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.

With the continuous development of China's aging society and the prevalence of unhealthy lifestyles, the incidence of cardiovascular disease in China has been increasing in recent years. Among them, atrial fibrillation (AF) is the most common arrhythmia disease. In recent years, pulsed field ablation (PFA) has been continuously applied to AF treatment as a novel treatment. This paper first introduces the principle of PFA applied to AF treatment, and introduces the research progress of PFA in different directions, such as the comparison of different ablation methods, the study of physical parameters, the study of ablation area, the study of tissue specificity and clinical research. Then, the clinical prior research of PFA is discussed, including the use of simulation software to obtain the simulation effect of different parameters, the evaluation of ablation effect during animal research, and finally the current AF treatment. Various prior studies and clinical studies are summarized, and suggestions are made for the shortcomings found in the study of AF treatment and the future research direction is prospected.

Objective:To analyze the relationship between the optimal surgical margin value and clinical prognosis of transoral robotic surgery（TORS） in treating human papillomavirus（HPV） -positive oropharyngeal squamous cell carcinoma. Methods:A single-center, prospective, observational cohort study was conducted, enrolling patients with early and moderated stage（≤T3 stage） oropharyngeal carcinoma undergoing TORS between July 2020 and April 2024. The proposed optimal surgical margin cutoff value for TORS was set as 2 mm. The primary objectives were to evaluate the optimal clear margin for TORS and its association with overall survival（OS） and progression-free survival（PFS）. Logistic regression was used to analyze correlations between surgical margins and clinical variables, while Cox regression models assessed the impact of surgical margins on OS and PFS. Results:A total of 90 patients（60 males, 66.7%） were included, all had squamous cell carcinoma, with a mean age of 58.0±9.0 years（range: 39-84 years） old. The 1, 2 and 3-year OS rates were 92.3%, 89.9% and 85.0%, respectively, while the 1, 2 and 3-year PFS rates were all 90.1%. For surgical margins ≤2 mm, the 1, 2 and 3-year OS rates were 80.8%, 69.3% and 69.3%, respectively, and PFS rates were 77.9% across three time points. For surgical margins>2 mm, the 1, 2 and 3-year OS rates were 96.5%, 96.5% and 90.6%, respectively, with PFS rates of 94.6%. Logistic regression showed no correlation between surgical margins and tumor type, T/N stage, smoking, alcohol use, or gender（P>0.05）. Cox analysis identified surgical margins>2 mm as a significant factor improving PFS（HR=0.14, 95%CI 0.02-0.90, P=0.038）. Conclusion:This systematic analysis suggests setting a 2 mm and longer as clear surgical margin for TORS. Margins>2 mm are associated with superior postoperative PFS rate and prolonged PFS time in HPV-positive oropharyngeal carcinoma patients.
Adult ; Aged ; Aged, 80 and over ; Female ; Humans ; Male ; Middle Aged ; Carcinoma, Squamous Cell/virology* ; Human Papillomavirus Viruses/isolation & purification* ; Margins of Excision ; Oropharyngeal Neoplasms/virology* ; Papillomavirus Infections/virology* ; Prognosis ; Prospective Studies ; Robotic Surgical Procedures/methods*

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

This study aimed to investigate the effects of acupuncture on dynamic changes in Ca²⁺, Na⁺, and H₂O₂ flux following eccentric exercise-induced muscle injury. The total of 324 healthy male Wistar rats were randomly divided into 6 groups: control group (C), eccentric exercise group (E), eccentric exercise with acupuncture group (EA), EA with TRP channel blocker group (EAT), EA with NOX2 blocker group (EAN) and EA with placebo group (EAP). Gastrocnemius muscles were subject to lengthening contractions with percutaneous electrical stimulation, followed by immediate pretreatment with blocking agents. After 30 min, acupuncture needling was administered to the gastrocnemius muscle, and real-time dynamic changes of Ca²⁺, Na⁺ and H₂O₂ flux were measured with non-invasive micro-test technique during the needle retention period, immediately, 3 h, 6 h, and 24 h post-extraction respectively. Results showed that compared with the E group, acupuncture significantly increased net Ca²⁺ efflux (P < 0.05), extended the period of net Na⁺ influx, and significantly decreased net H₂O₂ efflux (P < 0.05). However, these effects were significantly attenuated in the EAT and EAN groups, where excessive net H₂O₂ efflux was observed (P < 0.001). These findings indicate that acupuncture regulates the dynamic changes of Ca²⁺, Na⁺ and H₂O₂ flux by activating the TRP channels and interacting with NOX2 activity following eccentric exercise-induced skeletal muscle injury.
Animals ; Muscle, Skeletal/metabolism* ; Rats, Wistar ; Rats ; Male ; Calcium/metabolism* ; Hydrogen Peroxide/metabolism* ; Physical Conditioning, Animal ; Sodium/metabolism* ; Acupuncture Therapy ; NADPH Oxidase 2

In this study, we constructed a GLP-2R-HEK293 cell line and established a method for the determination of the in vitro biological activity of teduglutide based on HTRF, after optimizing experimental conditions and methodological verification. We also carried out relative potency detection of teduglutide pharmaceutical products using this method. The result showed that there was a quantitative-efficient relationship between the teduglutide activity and cAMP contents in GLP-2R-HEK293 cells, which conformed to four-parameter model. Method verification results of five concentrations of teduglutide (64%, 80%, 100%, 125% and 156%) met the requirements of the General Rules of Chinese Pharmacopoeia, 2020 edition, Volume IV (9401). We then analyzed the relative potency of three batches of teduglutide drug substances and three batches of drug products. The linearity, regression and parallelism of the obtained curves all fit the system suitability requirements. The relative potency of six batches of teduglutide was from 83% to 105%. In summary, the biological activity detection method established in this study was accurate, precise, simple and time-saving, which can be used for quality control of teduglutide pharmaceutical products.

ObjectiveTo explore the characteristics of traditional Chinese medicine （TCM） syndromes in the patients with concurrent knee osteoarthritis （KOA） and postmenopausal osteoporosis （PMOP） and provide a scientific basis for precise TCM syndrome differentiation， diagnosis， and treatment of such concurrent diseases. MethodsA prospective， multicenter， cross-sectional clinical survey was conducted to analyze the characteristics of TCM syndromes in the patients with concurrent PMOP and KOA. Excel 2021 was used to statistically analyze the general characteristics of the included patients. Continuous variables were reported as x¯±s， and binary variables were reported as percentages. UCINET and Gephi were used to construct a complex "isease-syndrome-symptom" network for in-depth mining. Topological structure indicators， edge connection information between nodes， and weighted adjacency matrices were calculated by UCINET and Python. Gephi was used for complex network visualization. ResultsA total of 157 patients with concurrent PMOP and KOA from 12 TCM hospitals or community health service centers were selected for the collection of TCM syndrome and symptom information. A total of 4 main TCM syndromes were obtained， which were kidney-Yang deficiency （47.13%）， liver-kidney Yin deficiency （36.94%）， spleen-kidney Yang deficiency （8.92%）， and kidney Yin-Yang deficiency （7.01%）. In addition， 10 concurrent syndromes （mainly Qi stagnation and blood stasis， Qi and blood deficiency， spleen Yang deficiency， and cold-dampness） were identified. Based on the results of comprehensive frequency statistics and complex network analysis， as well as TCM theoretical knowledge and relevant guidelines， the general characteristics of concurrent PMOP and KOA and the main TCM syndromes in the dimensions of physical symptoms， pain， tongue and pulse manifestations， and defecation and urination were obtained. ConclusionThe main TCM syndromes in the patients with concurrent PMOP and KOA may be kidney Yang deficiency， liver-kidney Yin deficiency， spleen-kidney Yang deficiency， and kidney Yin-Yang deficiency， among which kidney Yang deficiency and liver-kidney Yin deficiency are the core TCM syndromes.