Miracle-dz/UniFAR-FTUs huggingface dataset:
Where are the beachmasters? Unexpectedly weak polygyny among southern elephant seals on a South Shetland Island

Intraspecific variation in animal mating systems can have important implications for ecological, evolutionary and demographic processes in wild populations. For example, patterns of mating can impact social structure, dispersal, effective population size and inbreeding. However, few species have been studied in sufficient detail to elucidate mating system plasticity and its dependence on ecological and demographic factors. Southern elephant seals (Mirounga leonina) have long been regarded as a textbook example of a polygynous mating system, with dominant ‘beachmaster’ males controlling harems of up to several hundred females. However, behavioural and genetic studies have uncovered appreciable geographic variation in the strength of polygyny among elephant seal populations. We therefore used molecular parentage analysis to investigate patterns of parentage in a small satellite colony of elephant seals at the South Shetland Islands. We hypothesised that dominant males would be able to successfully monopolise the relatively small numbers of females present in the colony, leading to relatively high levels of polygyny. A total of 424 individuals (comprising 33 adult males, 101 adult females and 290 pups) sampled over eight years were genotyped at 20 microsatellites and reproductive success was analysed by genetically assigning parents. Paternity could only be assigned to 31 out of 290 pups (10.7%), despite our panel of genetic markers being highly informative and the genotyping error rate being very low. The strength of inferred polygyny was weak in comparison to previous genetic studies of the same species, with the most successful male fathering only seven pups over the entire course of the study. Our results show that, even in a species long regarded as a model for extreme polygyny, male reproductive skew can vary substantially among populations.
Development and Application of Cas13a-based Diagnostic Assay for Neisseria Gonorrhoeae Detection and Identification of Azithromycin Resistance

Gonorrhea caused by Neisseria gonorrhoeae has spread world-wide. Antimicrobial-resistant strains have emerged to an alarming level to most antibiotics including to the ceftriaxone-azithromycin combination, currently recommended as first-line dual therapy. Rapid testing for antimicrobial resistance will contribute to clinical decision-making for rational drug use and will slow this trend. Herein, we developed a Cas13a-based assay for N. gonorrhoeae detection (porA target) and azithromycin resistance identification (A2059G and C2611T point mutations). We evaluated the sensitivity and specificity of this method, and 10 copies per reaction can be achieved in porA detection and C2611T identification, with no cross-reactions. Comparison of the Cas13a-based assay (porA target) with Roche Cobas 4800 assay (n=23 urine samples) revealed 100% concordance. Isolated N. gonorrhoeae strains were used to validate the identification of A2059G and C2611T resistance mutations. All tested strains (8 A2059G strains, 8 C2611T strains, and 8 wild-type strains) were successfully distinguished by our assay and verified by testing MIC for azithromycin and sequencing the 23S rRNA gene. We adopted lateral flow for the SHERLOCK assay readout, which showed a visible difference between test group and NC group results. To further evaluate the capability of our assay, we tested 27 urethral swabs from patients with urethritis for N. gonorrhoeae detection and azithromycin-resistance identification. Of these, 62.96% (17/27) strains were detected with no mutant strains and confirmed by sequencing. In conclusion, the novel Cas13a-based assay for rapid and accurate N. gonorrhoeae detection combined with azithromycin drug resistance testing is a promising assay for application in clinical practice.
Validated machine learning algorithm with sub-clonal sensitivity reveals widespread pan-cancer human leukocyte antigen loss of heterozygosity

Human leukocyte antigen loss of heterozygosity (HLA LOH) allows cancer cells to escape immune recognition by deleting HLA alleles, causing the suppressed presentation of tumor neoantigens that would otherwise bind to them. Despite its importance in immunotherapy response, few methods exist to detect HLA LOH, and their accuracy is not well understood. Here, we develop DASH (Deletion of Allele-Specific HLAs), a novel machine learning-based algorithm to detect HLA LOH from paired tumor-normal sequencing data. Through validation with cell line mixtures and patient-specific digital PCR, we demonstrate increased sensitivity compared to previously published tools and pave the way for clinical utility. Using DASH on 611 patients across 15 tumor types, we found that 18% of patients had HLA LOH. Moreover, we show inflated HLA LOH rates compared to genome-wide LOH and correlations between CD274 (PD-L1) expression and MSI status, suggesting the HLA LOH is a key immune resistance strategy.
A dentate gyrus-CA3 inhibitory circuit promotes evolution of hippocampal-cortical ensembles during memory consolidation

Memories encoded in the dentate gyrus (DG) – CA3 circuit of the hippocampus are routed from CA1 to anterior cingulate cortex (ACC) for consolidation. Although CA1 parvalbumin inhibitory neurons (PV INs) orchestrate hippocampal-cortical communication, we know less about CA3 PV INs or DG – CA3 principal neuron – IN circuit mechanisms that contribute to evolution of hippocampal-cortical ensembles during memory consolidation. Using viral genetics to selectively mimic and boost an endogenous learning-dependent circuit mechanism, DG cell recruitment of CA3 PV INs and feed-forward inhibition (FFI) in CA3, in combination with longitudinal in vivo calcium imaging, we demonstrate that FFI facilitates formation and maintenance of context-associated neuronal ensembles in CA1. Increasing FFI in DG – CA3 promoted context specificity of neuronal ensembles in ACC over time and enhanced long-term contextual fear memory. In vivo LFP recordings in mice with increased FFI in DG – CA3 identified enhanced CA1 sharp-wave ripple – ACC spindle coupling as a potential network mechanism facilitating memory consolidation. Our findings illuminate how FFI in DG – CA3 dictates evolution of ensemble properties in CA1 and ACC during memory consolidation and suggest a teacher-like function for hippocampal CA1 in stabilization and re-organization of cortical representations.
Dynamic profiling and functional interpretation of histone lysine crotonylation and lactylation during neural development

Background Metabolites such as crotonyl-CoA and lactyl-CoA influence gene expression through covalently modifying histones, known as histone lysine crotonylation (Kcr) and histone lysine lactylation (Kla). However, their existence patterns, dynamic changes, biological functions, as well as associations with histone lysine acetylation (Kac) and gene expression during mammalian development remain largely unknown, which imped us from understanding the epigenetic regulations of histone lysine acylations. Results Histone Kcr and Kla are widely distributed and undergo global changes during neural development. By profiling genome-wide dynamics of H3K9ac, H3K9cr and H3K18la in combination with ATAC sequencing and RNA sequencing, we reveal that these histone marks cooperatively regulate chromatin state and gene expression, as well as promote transcriptome remodelling to favour cell fate transition in the developing telencephalon. Importantly, we demonstrate that global histone Kcr and Kla are not consequence of transcription and furtherly identify histone deacetylase 1-3 (HDAC1-3) as novel “erasers” of H3K18la. Taking advantage of induced differentiation system of P19 embryonal carcinoma (EC) cells, we find that a selective inhibitor of HDAC1-3, MS-275 pre-activates neural fate-related transcriptional programs via stimulating multiple histone lysine acylations simultaneously. Conclusions Our study uncover the interplays between histone lysine acylations to regulate gene expression and the differentiation-promoting functions of histone Kcr and Kla during development, and provide evidence that multiple histone lysine actlations synchronously alternate to orchestrate transcriptome responding under HDACs inhibition.
Brain-inspired Weighted Normalization for CNN Image Classification

We studied a local normalization paradigm, namely weighted normalization, that better reflects the current understanding of the brain. Specifically, the normalization weight is trainable, and has a more realistic surround pool selection. Weighted normalization outperformed other normalizations in image classification tasks on Cifar10, Imagenet and a customized textured MNIST dataset. The superior performance is more prominent when the CNN is shallow. The good performance of weighted normalization may be related to its statistical effect of gaussianizing the responses.
Development of Lentiviral Vectors Pseudotyped With Influenza B Hemagglutinins: Application in Vaccine Immunogenicity, mAb Potency, and Sero-Surveillance Studies

Influenza B viruses (IBV) cause respiratory disease epidemics in humans and are therefore components of seasonal influenza vaccines. Serological methods are employed to evaluate vaccine immunogenicity prior to licensure. However, classical methods to assess influenza vaccine immunogenicity such as the hemagglutination inhibition assay (HI) and the serial radial hemolysis assay (SRH), have been proven to have many limitations. As such, there is a need to develop innovative methods that can improve on these traditional assays and provide advantages such as ease of production and access, safety, reproducibility, and specificity. It has been previously demonstrated that the use of replication-defective viruses, such as lentiviral vectors pseudotyped with influenza A hemagglutinins in microneutralization assays (pMN) is a safe and sensitive alternative to study antibody responses elicited by natural influenza infection or vaccination. Consequently, we have produced Influenza B hemagglutinin-pseudotypes (IBV PV) using plasmid-directed transfection. To activate influenza B hemagglutinin, we have explored the use of proteases in increasing PV titers via their co-transfection during pseudotype virus production. When tested for their ability to transduce target cells, the influenza B pseudotypes produced exhibit tropism for different cell lines. The pseudotypes were evaluated as alternatives to live virus in microneutralization assays using reference sera standards, mouse and human sera collected during vaccine immunogenicity studies, surveillance sera from seals, and monoclonal antibodies (mAbs) against IBV. The influenza B pseudotype pMN was found to effectively detect neutralizing and cross-reactive responses in all assays and shows promise as an effective and versatile tool in influenza research.
Meaning and Measures: Interpreting and Evaluating Complexity Metrics

Research on language complexity has been abundant and manifold in the past two decades. Within typology, it has to a very large extent been motivated by the question of whether all languages are equally complex, and if not, which language-external factors affect the distribution of complexity across languages. To address this and other questions, a plethora of different metrics and approaches has been put forward to measure the complexity of languages and language varieties. Against this backdrop we address three major gaps in the literature by discussing statistical, theoretical, and methodological problems related to the interpretation of complexity measures. First, we explore core statistical concepts to assess the meaningfulness of measured differences and distributions in complexity based on two case studies. In other words, we assess whether observed measurements are neither random nor negligible. Second, we discuss the common mismatch between measures and their intended meaning, namely, the fact that absolute complexity measures are often used to address hypotheses on relative complexity. Third, in the absence of a gold standard for complexity metrics, we suggest that existing measures be evaluated by drawing on cognitive methods and relating them to real-world cognitive phenomena. We conclude by highlighting the theoretical and methodological implications for future complexity research.
Adaptive Cognitive Mechanisms to Maintain Calibrated Trust and Reliance in Automation

Trust calibration for a human–machine team is the process by which a human adjusts their expectations of the automation’s reliability and trustworthiness; adaptive support for trust calibration is needed to engender appropriate reliance on automation. Herein, we leverage an instance-based learning ACT-R cognitive model of decisions to obtain and rely on an automated assistant for visual search in a UAV interface. This cognitive model matches well with the human predictive power statistics measuring reliance decisions; we obtain from the model an internal estimate of automation reliability that mirrors human subjective ratings. The model is able to predict the effect of various potential disruptions, such as environmental changes or particular classes of adversarial intrusions on human trust in automation. Finally, we consider the use of model predictions to improve automation transparency that account for human cognitive biases in order to optimize the bidirectional interaction between human and machine through supporting trust calibration. The implications of our findings for the design of reliable and trustworthy automation are discussed.
Deep Cross-User Models Reduce the Training Burden in Myoelectric Control

The effort, focus, and time to collect data and train EMG pattern recognition systems is one of the largest barriers to their widespread adoption in commercial applications. In addition to multiple repetitions of motions, including exemplars of confounding factors during the training protocol has been shown to be critical for robust machine learning models. This added training burden is prohibitive for most regular use cases, so cross-user models have been proposed that could leverage inter-repetition variability supplied by other users. Existing cross-user models have not yet achieved performance levels sufficient for commercialization and require users to closely adhere to a training protocol that is impractical without expert guidance. In this work, we extend a previously reported adaptive domain adversarial neural network (ADANN) to a cross-subject framework that requires very little training data from the end-user. We compare its performance to single-repetition within-user training and the previous state-of-the-art cross-subject technique, canonical correlation analysis (CCA). ADANN significantly outperformed CCA for both intact-limb (86.8–96.2%) and amputee (64.1–84.2%) populations. Moreover, the ADANN adaptation computation time was substantially lower than the time otherwise devoted to conducting a full within-subject training protocol. This study shows that cross-user models, enabled by deep-learned adaptations, may be a viable option for improved generalized pattern recognition-based myoelectric control.
Stride-to-Stride Variability of the Center of Mass in Male Trained Runners After an Exhaustive Run: A Three Dimensional Movement Variability Analysis With a Subject-Specific Anthropometric Model

The motion of the human body can be described by the motion of its center of mass (CoM). Since the trajectory of the CoM is a crucial variable during running, one can assume that trained runners would try to keep their CoM trajectory constant from stride to stride. However, when exposed to fatigue, runners might have to adapt certain biomechanical parameters. The Uncontrolled Manifold approach (UCM) and the Tolerance, Noise, and Covariation (TNC) approach are used to analyze changes in movement variability while considering the overall task of keeping a certain task relevant variable constant. The purpose of this study was to investigate if and how runners adjust their CoM trajectory during a run to fatigue at a constant speed on a treadmill and how fatigue affects the variability of the CoM trajectory. Additionally, the results obtained with the TNC approach were compared to the results obtained with the UCM analysis in an earlier study on the same dataset. Therefore, two TNC analyses were conducted to assess effects of fatigue on the CoM trajectory from two viewpoints: one analyzing the CoM with respect to a lab coordinate system (PVlab) and another one analyzing the CoM with respect to the right foot (PVfoot). Full body kinematics of 13 healthy young athletes were captured in a rested and in a fatigued state and an anthropometric model was used to calculate the CoM based on the joint angles. Variability was quantified by the coefficient of variation of the length of the position vector of the CoM and by the components Tolerance, Noise, and Covariation which were analyzed both in 3D and the projections in the vertical, anterior-posterior and medio-lateral coordinate axes. Concerning PVlab we found that runners increased their stride-to-stride variability in medio-lateral direction (1%). Concerning PVfoot we found that runners lowered their CoM (4 mm) and increased their stride-to-stride variability in the absorption phase in both 3D and in the vertical direction. Although we identified statistically relevant differences between the two running states, we have to point out that the effects were small (CV ≤ 1%) and must be interpreted cautiously.
Small Landscape Elements Double Connectivity in Highly Fragmented Areas of the Brazilian Atlantic Forest

The Atlantic Forest in Brazil is a biodiversity hotspot, yet its diverse ecosystems and species are becoming increasingly threatened by habitat loss and extreme habitat fragmentation. Most habitat patches of Atlantic Forest are dispersed across agricultural landscapes (e.g., grazing and cropping) in relatively small and isolated fragments (80% < 50 ha). Forest fragments < 1 ha, scattered trees in pastures, tree lines on trenches and fences, and remnant riparian forest, collectively called here Small Landscape Elements (SLEs), are very common in this context. While these SLEs make up much of the Atlantic Forests footprint, very little is known about their role or impact on the persistence and conservation of species. In this study, we investigate the role of SLEs on landscape configuration, particularly their contribution toward landscape connectivity of individual species and the genetic flow of species between larger forest fragments. We randomly selected 20 buffers of 707 hectares within a 411,670 hectare area of the Atlantic Forest that was completely covered by forest in the past located in the south of Minas Gerais State, Brazil. The forest cover randomly varied between these buffers. We used graph theory to measure landscape connectivity as the probability of connectivity for different disperser movement types between landscape knots (habitat patches). We used three estimated dispersal distances in the models: pollen disperser insect (50 m), low-mobility seed disperser bird (100 m) and high-mobility seed disperser bird (760 m). The SLEs together increased the probability of connection by roughly 50%, for all model dispersers, if compared to a theoretical baseline landscape containing no SLEs. Of all SLEs, riparian forests contribute the most toward enhancing landscape connectivity. In these highly fragmented landscapes, such as the Atlantic Forest (>70%), the position of SLEs within the landscapes was more important than their respective areas for connectivity. Although the landscapes were deeply fragmented, we showed that the presence of SLEs can increase connectivity and reduce further biodiversity loss in the Atlantic Forest.
Noninvasive Ventilation in Patients With COVID-19-Related Acute Hypoxemic Respiratory Failure: A Retrospective Cohort Study

Introduction: Noninvasive ventilation (NIV) has been used to alleviate hypoxemia and dyspnea, but there is no consensus on the application of NIV in patients with coronavirus disease 2019 (COVID-19). Some staff use NIV as the rescue therapy which might lead to the adverse outcomes. This study was to identify early factors associated with intubation to help the medical staff select appropriate patients for receiving NIV treatment. Methods: Patients with laboratory-confirmed COVID-19 who were treated with NIV in emergency department or ICU of the Third People's Hospital (the only designated hospital for treating COVID-19 in Shenzhen) between January 1 and August 31, 2020, were retrospectively analyzed. Results: Thirty-nine patients with COVID-19 treated with NIV were included; of them, 16 (41%) received endotracheal intubation and 3 (8%) died. Significant differences were observed between intubated and non-intubated patients in PaO2/FiO2 before NIV initiation, hospitalization duration, NIV as the rescue therapy, and PaO2/FiO2 of ≤200 mmHg after 1–2 h of NIV initiation. Notably, 1–2 h after NIV initiation, a PaO2/FiO2 of ≤200 mmHg (odds ratio [OR], 9.35; 95% confidence interval [CI], 1.84–47.62; P = 0.007) and NIV as the rescue therapy (OR, 5.43; 95% CI, 1.09–27.12; P = 0.039) were the risk factors for intubation. Conclusions: In patients with COVID-19-related acute hypoxemic respiratory failure receiving NIV, close attention should be paid to PaO2/FiO2 after 1–2 h of NIV initiation. Also, using NIV as rescue therapy should draw our awareness that it might delay escalation of respiratory support and lead to adverse outcomes.
Cochlin Deficiency Protects Against Noise-Induced Hearing Loss

Cochlin is the most abundant protein in the inner ear. To study its function in response to noise trauma, we exposed adolescent wild-type (Coch+/+) and cochlin knock-out (Coch–/–) mice to noise (8–16 kHz, 103 dB SPL, 2 h) that causes a permanent threshold shift and hair cell loss. Two weeks after noise exposure, Coch–/– mice had substantially less elevation in noise-induced auditory thresholds and hair cell loss than Coch+/+ mice, consistent with cochlin deficiency providing protection from noise trauma. Comparison of pre-noise exposure thresholds of auditory brain stem responses (ABRs) and distortion product otoacoustic emissions (DPOAEs) in Coch–/– mice and Coch+/+ littermates revealed a small and significant elevation in thresholds of Coch–/– mice, overall consistent with a small conductive hearing loss in Coch–/– mice. We show quantitatively that the pro-inflammatory component of cochlin, LCCL, is upregulated after noise exposure in perilymph of wild-type mice compared to unexposed mice, as is the enzyme catalyzing LCCL release, aggrecanase1, encoded by Adamts4. We further show that upregulation of pro-inflammatory cytokines in perilymph and cochlear soft-tissue after noise exposure is lower in cochlin knock-out than wild-type mice. Taken together, our data demonstrate for the first time that cochlin deficiency results in conductive hearing loss that protects against physiologic and molecular effects of noise trauma.