ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

Objective To compare the performance of 7 Chinese-developed GenAI models (DeepSeek, Wenxin Yiyan, Tongyi, Doubao, Kimi, Hunyuan, and iFLYTEK Spark) in responding to common diseases of the pediatric genitourinary system and to explore their potential applications.Methods A total of 80 questions covering basic disease information, diagnosis, treatment, and prognosis related to “hypospadias, hydronephrosis, and cryptorchidism” were developed as prompts.The models were tested under 3 modes:“quick thinking, ”“deep thinking, ” and “deep thinking + internet access.” The results were evaluated in a blinded review by two pediatric urologists.The responses were graded into 4 levels—A, B, C, and D—based on accuracy, completeness, and relevance.The proportions of responses rated as A and A+B were statistically analyzed and compared across the different models/modes.Results The “deep thinking” mode of DeepSeek demonstrated the best performance, with 88% of responses rated as A and 96% rated as A+B.DeepSeek (deep thinking + internet access), Doubao (quick thinking), Hunyuan (deep thinking), and Doubao (deep thinking + internet access) followed closely, also showing excellent response capabilities.Among the top 5 models/modes, significant differences were observed in the proportion of Alevel responses (P＜0.05), while differences in the proportion of A+B-level responses were not statistically significant (P＞0.05).Conclusion Certain Chinese-developed GenAI models, represented by DeepSeek (deep thinking), demonstrate significant application potential.However, they still cannot consistently provide recommendations rated at the A+B level (recommended grade or higher) with 100% accuracy.In clinical practice, both doctors and patients should view GenAI as an auxiliary tool for education and information acquisition rather than as a final decision-making authority.All information must be reviewed and confirmed by professional physicians.

A growing global trend indicates a decline in semen quality, with a lack of physical activity identified as one of the contributing factors. Exercise is medication, and numerous studies have explored its effects on semen quality. However, there is no consensus on the most effective type and intensity of exercise for improving semen quality, owing to inconsistent findings across studies. These discrepancies may be attributable to variations in study populations ( e.g. , healthy versus infertile individuals) and research methodologies ( e.g., observational versus interventional studies). This paper reviews the existing literature from the databases PubMed, Web of Science, and Google Scholar, reclassifying articles on their subject and research designs to delineate the relationship between exercise and semen quality. It also summarizes the mechanisms through which exercise influences semen quality, including hormonal regulation, oxidative stress, and inflammatory factors.
Humans ; Semen Analysis ; Male ; Exercise/physiology* ; Oxidative Stress/physiology* ; Infertility, Male/physiopathology* ; Sperm Motility/physiology*

OBJECTIVE: To explore the efficacy and apoptosis of allogeneic hematopoietic stem cell transplantation (allo-HSCT) in the treatment of acute myeloid leukemia (AML) with ASXL1 mutation. METHODS: The clinical data of 80 AML patients with ASXL1 mutation treated in our hospital from January 2019 to December 2021 were retrospectively analyzed. The clinical characteristics of the patients were summarized, and the therapeutic effect and prognostic factors of allo-HSCT for the patients were analyzed. RESULTS: Among the 80 patients, 38 were males and 42 were females, and the median age was 39(14-65) years. There were 17 patients in low-risk group, 25 patients in medium-risk group and 38 patients in high-risk group. ASXL1 mutation co-occurred with many other gene mutations, and the frequent mutated genes were TET2 (71.25%), NRAS (18.75%), DNMT3A (16.25%), NPM1 (15.00%), CEBPA (13.75%). Among medium and high-risk patients, 29 underwent allo-HSCT, while 34 received chemotherapy. The 2-year overall survival (OS) rate and disease-free survival (DFS) rate of the allo-HSCT group were 72.4% and 70.2%, while those of the chemotherapy group were 44.1% and 34.0%, respectively. The statistical analysis showed significant differences between the two groups (both P < 0.01). Multivariate analysis showed that age at transplantation >50- years and occurrence of acute graft-versus-host disease after transplantation were poor prognostic factors for OS and DFS in transplantation patients. CONCLUSION Allo-HSCT can improve the prognosis of AML patients with ASXL1 mutation.
Humans ; Leukemia, Myeloid, Acute/therapy* ; Hematopoietic Stem Cell Transplantation ; Female ; Male ; Middle Aged ; Mutation ; Adult ; Repressor Proteins/genetics* ; Adolescent ; Retrospective Studies ; Aged ; Nucleophosmin ; Young Adult ; Transplantation, Homologous ; Prognosis ; Survival Rate

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

OBJECTIVE: This study reports the first imported case of Lassa fever (LF) in China. Laboratory detection and molecular epidemiological analysis of the Lassa virus (LASV) from this case offer valuable insights for the prevention and control of LF. METHODS: Samples of cerebrospinal fluid (CSF), blood, urine, saliva, and environmental materials were collected from the patient and their close contacts for LASV nucleotide detection. Whole-genome sequencing was performed on positive samples to analyze the genetic characteristics of the virus. RESULTS: LASV was detected in the patient's CSF, blood, and urine, while all samples from close contacts and the environment tested negative. The virus belongs to the lineage IV strain and shares the highest homology with strains from Sierra Leone. The variability in the glycoprotein complex (GPC) among different strains ranged from 3.9% to 15.1%, higher than previously reported for the seven known lineages. Amino acid mutation analysis revealed multiple mutations within the GPC immunogenic epitopes, increasing strain diversity and potentially impacting immune response. CONCLUSION The case was confirmed through nucleotide detection, with no evidence of secondary transmission or viral spread. The LASV strain identified belongs to lineage IV, with broader GPC variability than previously reported. Mutations in the immune-related sites of GPC may affect immune responses, necessitating heightened vigilance regarding the virus.
Humans ; China/epidemiology* ; Genome, Viral ; Lassa Fever/virology* ; Lassa virus/classification* ; Molecular Epidemiology ; Phylogeny

This study aims to explore the mechanism through which Yishen Jiangtang Decoction(YSJTD) regulates endoplasmic reticulum stress(ERS)-mediated NOD-like receptor thermal protein domain associated protein 3(NLRP3) inflammasome to improve diabetic nephropathy(DN) in db/db mice. Thirty db/db mice were randomly divided into the model group, YSJTD group, ERS inhibitor 4-phenylbutyric acid(4-PBA) group, with 10 mice in each group. Additionally, 10 db/m mice were selected as the control group. The YSJTD group was orally administered YSJTD at a dose of 0.01 mL·g~(-1), the 4-PBA group was orally administered 4-PBA at a dose of 0.5 mg·g~(-1), and the control and model groups were given an equal volume of carboxylmethyl cellulose sodium. The treatments were administered once daily for 8 weeks. Food intake, water consumption, and body weight were recorded every 2 weeks. After the intervention, fasting blood glucose(FBG), glycosylated hemoglobin(HbA1c), urine microalbumin(U-mALB), 24-hour urine volume, serum creatinine(Scr), and blood urea nitrogen(BUN) were measured. Inflammatory markers interleukin-1β(IL-1β) and interleukin-18(IL-18) were detected using the enzyme-linked immunosorbent assay(ELISA). Renal pathology was assessed through hematoxylin-eosin(HE), periodic acid-Schiff(PAS), and Masson staining, and transmission electron microscopy(TEM). Western blot was used to detect the expression levels of glucose-regulated protein 78(GRP78), C/EBP homologous protein(CHOP), NLRP3, apoptosis-associated speck-like protein containing CARD(ASC), cysteinyl aspartate-specific proteinase(caspase-1), and gasdermin D(GSDMD) in kidney tissues. The results showed that compared to the control group, the model group exhibited poor general condition, increased weight and food and water intake, and significantly higher levels of FBG, HbA1c, U-mALB, kidney index, 24-hour urine volume, IL-1β, and IL-18. Compared to the model group, the YSJTD and 4-PBA groups showed improved general condition, increased body weight, decreased food intake, and lower levels of FBG, U-mALB, kidney index, 24-hour urine volume, and IL-1β. Specifically, the YSJTD group showed a significant reduction in IL-18 levels compared to the model group, while the 4-PBA group exhibited decreased water intake and HbA1c levels compared to the model group. Although there was a decreasing trend in water intake and HbA1c in the YSJTD group, the differences were not statistically significant. No significant differences were observed in BUN, Scr, and kidney weight among the groups. Renal pathology revealed that the model group exhibited more severe renal damage compared to the control group. Kidney sections from the model group showed diffuse mesangial proliferation in the glomeruli, tubular edema, tubular dilation, significant inflammatory cell infiltration in the interstitium, and increased glycogen staining and blue collagen deposition in the basement membrane. In contrast, the YSJTD and 4-PBA groups showed varying degrees of improvement in renal damage, glycogen staining, and collagen deposition, with the YSJTD group showing more significant improvements. TEM analysis indicated that the model group had extensive cytoplasmic edema, homogeneous thickening of the basement membrane, fewer foot processes, and widening of fused foot processes. In the YSJTD and 4-PBA groups, cytoplasmic swelling of renal tissues was reduced, the basement membrane remained intact and uniform, and foot process fusion improved.Western blot results indicated that compared to the control group, the model group showed upregulation of GRP78, CHOP, GSDMD, NLRP3, ASC, and caspase-1 expression. In contrast, both the YSJTD and 4-PBA groups showed downregulation of these markers compared to the model group. These findings suggest that YSJTD exerts a protective effect against DN by alleviating NLRP3 inflammasome activation through the inhibition of ERS, thereby improving the inflammatory response in db/db DN mice.
Animals ; Endoplasmic Reticulum Stress/drug effects* ; Diabetic Nephropathies/metabolism* ; NLR Family, Pyrin Domain-Containing 3 Protein/genetics* ; Drugs, Chinese Herbal/administration & dosage* ; Mice ; Inflammasomes/drug effects* ; Male ; Kidney/pathology* ; Endoplasmic Reticulum Chaperone BiP ; Humans ; Interleukin-18/genetics* ; Mice, Inbred C57BL

Objective:To evaluate the effects and underlying mechanisms of preoperative intestinal microbiota modulation on the recovery of prolonged postoperative ileus(PPOI)in gastric cancer patients with sarcopenia Methods:Skeletal muscle mass(SMM)was assessed using bioelectrical impedance analysis(BIA),and the skeletal muscle index(SMI)was calculated.A total of 156 gastric cancer patients with sarcopenia who underwent surgery at the Department of Gastrointestinal Surgery,Liyang People's Hospital,from January 2022 to December 2024 were randomly assigned to either the control group or the experimental group.The control group received conventional prehabilitation interventions,including nutritional support,respiratory function training,and physical exercise.The experimental group received probiotic-based intestinal microbiota modulation in addition to conventional prehabilitation interventions.Postoperative recovery indicators,including time to first flatus,incidence of postoperative complications,length of hospital stay,and hospitalization costs,were compared between the two groups.Results:Among the 156 sarcopenic gastric cancer patients,121 were male,and 35 were female.Statistically significant differences were observed between the two groups in terms of time to first flatus,incidence of postoperative complications,and length of hospital stay(P<0.05).Postoperative complications occurred in 38 patients(24.3%),with 10 cases(6.4%)in the experimental group and 28 cases(17.9%)in the control group.The time to first flatus in the experimental group was significantly shorter than in the control group(48.0 hours vs 72.0 hours,P<0.001).Conclusion:Preoperative intestinal microbiota modulation significantly reduces the incidence of PPOI and postoperative complications in gastric cancer patients with low SMI,thereby promoting postoperative gastrointestinal function recovery.

Forensic medicine has been designated as a first-level discipline,presenting new opportunities and challenges for the development of forensic medicine.Since the 1980s,the establishment of foren-sic medicine discipline and the cultivation of high-level forensic talents have become hot topics in the development of forensic medicine in China.Since the 13th Five-Year Plan,the forensic team of Shanxi Medical University has been aiming at the forefront,proposing the development goals of"Five First-class"and the discipline development path"Six Major Achievements".It has selected benchmark disci-plines,identified gaps in disciplinary development,unified thoughts,formulated completion timelines,concentrated superior resources,assigned tasks to individuals,and created an"Organized Fill-in-the-Blank Format"forensic medicine discipline construction model with the characteristics of the new era.The construction model of forensic medicine has achieved good results in the goals,discipline frame-work,scientific research,talent cultivation,discipline team and platform construction,forming a rela-tively complete discipline construction and management system,and accumulating valuable experience for the construction of first-level discipline and high-level talent cultivation of forensic medicine.