bluuebunny/crossref_metadata_2025_split huggingface dataset:
DeepAIR: a deep-learning framework for effective integration of sequence and 3D structure to enable adaptive immune receptor analysis
Authors: Zhao Yu , He Bing , Li Chen , Xu Zhimeng , Su Xiaona , Rossjohn Jamie , Song Jiangning , Yao Jianhua 
Published: October 2022

AbstractStructural docking between the adaptive immune receptors (AIRs), including T cell receptors (TCRs) and B cell receptors (BCRs), and their cognate antigens is one of the most fundamental processes in adaptive immunity. However, current methods for predicting AIR-antigen binding largely rely on sequence-derived features of AIRs, omitting the structure features that are essential for binding affinity. In this study, we present a deep-learning framework, termed DeepAIR, for the accurate prediction of AIR-antigen binding by integrating both sequence and structure features of AIRs. DeepAIR consists of three feature encoders (a trainable-embedding-layer-based gene encoder, a transformer-based sequence encoder, and a pre-trained AlphaFold2-based structure encoder), a gating-based attention mechanism to extract important features, and a tensor fusion mechanism to integrate obtained features. We train and evaluate DeepAIR on three downstream prediction tasks, including the prediction of AIR-antigen binding affinity, the prediction of AIR-antigen binding reactivity, and the classification of the immune repertoire. On five representative datasets, DeepAIR shows outstanding prediction performance in terms of AUC (area under the ROC curve) in predicting the binding reactivity to various antigens, as well as the classification of immune repertoire for nasopharyngeal carcinoma (NPC) and inflammatory bowel disease (IBD). DeepAIR is freely available for academic purposes at https://github.com/TencentAILabHealthcare/DeepAIR. We anticipate that DeepAIR can serve as a useful tool for characterizing and profiling antigen binding AIRs, thereby informing the design of personalized immunotherapy.HighlightsIntegrating predicted AIR structures using AlphaFold2 significantly improves the prediction accuracy of the binding reactivity between AIRs and antigens.DeepAIR is featured by a novel deep learning architecture that leverages both the gating-based attention mechanism and tensor fusion mechanism to effectively extract and integrate informative features from three feature encoders, including a trainable embedding-layer-based gene encoder, a transformer-based sequence encoder, and a pre-trained AlphaFold2-based structure encoder.DeepAIR is implemented as a biologically interpretable deep learning framework that highlights the key residues in both α and β chains that are critical for predicting the AIR-antigen binding.
Fitness benefits from co-display favour subdominant male-male partnerships between phenotypes
Authors: Tolliver James D. M. , Kupán Krisztina , Lank David B. , Schindler Susanne , Küpper Clemens 
Published: October 2022

ABSTRACTMale-male competition over matings is a key driving force in the evolution of courtship. Typically, competition is an individual affair selecting for dominance and aggression. Yet, some males forgo direct confrontation and improve their reproductive success through cooperation. Occasionally, this leads to specialized alternative reproductive tactics that operate at the intersection of cooperation and conflict. We used a community game model, informed with empirical data derived from previous studies, to examine cooperation dynamics between lekking male ruffs (Calidris pugnax) using two different tactics: resident and satellite. Residents defend display courts against other residents on leks. In contrast, satellites forgo court defence and engage in cooperative co-display with selected residents. Co-displaying appears to alter female mate choice, yet the exact mechanism and consequences remain unclear. We modelled individual male mating success as a function of lek size, resident rank, and satellite competitiveness. Our most realistic model assumed that co-display draws copulations from residents proportional to the existing mating skew among them. Under this assumption, all residents benefit from co-display over single display when a satellite is on the lek, except for α-residents co-displaying with the most competitive satellites on large leks. Thus, satellites could nearly always choose their preferred co-display partner, but achieved the highest copulation rates with lower ranking (subdominant) residents on intermediate sized leks. Co-display between the satellite and lower ranking residents reduced the mating skew among residents. However, since copulations for satellites were similar over a range of potential co-display partners, a variety of co-displaying dyads is to be expected, which is consistent with observations in nature. We conclude that, given our model assumptions, co-displaying reduces the impact of male dominance on reproductive success and ultimately alters the course of sexual selection.
S100A4 plays a role in mouse arterial smooth muscle cell motility. Implication for intimal thickening formation
Authors: Cardoso dos Santos LM. , Klingelhöfer J. , Bochaton-Piallat ML. 
Published: October 2022

AbstractDuring atherosclerosis, smooth muscle cells (SMCs) migrate and accumulate in the intima, where they switch from a contractile to a synthetic phenotype. This process is associated with decreased expression or loss of contractile proteins, such as α-smooth muscle actin (α-SMA) or smooth muscle myosin heavy chains (SMMHCs). We previously demonstrated that S100A4, a small calcium-binding protein, which exhibits intra- and extracellular functions, is a marker of the synthetic SMC phenotype. We have recently shown that neutralization of extracellular S100A4 in an ApoE knockout (KO) mouse model with established atherosclerotic lesions decreased the overall atherosclerotic burden. To explore the role of S100A4 in the accumulation of SMCs in the intima, we induced intimal thickening (IT) formation in full S100A4 knockout (KO) and wild type (WT) mice by completely ligating the left common carotid artery. With this model, we generated SMC-rich lesions. The deletion of S100A4 did not influence the size of the IT, neither its composition, as assessed by the expression of α-SMA and SMMHCs in S100A4 KO animals compared with WT animals, 4 weeks after ligation. Using primary cells isolated from both strains, we demonstrated that S100A4 KO SMCs were less prone to migrate than WT SMCs but they did not differ in their proliferative capacity. Our results indicate that S100A4 plays a role in SMC motility in vitro but its deletion does not influence IT formation in the mouse carotid artery ligation model.
A primary rodent triculture model to investigate the role of glia-neuron crosstalk in regulation of neuronal activity
Authors: Phadke Leela , Lau Dawn H. W. , Aghaizu Nozie D. , Ibarra Shania , Navarron Carmen M. , Granat Lucy , Magno Lorenza , Whiting Paul , Jolly Sarah 
Published: October 2022

AbstractNeuroinflammation and hyperexcitability have been implicated in the pathogenesis of neurodegenerative disease, and new models are required to investigate the cellular crosstalk involved in these processes. We developed an approach to generate a quantitative and reproducible triculture system that is suitable for pharmacological studies. While primary rodent cells were previously grown in a coculture medium formulated to support only neurons and astrocytes, we now optimised a protocol to generate tricultures containing neurons, astrocytes and microglia by culturing in a medium designed to support all three cell types and adding exogenous microglia to cocultures. Immunocytochemistry was used to confirm the intended cell types were present. The percentage of ramified microglia in the tricultures decreases as the number of microglia present increases. Multi-electrode array (MEA) recordings indicate that microglia in the triculture model suppress neuronal activity in a dose-dependent manner. Neurons in both cocultures and tricultures were responsive to the potassium channel blocker 4-aminopyridine (4-AP) suggesting that neurons remained viable and functional in the triculture model. Furthermore, suppressed neuronal activity in tricultures correlated with decreased densities of dendritic spines and of the postsynaptic protein Homer1 along dendrites, indicative of a direct or indirect effect of microglia on synapse function.We thus present a functional triculture model, which, due to its more complete cellular composition, is a more relevant model than standard cocultures. The model can be used to probe glia-neuron interactions and subsequently aid the development of assays for drug discovery, using neuronal excitability as a functional endpoint.
Comparison between ribosomal assembly and machine learning tools for microbial identification of organisms with different characteristics
Authors: Chau Stephanie , Rojas Carlos , Jetcheva Jorjeta G. , Markart Mary , Vijayakumar Sudha , Yuan Sophia , Stowbunenko Vincent , Shelton Amanda N. , Andreopoulos William B. 
Published: October 2022

AbstractGenome assembly tools are used to reconstruct genomic sequences from raw sequencing data, which are then used for identifying the organisms present in a metagenomic sample. More recently, machine learning approaches have been applied to a variety of bioinformatics problems, and in this paper, we explore their use for organism identification. We start out by evaluating several commonly used metagenomic assembly tools, including PhyloFlash, MEGAHIT, MetaSPAdes, Kraken2, Mothur, UniCycler, and PathRacer, and compare them against state-of-the art deep learning-based machine learning classification approaches represented by DNABERT and DeLUCS, in the context of two synthetic mock community datasets. Our analysis focuses on determining whether ensembling metagenome assembly tools with machine learning tools has the potential to improve identification performance relative to using the tools individually. We find that this is indeed the case, and analyze the level of effectiveness of potential tool ensembling for organisms with different characteristics (based on factors such as repetitiveness, genome size, and GC content).Author SummaryMetagenomic studies focus on the challenging problem of identifying the presence and abundance of different species in a sample. This process typically involves the creation of digital reads from the sample which correspond to small parts of the genome sequence, and then have to be assembled together by a genome assembly tool. More recently, machine learning approaches have been applied to a variety of bioinformatics problems, and in this paper, we explore their use for organism identification, and how they might complement traditional bioinformatics approaches. We conduct experiments with two representative state-of-the-art machine learning approaches and six metagenomic assembly tools in the context of two synthetic datasets. We find that for organisms with certain characteristics (levels of repetitiveness, GC content, and genome size), ensembling metagenome assembly tools with machine learning tools has the potential to improve species identification performance relative to using the tools individually.
Novel inductively-coupled ear-bars (ICEs) for fMRI signal enhancement in rat entorhinal cortex
Authors: Chen Yi , Fernandez Zachary , Zhu David C. , Counts Scott E. , Dorrance Anne M. , Yu Xin , Scheel Norman , Qian Wei , Gifani Mahsa , Qian Chunqi 
Published: October 2022

ABSTRACTEntorhinal cortex (EC) is a potential target of deep brain stimulation in Alzheimer’s disease (AD) and fMRI can enable whole-brain dynamic mapping noninvasively. However, it remains challenging to study EC-based fMRI connectivity in rodents due to image signal loss and the lower sensitivity of the surface coil ring or array coil for deep brain areas. To reduce the magnetic susceptibility artifacts driven signal loss issue, we introduced baby cream into the middle ear. To improve detection sensitivity, we implemented novel inductively-coupled ear-bars (ICEs) in the 7 T Bruker scanner, which resulted in an approximately 2-fold signal-to-noise ratio (SNR) increase in EC over the conventional surface array. The ICE can be conveniently utilized as an add-on device, with no modulation to the scanner interface. To demonstrate the applicability of ICEs for both task and resting-state (rs) fMRI, whole-brain echo-planar imaging (EPI) was performed in anesthetized rats modeling AD mixed dementia. Seed-based rs-fMRI connectivity maps emanating from the left entorhinal cortex demonstrated its connectivity to the hippocampus, piriform cortex, septal nuclei, and prefrontal cortex. Hence, this work demonstrates an optimized procedure for ICE by acquiring large scale networks emanating from a seed region that was not easily accessible by conventional MRI detectors, enabling better observation of EC-based brain fMRI connectivity studies with a higher signal-to-noise ratio in rodent models of dementia.
Prior unsupervised experience leads to long lasting effects in sensory gating during discrimination learning
Authors: de Hoz Livia , Barniv Dana , Nelken Israel 
Published: October 2022

AbstractAs the animal moves in its environment, the brain detects and learns the structure of the surrounding stimuli, independently of the immediate relevance this has for the animal. This experience influences subsequent learning in a manner quantified using paradigms such as latent inhibition or stimulus preconditioning, which measure the effect that unsupervised (not-reinforced) learning has on subsequent reinforced learning. Despite our understanding of the behavioural consequences of prior neutral experience, there is little understanding about the influence of this previous experience on neuronal plasticity. Using latent inhibition, we have shown in mice that learning a two tone discrimination is slower in mice that have had previous neutral exposure to the same or similar tones (<2/3 octave away). Neutral exposure thus elicits profound changes in the brain that influence subsequent learning. To study how previous experience influences experience-dependent plasticity, and better understand the interactions between experience, learning, and plasticity, we recorded sound evoked responses in the auditory cortex of exposed and trained mice. We studied both changes in response magnitude and changes in sensory dynamics, and related both to the differential behavioral effects of different pre-exposure conditions. Here we describe the neuronal changes that paralleled the behavioral findings. We found that discrimination learning led to stronger initial sound-evoked responses and a long-lasting increase in response adaptation and an increase. The first effect was delayed in animals that showed latent inhibition, paralleling behavioural learning. Overall our data reveal that slow changes in behaviour that accompanied learning, paralleled the slow dynamics of experience-dependent plasticity in auditory cortex.
Neurodegenerative disease associated pathways in brain of the triple transgenic Alzheimer’s model are reversed in vivo following two weeks peripheral administration of fasudil
Authors: Killick Richard , Elliott Christina , Ribe Elena , Broadstock Martin , Ballard Clive , Aarsland Dag , Williams Gareth 
Published: October 2022

AbstractThe pan ROCK inhibitor fasudil acts as a vasodilator and has been used as a medication post cerebral stroke for the past 27 years in Japan and China. More recently, on the basis of the involvement of ROCK inhibition on synaptic function, neuronal survival and processes associated with neuroinflammation, it has been suggested that the drug may be repurposed for neurodegenerative diseases. Indeed, fasudil has demonstrated preclinical efficacy in many neurodegenerative disease models.To facilitate an understanding of the wider biological processes at play due to ROCK inhibition in the context of neurodegeneration we performed a global gene expression analysis on the brains of Alzheimer’s disease model mice treated with fasudil via peripheral i.p injection. Our results show that fasudil tends to drive gene expression in a reverse sense to that seen in postmortem neurodegenerative disease brains. The results are most striking in terms of pathway enrichment analysis where pathways regulated in Alzheimer’s disease and by fasudil treatment are overwhelmingly regulated in opposite directions.Thus, our results bolster the repurposing potential of fasudil by demonstrating an anti-neurodegenerative phenotype in a disease context and highlight the potential of in vivo transcriptional profiling of drug activity.
CiDRE+ M2c macrophages hijacked by SARS-CoV-2 cause COVID-19 severity
Authors: Mitsui Yuichi , Suzuki Tatsuya , Kuniyoshi Kanako , Inamo Jun , Yamaguchi Kensuke , Komuro Mariko , Watanabe Junya , Edamoto Mio , Li Songling , Kouno Tsukasa , Oba Seiya , Hosoya Tadashi , Koyama Shohei , Sakaguchi Nobuo , Standley Daron M. , Shin Jay W. , Akira Shizuo , Yasuda Shinsuke , Miyazaki Yasunari , Kochi Yuta , Kumanogoh Atsushi , Okamoto Toru , Satoh Takashi 
Published: October 2022

AbstractInfection of the lungs with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) via the angiotensin I converting enzyme 2 (ACE2) receptor induces a type of systemic inflammation known as a cytokine storm. However, the precise mechanisms involved in severe coronavirus disease 2019 (COVID-19) pneumonia are unknown. Here, we show that interleukin-10 (IL-10) changed normal alveolar macrophages into ACE2-expressing M2c-type macrophages that functioned as spreading vectors for SARS-CoV-2 infection. The depletion of alveolar macrophages and blockade of IL-10 attenuated SARS-CoV-2 pathogenicity. Furthermore, genome-wide association and quantitative trait locus analyses identified novel mRNA transcripts in human patients, COVID-19 infectivity enhancing dual receptor (CiDRE), which has unique synergistic effects within the IL-10-ACE2 system in M2c-type macrophages. Our results demonstrate that alveolar macrophages stimulated by IL-10 are key players in severe COVID-19. Collectively, CiDRE expression levels are potential risk factors that predict COVID-19 severity, and CiDRE inhibitors might be useful as COVID-19 therapies.Graphical abstract
History matters: thermal environment before, but not during wasp attack determines the efficiency of symbiont-mediated protection
Authors: Jones Jordan E. , Hurst Gregory D. D. 
Published: October 2022

AbstractThe outcome of natural enemy attack in insects is commonly impacted by the presence of defensive microbial symbionts residing within the host. Beyond their presence, the outcome of the interaction can also depend on genetic and environmental factors. The thermal environment is a key factor known to affect symbiont-mediated traits in insects, including their ability to defend against natural enemy attack. Cooler temperatures, for instance, have been previously shown to reduce Spiroplasma-mediated protection in Drosophila. Here, we dissect the effect of the thermal environment on Spiroplasma-mediated protection against Leptopilina boulardi in Drosophila melanogaster by examining the effect of temperature before, during and after wasp attack on fly survival and wasp success. We observed that the developmental temperature of the mothers’ of attacked larvae, and not the temperature of the attacked larvae themselves during or after wasp attack, strongly determines the protective influence of Spiroplasma. Spiroplasma-mediated fly survival was found to be weaker when parental flies were reared at 21°C before their larvae were exposed to wasps compared to larvae derived from parental flies reared at 23°C or 25°C. Contrastingly, there was no effect of thermal environment on protection when mothers were reared at 25°C, and their progeny exposed to lower temperatures during and after wasp attack. The effect of developmental temperature on Spiroplasma-mediated protection is likely mediated by reduced Spiroplasma titre combined, at cooler temperatures, with segregation of infection. These results indicate the historical thermal environment is a stronger determinant of protection than current environment, and that protective capacity is partly an epigenetic trait.
Homeostatic Control of Deep Sleep inDrosophila: Implications for Discovering Correlates of Sleep Pressure
Authors: Chowdhury Budhaditya , Abhilash Lakshman , Ortega Antonio , Liu Sha , Shafer Orie 
Published: October 2022

AbstractHomeostatic control of sleep is typically addressed through mechanical stimulation-induced forced wakefulness and the measurement of subsequent increases in sleep. A major confound attends this approach: biological responses to deprivation may reflect a direct response to the mechanical insult rather than to the loss of sleep. Similar confounds accompany all forms of sleep deprivation and represent a major challenge to the field. Here we describe a new paradigm for sleep deprivation inDrosophilathat fully accounts for sleep-independent effects. Our results reveal that deep sleep states are the primary target of homeostatic control and establish the presence of multi-cycle sleep rebound following deprivation. Furthermore, we establish that specific deprivation of deep sleep state results in state-specific homeostatic rebound. Finally, by accounting for the molecular effects of mechanical stimulation during deprivation experiments, we show that serotonin levels track sleep pressure in the fly’s central brain. Our results illustrate the critical need to control for sleep-independent effects of deprivation when examining the molecular correlates of sleep pressure and call for a critical reassessment of work that has not accounted for such non-specific effects.
Crystal structure of monkeypox H1 phosphatase, an Antiviral Drug Target
Authors: Cui Wen , Huang Haojun , Duan Yinkai , Luo Zhi , Wang Haofeng , Zhang Tenan , Nguyen Henry , Shen Wei , Su Dan , Ji Xiaoyun , Yang Haitao , Wang Wei 
Published: October 2022

AbstractThe current monkeypox outbreak has caused over 64,000 global cases, but the effective treatments are very limited. The dual specific phosphatase (H1) from monkeypox antagonizes the immune response and is crucial for viral replication, making it an attractive antiviral target. Here we determined a 1.8-Å crystal structure of H1, which forms a domain swapped dimer resembling a butterfly. Each active site, which consists of a Cys-Arg-Asp triad, captures a phosphate ion. The observed conformation mimics the final step of catalysis prior to product release. The crystal structure provides a strong foundation for the discovery of new antivirals against this emerging worldwide pathogen.