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.

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.

Integrin α _v β ₃ is overexpressed in various tumor cells and angiogenesis. To date, no drug has been proven to target it for therapy. A first-in-human study was designed to investigate the safety, pharmacokinetics, and dosimetry of ¹⁷⁷Lu-AB-3PRGD2, a novel integrin α _v β ₃-targeting radionuclide drug with an albumin-binding motif to optimize the pharmacokinetics. Ten patients (3 men, 7 women; aged 45 ± 16 years) with integrin α _v β ₃-avid tumors were recruited to accept ¹⁷⁷Lu-AB-3PRGD2 injection in a dosage of 1.57 ± 0.08 GBq (42.32 ± 2.11 mCi), followed by serial scans to obtain its dynamic distribution in the body. Safety tests were performed before and every 2 weeks after the treatment for 6-8 weeks. No adverse event over grade 3 was observed. ¹⁷⁷Lu-AB-3PRGD2 was excreted mainly through the urinary system, with intense radioactivity in the kidneys and bladder. Moderate distribution was found in the liver, spleen, and intestines. The estimated blood half-life was 2.85 ± 2.17 h. The whole-body effective dose was 0.251 ± 0.047 mSv/MBq. The absorbed doses were 0.157 ± 0.032 mGy/MBq in red bone marrow and 0.684 ± 0.132 mGy/MBq in kidneys. This first-in-human study of ¹⁷⁷Lu-AB-3PRGD2 treatment indicates its promising potential for targeted radionuclide therapy of integrin α _v β ₃-avid tumors. It merits further studies in more patients with escalating doses and multiple treatment courses.

The liver regenerative capacity is crucial for patients with end-stage liver disease following partial hepatectomy (PHx). The specific bacteria and mechanisms regulating liver regeneration post-PHx remain unclear. This study demonstrated dynamic changes in the abundance of Parabacteroides distasonis (P. distasonis) post-PHx, correlating with hepatocyte proliferation. Treatment with live P. distasonis significantly promoted hepatocyte proliferation and liver regeneration after PHx. Targeted metabolomics revealed a significant positive correlation between P. distasonis and β-hydroxybutyric acid (BHB), as well as hyodeoxycholic acid and 3-hydroxyphenylacetic acid in the gut after PHx. Notably, treatment with BHB, but not hyodeoxycholic acid or 3-hydroxyphenylacetic acid, significantly promoted hepatocyte proliferation and liver regeneration in mice after PHx. Moreover, STAT3 inhibitor Stattic attenuated the promotive effects of BHB on cell proliferation and liver regeneration both in vitro and in vivo. Mechanistically, P. distasonis upregulated the expression of fatty acid oxidation-related proteins, and increased BHB levels in the liver, and then BHB activated the STAT3 signaling pathway to promote liver regeneration. This study, for the first time, identifies the involvement of P. distasonis and its associated metabolite BHB in promoting liver regeneration after PHx, providing new insights for considering P. distasonis and BHB as potential strategies for promoting hepatic regeneration.

OBJECTIVE: To identify prognostic genes associated with lysosome-dependent cell death (LDCD) in patients with gastric cancer (GC). METHODS: Differentially expressed genes (DEGs) were identified using The Cancer Genome Atlas - Stomach Adenocarcinoma. Weighted gene co-expression network analysis was performed to identify the key module genes associated with LDCD score. Candidate genes were identified by DEGs and key module genes. Univariate Cox regression analysis, and least absolute shrinkage and selection operator regression and multivariate Cox regression analyses were performed for the selection of prognostic genes, and risk module was established. Subsequently, key cells were identified in the single-cell dataset (GSE183904), and prognostic gene expression was analyzed. Cell proliferation and migration were assessed using the Cell Counting Kit-8 assay and the wound healing assay. RESULTS: A total of 4,465 DEGs, 95 candidate genes, and 4 prognostic genes, including C19orf59, BATF2, TNFAIP2, and TNFSF18, were identified in the analysis. Receiver operating characteristic curves indicated the excellent predictive power of the risk model. Three key cell types (B cells, chief cells, and endothelial/pericyte cells) were identified in the GSE183904 dataset. C19orf59 and TNFAIP2 exhibited predominant expression in macrophage species, whereas TNFAIP2 evolved over time in endothelial/pericyte cells and chief cells. Functional experiments confirmed that interfering with C19orf59 inhibited proliferation and migration in GC cells. CONCLUSION C19orf59, BATF2, TNFAIP2, and TNFSF18 are prognostic genes associated with LDCD in GC. Furthermore, the risk model established in this study showed robust predictive power.
Stomach Neoplasms/pathology* ; Humans ; Prognosis ; Lysosomes/physiology* ; RNA-Seq ; Cell Death ; Single-Cell Analysis ; Gene Expression Regulation, Neoplastic ; Cell Proliferation ; Single-Cell Gene Expression Analysis

Objective:To investigate factors influencing frequent episodes (≥ 4 episodes within 1 year) in children with moderate-to-severe atopic dermatitis (AD) in China.Methods:A national multicenter cross-sectional study was conducted. Patients under the age of 18 years diagnosed with moderate-to-severe AD were enrolled at dermatology clinics in 18 medical institutions across 12 provinces and municipalities in China between June 12 and August 8, 2023. At the time of the visit, their guardians completed a structured questionnaire covering demographic characteristics, clinical features of AD, personal and family history, factors associated with frequent episodes of moderate-to-severe AD, compliance with treatment, and disease awareness. Statistical analyses included t tests, one-way analysis of variance, rank-sum tests, and chi-square tests, with multiple-response analysis applied for multiple-choice questions. Results:A total of 965 valid questionnaires were collected, and 965 children with moderate-to-severe AD were included. Among them, there were 531 males and 434 females, 678 (70.3%) were aged 2 - < 12 years, 837 (86.7%) were from urban areas, the age at onset was 2.47 ± 3.03 years, and the median frequency of AD episodes in the past year was 4 times. These children were divided into 2 groups based on the median episode frequency: < 4-episode group (439 cases, 45.5%) and ≥ 4-episode group (526 cases, 54.5%). Compared with the < 4-episode group, children in the ≥ 4-episode group showed younger ages at onset (2.22 ± 2.98 years vs. 2.76 ± 3.06 years, P = 0.006) and higher proportions of patients with comorbid allergic diseases in both the children themselves (82.9% [436/526] vs. 69.7% [306/439], χ2 = 23.42, P < 0.001) and their relatives (66.0% [347/526] vs. 57.4% [252/439], χ2 = 7.46, P = 0.006). Children in the ≥ 4- episode group also had higher monthly usage of moisturizers (150 [30, 300] g vs. 60 [6, 200] g) and daily frequency of moisturizer use, greater disease awareness, but more severe fear of medication use (all P < 0.05). The region and the human development index level were both significantly associated with the episode frequency (both P < 0.001), with the highest proportion of children from South China in the ≥ 4- episode group (36.3%, 191/526). Children in the ≥ 4-episode group also had a longer duration of topical glucocorticoid use than those in the < 4-episode group ( Z = -2.21, P = 0.027). External triggers associated with AD episodes mainly included heat exposure (50.36%, 486/965), hot water bathing (40.73%, 393/965), seafood (23.52%, 227/965), and dust mites (33.37%, 322/965) . Conclusion:In children with moderate-to-severe AD in China, factors influencing frequent episodes may include residence in southern or economically developed regions, earlier age at onset, having a personal or family history of allergic diseases, and fear of medication use.

Objective To analyze the imaging features of cerebral small vessel disease in patients with type 2 diabetes mellitus by multimodal MRI.Methods The clinical data of 160 patients with cerebral small vessel disease admitted to our hospital from January to December 2020 were retrospectively analyzed.According to whether they were complicated with type 2 diabetes mellitus,they were divided into the diabetic group and the non-diabetic group,with 80 cases in each group.Both groups underwent multimodal MRI scans.And the severity of lacunar infarction,the severity of subcortical and periventricular white matter lesions,white matter integral and cerebral microbleeds of patients in the two groups were compared.Results The severity of lacunar infarction(χ2=34.076,P=0.001),subcortical white matter lesions(χ2=25.000,P=0.001),periventricular white matter lesions(χ2=22.895,P=0.001)and white matter integral(t=12.370,P=0.001)of patients in the diabetic group were significantly higher than those in the non-diabetic group.No cerebral microbleeds were detected in either group of patients.Conclusion Patients with cerebral small vessel disease and type 2 diabetes mellitus show characteristic multimodal MRI changes.The increase in the number of lacunar infarction lesions and the aggravation of white matter lesions can be used as the characteristic imaging basis for the diagnosis of type 2 diabetes mellitus related cerebral small vessel disease.

Objective To analyze the value of MRI in evaluating the treatment efficacy of neoadjuvant chemotherapy(NAC)in breast cancer patients.Methods The clinical data of 130 patients with breast cancer were analyzed retrospectively.All patients under-went 4-8 cycles of NAC,with MRI examinations was performed before and after NAC treatment.Based on postoperative response eval-uation criteria in solid tumors(RECIST),the patients were categorized into effective and ineffective groups.The MRI related param-eters,early enhancement parameters and peak enhancement parameters before and after NAC were observed to evaluate the efficacy of MRI in evaluating the treatment efficacy of NAC in breast cancer.Results The sensitivity,specificity,and accuracy of MRI in evalua-ting the treatment efficacy of NAC in breast cancer were 96.74％,89.47％,and 94.62％,respectively.The Kappa value for consis-tency analysis between MRI and postoperative pathology reached 0.869,indicating good agreement.Receiver operating characteristic(ROC)curve analysis showed that the area under the curve(AUC)for MRI in predicting the treatment efficacy of NAC in breast cancer was 0.935[95％ confidence interval(CI)0.831-0.981].Significant differences were observed between the effective and ineffec-tive groups in early and peak enhancement parameters before and after NAC(P＜0.05).Conclusion MRI can effectively assesses the treatment efficacy of NAC in breast cancer patients,demonstrating high value in clinical applications.