACTEGFR-TKIs achieved excellent efficacy in EGFR-mutated patients. Unfortunately, most patients would inevitably develop progressive disease within a median of 10 to 14 months. Predicting the resistance probability remains a challenge. Therefore, we created an R-index model trained by single-cell RNA data with the OCLR algorithm. This model can be applied to estimate the level of EGFR-TKI resistance in cell line and xenograft mice models and predict prognosis in multiple cohorts. Comparing the high and the low R-index group, we found that the glycolysis pathway and KRAS up-regulation pathway were related to resistance, and MDSC was the leading cause of immunosuppression in the tumor microenvironment. These results are consistent with previous studies indicating that the R-index provides an insight into resistance status and a new way to explore resistance mechanisms and clinical treatment by the combination of Glucose metabolism-targeted or MDSC-targeted therapies. This is the first quantification method of EGFR-TKI resistance based on single-cell sequencing data solving the problem of the mixed resistance state of tumor cells and helping explore transcriptome characteristics of drug-resistant cell populations.
Injury risk functions for the four primary knee ligaments
Authors: Nusia Jiota , Xu Jia-Cheng , Knälmann Johan , Sjöblom Reimert , Kleiven Svein 
Published: August 2021

ABSTRACTThe purpose of this study was to develop Injury Risk Functions (IRFs) for the Anterior- and Posterior Cruciate Ligament (ACL and PCL, respectively) and the Medial- and Lateral Collateral Ligament (MCL and LCL, respectively) in the knee joint. The IRFs were based on Post-Mortem Human Subject (PMHS) tensile failure strains of either Bone-Ligament-Bone (BLB) or dissected LIGament (LIG) preparations. Due to insufficient sample sizes of the experimental data points available in the current literature, statistically-generated failure strains (virtual values) based on the reported mean- and standard deviation were used to accommodate for the unprovided specimen-specific results. All virtual and specimen-specific values were then categorized into groups of static and dynamic rates, respectively, and tested for the best fitting theoretical distribution to derive a ligament IRF. Ten IRFs were derived (3 for ACL, 2 for PCL, 2 for MCL and 3 for LCL). These IRFs are, to the best of the authors’ knowledge, the first attempt of knee ligament injury prediction tools based on PMHS data. For future improvements of the knee ligament IRFs, upcoming experiments need comparable testing and strain measurements. More emphasis on a clear definition of failure and transparent reporting of each specimen-specific result is necessary.
Energy efficient network activity from disparate circuit parameters
Authors: Deistler Michael , Macke Jakob H. , Gonçalves Pedro J. 
Published: August 2021

AbstractNeural circuits can produce similar activity patterns from vastly different combinations of channel and synaptic conductances. These conductances are tuned for specific activity patterns but might also reflect additional constraints, such as metabolic cost or robustness to perturbations. How do such constraints influence the range of permissible conductances? Here, we investigate how metabolic cost affects the parameters of neural circuits with similar activity in a model of the pyloric network of the crab Cancer borealis. We use a novel machine learning method to identify a range of network models that can generate activity patterns matching experimental data, and find that neural circuits can consume largely different amounts of energy despite similar circuit activity. Furthermore, a reduced but still significant range of circuit parameters gives rise to energy-efficient circuits. We then examine the space of parameters of energy-efficient circuits and identify potential tuning strategies for low metabolic cost. Finally, we investigate the interaction between metabolic cost and temperature robustness. We show that metabolic cost can vary across temperatures, but that robustness to temperature changes does not necessarily incur an increased metabolic cost. Our analyses show that, despite metabolic efficiency and temperature robustness constraining circuit parameters, neural systems can generate functional, efficient, and robust network activity with widely disparate sets of conductances.
Asymmetrical adaptations to increases and decreases in environmental volatility
Authors: Xu Jie , Van Dam Nicholas T. , Luo Yuejia , Aleman André , Ai Hui , Xu Pengfei 
Published: August 2021

AbstractHumans adapt their learning strategies to changing environments by estimating the volatility of the reinforcement conditions. Here, we examine how volatility affects learning and the underlying functional brain organizations using a probabilistic reward reversal learning task. We found that the order of conditions was critically important; participants adjusted learning rate going from volatile to stable, but not from stable to volatile, environments. Subjective volatility of the environment was encoded in the striatal reward system and its dynamic connections with the prefrontal control system. Flexibility, which captures the dynamic changes of network modularity in the brain, was higher in the environmental transition from volatile to stable than from stable to volatile. These findings suggest that behavioral adaptations and dynamic brain organizations in transitions between stable and volatile environments are asymmetric, providing critical insights into the way that people learn under uncertainty.
Sex-Dependent Effects of Chronic Microdrive Implantation on Acquisition of Trace Eyeblink Conditioning
Authors: Rapp Amy P , Hark Timothy J , Power John M , Savas Jeffrey N , Oh M Matthew , Disterhoft John F 
Published: August 2021

SummaryNeuroscience techniques, including in vivo recording, have allowed for a great expansion in knowledge; however, this technology may also affect the very phenomena researchers set out to investigate. Including both female and male mice in our associative learning experiments shed light on sex differences on the impact of chronic implantation of tetrodes on learning. While previous research showed intact female mice acquired trace eyeblink conditioning faster than male and ovariectomized females, implantation of chronic microdrive arrays showed sexually dimorphic effects on learning. Microdrive implanted male mice acquired the associative learning paradigm faster than both intact and ovariectomized females. These effects were not due to the weight of the drive alone, as there were no significant sex-differences in learning of animals that received “dummy drive” implants without tetrodes lowered into the brain. Tandem mass tag mass spectrometry and western blot analysis suggest that significant alterations in the MAPK pathway, acute inflammation, and brain derived neurotrophic factor may underlie these observed sex- and surgery-dependent effects on learning.
Evolutionary dynamics of indels in SARS-CoV-2 spike glycoprotein
Authors: Prasad Rao R. Shyama , Ahsan Nagib , Xu Chunhui , Su Lingtao , Verburgt Jacob , Fornelli Luca , Kihara Daisuke , Xu Dong 
Published: August 2021

AbstractSARS-CoV-2, responsible for the current COVID-19 pandemic that claimed over 4.2 million lives, belongs to a class of enveloped viruses that undergo quick evolutionary adjustments under selection pressure. Numerous variants have emerged in SARS-CoV-2 that are currently posing a serious challenge to the global vaccination effort and COVID-19 management. The evolutionary dynamics of this virus are only beginning to be explored. In this work, we have analysed 1.79 million spike glycoprotein sequences of SARS-CoV-2 and found that the virus is fine-tuning the spike with numerous amino acid insertions and deletions (indels). Indels seem to have a selective advantage as the proportions of sequences with indels were steadily increasing over time, currently at over 89%, with similar trends across countries/variants. There were as many as 420 unique indel positions and 447 unique combinations of indels. Despite their high frequency, indels resulted in only minimal alteration, including both gain and loss, of N-glycosylation sites. As indels and point mutations are positively correlated and sequences with indels have significantly more point mutations, they have implications in the context of evolutionary dynamics of the SARS-CoV-2 spike glycoprotein.
Performance of three molecular tests for SARS-CoV-2 on a university campus estimated jointly with Bayesian latent class modeling
Authors: Perkins T. Alex , Stephens Melissa , Barrios Wendy Alvarez , Cavany Sean , Rulli Liz , Pfrender Michael E. 
Published: August 2021

ABSTRACTAccurate tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been critical in efforts to control its spread. The accuracy of molecular tests for SARS-CoV-2 has been assessed numerous times, usually in reference to a gold standard diagnosis. One major disadvantage of that approach is the possibility of error due to inaccuracy of the gold standard, which is especially problematic for evaluating testing in a real-world surveillance context. We used an alternative approach known as Bayesian latent class modeling (BLCM), which circumvents the need to designate a gold standard by simultaneously estimating the accuracy of multiple tests. We applied this technique to a collection of 1,716 tests of three types applied to 853 individuals on a university campus during a one-week period in October 2020. We found that reverse transcriptase polymerase chain reaction (RT-PCR) testing of saliva samples performed at a campus facility had higher sensitivity (median: 0.923; 95% credible interval: 0.732-0.996) than RT-PCR testing of nasal samples performed at a commercial facility (median: 0.859; 95% CrI: 0.547-0.994). The reverse was true for specificity, although the specificity of saliva testing was still very high (median: 0.993; 95% CrI: 0.983-0.999). An antigen test was less sensitive and specific than both of the RT-PCR tests. These results suggest that RT-PCR testing of saliva samples at a campus facility can be an effective basis for surveillance screening to prevent SARS-CoV-2 transmission in a university setting.
Both consumptive and non-consumptive effects of predators impact mosquito populations and have implications for disease transmission
Authors: Russell Marie C. , Herzog Catherine M. , Gajewski Zachary , Ramsay Chloe , El Moustaid Fadoua , Evans Michelle V. , Desai Trishna , Gottdenker Nicole L. , Hermann Sara L. , Power Alison G. , McCall Andrew C. 
Published: August 2021

AbstractPredator-prey interactions influence prey traits through both consumptive and non-consumptive effects, and variation in these traits can shape vector-borne disease dynamics. Meta-analysis methods were employed to generate predation effect sizes by different categories of predators and mosquito prey. This analysis showed that multiple families of aquatic predators are effective in consumptively reducing mosquito survival, and that the survival ofAedes, Anopheles, andCulexmosquitoes is negatively impacted by consumptive effects of predators. Mosquito larval size was found to play a more important role in explaining the heterogeneity of consumptive effects from predators than mosquito genus. Mosquito survival and body size were reduced by non-consumptive effects of predators, but development time was not significantly impacted. In addition,Culexvectors demonstrated predator avoidance behavior during oviposition. The results of this meta-analysis suggest that predators limit disease transmission by reducing both vector survival and vector size, and that associations between drought and human West Nile virus cases could be driven by the vector behavior of predator avoidance during oviposition. These findings are likely to be useful to infectious disease modelers who rely on vector traits as predictors of transmission.
Evolutionary analysis of THAP9 transposase: conserved regions, novel motifs
Authors: Rashmi Richa , Nandi Chandan , Majumdar Sharmistha 
Published: August 2021

AbstractTHAP9 is a transposable element-derived gene that encodes the THAP9 protein, which is homologous to the Drosophila P-element transposase (DmTNP) and can cut and paste DNA. However, the exact functional role of THAP9 is unknown. Here, we perform evolutionary analysis and extensive in silico characterization of THAP9, including predicting domains and putative post-translational modification sites. We predict previously unreported mammalian-specific post-translational modification sites that may play a role in the subcellular localization of THAP9. We also observe that although THAP9 has evolved under a strong pervasive purifying selection, yielding high conservation of THAP9, there are distinct class-specific conservation patterns of key functional residues in certain domains. Furthermore, investigation of THAP9 expression profiles in various cancer and matched normal datasets demonstrated underexpression and overexpression in testicular cancers and thymic epithelial tumors, respectively, thus suggesting a possible role of THAP9 in cancer.
Deep Transfer Learning of Drug Responses by Integrating Bulk and Single-cell RNA-seq data
Authors: Chen Junyi , Wu Zhenyu , Qi Ren , Ma Anjun , Zhao Jing , Xu Dong , Li Lang , Ma Qin 
Published: August 2021

ABSTRACTMassively bulk RNA sequencing databases incorporating drug screening have opened up an avenue to inform the optimal clinical application of cancer drugs. Meanwhile, the growing single-cell RNA sequencing (scRNA-seq) data contributes to improving therapeutic effectiveness by studying the heterogeneity of drug responses for cancer cell subpopulations. There is a clear significance in developing computational biology approaches to predict and interpret cancer drug response in single cell data from clinical samples. Here, we introduce scDEAL, a deep transfer learning framework for cancer drug response prediction at single-cell level by integrating large-scale bulk cell line data. The true innovation of scDEAL is to translate cancer cell line drug responses into predicting clinical drug responses via learning relations of gene expressions and drug responses at bulk-level and transfer to predict drug responses in scRNA-seq. Another innovation is the integrated gradient feature interpretation to infer a comprehensive set of signature genes to reveal potential drug resistance mechanisms. We benchmarked scDEAL on six scRNA-seq datasets and indicate its model interpretability through these case studies. We believe that this work may help study cell reprogramming, drug selection, and repurposing for improving therapeutic efficacy.
Transcriptomes of Electrophysiologically Recorded Dbx1-derived Inspiratory Neurons of the preBötzinger Complex in Neonatal Mice
Authors: Kallurkar Prajkta S. , Picardo Maria Cristina D. , Sugimura Yae K. , Saha Margaret S. , Smith Gregory D. Conradi , Del Negro Christopher A. 
Published: August 2021

AbstractBreathing depends on interneurons in the preBötzinger complex (preBötC) derived from Dbx1-expressing precursors. Here we investigate whether rhythm- and pattern-generating functions reside in discrete classes of Dbx1 preBötC neurons. In a slice model of breathing with ∼5 s cycle period, putatively rhythmogenic Type-1 Dbx1 preBötC neurons activate 100-300 ms prior to Type-2 neurons, putatively specialized for output pattern, and 300-500 ms prior to the inspiratory motor output. We sequenced Type-1 and Type-2 transcriptomes and identified differential expression of 123 genes including ionotropic receptors (Gria3 and Gabra1) that may explain their preinspiratory activation profiles and Ca2+ signaling (Cracr2a, Sgk1) involved in inspiratory and sigh bursts. Surprisingly, neuropeptide receptors that influence breathing (e.g., µ-opioid and bombesin-like peptide receptors) were only sparsely expressed, which suggests that cognate peptides and opioid drugs exert their profound effects on a small fraction of the preBötC core. These data in the public domain help explain breathing’s neural origins.
Hidden in the deep: distinct benthic trajectories call for monitoring of mesophotic reefs
Authors: Hernandez-Agreda A , Sahit FM , Englebert N , Hoegh-Guldberg O , Bongaerts P 
Published: August 2021

AbstractLong-term monitoring studies are central to coral reef ecology and conservation management. However, ongoing monitoring programs are almost exclusively focused on shallow depths, and it remains unclear to what extent those are representative of the whole ecosystem. Here, we present a temporal comparison (2012-2017) of directly adjacent shallow and mesophotic benthic communities across seven sites from the Great Barrier Reef and Western Coral Sea. We found a positive correlation initially between shallow and mesophotic coral cover, with higher cover at shallow depths. However, this correlation broke down after multiple disturbances, with coral cover declining only at shallow depths. Point-based tracking revealed the dynamic nature of mesophotic communities, with their consistent coral cover reflecting a net balance between substantial growth and mortality. Overall, the divergent trajectories highlight the urgency to expand monitoring efforts into mesophotic depths, to decipher the processes governing these habitats and enable better-informed management of the overall ecosystem.