Yuxian People's Hospital

CRISPR technology has profoundly transformed both genome editing and the next generation of nucleic acid detection. In this study, we characterized a Cas12a ortholog, Gs12-9 (EsoCas12a), which recognizes a broad PAM motif (NYYN, where Y denotes C or T) and maintains robust cis- and trans-cleavage activity across a wide temperature range (16–60 ℃), outperforming established Cas12a variants such as LbCas12a. Leveraging Gs12-9, we established a rapid, highly sensitive, and temperature-tolerant nucleic acid detection platform that enables precise genotyping without stringent thermal control. By integrating recombinase polymerase amplification (RPA) with CRISPR/Gs12-9-mediated detection, we accurately discriminated myostatin (MSTN) knockout pigs from wild-type individuals, achieving a detection limit of 40 copies per reaction with 100% accuracy. While the MSTN knockout (KO) pig served as a proof-of-concept model in this work, the versatility of Gs12-9 supports its broader application in CRISPR-based diagnostics, including pathogen screening and genetic variant detection.

Fibrosis is a pathological process characterized by excessive extracellular matrix deposition, leading to tissue stiffening and organ dysfunction, posing a significant threat to human health. In recent years, histone methylation, a key epigenetic modification, has been increasingly recognized for its crucial regulatory role in the initiation and progression of fibrosis. By modulating chromatin structure and gene expression, histone methylation influences the activation of fibrosis-related cells, inflammatory responses, and cellular fate transitions. This review systematically summarizes the molecular mechanisms of histone methylation in fibrosis across multiple organs, including the kidney, liver, heart, and lungs. It emphasizes the functions and regulatory networks of methyltransferases and demethylases, integrating the latest experimental and clinical findings. Furthermore, potential therapeutic strategies targeting histone methylation are discussed, highlighting their promise for precise anti-fibrotic interventions. By consolidating advances in multi-organ fibrosis research, this article aims to provide a theoretical foundation and practical guidance for the future development of targeted fibrosis therapies.

We read with great interest the article by Sitaula et al. entitled “Efficacy of Platelet-Rich Plasma Therapy in Melasma Using Microinjections and Microneedling Techniques” [1]. The authors are to be commended for conducting a rigorous randomized split-face study that addresses a critical clinical question: the optimal delivery modality for platelet-rich plasma (PRP) in melasma management. Their findings, demonstrating a statistically superior efficacy of microneedling over microinjection (70.21% vs. 36.6% improvement in modified Melasma Area and Severity Index [MASI] score, p < 0.001), provide valuable, high-level evidence that will inform therapeutic decision-making. The split-face design effectively mitigates inter-individual variability, enhancing the validity of the conclusions [2]. While the study robustly establishes the superiority of microneedling, we wish to explore potential mechanistic underpinnings and future research directions to build upon this foundation. First, the authors attribute the enhanced efficacy of microneedling to improved drug penetration via microchannels. This physical explanation is plausible, but we hypothesize that the mechanism may involve active biological synergy. Microneedling induces a controlled wound-healing response, triggering the release of cytokines and growth factors that modulate the local microenvironment [3]. Concurrently, PRP delivers a concentrated bolus of growth factors (e.g., TGF-β, PDGF, VEGF), which may synergize with the microneedling-induced response to amplify regenerative and anti-melanogenic effects [4]. For instance, network meta-analyses have highlighted the efficacy of intradermal PRP, potentially mediated by TGF-β1-induced inhibition of melanogenesis [5]. This synergy—where physical intervention primes the tissue for enhanced biological response—could explain the significant outcome disparity. Future studies incorporating sequential skin biopsies for immunohistochemical analysis of melanocyte activity (Melan-A), angiogenesis (CD31), and collagen remodeling pre- and post-treatment could directly test this hypothesis and provide unprecedented mechanistic insight into the combination therapy [6]. However, microinjection combines two types of stimulation: physical and pharmacological. Physical stimulation is initiated by skin puncture, triggering a complex wound healing cascade. Pharmacological stimulation relates to the biological activity of the injected substances. Due to the precise placement of products within the dermis, high concentrations of active ingredients can directly target cells, such as fibroblasts or melanocytes. In contrast, microneedle therapy primarily provides physical stimulation and lacks the ability to directly deliver products to target cells. Therefore, further research is needed to validate the superiority of microneedle technology over microinjection and to explore its underlying mechanisms. Second, the impressive > 75% improvement in 46.7% of the microneedling group underscores the need for long-term follow-up. Melasma is notoriously chronic and recurrent, and durability of treatment response is paramount [5]. While the open-label design may introduce bias in subjective endpoints, the concordance between modified MASI scores and global assessments strengthens the findings. However, data on relapse rates and duration of response at 6–12 months post-treatment would clarify whether microneedling with PRP offers transient improvement or sustained disease modification. Such follow-up would align with emerging research on microneedling-based strategies for long-term skin remodeling and controlled drug delivery [6]. In conclusion, we applaud Sitaula et al. for their valuable contribution [1]. Their work definitively establishes microneedling as the superior PRP delivery method for melasma. We encourage further research to unravel the mechanistic synergy and evaluate long-term outcomes, which could pave the way for optimized combination therapies for this challenging condition. Zhicun Han conceived the idea for this correspondence and drafted the manuscript. Dandan Wang and Ying Chen wrote the manuscript together. All authors reviewed and approved the final version. The authors declare no conflicts of interest. This article is linked to Sitaula et al. papers. To view this article, visit https://doi.org/10.1111/jocd.70246. The data that support the findings of this study are available from the corresponding author upon reasonable request.

Neonatal obesity has profound effects across the entire life. Although maternal diet and environmental exposures such as high altitude are potential influencing factors, the modulating effects of the unique high-altitude environment and distinct ethnic dietary patterns prevalent on the Tibetan Plateau remain unexplored. To investigate this association, we utilized Compositional Data Analysis (CoDA) to model dietary patterns. This study aims to investigate the associations between maternal dietary patterns during pregnancy and neonatal obesity, examining the potential modification effect by altitude and ethnicity. Furthermore, we apply the CoDA approach to quantify the impact of dietary redistribution on obesity risk. The findings are expected to inform targeted dietary interventions and public health strategies for high-risk populations. A birth cohort study encompassed 1173 pregnant women from the Tibetan Plateau. Dietary intake frequency during pregnancy was assessed using the food frequency questionnaire. Principal component analysis was used to identify the dietary patterns. Linear and logistic regression was used to examine the associations between dietary patterns and neonatal obesity. CoDA was employed to assess the association between redistribution of diet servings during pregnancy and altered risk of high ponderal index (HPI). Of the total 1173 mother-neonate pairs, 40.3% were Tibetans, 22.7% resided in ultra-high altitude areas, and 4.9% of neonates had obesity. Four dietary patterns were identified. A higher protein-fruit pattern score was significantly associated with a lower risk of HPI (OR = 0.66, 95% CI 0.47-0.93). We also observed a modification effect by altitude (Pinteraction = 0.026). Stratified by living altitude, this association was statistically significant only in Tibetans who lived in ultra-high altitude areas (OR = 0.39, 95% CI 0.20-0.69, P = 0.003). Composition of data analysis showed that when fruit consumption increased, estimated Δβ of HPI and z-score of ponderal index (PI) decreased. Higher adherence to protein-fruit dietary patterns during pregnancy was negatively associated with neonatal obesity in the Tibetans living in ultra-high altitude areas. Encouraging healthy diets during pregnancy, particularly through initiatives such as increasing fruit intake, may help to prevent neonatal obesity.

This study aimed to compare the inter-arm blood pressure difference (IAD) based on the first reading versus the average of the second and the third readings using computer-programmed blood pressure measurement (CCBPM) in 3067 rural community residents. The detection rate of abnormal systolic IAD (sIAD) was 9.1% based on the first reading, compared to 5.6% based on the average reading-a difference of approximately 40%. These findings suggest that CCBPM should be used with the average of the second and the third readings for sIAD evaluation.

To explore the feasibility of establishing an auxiliary diagnostic model for secondary pulmonary bacterial infection in influenza using routine indicators from fever clinics. A retrospective analysis of 510 influenza cases (divided into modeling and validation sets in a 7:3 ratio) was conducted, with an additional 72 cases selected for external validation. Logistic regression was adopted as the traditional diagnostic model, while two machine learning models (decision tree and random forest) were constructed using R4.2.3 software. The diagnostic performance of each model was evaluated using multiple indicators, including accuracy, sensitivity, specificity, positive predictive value, negative predictive value, receiver operating characteristic curve, and area under the curve (AUC). Among the 357 influenza patients in the modeling set, 101 developed secondary pulmonary bacterial infection, while 256 did not. Multivariate logistic regression analysis showed that age, white blood cell count, C-reactive protein, serum amyloid A, creatine kinase isoenzyme, and D-dimer were independent risk factors for secondary pulmonary bacterial infection (all P<0.05). In the modeling set, validation set, and external validation set, the machine learning model generally outperformed the logistic regression model in all diagnostic performance metrics. The random forest model performed exceptionally well on all three datasets, with AUC values of 0.951, 0.902, and 0.852, respectively. In auxiliary diagnostic models constructed based on routine fever clinic testing indicators, machine learning models, especially the random forest model, demonstrate high diagnostic accuracy and good generalization ability for influenza-related secondary pulmonary bacterial infection.

To the Editor, We have read with great interest the article titled “Associations between peripheral blood mitochondrial genomic variants and gestational diabetes mellitus and postpartum abnormal glucose metabolism,”1 which explores the associations between peripheral blood mitochondrial genomic variants and both gestational diabetes mellitus (GDM) and postpartum abnormal glucose metabolism (AGM). The authors conducted a well-designed case–control study, yielding valuable insights into the potential genetic susceptibility factors underlying GDM and postpartum AGM. Their findings are particularly noteworthy: specific single-nucleotide polymorphisms (SNPs) in the mitochondrial DNA (mtDNA) D-loop region (e.g., 249 days as a risk factor, 309 + C and 16,193 + C as protective factors for GDM), distinct haplogroup associations (e.g., R9 linked to increased GDM risk and M* to reduced risk), and the differential dynamics of mtDNA copy number between whole blood and plasma. These observations meaningfully advance our understanding of mitochondrial involvement in glucose metabolism disorders during and after pregnancy. However, we wish to highlight a key limitation that may impact the generalizability of the findings and the validity of causal inferences. The study population was restricted to a single geographic region with Han Chinese participants exclusively. Mitochondrial DNA haplogroups are known to exhibit marked racial variability and geographic specificity—for example, haplogroups R9 and M7b, identified as significant in this analysis, are highly prevalent in East Asian populations1. This regional homogeneity raises concerns about population stratification bias, which may lead to overestimated effect sizes for these specific haplogroups. Importantly, the findings may not be directly translatable to populations with divergent mtDNA haplogroup distributions (e.g., individuals of European or African ancestry), thereby constraining the external validity of the results. Furthermore, while the cross-sectional case–control design employed for the primary GDM analysis is valuable for identifying associations2, it inherently limits the ability to establish causality between the reported mtDNA variants and GDM development. The observed associations could be confounded by unmeasured factors or may represent epiphenomena. The authors appropriately acknowledge this limitation and call for longitudinal cohort studies and functional experiments to address it. To strengthen causal inference, future research should prioritize multi-ethnic cohorts to validate these associations across diverse genetic backgrounds. Additionally, longitudinal designs that assess mtDNA variants prior to pregnancy and track subsequent GDM incidence would provide more robust evidence for a temporal relationship—and thus potential causality. In conclusion, while Qing Luo et al.'s study provides important preliminary evidence, the geographic restriction of the cohort and the cross-sectional nature of the design warrant cautious interpretation. We believe that addressing these limitations in future work will be critical to confirming the role of mitochondrial genomic variants in the pathogenesis of GDM and postpartum AGM, as well as evaluating their potential as biomarkers across diverse populations. Sincerely, This research did not receive any specific grant from funding agencies in the public, commercial, or not-for profit sectors. The authors declare no conflict of interest. Approval of the research protocol: N/A. Informed consent: N/A. Registry and the registration no. of the study/trial: N/A. Animal studies: N/A. The data that support the findings of this study are available from the corresponding author upon reasonable request.

BackgroundIn the wake of COVID-19, a resurgence of Mycoplasma pneumoniae pneumonia (MPP) has emerged globally since mid-2023. However, the clinical manifestations and immune responses following infection vary across different age groups of pediatric patients (infants, preschoolers and school-aged children), increasing the complexity of diagnosis and treatment.MethodsThis study retrospectively analyzed serum cytokine levels in 40 healthy children and 87 MPP patients, with additional cytokine profiling of bronchoalveolar lavage fluid (BALF) in severe cases, combining KEGG pathway analysis to investigate age-related immune patterns. SARS-CoV-2 antibody levels were further detected in these MPP patients, followed by Spearman correlation analysis to assess their correlation with cytokines in MPP children.ResultsAge-specific cytokine patterns emerged in MPP children. In 0–2 years, cytokines enriched in IL-17, TLR, and TNF pathways were upregulated in MPP groups compared to controls, while in 6–12 years, cytokines enriched in TLR, RLR, and JAK-STAT pathways were downregulated in MPP groups. Serum patterns in 3–5 years resembled those in 0–2 years, but BALF aligned with 6–12 years. SARS-CoV-2 IgG positively correlated with TWEAK, IL-22, IL-16, IL-12p40, CCL7, and CD152 in 0–2 years (P < 0.05), but negatively with CCL13 in 6–12 years (P < 0.01).ConclusionOverall, the immune pattern in children with MPP is age-specific and severity-dependent. Higher levels of SARS-CoV-2 IgG are associated with a more robust and mature anti-infective immune response in younger MPP patients, while in older children, besides providing immune memory against pathogens, SARS-CoV-2 IgG also appears to plant a landmine of immune exhaustion.