Jing Chen, Jing Du, Baoxi Mu, Jie Zhang, Guangbin Shang, Xiaojun Yan
Ulcerative colitis (UC) is sustained by reciprocal interactions among intestinal dysbiosis, altered microbial metabolism, epithelial barrier dysfunction, and mucosal immune activation. This narrative review examines that microbiota–metabolism–barrier–immune network and evaluates how traditional Chinese medicine (TCM) may influence it. Human multi-omics studies indicate that UC-associated dysbiosis is more reproducible at the level of microbial function and metabolite output than at the level of individual taxa. Experimental studies further implicate short-chain fatty acids, bile acids, tryptophan-derived indoles, arginine, and choline-related metabolites in epithelial and immune regulation. Most evidence for TCM-mediated microbiota modulation, however, comes from chemically induced experimental colitis, organoid, or cell systems; human interventional evidence remains limited. We therefore grade mechanistic evidence from association through microbiota dependence, candidate strain/metabolite sufficiency, host-target validation, and integrated causal-chain validation. This distinction avoids treating genus-level relative-abundance changes as proof of microbial benefit or mediation. Emerging clinical trials of indigo naturalis, Curcumin–QingDai, Andrographis paniculata extract, curcumin, and selected multicomponent Chinese herbal therapies provide short-term efficacy signals, but results are preparation- and dose-dependent and do not yet establish microbiota-mediated clinical efficacy. Translation will require chemically standardized products, rigorous safety surveillance, strain- and function-resolved microbiome measurements, explicit experiments separating direct herbal actions from microbiota-dependent effects, and clinical trials incorporating endoscopic, histological, pharmacokinetic, microbial, metabolic, and long-term safety outcomes.
Original ResearchFrontiers in Cellular and Infection Microbiology
Yuyang Zhang, Ziyang Zhang, Dongyang Zhang, Jiulin Tan, Zhaoxin Ma, Qingyang Xiao, Jie Zhang, Qixiu Yu, Zehua Zhang, Yong Tang, Ce Dou, Fei Luo
In bone tuberculosis, Mycobacterium tuberculosis (Mtb) infection triggers inflammatory bone destruction, but the macrophage programs that convert Mtb signals into osteoclastogenesis remain poorly defined. We generated single-cell RNA-seq data from human spinal tuberculosis lesions and integrated them with public H3K27ac ChIP-seq, RNA-seq, Hi-C, and motif data. Key findings were validated in primary macrophages stimulated with Mtb lysate. We identified 64 Mtb-induced super-enhancers, and integrated analysis prioritized RIPK2 as a candidate. Lesion-associated myeloid populations showed enhanced inflammatory and osteoclast-priming signatures, followed a mononuclear phagocyte-to-osteoclast trajectory, and exhibited a linear correlation between RIPK2 expression and osteoclast score. In mice, RIPK2 localized to CTSK-positive bone interfaces. In vitro, Mtb stimulation induced Il1b, Nfkbiz, and Tnfrsf11a expression, IL-1β secretion, and surface RANK upregulation; these responses were suppressed by the RIPK2 inhibitor GSK583. These findings link RIPK2 to both macrophage inflammatory signaling and osteoclastogenesis in bone tuberculosis, suggesting that RIPK2 may be a target for limiting infection-driven bone destruction.
Jie Zhang, Shan Zhang, Yan Cui, Yijie Huang, Yiran Dan, Xiuling Wu, Xing Ye, Hao Zeng, Bitai Wu, Mingyue Yin
To systematically evaluate the effects of different velocity loss (VL) thresholds during resistance training on jump and sprint performance in trained populations and to examine potential moderators. PubMed, Web of Science, Embase, the Cochrane Library, and SPORTDiscus were searched from inception through April 10, 2026. Randomized controlled trials meeting the prespecified PICOS criteria were included. A three-level random-effects meta-analysis was conducted to calculate Hedges’ g and 95% confidence intervals (CIs), accounting for dependence among multiple effect sizes within studies. Risk of bias and certainty of evidence were assessed using RoB 2 and GRADE, respectively. Twelve randomized controlled trials comprising 42 effect sizes were included. Lower VL thresholds produced a small but statistically significant favorable effect on combined jump and sprint performance compared with higher VL thresholds (g=0.29, 95% CI: 0.17 to 0.42, p<0.001), with negligible heterogeneity ( I total 2 = 0.1 % ). Domain-specific analyses showed significant favorable effects for both jump performance (g=0.27, 95% CI: 0.10 to 0.45, p=0.002) and sprint performance (g=0.32, 95% CI: 0.13 to 0.50, p<0.001). Outcome-specific analyses indicated clearer effects for countermovement jump, 10 m sprint, and 30 m sprint, whereas the estimates for squat jump and 20 m sprint were not statistically significant. Significant effects were observed for the 10% versus 30% VL and 10% versus 20% VL comparisons, whereas the 20% versus 40% VL comparison yielded a smaller, non-significant effect. Exploratory moderator analyses did not detect statistically significant effects of population type, training frequency, training mode, intervention duration, or VL-threshold difference; however, these analyses may have been underpowered because of the limited number of included studies. The direction and statistical significance of the pooled effect were robust across alternative pre–post correlation assumptions and model specifications, although heterogeneity estimates and prediction intervals were more sensitive to higher assumed correlations. No evidence of significant small-study effects was detected. Lower VL thresholds may confer small favorable effects on jump and sprint performance in trained populations, with clearer evidence for countermovement jump and selected sprint outcomes. However, the effects were not consistent across all outcomes, and the certainty of evidence ranged from low to moderate. Lower VL may therefore be considered as one potential option for speed–power-oriented resistance training rather than a universally superior prescription. https://www.crd.york.ac.uk/PROSPERO/ , identifier CRD420261396083.
Scientific data sharing is central to open science, yet its development is constrained by fragmented data resources, heterogeneous stakeholder incentives, privacy risks, and limited regulatory capacity. This study develops a bounded-rationality, four-population evolutionary game framework involving data providers, data users, government agencies, and sharing platforms. The model constructs the strategic payoff structure among these actors, derives the corresponding replicator dynamics, and examines the local stability of boundary equilibria through Jacobian eigenvalue analysis. Numerical simulations based on the same dynamic equations are used to illustrate convergence tendencies and parameter sensitivity, rather than to provide independent empirical validation. The results show that cooperative data-sharing behavior can emerge when reputational gains, user benefits, platform incentives, and regulatory instruments are jointly sufficient to offset sharing costs, verification burdens, and privacy-related losses. The analysis further suggests that lower-intensity government involvement can coexist with active participation by providers, users, and platforms, provided that incentive and penalty mechanisms remain in place. Privacy risk is identified as a key boundary condition that may disrupt cooperative sharing when it becomes excessive, while over-intensified subsidies may yield diminishing behavioral returns once strategic probabilities approach stable boundary states. Because the platform payoff and fiscal constraints are deliberately simplified, the findings should be interpreted as model-based policy insights for phased regulation, privacy-risk governance, and incentive design rather than as direct empirical prescriptions.
This paper investigates the applicability of detecting ammonia impurities in plasma electron spectroscopy (PLES) through both numerical and experimental approaches. A self-consistent plasma hybrid fluid-kinetic model is used to accurately describe the formation of characteristic peaks associated with fast electrons in inelastic collision reactions observed in experiments. The model is introduced to calculate the minimum of detectable impurity density at low pressure. Numerical simulations based on the 1D model predict an idealized theoretical detection limit of approximately 5 ppm for ammonia impurities; however, this value should be regarded as a model-derived theoretical lower bound rather than an experimentally confirmed figure. In practice, factors such as signal-to-noise ratio, probe contamination, and measurement noise make it challenging at this stage to achieve direct and stable detection at such low densities. In addition, the effect of ammonia densities on the electron energy distribution function is studied. At low densities, Penning ionization of metastable helium atoms correlates linearly with ammonia density. This process increases the energy transfer rate and significantly enhances characteristic peak intensities. Conversely, at high densities, metastable species undergo rapid depletion. Frequent inelastic collisions between electrons and ammonia molecules dissipate energy into vibrational modes, ultimately driving the electron energy distribution function into a saturated state dominated by collisional quenching. The results can provide significant reference for the detection of trace impurities in gases based on PLES method.
Original ResearchFrontiers in Clinical Diabetes and Healthcare
Achou Su, Jie Zhang, Xizhenzi Fan, Wenhui Song, Mingwei Li, Tianxiao Yu, Jin Zhang
This retrospective cohort study included 700 pregnant women who underwent antenatal check-ups and delivered at the Fourth Hospital of Shijiazhuang from January 2022 to December 2023, aiming to investigate the associations of second°trimester serum magnesium, phosphorus, and calcium with adverse pregnancy outcomes including gestational diabetes mellitus (GDM), anemia, and preterm birth. Mineral indicators were measured at 24–28 weeks of gestation, and baseline data were collected. Mann-Whitney U test was adopted to compare the serum mineral levels among women with different pregnancy outcomes, multivariable logistic regression and ROC curve analysis was utilized to further explore the correlations. After adjusting for potential confounders, magnesium, phosphorus, and calcium levels were correlated with GDM risk, with magnesium and calcium exerting statistically significant protective effects against GDM while high phosphorus serving as a statistically significant GDM risk factor. High calcium was also negatively associated with the risks of anemia and preterm birth whereas high phosphorus was positively linked to preterm birth risk. These findings demonstrate that second-trimester serum magnesium, phosphorus, and calcium levels are associated with GDM, providing clinical evidence for glycemic control interventions and individualized nutritional guidance during pregnancy.
Alison Ziesel, Jennifer Reeves, Anastasia Mallidou, Lorelei Newton, Ryan E. Rhodes, Jie Zhang, Theone Paterson, Hosna Jabbari
Biological aging is a rapidly growing area of research, which entails characterizing the rate of aging independent of an individual’s chronological age. In this scoping review, we analyze the results of biological aging research in 435 papers published in a 12 year window spanning 2011 through June 2023, 309 of which focus on non-methylation-based biomarkers, revealing changing patterns of molecular markers of biological aging use over time as well as the development of novel metrics of biological aging. We further identify consistent and discordant research findings, as well as areas of potential future research focusing on questions of measurement with biomarker-based assessment and other variables relevant to the study of biological age.
Jie Zhang, Xiaoe Wang, Xiaoli Xu., Williamson Gustave, Xiaokai Zhang
Plutella xylostella is a major pest of cruciferous vegetables. The prolonged overuse of chemical insecticides has resulted in increased resistance in P. xylostella populations, highlighting the urgent need for environmentally friendly and effective alternative control strategies. In this study, ethanol extracts from 15 plant species collected from the Qinling Mountains of China were systematically evaluated for their insecticidal, antifeedant, and oviposition-repellent activities against P. xylostella.
Laboratory bioassays were conducted using leaf-dipping and leaf-disc methods. Among the tested plants, ethanol extracts of Atropa belladonna and Blumea riparia var. megacephala exhibited the strongest biological activities. A. belladonna extract achieved corrected mortality, antifeedant, and oviposition-repellent rates of 83.11%, 89.46%, and 78.57%, respectively, whereas B. riparia var. megacephala extract produced corrected mortality, antifeedant, and oviposition-repellent rates of 73.53%, 87.45%, and 82.14%, respectively.
When combined at a volume ratio of 8:2, the two extracts showed enhanced insecticidal activity, with a median lethal concentration (LC50) of 65.762 mg/mL and a co-toxicity coefficient consistent with an additive effect without antagonism. A stable emulsifiable concentrate formulation was subsequently developed through optimization of the solvent and surfactant system. Field trials demonstrated that the 10% botanical formulation achieved a control efficacy of 58.35% at 7 days after application, comparable to that of emamectin benzoate under the tested conditions.
These findings suggest that A. belladonna and B. riparia var. megacephala are promising botanical insecticide resources for further investigation in integrated management strategies against P. xylostella. Additional research is required to establish long-term stability, active constituents, non-target safety, and performance across multiple field environments.
Environmental HealthFrontiers in Environmental Health
Jing He, Rong Wan, Xue Xiao, Jie Zhang, Yi Liang, Zixin Zhu, Yu Cao
The health benefits of bamboo forest recreation on the human body are becoming increasingly recognized. However, limited research has focused on integrating environmental factor monitoring with smart platforms for population health management and assessment. This study monitors environmental parameters, including anion concentration, temperature, relative humidity, wind speed, acoustic environment, and volatile organic compounds in a bamboo forest, while recruiting elderly participants with essential hypertension, type II diabetes, and sleep disorders. A non-invasive wearable device was employed to track the health of the participants, followed by a 21-day precision health management intervention within the bamboo forest. The concentration of negative oxygen ions in this region exceeds 10,000 ions per cm 3, alongside terpenes and other health-promoting volatile substances. A total of 70 participants participated in the platform. Compared to baseline measurements, hypertensive participants experienced significant reductions in systolic and diastolic blood pressure, as well as pulse rate (p < 0.001). Diabetic participants showed significant decreases in fasting and pre-bedtime blood glucose levels (p < 0.001), along with reduced blood glucose fluctuations post-meal. Participants with sleep disorders demonstrated statistically significant improvements in key sleep parameters, including the minimum blood oxygen level at sleep onset, the Oxygen Desaturation Index, wake frequency, percentage of rapid eye movement (REM) sleep, and subjective sleep quality (p < 0.05). The overall sleep quality score also showed significant improvement. This study substantiates the therapeutic potential of bamboo forests in alleviating chronic diseases among the elderly, offering valuable insights for planning “bamboo bath” experiences.
Yawen Huang, Jiangtao Sha, Jie Zhang, Wuyuan Zhang
In the past 20 years, unspecific peroxygenases (UPOs) have emerged as promising biocatalysts for various organic transformations. Particularly, we have witnessed great attention being paid to the screening of new enzymes and expansion of the substrates/products. However, challenges such as enzyme stability, low turnover numbers, and substrate specificity hinder their widespread utilization in practical organic synthesis. This review article provides a concrete and mini-overview of the challenges associated with using UPOs in organic synthesis and discusses strategies for enzyme engineering to overcome these limitations. The article highlights recent advancements in UPO research and presents potential solutions to enhance their catalytic efficiency, stability, substrate specificity, and regioselectivity. Additionally, the review outlines the current methodologies employed for directed evolution and protein engineering of UPOs, along with computational modeling approaches for rational enzyme design. By addressing the challenges and exploring avenues for enzyme engineering, this review aims to shed light on the prospects of UPOs in organic synthesis.
