Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of immune subtypes and their prognosis and molecular implications in colorectal cancer

Immune composition is commonly heterogeneous and varies among colorectal cancer (CRC) patients. A comprehensive immune classification may act as important characteristics to predict CRC prognosis. Thus, we aimed to identify novel immune specific subtypes to guide future therapies. Unsupervised clustering was used to classify CRC samples into different immune subtypes based on abundances of immune cell populations, during which TCGA and GSE17536 datasets were used as training and validation sets, respectively. The associations between the immune subtypes and patient prognosis were investigated. Further, we identified differentially expressed genes (DEGs) between immune high and low subtypes, followed by functional enrichment analyses of DEGs. The expression levels of 74 immunomodulators (IMs) across immune subtypes were analyzed. As a result, we clustered CRC samples into three distinct immune subtypes (immune high, moderate, and low). Patients with immune-high subtype showed the best prognosis, and patients with immune-low subtype had the worst survival in both TCGA and GSE17536 cohorts. A group of 2735 up-regulated DEGs were identified across immune high and low subtypes. The main DEGs were the members of complement components, chemokines, immunoglobulins, and immunosuppressive genes that are involved in immune modulation-related pathways (e.g., cytokine-cytokine receptor interaction) or GO terms (e.g., adaptive immune response and T cell activation). The expression levels of 63 IMs were significantly varied across immune subtypes. In conclusion, this study provides a conceptual framework and molecular characteristics of CRC immune subtypes, which may accurately predict prognosis and offer novel targets for personalized immunotherapy through modifying subtype-specific tumor immune microenvironment.
Small immune effectors coordinate peptidoglycan-derived immunity to regulate intestinal bacteria in shrimp

Small antibacterial effectors, including lysozymes, lectins, and antimicrobial peptides, are key regulators of intestinal immunity. However, whether there is coordination among them during regulation is an interesting, but largely unknown, issue. In the present study, we revealed that small effectors synergistically regulate peptidoglycan-derived intestinal immunity in the kuruma shrimp, Marsupenaeus japonicus. A C-type lysozyme (LysC) was screened as a responsive factor for the intestine-bacteria interaction. LysC functions to restrict intestinal bacteria, mainly by cleaving Photobacterium damselae peptidoglycan to generate muropeptides which are powerful stimulators that induce anti-lipopolysaccharides factor B1 (AlfB1), an effective bactericidal peptide. The muropeptides also induce a C-type lectin (Ctl24), which recognizes peptidoglycan and coats bacteria. By counteracting LysC-mediated muropeptide release and AlfB1’s bactericidal activity, Ctl24 prevents the continuous elimination of intestinal bacteria. Therefore, this study demonstrates a mechanism by which small immune effectors coordinate to achieve intestinal homeostasis, and provides new insights into peptidoglycan-derived intestinal immunity in invertebrates.
Variation in carbon and nitrogen concentrations among peatland categories at the global scale

Peatlands account for 15 to 30% of the world’s soil carbon (C) stock and are important controls over global nitrogen (N) cycles. However, C and N concentrations are known to vary among peatlands contributing to the uncertainty of global C inventories, but there are few global studies that relate peatland classification to peat chemistry. We analyzed 436 peat cores sampled in 24 countries across six continents and measured C, N, and organic matter (OM) content at three depths down to 70 cm. Sites were distinguished between northern (387) and tropical (49) peatlands and assigned to one of six distinct broadly recognized peatland categories that vary primarily along a pH gradient. Peat C and N concentrations, OM content, and C:N ratios differed significantly among peatland categories, but few differences in chemistry with depth were found within each category. Across all peatlands C and N concentrations in the 10–20 cm layer, were 440 ± 85.1 g kg-1 and 13.9 ± 7.4 g kg-1, with an average C:N ratio of 30.1 ± 20.8. Among peatland categories, median C concentrations were highest in bogs, poor fens and tropical swamps (446–532 g kg-1) and lowest in intermediate and extremely rich fens (375–414 g kg-1). The C:OM ratio in peat was similar across most peatland categories, except in deeper samples from ombrotrophic tropical peat swamps that were higher than other peatlands categories. Peat N concentrations and C:N ratios varied approximately two-fold among peatland categories and N concentrations tended to be higher (and C:N lower) in intermediate fens compared with other peatland types. This study reports on a unique data set and demonstrates that differences in peat C and OM concentrations among broadly classified peatland categories are predictable, which can aid future studies that use land cover assessments to refine global peatland C and N stocks.
Throughput screening of Bacillus subtilis strains that abundantly secrete surfactin in vitro identifies effective probiotic candidates

Since the prohibition of antibiotics as animal growth promoters, demand for effective probiotic strains has steadily increased. The goal is to maintain productivity and mitigate environmental concerns in the livestock industry. There are many probiotic animal-diet supplements available, over 2,000 products in the Republic of Korea alone, with little explanation about the desirable properties of each probiotic strain. The purpose of this study was to describe the underlying logic and methods used to select two novel strains of probiotic candidates. To economically screen these candidates, the abundance of surfactin secreted was used as an in vitro marker. We used a modified oil-misting method to screen ~2,000 spore-forming bacteria for novel strains of Bacillus subtilis. Of these, 18 strains were initially selected based on the semiquantitative criterion that they secreted more surfactin than B. subtilis ATCC21322 on Luria-Berani (LB) agar plates. The whole genome sequence was determined for two of the 18 strains to verify their identity. A phylogeny of 1,162 orthologous genes, genome contents, and genome organization confirmed them as novel strains. The surfactin profiles produced by these two strains consisted of at least four isoforms similar to standard surfactin and enhanced cellulase activities up to 50%. Four fractionated individual isoforms of surfactin suppressed inflammation induced by lipopolysaccharides. The half-maximal inhibitory concentration (IC50) was about 20 μM for each isoform. Both selected strains were susceptible to seven important antibiotics. Our results implied that an abundant secretion of surfactin was a useful biomarker in vitro and could be utilized for mining probiotic candidates through high-throughput screening of environmental samples.
Large scale geometry of 4-dimensional closed nonpositivelycurved real analytic manifolds

We study the asymptotic cones of the universal covering spaces of closed 4-dimensional nonpositively curved real analytic manifolds. We show that the existence of nonstandard components in the Tits boundary, discovered by Christoph Hummel and Victor Schroeder, depends only on the quasi-isometry type of the fundamental group.
Prevalence of food addiction among patients undergoing metabolic/bariatric surgery: A systematic review and meta‐analysis

Candidates for metabolic/bariatric surgery show a high prevalence of food addiction (FA). However, few studies have investigated FA prevalence after bariatric surgery, especially using longitudinal studies. This systematic review with a meta‐analysis aimed to determine pre‐ and postoperative prevalence of FA among patients undergoing metabolic/bariatric surgery. It included both cross‐sectional and longitudinal studies that used the Yale Food Addiction Scale (YFAS). The following databases were searched: MEDLINE, ScienceDirect, LILACS, PsycArticles, CENTRAL, greylit.org, and opengrey.eu. Studies that used the YFAS to evaluate FA in pre‐ or postoperative patients were included. A random‐effects meta‐analysis was performed with cross‐sectional studies to calculate the weighted prevalence of FA at the pre‐ and postoperative moments. For longitudinal studies, which measured FA at both time points for the same individuals, absolute prevalence reduction (APR) was calculated. Of the 6626 records, 40 studies were included in the meta‐analysis. The preoperative weighted prevalence of FA was 32% (95% CI: 27–37%; 33 groups), whereas the postoperative prevalence was 15% (95% CI: 12–18%; 14 groups). Seven longitudinal studies showed a weighted APR of 26 p.p. (95% CI: 10–41 p.p.). Observational data suggest a reduction in the prevalence of FA among patients that undergo bariatric surgery. Interventional studies are needed to confirm these findings.
More Efficient Complement Activation by Anti–Aquaporin-4 Compared With Anti–Myelin Oligodendrocyte Glycoprotein Antibodies

Background and Objectives The objective was to study complement-mediated cytotoxicity induced by immunoglobulin G (IgG) anti–aquaporin-4 antibodies (AQP4-IgG) and anti–myelin oligodendrocyte glycoprotein antibodies (MOG-IgG) in human serum samples from patients suffering from the rare demyelinating diseases of the CNS neuromyelitis optica spectrum disorder (NMOSD) and MOG-IgG–associated disease (MOGAD). Methods A cell-based assay with HEK293A cells expressing different MOG isoforms (MOGα1-3β1-3) or AQP4-M23 was used. Cells were incubated with human MOG-IgG or AQP4-IgG–positive serum samples together with active or heat-inactivated human complement, and complement-dependent cytotoxicity (CDC) was measured with a lactate dehydrogenase assay. To further quantify antibody-mediated cell damage, formation of the terminal complement complex (TCC) was analyzed by flow cytometry. In addition, immunocytochemistry of the TCC and complement component 3 (C3) was performed. Results AQP4-IgG–positive serum samples induced higher CDC and TCC levels than MOG-IgG–positive sera. Notably, both showed a correlation between antibody titers and CDC and also between titers and TCC levels. In addition, all 6 MOG isoforms tested (MOGα1-3β1-3) could induce at least some CDC; however, the strongest MOG-IgG–induced CDC levels were found on MOGα1, MOGα3, and MOGβ1. Different MOG-IgG binding patterns regarding recognition of different MOG isoforms were investigated, and it was found that MOG-IgG recognizing all 6 isoforms again induced highest CDC levels on MOGα1 and MOGβ1. Furthermore, surface staining of TCC and C3 revealed positive staining on all 6 MOG isoforms tested, as well as on AQP4-M23. Discussion Both MOG-IgG and AQP4-IgG are able to induce CDC in a titer-dependent manner. However, AQP4-IgG showed markedly higher levels of CDC compared with MOG in vitro on target cells. This further highlights the role of complement in AQP4-IgG–mediated disease and diminishes the importance of complement activation in MOG-IgG–mediated autoimmune disease.
Isocausal spacetimes may have different causal boundaries

We construct an example which shows that two isocausal spacetimes, in the sense introduced recently in García-Parrado and Senovilla (2003 Class. Quantum Grav. 20 625–64), may have c-boundaries which are not equal (more precisely, not equivalent, as no bijection between the completions can preserve all the binary relations induced by causality). This example also suggests that isocausality can be useful for the understanding and computation of the c-boundary.
An implementation of the learning curve cumulative summation test to evaluate a practicum for endometrial cancer ultrasound staging

Purpose The learning curve cumulative summation (LC-CUSUM) test is commonly used as a quantitative assessment of the individual learning process. This study aimed to evaluate the skill acquisition process for performing ultrasound staging of endometrial cancer using the LC-CUSUM test. Methods Sixty-seven ultrasound examinations performed by two operators were evaluated using the LC-CUSUM test according to their rate of success or failure to correctly stage myometrial invasion, serosa involvement, and pelvic and para-aortic lymph node involvement. The reference standard was the pathologic result. After the learning phase, the cumulative summation (CUSUM) test was applied to assess performance maintenance. Results The processes achieved satisfactory performance in the majority of the cases according to the established definitions. Operator 1 reached adequate performance within the 30th procedure for all the locations considered, while operator 2 performed fewer than 30 ultrasound examinations by the audit time. The CUSUM test confirmed that the target quality was preserved after the learning phase. Moreover, the ultrasound staging for endometrial cancer was highly accurate. Conclusion Using the LC-CUSUM test made it possible to monitor the achievement and maintenance of a satisfactory performance quantitatively. The LC-CUSUM test could be a valuable instrument to survey diagnostic pathways in gynecological ultrasonography quantitatively.
Differences in COVID-19 testing and adverse outcomes by race, ethnicity, sex, and health system setting in a large diverse US cohort

Background Racial/ethnic disparities during the first six months of the COVID-19 pandemic led to differences in COVID-19 testing and adverse outcomes. We examine differences in testing and adverse outcomes by race/ethnicity and sex across a geographically diverse and system-based COVID-19 cohort collaboration. Methods Observational study among adults (≥18 years) within six US cohorts from March 1, 2020 to August 31, 2020 using data from electronic health record and patient reporting. Race/ethnicity and sex as risk factors were primary exposures, with health system type (integrated health system, academic health system, or interval cohort) as secondary. Proportions measured SARS-CoV-2 testing and positivity; attributed hospitalization and death related to COVID-19. Relative risk ratios (RR) with 95% confidence intervals quantified associations between exposures and main outcomes. Results 5,958,908 patients were included. Hispanic patients had the highest proportions of SARS-CoV-2 testing (16%) and positivity (18%), while Asian/Pacific Islander patients had the lowest portions tested (11%) and White patients had the lowest positivity rates (5%). Men had a lower likelihood of testing (RR = 0.90 [0.89–0.90]) and a higher positivity risk (RR = 1.16 [1.14–1.18]) compared to women. Black patients were more likely to have COVID-19-related hospitalizations (RR = 1.36 [1.28–1.44]) and death (RR = 1.17 [1.03–1.32]) compared with White patients. Men were more likely to be hospitalized (RR = 1.30 [1.16–1.22]) or die (RR = 1.70 [1.53–1.89]) compared to women. These racial/ethnic and sex differences were reflected in both health system types. Conclusions This study supports evidence of disparities by race/ethnicity and sex during the COVID-19 pandemic that persisted even in healthcare settings with reduced barriers to accessing care. Further research is needed to understand and prevent the drivers that resulted in higher burdens of morbidity among certain Black patients and men.
Time-Aware Datasets are Adaptive Knowledgebases for the New Normal

Recent advances in text classification and knowledge capture in language models have relied on availability of large-scale text datasets. However, language models are trained on static snapshots of knowledge and are limited when that knowledge evolves. This is especially critical for misinformation detection, where new types of misinformation continuously appear, replacing old campaigns. We propose time-aware misinformation datasets to capture time-critical phenomena. In this paper, we first present evidence of evolving misinformation and show that incorporating even simple time-awareness significantly improves classifier accuracy. Second, we present COVID-TAD, a large-scale COVID-19 misinformation da-taset spanning 25 months. It is the first large-scale misinformation dataset that contains multiple snapshots of a datastream and is orders of magnitude bigger than related misinformation datasets. We describe the collection and labeling pro-cess, as well as preliminary experiments.
Pressure–strain interaction. III. Particle-in-cell simulations of magnetic reconnection

How energy is converted into thermal energy in weakly collisional and collisionless plasma processes, such as magnetic reconnection and plasma turbulence, has recently been the subject of intense scrutiny. The pressure–strain interaction has emerged as an important piece, as it describes the rate of conversion between bulk flow and thermal energy density. In two companion studies, we presented an alternate decomposition of the pressure–strain interaction to isolate the effects of converging/diverging flow and flow shear instead of compressible and incompressible flow, and we derived the pressure–strain interaction in magnetic field-aligned coordinates. Here, we use these results to study pressure–strain interaction during two-dimensional anti-parallel magnetic reconnection. We perform particle-in-cell simulations and plot the decompositions in both Cartesian and magnetic field-aligned coordinates. We identify the mechanisms contributing to positive and negative pressure–strain interaction during reconnection. This study provides a roadmap for interpreting numerical and observational data of the pressure–strain interaction, which should be important for studies of reconnection, turbulence, and collisionless shocks.
Evaluating Feature Attribution Methods for Electrocardiogram

The performance of cardiac arrhythmia detection with electrocardiograms(ECGs) has been considerably improved since the introduction of deep learning models. In practice, the high performance alone is not sufficient and a proper explanation is also required. Recently, researchers have started adopting feature attribution methods to address this requirement, but it has been unclear which of the methods are appropriate for ECG. In this work, we identify and customize three evaluation metrics for feature attribution methods based on the characteristics of ECG: localization score, pointing game, and degradation score. Using the three evaluation metrics, we evaluate and analyze eleven widely-used feature attribution methods. We find that some of the feature attribution methods are much more adequate for explaining ECG, where Grad-CAM outperforms the second-best method by a large margin.
Kähler metrics via Lorentzian Geometry in dimension four

Abstract Given a semi-Riemannian 4-manifold (M, g) with two distinguished vector fields satisfying properties determined by their shear, twist and various Lie bracket relations, a family of Kähler metrics gK is constructed, defined on an open set in M, which coincides with M in many typical examples. Under certain conditions g and gK share various properties, such as a Killing vector field or a vector field with a geodesic flow. In some cases the Kähler metrics are complete. The Ricci and scalar curvatures of gK are computed under certain assumptions in terms of data associated to g. Many examples are described, including classical spacetimes in warped products, for instance de Sitter spacetime, as well as gravitational plane waves, metrics of Petrov type D such as Kerr and NUT metrics, and metrics for which gK is an SKR metric. For the latter an inverse ansatz is described, constructing g from the SKR metric.
ManVatar : Fast 3D Head Avatar Reconstruction Using Motion-Aware Neural Voxels

With NeRF widely used for facial reenactment, recent methods can recover photo-realistic 3D head avatar from just a monocular video. Unfortunately, the training process of the NeRF-based methods is quite time-consuming, as MLP used in the NeRF-based methods is inefﬁcient and requires too many iterations to converge. To overcome this problem, we propose ManVatar, a fast 3D head avatar reconstruction method using Motion-Aware Neural Voxels. ManVatar is the ﬁrst to decouple expression motion from canonical appearance for head avatar, and model the expression motion by neural voxels. In particular, the motion-aware neural voxels is generated from the weighted concatenation of multiple 4D tensors. The 4D tensors semantically correspond one-to-one with 3DMM expression bases and share the same weights as 3DMM expression coefﬁ-cients. Beneﬁting from our novel representation, the proposed ManVatar can recover photo-realistic head avatars in just 5 minutes (implemented with pure PyTorch), which is signiﬁcantly faster than the state-of-the-art facial reenact-ment methods.
GraphWOZ: Dialogue Management with Conversational Knowledge Graphs

We present a new approach to dialogue management using conversational knowledge graphs as core representation of the dialogue state. To this end, we introduce a new dataset, GraphWOZ, which comprises Wizard-of-Oz dialogues in which human participants interact with a robot acting as a receptionist. In contrast to most existing work on dialogue management, GraphWOZ relies on a dialogue state explicitly represented as a dynamic knowledge graph instead of a fixed set of slots. This graph is composed of a varying number of entities (such as individuals, places, events, utterances and mentions) and relations between them (such as persons being part of a group or attending an event). The graph is then regularly updated on the basis of new observations and system actions. GraphWOZ is released along with detailed manual annotations related to the user intents, system responses, and reference relations occurring in both user and system turns. Based on GraphWOZ, we present experimental results for two dialogue management tasks, namely conversational entity linking and response ranking. For conversational entity linking, we show how to connect utterance mentions to their corresponding entity in the knowledge graph with a neural model relying on a combination of both string and graph-based features. Response ranking is then performed by summarizing the relevant content of the graph into a text, which is concatenated with the dialogue history and employed as input to score possible responses to a given dialogue state.