Objective To explore the mechanism by which breast cancer-derived LncRNA OIP5-AS1 regulates the migration, invasion, and epithelial-mesenchymal transition of breast cancer cells through the M2 polarization of tumor-associated macrophages (TAM). Methods MDA-MB-231 cells were divided into the control group (blank control), the NC group (transfected with NC siRNA), and the si-OIP5 group (transfected with LncRNA OIP5-AS1 siRNA). The mRNA expression levels of LncRNAs OIP5-AS1, IL-4, and IL-13 were detected by RT-qPCR. The protein expression levels of IL-4 and IL-13 in the culture supernatant were detected by ELISA. The culture supernatant from the control group was added to RPMI 1640 medium at different volume ratios to induce the polarization of M0 macrophages into TAMs. The mRNA expression of CD206 in TAMs was detected by RT-qPCR. M0-type macrophages were induced with the medium supernatant of the NC group/si-OIP5 group, and the expression of CD206 was detected by Western blot. Subsequently, a co-culture model of macrophage and MDA-MB-231 was constructed to evaluate the migration and invasion abilities of MDA-MB-231 cells and detect the expression changes in Vimentin, N-cadherin and E-cadherin. Results Compared with the control and NC groups, the si-OIP5 group showed significantly downregulated expression of LncRNA OIP5-AS1 (P<0.001) and significantly decreased IL-13 mRNA and protein levels (P<0.05). Meanwhile, no significant difference was observed in the expression of IL-4 among the groups. Conditioned medium induced CD206 expression in M0 macrophages in a volume-dependent manner, with the strongest effect at a 40% volume ratio (P<0.001). The CD206 protein level in the si-OIP5 group significantly decreased (P<0.01). In the co-culture system, the migration and invasion abilities of MDA-MB-231 cells in the si-OIP5 group significantly weakened (P<0.001), the expression of E-cadherin was upregulated, and the expression levels of N-cadherin and Vimentin were downregulated (both P<0.01). Conclusion Breast cancer-derived LncRNA OIP5-AS1 can induce TAM M2 polarization mediated by IL-13, thereby promoting the migration, invasion, and EMT of breast cancer cells.

ObjectiveTo observe the effects of Danggui Shaoyaosan on macrophage polarization and renal inflammation in db/db mice with diabetic kidney disease （DKD）， and to explore its renal protective effects and underlying mechanisms. MethodsEight db/m mice were assigned to the normal group， and forty db/db mice were randomly divided into a model group， low-， medium-， and high-dose Danggui Shaoyaosan groups （8.39， 16.77， 33.54 g·kg^-1）， and an irbesartan group （0.025 g·kg^-1）. All mice were administered treatment by gavage for 12 consecutive weeks. General conditions of the mice were observed during the intervention. At the end of the 12-week intervention， 24-h urine samples were collected using metabolic cages， after which the mice were anesthetized for sample collection. Blood was collected by enucleation and centrifuged to obtain serum for the determination of glycated serum protein （GSP）， serum creatinine （SCr）， blood urea nitrogen （BUN）， total cholesterol （TC）， and triglycerides （TG）. The urinary albumin-to-creatinine ratio （UACR） was measured. Renal pathological changes were observed using hematoxylin-eosin （HE） staining， periodic acid-Schiff （PAS） staining， and Masson staining. Enzyme-linked immunosorbent assay （ELISA） was used to detect serum tumor necrosis factor-α （TNF-α）， interleukin-10 （IL-10）， and monocyte chemoattractant protein-1 （MCP-1） levels. Immunofluorescence （IF） was performed to detect F4/80 expression in renal tissue， and immunohistochemistry （IHC） was used to assess CD206 expression. Real-time quantitative polymerase chain reaction （Real-time PCR） was employed to measure the mRNA expression of TNF-α， IL-10， inducible nitric oxide synthase （iNOS）， and arginase-1 （Arg-1）. Western blot analysis was used to detect the protein expression of iNOS， Arg-1， CD86， and CD206 in renal tissue. ResultsCompared with the normal group， the model group showed increased levels of GSP， UACR， SCr， BUN， TC， and TG， elevated levels of the inflammatory factor TNF-α and the chemokine MCP-1， and decreased IL-10 levels （P<0.01）. Pathological examination revealed glomerular hypertrophy， mesangial cell proliferation with marked mesangial expansion， inflammatory cell infiltration， vacuolar degeneration of renal tubular epithelial cells， prominent glycogen deposition， and increased collagen fiber deposition. In addition， relative F4/80 fluorescence intensity was enhanced， CD206 expression in the glomeruli and renal interstitium was reduced， and TNF-α and iNOS mRNA expression was increased. IL-10 and Arg-1 mRNA expression was decreased， iNOS and CD86 protein expression was increased， and Arg-1 and CD206 protein expression was decreased （P<0.05， P<0.01）. Compared with the model group， the Danggui Shaoyaosan groups and the irbesartan group showed decreased levels of GSP， UACR， SCr， BUN， TC， and TG， reduced serum TNF-α and MCP-1 levels， and increased IL-10 levels. Renal pathological damage was improved to varying degrees. Relative F4/80 fluorescence intensity was reduced， CD206 expression in the glomeruli and renal interstitium was increased， and TNF-α and iNOS mRNA expression was decreased. IL-10 and Arg-1 mRNA expression was increased， iNOS and CD86 protein expression was reduced， and Arg-1 and CD206 protein expression was increased （P<0.05， P<0.01）. ConclusionDanggui Shaoyaosan can improve renal function and alleviate renal pathological damage in db/db mice. Its mechanism may be related to inhibiting M1 pro-inflammatory macrophage polarization， promoting M2 anti-inflammatory macrophage polarization， reducing inflammatory responses， delaying the progression of renal fibrosis， improving renal pathological injury， and thereby exerting renal protective effects.

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 analyze the iodine nutrition status of children and adolescents and influencing factors in Zhejiang Province, providing scientific basis for optimizing iodine deficiency disorders (IDD) prevention and control strategies.Methods:In June 2022, a multistage stratified sampling method was used to divide 16 counties (cities, districts, abbreviated as counties) in Zhejiang Province into three categories based on their geographical locations (average distance from the coastline): coastal areas (including Dinghai District, Jiaojiang District, Sanmen County, Cixi City and Lucheng District), sub-coastal areas (including Wuxing District, Haining City, Linping District, Fuyang District and Fenghua District), and inland areas(including Suichang County, Changshan County, Shengzhou City, Jindong District, Dongyang City and Yongjia County). One county was selected from each category, and one township (street) was selected from each county. Two administrative villages (neighborhood committees) were selected from each township (street). Ten households including all children and adolescents aged 6-17 in each household were selected from each administrative village (neighborhood committee). Demographic information and personal dietary characteristics were collected via questionnaires, while household salt and a random urine sample were tested for iodine level. Trend analysis was conducted using a χ 2trend test, and a multivariate logistic stepwise regression model was used to analyze the influencing factors of urinary iodine levels. Results:A total of 755 children and adolescents aged 6-17 were selected, including 387 males (51.26%) and 368 females (48.74%), with an age of (11.24 ± 3.32) years. There were 269 children and adolescents in coastal areas (35.63%) and 409 children and adolescents in urban areas (54.17%). A total of 755 household salt samples were collected, with a median salt iodine concentration of 21.80 mg/kg. These included 263 non-iodized salt samples, 38 unqualified iodized salt samples, and 454 qualified iodized salt samples. The coverage rate of iodized salt was 65.17% (492/755), and the consumption rate of qualified iodized salt was 60.13% (454/755). The distribution of salt iodine quality among children and adolescents in different geographical locations showed statistically significant differences (χ 2 = 111.95, P < 0.001), with the proportion of non-iodized salt gradually decreasing from coastal areas to inland areas (χ 2trend = 90.17, P < 0.001). A total of 755 urine samples were collected, with a median urinary iodine concentration of 186.60 μg/L. The proportions of urinary iodine < 100, 100-199, 200-299, and ≥300 μg/L were 16.95% (128/755), 37.62% (284/755), 24.37% (184/755), and 21.06% (159/755), respectively. The χ 2trend test revealed a nonlinear positive correlation between salt iodine level and urinary iodine level (χ 2regression = 21.98, P < 0.001; χ 2partial = 6.96, P < 0.001). The frequency distribution of urinary iodine in children and adolescents from different geographical locations and between urban and rural areas showed statistically significant differences (χ 2 = 29.63, 16.56, P < 0.001). Among them, the proportion of children and adolescents with urinary iodine < 100 μg/L gradually decreasing from coastal areas to inland areas (χ 2trend = 6.15, P = 0.013). The results of multivariate logistic regression analysis revealed that sub-coastal regions, inland regions, and urban-rural regions ( OR = 1.57, 1.53, 1.64, 95% CI: 1.11-2.24, 1.03-2.27, 1.17-2.32, P < 0.05) were significantly associated with urinary iodine levels in children and adolescents aged 6-17. Conclusions:In 2022, the iodine nutrition of children and adolescents in Zhejiang Province is generally suitable, but there is a risk of iodine deficiency among coastal children and adolescents. Geographic location and urban/rural areas are influencing factors on iodine nutrition status of children and adolescents in Zhejiang Province.

Objective:To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of extraprostatic extension (EPE) in prostate cancer (PCa).Methods:In this cross-sectional study, consecutive bpMRI of patients undergoing prostatectomy for PCa were retrospectively collected from the First Medical Center (center 1) and the Third Medical Center (center 2) of Chinese PLA General Hospital. A total of 274 patients were finally enrolled. Patients at center 1 from January 2020 to December 2022 were randomly divided into a training set (149 cases) and an internal validation set (63 cases) by stratified random sampling. Patients at center 2 from January 2023 to March 2024 were assigned to the external test set (62 cases). Patients were categorized into EPE-positive group and EPE-negative group according to pathological assessment postoperatively. In the training set, there were 49 cases in EPE-positive group and 100 cases in EPE-negative group. In the internal validation set, there were 26 cases in EPE-positive group and 37 cases in EPE-negative group. In the external test set, there were 22 cases in EPE-positive group and 40 cases in EPE-negative group. Axial T 2WI and apparent diffusion coefficient (ADC) images were manually annotated to obtain index lesion regions of interest (ROIs), with the peritumoral ROIs subsequently delineated by semi-automatic segmentation technique. Radiomics features were extracted from intra-tumoral, peri-tumoral, and intra-tumoral plus peri-tumoral ROIs. The training set data was employed to select and optimize features to build the radiomics models. The logistic regression analysis was used to develop radiomics, clinical, and integrated models. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC) in the external test set, and compared by the DeLong test. The sensitivity and specificity were compared by the exact McNemar test. Results:In the external test set, the peri-tumoral radiomics model based on bpMRI showed the highest performance in evaluating EPE, with an AUC of 0.739 (95% CI 0.611-0.842), which was identified as the optimal radiomics model. EPE grade ( OR=6.151, 95% CI 3.371-11.226, P<0.001) was incorporated into the clinical model, with an AUC of 0.780 (95% CI 0.657-0.875) in the external test set. The integrated model had an AUC of 0.817 (95% CI 0.698-0.904) in the external test set. There was no statistically significant difference in comparisons of AUCs among the three models (all P>0.05). The sensitivity of the integrated model (68.2%) showed no significant difference from those of the clinical model and the optimal radiomics model (77.3% and 86.4%, respectively; P=0.500 and P=0.289). However, the specificity of the integrated model (85.0%) was significantly higher than those of the clinical model (67.5%, P=0.016) and the optimal radiomics model (50.0%, P<0.001). Conclusion:A bpMRI-based peritumoral radiomics integrating clinical model demonstrates high performance for preoperative prediction of EPE in PCa.

Traditional Chinese medicine(TCM)exerts integrative effects on complex diseases owing to the char-acteristics of multiple components with multiple targets.However,the syndrome-based system of diagnosis and treatment in TCM can easily lead to bias because of varying medication preferences among physicians,which has been a major challenge in the global acceptance and application of TCM.Therefore,a standardized TCM prescription system needs to be explored to promote its clinical application.In this study,we first developed a gradient weighted disease-target-herbal ingredient-herb network to aid TCM formulation.We tested its efficacy against intracerebral hemorrhage(ICH).First,the top 100 ICH targets in the GeneCards database were screened according to their relevance scores.Then,SymMap and Traditional Chinese Medicine Systems Pharmacology(TCMSP)databases were applied to find out the target-related ingredients and ingredient-containing herbs,respectively.The relevance of the resulting ingredients and herbs to ICH was determined by adding the relevance scores of the corresponding targets.The top five ICH therapeutic herbs were combined to form a tailored TCM prescriptions.The absorbed components in the serum were detected.In a mouse model of ICH,the new prescription exerted multifaceted effects,including improved neurological function,as well as attenuated neuronal damage,cell apoptosis,vascular leakage,and neuroinflammation.These effects matched well with the core pathological changes in ICH.The multi-targets-directed gradient-weighting strategy presents a promising avenue for tailoring precise,multipronged,unbiased,and standardized TCM prescriptions for complex diseases.This study provides a paradigm for advanced achievements-driven modern innovation in TCM concepts.

Objective:To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of extraprostatic extension (EPE) in prostate cancer (PCa).Methods:In this cross-sectional study, consecutive bpMRI of patients undergoing prostatectomy for PCa were retrospectively collected from the First Medical Center (center 1) and the Third Medical Center (center 2) of Chinese PLA General Hospital. A total of 274 patients were finally enrolled. Patients at center 1 from January 2020 to December 2022 were randomly divided into a training set (149 cases) and an internal validation set (63 cases) by stratified random sampling. Patients at center 2 from January 2023 to March 2024 were assigned to the external test set (62 cases). Patients were categorized into EPE-positive group and EPE-negative group according to pathological assessment postoperatively. In the training set, there were 49 cases in EPE-positive group and 100 cases in EPE-negative group. In the internal validation set, there were 26 cases in EPE-positive group and 37 cases in EPE-negative group. In the external test set, there were 22 cases in EPE-positive group and 40 cases in EPE-negative group. Axial T 2WI and apparent diffusion coefficient (ADC) images were manually annotated to obtain index lesion regions of interest (ROIs), with the peritumoral ROIs subsequently delineated by semi-automatic segmentation technique. Radiomics features were extracted from intra-tumoral, peri-tumoral, and intra-tumoral plus peri-tumoral ROIs. The training set data was employed to select and optimize features to build the radiomics models. The logistic regression analysis was used to develop radiomics, clinical, and integrated models. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC) in the external test set, and compared by the DeLong test. The sensitivity and specificity were compared by the exact McNemar test. Results:In the external test set, the peri-tumoral radiomics model based on bpMRI showed the highest performance in evaluating EPE, with an AUC of 0.739 (95% CI 0.611-0.842), which was identified as the optimal radiomics model. EPE grade ( OR=6.151, 95% CI 3.371-11.226, P<0.001) was incorporated into the clinical model, with an AUC of 0.780 (95% CI 0.657-0.875) in the external test set. The integrated model had an AUC of 0.817 (95% CI 0.698-0.904) in the external test set. There was no statistically significant difference in comparisons of AUCs among the three models (all P>0.05). The sensitivity of the integrated model (68.2%) showed no significant difference from those of the clinical model and the optimal radiomics model (77.3% and 86.4%, respectively; P=0.500 and P=0.289). However, the specificity of the integrated model (85.0%) was significantly higher than those of the clinical model (67.5%, P=0.016) and the optimal radiomics model (50.0%, P<0.001). Conclusion:A bpMRI-based peritumoral radiomics integrating clinical model demonstrates high performance for preoperative prediction of EPE in PCa.

Objective:To evaluate the effectiveness of diaphragm ultrasound in predicting the success of extubation from tracheotomy in patients with acquired brain injury.Methods:A retrospective analysis was conducted on 51 brain-injured patients. They were divided into an extubation failure group and an extubation success group. The results of ultrasound examination of the diaphragm in the 2 groups were analyzed by univariate analysis, and the independent variables with significance were further subjected to multivariate logistic regression analysis. R software was applied to build the diaphragm indicators showing significant predictive power into a histogram model. The predictive value of this nomogram model was assessed using the receiver operating characteristics (ROC) curve.Results:The univariate analysis revealed significant differences between the two groups in terms of diaphragm excursion, diaphragm thickening fraction and diaphragm excursion-time index. The multivariate logistic regression analysis and the nomogram showed that those three variables are independent influencing factors predicting the success of decannulation. The areas under the ROC curves confirmed that finding.Conclusions:Diaphragm excursion, diaphragm thickening fraction and the diaphragm excursion-time index are useful independent predictors of the success of decannulation among brain injury patients.

Purpose This study aimed to investigate the expression and clinical significance of TLDC2 in colorec-tal adenocarcinoma.Methods Data from the human protein atlas(HPA)and the cancer genome atlas(TCGA)indi-cated that TLDC2 was highly expressed in colorectal adenocarcinoma.We further analyzed the expression of TLDC2 in 400 colorectal adenocarcinomas and 447 other solid tumors using tissue microarrays and immunohistochemical(IHC)staining.Result The positive expression rate of TLDC2 was significantly higher than that of SATB2 in colorectal ade-nocarcinomas(96.5％vs 87.0％,P＜0.000 1).TLDC2 positivity exceeded that of SATB2 in both low-or high-grade colorectal adenocarcinoma(99.4％vs 88.7％,P＜0.000 1;83.3％vs 79.2％,P=0.669 9).In addition,the expression of TLDC2 and SATB2 was evaluated in 447 cases of other types of solid tumors.TLDC2 was expressed in neuroendocrine tumors as well as in gastric and appendiceal adenocarcinomas,whereas SATB2 was detected in a small number of melanomas,ovarian cancers,breast cancers and gallbladder cancers.The positive and specificity of TLDC2 for colorectal adenocarcinoma were 97％(95％CI=0.94-0.98)and 85％(95％CI=0.81-0.88),respectively.Combined detection of TLDC2 and SATB2 yielded a sensitivity of 96％(95％CI=0.93-0.97)and a specificity of 93％(95％CI=0.90-0.95).Conclusion Analysis of large-scale datasets and IHC staining demonstrated that TLDC2 is a highly sensitive and specific biomarker for colorectal adenocarcinoma.