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Mesenchymal stem cells (MSCs) are multipotent stem cells characterized by self-renewal, production of clonal cell populations, and multilineage differentiation. They exist in nearly all tissues and play a significant role in tissue repair and regeneration. Additionally, MSCs possess wide immunoregulatory properties via interaction with immune cells in both innate and adaptive immune systems, leading to immunosuppression of various effector functions. Numerous bioactive molecules secreted by MSCs, particularly cytokines, growth factors, and chemokines, exert autocrine/paracrine effects that modulate the physiological processes of MSCs. These invaluable virtues of MSCs provide new insight into potential treatments for tissue damage and inflammation. In particular, their extensive immunosuppressive properties are being explored for promising therapeutic application in immune disorders. Recently, clinical trials for MSC-mediated therapies have rapidly developed for immune-related diseases following reports from preclinical studies declaring their therapeutic safety and efficacy. Though immunotherapy of MSCs remains controversial, these clinical trials pave the way for their widespread therapeutic application in immune-based diseases. In this review, we will summarize and update the latest research findings and clinical trials on MSC-based immunomodulation.

Based on a quantitative analysis of a novel dataset comprising 10,093 publicly available judgments of adjudicated child custody disputes from the China Judgments Online website, this article identifies potential gender bias in Chinese family courts under certain conditions. Key findings include: 1. Mothers are generally more proactive in seeking custody and are awarded custody in the majority of cases compared to fathers. 2. Specifically, mothers have a significant advantage in cases involving daughters, while their advantage in cases involving sons is less pronounced. 3. In rural courts, the results are notably different: mothers are disadvantaged overall, fathers are particularly assertive in seeking custody of sons compared to daughters, and mothers are less likely than fathers to be awarded custody of sons. Building on existing literature, this study highlights potential judicial biases rooted in societal gender norms prevalent in rural areas. This raises questions about whether courts have achieved substantive gender equality and whether the legal principle of ’the best interests of the child’ is consistently upheld in every court decision. This study enhances the understanding of gender bias within China’s family court system by providing valuable insights for those interested in addressing gender inequality. It not only highlights specific challenges women face in custody cases but also calls for broader societal and policy changes to support women and combat gender discrimination in all its forms.

Accurate quantification of volatile fatty acid (VFA) concentrations in rumen fluid are essential for research on rumen metabolism. The study comprehensively investigated the pros and cons of High-performance liquid chromatography (HPLC) and 1 H Nuclear magnetic resonance ( 1 H-NMR) analysis methods for rumen VFAs quantification. We also investigated the performance of several commonly used data pre-treatments for the two sets of data using correlation analysis, principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). The molar proportion and reliability analysis demonstrated that the two approaches produce highly consistent VFA concentrations. In the pre-processing of NMR spectra, line broadening and shim correction may reduce estimated concentrations of metabolites. We observed differences in results using multiplet of different protons from one compound and identified “handle signals” that provided the most consistent concentrations. Different data pre-treatment strategies tested with both HPLC and NMR significantly affected the results of downstream data analysis. “Normalized by sum” pre-treatment can eliminate a large number of positive correlations between NMR-based VFA. A “Combine” strategy should be the first choice when calculating the correlation between metabolites or between samples. The PCA and PLS-DA suggest that except for “Normalize by sum”, pre-treatments should be used with caution.

To improve the accuracy of short-term wind power prediction, a short-term wind power prediction model based on the LSTM model and multiple error correction is proposed. First, an affine wind power correction model based on assimilative migration is established to reduce the errors caused by false positives from the initial data. Then, a self-moving window LSTM prediction model based on the improved particle swarm optimization algorithm was established. By improving the particle swarm optimization algorithm, the optimal hidden neuron number and the optimal learning rate of the LSTM model were calculated to enhance the model’s accuracy. Definitively, the idea of error feedback prediction is used to correct the initial prediction error, and the prediction error is fed back to the LSTM model to reduce the error caused by the calculation of the LSTM model. By starting from the initial data error, model accuracy error, and model prediction error, multiple error correction of wind power is realized to improve the model accuracy. The simulation results show that the method improves the model’s prediction accuracy by using assimilative transfer and error feedback, contributing to the economic operation and sustainable development of the power system. Unlike traditional improvement ideas, the proposed improvement ideas do not involve the inherent characteristics of the original prediction methods. This method does not need to introduce other auxiliary methods and has good universality.

Sepsis is a critical global health concern linked to high mortality rates, often due to acute lung injury (ALI)/acute respiratory distress syndrome (ARDS). While the gut-lung axis involvement in ALI is recognized, direct migration of gut immune cells to the lung remains unclear. Our study reveals sepsis-induced migration of γδ T17 cells from the small intestine to the lung, triggering an IL-17A-dominated inflammatory response in mice. Wnt signaling activation in alveolar macrophages drives CCL1 upregulation, facilitating γδ T17 cell migration. CD44 + Ly6C – IL-7R high CD8 low cells are the primary migratory subtype exacerbating ALI. Esketamine attenuates ALI by inhibiting pulmonary Wnt/β-catenin signaling-mediated migration. This work underscores the pivotal role of direct gut-to-lung memory γδ T17 cell migration in septic ALI and clarifies the importance of localized IL-17A elevation in the lung. Sepsis can result in acute lung injury which may involve cross interaction via the gut-lung axis. Here the authors show γδ T17 cell migration from the gut to the lung in a murine model of sepsis and link IL-17A-mediated lung inflammation regulation by Wnt/β-catenin signaling in alveolar macrophages via CCL1.

PurposeHerbivore grazing and nitrogen (N) input may alter the multiple ecosystem functions (i.e., multifunctionality, hereafter) associated with carbon (C), N, and phosphorus (P) cycling. Most studies on variations in plant diversity, soil biotic or abiotic factors, and linkages to ecosystem functions have focused on grazing or N enrichment alone. Few studies have combined these two factors to explore the role of plant resource stoichiometry (C:N:P ratios) in ecosystem multifunctionality (EMF) control. Here, we evaluated the direct and indirect effects of stocking rate (0, 2.7, 5.3, and 8.7 sheep ha− 1) and N addition rate (0, 5, 10, and 20 g N m− 2 yr− 1) on a range of ecosystem functions and EMF via changing plant diversity, soil pH and plant resource stoichiometry in a typical steppe on the Loess Plateau.ResultsWe found that increasing stocking rate and interaction between grazing and N addition significantly decreased EMF, while increasing N addition rate significantly promoted EMF. Grazing decreased soil NH4+-N, soil NO3−-N, aboveground biomass, and plant C, N, and P pools, but increased soil total N and P at 8.7 and 5.3 sheep ha− 1, respectively. N addition increased soil NH4+-N, NO3−-N, and total P. Plant aboveground biomass, and plant C, N, and P pools increased at the lower N addition rate (≤ 5 g N m− 2 yr− 1) under grazing. The structural equation models indicated that (1) EMF was driven by the direct effects of grazing and the indirect effects of grazing on plant resource stoichiometry and soil pH; (2) EMF increased with increasing N addition rates, but such positive response of EMF to increasing N addition rates was alleviated at high levels of plant resource stoichiometry and diversity; and (3) the indirect effects of plant diversity induced by grazing and N addition had moderate effects on EMF via the variations of plant resource stoichiometry.ConclusionsThis study demonstrated grazing and N addition had contrasting effects on ecosystem multifunctionality in a typical steppe, and highlighted the capacity of plant diversity in balancing plant elements that serve as a key mechanism in the maintenance of EMF in response to intensive grazing and N enrichment.

Background The elevation of TyG is considered an important factor in promoting the progression of non-alcoholic fatty liver disease (NAFLD), but its impact on the degree of liver steatosis remains unclear. This study aims to explore the relationship between TyG and TyG-related indices, such as triglyceride glucose-body mass index (TyG-BMI), with the degree of liver fat accumulation. Methods From January 2021 to March 2022, 1171 participants underwent health check-ups, and all underwent FibroScan transient elastography. The analysis focused on identifying the factors that contribute to the onset of NAFLD and the degree of hepatic steatosis. Results The predictive value of TyG-BMI (OR = 1.039, 95% CI 1.031–1.046) in triggering NAFLD development was greater than that of TyG alone. The areas under the curve for TyG-BMI and TyG were calculated at 0.808 and 0.720, respectively. TyG-BMI (OR = 1.034, P  < 0.001) was identified as a main independent factor affecting hepatic steatosis severity. With each incremental increase in TyG-BMI, the likelihood of experiencing an increase in the extent of hepatic steatosis was 1.034 times higher than that of the preceding unit. Conclusions The TyG-BMI showed higher accuracy in predicting NAFLD than did the TyG, and was more closely linked to the severity of hepatic steatosis. Therefore, it can be included as a parameter in health management centers and should be widely used to screen and evaluate patients with NAFLD.

Theaflavin is a kind of multi-pharmacological and health beneficial black tea factor. The aim of this study is to investigate the mechanisms by which theaflavin interacts with glycosylated and non-glycosylated serum albumins and compares their binding properties. Fluorescence and ultraviolet spectra indicated that theaflavin interacted with native and glycated human serum albumin through a static quenching mechanism and had a higher degree of quenching of human serum albumin. The thermodynamic parameters revealed that the combinations of theaflavin with native and glycated human serum albumin were a spontaneous endothermic reaction, and the hydrophobic force was a major driving force in the interaction process. Zeta potential, particle size, synchronous fluorescence, three-dimensional fluorescence spectroscopy and circular dichroism further clarified the effect of theaflavin on the conformation of human serum albumin structure were more pronounced. In addition, site competition experiments and molecular docking technique confirmed that the binding sites of theaflavin on both native and glycated human serum albumin were bound at site II. This study had investigated the effects of glycation on the binding of HSA with polyphenols and the potential nutriology significance of these effects.

As an important transportation hub connecting the two sides of the Yellow River, the Yellow River Grand Bridge is of great significance for strengthening regional exchanges and promoting the high-quality development of the Yellow River Basin. However, due to the complex terrain, changeable climate, high sediment concentration, long construction duration, complicated process, strong dynamic, and many factors affecting construction. It often brings many problems, including low quality, waste of resources, and environmental pollution, which makes it difficult to achieve the balance of multiple objectives at the same time. Therefore, it is very important to carry out multi-objective optimization research on the construction of the Yellow River Grand Bridge. This paper takes the Yellow River Grand Bridge on a highway as the research object and combines the concept of “green construction” and the national policy of “carbon neutrality and carbon peaking” to construct six major construction projects, including construction time, cost, quality, environment, resources, and carbon emission. Then, according to the multi-attribute utility theory, the objectives of different attributes are normalized, and the multi-objective equilibrium optimization model of construction time-cost-quality-environment-resource-carbon emission of the Yellow River Grand Bridge is obtained; finally, in order to avoid the shortcomings of a single algorithm, the particle swarm optimization algorithm and the simulated annealing algorithm are combined to obtain the simulated annealing particle swarm optimization (SA-PSO) algorithm. The multi-objective equilibrium optimization model of the construction of the Yellow River Grand Bridge is solved. The optimization result is 108 days earlier than the construction period specified in the contract, which is 9.612 million yuan less than the maximum cost, 6.3% higher than the minimum quality level, 11.1% lower than the maximum environmental pollution level, 4.8% higher than the minimum resource-saving level, and 3.36 million tons lower than the maximum carbon emission level. It fully illustrates the effectiveness of the SA-PSO algorithm for solving multi-objective problems.

Utilizing hydrogen as a viable substitute for fossil fuels requires the exploration of hydrogen storage materials with high capacity, high quality, and effective reversibility at room temperature. In this study, the stability and capacity for hydrogen storage in the Sc-modified C3N4 nanotube are thoroughly examined through the application of density functional theory (DFT). Our finding indicates that a strong coupling between the Sc-3d orbitals and N-2p orbitals stabilizes the Sc-modified C3N4 nanotube at a high temperature (500 K), and the high migration barrier (5.10 eV) between adjacent Sc atoms prevents the creation of metal clusters. Particularly, it has been found that each Sc-modified C3N4 nanotube is capable of adsorbing up to nine H2 molecules, and the gravimetric hydrogen storage density is calculated to be 7.29 wt%. It reveals an average adsorption energy of −0.20 eV, with an estimated average desorption temperature of 258 K. This shows that a Sc-modified C3N4 nanotube can store hydrogen at low temperatures and harness it at room temperature, which will reduce energy consumption and protect the system from high desorption temperatures. Moreover, charge donation and reverse transfer from the Sc-3d orbital to the H-1s orbital suggest the presence of the Kubas effect between the Sc-modified C3N4 nanotube and H2 molecules. We draw the conclusion that a Sc-modified C3N4 nanotube exhibits exceptional potential as a stable and efficient hydrogen storage substrate.