Huangshi Central Hospital

Atractylodes lancea, listed as one of the “Ten Great Medicinal Herbs of Chu” in Hubei Province, China, is used in traditional medicine for its dried rhizome. Approximately 75% of A. lancea plants exhibited leaf spot symptoms in April 2025 in a cultivated field in Yingshan County, Hubei Province. Initial symptoms appeared as black necrotic lesions with brown margins at leaf tips or centers, which expanded over time and often led to leaf abscission. To identify the causal agent, symptomatic leaves were surface-sterilized and placed on potato dextrose agar (PDA). After incubation at 28℃ in the dark, hyphal tips from emerging colonies were transferred to fresh PDA for purification. Ten fungal strains were isolated, two of which—named MCZ7 and MCZ14—were selected for further study. On PDA, isolate MCZ7 formed vigorous colonies that were initially white and later turned grayish-brown, with a cottony texture, dense grayish-white aerial mycelium, and concentric rings in later stages. Conidia were mostly ovoid to short-cylindrical, pale olive-green, smooth-walled, with 3–4 transverse septa and 0–2 longitudinal septa, measuring (17.95 ± 7.64) × (9.14 ± 2.09) μm on average. Isolate MCZ14 produced brown colonies with irregular white margins on PDA. Aerial mycelium became sparse in later stages, and dark brown punctuate structures developed. Its growth rate was notably slower than MCZ7. Conidia were ovoid to obclavate, light brown, smooth-walled, with 2–5 transverse septa and 0–1 longitudinal septum, averaging (18.79 ± 6.20) × (7.49 ± 1.00) μm. For molecular identification, the internal transcribed spacer (ITS), β-tubulin (TUB2), and RNA polymerase II second largest subunit (RPB2) were amplified and sequenced (Romain et al. 2022; Zheng et al. 2023). Sequences were deposited in GenBank under the following accession numbers PX915538, PX929565, PX929567 for MCZ7; PX915539, PX929566, PX929568 for MCZ14. Phylogenetic analysis using MEGA11 and Phylosuite placed MCZ7 in the Alternaria alternata clade and MCZ14 with Alternaria tenuissima. Pathogenicity was tested following Koch’s postulates. Healthy A. lancea leaves were surface-sterilized with 75% ethanol (15–30 s) and 1.5% NaClO (90 s), rinsed three times in sterile water, and dried. Leaves were wounded and inoculated with 5-mm mycelial plugs from active PDA cultures; controls received sterile PDA plugs. Each treatment had three technical and three biological replicates. After 3 days at 28°C under dark, humid conditions, leaves inoculated with MCZ7 or MCZ14 developed typical leaf-spot symptoms, while controls remained healthy. The same fungi were re-isolated from lesions and confirmed morphologically and molecularly. Previous studies have reported A. alternata, Alternaria gaisen, Fusarium acuminatum, and Epicoccum sorghinum as leaf spot pathogens of A. lancea (Du et al. 2020; Hu et al. 2024; Kawashimo et al. 2024; Zheng et al. 2023). However, A. tenuissima has not previously been reported to cause leaf spot on this host. Currently, chemical pesticides remain the primary control method for A. lancea diseases. This report has refined the diagnostic methodologies for A. lancea leaf spot disease, and future studies should focus on its control.

ObjectiveThis study aimed to evaluate the effectiveness of the GAiSOLEs teaching model, which integrates Self-Organised Learning Environments (SOLEs) with Generative Artificial Intelligence (GAI), in improving teaching effectiveness, digital literacy and teaching satisfaction in the standardized training of residents.MethodsA single-center, double-blind randomized controlled trial was conducted in this study. A total of 114 standardized training participants for rotating residents were enrolled and randomly divided into two groups: the intervention group (GAiSOLEs teaching model, n = 57) and the control group (traditional teaching model, n = 57). The primary outcome was the teaching effectiveness score before and after intervention. Secondary outcomes included digital literacy score and teaching satisfaction score, both evaluated by standardized scales. Data analysis was performed using χ2 test. Paired and independent samples t-tests, Mann–Whitney U test, and hierarchical multiple linear regression.ResultsPost-intervention teaching effectiveness scores were significantly elevated relative to baseline levels in both the intervention and control groups (all p < 0.05). For all dimensions of teaching effectiveness, the gain scores in the intervention group were markedly higher than those in the control group, with large effect sizes observed across all metrics (theoretical knowledge test: p < 0.001, Hedges’ g = 1.0; clinical skill operation: p < 0.001, Hedges’ g = 1.87; standardized medical record writing: p < 0.001, Hedges g = 1.16; clinical thinking ability: p < 0.001, Hedges’ g = 1.21; doctor-patient communication skills: p < 0.001, Hedges’ g = 1.27). Hierarchical linear regression analysis, after adjusting for covariates including gender, educational background, professional distribution and pre-test scores, revealed that the GAiSOLE intervention (versus the control condition) was a significant positive predictor of higher scores for all five training outcomes (all p < 0.05): theoretical examination (β = 2.329, ΔR2 = 0.294), clinical skill operation (β = 2.947, ΔR2 = 0.499), standardized medical record writing (β = 3.366, ΔR2 = 0.331), clinical thinking ability (β = 3.391, ΔR2 = 0.412), and doctor-patient communication competence (β = 3.157, ΔR2 = 0.355). Moreover, the experimental group achieved significantly higher scores than the control group across all dimensions of digital literacy (all p < 0.05). Additionally, the group also reported significantly higher satisfaction ratings for all teaching parameters relative to the control group (all p < 0.05).ConclusionThe GAiSOLE teaching model was associated with improved teaching effectiveness, digital literacy and teaching satisfaction among residents, and thus holds promising potential as a novel approach for the standardized training of residents.

The exact role of transcription factor PU.1 in traumatic brain injury (TBI) remains unclear. This study aims to investigate the role of PU.1 in microglial function and neuroinflammation following TBI. A combination of bioinformatic analysis of public sequencing data sets (GSE269748 and GSE128543), a mouse TBI model (controlled cortical impact), and in vitro experiments using LPS-stimulated BV2 microglial cells was used. The specific PU.1 inhibitor DB2313 was administered to assess its effects. RNA sequencing, reverse transcription-polymerase chain reaction (RT-PCR), Western blot, immunofluorescence staining, scratch wound assay, and phagocytic capacity assay were used. PU.1 was significantly up-regulated in the sites of injured cortex post-TBI and LPS-treated microglia. Its inhibition by DB2313 attenuated microglial polarization towards the proinflammatory M1 phenotype, reduced the expression of inflammatory mediators, and suppressed microglial migration while enhancing phagocytosis. Mechanistically, PU.1 exacerbated neuroinflammation via the TLR4/MyD88/NF-κB signaling pathway and promoted NLRP3 inflammasome-Caspase-1-mediated pyroptosis. PU.1 is a key regulator of neuroinflammation and pyroptosis after TBI. Targeting PU.1 represents a promising therapeutic strategy to mitigate microglial-mediated inflammatory damage and improve outcomes following TBI.

Conventional antibiotic treatments for infected wounds often inadequately regulate the complex inflammatory cascade and fail to sufficiently promote tissue regeneration, leading to delayed healing and potential secondary tissue damage. Consequently, designing multifunctional biomaterials capable that can simultaneously exert antibacterial, anti-inflammatory, and pro-regenerative actions remains a critical challenge in wound management. In this study, we developed a soluble microneedle (MN) array loaded with nanovesicles derived from Coptis chinensis (CDVs), which serves as an integrated tri-functional platform to synergistically accelerate healing of infected wounds. The CDVs were effectively encapsulated within sodium alginate-based microneedles, with calcium ions introduced to reinforce structural crosslinking. Upon penetration into the wound bed, the MNs facilitated deep tissue delivery and sustained release of CDVs, which triggered a ROS burst inside bacteria, resulting in membrane disruption and bacterial eradication. Both in vitro and in vivo evaluations confirmed that the released CDVs promoted macrophage polarization toward the M2 phenotype and enhanced glucose uptake via the AMPK/mTOR pathway, thereby remodeling the inflammatory microenvironment and stimulating angiogenesis and tissue regeneration. Notably, in vivo wound healing assays demonstrated that the MN-mediated delivery of CDVs significantly enhanced repair outcomes compared to free vesicle treatment. This study highlights the rational integration of multifunctional plant-derived nanovesicles with a microneedle platform as a promising and translatable strategy for developing safe and effective therapeutics for infected wound healing.Graphical Graphical Supplementary InformationThe online version contains supplementary material available at 10.1186/s12951-026-04218-3.

Dear Editor, I am writing to express my perspectives on the article entitled “Identifying the minimum number of retrieved lymph nodes in node-negative duodenal adenocarcinoma: a retrospective analysis of real-world data and the SEER database” by Zhenxing Jiang et al[1]. This study addresses a critical clinical challenge in the management of duodenal adenocarcinoma (DA), aiming to define the optimal number of retrieved lymph nodes (rLNs) for accurate N-stage assessment. By leveraging dual-cohort data (real-world data and SEER database), the authors established stratified rLN thresholds for node-negative (N0) and node-positive (N1) DA patients, providing valuable insights for optimizing surgical and postoperative therapeutic strategies[1]. Nevertheless, after a careful review of the manuscript, we identified several critical points that require further clarification and improvement to enhance the validity and generalizability of the conclusions. First, the retrospective design inherently carries selection bias, and temporal confounding factors may have compromised the consistency of the results. This study relies on historical data with a 10-year follow-up period, during which significant advancements have been made in DA diagnostic techniques (e.g., enhanced imaging modalities) and treatment protocols (e.g., refined surgical approaches and adjuvant therapy regimens). Such dynamic changes in the clinical management system are likely to reduce the homogeneity of research data across different periods, thereby undermining the stability of the study conclusions. Notably, Figure 3B of the external validation cohort clearly demonstrates an upward trend in rLN counts over time. This observation directly corroborates the interference of time-related confounding factors, suggesting that variations in diagnosis and treatment practices across the study period may have biased the core research indicator (rLN count). Second, the lack of detailed information on surgical approaches precludes clarification of the causal relationship between rLNs and prognosis. The manuscript fails to specify the surgical procedures adopted for the included patients. Extant literature has well established that standard surgical approaches for DA are heterogeneous, including distal gastrectomy, pancreaticoduodenectomy (PD), and segmental/local excision[2]. These surgical approaches not only exert a direct and significant impact on patient prognosis but also indirectly affect prognostic analyses by altering rLN counts. For instance, Sakamoto et al confirmed that patients undergoing PD have significantly higher rLN counts than those receiving limited resection[2]. Consequently, the current study cannot distinguish between two potential causal pathways: whether rLN count itself is a prognostic factor, or whether different surgical approaches indirectly influence prognosis by modifying rLN counts through a mediating effect. We recommend the authors supplement detailed surgical data and perform mediation effect analysis to clarify the true relationship between these core variables. Third, the prognostic association pattern of rLNs remains unclear, and the methods used to determine cut-off values have inherent flaws. On one hand, existing studies have reported an association between increased rLN counts and decreased survival rates in certain tumor types[3]. However, this study did not explore whether such a specific association exists in DA, leading to an incomplete understanding of the rLN-prognosis relationship. On the other hand, the authors employed the Contal and O’Quigley method and X-tile method to determine optimal rLN cut-off values, which have three major limitations: (1) forced stratification of the continuous rLN variable (e.g., binary or ternary classification) results in loss of continuous distribution information; (2) inability to capture potential non-linear associations between rLNs and prognosis; and (3) data-driven segmentation is susceptible to outliers, leading to high overfitting risk and poor result stability. If cut-off value analysis is retained, strict statistical validation (e.g., cross-validation, multiple comparison correction, and external cohort validation) is essential to reduce bias and ensure result reliability and generalizability. A more robust alternative is to adopt restricted cubic splines or the K-Adaptive Partitioning for Survival Data method, which preserve variable continuity, accurately characterize non-linear relationships, and enhance result scientificity[4]. In conclusion, Jiang et al’s study explores an important clinical question, but the aforementioned limitations may affect the validity of its conclusions. Addressing these issues will significantly improve the study’s academic value and clinical implications.

Abstract Background MicroRNAs (miRNAs) play a crucial role in tumorigenesis and malignant transformation. Studies indicate that miR-4652-3p is aberrantly expressed in various cancer types. However, its impact and underlying mechanisms in non-small cell lung cancer (NSCLC) have not been investigated. Methods A549 cells were stimulated with IL-1β, TNF-α, and IL-6 (each at 10 ng/ml) to mimic an inflammatory microenvironment. Metabolic status was evaluated by measuring glutamine uptake, α-ketoglutarate (α-KG), and ATP levels. Functional studies employed the glutaminase inhibitor (CB-839), the MYC inhibitor (10058-F4), SLC1A5 small interfering RNA (siSLC1A5-2), a miR-4652-3p mimic, and overexpression plasmids. Molecular interactions were validated using chromatin immunoprecipitation (ChIP), dual-luciferase reporter assays, and RNA pull-down experiment. CCK-8 and Transwell assays were used for the assessment of cell malignant phenotypes. The functional significance of miR-4652-3p was further verified in a xenograft mouse model. Results miR-4652-3p was downregulated in NSCLC, while MYC and SLC1A5 were upregulated. Inflammatory stimulation enhanced A549 cell proliferation, glutamine uptake, and α-KG/ATP production; these effects were attenuated by CB-839. ChIP and dual-luciferase assays demonstrated that MYC binds the SLC1A5 promoter and activates its transcription. Inhibiting MYC or knocking down SLC1A5 significantly reduced glutamine uptake. Mechanistic analysis revealed that miR-4652-3p directly targets both MYC and SLC1A5 mRNA. miR-4652-3p suppressed glutamine metabolism in NSCLC cells by negatively regulating the MYC/SLC1A5 axis, consequently inhibiting cell growth and tumor progression in a xenograft mouse model, an effect reversed by MYC or SLC1A5 overexpression. Conclusions miR-4652-3p blocked the inflammatory microenvironment-induced glutamine metabolic reprogramming by directly suppressing the MYC/SLC1A5 axis, thereby inhibiting NSCLC progression. The miR-4652-3p/MYC/SLC1A5 pathway represents a key regulatory mechanism for metabolic adaptation in NSCLC.

Chronic nonspecific low back pain (CNSLBP), a debilitating condition associated with abnormal anterior cingulate cortex (ACC) activity and central sensitization, may be addressed through intermittent theta-burst stimulation (iTBS), a non-invasive neuromodulation technique. iTBS is designed to restore the ACC’s excitatory/inhibitory balance by suppressing abnormal gamma oscillations and enhancing synaptic plasticity. Clinical evidence shows that iTBS can reduce ACC gamma power, strengthen corticostriatal circuit connectivity, and provide short-term pain relief, although efficacy varies with protocol, pain subtype, and individual differences. In conclusion, iTBS represents a promising approach for managing CNSLBP by modulating neuroplasticity. Future efforts should focus on optimizing stimulation parameters, integrating multimodal data for personalized treatment, and validating long-term benefits through large-scale trials to shift the therapeutic paradigm towards remodeling maladaptive neural pathways.

BackgroundThe subcortical maternal complex (SCMC) orchestrates early embryogenesis; TLE6, a core SCMC component, stabilizes the complex and regulates cytoskeletal dynamics during the oocyte-to-embryo transition. Pathogenic TLE6 variants are associated with pre-implantation arrest and infertility, but the mutational spectrum and rescue strategies remain incompletely defined. This study aims to describe a case of embryonic arrest associated with a novel homozygous TLE6 variant, elucidate its pathogenic mechanism, and evaluate an mRNA add-back rescue approach.Materials and methodsA case of primary infertility with repeated IVF failure underwent whole-exome sequencing, followed by confirmatory Sanger sequencing performed in the proband and parents. The variant function was assessed using a minigene splicing assay, Mutalyzer prediction, and structural modeling. A CRISPR/Cas9 Tle6 mouse model was evaluated for developmental consequences. Wild-type Tle6 mRNA was microinjected into mutant zygotes to test its rescue potential.ResultsA novel homozygous splice-region variant in TLE6 (NM_001143986.1: exon7: c.286-7G > A) was identified, with both parents confirmed as heterozygous carriers. The minigene assay showed aberrant splicing with a 5-nucleotide insertion, producing a frameshift and premature truncation. Structural modeling predicted the loss of the C-terminal domain essential for SCMC integrity. The Tle6 mutant mouse recapitulated cleavage-stage arrest with reduced blastocyst formation. Zygotic add-back of wild-type Tle6 mRNA yielded only limited improvement, with persistent developmental failure.ConclusionThese findings expand the TLE6 variant spectrum and support a loss-of-function mechanism causing embryonic arrest through SCMC disruption. Acute zygotic mRNA supplementation was insufficient to restore developmental competence, indicating the need for alternative or early-stage interventions and informing genetic counseling for affected families.

Extracapsular extension (ECE) of prostate cancer (PCa) is a crucial determinant for preoperative staging, significantly influencing urologists’ surgical planning. While magnetic resonance imaging (MRI) aids staging by depicting ECE, its diagnostic accuracy is frequently constrained by poor image quality. Deep learning-based diffusion-weighted imaging (DL-DWI) holds potential for enhancing diagnostic accuracy through improved image quality. This multicenter retrospective study enrolled 252 consecutive patients with clinically suspected PCa from five centers between June 2019 and September 2023. All patients underwent multiparametric MRI (mpMRI) followed by radical prostatectomy. A denoising diffusion probabilistic model (DDPM) was developed to synthesize high-b-value DL-DWI images. Two radiologic residents independently evaluated the image quality of DL-DWI and conventionally obtained DWI (C-DWI) using a five-point Likert scale. Objective image quality metrics including estimated signal-to-noise ratio (eSNR), contrast-to-noise ratio (CNR), edge rise distance (ERD), and edge rise slope (ERS) were quantitatively assessed and compared between sequences. Four radiologists (experience range: 2–20 years) independently made the diagnosis of each patient based on the DL-DWI and C-DWI using the four-scale ECE grade system. Intra-reader agreement was assessed using weighted kappa, and inter-reader agreement using Fleiss’ kappa. Diagnostic performance was compared using multi-reader multi-case receiver operating characteristic analysis, with the area under the curve (AUC) as the metric. Decision curve analysis (DCA) evaluated the net clinical benefit. Statistical significance was defined as a two-sided P < 0.05. DL-DWI demonstrated significantly superior image quality compared to C-DWI (P < 0.05) and higher agreement for both intra-reader (weighted κ: 0.59, 0.45 vs. 0.40, 0.33 for readers 1 and 2, respectively) and inter-reader (weighted κ: 0.59 vs. 0.48) quality assessments. Quantitative analysis confirmed substantial improvement in DL-DWI across all objective metrics: eSNR (56.66 ± 7.36 vs. 31.76 ± 12.97, P < 0.001), CNR (28.89 ± 9.27 vs. 10.53 ± 5.48, P < 0.001), ERD (2.85 [IQR:1.90–3.80] vs. 4.27 [IQR:3.27–5.60], P < 0.001), and ERS (69.48 ± 19.15 vs. 23.82 ± 10.29, P < 0.001). For ECE detection, DL-DWI showed higher intra-reader agreement (weighted κ for readers 3–6: 0.53, 0.56, 0.67, 0.70 vs. 0.53, 0.34, 0.52, 0.49) and inter-reader agreement (Fleiss κ: 0.25 vs. 0.18) compared to C-DWI. DL-DWI achieved significantly higher diagnostic performance (mean AUC: 0.76 [95% CI: 0.71–0.80] vs. 0.70 [95% CI: 0.65–0.74], P < 0.001). DCA indicated greater net clinical benefit for DL-DWI compared to C-DWI. DL-DWI appears to outperform C-DWI in both image quality and clinical utility, showing potential to improve ECE diagnostic accuracy for residents, enhance inter-reader consistency, and provide greater net benefit in clinical decision-making. Not applicable.