OBJECTIVE:Disorders in iron metabolism increase the risk of type 2 diabetes mellitus.Hepcidin play an important role in maintaining iron homeostasis in the body,but its level increases with increased inflammation.Changes in hepcidin and iron homeostasis and the extent of their association with inflammation in people with and without type 2 diabetes mellitus are unknown.Meta-analysis was used to evaluate the effect of inflammation on serum hepcidin and iron metabolism related parameters in patients with type 2 diabetes mellitus.METHODS:CNKI,PubMed,Web of Science and EBSCOhost databases were searched by computer to collect observational studies related to inflammatory index and hepcidin in patients with type 2 diabetes mellitus.The search time was from September 1,2000 to September 30,2024.Three researchers independently screened the literature,extracted data and evaluated the quality of the included literature.Meta-analysis was performed by Review Manager 5.3,Stata 17.0 and GraphPad Prism 8.0.2 software.RESULTS:A total of 15 articles(17 studies)involving 3 159 participants,including 1 357 patients with type 2 diabetes mellitus,were included.Meta-analysis results showed that compared with the control group,patients with type 2 diabetes mellitus had higher levels of serum hepcidin[standardized mean difference(SMD)=0.35,95％confidence interval(CI)(0.05,0.65),P＜0.05],serum ferritin(SMD=0.49,95％CI(0.21,0.78),P＜0.01)and serum transferrin(SMD=0.19,95％CI(0.00,0.37),P＜0.05).Subgroup analysis results indicated that inflammation had a significant effect on serum hepcidin(SMD=0.76,95％CI(0.17,1.34),P＜0.05)and serum ferritin(SMD=0.77,95％CI(0.06,1.47),P＜0.05)in patients with type 2 diabetes mellitus.CONCLUSION:Hepcidin concentration is positively correlated with type 2 diabetes mellitus.Inflammation is one of the risk factors of type 2 diabetes mellitus.Early prevention of inflammation has certain significance in preventing iron metabolism disorder in patients with type 2 diabetes mellitus.

IgA nephropathy (IgAN) is the most common primary glomerulonephritis worldwide and a major cause of chronic kidney disease and kidney failure. IgAN exhibits marked heterogeneity in clinical presentation, histopathology, and pathogenic mechanisms, contributing to variable treatment responses and prognosisamong patients. Precise risk assessment and individualized intervention are therefore of critical importance. This review systematically traces the evolution of IgAN management from traditional risk stratification toward biomarker-driven precision medicine. We first review the clinical utility and limitations of established risk stratification tools, including the KDIGO guidelines, the Oxford MEST-C classification, and the International IgAN Prediction Tool. We then discuss emerging biomarkers closely linked to disease pathogenesis, including galactose-deficient IgA1 (Gd-IgA1), anti-Gd-IgA1 autoantibodies, B cell activating factor (BAFF), a proliferation-inducing ligand (APRIL), and complement components, as well as the targeted therapies they have informed. In addition, urinary biomarkers and multi-omics approaches show promise for dynamic disease monitoring and individualized risk stratification.

OBJECTIVE To analyze the impact of the diagnosis-related groups （DRG） payment reform on the length of stay and medical costs in patients with chronic obstructive pulmonary disease （COPD） in Kashgar region， aiming to provide localized empirical evidence for the optimization of regional medical insurance payment methods. METHODS Based on the inpatient settlement database of the Xinjiang Uygur Autonomous Region Healthcare Security Administration， settlement data of COPD inpatients from 17 medical institutions in Kashgar region between January 1， 2022， and December 31， 2024， were extracted. The overall changes in patients’ length of stay and costs were compared before and after the reform. Subsequently， interrupted time series analysis （ITSA） was employed to explore the impact of the DRG payment reform on these variables. RESULTS Following the reform， both the average length of stay and various cost decreased significantly compared to the pre-reform period （ P ＜0.001）. At the overall sample level， the average length of stay， average total cost， average drug cost， average medical service cost， and average examination cost per admission all demonstrated significant long-term downward trends after the reform （ P ＜0.05）. However， the decrease in average out-of-pocket costs and the increase in average consumable costs per admission were not statistically significant （ P ＞0.05）. In tertiary medical institutions， the average length of stay and all categories of costs （except average consumable costs per admission） exhibited significant long-term upward trends after the reform （ P ＜0.05）； conversely， in secondary and lower-level medical institutions， the average length of stay， average total cost， average drug cost， average medical service cost， and average examination cost per admission showed significant long-term downward trends （ P ＜0.05）. CONCLUSIONS The DRG payment reform has achieved an overall effect of reducing the length of stay and controlling costs in COPD patients from Kashgar region. However， the effects vary across different levels of medical institutions： secondary and lower-level institutions show a long-term downward trend in length of stay and costs， whereas tertiary institutions exhibit a long-term upward trend. Furthermore， patients’ out-of-pocket financial burden does not show significant improvement.

OBJECTIVE To provide reference for medical institutions to establish the record management mode and review rules of off-label use of 5-aminolevulinic acid （ALA） in photodynamic therapy based on the level of evidence. METHODS All ALA-containing outpatient prescriptions in the rational drug use system in our hospital from January 1， 2024 to December 31， 2025 were retrospectively collected. Based on the drug instructions， the current status of off-label use of ALA in photodynamic therapy was identified . The relevant studies in Micromedex， PubMed， CNKI， Wanfang Data and other databases were systematically searched as the relevant evidence-based evidence of ALA off-label use. According to the Off-label Drug Use Filing Standard of the hospital，the evidence-based evaluation method was used to evaluate the evidence-based evidence of ALA off-label use and carry out hierarchical management. RESULTS A total of 1 803 effective prescriptions were included， of which 676 （37.49%） were off-label use， distributed in the dermatology department （564 prescriptions，83.43%） and the plastic surgery department （112 prescriptions，16.57%）. All 676 prescriptions were off-indications medication， involving ten types of skin diseases， primarily including moderate to severe acne （39.94%）， skin warts （25.44%）， Bowen’s disease （11.98%）， and others. According to evidence-based evidence，off-label uses such as moderate to severe acne， actinic keratosis， and Bowen’s disease were managed according to the evidence categoryⅠ orⅡ.The uses of extramammary Paget’s disease and rosacea were managed according to the evidence category Ⅲ.The uses of lichen sclerosus and keloids were managed according to the evidence category Ⅳ.The results of evidence-based evaluation showed that 92.01% of off-label use in our hospital had high-level evidence-based support （ evidence category was gradeⅠ-Ⅱ）. CONCLUSIONS Off-label uses supported by high-level evidence， such as moderate to severe acne， skin warts， and Bowen’s disease， can be managed under filing category Ⅰ or Ⅱ. For the use of lichen sclerosus and keloids， evidence-based evidence is insufficient and should be strictly restricted.The vast majority of ALA off-label use in our hospital has sufficient evidence-based basis.

ObjectiveThis study aims to compare the modeling effects of submaxillary gland antigen and salivary gland antigen in the establishment of Sjögren syndrome (SS) mouse models, and to characterize the phenotypic and immunological features of these models in comparison with spontaneous SS-prone non-obese diabetic (NOD)/LtJ mice. MethodsAdult C57BL/6J mice (equal numbers of males and females) were immunized with submaxillary gland antigen or salivary gland antigen, respectively, combined with Freund's adjuvant to induce SS models. Mice immunized with phosphate-buffered saline (PBS) combined with Freund's adjuvant served as the control group. Immunization was induced via multiple subcutaneous injections in the back with antigen combined with Freund's complete adjuvant (FCA) on Days 1 and 7. A booster immunization was administered via multiple subcutaneous injections in the back with antigen combined with Freund's incomplete adjuvant (FIA) on Day 14. Female NOD/LtJ mice were used as the spontaneous SS model group, with ICR mice as the corresponding control strain for comparative analysis. Body weight, water intake, and salivary flow rate of mice were dynamically monitored for 4 weeks. At the end of the experiment, tissue and serum samples were collected, the weights of submaxillary glands, thymus, and spleen were measured, and organ indices (organ-to-body weight ratios) were calculated. Pathological morphological analysis of the submaxillary gland and spleen was performed with hematoxylin and eosin (HE) staining. Serum interleukin-17 (IL-17) level was detected using enzyme-linked immunosorbent assay (ELISA). Real-time quantitative polymerase chain reaction was used to detect the mRNA expression levels of SS type A (SSA) and SS type B (SSB) in submaxillary gland tissues. ResultsFemale mice in the submaxillary gland antigen group exhibited significantly increased water intake (P<0.05) and reduced salivary flow rate (P<0.05) compared with the female control group. No statistically significant differences were observed in the submaxillary gland index, thymus index and spleen index (P>0.05). Focal lymphocytic infiltration was observed in the submaxillary glands, and the splenic marginal zone was enlarged. Serum IL-17 levels were significantly increased (P<0.05). There was no significant difference in submaxillary gland SSA/SSB expression levels (P>0.05). Compared with the female control group, female mice in the salivary gland antigen group showed no statistically significant differences in water intake, salivary flow rate, submaxillary gland index, and spleen index (P>0.05), whereas the thymus index was significantly reduced (P<0.01). Mild inflammatory cell infiltration and glandular atrophy were observed in the submaxillary glands, and the splenic white pulp and marginal zone were slightly enlarged. Serum IL-17 levels and submaxillary gland SSB mRNA expression levels were significantly increased (P<0.01), whereas no significant change was observed in submaxillary gland SSA expression levels (P>0.05). Compared with the male control group, mild submaxillary gland atrophy was observed in male mice in the submaxillary gland antigen group, whereas no obvious changes were found in other modeling-related indicators (P>0.05). Compared with the ICR control group, NOD/LtJ model mice exhibited elevated water intake (P<0.05), significantly reduced salivary flow rate (P<0.01), no significant differences in the submaxillary gland index or spleen index (P>0.05), but a significantly increased thymus index (P<0.05). Marked focal infiltration was observed in the submaxillary glands, the splenic marginal zone was obviously enlarged, and serum IL-17 concentrations as well as submaxillary gland SSA/SSB expression levels were significantly increased (P<0.05). ConclusionSubmaxillary gland antigen and salivary gland antigen can induce SS-related features in female C57BL/6J mice. The SS-related phenotype is more pronounced in the submaxillary gland antigen group than in the salivary gland antigen group, but weaker than that in spontaneously SS-prone female NOD/LtJ mice. Immunization of male C57BL/6J mice with submaxillary or salivary gland antigens fails to induce an obvious SS phenotype.

OBJECTIVE: To develop a user-friendly visualization application for the automatic annotation of Human Phenotype Ontology (HPO) terms based on large language models and retrieval-augmented generation (RAG) technology, and to validate its performance in an authoritative case dataset. METHODS: By integrating the domestic open-source large language model DeepSeek-V3 with RAG technology, an interactive web application was deployed on the Streamlit cloud platform. Using only the latest official HPO dataset as the data source, the lightweight sentence-embedding model BAAI/bge-small-en-v1.5 was employed to construct a FAISS vector index. During the online phase, a four-step closed-loop process is automatically completed: multilingual translation, phenotype phrase extraction, RAG candidate retrieval, term mapping, and official database validation. 121 English case reports publicly released by BMJ Case Reports and Oxford Medical Case Reports (with a gold-standard HPO set of 1 794 terms) were selected for application validation. Precision, recall, and F1 score were calculated and compared horizontally with traditional dictionary tools, standalone large language models, and the similar application "RAG-HPO". Finally, replace the model with the more advanced ChatGPT-5 and evaluate its performance on the newly extracted dataset. RESULTS: An HPO term automatic annotation visualization application named PhenoRAG, based on large language models and RAG technology, was successfully developed. Users can access it directly via a web link. Across the 112 cases, a total of 2 150 HPO terms were generated; 2,064 (96.0%) were fully validated by the official database, with a hallucination rate of 1.3% and an HPO ID-name mismatch rate of 2.7%. After deduplication, 1,906 terms remained for testing. The overall precision was 63.65%, recall was 67.34%, and F1 was 65.44%, significantly outperforming traditional annotation tools (F1: 0.45-0.49, P < 0.001). Although PhenoRAG's F1 was lower than that of RAG-HPO (F1 = 0.78, P < 0.001), which relies on a manually constructed synonym database of 54 000 entries plus the HPO dataset, it requires no additional dictionary maintenance and can be used without any background in computer programming. Moreover, after switching to the GPT-5 model, PhenoRAG exhibited no hallucination rate on the new dataset, and its F1 score significantly increased (P = 0.038). CONCLUSION Without constructing a synonym database, the PhenoRAG achieved high-accuracy automatic mapping from clinical text to standard HPO terms. It features a low usage threshold, free access, and a Chinese-language interface, and can directly serve rare disease diagnosis, genetic counseling, and research scenarios in China and worldwide, warranting further clinical promotion and multicenter validation.
Humans ; Phenotype ; Biological Ontologies ; Language ; Software ; Large Language Models

OBJECTIVE: To analyze the functional impact of a rare heterozygous variant of SOS1 gene (c.283G>A, p.E95K) identified in a fetus with cervical cystic hygroma and to explore its association with the disease phenotype. METHODS: A pedigree analysis was carried out to evaluate the co-segregation of the variant with the disease phenotype. Bioinformatic tools were employed to assess the conservation, protein structure and stability. Functional validation was conducted on HEK293T cells using fluorescence quantitative reverse transcription-PCR and Western blotting to measure the expression of SOS1 and phosphorylation levels of extracellular regulated protein kinases (ERK) and c-Jun N-terminal kinase. A literature review of previously reported disease-associated SOS1 variants was also carried out. This study has been approved by the Medical Ethics Committee of West China Second University Hospital, Sichuan University (Ethics No.: 201940). RESULTS: The variant was inherited from the husband of the woman with distinctive facial features and has co-segregated with the phenotype. Bioinformatics analysis indicated that the variant is located in a highly conserved region, and that p.E95K could disrupt key amino acid interactions and protein stability. Multiple bioinformatic predictions consistently suggested the pathogenicity of this variant. Functional assays demonstrated reduced SOS1 protein expression and decreased ERK phosphorylation. CONCLUSION This study has revealed the functional impact of the SOS1 c.283G>A (p.E95K) variant, suggesting that it may contribute to the developmental phenotypes through a haploinsufficiency mechanism.
Humans ; SOS1 Protein/chemistry* ; Female ; HEK293 Cells ; Male ; Pedigree ; Phenotype ; Adult

Vascular endothelial growth factor (VEGF) inhibitors are drugs that target and inhibit tumor angiogenesis. By blocking the signaling pathway of VEGF and its receptor, they suppress tumor proliferation and play a crucial role in tumor treatment. However, their side effects, such as hypertension, proteinuria, hand-foot skin reactions, and myelosuppression, during treatment seriously affect patients' treatment compliance and quality of life. The development of intervention strategies for the side effects of VEGF inhibitors is of great importance for tumor treatment. This article reviews the clinical characteristics and toxic mechanisms of common side effects caused by VEGF inhibitors during tumor treatment and summarizes intervention strategies that combine traditional Chinese and Western medicines. Drug dosages were precisely monitored and adjusted to achieve antitumor treatment. Patients' discomfort symptoms are improved through prescriptions that act by tonifying qi and promoting blood circulation, strengthening the spleen, and tonifying the kidney. The combination of traditional Chinese and Western medicines is used to treat patients, thus providing a safe and effective treatment plan for patients with cancer.

ObjectiveTo delineate imaging findings using an imaging platform and investigate the correlation between MRI characteristics of spinal cord atrophy and clinical diagnosis in children with spinal cord injury (SCI). MethodsImaging data of 150 children with SCI admitted to Beijing Bo'ai Hospital, China Rehabilitation Research Center, from January, 2002 to March, 2024 were collected and imported into the imaging platform. The anteroposterior and transverse diameters of the middle part of the spinal cord at the cross-section with the most severe atrophy were measured, and the relevant indicators of the previous normal spinal cord segment were measured as controls; the radiomic features were extracted. Clinical data of the children including gender, age, cause of injury, sensory level, motor level, spinal cord injury level, injury severity and disease course were collected. ResultsSpinal cord atrophy was identified in 81 cases (54%), among which 78 cases (96%) were American Spinal Injury Association Impairment Scale (AIS) grade A and 3 cases (4%) were AIS grade C. The upper boundary of the spinal cord atrophy site strongly correlated with the injury level, motor level and sensory level (r > 0.8, P < 0.001). ConclusionMore than half of children with SCI may develop secondary spinal cord atrophy, the vast majority of whom suffer from complete spinal cord injury; the upper boundary of spinal cord atrophy is correlated with the injury level.

Optical microscopy is essential for exploring biological and material structures, with resolution determining the level of observable detail. The advent of super-resolution fluorescence microscopy has broken the diffraction limit, achieving nanoscale resolution. However, traditional assessment methods, such as the Rayleigh criterion and point spread function (PSF) width measurement, rely on empirical judgments and diffraction-limited models, rendering them inadequate for modern super-resolution imaging. This review systematically traces the evolution of resolution assessment methodologies, from classical criteria to advanced strategies tailored for various super-resolution modalities. We first discuss Fourier-based quantitative methods. Fourier ring correlation (FRC) and its 3D counterpart, Fourier shell correlation (FSC), objectively determine resolution by evaluating the statistical correlation of two independent image reconstructions in frequency space. These methods offer robustness against noise and provide a global resolution metric, but they require data independence and are computationally intensive. They have become the prevailing standards in electron and super-resolution microscopy. Subsequently, we examine adaptations for specific super-resolution techniques. For single-molecule localization microscopy (SMLM) techniques such as PALM and STORM, the Fourier image resolution (FIRE) method extends FRC by incorporating a physical model that accounts for localization precision and labeling density. For stimulated emission depletion (STED) microscopy and other nonlinear techniques, assessment strategies differ. While PSF shrinkage measurements using fluorescent beads are useful for system calibration, evaluating the effective resolution directly on biological samples is more practical. This is typically performed via linewidth analysis of known structures (e.g., microtubules) or edge-spread function measurements, capturing the effects of photobleaching and sample-induced aberrations. A major paradigm shift is parameter-free resolution estimation based on decorrelation analysis. This method analyzes the autocorrelation decay of a single image’s Fourier spectrum to identify the cutoff spatial frequency without requiring dual datasets or user-defined thresholds. Its high efficiency and broad applicability have been validated across widefield, confocal, STED, SIM, and SMLM modalities. Optimized rendering strategies for SMLM data further enhance its accuracy, and it is emerging as a tool for real-time optimization of experimental parameters. The review also addresses the “gold standard” of resolution validation using well-defined nanostructures, such as DNA origami and nuclear pore complexes, which provide ground truth for verifying resolution claims and detecting artifacts. In the era of artificial intelligence, deep learning plays a dual role: it powerfully enhances image resolution but also introduces challenges, as models may generate “hallucinations” or false details. This underscores the need for new validation metrics to verify the physical fidelity of AI-generated content. Finally, we outline future directions: developing unified cross-modality standards, enabling real-time dynamic resolution monitoring for live-cell imaging, creating techniques for generating local resolution maps to capture sample heterogeneity, and integrating intelligent error correction to ensure data veracity. By providing a comprehensive overview of resolution assessment progress and challenges, this review aims to equip researchers with the knowledge to select appropriate tools, thereby fostering rigorous quantitative imaging in the life and material sciences.