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.

Erchentang is a classic formula widely used by medical practitioners throughout history. In this paper，ancient and modern literature of Erchentang were collected， and bibliometrics was employed to analyze its historic evolution，prescription meaning，herbs origin， processing method，preparation methods， and clinical application. A total of 84 pieces of data were collected， and 58 pieces of data involving 53 ancient medical Chinese books were screened， sorted， and processed. Combined with research of modern scholars，the research has found that the Erchentang originated from the Taiping Huimin Huiye Shijie Fang compiled by the Imperial Medical Bureau of the Song Dynasty. The basic information about the origin of the drugs is quite clear. Pinelliae rhizoma in the formula is the dried tuber of Pinellia ternata. Citri exocarpium rubrum is the dried mature peel of Citrus reticulata and its cultivated varieties， with the inner white membrane removed. Poria is the whitest dry sclerotia of Poria cocos； Glycyrrhizae radix et rhizoma is the dried root and rhizome of the Glycyrrhiza uralensis. The dosage is 5.70 g Pinelliae rhizome and Citri exocarpium rubrum， 3.43 g Poria， and 1.69 g Glycyrrhizae radix et rhizoma praeparata cum melle. During the decoction process， the above-mentioned herbs should be chopped， with 300 mL water， 7 g ginger in thick slices， and 2 g Mume fructus added， and it was then simmered together to 180 mL. After removing the medicinal residue， it can be taken warmly. Erchentang has the effect of drying dampness and resolving phlegm， regulating Qi and harmonizing the middle. It can be used in treating the syndrome of phlegm and dampness，as well as symptoms such as frequent cough，white phlegm，fullness in chest and diaphragm，nausea and vomiting，limb drowsiness，anorexia，dizziness，palpitations，white and greasy tongue coating， and slippery pulse. The above results provide reference for future research and development of Erchentang.

ObjectiveTo explore the clinical efficacy and mechanism of Bupi Qingfei prescription （BPQF） in treating stable bronchiectasis in the patients with syndromes of lung-spleen Qi deficiency and phlegm-heat accumulation in the lungs. MethodsA randomized， double-blind， placebo-controlled trial was conducted. Patients were randomized into BPQF and placebo control （PC） groups. On the basis of conventional Western medicine treatment， the BPQF granules and placebo were respectively administered at 10 g each time， twice a day， for a course of 24 weeks. The TCM symptom scores， Quality of Life Questionnaire for Bronchiectasis （QOL-B） scores， lung function indicators， T lymphocyte subsets， level of inflammatory factors in the sputum， level of neutrophil elastase （NE） in the sputum， and occurrence of adverse reactions were observed before and after treatment in the two groups. ResultsA total of 64 patients completed the study， encompassing 32 in the BPQF group and 32 in the PC group. After treatment， the BPQF group showed decreased TCM symptom scores （P<0.01）， increased QOL-B scores （P<0.01）， and declined levels of tumor necrosis factor （TNF）-α and NE （P<0.05， P<0.01）. The PC group showed decreased TCM symptom （except spleen deficiency） scores （P<0.01）， increased the QOL-B health cognition and respiratory symptom domain scores （P<0.05， P<0.01）， and a declined TNF-α level （P<0.01）. Moreover， the BPQF group had lower TCM symptom （except chest tightness） scores （P<0.05， P<0.01）， higher QOL-B （except treatment burden） scores （P<0.05， P<0.01）， and lower levels of interleukin-6 and TNF-α （P<0.05） than the PC group. Neither group showed serious adverse reactions during the treatment process. ConclusionBPQF can ameliorate the clinical symptoms of stable bronchiectasis patients who have lung-spleen Qi deficiency or phlegm-heat accumulation in the lungs by regulating the immune balance and inhibiting airway inflammatory responses.

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.

To analyze global trends and research hotspots in exercise intervention for overweight and obesity from 2010 to 2024, to provide novel perspectives for comprehensive management research on overweight and obesity.

Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive decline and memory impairment in clinical. Currently, there are no effective treatments for AD. In recent years, a variety of therapeutic approaches from different perspectives have been explored to treat AD. Although the drug therapies targeted at the clearance of amyloid β-protein (Aβ) had made a breakthrough in clinical trials, there were associated with adverse events. Neuroinflammation plays a crucial role in the onset and progression of AD. Continuous neuroinflammatory was considered to be the third major pathological feature of AD, which could promote the formation of extracellular amyloid plaques and intracellular neurofibrillary tangles. At the same time, these toxic substances could accelerate the development of neuroinflammation, form a vicious cycle, and exacerbate disease progression. Reducing neuroinflammation could break the feedback loop pattern between neuroinflammation, Aβ plaque deposition and Tau tangles, which might be an effective therapeutic strategy for treating AD. Traditional Chinese herbs such as Polygonum multiflorum and Curcuma were utilized in the treatment of AD due to their ability to mitigate neuroinflammation. Non-steroidal anti-inflammatory drugs such as ibuprofen and indomethacin had been shown to reduce the level of inflammasomes in the body, and taking these drugs was associated with a low incidence of AD. Biosynthetic nanomaterials loaded with oxytocin were demonstrated to have the capability to anti-inflammatory and penetrate the blood-brain barrier effectively, and they played an anti-inflammatory role via sustained-releasing oxytocin in the brain. Transplantation of mesenchymal stem cells could reduce neuroinflammation and inhibit the activation of microglia. The secretion of mesenchymal stem cells could not only improve neuroinflammation, but also exert a multi-target comprehensive therapeutic effect, making it potentially more suitable for the treatment of AD. Enhancing the level of TREM2 in microglial cells using gene editing technologies, or application of TREM2 antibodies such as Ab-T1, hT2AB could improve microglial cell function and reduce the level of neuroinflammation, which might be a potential treatment for AD. Probiotic therapy, fecal flora transplantation, antibiotic therapy, and dietary intervention could reshape the composition of the gut microbiota and alleviate neuroinflammation through the gut-brain axis. However, the drugs of sodium oligomannose remain controversial. Both exercise intervention and electromagnetic intervention had the potential to attenuate neuroinflammation, thereby delaying AD process. This article focuses on the role of drug therapy, gene therapy, stem cell therapy, gut microbiota therapy, exercise intervention, and brain stimulation in improving neuroinflammation in recent years, aiming to provide a novel insight for the treatment of AD by intervening neuroinflammation in the future.

ObjectiveTo evaluate the effectiveness and safety of Sufei Pingchuan Formula （肃肺平喘方） in the treatment of bronchiectasis with airflow limitation， phlegm-heat obstructing the lung， and lung-spleen qi deficiency syndrome. MethodsA randomized， double-blind， placebo-controlled trial was conducted. A total of 72 patients with stable bronchiectasis with airflow limitation of phlegm-heat obstructing the lung and lung-spleen qi deficiency syndrome were randomly divided into treatment group and control group， with 36 cases in each group. On the basis of regular inhalation of tiotropium bromide inhalation spray， the treatment group was given Sufei Pingchuan Formula granules， and the control group was given Sufei Pingchuan Formula granule simulant. The course of treatment in both groups was 12 weeks. The pulmonary function of both groups before and after treatment was observed， specifically focusing on forced expiratory volume in one second （FEV1）； the modified British Medical Research Council （mMRC） dyspnea scale， 24-hour sputum volume， COPD assessment test （CAT）， and traditional Chinese medicine （TCM） syndrome scores were assessed before treatment and after 4， 8， and 12 weeks of treatment； acute exacerbations were recorded at weeks 4， 8， and 12； additionally， changes in routine blood tests， urinalysis， liver and kidney function， and adverse events were monitored before and after treatment. ResultsAfter treatment， 4 patients in the treatment group and 6 in the control group dropped out. After 12 weeks of treatment， FEV1 increased in both groups compared to pre-treatment levels （P＜0.05）， but the difference between groups was not statistically significant （P＞0.05）. Compared to before treatment， the treatment group showed a reduction in mMRC scores after 12 weeks （P＜0.05） and a decrease in 24-hour sputum volume， CAT scores， and TCM syndrome scores at weeks 4， 8， and 12 （P＜0.05）. In the control group， 24-hour sputum volume decreased after 12 weeks （P＜0.05）， and TCM syndrome scores decreased at weeks 8 and 12 （P＜0.05）. Compared to the control group， the treatment group showed a greater reduction in mMRC scores at week 12 （P＜0.05）， a decrease in 24-hour sputum volume and TCM syndrome scores at weeks 4， 8， and 12 （P＜0.05）， and lower CAT scores at weeks 8 and 12 （P＜0.05）. The frequency and number of acute exacerbations in the treatment group were significantly lower than those in the control group at week 12 （P＜0.05）. No severe adverse events occurred in either group. ConclusionSufei Pingchuan Formula can improve the pulmonary function FEV1， the severity of dyspnea， reduce 24-hour sputum volume and frequent acute exacerbations， and improve the quality of life in patients with bronchiectasis and airflow limitation， with good safety.

Objective To evaluate the early efficacy and safety of the regimens containing delamanid and linezolid in the treatment of rifampicin resistant tuberculosis(RR-TB).Methods A total of 47 patients diagnosed with RR-TB at Public Health Clinical Center of Chengdu from August 2020 to December 2021 were enrolled,including 22 cases(46.8％)of multidrug-resistant tuberculosis(MDR-TB),8 cases(17.0％)of RR-TB,and 17 cases(36.2％)of pre-extensively drug-resistant tuberculosis(pre-XDR-TB).All patients were treated with a regimen based on delamanid and linezolid.The efficacy and safety were evaluated at 24 weeks of treatment.Results Among the 47 patients,46(97.9％)completed 24 weeks of treatment and 1(2.1％)was lost to follow-up.At 24 weeks,the sputum culture conversion rate was 100％in the 43 patients with positive baseline sputum culture.The median conversion time was 2(2,8)weeks.Imaging examination showed absorption in 46 patients(97.9％).Overall,40 patients(85.1％)experienced varying degrees of adverse events(AEs)within 24 weeks.Eleven patients(23.4％)experienced AEs possibly related to delamanid,mainly including QTcF interval prolongation(12.8％),gastrointestinal reactions(8.5％),dizziness(2.1％),headache(2.1％),and allergy(2.1％).Six patients permanently discontinued delamanid due to AEs including gastrointestinal reactions(6.4％),prolonged QTcF interval(2.1％),severe dizziness(2.1％),and drug allergy(2.1％).Patients with low baseline CD4+T lymphocyte counts(OR=0.991,95％CI:0.984-0.999)were more likely to experience delamanid-related AEs.Thirty patients(63.8％)experienced AEs possibly related to linezolid,including myelosuppression(55.3％),peripheral neuropathy(6.4％),optic neuritis occurred(2.1％),and allergy(2.1％).Three patients(6.4％)discontinued linezolid permanently due to severe anemia,peripheral neuropathy,and allergy.Conclusions The treatment regimens containing delamanid and linezolid for RR-TB showed a high sputum culture conversion rate and good tolerance at 24 weeks.Attention should be paid to gastrointestinal reactions and cellular immunity during treatment.

Objective To investigate the impact of sleep modes on the risk for diseases of the body systems.Methods Based on a subset of UK Biobank dataset comprising 87 617 participants,3 sleep dimensions including 6 sleep indicators were obtained through a wrist-worn accelerometer,that is sleep duration and onset,sleep rhythm(relative amplitude and stability),and sleep quality(sleep efficiency and number of awakenings).Latent profile analysis(LPA)was applied to identify and classify distinct sleep modes.Then their longitudinal medical records were the association between different sleep modes and the risk for 467 diseases.Results LPA identified 5 subgroups of unique sleep modes in the participants.Among the 5 subgroups,the subgroup 4 had relatively optimal levels in above sleep indicators.Compared to the subgroup 4,the other 4 subgroups exhibited variations in different sleep dimensions,with at least one indicator demonstrating an unfavorable trend.These subgroups also revealed differences in racial composition,shift work and social deprivation index.Moreover,there were notable differences in the risk of various system diseases among the subgroups(P<0.05).When compared to the subgroup 4,the other 4 subgroups exhibited an elevated risk for certain diseases(comprising a total of 126 diseases),with the diseases of the circulatory system,digestive system and musculoskeletal system most common.Among the 5 subgroups,the subgroup 2(shorter sleep duration and later sleep onset)and the subgroup 5(rhythm disorder)had the highest counts of associated risks,amounting to 85 and 91 types,respectively,but there was certain difference in their systematic composition.Conclusion There are different sleep modes within the participants,and the modes are potentially associated with an increased risk for diseases of body systems.Comprehensive interventions targeting overall sleep modes rather than single sleep indicator may yield obvious health benefits.

Purpose To evaluate the value of preoperative MRI-based radiomic models for assessing tumor-infiltrating CD8+T-cell expression in glioblastoma patients,and to identify the most stable and efficient radiomic feature region for predicting prognosis following immunotherapy.Materials and Methods This retrospective study included 150 patients with histopathologically confirmed glioblastoma from Lanzhou University Second Hospital(January 2018 to April 2022).Tumor-infiltrating CD8+T-cell expression was quantitatively assessed using immunohistochemical staining,with patients stratified into CD8-high and CD8-low expression groups based on overall survival.A total of 1 185 radiomic features were extracted from each patient's contrast-enhanced T1C and T2WI images,covering the original tumor region and sequentially expanded peritumoral regions(2.5 mm,5.0 mm,7.5 mm,10.0 mm,12.5 mm,15.0 mm morphological dilation of tumor core+peritumoral area).Feature selection was performed using variance threshold,minimum redundancy maximum relevance,and least absolute shrinkage and selection operator methods.XGBoost classifier was employed to construct clinical,radiomic,and clinical-radiomic multimodal combined prediction models.Diagnostic performance was evaluated using receiver operating characteristic curve analysis.Results The radiomic model based on tumor expansion of 7.5 mm(tumor+peritumoral region)demonstrated optimal predictive performance.The clinical-radiomic multimodal combined model showed superior predictive capability compared to clinical and radiomic models alone,achieving an area under the curve of 0.991 and accuracy of 99.0%in the training set,and area under the curve of 0.840 with accuracy of 80.0%in the validation set.Conclusion MRI radiomics provides a feasible approach for evaluating tumor-infiltrating CD8+T-cell expression in glioblastoma patients,offering potential for preoperative prognosis prediction.