bluuebunny/crossref_metadata_2025_split huggingface dataset:
Machine learning reveals limited contribution of trans-only encoded variants to the HLA-DQ immunopeptidome by accurate and comprehensive HLA-DQ antigen presentation prediction
Authors: Nilsson Jonas Birkelund , Kaabinejadian Saghar , Yari Hooman , Peters Bjoern , Barra Carolina , Gragert Loren , Hildebrand William , Nielsen Morten 
Published: September 2022

AbstractHLA class II antigen presentation is key for controlling and triggering T cell immune responses. HLA-DQ molecules, which are believed to play a major role in autoimmune diseases, are heterodimers that can be formed as both cis and trans variants depending on whether the α- and β-chains are encoded on the same (cis) or opposite (trans) chromosomes. So far, limited progress has been made for predicting HLA-DQ antigen presentation. In addition, the contribution of trans-only variants (i.e. variants not observed in the population as cis) in shaping the HLA-DQ immunopeptidome remains largely unresolved. Here, we seek to address these issues by integrating state-of-the-art immunoinformatics data mining models with large volumes of high-quality HLA-DQ specific MS-immunopeptidomics data. The analysis demonstrated a highly improved predictive power and molecular coverage for models trained including these novel HLA-DQ data. More importantly, investigating the role of trans-only HLA-DQ variants revealed a limited to no contribution to the overall HLA-DQ immunopeptidome. In conclusion, this study has furthered our understanding of HLA-DQ specificities and has for the first time cast light on the relative role of cis versus trans-only HLA-DQ variants in the HLA class II antigen presentation space. The developed method, NetMHCIIpan-4.2, is available athttps://services.healthtech.dtu.dk/services/NetMHCIIpan-4.2.
The effects of oral supplementation of Japanese sake yeast on anxiety, depressive-like symptoms, oxidative stress, and BDNF changes in chronically stressed adolescent rats
Authors: Haghipanah Motahareh , Saadat Maryam , Safarbalou Asal , Budde Thomas , Mohamed Wael , Sadat Afraz Elham , Moradikor Nasrollah 
Published: September 2022

AbstractChronic stress during the pre-pubertal period has adverse effects in developing neuropsychiatric disorders such as depression and anxiety. The administration of supplements with antioxidant properties may alleviate depression and anxiety behavior. This study investigated the effects of oral supplementation of Japanese sake yeast on anxiety, depressive-like symptoms, oxidative stress, and changes in brain-derived neurotropic factor (BDNF) in adolescence rats subjected to chronic stress.In order to assess the effects of chronic stress, adolescent rats were grouped into one non-stressed control group (non-stress) and four different experimental groups. The other animals were subjected to stress and orally received normal saline (Control-stress), 15 mg/kg yeast (Stress-15), 30 mg/kg yeast (Stress-30) and 45 mg/kg yeast (Stress-45). Anxiety and depression-like behavior, BDNF levels, and oxidative stress markers were evaluated.The rats exposed to stress exhibited anxiogenic and depression-like behavior as well as lower levels of BDNF and higher levels of oxidative markers compared with non-stressed rats (P<0.05). However, the oral supplementation of sake yeast decreased anxiogenic and depression-like behavior and oxidative indices, and also increased BDNF levels compared to stressed rats treated with saline in a dose-dependent manner (P<0.05).In sum, stress caused anxiety and depression behavior, increased oxidative indices, and reduced BDNF levels while sake yeast alleviated adverse effects of stress on anxiety and depression behaviors, decreased oxidative markers, and increased BDNF levels.
Effects of Oxytocin Receptor Blockade on Dyadic Social Behavior in Monogamous and Non-MonogamousEulemur
Authors: Grebe Nicholas M. , Sheikh Alizeh , Ohannessian Laury , Drea Christine M. 
Published: September 2022

AbstractA prominent body of research spanning disciplines has been focused on the potential underlying role for oxytocin in the social signatures of monogamous mating bonds. Behavioral differences between monogamous and non-monogamous vole species, putatively mediated by oxytocinergic function, constitute a key source of support for this mechanism, but it is unclear to what extent this hormone–behavior linkage extends to the primate order. In a preregistered experiment, we test if oxytocin receptor blockade affects affiliative behavior in mixed-sex pairs ofEulemur, a genus of strepsirrhine primate containing both monogamous and non-monogamous species. Inconsistent with past studies in monogamous voles or monkeys, we do not find confirmatory evidence inEulemurthat monogamous pairs affiliate more than non-monogamous pairs, nor that oxytocin receptor blockade of one pair member selectively corresponds to reduced affiliative or scent-marking behavior in monogamous species. We do, however, find exploratory evidence of a pattern not previously investigated: simultaneously blocking oxytocin receptors in both members of a monogamous pair predicts lower rates of affiliative behavior relative to controls. Our study demonstrates the value of non-traditional animal models in challenging generalizations based on model organisms, and of methodological reform in providing a potential path forward for behavioral oxytocin research.
Combined multidimensional single-cell protein and RNA profiling dissects the cellular and functional heterogeneity of thymic epithelial cells
Authors: Klein Fabian , Veiga-Villauriz Clara , Börsch Anastasiya , Maio Stefano , Palmer Sam , Zuklys Saulius , Calvo-Asensio Irene , Musette Lucas , Deadman Mary E. , Dhalla Fatima , White Andrea , Lucas Beth , Anderson Graham , Holländer Georg A. 
Published: September 2022

AbstractThe network of thymic stromal cells provides essential niches with unique molecular cues controlling T-cell development and selection. Recent single-cell RNA-sequencing studies uncovered a large transcriptional heterogeneity among thymic epithelial cells (TEC) demonstrating a previously unappreciated complexity. However, there are only very few cell markers that allow a comparable phenotypic identification of TEC. Here we deconvoluted by massively parallel flow cytometry and machine learning known and novel TEC phenotypes into novel subpopulations and related these by CITEseq to the corresponding TEC subtypes defined by the cells’ individual RNA profiles. This approach phenotypically identified perinatal cTEC, physically located these cells within the cortical stromal scaffold, displayed their dynamic change during the life course and revealed their exceptional efficiency in positively selecting immature thymocytes. Collectively, we have identified novel markers that allow for an unprecedented dissection of the thymus stromal complexity, the cells physical isolation and assignment of specific functions to individual TEC subpopulations.
Hotspot propensity across mutational processes
Authors: Arnedo-Pac Claudia , Muiños Ferran , Gonzalez-Perez Abel , Lopez-Bigas Nuria 
Published: September 2022

AbstractThe ability to study mutation rate variability at nucleotide resolution is impaired by the sparsity of observed mutational events across the genome. To circumvent this problem, here we investigated the propensity of 14 different mutational processes to form recurrently mutated sites across tumour samples (hotspots). We found that mutational signatures 1 (SBS1) and 17 (SBS17a and SBS17b) have the highest propensity to form hotspots, generating 5-78 times more than other common somatic mutational processes. After accounting for trinucleotide mutational probabilities, sequence composition and heterogeneity of mutation rates at 10 Kbp, the majority (89-95%) of SBS17a and b hotspots remain unexplained. This suggests that local genomic features play a significant role in SBS17a and b hotspot propensity, among which we identify CTCF binding as a minor contributor. In the case of SBS1, we demonstrate that including genome-wide distribution of methylated CpGs sites into our models can explain most (80-100%) of its hotspot propensity. We also observe an increased hotspot propensity of SBS1 in normal tissues from mammals, as well as inde novogermline mutations. We demonstrate that hotspot propensity is a useful readout to assess the accuracy of mutation rate models at nucleotide resolution. This new approach and the findings derived from it open up new avenues for a range of somatic and germline studies investigating and modelling mutagenesis.
Whole-genome resequencing data support a single introduction of the invasive white pine sawfly, Diprion similis
Authors: Davis Jeremy S. , Sim Sheina , Geib Scott , Sheffler Brian , Linnen Catherine R. 
Published: September 2022

AbstractBiological introductions are unintended “natural experiments” that provide unique insights into evolutionary processes. Invasive phytophagous insects are of particular interest to evolutionary biologists studying adaptation, as introductions often require rapid adaptation to novel host plants. However, adaptive potential of invasive populations may be limited by reduced genetic diversity—a problem known as the “genetic paradox of invasions”. One potential solution to this paradox is if there are multiple invasive waves that bolster genetic variation in invasive populations. Evaluating this hypothesis requires characterizing genetic variation and population structure in the introduced range. To this end, we assemble a reference genome and describe patterns of genetic variation in the introduced white pine sawfly, Diprion similis. This species was introduced to North America in 1914, where it has undergone a rapid host shift to the thin-needled eastern white pine (Pinus strobus), making it an ideal invasion system for studying adaptation to novel environments. To evaluate evidence of multiple introductions, we generated whole-genome resequencing data for 64 D. similis females sampled across the North American range. Both model-based and model-free clustering analyses supported a single population for North American D. similis. Within this population, we found evidence of isolation-by-distance and a pattern of declining heterozygosity with distance from the hypothesized introduction site. Together, these results support a single-introduction event. We consider implications of these findings for the genetic paradox of invasion and discuss priorities for future research in D. similis, a promising model system for invasion biology.
Sustainable reference points for multispecies coral reef fisheries
Authors: Zamborain-Mason Jessica , Cinner Joshua E. , MacNeil M. Aaron , Graham Nicholas A. J. , Hoey Andrew S. , Beger Maria , Brooks Andrew J. , Booth David J. , Edgar Graham J. , Feary David A. , Ferse Sebastian C. A. , Friedlander Alan M. , Gough Charlotte L. A. , Green Alison L. , Mouillot David , Polunin Nicholas V.C. , Stuart-Smith Rick D. , Wantiez Laurent , Williams Ivor D. , Wilson Shaun K. , Connolly Sean R. 
Published: September 2022

AbstractSustainably managing fisheries requires regular and reliable evaluation of stock status. However, most multispecies reef fisheries around the globe tend to be data-poor and lack research and monitoring capacity (e.g., long-term fishery data), preventing the estimation of sustainable reference points against which stocks can be assessed. Here, combining fish biomass data for more than 2000 coral reefs with catch estimates from 99 jurisdictions, we estimate site-specific sustainable reference points for coral reef fisheries and use these to assess the status of coral reef fish stocks. We reveal that more than half of jurisdictions with available information have stocks of conservation concern, having failed at least one fisheries sustainability benchmark. We quantify the trade-offs between biodiversity, mean fish length, and ecosystem functions relative to key benchmarks and highlight the ecological benefits of increasing sustainability. Our approach yields multispecies sustainable reference points for coral reef fisheries using environmental conditions, a promising means for enhancing the sustainability of the world’s coral reef fisheries.TeaserA global assessment of the sustainability of multispecies reef fisheries indicates that more than half of jurisdictions have failed at least one of two key sustainability benchmarks.
Common insecticide affects spatial navigation in bats at environmentally-realistic doses
Authors: Sandoval-Herrera Natalia , Lara-Jacobo Linda , Vargas Soto Juan S. , Faure Paul A. , Simmons Denina , Welch Kenneth 
Published: September 2022

AbstractBats are potentially exposed to pesticides via foraging in croplands. Common pesticides like organophosphates are neurotoxic for vertebrates and even low doses can impair essential processes such as locomotion and cognition. These sublethal effects are usually studied using molecular biomarkers with limited ecological relevance. Behavioral studies, in contrast, represent a more informative yet sensitive approach. Spatial navigation, for example, is an ecologically relevant behavior that is modulated by cellular pathways potentially targeted by neurotoxicants. We evaluated whether bats’ ability to memorize and navigate novel spaces was negatively affected by environmental relevant doses of chlorpyrifos, a common organophosphate insecticide. We also tested how the behavioral response correlated with molecular biomarkers. We orally dosed captive big brown bats (Eptesicus fuscus) with chlorpyrifos and studied exploratory behavior in two testing arenas. We evaluated similarity of stereotype flight trajectories in a flight tent, and associative memory in a Y-maze. We quantified brain cholinesterase (ChE) activity as a cellular biomarker and employed non-targeted proteomics as molecular biomarkers. Bats exposed to chlorpyrifos were less explorative and made more incorrect choices in the Y-maze, but the consistency of their flight trajectories was unaffected. Exposed bats had 30% lower ChE activity, showed down-regulation of proteins involved in memory (VP37D), learning and sound perception (NOX3). Other important nervous system processes such as synaptic function, plasticity, oxidative stress, and apoptosis were enriched in chlorpyrifos-exposed bats. These results support the sensitivity of behavior as a biomarker of toxicity and the importance of considering other levels of organization to help explain the mechanisms underlying altered behavior due to human activities.
Melanoma-intrinsic NR2F6 activity regulates anti-tumor immunity
Authors: Kim Hyungsoo , Feng Yongmei , Murad Rabi , Klepsch Victoria , Baier Gottfried , Ronai Ze’ev A 
Published: September 2022

AbstractNuclear receptors (NRs) have been implicated in tumor and immune cell regulation, most notably in hormone-dependent cancers. Here we identify a tumor-intrinsic function of the orphan nuclear receptor NR2F6 in regulating anti-tumor immunity. We selected NR2F6 among 48 candidate NRs based on an expression pattern in melanoma patient specimens coinciding with the IFNγ signature, which is associated with positive responses to immunotherapy and favorable patient outcomes. Further delay of melanoma development was achieved upon combination of NR2F6 inhibition with anti-PD1 therapy. NR2F6 loss in B16F10 and YUMM1.7 melanoma cells attenuated tumor development in immune-competent but not -incompetent mice via increased CD8+ T cell infiltration and activation. Inhibition of NACC1 and FKBP10, identified here as NR2F6 effectors, phenocopied NR2F6 loss. Remarkably, inoculation of NR2F6 KD melanoma cells into mice genetically deficient in NR2F6 further enhanced tumor growth inhibition. Identifying a tumor-intrinsic function of NR2F6 which complements its tumor-extrinsic role could be thus exploited to develop novel anti-cancer therapies.
Evaluating the Robustness of Connectivity Methods to Noise for In Silico Drug Repurposing Studies
Authors: Tham Nevin , Langley Sarah R 
Published: September 2022

AbstractDrug repurposing is an approach to identify new therapeutic applications for existing drugs and small molecules. It is a field of growing research interest due to its time and cost effectiveness as compared withde novodrug discovery. One method for drug repurposing is to adopt a systems biology approach to associate molecular ‘signatures’ of drug and disease. Drugs which have an inverse relationship with the disease signature may be able to reverse the molecular effects of the disease and thus be candidates for repurposing. Conversely, drugs which mimic the disease signatures can inform on potential molecular mechanisms of disease. The relationship between these disease and drug signatures are quantified through connectivity scores. Identifying a suitable drug-disease scoring method is key for in silico drug repurposing, so as to obtain an accurate representation of the true drug-disease relationship. There are several methods to calculate these connectivity scores, notably the Kolmogorov-Smirnov (KS), Zhang and eXtreme Sum (XSum). However, these methods can provide discordant estimations of the drug-disease relationship and this discordance can affect the drug-disease indication. Using the gene expression profiles from the Library of Integrated Network-Based Cellular Signatures (LINCS) database, we evaluated the methods based on their drug-disease connectivity scoring performance. In this first-of-its-kind analysis, we varied the quality of disease signatures by using only highly differential genes or by the inclusion of non-differential genes. Further, we simulated noisy disease signatures by introducing varying levels of noise into the gene expression signatures. Overall, we found that there was not one method that outperformed the others in all instances, but the Zhang method performs well in a majority of our analyses. Our results provide a framework to evaluate connectivity scoring methods, and considerations for deciding which scoring method to apply in future systems biology studies for drug repurposing.
Real Time Breast Histology Image Classification with a Mobile Phone
Authors: Ikemura Kenji 
Published: September 2022

AbstractBackgroundDeep learning, specifically convolutional neural network, has made a breakthrough in the complex task of computer image recognition. In this study, depthwise separable convolutional neural network (DS-CNN), MobileNets v1, was used in classifying breast cancer histology images on the computer and then on a mobile/smart phone, in real time. This study propose that DS-CNN can be applied for histological image analysis and its network can be transferred to a commercially available mobile phone for real-time histological image analysis captured through the mobile phone camera.MethodThis study utilizes the DS-CNN on breast cancer histology images downloaded from publicly available repository: https://rdm.inesctec.pt/dataset/nis-2017-003. Training set images are augmented by rotation and mirroring the images. DS-CNN is trained to classify breast tissue images between 4 categories: i) normal, ii) benign, iii) carcinoma in-situ, and iv) invasive carcinoma. Finally, the trained DS-CNN is deployed on to a mobile phone to classify the images captured through the mobile phone camera in real-time. The output on the mobile phone screen is the real-time image from the camera and its probability of it being one of the 4 categories (from high to low confidence). Accuracy of DS-CNN is assessed, both on the computer and on mobile phone, by whether its prediction with highest confidence matches the true class in the test dataset. Secondary results of sensitivity and specificities were calculated.ResultsThe trained DS-CNN accuracy on the computer reached as high as 86% in 4 class classification. On the mobile phone, accuracy reached 67% in 4 class classification and 78% in 2 class classification (normal or benign vs. in situ or invasive). Training time took less than 30 min on 1.4 GHz Intel Core i5 dual-core CPU. Latency for evaluation on mobile phone was less than 1 second. Demo video of real time histology image analysis with mobile phone can be found here: https://www.youtube.com/watch?v=qx2CdrSuazgConclusionDS-CNN is a fast and efficient neural network architecture that can learn to distinguish histological images even with limited sample size and computational power. The architecture can be deployed onto a mobile phone and maintain relatively good accuracy through the phone camera. It is likely that the accuracy can be increased by expanding the dataset and with updated CNN that are optimized for mobile phones.
Stratification of COVID-19 severity using SeptiCyte RAPID, a novel host immune response test
Authors: Gravrand Victor , Mellot François , Ackermann Felix , Ballester Marie-Christine , Zuber Benjamin , Kirk James T. , Navalkar Krupa , Yager Thomas D. , Petit Fabien , Pascreau Tiffany , Farfour Eric , Vasse Marc 
Published: September 2022

AbstractSeptiCyte® RAPID is a gene expression assay measuring the relative expression levels of host response genes PLA2G7 and PLAC8, indicative of a dysregulated immune response during sepsis. As severe forms of COVID-19 may be considered viral sepsis, we evaluated SeptiCyte RAPID in a series of 94 patients admitted to Foch Hospital (Suresnes, France) with proven SARS-CoV-2 infection. EDTA blood was collected prospectively in the emergency department (ED) in 67 cases, in the intensive care unit (ICU) in 23 cases and in conventional units in 4 cases. SeptiScore (0-15 scale) increased with COVID-19 severity. Patients in ICU had the highest SeptiScores, producing values comparable to 8 patients with culture-confirmed bacterial sepsis. Receiver operating characteristic (ROC) curve analysis had an area under the curve (AUC) of 0.81 for discriminating patients requiring ICU admission from patients who were immediately discharged or from patients requiring hospitalization in conventional units. SeptiScores increased with the extent of the lung injury. For 68 patients, a chest computed tomography (CT) scan was performed within 24 hours of COVID-19 diagnosis. SeptiScore > 7 suggested lung injury ≥ 50 % (AUC = 0.86). SeptiCyte RAPID was compared to other biomarkers for discriminating Critical + Severe COVID-19 in ICU, versus Moderate + Mild COVID-19 not in ICU. The mean AUC for SeptiCyte RAPID was superior to that of any individual biomarker or combination thereof. In contrast to C-reactive protein (CRP), correlation of SeptiScore with lung injury was not impacted by treatment with anti-inflammatory agents. SeptiCyte RAPID can be a useful tool to identify patients with severe forms of COVID-19 in ED, as well as during follow-up.