Miracle-dz/UniFAR-FTUs huggingface dataset:
Human Regulatory Dendritic Cells Develop From Monocytes in Response to Signals From Regulatory and Helper T Cells

Dendritic cells (DCs) are powerful antigen presenting cells, derived from bone marrow progenitors (cDCs) and monocytes (moDCs), that can shape the immune response by priming either proinflammatory or tolerogenic immune effector cells. The cellular mechanisms responsible for the generation of DCs that will prime a proinflammatory or tolerogenic response are poorly understood. Here we describe a novel mechanism by which tolerogenic DCs are formed from monocytes. When human monocytes were cultured with CD4+FoxP3+ natural regulatory T cells (Tregs) and T helper cells (Th) from healthy donor blood, they differentiated into regulatory DCs (DCReg), capable of generating induced Tregs from naïve T cells. DCReg exhibited morphology, surface phenotype, cytokine secretion, and transcriptome that were distinct from other moDCs including those derived from monocytes cultured with Th or with GM-CSF/IL-4, as well as macrophages (MΦ). Direct cell contact between monocytes, Tregs and Th, along with Treg-derived CTLA-4, IL-10 and TGF-β, was required for the phenotypic differentiation of DCReg, although only IL-10 was required for imprinting the Treg-inducing capacity of DCReg. High ratios of Treg:Th, along with monocytes and DCReg similar in function and phenotype to those induced in vitro, were present in situ in human colorectal cancer specimens. Thus, through the combined actions of Tregs and Th, monocytes differentiate into DCs with regulatory properties, forming a positive feedback loop to reinforce Treg initiated immune regulation. This mechanism may contribute to immune tolerance in tissues such as tumors, which contain an abundance of Tregs, Th and monocytes.
A Four-Step Method for the Development of an ADHD-VR Digital Game Diagnostic Tool Prototype for Children Using a DL Model

Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder among children resulting in disturbances in their daily functioning. Virtual reality (VR) and machine learning technologies, such as deep learning (DL) application, are promising diagnostic tools for ADHD in the near future because VR provides stimuli to replace real stimuli and recreate experiences with high realism. It also creates a playful virtual environment and reduces stress in children. The DL model is a subset of machine learning that can transform input and output data into diagnostic values using convolutional neural network systems. By using a sensitive and specific ADHD-VR diagnostic tool prototype for children with DL model, ADHD can be diagnosed more easily and accurately, especially in places with few mental health resources or where tele-consultation is possible. To date, several virtual reality-continuous performance test (VR-CPT) diagnostic tools have been developed for ADHD; however, they do not include a machine learning or deep learning application. A diagnostic tool development study needs a trustworthy and applicable study design and conduct to ensure the completeness and transparency of the report of the accuracy of the diagnostic tool. The proposed four-step method is a mixed-method research design that combines qualitative and quantitative approaches to reduce bias and collect essential information to ensure the trustworthiness and relevance of the study findings. Therefore, this study aimed to present a brief review of a ADHD-VR digital game diagnostic tool prototype with a DL model for children and the proposed four-step method for its development.
Readaptation Treatment of Mal de Debarquement Syndrome With a Virtual Reality App: A Pilot Study

Mal de Debarquement syndrome (MdDS) is composed of constant phantom sensations of motion, which are frequently accompanied by increased sensitivity to light, inability to walk on a patterned floor, the sensation of ear fullness, head pressure, anxiety, and depression. This disabling condition generally occurs in premenopausal women within 2 days after prolonged passive motion (e.g., travel on a cruise ship, plane, or in a car). It has been previously hypothesized that MdDS is the result of maladaptive changes in the polysynaptic vestibulo-ocular reflex (VOR) pathway called velocity storage. Past research indicates that full-field optokinetic stimulation is an optimal way to activate velocity storage. Unfortunately, such devices are typically bulky and not commonly available. We questioned whether virtual reality (VR) goggles with a restricted visual field could effectively simulate a laboratory environment for MdDS treatment. A stripes program for optokinetic stimulation was implemented using Google Daydream Viewer. Five female patients (42 ± 10 years; range 26–50), whose average MdDS symptom duration was 2 months, participated in this study. Four patients had symptoms triggered by prolonged passive motion, and in one, symptoms spontaneously occurred. Symptom severity was self-scored by patients on a scale of 0–10, where 0 is no symptoms at all and 10 is the strongest symptoms that the patient could imagine. Static posturography was obtained to determine objective changes in body motion. The treatment was considered effective if the patient's subjective score improved by at least 50%. All five patients reported immediate improvement. On 2-month follow-ups, symptoms returned only in one patient. These data provide proof of concept for the limited-visual-field goggles potentially having clinical utility as a substitute for full-field optokinetic stimulation in treating patients with MdDS in clinics or via telemedicine.
Effects of UV-B on Environmental Preference and Egg Parasitization by Trichogramma Wasps (Hymenoptera: Trichogrammatidae)

Abstract The intensity of ultraviolet (UV) radiation varies widely in space, both across the globe and over small spatial scales (a few millimeters), depending on patterns of light and shade. Gradients of UV radiation can control the movement of organisms on landscapes and how the organisms perform. It is likely that insects are at high risk from UV radiation because of their small size; radiation may penetrate significantly deeper into insect tissues than into larger organisms, thereby disproportionately affecting their performance. We investigated the effects of UV radiation on the behavior and parasitism success of the agriculturally important egg parasitoid wasp, Trichogramma spp. We found that Trichogramma preferred to move toward higher intensities of UV-B radiation and parasitized more eggs in areas with higher UV-B radiation. However, higher UV-B radiation reduced the number of adult wasps emerging from host eggs. Trichogramma reproductive behavior may, therefore, be maladaptive depending on environmental context. These results could be of particular importance in the agricultural release of Trichogramma, especially in greenhouse settings, where levels of UV-B radiation are low.
Leader–Member Exchange Fosters Beneficial and Prevents Detrimental Workplace Behavior: Organizational Identification as the Linking Pin

Discretionary behaviors, such as counterproductive work behavior (CWB) and organizational citizenship behavior (OCB), directly refer to an organization’s normative expectations. As such, employees engaging in these behaviors violate or exceed organizational norms, respectively. An employee’s relationship quality with his or her supervisor [i.e., leader–member exchange (LMX)] has been found to be a prominent antecedent of employees’ workplace behavior. However, the actual mechanisms that link LMX and discretionary behaviors (i.e., CWB and OCB) are not yet well understood. Integrating social exchange as well as the social identity theory, we present an employee’s organizational identification (OI) as a mechanism that sheds light on why LMX leads to employees’ subsequent discretionary behavior. Across four empirical studies employing complementary study designs, we demonstrate that LMX is positively associated with OI, which, in turn, curbs CWB and fosters OCB. Specifically, this pattern of findings is consistent across (1) a cross-sectional study with 188 Swiss employees, (2) a time-lagged study with 502 Swiss employees, (3) an online recall experiment with 131 US participants, and (4) an online vignette experiment with 139 US participants. In sum, we present an integrative theoretical model and respective empirical support to shed light on OI as a pivotal mechanism that can explain why the relationship quality with one’s supervisor can simultaneously serve as a deterrent for CWB and foster OCB.
Differential Roles of IDO1 and IDO2 in T and B Cell Inflammatory Immune Responses

Indoleamine-2,3-dioxygenase (IDO)1 and IDO2 are two closely related tryptophan catabolizing enzymes encoded by linked genes. The IDO pathway is also immunomodulatory, with IDO1 well-characterized as a mediator of tumor immune evasion. Due to its homology with IDO1, IDO2 has been proposed to have a similar immunoregulatory function. Indeed, IDO2, like IDO1, is necessary for the differentiation of regulatory T cells in vitro. However, compared to IDO1, in vivo studies demonstrated a contrasting role for IDO2, with experiments in preclinical models of autoimmune arthritis establishing a proinflammatory role for IDO2 in mediating B and T cell activation driving autoimmune disease. Given their potentially opposing roles in inflammatory responses, interpretation of results obtained using IDO1 or IDO2 single knockout mice could be complicated by the expression of the other enzyme. Here we use IDO1 and IDO2 single and double knockout (dko) mice to define the differential roles of IDO1 and IDO2 in B cell-mediated immune responses. Autoreactive T and B cell responses and severity of joint inflammation were decreased in IDO2 ko, but not IDO1 ko arthritic mice. Dko mice had a reduction in the number of autoantibody secreting cells and severity of arthritis: however, percentages of differentiated T cells and their associated cytokines were not reduced compared to IDO1 ko or wild-type mice. These data suggest that autoreactive B cell responses are mediated by IDO2, while autoreactive T cell responses are indirectly affected by IDO1 expression in the IDO2 ko mice. IDO2 also influenced antibody responses in models of influenza infection and immunization with T cell-independent type II antigens. Taken together, these studies provide evidence for the contrasting roles IDO1 and IDO2 play in immune responses, with IDO1 mediating T cell suppressive effects and IDO2 working directly in B cells as a proinflammatory mediator of B cell responses.
Excessive Neutrophils and Neutrophil Extracellular Traps in COVID-19

Background: Cases of excessive neutrophil counts in the blood in severe coronavirus disease (COVID-19) patients have drawn significant attention. Neutrophil infiltration was also noted on the pathological findings from autopsies. It is urgent to clarify the pathogenesis of neutrophils leading to severe pneumonia in COVID-19. Methods: A retrospective analysis was performed on 55 COVID-19 patients classified as mild (n = 22), moderate (n = 25), and severe (n = 8) according to the Guidelines released by the National Health Commission of China. Trends relating leukocyte counts and lungs examined by chest CT scan were quantified by Bayesian inference. Transcriptional signatures of host immune cells of four COVID19 patients were analyzed by RNA sequencing of lung specimens and BALF. Results: Neutrophilia occurred in 6 of 8 severe patients at 7–19 days after symptom onset, coinciding with lesion progression. Increasing neutrophil counts paralleled lesion CT values (slope: 0.8 and 0.3–1.2), reflecting neutrophilia-induced lung injury in severe patients. Transcriptome analysis revealed that neutrophil activation was correlated with 17 neutrophil extracellular trap (NET)-associated genes in COVID-19 patients, which was related to innate immunity and interacted with T/NK/B cells, as supported by a protein–protein interaction network analysis. Conclusion: Excessive neutrophils and associated NETs could explain the pathogenesis of lung injury in COVID-19 pneumonia.
Diversity and Bioactivity of Endophytes From Angelica sinensis in China

Plant seeds are not merely reproductive organs, they are also carriers of microorganism, particularly, inherent and non-invasive characteristic endophytes in host plant. Therefore, in this study, the endophytic diversity of Angelica seeds was studied and compared with endophytes isolated from healthy leaves, stems, roots, and seeds of A. sinensis using 20 different media. The metabolites of endophytic strains were evaluated with six different methods for their antioxidant activity and the paper disc diffusion method for antimicrobial activities. As a result, 226 endophytes were isolated. Compared with the biodiversity and abundance of uncultured fungi from Angelica seed, the result showed that the most frequent endophytic fungi were Alternaria sp. as seen in artificial media; moreover, compared with artificial media, the pathogenic fungi, including Fusarium sp. and Pseudallescheria sp. , were not found from the Angelica seed, the results suggested it may not be inherent endophytes in plants. In addition, bacteria from seven phyla were identified by high-throughput sequencing, while five phyla of endophytic bacteria were not isolated on artificial media including Proteobacteria, Actinobacteria, Bacteroidetes, Microgenomates, and Saccharibacteria. Furthermore, the sample JH-4 mycelium displayed the best antioxidant activity, and the active constituent may be a flavonoid as determined by total phenol and flavonoid content. Moreover, YH-12-1 mycelium had strong inhibitory activity against the five tested strains and the minimum inhibitory concentration (MIC) against Pseudomonas aeruginosa and Streptococcus pneumoniae was found to be 25 μg/mL. Our results confirm that plant endophytes are rich in biodiversity and contain important resource of many uncultured microorganisms.
Structural Variations Affecting Genes and Transposable Elements of Chromosome 3B in Wheats

Structural variations (SVs) such as copy number and presence–absence variations are polymorphisms that are known to impact genome composition at the species level and are associated with phenotypic variations. In the absence of a reference genome sequence, their study has long been hampered in wheat. The recent production of new wheat genomic resources has led to a paradigm shift, making possible to investigate the extent of SVs among cultivated and wild accessions. We assessed SVs affecting genes and transposable elements (TEs) in a Triticeae diversity panel of 45 accessions from seven tetraploid and hexaploid species using high-coverage shotgun sequencing of sorted chromosome 3B DNA and dedicated bioinformatics approaches. We showed that 23% of the genes are variable within this panel, and we also identified 330 genes absent from the reference accession Chinese Spring. In addition, 60% of the TE-derived reference markers were absent in at least one accession, revealing a high level of intraspecific and interspecific variability affecting the TE space. Chromosome extremities are the regions where we observed most of the variability, confirming previous hypotheses made when comparing wheat with the other grasses. This study provides deeper insights into the genomic variability affecting the complex Triticeae genomes at the intraspecific and interspecific levels and suggests a phylogeny with independent hybridization events leading to different hexaploid species.
Functional shifts of soil microbial communities associated with Alliaria petiolata invasion

Soil feedback is thought to be an important contributor to the success of invasive plants. Despite evidence that invasive plants change soil microbial diversity, the functional roles of microbes impacted by invasion are still unclear. This knowledge is a critical component of our understanding of ecological mechanisms of plant invasion. Mounting evidence suggests Alliaria petiolata can suppress arbuscular mycorrhizal fungi (AMF) to disrupt native plant communities in controlled laboratory and greenhouse experiments, though it is less clear if allelochemicals persist under natural field conditions. Alternatively, invasive plants may accumulate pathogens that are more harmful to competitors as predicted by the Enemy of my Enemy Hypothesis (EEH). We examined changes in functional groups of soil bacteria and fungi associated with ten naturally occurring populations of A. petiolata using amplicon sequences (16S and ITS rRNA). To relate soil microbial communities to impacts on co-occurring plants, we measured root infections and AMF colonization. We found no changes in the diversity and abundance of AMF in plants co-occurring with A. petiolata, suggesting that mycorrhizal suppression in the field may not be as critical to the invasion of A. petiolata as implied by more controlled experiments. Instead, we found changes in pathogen community composition and marginal evidence of increase in root lesions of plants growing with A. petiolata, lending support to the EEH. In addition to these impacts on plant health, changes in ectomycorrhiza, and other nutrient cycling microbes may be important forces underlying the invasion of A. petiolata and its impact on ecosystem function.
Scalable Low-Rank Autoregressive Tensor Learning for Spatiotemporal Traffic Data Imputation

Missing value problem in spatiotemporal traffic data has long been a challenging topic, in particular for large-scale and high-dimensional data with complex missing mechanisms and diverse degrees of missingness. Recent studies based on tensor nuclear norm have demonstrated the superiority of tensor learning in imputation tasks by effectively characterizing the complex correlations/dependencies in spatiotemporal data. However, despite the promising results, these approaches do not scale well to large tensors. In this paper, we focus on addressing the missing data imputation problem for large-scale spatiotemporal traffic data. To achieve both high accuracy and efficiency, we develop a scalable autoregressive tensor learning model---Low-Tubal-Rank Autoregressive Tensor Completion (LATC-Tubal)---based on the existing framework of Low-Rank Autoregressive Tensor Completion (LATC), which is well-suited for spatiotemporal traffic data that characterized by multidimensional structure of location$\times$ time of day $\times$ day. In particular, the proposed LATC-Tubal model involves a scalable tensor nuclear norm minimization scheme by integrating linear unitary transformation. Therefore, the tensor nuclear norm minimization can be solved by singular value thresholding on the transformed matrix of each day while the day-to-day correlation can be effectively preserved by the unitary transform matrix. Before setting up the experiment, we consider two large-scale 5-minute traffic speed data sets collected by the California PeMS system with 11160 sensors. We compare LATC-Tubal with state-of-the-art baseline models, and find that LATC-Tubal can achieve competitively accuracy with a significantly lower computational cost. In addition, the LATC-Tubal will also benefit other tasks in modeling large-scale spatiotemporal traffic data, such as network-level traffic forecasting.
DeepPSC (protein structure camera): computer vision-based protein backbone structure reconstruction from alpha carbon trace as a case study

Deep learning has been increasingly used in protein tertiary structure prediction, a major goal in life science. However, all the algorithms developed so far mostly use protein sequences as input, whereas the vast amount of protein tertiary structure information available in the Protein Data Bank (PDB) database remains largely unused, because of the inherent complexity of 3D data computation. In this study, we propose Protein Structure Camera (PSC) as an approach to convert protein structures into images. As a case study, we developed a deep learning method incorporating PSC (DeepPSC) to reconstruct protein backbone structures from alpha carbon traces. DeepPSC outperformed all the methods currently available for this task. This PSC approach provides a useful tool for protein structure representation, and for the application of deep learning in protein structure prediction and protein engineering.
Phosphatidylserine prevents the generation of a protein-free giant plasma membrane domain in yeast

Membrane phase separation accompanied with micron-scale domains of lipids and proteins occurs in artificial membranes; however, a similar large phase separation has not been reported in the plasma membrane of the living cells. We demonstrate here that a stable micron-scale protein-free region is generated in the plasma membrane of the yeast mutants lacking phosphatidylserine. We named this region the “void zone”. Transmembrane proteins, peripheral membrane proteins, and certain phospholipids are excluded from the void zone. The void zone is rich in ergosterol and requires ergosterol and sphingolipids for its formation. These characteristics of the void zone are similar to the properties of the cholesterol-enriched domain in phase-separated artificial membranes. We propose that phosphatidylserine prevents the formation of the void zone by preferentially interacting with ergosterol. We also found that void zones were frequently in contact with vacuoles, in which a membrane domain was also formed at the contact site. Summary statement Yeast cells lacking phosphatidylserine generate protein-free plasma membrane domains, and vacuoles contact with this domain. This is the first report of micron-scale plasma membrane domains in living cells.
Swarming bacteria undergo localized dynamic phase transition to form stress-induced biofilms

Self-organized multi-cellular behaviors enable cells to adapt and tolerate stressors to a greater degree than isolated cells. However, whether and how cellular communities alter their collective behaviors adaptively upon exposure to stress is largely unclear. Here we address this question using Bacillus subtilis, a model system for bacterial multicellularity. We discover that, upon exposure to a spatial gradient of kanamycin, swarming bacteria activate matrix genes and transit to biofilms. The initial stage of this transition is underpinned by a stress-induced multi-layer formation, emerging from a biophysical mechanism reminiscent to motility-induced phase separation (MIPS). The physical nature of the process suggests that stressors which suppress the expansion of swarms would induce biofilm formation. Indeed, a simple physical barrier also induces a swarm-to-biofilm transition. Based on the gained insight, we propose a promising strategy of antibiotic treatment to effectively inhibit the transition from swarms to biofilms by targeting the localized phase transition.