Miracle-dz/UniFAR-FTUs huggingface dataset:
SARS-CoV-2 Mac1 is required for IFN antagonism and efficient virus replication in mice

Several coronavirus (CoV) encoded proteins are being evaluated as targets for antiviral therapies for COVID-19. Included in this set of proteins is the conserved macrodomain, or Mac1, an ADP-ribosylhydrolase and ADP-ribose binding protein. Utilizing point mutant recombinant viruses, Mac1 was shown to be critical for both murine hepatitis virus (MHV) and severe acute respiratory syndrome (SARS)-CoV virulence. However, as a potential drug target, it is imperative to understand how a complete Mac1 deletion impacts the replication and pathogenesis of different CoVs. To this end, we created recombinant bacterial artificial chromosomes (BACs) containing complete Mac1 deletions (ΔMac1) in MHV, MERS-CoV, and SARS-CoV-2. While we were unable to recover infectious virus from MHV or MERS-CoV ΔMac1 BACs, SARS-CoV-2 ΔMac1 was readily recovered from BAC transfection, indicating a stark difference in the requirement for Mac1 between different CoVs. Furthermore, SARS-CoV-2 ΔMac1 replicated at or near wild-type levels in multiple cell lines susceptible to infection. However, in a mouse model of severe infection, ΔMac1 was quickly cleared causing minimal pathology without any morbidity. ΔMac1 SARS-CoV-2 induced increased levels of interferon (IFN) and interferon-stimulated gene (ISG) expression in cell culture and mice, indicating that Mac1 blocks IFN responses which may contribute to its attenuation. ΔMac1 infection also led to a stark reduction in inflammatory monocytes and neutrophils. These results demonstrate that Mac1 only minimally impacts SARS-CoV-2 replication, unlike MHV and MERS-CoV, but is required for SARS-CoV-2 pathogenesis and is a unique antiviral drug target. SIGNIFICANCE All CoVs, including SARS-CoV-2, encode for a conserved macrodomain (Mac1) that counters host ADP-ribosylation. Prior studies with SARS-CoV-1 and MHV found that Mac1 blocks IFN production and promotes CoV pathogenesis, which has prompted the development of SARS-CoV-2 Mac1 inhibitors. However, development of these compounds into antivirals requires that we understand how SARS-CoV-2 lacking Mac1 replicates and causes disease in vitro and in vivo. Here we found that SARS-CoV-2 containing a complete Mac1 deletion replicates normally in cell culture but induces an elevated IFN response, has reduced viral loads in vivo, and does not cause significant disease in mice. These results will provide a roadmap for testing Mac1 inhibitors, help identify Mac1 functions, and open additional avenues for coronavirus therapies.
Emergence of belief-like representations through reinforcement learning

To behave adaptively, animals must learn to predict future reward, or value. To do this, animals are thought to learn reward predictions using reinforcement learning. However, in contrast to classical models, animals must learn to estimate value using only incomplete state information. Previous work suggests that animals estimate value in partially observable tasks by first forming “beliefs”—optimal Bayesian estimates of the hidden states in the task. Although this is one way to solve the problem of partial observability, it is not the only way, nor is it the most computationally scalable solution in complex, real-world environments. Here we show that a recurrent neural network (RNN) can learn to estimate value directly from observations, generating reward prediction errors that resemble those observed experimentally, without any explicit objective of estimating beliefs. We integrate statistical, functional, and dynamical systems perspectives on beliefs to show that the RNN’s learned representation encodes belief information, but only when the RNN’s capacity is sufficiently large. These results illustrate how animals can estimate value in tasks without explicitly estimating beliefs, yielding a representation useful for systems with limited capacity.
Latent evolution of biofilm formation depends on life-history and genetic background

Adaptation to one environment can often generate phenotypic and genotypic changes which impact the future ability of an organism to thrive in other environmental conditions. In the context of host-microbe interactions, biofilm formation can increase survival rates in vivo upon exposure to stresses, like the host’s immune system or antibiotic therapy. However, how the generic process of adaptation impacts the ability to form biofilm and how it may change through time has seldomly been studied. To do so, we used a previous evolution experiment with three strains of the Klebsiella pneumoniae species complex, in which we specifically did not select for biofilm formation. We observed that changes in the ability to form biofilm happened very fast at first and afterwards reverted to ancestral levels in many populations. Biofilm changes were associated to changes in population yield and surface polysaccharide production. Genotypically, mutations in the tip adhesin of type III fimbriae ( mrkD ) or the fim switch of type I fimbriae were shaped by nutrient availability during evolution, and their impact on biofilm formation was dependent on capsule production. Analyses of natural isolates revealed similar mutations in mrkD , suggesting that such mutations also play an important role in adaptation outside the laboratory. Our work reveals that the latent evolution of biofilm formation, and its temporal dynamics, depend on nutrient availability, the genetic background and other intertwined phenotypic and genotypic changes. Ultimately, it suggests that small differences in the environment can alter an organism’s fate in more complex niches like the host.
Human Segmentation Algorithm in Infrared Images Based on K-means Clustering Centers Analysis

Due to the differences of various infrared cameras parameters and the surroundings influence,the robustness of the threshold auto-selection algorithm in infrared images segmentation has not been well resolved. Based on the mechanism of infrared imaging,we presented a new solving scheme and put it into practice. Firstly,the image histogram was clustered by K-means clustering method,and then the distribution characteristic of the cluster centers was analyzed in detail and the threshold for image segmentation was determined. This algorithm doesn’t need to equalize the image before segmentation and assume the distribution of the background. Experimental result shows good robustness.
Logic-Based Modeling of Inflammatory Macrophage Crosstalk with Glomerular Endothelial Cells in Diabetic Kidney Disease

Diabetic kidney disease is a complication in 1 out of 3 patients with diabetes. Aberrant glucose metabolism in diabetes leads to an immune response causing inflammation and to structural and functional damage in the glomerular cells of the kidney. Complex cellular signaling lies at the core of metabolic and functional derangement. Unfortunately, the mechanism underlying the role of inflammation in glomerular endothelial cell dysfunction during diabetic kidney disease is not fully understood. Computational models in systems biology allow the integration of experimental evidence and cellular signaling networks to understand mechanisms involved in disease progression. We built a logic-based ordinary differential equations model to study macrophage-dependent inflammation in glomerular endothelial cells during diabetic kidney disease progression. We studied the crosstalk between macrophages and glomerular endothelial cells in the kidney using a protein signaling network stimulated with glucose and lipopolysaccharide. The network and model were built using the open-source software package Netflux. This modeling approach overcomes the complexity of studying network models and the need for extensive mechanistic details. The model simulations were fitted and validated against available biochemical data from in vitro experiments. The model identified mechanisms responsible for dysregulated signaling in macrophages and glomerular endothelial cells during diabetic kidney disease. In addition, we investigated the influence of signaling interactions and species that on glomerular endothelial cell morphology through selective knockdown and downregulation. We found that partial knockdown of VEGF receptor 1, PLC-γ, adherens junction proteins, and calcium partially recovered the endothelial cell fenestration size. Our model findings contribute to understanding signaling and molecular perturbations that affect the glomerular endothelial cells in the early stage of diabetic kidney disease. NEW & NOTEWORTHY We describe the findings of our novel analysis of signaling crosstalk between macrophages and glomerular endothelial cells in the early stage of diabetic kidney disease. Through a logic-based modeling approach, we identified key signaling molecules and interactions that regulate glucose-mediated inflammation in the glomerular endothelial cells and that damage endothelial fenestrations in the diabetic kidney. Our research revealed that the interaction among vascular endothelial growth factor A, nitric oxide, and junction proteins significantly affects the size of endothelial fenestrations.
Objects sharpen visual scene representations: evidence from MEG decoding

Real-world scenes consist of objects, defined by local information, and scene background, defined by global information. While objects and scenes are processed in separate pathways in visual cortex, their processing interacts. Specifically, previous studies have shown that scene context makes blurry objects look sharper, an effect that can be observed as a sharpening of object representations in visual cortex from around 300 ms after stimulus onset. Here, we use MEG to show that objects can also sharpen scene representations, with the same temporal profile. Photographs of indoor (closed) and outdoor (open) scenes were blurred such that they were difficult to categorize on their own but easily disambiguated by the inclusion of an object. Classifiers were trained to distinguish MEG response patterns to intact indoor and outdoor scenes, presented in an independent run, and tested on degraded scenes in the main experiment. Results revealed better decoding of scenes with objects than scenes alone and objects alone from 300 ms after stimulus onset. This effect was strongest over left posterior sensors. These findings show that the influence of objects on scene representations occurs at similar latencies as the influence of scenes on object representations, in line with a common predictive processing mechanism.
Investigations of film cooling and its nonuniform distribution for the conjugate heat transfer passage with a compound inclined angle jet

ABSTRACT Film cooling effectiveness and its distribution characteristics on the gas turbine blade surface were investigated numerically. Seven rectangular ribs were located on the internal wall, and a film cooling hole had a compound inclined angle. The case with a compound angle of 45° was designed to improve the lateral film cooling effectiveness on the downstream surface. The secondary flow jet from the internal channel was affected by the flow velocity ratios, and an investigation of the external film cooling was considered for various values of thermal conductivity and heat conduction. Two different plate materials were used to analyze the effect of plate thermal conductivity. The results showed that the compound angle of 45° causes an asymmetric distribution of the film cooling effectiveness. However, the bending effect can be of advantage to increase the film cooling effectiveness in the horizontal direction, so a better distribution of the lateral film cooling effectiveness can be achieved. The area-average cooling effectiveness is improved by an increase of the flow rate at the internal passage inlet. A new definition of Dn is introduced to evaluate the nonuniformity of the distribution of the local film cooling effectiveness quantitatively and conveniently. The downstream cooling effectiveness distribution becomes more uniform using a compound angle of 45°. For the high thermal conductivity case, higher blade-wall heat flux is transferred by heat conduction, which drops the area-average wall temperature along the secondary flow direction.
Time-of-day-dependent variation of the hepatic transcriptome and metabolome is disrupted in non-alcoholic fatty liver disease patients

Liver homeostasis is ensured in part by time-of-day-dependent processes, many of them being paced by the molecular circadian clock. Liver functions are compromised in non-alcoholic fatty liver (NAFL) and non-alcoholic steatohepatitis (NASH), and clock disruption increases susceptibility to non-alcoholic fatty liver disease (NAFLD) progression in rodent models. We therefore investigated whether time-of-day-dependent transcriptome and metabolome are significantly altered in human NAFL and NASH livers. Liver biopsies, collected within an 8 hour- window from a carefully phenotyped cohort of 290 patients and histologically diagnosed to be either normal, NAFL or NASH hepatic tissues, were analyzed by RNA sequencing and unbiased metabolomic approaches. Time-of-day-dependent gene expression patterns and metabolomes were identified and compared between histologically normal, NAFL and NASH livers. We provide here a first-of-its-kind report of a daytime-resolved human liver transcriptome-metabolome and associated alterations in NAFLD. Transcriptomic analysis showed a robustness of core molecular clock components in NAFL and NASH livers. It also revealed stage-specific, time-of-day- dependent alterations of hundreds of transcripts involved in cell-to-cell communication, intra- cellular signaling and metabolism. Similarly, rhythmic amino acid and lipid metabolomes were affected in pathological livers. Both TNFa and PPARγ signaling are predicted as important contributors to altered rhythmicity. NAFLD progression to NASH perturbs time-of-day-dependent processes in human livers, while core molecular clock component differential expression is maintained.
Dietary ketone ester attenuates the accretion of adiposity and liver steatosis in mice fed a high-fat, high-sugar diet

Objective: The ketone diester, R,S-1,3-butanediol diacetoacetate (BD-AcAc2), attenuates the accretion of adiposity and reduces hepatic steatosis in high-fat diet-induced obese mice when carbohydrate energy is removed from the diet to accommodate energy from the ester. Reducing carbohydrate energy is a potential confounder due to the well-known effects of carbohydrate restriction on components of energy balance and metabolism. Therefore, the current investigation was designed to determine whether the addition of BD-AcAc2 to a high-fat, high-sugar diet (with no reduction in carbohydrate energy) would attenuate the accretion of adiposity and markers of hepatic steatosis and inflammation. Methods: Sixteen 11-week-old male C57BL/6J mice were randomized to one of two groups for 9 weeks (n = 8 per group): 1) Control (CON, HFHS diet) or 2) Ketone ester (KE, HFHS diet + BD-AcAc2, 25% by kcals). Results: Body weight increased by 56% in CON (27.8 ± 2.5 to 43.4 ± 3.7 g, p < 0.001) and by 13% in KE (28.0 ± 0.8 to 31.7 ± 3.1 g, p = 0.001). Non-alcoholic fatty liver disease activity scores (NAS) for hepatic steatosis, inflammation, and ballooning were lower in the KE group compared to CON (p < 0.001 for all). Markers of hepatic inflammation [Tnfα (p = 0.036); Mcp1 (p < 0.001)], macrophage content [(Cd68 (p = 0.012)], and collagen deposition and hepatic stellate cell activation [(αSma (p = 0.004); Col1A1 (p < 0.001)] were significantly lower in the KE group compared to CON. Conclusion: These findings extend those of our previous work and show that BD-AcAc2 attenuates the accretion of adiposity and reduces markers of liver steatosis, inflammation, ballooning, and fibrosis in lean mice placed on a HFHS diet where carbohydrate energy was not removed to accommodate energy from addition of the diester.
Biomarkers of post-match recovery in semi-professional and professional football (soccer)

High-level football (soccer) players face intense physical demands that result in acute and residual fatigue, impairing their physical performance in subsequent matches. Further, top-class players are frequently exposed to match-congested periods where sufficient recovery times are not achievable. To evaluate training and recovery strategies, the monitoring of players’ recovery profiles is crucial. Along with performance and neuro-mechanical impairments, match-induced fatigue causes metabolic disturbances denoted by changes in chemical analytes that can be quantified in different body fluids such as blood, saliva, and urine, thus acting as biomarkers. The monitoring of these molecules might supplement performance, neuromuscular and cognitive measurements to guide coaches and trainers during the recovery period. The present narrative review aims to comprehensively review the scientific literature on biomarkers of post-match recovery in semi-professional and professional football players as well as provide an outlook on the role that metabolomic studies might play in this field of research. Overall, no single gold-standard biomarker of match-induced fatigue exists, and a range of metabolites are available to assess different aspects of post-match recovery. The use of biomarker panels might be suitable to simultaneously monitoring these broad physiological processes, yet further research on fluctuations of different analytes throughout post-match recovery is warranted. Although important efforts have been made to address the high interindividual heterogeneity of available markers, limitations inherent to these markers might compromise the information they provide to guide recovery protocols. Further research on metabolomics might benefit from evaluating the long-term recovery period from a high-level football match to shed light upon new biomarkers of post-match recovery.
Safety and efficacy of substance-based medical devices: Design of an in vitro barrier effect test

This study aims to develop an in vitro barrier effect test over biomimetic membrane, which is useful to establish the film forming ability of a substance-based medical device (SB-MD). The method contemplates a multiparametric approach including: i) the measurement of the transmembrane passage of a molecular-like marker over a lipid-impregnated biomimetic membrane (simulating the skin and gastro-intestinal and buccal tissues) by using a static diffusion cell apparatus (Franz cell); and ii) the evaluation of the integrity of the membrane (colorimetric test). In the first step, a series of lipid-impregnated biomimetic membranes (simulating gastro-intestinal, buccal, and skin tissues) were implemented and their permeability performance validated using model drugs (caffeine and acyclovir) by referring to literature data. As a result, the apparent permeability (Papp) of caffeine over the biomimetic gastro-intestinal membrane (Papp = 30.5E-6 cm/s) was roughly comparable to the literature values obtained with Caco-2 cell line membrane (Papp = 30.8E-6 cm/s) and with the Franz cell method (Papp = 36.2E-6 cm/s). Acyclovir was shown to be a poorly permeable substance both in the literature and experimental data. Following this step, the permeability study was extended to both biomimetic buccal and skin (STRAT-M®) membranes: for caffeine, biomimetic gastro-intestinal membrane was the most permeable (Papp = 30.5E-6 cm/s), followed by the buccal (Papp = 18.2E-6 cm/s) then the skin (Papp = 0.5E-6 cm/s) biomimetic membranes. In a second part of the work, the barrier effect test was developed following a similar permeability-like approach. The protocol was designed with the idea of assessing the capacity of a certain product to prevent the passage of caffeine across the biomimetic membrane with respect to a negative and positive control. The untreated membrane was the negative control, while membrane covered with a Vaseline film was the positive. As a last step, the developed barrier effect protocol was applied to an experimental gel-like SB-MD under development for the treatment of aphthae (Aphthae gel, an invented trade name), herein used as a case study. Regarding the results, Aphthae gel reduced the caffeine passage by 60.3%, thus highlighting its effectiveness to form a protective film. Overall, these results provide important knowledge and may pave the way for the use—including for industrial applications—of these simple but effective biomimetic membranes for carrying out high throughput screening necessary to design safe and effective SB-MDs before proceeding further with clinical trials, as requested by the regulations.
The accuracy of international and national fetal growth charts in detecting small-for-gestational-age infants using the Lambda-Mu-Sigma method

Objective To construct a national fetal growth chart using retrospective data and compared its diagnostic accuracy in predicting SGA at birth with existing international growth charts. Method This is a retrospective study where datasets from May 2011 to Apr 2020 were extracted to construct the fetal growth chart using the Lambda-Mu-Sigma method. SGA is defined as birth weight <10th centile. The local growth chart's diagnostic accuracy in detecting SGA at birth was evaluated using datasets from May 2020 to Apr 2021 and was compared with the WHO, Hadlock, and INTERGROWTH-21st charts. Balanced accuracy, sensitivity, and specificity were reported. Results A total of 68,897 scans were collected and five biometric growth charts were constructed. Our national growth chart achieved an accuracy of 69% and a sensitivity of 42% in identifying SGA at birth. The WHO chart showed similar diagnostic performance as our national growth chart, followed by the Hadlock (67% accuracy and 38% sensitivity) and INTERGROWTH-21st (57% accuracy and 19% sensitivity). The specificities for all charts were 95–96%. All growth charts showed higher accuracy in the third trimester, with an improvement of 8–16%, as compared to that in the second trimester. Conclusion Using the Hadlock and INTERGROWTH-21st chart in the Malaysian population may results in misdiagnose of SGA. Our population local chart has slightly higher accuracy in predicting preterm SGA in the second trimester which can enable earlier intervention for babies who are detected as SGA. All growth charts' diagnostic accuracies were poor in the second trimester, suggesting the need of improvising alternative techniques for early detection of SGA to improve fetus outcomes.