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.

Objectives: . The prognostic value of the pretreatment albumin-to-alkaline phosphatase ratio (AAPR) in head and neck cancer (HNC) remains uncertain. This meta-analysis aimed to evaluate the predictive role of AAPR for survival outcomes in patients with HNC. Methods: . A comprehensive search of the Cochrane Library, PubMed, and Embase databases was conducted to identify relevant studies published up to July 30, 2024. We included studies on AAPR and survival outcomes in HNC patients. Results: . Eight studies comprising 1,737 HNC patients were analyzed using random-effects models. Lower AAPR values were significantly correlated with worse overall survival (hazard ratio [HR], 2.08), progression-free survival (HR, 2.00), and disease-free survival (HR, 2.18). Sensitivity analyses confirmed the robustness of these results, with no significant publication bias detected. Conclusion . Our findings suggest that pretreatment AAPR could serve as a valuable and cost-effective prognostic indicator in HNC, potentially aiding clinicians in risk stratification and treatment decision-making. However, additional validation studies are warranted to confirm its clinical applicability.

Multidrug-resistant (MDR) bacterial infections have emerged as a serious challenge of global public health crisis. The overuse and misuse of conventional antibiotics have dramatically accelerated the emergence, evolution and worldwide spread of drug-resistant bacterial strains, necessitating urgent exploration of novel antibacterial strategies. Bacteriophages serve as natural bacterial predators offering distinct advantages including high host specificity, autonomous self-replication capabilities and cost-effective large-scale production. However, wild-type phages present significant clinical limitations due to their narrow host ranges, susceptibility to rapid immune clearance and poor penetration of bacterial biofilms, which severely restrict their therapeutic applications. The convergence of synthetic biology, nanotechnology and advanced gene editing technologies has accelerated the development of engineered bacteriophage platforms, providing programmable, scalable and clinically translatable pathways to overcome these inherent biological constraints. Here, we systematically delineate four fundamental strategies for engineered bacteriophage development. Chemical modification utilizes reactive functional groups such as amino, carboxyl and thiol moieties on capsid proteins through esterification, amidation or click chemistry reactions to achieve precise drug conjugation and surface functionalization. In vivo editing encompasses ultraviolet or chemical mutagenesis for random mutation induction, homologous recombination for targeted genetic alterations, recombineering methodologies including electroporation-mediated bacteriophage recombination engineering, and CRISPR-Cas systems for precise genome editing to enable exact genetic reconstruction and host range reprogramming. In vitro synthesis leverages genome engineering platforms where intact phage genomes are transferred into yeast or host bacteria to facilitate highly efficient homologous recombination, enabling large DNA fragment assembly and cross-gene host range expansion without bacterial toxicity constraints. Directed evolution combines artificial selection through mutation library screening with rational design approaches involving chimeric receptor binding protein construction or site-specific mutagenesis, effectively balancing the discovery of unknown adaptive pathways with targeted host specificity modification. Moreover, we comprehensively discuss therapeutic applications across diverse clinical scenarios. Engineered bacteriophage effectively disrupt bacterial biofilms through sophisticated functionalized delivery platforms including nanozyme-conjugated phages, phage-liposome nanoconjugates and bio-responsive hydrogels, demonstrating significantly enhanced bactericidal efficiency compared to unmodified free phages. These bioengineered vectors attenuate bacterial virulence and resensitize pathogens to antibiotics by delivering CRISPR-Cas systems or base editors to disrupt critical virulence factors such as pili, capsule synthesis machineries and quorum sensing systems, or by inactivating antibiotic resistance determinants including beta-lactamase genes. As an intelligent nanomedicine delivery platform, engineered bacteriophage enable precise pathogen elimination an through photocatalytic reactive oxygen species generation, immunomodulatory interventions, or controlled release of antibacterial drugs. Furthermore, oral administration of engineered bacteriophage facilitates microbiota modulation, which selectively eliminate intestinal pathogens while preserve beneficial commensal microbiota, thereby restoring microbial community balance and preventing complications associated with dysbiosis. Finally, we critically analyze persistent challenges including host strain matching complexity, evolution of bacterial resistance mechanisms, pharmacokinetic optimization requirements, optimal administration route selection, large-scale production quality control standards and clinical dosing determination protocols. Through multidisciplinary integration of synthetic biology, infectious disease medicine and immunology, future translational medicine studies of bacteriophage should establish comprehensive technical platforms encompassing rapid phage screening, intelligent rational design, rigorous in vivo evaluation and standardized clinical validation processes, ultimately advancing engineered bacteriophage from laboratory innovations to clinically approved therapeutics for effectively combating MDR bacterial infections.

Objective To analyze the overall characteristics, research hotspots, and development trends of immune cell-related studies in radiotherapy for rectal cancer. Methods A systematic search was conducted by using Web of Science Core Collection to retrieve articles related to radiation therapy and immune cells in rectal cancer published from 1991 to 2024. Advanced bibliometric tools, such as VOSviewer and CiteSpace, were utilized to facilitate analysis and describe publication trends, geographic contributions, institutional affiliations, journal prominence, author collaboration, and prominent keywords. Results The annual number of relevant publications has increased steadily, showing remarkable growth over the past five years. Studies focusing on adaptive immune cells (T and B cells) account for the largest proportion of works and form the most extensive collaboration networks, reflecting the central role of T cell–mediated antitumor immunity in radiotherapy. Meanwhile, innate immune cells, including myeloid-derived suppressor cells, macrophages, monocytes, and neutrophils, are increasingly investigated for their regulatory roles in shaping the tumor immune microenvironment and influencing therapeutic responses. Among countries, China and the United States have contributed the highest number of publications and demonstrated strong academic influence. While several stable research groups have been formed, intergroup collaboration remains limited. Keyword analysis revealed that radiotherapy-induced immune modulation, tumor immune microenvironment remodeling, and treatment response have emerged as major research hotspots. Conclusion Research on immune cells in rectal cancer radiotherapy has progressed rapidly in recent years. The emphasis of this field has gradually shifted from single-treatment approaches to mechanistic studies investigating the interaction between radiotherapy and the tumor immune microenvironment. The field still demonstrates considerable potential for future research and clinical translational applications.

Objective To explore the potential causal relationship between occupational pneumoconiosis (hereinafter referred to as "pneumoconiosis") and five mental disorders (depression, bipolar disorder, schizophrenia, insomnia and anxiety) using the two-sample Mendelian randomization (MR) method. Methods Single nucleotide polymorphisms (SNPs) loci associated with pneumoconiosis and five mental disorders were screened from Genome-Wide Association Studies. Inverse variance weighting (IVW), weighted median (WM) and MR-Egger regression methods were used to evaluate the significance of the causal relationship between pneumoconiosis and five mental disorders. Sensitivity analysis was used to evaluate the accuracy and reliability of the research results. Results After matching data of pneumoconiosis and the five mental disorders, 16 SNPs were ultimately included as instrumental variables in this study. The result of MR analysis revealed a positive causal relationship between pneumoconiosis and both depression [IVW: odds ratio (OR) and 95% confidence interval (CI) was 1.017 (1.000-1.035), P<0.05] and bipolar disorder [IVW: OR(95%CI)was 1.046(1.009-1.083), P<0.05; WM: OR (95%CI) was 1.055(1.007-1.105), P<0.05]. Result of sensitivity analysis indicated there was no heterogeneity and horizontal pleiotropy in the above results. There was no causal association observed between pneumoconiosis and schizophrenia, insomnia, or anxiety disorders (all P>0.05). Conclusion This study provides genetic evidence supporting a positive causal relationship between pneumoconiosis and both depression and bipolar disorder.

OBJECTIVE: The aim of this study is to analyze the clinical features and genetic etiology of a patient with multiple morphological abnormalities of the sperm flagella (MMAF) retrospectively. METHODS: A severely oligospermic patient from the Reproductive Center of the First Affiliated Hospital of Ningbo University was selected as the study subject. Clinical data and examination results were collected. High-throughput sequencing and bioinformatics were used to analyze the genetic etiology. And Sanger sequencing was employed to validate findings in the family. Transmission electron microscopy (TEM) was used to observe the sperm ultrastructure, and immunofluorescence analysis was performed to examine the localization of FSIP2 protein in the sperm. RESULTS: The patient presented with severe oligospermia, and sperm morphology displayed MMAF. TEM revealed fibrous sheath and 9+2 microtubule structural disruptions in the sperm. Sequencing identified compound heterozygous variants in the FSIP2 gene (c.17798C > T, c.5927T > G), inherited from the father and mother, respectively. According to the guidelines of the American College of Medical Genetics and Genomics, the variants were classified as pathogenic. The patient's spouse underwent intracytoplasmic single sperm injection, resulting in one embryo, but no clinical pregnancy occurred after embryo transfer. CONCLUSION This study reported the mutation of FSIP2 gene c.17798C > T, c.5927T > G in a patient with MMAF. These findings expand the mutational spectrum of the FSIP2 gene and provide insights for genetic and assisted reproductive counseling for patients with MMAF.
Humans ; Male ; Sperm Tail/pathology* ; Heterozygote ; Oligospermia/genetics* ; Spermatozoa ; Mutation ; Infertility, Male/genetics* ; Adult ; Pedigree ; Retrospective Studies ; Sperm Injections, Intracytoplasmic

OBJECTIVE: To illustrate the role of dehydrocorydaline (DHC) in chronic constriction injury (CCI)-induced neuropathic pain and the underlying mechanism. METHODS: C57BL/6J mice were randomly divided into 3 groups by using a random number table, including sham group (sham operation), CCI group [intrathecal injection of 10% dimethyl sulfoxide (DMSO)], and CCI+DHC group (intrathecal injection of DHC), 8 mice in each group. A CCI mouse model was conducted to induce neuropathic pain through ligating the right common sciatic nerve. On day 14 after CCI modeling or sham operation, mice were intrathecal injected with 5 µL of 10% DMSO or 10 mg/kg DHC (5 µL) into the 5th to 6th lumbar intervertebral space (L5-L6). Pregnant ICR mice were sacrificed for isolating primary spinal neurons on day 14 of embryo development for in vitro experiment. Pain behaviors were evaluated by measuring the paw withdrawal mechanical threshold (PWMT) of mice. Immunofluorescence was used to observe the activation of astrocytes and microglia in mouse spinal cord. Protein expressions of inducible nitric oxide synthase (iNOS), tumor necrosis factor alpha (TNF-α), interleukin 6 (IL-6), phosphorylation of N-methyl-D-aspartate receptor subunit 2B (p-NR2B), and NR2B in the spinal cord or primary spinal neurons were detected by Western blot. RESULTS: In CCI-induced neuropathic pain model, mice presented significantly decreased PWMT, activation of glial cells, overexpressions of iNOS, TNF-α, IL-6, and higher p-NR2B/NR2B ratio in the spinal cord (P<0.05 or P<0.01), which were all reversed by a single intrathecal injection of DHC (P<0.05 or P<0.01). The p-NR2B/NR2B ratio in primary spinal neurons were also inhibited after DHC treatment (P<0.05). CONCLUSION An intrathecal injection of DHC relieved CCI-induced neuropathic pain in mice by inhibiting the neuroinflammation and neuron hyperactivity.
Animals ; Neuralgia/etiology* ; Mice, Inbred C57BL ; Analgesics/pharmacology* ; Neuroinflammatory Diseases/pathology* ; Constriction ; Male ; Receptors, N-Methyl-D-Aspartate/metabolism* ; Nitric Oxide Synthase Type II/metabolism* ; Mice, Inbred ICR ; Microglia/pathology* ; Spinal Cord/drug effects* ; Female ; Mice ; Tumor Necrosis Factor-alpha/metabolism* ; Disease Models, Animal ; Constriction, Pathologic/complications* ; Interleukin-6/metabolism* ; Astrocytes/metabolism* ; Chronic Disease ; Neurons/metabolism*

Eightly-four novel thioheterocyclic nucleoside derivatives were designed, synthesized, and evaluated for antitumor activity in vitro and in vivo. Most of the compounds inhibited the growth of HCT116 and HeLa cancer cells in vitro, among them 33a and 36b exhibited potent activity against HCT116 cells (IC₅₀ = 0.27 and 0.49 μmol/L, respectively). Both compounds 33a and 36b inhibited cell metastasis, arrested the cell cycle in the G₂/M phase, and induced apoptosis in vitro. Mechanistic studies revealed that 33a and 36b increased ROS levels, led to DNA damage, ER stress, and mitochondrial dysfunction, and inhibited autophagy in HCT116 cells. Biological information analysis, RNA-sequencing, Gene Set Enrichment Analysis (GSEA), drug affinity responsive target stability (DARTS) assay, cellular thermal shift assay (CETSA), and SPR experiments identified that compounds 33a and 36b showed antitumor activity by suppressing the c-MYC pathway. c-MYC silencing assays indicated that c-MYC proteins participated in 33a-mediated anticancer activities in HCT116 cells. More importantly, compound 33a presented favorable pharmacokinetic properties in mice (T _1/2 = 6.8 h) and showed significant antitumor efficacy in vivo without obvious toxicity, showing promising potential for further clinical development.