Miracle-dz/UniFAR-FTUs huggingface dataset:
AAV‐Mediated nuclear localized PGC1α4 delivery in muscle ameliorates sarcopenia and aging‐associated metabolic dysfunctions

Sarcopenia is characterized of muscle mass loss and functional decline in elder individuals which severely affects human physical activity, metabolic homeostasis, and life quality. Physical exercise is considered effective in combating muscle atrophy and sarcopenia, yet it is not feasible to elders with limited mobility. PGC‐1α4, a short isoform of PGC‐1α, is strongly induced in muscle under resistance training, and promotes muscle hypertrophy. In the present study, we showed that the transcriptional levels and nuclear localization of PGC1α4 was reduced during aging, accompanied with muscle dystrophic morphology, and gene programs. We thus designed NLS‐PGC1α4 and ectopically express it in myotubes to enhance PGC1α4 levels and maintain its location in nucleus. Indeed, NLS‐PGC1α4 overexpression increased muscle sizes in myotubes. In addition, by utilizing AAV‐NLS‐PGC1α4 delivery into gastrocnemius muscle, we found that it could improve sarcopenia with grip strength, muscle weights, fiber size and molecular phenotypes, and alleviate age‐associated adiposity, insulin resistance and hepatic steatosis, accompanied with altered gene signatures. Mechanistically, we demonstrated that NLS‐PGC‐1α4 improved insulin signaling and enhanced glucose uptake in skeletal muscle. Besides, via RNA‐seq analysis, we identified myokines IGF1 and METRNL as potential targets of NLS‐PGC‐1α4 that possibly mediate the improvement of muscle and adipose tissue functionality and systemic energy metabolism in aged mice. Moreover, we found a negative correlation between PGC1α4 and age in human skeletal muscle. Together, our results revealed that NLS‐PGC1α4 overexpression improves muscle physiology and systematic energy homeostasis during aging and suggested it as a potent therapeutic strategy against sarcopenia and aging‐associated metabolic diseases.
The Project Siberian High in CMIP5 Models

Abstract The Siberian high (SH) experienced a decline from the 1970s to 1990s and a recovery in recent years. The evolution of the SH under global warming is unclear. In this study, 41 Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models are evaluated in terms of their ability to simulate the temporal evolution of the SH in the 19th and 20th centuries and the spatial pattern of the SH during 1981–2005. The results show that 12 models can capture the temporal evolution of the SH center intensity (SHCI) for 1872–2005. The linear correlation coefficient between the SHCI from the Twentieth Century Reanalysis and the simulated SHCI from the multi-model ensemble (MME) of the 12 models is 0.3 on annual and inter-annual scales (above the 99% confidence level). On decadal and multi-decadal time scales, the MME also captures the pronounced reduction (between 1981–2000 and 1881–1900 period) and the recovery (during 1991–2005) of the SH intensity. Finally, the future evolution of the SH is investigated using the MME of the 12 models under the +4.5 and +8.5 W m-2 Representative Concentration Pathway (RCP) scenarios (RCP4.5 and RCP8.5). It is shown that the SHCI, similar to the SHCI in the 20th century, has no significant long-term trend in the 21st century under global warming (RCP8.5 scenario). At the end of 21st century (2081–2100), the SH shows stronger interannual variability than the SH at the end of 20th century (1981–2000). The increased interannual variability likely favors the increased interannual variability in winter air temperature over midlatitude Eurasia at the end of 21st century.
DNASE1L3 enhances antitumor immunity and suppresses tumor progression in colon cancer

DNASE1L3, an enzyme highly expressed in DCs, is functionally important for regulating autoimmune responses to self-DNA and chromatin. Deficiency of DNASE1L3 leads to development of autoimmune diseases in both humans and mice. However, despite the well-established causal relationship between DNASE1L3 and immunity, little is known about the involvement of DNASE1L3 in regulation of antitumor immunity, the foundation of modern antitumor immunotherapy. In this study, we identify DNASE1L3 as a potentially new regulator of antitumor immunity and a tumor suppressor in colon cancer. In humans, DNASE1L3 is downregulated in tumor-infiltrating DCs, and this downregulation is associated with poor patient prognosis and reduced tumor immune cell infiltration in many cancer types. In mice, Dnase1l3 deficiency in the tumor microenvironment enhances tumor formation and growth in several colon cancer models. Notably, the increased tumor formation and growth in Dnase1l3-deficient mice are associated with impaired antitumor immunity, as evidenced by a substantial reduction of cytotoxic T cells and a unique subset of DCs. Consistently, Dnase1l3-deficient DCs directly modulate cytotoxic T cells in vitro. To our knowledge, our study unveils a previously unknown link between DNASE1L3 and antitumor immunity and further suggests that restoration of DNASE1L3 activity may represent a potential therapeutic approach for anticancer therapy.
Multimodal Batch-Wise Change Detection

We address the problem of detecting distribution changes in a novel batch-wise and multimodal setup. This setup is characterized by a stationary condition where batches are drawn from potentially different modalities among a set of distributions in $\mathbb {R}^{d}$ represented in the training set. Existing change detection (CD) algorithms assume that there is a unique—possibly multipeaked—distribution characterizing stationary conditions, and in batch-wise multimodal context exhibit either low detection power or poor control of false positives. We present MultiModal QuantTree (MMQT), a novel CD algorithm that uses a single histogram to model the batch-wise multimodal stationary conditions. During testing, MMQT automatically identifies which modality has generated the incoming batch and detects changes by means of a modality-specific statistic. We leverage the theoretical properties of QuantTree to: 1) automatically estimate the number of modalities in a training set and 2) derive a principled calibration procedure that guarantees false-positive control. Our experiments show that MMQT achieves high detection power and accurate control over false positives in synthetic and real-world multimodal CD problems. Moreover, we show the potential of MMQT in Stream Learning applications, where it proves effective at detecting concept drifts and the emergence of novel classes by solely monitoring the input distribution.
Aucubin alleviates methotrexate‐induced enteritis in rats by inducing autophagy

One of the toxic side effects of methotrexate (MTX) is enteritis. Aucubin, an iridoid glycoside derived from traditional medicinal herbs, has been proven to have anti‐inflammation, anti‐apoptosis and anti‐oxidation properties. This work explored the effect and mechanism of aucubin in treating MTX‐induced enteritis in a rat model. Two doses of aucubin (5 and 10 mg/kg) were adopted for the assessment of its pharmacological activity. We observed that in rats with MTX‐induced enteritis, the body weight and small intestinal weight decreased. The intestine barrier was injured, as reflected by pathological examinations and an increase in D‐lactate and diamine oxidase concentration in serum. Intestinal inflammation was shown by the observation of macrophages in the intestine and the concentrations of inflammatory cytokines tumour necrosis factor‐α (TNF‐α) and interleukin‐6 (IL‐6) in serum. The NLR family pyrin domain containing 3 (NLRP3) inflammasome was shown to be activated by the enhancement of NLRP3, cleaved‐caspase 1, IL‐18 and IL‐1β. Moreover, autophagy was reflected by transmission electron microscopy as slightly induced, along with changes in autophagy‐related markers microtubule‐associated protein 1 light chain 3 (LC3) and Beclin1. Remarkably, aucubin treatment attenuated the MTX‐induced disease activity index increase, intestinal damage, inflammatory response and NLRP3 inflammasome activation, but provoked autophagy. Rapamycin, an autophagy activator, showed similar therapeutic effects to aucubin on MTX‐induced enteritis. However, 3‐methyladenine, an autophagy inhibitor, reversed the protective effects of aucubin. These findings prompted the hypothesis that aucubin alleviates MTX‐induced enteritis by aggravating autophagy. This study might provide evidence for further investigation on the therapeutic role of aucubin in MTX‐resulted enteritis.
Stability analysis for some numerical schemes of partial differential equation with extra measurements

This paper is devoted to study the stability analysis of some finite difference schemes for an inverse problem with unknowns time-dependent coefficients subject to extra measurements. We prove that the popular forward time centered space scheme is a conditional method. But the backward time centered space and Crank Nicolson methods are suitable schemes because they are unconditional methods. We justify this advantage of the stability analysis versus the some numerical methods with an example. All the results and a numerical example are in two-dimensional setting.
Alcohol use associated alterations in the circulating metabolite profile in the general population and in individuals with major depressive disorder

Our aim was to evaluate whether alcohol use is associated with changes in the circulating metabolite profile similar to those present in persons with depression. If so, these findings could partially explain the link between alcohol use and depression. We applied a targeted liquid chromatography mass spectrometry method to evaluate correlates between concentrations of 86 circulating metabolites and self-reported alcohol use in a cohort of the non-depressed general population (GP) (n = 247) and a cohort of individuals with major depressive disorder (MDD) (n = 99). Alcohol use was associated with alterations in circulating concentrations of metabolites in both cohorts. Our main finding was that self-reported alcohol use was negatively correlated with serum concentrations of hippuric acid in the GP cohort. In the GP cohort, consumption of six or more doses per week was associated with low hippuric acid concentrations, similar to those observed in the MDD cohort, but in these individuals it was regardless of their level of alcohol use. Reduced serum concentrations of hippuric acid suggest that already moderate alcohol use is associated with depression-like changes in the serum levels of metabolites associated with gut microbiota and liver function; this may be one possible molecular level link between alcohol use and depression.
An Expert's Guide to Training Physics-informed Neural Networks

Physics-informed neural networks (PINNs) have been popularized as a deep learning framework that can seamlessly synthesize observational data and partial differential equation (PDE) constraints. Their practical effectiveness however can be hampered by training pathologies, but also oftentimes by poor choices made by users who lack deep learning expertise. In this paper we present a series of best practices that can significantly improve the training efficiency and overall accuracy of PINNs. We also put forth a series of challenging benchmark problems that highlight some of the most prominent difficulties in training PINNs, and present comprehensive and fully reproducible ablation studies that demonstrate how different architecture choices and training strategies affect the test accuracy of the resulting models. We show that the methods and guiding principles put forth in this study lead to state-of-the-art results and provide strong baselines that future studies should use for comparison purposes. To this end, we also release a highly optimized library in JAX that can be used to reproduce all results reported in this paper, enable future research studies, as well as facilitate easy adaptation to new use-case scenarios.
Real-Time Numerical Differentiation of Sampled Data Using Adaptive Input and State Estimation

Real-time numerical differentiation plays a crucial role in many digital control algorithms, such as PID control, which requires numerical differentiation to implement derivative action. This paper addresses the problem of numerical differentiation for real-time implementation with minimal prior information about the signal and noise using adaptive input and state estimation. Adaptive input estimation with adaptive state estimation (AIE/ASE) is based on retrospective cost input estimation, while adaptive state estimation is based on an adaptive Kalman filter in which the input-estimation error covariance and the measurement-noise covariance are updated online. The accuracy of AIE/ASE is compared numerically to several conventional numerical differentiation methods. Finally, AIE/ASE is applied to simulated vehicle position data generated from CarSim.
SCHIZORIZA domain–function analysis identifies requirements for its specific role in cell fate segregation

Abstract Plant development continues postembryonically with a lifelong ability to form new tissues and organs. Asymmetric cell division, coupled with fate segregation, is essential to create cellular diversity during tissue and organ formation. Arabidopsis (Arabidopsis thaliana) plants harboring mutations in the SCHIZORIZA (SCZ) gene display fate segregation defects in their roots, resulting in the presence of an additional layer of endodermis, production of root hairs from subepidermal tissue, and misexpression of several tissue identity markers. Some of these defects are observed in tissues where SCZ is not expressed, indicating that part of the SCZ function is nonautonomous. As a class B HEAT-SHOCK TRANSCRIPTION FACTOR (HSFB), the SCZ protein contains several conserved domains and motifs. However, which domain(s) discriminates SCZ from its family members to obtain a role in development remains unknown. Here, we investigate how each domain contributes to SCZ function in Arabidopsis root patterning by generating altered versions of SCZ by domain swapping and mutation. We show that the SCZ DNA-binding domain is the main factor for its developmental function, and that SCZ likely acts as a nonmotile transcriptional repressor. Our results demonstrate how members of the HSF family can evolve toward functions beyond stress response.
Certifying Stability and Performance of Uncertain Differential-Algebraic Systems: A Dissipativity Framework

This paper presents a novel framework for characterizing dissipativity of uncertain dynamical systems subject to algebraic constraints. The main results provide sufficient conditions for dissipativity when uncertainties are characterized by integral quadratic constraints. For polynomial or linear dynamics, these conditions can be efficiently verified through sum-of-squares or semidefinite programming. The practical impact of this work is illustrated through a case study that examines performance of the IEEE 39-bus power network with uncertainties used to model a set of potential line failures.
Novel insights into molecular patterns of ROS1 fusions in a large Chinese NSCLC cohort: a multicenter study

ROS proto‐oncogene 1, receptor tyrosine kinase (ROS1) rearrangements are a crucial therapeutic target in non‐small cell lung cancer (NSCLC). However, there is limited comprehensive analysis of the molecular patterns of ROS1 fusions. This study aimed to address this gap by analysing 135 ROS1 fusions from 134 Chinese NSCLC patients using next‐generation sequencing (NGS). The fusions were categorized into common and uncommon based on their incidence. Our study revealed, for the first time, a unique distribution preference of breakpoints within ROS1, with common fusions occurring in introns 31–33 and uncommon fusions occurring in introns 34 and 35. Additionally, we identified previously unknown breakpoints within intron 28 of ROS1. Furthermore, we identified a close association between the distribution patterns of fusion partners and breakpoints on ROS1, providing important insights into the molecular landscape of ROS1 fusions. We also confirmed the presence of inconsistent breakpoints in ROS1 fusions between DNA‐based NGS and RNA‐based NGS through rigorous validation methods. These inconsistencies were attributed to alternative splicing resulting in out‐of‐frame or exonic ROS1 fusions. These findings significantly contribute to our understanding of the molecular characteristics of ROS1 fusions, which have implications for panel design and the treatment of NSCLC patients with ROS1 rearrangements.
TIT FOR TAT : FOUNDATIONS OF PREFERENCES FOR RECIPROCITY IN STRATEGIC SETTINGS BY UZI SEGAL AND

This paper assumes that in addition to the conventional (sel sh) preferences over outcomes, players in a strategic environment have preferences over strategies. In the context of two-player games, it provides conditions under which a player's preferences over strategies can be represented as a weighted average of the individual's sel sh payo s and the sel sh payo s of the opponent. The weight one player places on the opponent's sel sh utility depends on the opponent's behavior. In this way, the framework is rich enough to describe the behavior of individuals who repay kindness with kindness and meanness with meanness. The paper assumes that each player has an ordering over his opponent's strategies that describes the niceness of these strategies. It introduces a condition that insures that the weight on opponent's utility increases if and only if the opponent chooses a nicer strategy. We are grateful to Miguel Costa-Gomes, David Levine, Joe Ostroy, Ariel Rubinstein, Dan Vincent, and Bill Zame for their comments. We thank SSHRCC and NSF for nancial support. Department of Economics, University of Western Ontario, London N6A 5C2, Canada. E-mail: usegal@julian.uwo. ca Department of Economics, University of California, San Diego, La Jolla, CA 92093, U.S.A. E-mail: jsobel@weber.ucsd. edu
Clinical Impact of JAK2V617F Allele Burden in Philadelphia-Negative Myeloproliferative Neoplasms

Objective: The impact of JAK2V617F allele burden on clinical course in Philadelphia-negative (Ph-negative) myeloproliferative neoplasms (MPNs) is not clear. We analyzed the clinical impact of JAK2V617F allele burden in a relatively large series of patients with Ph-negative MPNs and long-term follow-up. Materials and Methods: A total of 228 patients with Ph-negative MPNs, including 118 with essential thrombocythemia (ET), 84 with primary myelofibrosis (PMF), and 26 with polycythemia vera (PV), were analyzed. The JAK2 MutaScreen assay was used to quantify JAK2V617F allele burden in genomic DNA. Results: In PV cases, high JAK2V617F allele burden was associated with a trend towards inferior overall survival. In ET, high JAK2V617F allele burden was associated with lower hemoglobin and hematocrit levels, higher lactate dehydrogenase (LDH) levels, larger spleen size, and increased bleeding and mortality rates. In PMF, high JAK2V617F allele burden was associated with higher leukocyte counts and larger spleen size. In the entire cohort, high allele burden was associated with higher leukocyte and lower platelet counts, higher LDH levels, larger spleen size, higher percentage of bleeding events, higher death rate, and inferior overall survival. Conclusion: Our results suggest that high JAK2V617F allele burdens are associated with more severe disease in PV and ET. In PMF, high JAK2V617F allele burdens were associated with more pronounced myeloproliferative phenotypes. In Ph-negative MPNs, high allele burdens were associated with more aggressive phenotypes. Our data with a long follow-up period support the possibility of JAK2V617F allele burden being used as a marker for predicting clinical phenotype in cases of Ph-negative MPNs.
What is the source of the PTA GW signal?

The most conservative interpretation of the nHz stochastic gravitational wave background (SGWB) discovered by NANOGrav and other Pulsar Timing Array (PTA) Collaborations is astrophysical, namely that it originates from supermassive black hole (SMBH) binaries. However, alternative cosmological models have been proposed, including cosmic strings, phase transitions, domain walls, primordial fluctuations and"audible"axions. We perform a multi-model analysis (MMA) to compare how well these different hypotheses fit the NANOGrav data, both in isolation and in combination with SMBH binaries, and address the questions: Which interpretations fit the data best, and which are disfavoured? We also discuss experimental signatures that can help discriminate between different sources of the PTA GW signal, including fluctuations in the signal strength between frequency bins, individual sources and how the PTA signal extends to higher frequencies.
Knowledge-Enhanced Multi-Label Few-Shot Product Attribute-Value Extraction

Existing attribute-value extraction (AVE) models require large quantities of labeled data for training. However, new products with new attribute-value pairs enter the market every day in real-world e-Commerce. Thus, we formulate AVE in multi-label few-shot learning (FSL), aiming to extract unseen attribute value pairs based on a small number of training examples. We propose a Knowledge-Enhanced Attentive Framework (KEAF) based on prototypical networks, leveraging the generated label description and category information to learn more discriminative prototypes. Besides, KEAF integrates with hybrid attention to reduce noise and capture more informative semantics for each class by calculating the label-relevant and query-related weights. To achieve multi-label inference, KEAF further learns a dynamic threshold by integrating the semantic information from both the support set and the query set. Extensive experiments with ablation studies conducted on two datasets demonstrate that our proposed model significantly outperforms other SOTA models for information extraction in few-shot learning.
A protocol for systematic review and network meta-analysis

Background: Vascular complications at the puncture site is a common complication after femoral artery puncture. It will not only affect the postoperative effect and patient comfort, but also may endanger the life of the patient. The effective compression hemostasis methods at the puncture site can improve the comfort of the patient, shorten the hospital stay, and reduce the burden on the medical staff. The purpose of this research is to evaluate the effectiveness and safety of different compression methods after femoral artery puncture. Methods:We will include all relevant randomized controlled trials by searching major Chinese and English databases and clinical trial registration platforms. Use Cochrane Collaboration’s Risk of bias tool for bias risk analysis. Use the Grades of Recommendation, Assessment, Development, and Evaluation to assess the quality of evidence. Data analysis will be performed using Stata (V.15.0) and WinBUGS (V.1.4.3). Results: Five hundred ninety-seven records were obtained by searching the database but no records were obtained by other means. After removing duplicate records, 377 records remain. We excluded 103 records through abstract and title, leaving 274 fulltext articles. Conclusion: This study will compare the application effects of different compression methods after femoral artery puncture. We hope that this study will help guide clinical decision-making and provide evidence for the management of patients after femoral artery puncture. Protocol Registration number: INPLASY2020120094. Abbreviations: NMA = network meta-analysis, RCTs = randomized controlled trials.