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

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

Objective To evaluate the clinical characteristics, diagnostic reasoning, and therapeutic strategies of prostatic paraganglioma (PPG) to provide an evidence-based foundation for early diagnosis and precision treatment of this rare malignancy. Methods The clinical data of a patient with PPG admitted to our hospital were retrospectively analyzed. Concurrently, a systematic search was conducted across domestic and international databases, including PubMed, CNKI, and Wanfang.Clinical manifestations, laboratory tests, pathological features, therapeutic modalities, and prognostic data of 24 cases reported between 1979 and 2025 were pooled with the institutional case for a comprehensive analysis (n=25). Results Epidemiological features: the age at onset ranged from 8 to 76 years, with a mean age of (44.6±15.2) years, predominantly affecting young and middle-aged adults (30-50 years).Notably, 20.0% (5/25) of the patients exhibited characteristic micturition-associated catecholamine release symptoms (e.g., post-micturition palpitations, transient hypertension).Laboratory findings: among the 19 patients who underwent catecholamine metabolite testing, 14 (73.7%) showed significant elevation in serum or urinary norepinephrine and methoxyadrenaline levels.Pathological and immunohistochemical features: the positivity rate for neuroendocrine markers (chromogranin A, synaptophysin, and neuron-specific enolase) was 100%, while the negativity rate for prostate-specific markers (prostate-specific antigen and prostate-specific acid phosphatase) was also 100%.Treatment and prognosis: surgical intervention was performed in 96.0% (24/25) of the patients, including radical prostatectomy (37.5%), precision tumor excision (25.0%), and transurethral resection (12.5%).Favorable outcomes without recurrence were observed in 89.5% (17/19) of the total cohort. Conclusion PPG is clinically exceedingly rare.The disease should be highly suspected in patients presenting with a prostatic mass, normal prostate-specific antigen level, and micturition-associated cardiovascular symptoms.Testing for catecholamine metabolites is the key screening tool.Robot-assisted surgery facilitates precise tumor excision while ensuring optimal functional preservation.Given the malignant potential and genetic correlations of PPG, lifelong follow-up is recommended.

AIM: To investigate the effects of high-concentration glucose on the cell viability of retinal pigment epithelialcells(ARPE-19)/ human umbilical vein endothelial cells(HUVEC)cells, as well as on the expression levels of sirtuin 6(SIRT6).

METHODS:ARPE-19 and HUVEC cells were cultured for 48 h in media containing various glucose concentrations(5.5, 25, 50, 75, 100 mmol/L)and cellular morphology was observed under an optical microscope.Cell viability was assessed using the CCK-8 assay. Flow cytometry was utilized to evaluate apoptosis levels, and Western blot analysis was conducted to measure the expression of Bcl-2 and SIRT6. ARPE-19/HUVEC cells were treated with 50 mmol/L glucose for 48 h, after which immunofluorescence staining was performed to determine the subcellular localization and expression level of SIRT6 protein. In parallel, cells receiving the same treatment were harvested at different time points(0, 6, 12, 24, 36, 48, and 72 h), and the temporal changes in SIRT6 protein expression were assessed by Western blot analysis. SIRT6 overexpressing stable ARPE-19/HUVEC cell lines were constructed. Western blot was performed to detect the effects of SIRT6 overexpression on the expression levels of glucose transporters in ARPE-19/HUVEC cells treated with high glucose(50 mmol/L glucose).

RESULTS:Compared with the 5.5 mmol/L glucose group, cell number was decreased and cell viability was significantly reduced in ARPE19/HUVEC cells with increasing glucose concentrations(all P<0.01). Meanwhile, the protein expression level of SIRT6 was markedly downregulated(P<0.05). Such inhibitory effects exhibited both concentration-and time-dependent patterns(all P<0.05). Furthermore, high glucose induced cell apoptosis and downregulated the protein expression of Bcl-2(P<0.05). Immunofluorescence staining revealed that SIRT6 protein was predominantly localized in the nucleus after 48 h of high-glucose treatment, accompanied by pyknosis and nuclear fragmentation. After incubation with highg-lucose medium(50 mmol/L glucose)for different durations, long-term high-glucose intervention was found to reduce SIRT6 protein expression in ARPE19/HUVEC cells. Successful construction of the SIRT6-overexpressing stable ARPE-19/HUVEC cell lines was confirmed via immunofluorescence and Western blotting. Western blot analysis revealed that, compared with the HG+LV-con group, the HG+LV-SIRT6 group exhibited no significant differences in GLUT1 or GLUT4 expression in ARPE-19 cells, whereas GLUT3 expression was elevated(P<0.05). Compared with the HG+LV-con group, the HG+LV-SIRT6 group showed no significant change in GLUT1 expression, while GLUT3 and GLUT4 levels were increased(both P<0.05).

CONCLUSION:High-concentration glucose-reduce the proliferative activity of ARPE-19/HUVEC cells, induce apoptosis, and downregulate SIRT6 expression. SIRT6 may alleviate high glucose-induced retinal cell damage by promoting the expression of glucose transporters.

The Expert Consensus on Clinical Application of Qinbaohong Zhike Oral Liquid in Treatment of Acute Bronchitis and Acute Attack of Chronic Bronchitis （GS/CACM 337-2023） was released by the China Association of Chinese Medicine on December 13^th， 2023. This expert consensus was developed by experts in methodology， pharmacy， and Chinese medicine in strict accordance with the development requirements of the China Association of Chinese Medicine （CACM） and based on the latest medical evidence and the clinical medication experience of well-known experts in the fields of respiratory medicine （pulmonary diseases） and pediatrics. This expert consensus defines the application of Qinbaohong Zhike oral liquid in the treatment of cough and excessive sputum caused by phlegm-heat obstructing lung， acute bronchitis， and acute attack of chronic bronchitis from the aspects of applicable populations， efficacy evaluation， usage， dosage， drug combination， and safety. It is expected to guide the rational drug use in medical and health institutions， give full play to the unique value of Qinbaohong Zhike oral liquid， and vigorously promote the inheritance and innovation of Chinese patent medicines.

BACKGROUND:Osteoarthritis is now considered a metabolic disease.Previous studies have shown that glycolysis plays an important role in the occurrence and development of osteoarthritis.Compound 3k,as a novel small molecule inhibitor of glycolysis,has anti-inflammatory and anti-tumor effects.Therefore,it can target glycolysis and is expected to provide new ideas for the treatment of osteoarthritis. OBJECTIVE:To explore the role of Compound 3k in osteoarthritis caused by glycolytic overactivity based on the hypoxia-inducible factor 1 alpha(HIF-1α)/reactive oxygen species(ROS)pathway. METHODS:ATDC5 chondroblasts at logarithmic growth phase were taken to induce osteoarthritis in an in vitro cellular model by the action of 10 ng/mL interleukin-1β for 24 hours.The cytotoxicity of Compound 3k at different concentrations(0.25,0.5,1,2.5,5,10,15 μmol/L)was detected by cell counting kit-8 assay,and the appropriate concentrations were selected for the subsequent experiments.The chondrocytes were randomly divided into control,model and treatment groups.The model group was induced with 10 ng/mL interleukin 1β,and the treatment group was pre-stimulated with Compound 3k for 2 hours and then co-cultured with interleukin 1β.The proliferation of the cells in each group was detected by the cell counting kit-8 assay;the inflammatory level of the cells in each group was detected by the ELISA kit;the ROS,extracellular lactate and glucose contents were detected using the kit;qRT-PCR and western blot were used to detect the levels of related inflammatory factors,interleukin-6 and tumor necrosis factor-α,glycolysis-related genes glucose transporter protein-1,glyceraldehyde 3-phosphate dehydrogenase,monocarboxylate transporter protein-1 and HIF-1α. RESULTS AND CONCLUSION:Compared with the control group,the model group showed a decrease in cell proliferative activity,active glycolysis level,manifested by an increase in extracellular lactate content(P<0.001)and a decrease in glucose content(P<0.001),interleukin-6(P<0.000 1)and tumor necrosis factor-α(P<0.001).The expression levels of glycolysis-related genes glucose transporter protein-1(P<0.001),glyceraldehyde 3-phosphate dehydrogenase(P<0.001),monocarboxylic acid transporter protein-1(P<0.001)and HIF-1α(P<0.001)in the model group were all up-regulated,accompanied by oxidative stress and overproduction of ROS.Compared with the model group,Compound 3k treatment effectively increased cell proliferation activity and inhibited the level of overactive glycolysis(P<0.001),while suppressing the expression of genes related to inflammation(P<0.001)and glycolysis in osteoarthritic chondrocytes,inhibiting oxidative stress,downregulating the expression level of HIF-1α(P<0.000 1)and decreasing the content of ROS.To conclude,Compound 3k inhibits interleukin-1β induced chondrocyte inflammation,and its mechanism may be related to glycolysis and HIF-1α/ROS mediated oxidative stress.

OBJECTIVE: To investigate the clinical efficacy and advantages of robot-assisted total knee arthroplasty (TKA) in patients with varus knee osteoarthritis. METHODS: Between October 2022 and June 2023, a total of 59 patients with severe knee osteoarthritis resulting in varus were treated with total knee arthroplasty, aged from 59 to 81 years with an average (70.90±4.63) years, including 19 mals and 40 females. The patients were divided into two groups based on the surgical method used:28 patients in the robot group and 31 patients in the traditional group. The robot group consisted of 8 males and 20 femalse patients, with an average age of (70.54±4.80) years and an average disease duration of (14.89±8.72) months. The traditional group consisted of 11 males and 20 females patients, with an average age of (71.39±4.5) years and an average disease duration of (12.32±6.73) months. The operative duration, amount of bleeding during the operation, postoperative activity time after the operation, hip-knee-ankle angle (HKA), lateral distal femoral angle (LDFA), medial proximal tibial angle (MPTA), and complications were compared between the two groups before and after the operation. Lateral tibia component (LTC), frontal tibia component (FTC), frontal femoral component (FFC) and lateral femoral component (LFC) were measured 6 months after operation Additionally, the degree of knee joint motility, American Knee Society score (KSS), and visual analogue scale(VAS) were compared before and after the operation. RESULTS: All patients had gradeⅠwound healing without any complications, and all patients were followed up for 6 to 8 months, with an average of (6.5±1.5) months. There were no significant differences preoperative imaging evaluation indexes (including HKA, LDFA, and MPTA), preoperative knee mobility, preoperative VAS, and preoperative KSS between the two groups (P>0.05). Comparing the operation time (109.11±7.16) min vs. (83.90±7.85) min, length of the incision (16.60±2.33) cm vs. (14.47±1.41) cm, intraoperative bleeding (106.93±6.15) ml vs. (147.97±7.62) ml, postoperative activity time (17.86±1.84) h vs. (21.77±2.68) h, between the two groups showed statistically significant differences (P<0.05). There were significant differences in FFC (88.96±0.84)° vs. (87.93±1.09)° and LFC (88.57±1.10)° vs. (87.16±1.2)° between the two groups at 6 months after operation (P<0.05). The robotic group 1, 3, 6 months after KSS (75.96±3.96), (81.53±3.78), (84.50±3.29) scores, VAS (3.68±0.67), (2.43±0.79), (0.54±0.64), knee joint mobility (113.32±4.72) °, (123.93±3.99) °, (135.36±2.34) °;Traditional group KSS (73.77±4.18), (76.48±3.60), (80.19±3.28) scores, VAS (4.16±1.04), (3.03±0.75), (1.42±0.76) scores, knee joint mobility (109.19±6.95) °, (119.94±6.08) °, (134.48±2.14) °. Compared to before surgery, both groups showed significant improvement in KSS, VAS and knee mobility during the three follow-up visits (P<0.001). Additionally, postoperative HKA (180.39±1.95)° vs. (178.52±2.23)°, LDFA (89.67±0.63) ° vs. (89.63±0.63)°, and MPTA (89.44±0.55)° vs. (89.29±0.60)° were significantly improved in both groups compared to before surgery (P<0.001). The robotic group had higher KSS than the traditional group at 1, 3, and 6 months after surgery (P<0.05). The robotic group also had lower VAS than the traditional group at 1, 3, and 6 months after surgery (P<0.05). Furthermore, knee mobility was higher in the robotic group than those in the traditional group at 1 and 6 months after surgery (P<0.05), but there was no significant difference between the two groups at 6 months after surgery. CONCLUSION Robot-assisted total knee arthroplasty is a safe and effective method for total knee replacement. The use of robotics can improve the limb axis and prosthesis alignment for patients with preoperative varus deformity, resulting in better clinical and imaging outcomes compared to the conventional group.
Humans ; Female ; Male ; Arthroplasty, Replacement, Knee/methods* ; Aged ; Middle Aged ; Osteoarthritis, Knee/physiopathology* ; Aged, 80 and over ; Robotic Surgical Procedures/methods*

PURPOSE: Intertrochanteric fracture (ITF) classification is crucial for surgical decision-making. However, orthopedic trauma surgeons have shown lower accuracy in ITF classification than expected. The objective of this study was to utilize an artificial intelligence (AI) method to improve the accuracy of ITF classification. METHODS: We trained a network called YOLOX-SwinT, which is based on the You Only Look Once X (YOLOX) object detection network with Swin Transformer (SwinT) as the backbone architecture, using 762 radiographic ITF examinations as the training set. Subsequently, we recruited 5 senior orthopedic trauma surgeons (SOTS) and 5 junior orthopedic trauma surgeons (JOTS) to classify the 85 original images in the test set, as well as the images with the prediction results of the network model in sequence. Statistical analysis was performed using the SPSS 20.0 (IBM Corp., Armonk, NY, USA) to compare the differences among the SOTS, JOTS, SOTS + AI, JOTS + AI, SOTS + JOTS, and SOTS + JOTS + AI groups. All images were classified according to the AO/OTA 2018 classification system by 2 experienced trauma surgeons and verified by another expert in this field. Based on the actual clinical needs, after discussion, we integrated 8 subgroups into 5 new subgroups, and the dataset was divided into training, validation, and test sets by the ratio of 8:1:1. RESULTS: The mean average precision at the intersection over union (IoU) of 0.5 (mAP50) for subgroup detection reached 90.29%. The classification accuracy values of SOTS, JOTS, SOTS + AI, and JOTS + AI groups were 56.24% ± 4.02%, 35.29% ± 18.07%, 79.53% ± 7.14%, and 71.53% ± 5.22%, respectively. The paired t-test results showed that the difference between the SOTS and SOTS + AI groups was statistically significant, as well as the difference between the JOTS and JOTS + AI groups, and the SOTS + JOTS and SOTS + JOTS + AI groups. Moreover, the difference between the SOTS + JOTS and SOTS + JOTS + AI groups in each subgroup was statistically significant, with all p < 0.05. The independent samples t-test results showed that the difference between the SOTS and JOTS groups was statistically significant, while the difference between the SOTS + AI and JOTS + AI groups was not statistically significant. With the assistance of AI, the subgroup classification accuracy of both SOTS and JOTS was significantly improved, and JOTS achieved the same level as SOTS. CONCLUSION In conclusion, the YOLOX-SwinT network algorithm enhances the accuracy of AO/OTA subgroups classification of ITF by orthopedic trauma surgeons.
Humans ; Hip Fractures/diagnostic imaging* ; Orthopedic Surgeons ; Algorithms ; Artificial Intelligence

The choice of biopsy method is critical in diagnosing prostate cancer (PCa). This retrospective cohort study compared systematic biopsy (SB) or cognitive fusion-targeted biopsy combined with SB (CB) in detecting PCa and clinically significant prostate cancer (csPCa). Data from 2572 men who underwent either SB or CB in Fudan University Shanghai Cancer Center (Shanghai, China) between January 2019 and December 2023 were analyzed. Propensity score matching (PSM) was used to balance baseline characteristics, and detection rates were compared before and after PSM. Subgroup analyses based on prostate-specific antigen (PSA) levels and Prostate Imaging-Reporting and Data System (PI-RADS) scores were performed. Primary and secondary outcomes were the detection rates of PCa and csPCa, respectively. Of 2572 men, 1778 were included in the PSM analysis. Before PSM, CB had higher detection rates for both PCa (62.9% vs 52.4%, odds ratio [OR]: 1.54, P < 0.001) and csPCa (54.9% vs 43.3%, OR: 1.60, P < 0.001) compared to SB. After PSM, CB remained superior in detecting PCa (63.1% vs 47.9%, OR: 1.86, P < 0.001) and csPCa (55.0% vs 38.2%, OR: 1.98, P < 0.001). In patients with PSA 4-12 ng ml -1 (>4 ng ml -1 and ≤12 ng ml -1 , which is also applicable to the following text), CB detected more PCa (59.8% vs 40.7%, OR: 2.17, P < 0.001) and csPCa (48.1% vs 27.7%, OR: 2.42, P < 0.001). CB also showed superior csPCa detection in those with PI-RADS 3 lesions (32.1% vs 18.0%, OR: 2.15, P = 0.038). Overall, CB significantly improves PCa and csPCa detection, especially in patients with PSA 4-12 ng ml -1 or PI-RADS 3 lesions.
Humans ; Male ; Prostatic Neoplasms/diagnosis* ; Propensity Score ; Retrospective Studies ; Middle Aged ; Aged ; Image-Guided Biopsy/methods* ; Prostate-Specific Antigen/blood* ; Prostate/diagnostic imaging*

To guide clinical blood transfusion practices for pediatric patients, the National Health Commission has issued the health standard "Guideline for pediatric transfusion" (WS/T 795-2022). Blood transfusion is one of the most commonly used supportive treatments for children with hematological diseases. This guideline provides guidance and recommendations for blood transfusions in children with aplastic anemia, thalassemia, autoimmune hemolytic anemia, glucose-6-phosphate dehydrogenase deficiency, acute leukemia, myelodysplastic syndromes, immune thrombocytopenic purpura, and thrombotic thrombocytopenic purpura. This article presents the evidence and interpretation of the blood transfusion provisions for children with hematological diseases in the "Guideline for pediatric transfusion", aiming to assist in the understanding and implementing the blood transfusion section of this guideline.
Humans ; Child ; Hematologic Diseases/therapy* ; Blood Transfusion/standards* ; Practice Guidelines as Topic