Miracle-dz/UniFAR-FTUs huggingface dataset:
Loss of pH switch unique to SARS-CoV2 supports unfamiliar virus pathology

Cell surface receptor engagement is a critical aspect of viral infection. This paper compares the dynamics of virus-receptor interactions for SARS-CoV (CoV1) and CoV2. At low (endosomal) pH, the binding free energy landscape of CoV1 and CoV2 interactions with the angiotensin-converting enzyme 2 (ACE2) receptor is almost the same. However, at neutral pH the landscape is different due to the loss of a pH-switch (His445Lys) in the receptor binding domain (RBD) of CoV2 relative to CoV1. Namely, CoV1 stabilizes a transition state above the bound state. In situations where small external strains are applied by, say, shear flow in the respiratory system, the off rate of the viral particle is enhanced. As a result, CoV1 virions are expected to detach from cell surfaces in time scales that are much faster than the time needed for other receptors to reach out and stabilize virus attachment. On the other hand, the loss of this pH-switch, which sequence alignments show is unique to CoV2, eliminates the transition state and allows the virus to stay bound to the ACE2 receptor for time scales compatible with the recruitment of additional ACE2 receptors diffusing in the cell membrane. This has important implications for viral infection and its pathology. CoV1 does not trigger high infectivity in the nasal area because it either rapidly drifts down the respiratory tract or is exhaled. By contrast, this novel mutation in CoV2 should not only retain the infection in the nasal cavity until ACE2-rich cells are sufficiently depleted, but also require fewer particles for infection. This mechanism explains observed longer incubation times, extended period of viral shedding, and higher rate of transmission. These considerations governing viral entry suggest that number of ACE2-rich cells in human nasal mucosa, which should be significantly smaller for children (and females relative to males), should also correlate with onset of viral load that could be a determinant of higher virus susceptibility. Critical implications for the development of new vaccines to combat current and future pandemics that, like SARS-CoV2, export evolutionarily successful strains via higher transmission rates by viral retention in nasal epithelium are also discussed.
Ontogeny of a sexual dimorphism in tiger salamanders

Sexual dimorphism results when the sexes differ in the degree to which trait elaboration confers a reproductive or survival advantage. Trait size dimorphism is often reported in terms of allometry, typically using adults of varying ages (static allometry). A static allometric analysis of tail length in breeding tiger salamanders (Ambystoma tigrinum (Green, 1825)) revealed that tail length is a positive allometric trait in both sexes, as well as a sexually dimorphic trait. Although static analyses are common in the literature, ontogenetic allometric analyses in which individuals are measured through time are preferred because they provide insight into the heterochronic process underlying trait divergence between the sexes and which sex is diverging from its earlier growth trajectory. I reared 91 individuals from the zygote stage to sexual maturity. An ontogenetic analysis revealed that tail length was isometric in larvae and young metamorphs of both sexes; however, tail length became allometric in males bu.
Automated Discovery of Local Rules for Desired Collective-Level Behavior Through Reinforcement Learning

Complex global behavior patterns can emerge from very simple local interactions between many agents. However, no local interaction rules have been identified that generate some patterns observed in nature, for example the rotating balls, rotating tornadoes and the full-core rotating mills observed in fish collectives. Here we show that locally interacting agents modeled with a minimal cognitive system can produce these collective patterns. We obtained this result by using recent advances in reinforcement learning to systematically solve the inverse modeling problem: given an observed collective behavior, we automatically find a policy generating it. Our agents are modeled as processing the information from neighbor agents to choose actions with a neural network and move in an environment of simulated physics. Even though every agent is equipped with its own neural network, all agents have the same network architecture and parameter values, ensuring in this way that a single policy is responsible for the emergence of a given pattern. We find the final policies by tuning the neural network weights until the produced collective behavior approaches the desired one. By using modular neural networks with modules using a small number of inputs and outputs, we built an interpretable model of collective motion. This enabled us to analyse the policies obtained. We found a similar general structure for the four different collective patterns, not dissimilar to the one we have previously inferred from experimental zebrafish trajectories; but we also found consistent differences between policies generating the different collective pattern, for example repulsion in the vertical direction for the more three-dimensional structures of the sphere and tornado. Our results illustrate how new advances in artificial intelligence, and specifically in reinforcement learning, allow new approaches to analysis and modeling of collective behavior.
Correlation Between Decreased Amygdala Subnuclei Volumes and Impaired Cognitive Functions in Pediatric Bipolar Disorder

Background The amygdala has been proposed to be involved in the pathophysiology of pediatric and adult bipolar disorder (BD). The goal of this structural magnetic resonance imaging (sMRI) study was to investigate the morphometric characteristics of amygdala subnuclei in patients with pediatric bipolar disorder (PBD) compared to healthy controls (HCs). Simultaneously, we examined correlation between amygdala subnuclei volumes and cognitive dysfunction. Materials and Methods We assessed 40 adolescent outpatients, diagnosed with manic or euthymic PBD according to the DSM-5 criteria for BD and 19 HCs. Cognitive functions were evaluated using a Stroop color-word test (SCWT), trail making test (TMT), visual reproduction immediate recall subtest (VR I), and digit span subtest (DST). Amygdala and its subnuclei structures were automated segmented using FreeSurfer software and the volumes of them were compared between groups and correlation with clinical and cognitive outcomes was conducted. Results Manic patients exhibited significantly decreased volumes in the bilateral whole amygdala and its basal nucleus, cortico-amygdaloid transition (CAT), and accessory basal nucleus (ABN) compared with HCs. Euthymic patients had decreased volume in the bilateral ABN and left CAT. In addition, we found significant positive associations between VR I scores and the right whole amygdala and its bilateral basal, right lateral, and ABN volumes in the manic group. Conclusion These findings support previous reports of smaller amygdala volumes and cognitive dysfunctions in PBD, and further mapping abnormalities to specific amygdala subnuclei. Correlation between basolateral volume and VR I of PBD may expand our understanding of neural abnormalities that could be targeted by treatment.
Current Limitations for the Assessment of the Role of the Gut Microbiome for Attention Deficit Hyperactivity Disorder (ADHD)

High throughput sequencing of bacterial 16S rRNA genes and metagenomes were applied to analyze complex microbial communities inhabiting the human gut and other body sites, and their role in numerous diseases. Studies in animals were important for elucidating the effects of the gut microbiota on the brain and behavior, and the responsible mechanisms. Recent studies in patients have identified bacterial taxa of the gut microbiome possibly impacting different neurological and psychiatric disorders including ADHD. Furthermore, antibiotic treatment of infections globally shape compositions of gut microbiota and might indirectly influence ADHD development. However, published studies revealed still partially incongruent results. Potential reasons for the still ill defined role of gut microbiota in ADHD comprise a) different study designs b) small number of patients c) different age groups analyzed d) inclusion of only treatment naive patients versus patients under medication e) differences of males versus females ratios and f) the heterogenous technology applied for microbiome sequence analysis. Furthermore, the complex interplay between the gut microbiome and individual host genetic factors requires much larger sample sizes and additional patient genome information. Alternative treatment options like probiotics or dietary interventions for ADHD therapy might offer new opportunities to prevent or treat this increasingly common disease. Clearly, further studies are needed to clarify molecular mechanisms imparting the gut brain axis as basis to modify commensal microbiota or their functions to target ADHD. The purpose of this review is to evaluate the most recent literature on the role of the gut microbiome in ADHD.
Chest Computed Tomography and Lung Ultrasound Findings in COVID-19 Pneumonia: A Pocket Review for Non-radiologists

COVID-19 is an infectious disease that has quickly spread worldwide, causing a pandemic. The main clinical manifestation is pneumonia. The most important test for the diagnosis is represented by RT-PCR, but, given the limited sensitivity, further radiological examinations are necessary. We reviewed the literature to highlight the typical manifestations and advantages of chest computed tomography and lung ultrasound in COVID-19 pneumonia in order to assist clinical researchers in the management of this disease.
Reperfusion Into Severely Damaged Brain Tissue Is Associated With Occurrence of Parenchymal Hemorrhage for Acute Ischemic Stroke

Background and Purpose: This study aims to quantify the reperfusion status within severely damaged brain tissue and to evaluate its relationship with high grade of hemorrhagic transformation (HT). Methods: Pseudo-continuous ASL was performed along with DWI in 102 patients within 24 h post-treatments. The infarction core was identified using ADC values <550 × 10−6 mm2/s. CBF within the infarction core and its contralateral counterpart were acquired. CBF at the 25th, median, and 75th percentiles of the contralateral counterpart were used as thresholds and the ASL reperfusion volume above the threshold was labeled as vol-25, -50, and -75, respectively. Recanalization was defined according to Thrombolysis in Myocardial Infarction (TIMI) criteria. Results: Quantified reperfusion within the infarction core differed significantly in patients with complete and incomplete recanalization. In the ROC analysis for the prediction of parenchymal hematoma (PH), ASL reperfusion vol-25 had the highest area under the curve (AUC) when compared with ASL vol-50 and ASL vol-75. ASL reperfusion vol-25 had significantly higher AUC compared with ADC threshold volume in the prediction of PH (0.783 vs. 0.685, P = 0.0036) and PH-2 (0.844 vs. 0.754, P = 0.0035). In stepwise multivariate logistic regression analysis, only ASL reperfusion vol-25 emerged as an independent predictor of PH (OR = 3.51, 95% CI: 1.65–7.45, P < 0.001) and PH-2 (OR = 2.32, 95% CI: 1.13–4.76, P = 0.022). Conclusions: Increased reperfusion volume within severely damaged brain tissue is associated with the occurrence of higher grade of HT.
Estimation of Genetic-Gain Multipliers for Modeling Douglas-Fir Height and Diameter Growth

Methods were developed to calculate genetic-gain multipliers for use in individual-tree models that predict periodic height and diameter growth of coast Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) in the Pacific Northwest. Genetic-gain multipliers are used in growth models that are typically based on extensive measurements of unimproved or "woods-run" stands, to adjust for the increased growth of stands generated from improved seedlots. First-generation progeny test data from multiple breeding zones in the Northwest Tree Improvement Cooperative were used. Data sets included initial heights and diameters and 5-year growth increments for 10- and 15-year-old trees that were identified by open-pollinated families. Nonlinear mixed-effect models were initially developed to predict the average growth of trees in all families, which, taken together, represented woods-run populations. Phenotypic differences in growth rates were then calculated at the family level. Differences among families in height and diameter growth rates were examined using methods from quantitative genetics and raw phenotypic values. Because gain in total height and diameter at age 10 years is currently the most widely available genetic information for improved Douglas-fir, equations were developed to predict genetic-gain multipliers from family breeding values for these traits. A verification procedure illustrated how incorporating multipliers in growth projections could reduce the mean-square error of predicted growth of selected families. FOR. SCI, 54(6):588-596.
Applications of Natural Language Processing in Bilingual Language Teaching: An Indonesian-English Case Study

Multilingual corpora are difficult to compile and a classroom setting adds pedagogy to the mix of factors which make this data so rich and problematic to classify. In this paper, we set out methodological considerations of using automated speech recognition to build a corpus of teacher speech in an Indonesian language classroom. Our preliminary results (64% word error rate) suggest these tools have the potential to speed data collection in this context. We provide practical examples of our data structure, details of our piloted computer-assisted processes, and fine-grained error analysis. Our study is informed and directed by genuine research questions and discussion in both the education and computational linguistics fields. We highlight some of the benefits and risks of using these emerging technologies to analyze the complex work of language teachers and in education more generally.
Fas-Fas Ligand Interactions Are Essential for the Binding to and Killing of Activated Macrophages by γδ T Cells

γδ T cells have a direct role in resolving the host immune response to infection by eliminating populations of activated macrophages. Macrophage reactivity resides within the Vγ1/Vδ6. 3 subset of γδ T cells, which have the ability to kill activated macrophages following infection with Listeria monocytogenes (Lm). However, it is not known how γδ T cell macrophage cytocidal activity is regulated, or what effector mechanisms γδ T cells use to kill activated macrophages. Using a macrophage-T cell coculture system in which peritoneal macrophages from naive or Lm-infected TCRδ−/− mice were incubated with splenocytes from wild-type and Fas ligand (FasL)-deficient mice (gld), the ability of Vγ1 T cells to bind macrophages was shown to be dependent upon Fas-FasL interactions. Combinations of anti-TCR and FasL Abs completely abolished binding to and killing of activated macrophages by Vγ1 T cells. In addition, confocal microscopy showed that Fas and the TCR colocalized on Vγ1 T cells at points of contact with macrophages. Collectively, these studies identify an accessory or coreceptor-like function for Fas-FasL that is essential for the interaction of Vγ1 T cells with activated macrophages and their elimination during the resolution stage of pathogen-induced immune responses.
Potent Natural Antioxidant Carveol Attenuates MCAO-Stress Induced Oxidative, Neurodegeneration by Regulating the Nrf-2 Pathway

Ischemic stroke is a severe neurological disorder with a high prevalence rate in developed countries. It is characterized by permanent or transient cerebral ischemia and it activates syndrome of pathological events such as membrane depolarization, glutamate excitotoxicity, and intracellular calcium buildup. Carveol is widely employed as anti-inflammatory and antioxidant in traditional Chinese medicine. In the present study, the neuroprotective effects of post-treated carveol were demonstrated against transient middle cerebral artery occlusion (MCAO) induced focal ischemic cerebral injury. Male Sprague Dawley (SD) rats were subjected to two different experimental protocols to determine the dose and effects of carveol, and to demonstrate the underlying role of the nuclear factor E2-related factor (Nrf2) pathway. Our results showed that MCAO induced marked neuronal injury in the ipsilateral cortex and striatum associated with higher inflammatory cytokines expression, along with apoptotic markers such as caspase-3 and the phosphorylated c-Jun N-terminal kinase (JNK). Furthermore, MCAO induced a marked increase in oxidative stress as evidenced by high lipid peroxidase (LPO) content accompanied by the depressed antioxidant system. Carveol significantly reversed the oxidative stress and downregulated inflammatory cascades by enhancing endogenous antioxidant mechanisms including the Nrf2 gene, which critically regulates the expression of several downstream antioxidants. Further, to determine the possible involvement of Nrf2 in carveol mediated neuroprotection, we antagonized Nrf2 by all-trans retinoic acid (ATRA), and such treatment abrogated the protective effects of carveol accompanied with exaggerated neuronal toxicity as demonstrated by higher infarction area. The target effects of carveol were further supported by molecular docking analysis of drug–protein interactions. Together, our findings suggest that carveol could activate endogenous master anti-oxidant Nrf2, which further regulates the expression of downstream antioxidants, eventually ameliorating MCAO-induced neuroinflammation and neurodegeneration.
Combining Threshold, Thurstonian and Classical Linear Models in Horse Genetic Evaluations for Endurance Competitions

Simple Summary Endurance competitions are carried out across the countryside worldwide, where the adapted physical and metabolic conditions of the horses are essential to satisfactorily end the competition. Horse breeding programs usually use the rank and time to improve the performance of horses in competitions. It is also relevant to analyse the placing trait i.e., whether or not a horse finishes the race. The discontinuous nature of rank and placing traits require special methodologies to deal with them. Here we have used 6135 endurance records from 1419 horses, with a pedigree containing 10,868 animals, to develop a multitrait model with a new free software tool (GIBBSTHUR). The obtained results suggest that it is possible to ignore the race time and use rank and placing to perform the genetic evaluation in endurance horse populations. Abstract The racing time and rank at finish traits are commonly used for endurance horse breeding programs as a measure of their performance. Even so, given the nature of endurance competitions, many horses do not finish the race. However, the exclusion of non placed horses from the dataset could have an influence on the prediction of individual breeding values. The objective of the present paper was to develop a multitrait model including race time (T), rank (R) and placing (P), with different methodologies, to improve the genetic evaluation in endurance competitions in Spain. The database contained 6135 records from 1419 horses, with 35% of the records not placed. Horse pedigree included 10868 animals, with 52% Arab Horses. All models included gender, age and race effect as systematic effects and combined different random effects beside the animal and residual effects: rider, permanent environmental effect, and interaction horse-rider. The kilometers per race was included as a covariate for T. Heritabilities were estimated as moderately low, ranging from 0.06 to 0.14 for T, 0.09 to 0.15 for P, and 0.07 to 0.17 for R, depending on the model. T and R appeared mostly as inverse measures of the same trait due to their high genetic correlation, suggesting that T can be ignored in future genetic evaluations. P was the most independent trait from the genetic correlations. The possibility of simultaneously processing the threshold, Thurstonian and continuous traits has opened new opportunities for genetic evaluation in horse populations, and much more practical genetic evaluations can be done to help a proper genetic selection.
Androgen receptor affects the response to immune checkpoint therapy by suppressing PD-L1 in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a heterogeneous malignancy with gender-related differences in onset and course. Androgen receptor (AR), a male hormone receptor, is critical in the initiation and progression of HCC. The role of AR in HCC has been mechanistically characterized and anti-AR therapies have been developed, showing limited efficacy. Immunotherapy targeting immune checkpoint proteins may substantially improve the clinical management of HCC. The mechanism by which AR influences HCC immune state remains unclear. In this study, we demonstrated that AR negatively regulated PD-L1, by acting as a transcriptional repressor of PD-L1. Notably, AR over-expression in HCC cells enhanced CD8+T function in vitro. We then verified the AR/PD-L1 correlation in patients. In animal experiment we found that lower AR expressed tumor achieved better response to PD-L1 inhibitor. Thus, AR suppressed PD-L1 expression, possibly contributing to gender disparity in HCC. Better understanding of the roles of AR during HCC initiation and progression will provide a novel angle to develop potential HCC immunotherapies.