BACKGROUND:Although previous studies have reported associations between lipids and the risk of osteoporotic pathological fractures,the specific causal relationships between lipid level and osteoporotic pathological fractures remain unclear.OBJECTIVE:To elucidate the causal relationship between lipids and osteoporotic pathological fractures using a two-sample bidirectional Mendelian randomization analysis.METHODS:The data for 178 lipid metabolites were obtained from the IEU-GWAS database(developed by the MRC Integrative Epidemiology Unit at the University of Bristol,UK,which provides extensive summary data from genome-wide association studies),while osteoporotic pathological fracture data(from 173 619 European participants)were acquired from the FinnGen database(constructed by the Finnish national gene research program,focusing on investigating relationships between genomics and health/disease in the Finnish population).Osteoporotic pathological fracture data were used as the outcome variable,with lipids serving as exposures,for the bidirectional Mendelian randomization study to evaluate the causal effects of different lipids on osteoporotic pathological fractures.The UK Biobank database was employed as a validation set by switching the outcome variable to verify the findings horizontally.RESULTS AND CONCLUSION:(1)The inverse variance weighted analysis indicated that each unit increase in sterol ester(27∶1/20∶2)levels was associated with a 25.55％increase in the risk of osteoporotic pathological fractures(odds ratio=1.256,95％confidence interval:1.001-1.575,P=0.049),suggesting a significant positive correlation between elevated sterol ester levels and increased fracture risk.Reverse Mendelian randomization analysis revealed a significant negative association between osteoporotic pathological fractures and three types of phosphatidylcholine.Horizontal validation yielded consistent results,confirming sterol ester as a risk factor for osteoporotic pathological fractures.(2)The results indicate that sterol ester is a risk factor for osteoporotic pathological fractures,while phosphatidylcholine serves as a protective factor.These findings strengthen the evidence supporting the effect of lipids on the risk of osteoporotic pathological fractures.Although the GWAS data used in this study were derived from European populations,given the broad commonality of human genetics,the results provide valuable reference significance for improving osteoporosis in Chinese populations through lipid regulation.

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.

BACKGROUND:Although previous studies have reported associations between lipids and the risk of osteoporotic pathological fractures,the specific causal relationships between lipid level and osteoporotic pathological fractures remain unclear.OBJECTIVE:To elucidate the causal relationship between lipids and osteoporotic pathological fractures using a two-sample bidirectional Mendelian randomization analysis.METHODS:The data for 178 lipid metabolites were obtained from the IEU-GWAS database(developed by the MRC Integrative Epidemiology Unit at the University of Bristol,UK,which provides extensive summary data from genome-wide association studies),while osteoporotic pathological fracture data(from 173 619 European participants)were acquired from the FinnGen database(constructed by the Finnish national gene research program,focusing on investigating relationships between genomics and health/disease in the Finnish population).Osteoporotic pathological fracture data were used as the outcome variable,with lipids serving as exposures,for the bidirectional Mendelian randomization study to evaluate the causal effects of different lipids on osteoporotic pathological fractures.The UK Biobank database was employed as a validation set by switching the outcome variable to verify the findings horizontally.RESULTS AND CONCLUSION:(1)The inverse variance weighted analysis indicated that each unit increase in sterol ester(27∶1/20∶2)levels was associated with a 25.55％increase in the risk of osteoporotic pathological fractures(odds ratio=1.256,95％confidence interval:1.001-1.575,P=0.049),suggesting a significant positive correlation between elevated sterol ester levels and increased fracture risk.Reverse Mendelian randomization analysis revealed a significant negative association between osteoporotic pathological fractures and three types of phosphatidylcholine.Horizontal validation yielded consistent results,confirming sterol ester as a risk factor for osteoporotic pathological fractures.(2)The results indicate that sterol ester is a risk factor for osteoporotic pathological fractures,while phosphatidylcholine serves as a protective factor.These findings strengthen the evidence supporting the effect of lipids on the risk of osteoporotic pathological fractures.Although the GWAS data used in this study were derived from European populations,given the broad commonality of human genetics,the results provide valuable reference significance for improving osteoporosis in Chinese populations through lipid regulation.

ObjectiveTo analyze the research hotspots and development trends of brain-computer interface (BCI) in the treatment for spinal cord injury (SCI). MethodsRelevant literatures on BCI applied in SCI treatment, published from the inception of the Web of Science Core Collection to July, 2025, were retrieved. Visualization analysis was performed using CiteSpace, VOSviewer and Tableau Desktop. ResultsA total of 437 literatures were included, and the annual number of publications showed an overall increasing trend. The United States ranked first in the number of publications; Graz University of Technology was the institution with the highest number of publication; Gernot R Mueller-Putz was the most productive author, while Jonathan R Wolpaw was the most cited author. Brain-computer interface and artificial intelligence were identified as the high-frequency and bursting keywords in this field. The researches were characterized by the cross-integration of five core disciplines: neuroscience and rehabilitation medicine, biomedical engineering, computer science and artificial intelligence, neurophysiology, and materials science. ConclusionResearches on BCI in SCI treatment are accelerating continuously, and technological integration is becoming the core trend.

ObjectiveTo analyze the research hotspots and development trends of brain-computer interface (BCI) in the treatment for spinal cord injury (SCI). MethodsRelevant literatures on BCI applied in SCI treatment, published from the inception of the Web of Science Core Collection to July, 2025, were retrieved. Visualization analysis was performed using CiteSpace, VOSviewer and Tableau Desktop. ResultsA total of 437 literatures were included, and the annual number of publications showed an overall increasing trend. The United States ranked first in the number of publications; Graz University of Technology was the institution with the highest number of publication; Gernot R Mueller-Putz was the most productive author, while Jonathan R Wolpaw was the most cited author. Brain-computer interface and artificial intelligence were identified as the high-frequency and bursting keywords in this field. The researches were characterized by the cross-integration of five core disciplines: neuroscience and rehabilitation medicine, biomedical engineering, computer science and artificial intelligence, neurophysiology, and materials science. ConclusionResearches on BCI in SCI treatment are accelerating continuously, and technological integration is becoming the core trend.

ObjectiveTo analyze the epidemiological characteristics of 8 major respiratory pathogens in influenza-like illness (ILI) cases with acute respiratory infections at fever clinics in Huangpu District, Shanghai from 2015 to 2024, and to provide a scientific basis for the prevention and treatment of respiratory diseases. MethodsA retrospective study was conducted in Huangpu District. Individuals meeting the case definition of ILI from 2015 to 2024 was registered. Their nasopharyngeal swabs were collected for pathogen detection. A total of 8 respiratory viruses were tested, including Influenza A virus (Flu A), Influenza B virus (Flu B), adenovirus (ADV), enterovirus/human rhinovirus (EV/HRV), human parainfluenza virus (HPIV), human coronavirus (HCoV), respiratory syncytial virus (RSV), and human metapneumovirus (HMPV). ResultsFrom 2015 to 2019, a total of 344 ILI cases were tested, of which 192 out of 344 cases (55.81%) were tested positive for single respiratory pathogen. From 2023 to 2024, 1 557 ILI cases were tested, with 572 out of 1 557 cases (36.74%) being positive for single pathogen. From 2023 to 2024, the positive rate of single pathogen in ILI cases was significantly lower than that in 2015‒2019 (χ²=42.66, P<0.001). Specifically, the positive rate of Flu A (χ²=74.43, P<0.001) decreased, while that of HPIV (χ²=8.66, P=0.003) increased, both with statistically significant differences. According to the seasonal pattern, the epidemic intensity of Flu A decreased in summer, while that of HPIV increased in summer and autumn. Demographic results showed statistically significant differences in the positive rates of EV/HRV between genders (χ²=22.38, P<0.001), with males exhibiting a higher positive rate than females. No statistically significant differences were identified in the positive rates of single pathogen among different age groups (χ²=4.42, P=0.110). Nevertheless, statistically significant differences were noted when comparing the positive rates of EV/HRV, Flu A, Flu B and HPIV across different age groups (P<0.05). EV/HRV was more commonly detected in the 15‒<25 age group (10.93%), while Flu A and HPIV had the highest positive rates in the ≥60 age group (21.24% and 4.77%). Flu B had the highest positive rate in the 25‒<60 age group (11.26%). 52.63% of cases with co-infections occurred during winter, with the primary pathogens involved being EV/HRV (9 cases) and HCoV (6 cases). The most prevalent combination of co-infection was Flu A with EV/HRV. ConclusionThe prevalence of respiratory pathogens among ILI cases from 2023 to 2024 exhibited notable fluctuations compared to that from 2015 to 2019. Therefore, influenza surveillance should be strengthened, and attention should also be paid to the prevalence of respiratory pathogens such as HPIV. These findings have profound implications for future research, surveillance, vaccine planning, and public health policy making.

ObjectiveTo investigate the risk factors for bleeding within 5 days and 2 weeks after endoscopic variceal ligation （EVL） or endoscopic cyanoacrylate injection （ECI） for the treatment of esophagogastric varices in patients with liver cirrhosis， as well as the safety of EVL/ECI in patients with thrombocytopenia. MethodsA total of 489 patients with liver cirrhosis and esophagogastric varices who underwent EVL/ECI in Guangzhou Eighth People’s Hospital， Guangzhou Medical University， from January 2018 to December 2023 were enrolled as subjects， and according to the presence or absence of bleeding after surgery， they were divided into bleeding group and non-bleeding group. The risk factors for bleeding within 5 days and 2 weeks after surgery were analyzed. The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between groups， and the chi-square test or the continuity-corrected chi-square test was used for comparison of categorical data between groups； the receiver operating characteristic （ROC） curve was plotted to determine the cut-off value of MELD score； a multivariate logistic regression analysis was used to identify the independent risk factors for postoperative bleeding. ResultsThere were no significant differences in the bleeding rates within 5 days and 2 weeks after EVL/ECI between the 386 patients with a platelet count of ≥50×10⁹/L and the 103 patients with a platelet count of （25 — 49）×10⁹/L （5 days： 1.94% vs 2.85%， P=0.870； 2 weeks： 2.91% vs 4.92%， P=0.544）. The overall bleeding rate was 2.66% （13/489） and 4.50% （22/489）， respectively， within 5 days and 2 weeks after EVL/ECI. The multivariate logistic regression analysis showed that MELD score was an independent risk factor for bleeding within 5 days （odds ratio ［OR］=3.726， 95% confidence interval ［CI］： 1.214 — 11.429， P=0.021） and 2 weeks （OR=5.760， 95%CI： 1.779 — 18.651， P=0.003） after EVL/ECI， while hemoglobin （Hb） was a protective factor against bleeding within 5 days （OR=0.972， 95%CI： 0.948 — 0.996， P=0.025） and 2 weeks （OR=0.976， 95%CI： 0.957 — 0.995， P=0.016） after surgery； portal vein tumor thrombus （OR=2.667， 95%CI： 1.000 — 7.117， P=0.050） was an independent risk factor for bleeding within 2 weeks after surgery， while platelet count ［（25 — 49）×10⁹/L］ was not a risk factor for postoperative bleeding （P>0.05）. ConclusionBoth EVL and ECI have good safety in patients with liver diseases and grade 3 thrombocytopenia. MELD score is an independent risk factor for bleeding within 5 days and 2 weeks after EVL/ECI， while Hb is a protective factor； portal vein tumor thrombus is an independent risk factor for bleeding within 2 weeks after surgery.

ObjectiveTo analyze the research hotspots and development trends of brain-computer interface (BCI) in the treatment for spinal cord injury (SCI). MethodsRelevant literatures on BCI applied in SCI treatment, published from the inception of the Web of Science Core Collection to July, 2025, were retrieved. Visualization analysis was performed using CiteSpace, VOSviewer and Tableau Desktop. ResultsA total of 437 literatures were included, and the annual number of publications showed an overall increasing trend. The United States ranked first in the number of publications; Graz University of Technology was the institution with the highest number of publication; Gernot R Mueller-Putz was the most productive author, while Jonathan R Wolpaw was the most cited author. Brain-computer interface and artificial intelligence were identified as the high-frequency and bursting keywords in this field. The researches were characterized by the cross-integration of five core disciplines: neuroscience and rehabilitation medicine, biomedical engineering, computer science and artificial intelligence, neurophysiology, and materials science. ConclusionResearches on BCI in SCI treatment are accelerating continuously, and technological integration is becoming the core trend.

OBJECTIVE: To analyze the clinical characteristics, treatment, and prognosis of seven pediatric patients with Acute myeloid leukemia (AML) positive for the t(16;21)(p11;q22) FUS::ERG fusion gene. METHODS: A retrospective analysis was carried out on the clinical data, treatment, and prognosis of seven AML patients with t(16;21)(p11;q22) FUS::ERG fusion gene admitted to Henan Children's Hospital between June 2015 and November 2024. Relevant literature was also reviewed. This study was approved by the Medical Ethics Committee of the Hospital (Ethics No.: 2024-102-001). RESULTS: Among 297 pediatric patients with AML, 7 cases (2.36%) were positive for the t(16;21)(p11;q22) FUS::ERG fusion gene, including 3 males and 4 females, with a median age of 11 years (range: 3 ~ 12 years). According to the FAB classification, these included 1 case of M2, 3 cases of M5, and 3 cases of AML-not otherwise specified (non-M3). All 7 patients were found to harbor the t(16;21)(p11;q22) translocation, with 3 cases showing additional chromosomal abnormalities. Immunophenotyping revealed universal expression of CD13, CD33, CD34, and CD117, with partial expression of CD56, CD4, CD64, CD123, CD15, CD38, CD11b, HLA-DR, cMPO, and CD16. One patient achieved complete remission (CR) after the first course of DAE (cytarabine + daunorubicin + etoposide) induction chemotherapy but relapsed and discontinued the treatment. Six patients received DAH (cytarabine + daunorubicin + homoharringtonine) induction therapy, of whom 2 achieved CR after two courses and underwent allogeneic hematopoietic stem cell transplantation (allo-HSCT), resulting in an overall CR rate of 42.86%. Five children did not receive allo-HSCT and had a median overall survival of 9 months (range: 6 ~ 18 months). Two children who underwent transplantation achieved bone marrow morphological and molecular biological relapse at 6 and 9 months post-transplantation, respectively. After receiving combined chemotherapy and donor lymphocyte infusion, one child failed to achieve remission and died at 22 months post-transplantation, while the other has been followed up to date with positive fusion gene status. Their overall survival was 25 months and 30 months, respectively. CONCLUSION The t(16;21)(p11;q22) FUS::ERG fusion gene is rare in pediatric AML and associated with poor prognosis. Allo-HSCT may mitigate the adverse prognostic impact of the FUS::ERG fusion gene and contribute to prolonged survival.
Humans ; Male ; Child ; Female ; Leukemia, Myeloid, Acute/drug therapy* ; Oncogene Proteins, Fusion/genetics* ; Translocation, Genetic ; Retrospective Studies ; RNA-Binding Protein FUS/genetics* ; Chromosomes, Human, Pair 16/genetics* ; Adolescent ; Child, Preschool ; Chromosomes, Human, Pair 21/genetics* ; Prognosis ; Treatment Outcome