Miracle-dz/UniFAR-FTUs huggingface dataset:
Intercellular crosstalk regulating ARRB2/RARRES1 is involved in transition from fibrosis to cancer

Progressive fibrogenesis in chronic liver injury is often associated with cancer development. Beta-arrestin-2 (ARRB2) is a regulator of the profibrotic Angiotensin II type 1 receptor (AGTR1). The role of ARRB2 in liver fibrosis and in the transition from fibrosis to cancer is not fully understood and was investigated in this study. This study demonstrates that upregulation of the retinoic acid receptor responder 1 (RARRES1) in HSC mediated by ARRB2 leads to fibrosis. This process is driven by exosomal ARRB2 transfer to HSC, major fibrosis contributors, from injured hepatocytes, which highly express ARRB2. By contrast, downregulation of RARRES1 in hepatocytes induces malignant transformation and hepatocellular carcinoma (HCC) development. Consequently, Arrb2-deficient mice show higher number and size of liver tumors than wild-type mice in a hepatocellular carcinoma model with fibrosis. The identified relationship between ARRB2 and RARRES1 was observed in at least two species, including human cells and tissues in fibrosis and HCC and has a predictive value for survival in cancer patients. This study describes the discovery of a novel molecular pathway mediating the transition from fibrosis to cancer offering potential diagnostics and therapeutics.
Pro-apoptotic caspase deficiency reveals a cell-extrinsic mechanism of NK cell regulation

Regulated cell death is essential for the maintenance of cellular and tissue homeostasis. In the hematopoietic system, genetic defects in apoptotic cell death generally produce the accumulation of immune cells, inflammation and autoimmunity. In contrast, we found that genetic deletion of caspases of the mitochondrial apoptosis pathway reduces natural killer (NK) cell numbers and makes NK cells functionally defective in vivo and in vitro. Caspase deficiency results in constitutive activation of a type I interferon (IFN) response, due to leakage of mitochondrial DNA and activation of the cGAS/STING pathway. The NK cell defect in caspase-deficient mice is independent of the type I IFN response, but the phenotype is partially rescued by cGAS or STING deficiency. Finally, caspase deficiency alters NK cells in a cell-extrinsic manner. Type I IFNs and NK cells are two essential effectors of antiviral immunity, and our results demonstrate that they are both regulated in a caspase-dependent manner. Beyond caspase-deficient animals, our observations may have implications in infections that trigger mitochondrial stress and caspase-dependent cell death.
A flow-based latent state generative model of neural population responses to natural images

We present a joint deep neural system identification model for two major sources of neural variability: stimulus-driven and stimulus-conditioned fluctuations. To this end, we combine (1) state-of-the-art deep networks for stimulus-driven activity and (2) a flexible, normalizing flow-based generative model to capture the stimulus-conditioned variability including noise correlations. This allows us to train the model end-to-end without the need for sophisticated probabilistic approximations associated with many latent state models for stimulus-conditioned fluctuations. We train the model on the responses of thousands of neurons from multiple areas of the mouse visual cortex to natural images. We show that our model outperforms previous state-of-the-art models in predicting the distribution of neural population responses to novel stimuli, including shared stimulus-conditioned variability. Furthermore, it successfully learns known latent factors of the population responses that are related to behavioral variables such as pupil dilation, and other factors that vary systematically with brain area or retinotopic location. Overall, our model accurately accounts for two critical sources of neural variability while avoiding several complexities associated with many existing latent state models. It thus provides a useful tool for uncovering the interplay between different factors that contribute to variability in neural activity.
Population differentiation of polygenic score predictions under stabilizing selection

Given the many small-effect loci uncovered by genome-wide association studies (GWAS), polygenic scores have become central to the drive for genomic medicine and have spread into various areas including evolutionary studies of adaptation. While promising, these scores are fraught with issues of portability across populations, due to mis-estimated effect sizes and missing causal loci across populations unrepresented in large-scale GWAS. The poor portability of polygenic scores at first seems at odds with the view that much of common genetic variation is shared among populations. Here we investigate one potential cause of this discrepancy, stabilizing selection on complex traits. Somewhat counter-intuitively, while stabilizing selection to the same optimum phenotype leads to lower phenotypic differentiation among populations, it increases genetic differentiation at GWAS loci because it accelerates the turnover of polymorphisms underlying trait variation within populations. We develop theory to show how stabilizing selection impacts the utility of polygenic scores when applied to unrepresented populations. Specifically, we quantify their reduced prediction accuracy and find they can substantially overstate average genetic differences of phenotypes among populations. Our work emphasizes stabilizing selection to the same optimum as a useful null evolutionary model to draw connections between patterns of allele frequency and polygenic score differentiation.
Phenotypic and genomic adaptations to the extremely high elevation in plateau zokor (Myospalax baileyi)

The evolutionary outcomes of high elevation adaptation have been extensively described. However, whether widely distributed high elevation endemic animals adopt uniform mechanisms during adaptation to different elevational environments remains unknown, especially with respect to extreme high elevation environments. To explore this, we analysed the phenotypic and genomic data of seven populations of plateau zokor (Myospalax baileyi) along elevations ranging from 2,700 to 4,300 m. Based on whole‐genome sequencing data and demographic reconstruction of the evolutionary history, we show that two populations of plateau zokor living at elevations exceeding 3,700 m diverged from other populations nearly 10,000 years ago. Further, phenotypic comparisons reveal stress‐dependent adaptation, as two populations living at elevations exceeding 3,700 m have elevated ratios of heart mass to body mass relative to other populations, and the highest population (4,300 m) displays alterations in erythrocytes. Correspondingly, genomic analysis of selective sweeps indicates that positive selection might contribute to the observed phenotypic alterations in these two extremely high elevation populations, with the adaptive cardiovascular phenotypes of both populations possibly evolving under the functional constrains of their common ancestral population. Taken together, phenotypic and genomic evidence demonstrates that heterogeneous stressors impact adaptations to extreme elevations and reveals stress‐dependent and genetically constrained adaptation to hypoxia, collectively providing new insights into the high elevation adaptation.
Modified expression of TaCYP78A5 enhances grain weight with yield potential by accumulating auxin in wheat (Triticum aestivum L.)

Summary Increasing grain yield has always been the primary goal of crop breeding. KLUH/CYP78A5 has been shown to affect seed size in several plant species, but the relevant molecular mechanism is still unclear and there are no reports of this gene contributing to yield. Here, we demonstrate that modified expression of TaCYP78A5 can enhance wheat grain weight and grain yield per plant by accumulating auxin. TaCYP78A5 is highly expressed in maternal tissues, including ovary and seed coat during wheat development. The constitutive overexpression of TaCYP78A5 leads to significantly increased seed size and weight but not grain yield per plant due to the strengthening of apical dominance. However, localized overexpression of TaCYP78A5 in maternal integument enhances grain weight and grain yield per plant by 4.3%–18.8% and 9.6%–14.7%, respectively, in field trials. Transcriptome and hormone metabolome analyses reveal that TaCYP78A5 participates in auxin synthesis pathway and promotes auxin accumulation and cell wall remodelling in ovary. Phenotype investigation and cytological observation show that localized overexpression of TaCYP78A5 in ovary results in delayed flowering and prolonged proliferation of maternal integument cells, which promote grain enlargement. Moreover, naturally occurring variations in the promoter of TaCYP78A5‐2A contribute to thousand‐grain weight (TGW) and grain yield per plant of wheat;TaCYP78A5‐2A haplotype Ap‐HapII with higher activity is favourable for improving grain weight and grain yield per plant and has been positively selected in wheat breeding. Then, a functional marker of TaCYP78A5 haplotype Ap‐HapII is developed for marker‐assisted selection in wheat grain and yield improvement.
How Neuroimaging Can Aid the Interpretation of Art

Cognitive neuroscience of art continues to be criticized for failing to provide interesting results about art itself. In particular, results of brain imaging experiments have not yet been utilized in interpretation of particular works of art. Here we revisit a recent study in which we explored the neuronal and behavioral response to painted portraits with a direct versus an averted gaze. We then demonstrate how fMRI results can be related to the art historical interpretation of a specific painting. The evidentiary status of neuroimaging data is not different from any other extra-pictorial facts that art historians uncover in their research and relate to their account of the significance of a work of art. They are not explanatory in a strong sense, yet they provide supportive evidence for the art writer’s inference about the intended meaning of a given work. We thus argue that brain imaging can assume an important role in the interpretation of particular art works.
P2RY12-Inhibitors Reduce Cancer-Associated Thrombosis and Tumor Growth in Pancreatic Cancers

Platelet function can be modified by cancer cells to support tumor growth, causing alterations in the delicate hemostatic equilibrium. Cancer-cell and platelet interactions are one of the main pillars of Trousseau’s syndrome: a paraneoplastic syndrome with recurring and migrating episodes of thrombophlebitis. Altogether, this leads to a four-fold risk of thrombotic events in cancer patients, which in turn, portend a poor prognosis. We previously demonstrated that anti-P2RY12 drugs inhibit cancer-associated-thrombosis and formation of tumor metastasis in pancreatic cancer models. Here, we aimed to (1) compare the effects of aspirin and clopidogrel on pancreatic cancer prevention, (2) characterize the effects of clopidogrel (platelet P2RY12 inhibitor) on cancer-associated thrombosis and cancer growth in vivo, (3) determine the effect of P2RY12 across different digestive-tract cancers in vitro, and (4) analyze the expression pattern of P2RY12 in two different cancer types affecting the digestive system. Clopidogrel treatment resulted in better survival rates with smaller primary tumors and less metastasis than aspirin treatment. Clopidogrel was also more effective than aspirin at dissolving spontaneous endogenous thrombi in our orthotopic advanced cancer mouse model. P2RY12 expression gives pancreatic adenocarcinomas proliferative advantages. In conclusion, we propose the hypothesis that clopidogrel should be further studied to target and prevent Trousseau’s syndrome; as well as diminish cancer growth and spread. However, more studies are required to determine the implicated pathways and effects of these drugs on cancer development.
Discrimination Between Invasive and In Situ Melanomas Using Clinical Close-Up Images and a De Novo Convolutional Neural Network

Background: Melanomas are often easy to recognize clinically but determining whether a melanoma is in situ (MIS) or invasive is often more challenging even with the aid of dermoscopy. Recently, convolutional neural networks (CNNs) have made significant and rapid advances within dermatology image analysis. The aims of this investigation were to create a de novo CNN for differentiating between MIS and invasive melanomas based on clinical close-up images and to compare its performance on a test set to seven dermatologists. Methods: A retrospective study including clinical images of MIS and invasive melanomas obtained from our department during a five-year time period (2016–2020) was conducted. Overall, 1,551 images [819 MIS (52.8%) and 732 invasive melanomas (47.2%)] were available. The images were randomized into three groups: training set (n = 1,051), validation set (n = 200), and test set (n = 300). A de novo CNN model with seven convolutional layers and a single dense layer was developed. Results: The area under the curve was 0.72 for the CNN (95% CI 0.66–0.78) and 0.81 for dermatologists (95% CI 0.76–0.86) (P < 0.001). The CNN correctly classified 208 out of 300 lesions (69.3%) whereas the corresponding number for dermatologists was 216 (72.0%). When comparing the CNN performance to each individual reader, three dermatologists significantly outperformed the CNN. Conclusions: For this classification problem, the CNN was outperformed by the dermatologist. However, since the algorithm was only trained and validated on 1,251 images, future refinement and development could make it useful for dermatologists in a real-world setting.
An Improvement of Robot Stiffness-Adaptive Skill Primitive Generalization Using the Surface Electromyography in Human–Robot Collaboration

Learning from Demonstration in robotics has proved its efficiency in robot skill learning. The generalization goals of most skill expression models in real scenarios are specified by humans or associated with other perceptual data. Our proposed framework using the Probabilistic Movement Primitives (ProMPs) modeling to resolve the shortcomings of the previous research works; the coupling between stiffness and motion is inherently established in a single model. Such a framework can request a small amount of incomplete observation data to infer the entire skill primitive. It can be used as an intuitive generalization command sending tool to achieve collaboration between humans and robots with human-like stiffness modulation strategies on either side. Experiments (human–robot hand-over, object matching, pick-and-place) were conducted to prove the effectiveness of the work. Myo armband and Leap motion camera are used as surface electromyography (sEMG) signal and motion capture sensors respective in the experiments. Also, the experiments show that the proposed framework strengthened the ability to distinguish actions with similar movements under observation noise by introducing the sEMG signal into the ProMP model. The usage of the mixture model brings possibilities in achieving automation of multiple collaborative tasks.
Using Artificial Intelligence for Automatic Segmentation of CT Lung Images in Acute Respiratory Distress Syndrome

Knowledge of gas volume, tissue mass and recruitability measured by the quantitative CT scan analysis (CT-qa) is important when setting the mechanical ventilation in acute respiratory distress syndrome (ARDS). Yet, the manual segmentation of the lung requires a considerable workload. Our goal was to provide an automatic, clinically applicable and reliable lung segmentation procedure. Therefore, a convolutional neural network (CNN) was used to train an artificial intelligence (AI) algorithm on 15 healthy subjects (1,302 slices), 100 ARDS patients (12,279 slices), and 20 COVID-19 (1,817 slices). Eighty percent of this populations was used for training, 20% for testing. The AI and manual segmentation at slice level were compared by intersection over union (IoU). The CT-qa variables were compared by regression and Bland Altman analysis. The AI-segmentation of a single patient required 5–10 s vs. 1–2 h of the manual. At slice level, the algorithm showed on the test set an IOU across all CT slices of 91.3 ± 10.0, 85.2 ± 13.9, and 84.7 ± 14.0%, and across all lung volumes of 96.3 ± 0.6, 88.9 ± 3.1, and 86.3 ± 6.5% for normal lungs, ARDS and COVID-19, respectively, with a U-shape in the performance: better in the lung middle region, worse at the apex and base. At patient level, on the test set, the total lung volume measured by AI and manual segmentation had a R2 of 0.99 and a bias −9.8 ml [CI: +56.0/−75.7 ml]. The recruitability measured with manual and AI-segmentation, as change in non-aerated tissue fraction had a bias of +0.3% [CI: +6.2/−5.5%] and −0.5% [CI: +2.3/−3.3%] expressed as change in well-aerated tissue fraction. The AI-powered lung segmentation provided fast and clinically reliable results. It is able to segment the lungs of seriously ill ARDS patients fully automatically.
Silicon Alleviates the Disease Severity of Sclerotinia Stem Rot in Rapeseed

Sclerotinia stem rot, caused by Sclerotinia sclerotiorum, is a devastating disease in rapeseed. The objective of this study was to investigate the role and the mechanism of silicon (Si) in alleviating the disease severity of S. sclerotiorum in rapeseed. In the absorption assays, the rapeseed that absorbed 10 mM of K2SiO3 exhibited an 86% decrease in lesion size on infected leaves as compared with controls. In the spray assay, the lesion length on rapeseed stems was reduced by 30.5–32.9% with the use of 100 mM of a foliar Si fertilizer as compared with controls. In the pot assay, the lesion length on rapeseed stems was reduced by 34.9–38.3% when using the Si fertilizer as basal fertilizer. In the field assay, both the disease incidence and disease index of sclerotinia stem rot were significantly reduced with the usage of a solid Si fertilizer, Si foliar fertilizer, and the application of both, without negative affection on the main agronomic traits and seed quality of rapeseed. The transcriptome sequencing, quantitative reverse transcription PCR (qRT-PCR), and biochemical assays between K2SO4- and K2SiO3- treated rapeseed leaves revealed that Si promoted the biosynthesis of defense-related substances and enhanced the antioxidation and detoxification abilities of rapeseed after infection. Thus, this study concluded that Si can alleviate the disease severity of S. sclerotiorum in rapeseeds, partially due to the induced defense responses.
Heterogeneity of Treatment Effects Among Patients With Type 2 Diabetes and Elevated Body Mass Index in a Study Comparing Group Medical Visits Focused on Weight Management and Medication Intensification

Supplemental Digital Content is available in the text. Background: Illuminating heterogeneity of treatment effect (HTE) within trials is important for identifying target populations for implementation. Objective: The aim of this study was to examine HTE in a trial of group medical visits (GMVs) for patients with type 2 diabetes and elevated body mass index. Research Design and Measures: Participants (n=263) were randomized to GMV-based medication management plus low carbohydrate diet-focused weight management (WM/GMV; n=127) or GMV-based medication management alone (GMV; n=136) for diabetes control. We used QUalitative INteraction Trees, a tree-based clustering method, to identify subgroups with greater improvement in hemoglobin A1c (HbA1c) and weight from either WM/GMV or GMV. Subgroup predictors included 32 baseline demographic, clinical, and psychosocial factors. Internal validation was conducted to estimate bias in the range of mean outcome differences between arms. Results: QUalitative INteraction Trees analyses indicated that for patients who had not previously attempted weight loss, WM/GMV resulted in better glycemic control than GMV (mean difference in HbA1c improvement=1.48%). For patients who had previously attempted weight loss and had lower cholesterol and blood urea nitrogen, GMV was better than WM/GMV (mean difference in HbA1c improvement=1.51%). No treatment-subgroup effects were identified for weight. Internal validation resulted in moderate corrections in mean HbA1c differences between arms; however, differences remained in the clinically significant range. Conclusion: This work represents a novel step toward targeting care approaches for patients to maximize benefit based on individual patient characteristics.
Bacterial flavoprotein monooxygenase YxeK salvages toxic S‐(2‐succino)‐adducts via oxygenolytic C–S bond cleavage

Thiol‐containing nucleophiles such as cysteine react spontaneously with the citric acid cycle intermediate fumarate to form S‐(2‐succino)‐adducts. In Bacillus subtilis, a salvaging pathway encoded by the yxe operon has recently been identified for the detoxification and exploitation of these compounds as sulfur sources. This route involves acetylation of S‐(2‐succino)cysteine to N‐acetyl‐2‐succinocysteine, which is presumably converted to oxaloacetate and N‐acetylcysteine, before a final deacetylation step affords cysteine. The critical oxidative cleavage of the C–S bond of N‐acetyl‐S‐(2‐succino)cysteine was proposed to depend on the predicted flavoprotein monooxygenase YxeK. Here, we characterize YxeK and verify its role in S‐(2‐succino)‐adduct detoxification and sulfur metabolism. Detailed biochemical and mechanistic investigation of YxeK including 18O‐isotope‐labeling experiments, homology modeling, substrate specificity tests, site‐directed mutagenesis, and (pre‐)steady‐state kinetics provides insight into the enzyme’s mechanism of action, which may involve a noncanonical flavin‐N5‐peroxide species for C–S bond oxygenolysis.
Safety and Preliminary Efficacy of a Novel Host-Modulatory Therapy for Reducing Gingival Inflammation

Background Periodontal disease is among the sixth most common inflammatory diseases worldwide with high risk to promote complications from other inflammatory diseases including diabetes, cardiovascular disease and Alzheimer’s Disease. Failure of active resolution of inflammation pathways is implicated in pathogenesis of periodontal diseases, including gingivitis. Lipoxin A4 (LXA4), a member of the specialized pro-resolving lipid mediators (SPMs) that drive resolution of inflammation via GPC-receptor mediated pathways, offered therapeutic advantages in preclinical models of periodontitis. Methods We conducted a randomized, placebo-controlled, parallel-group Phase 1 clinical trial to determine the safety and preliminary efficacy of an LXA4 analog in patients with gingival inflammation. One hundred twenty-seven (127) individuals were randomized to daily use of an oral rinse containing a LXA4 mimetic, methyl ester-benzo-lipoxin A4 (BLXA4), placebo rinse or a no-rinse control group for 28 days. Treatment emergent adverse events (TEAEs) were assessed for safety, the primary outcome. Secondary outcomes included the change in the level of gingival inflammation and periodontal pocket depth (PD). Serum SPMs were monitored using targeted lipid mediator lipidomics to assess potential systemic impact of BLXA4. Results The frequency of TEAEs was similar in BLXA4 and placebo-treated groups with no study-related SAEs. Once-daily rinsing with BLXA4 for 28-days resulted in a greater decrease in gingival inflammation compared to placebo rinse and no-rinse control groups (mean change: 0.26 GI unit vs 0.21 and 0.17, respectively). PD reduction was also greater with BLXA4 oral rinse compared to placebo and no-rinse groups (mean reduction: 1.23 mm vs. 0.71 mm and 0.46 mm, respectively). Topical application of BLXA4 increased serum levels of SPMs. Conclusion Treatment with BLXA4 reduces local inflammation, and increases abundance of pro-resolution molecules systemically, which may dampen inflammation that can mediate progression and course of inflammatory diseases beyond periodontitis. Clinical Trial Registration ClinicalTrials.gov, identifier (NCT02342691).