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.

To summarize the clinical characteristics, antibody spectrum and neuroelectrophysiological features of autoimmune nodopathy(AN), and to explore the phenotypic differences among different antibody-positive subgroups.

ObjectiveTo explore the regulatory effects and mechanisms of Astragali Radix polysaccharide （APS） on inhibitor of differentiation1 （ID1） and protein kinase B （Akt） in gastric cancer. MethodsImmunohistochemical staining was used to detect the expression of ID1 and Akt in 61 gastric cancer tissue samples and 20 adjacent normal gastric tissue samples. Immunofluorescence was used to detect the localization of ID1 and Akt. The effects of APS at the concentrations of 0.625， 1.25， 2.5， 5， 10， 20 mg·L^-1 on the proliferation of gastric cancer MGC-803 cells were examined by the cell counting kit-8（CCK-8） method and the colony formation assay. The target information of APS was retrieved from the Traditional Chinese Medicine Systems Pharmacology and Analysis Platform and Swiss Target Prediction. Keywords such as gastric cancer， gastric tumor， and stomach cancer were searched against GeneCards， UniProt， DisGeNET， and Online Mendelian Inheritance in Man （OMIM） for the screening of gastric cancer-related targets. The online tool jvenn was used to create the Venn diagram to identify the common targets， and STRING and Cytoscape were used to construct the protein-protein interaction network. Gene Ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analyses were conducted via R 4.2.2 to predict the potential roles of APS in the development of gastric cancer. The cell scratch assay was employed to assess the effect of APS on the migration of MGC-803 cells. The protein and mRNA levels of ID1 and Akt in the cells treated with APS were determined by Western blot and Real-time PCR， respectively. ResultsCompared with the adjacent normal gastric tissue， the gastric adenocarcinoma tissue showed increased positive expression of ID1 （χ² =81.00， P<0.01）. Immunofluorescence detection showed that ID1 and Akt were mainly located in the cytoplasm of gastric adenocarcinoma cells. Bioinformatics analysis identified 14 common genes shared between APS and gastric cancer. The average degree of protein-protein interaction network nodes was 14.29. GO and KEGG pathway enrichment results showed that ID1 and Akt were significantly enriched in the Rap1 and phosphatidylinositol-3-kinase （PI3K） /Akt signaling pathways. Cell experiments demonstrated that 5-fluorouracil （0.1 mg·L^-1） and APS （10， 20 mg·L^-1） groups showed decreased cell proliferation， migration， and colony formation. Compared with the control group， 10， 20 mg·L^-1 APS inhibited the proliferation of MGC-803 cells （P<0.01）， with 10 mg·L^-1 APS demonstrating stronger inhibitory effect. In addition， APS at 10， 20 mg·L^-1 inhibited the migration （P<0.01） and colony formation （P<0.05， P<0.01） of MGC-803 cells. Compared with the control group， APS at 10， 20 mg·L^-1 down-regulated the protein levels of ID1 （P<0.01） and Akt （P<0.05） and the mRNA levels of ID1 （P<0.05， P<0.01） and Akt （P<0.05， P<0.01） in MGC-803 cells. ConclusionID1 and Akt are highly expressed in the gastric adenocarcinoma tissue， which may be related to the development of gastric cancer. APS can down-regulate the protein and mRNA levels of ID1 and Akt to exert anti-tumor effects， which is expected to provide new therapeutic targets for gastric cancer treatment.

Gouty arthritis （GA） is an inflammatory disorder caused by monosodium urate （MSU） crystal deposition， accompanied by elevated oxidative stress and aberrant release of inflammatory cytokines， resulting in joint tissue damage and intense pain. Nuclear factor E₂-related factor 2 （Nrf2）， a key transcription factor regulating the antioxidant defence system， exerts cytoprotective effects through dissociation from Kelch-like ECH-associated protein 1 （Keap1） and activates downstream antioxidant response element （ARE）-mediated pathways. It can upregulate the expression of heme oxygenase-1 （HO-1）， NADH quinone oxidoreductase 1 （NQO1）， superoxide dismutase （SOD）， and glutathione transferase （GST） to preserve redox homeostasis. Moreover， Nrf2 can suppress activation of NOD-like receptor protein 3 （NLRP3） inflammasomes， reduce pro-inflammatory cytokine production and release， modulate nuclear factor-κB （NF-κB） transcriptional activity， regulate gut microbiota balance， enhance mitophagy， and inhibit apoptosis， so as to reduce joint inflammation and pain and promote body recovery. This review systematically examined recent advancements in traditional Chinese medicine （TCM） for GA prevention and treatment via regulating the Nrf2 signaling pathway. It delineated Nrf2's molecular mechanisms and its role in GA pathogenesis and elucidated how TCM intervenes in multiple pathways including Keap1/Nrf2/ARE， Nrf2/HO-1（NQO1）， and Nrf2/NF-κB/NLRP3 to exert therapeutic effects. The study demonstrated that TCM monomers and compounds effectively counteract oxidative damage， attenuate inflammatory responses， promote autophagy， and inhibit apoptosis via regulating the Nrf2 signaling pathway. These findings not only clarify the scientific basis of TCM in GA treatment but also offer strategic insights for developing novel Nrf2-targeted anti-gout drugs.

Objective To evaluate the clinical characteristics of human immunodeficiency virus (HIV) infected patients with peripheral lung masses (PLMs), and to assess the diagnostic utility of contrast-enhanced ultrasound (CEUS) in differentiating benign and malignant PLMs. Methods A retrospective analysis was performed on the clinical data of 69 patients with PLM treated in Shanghai Public Health Clinical Center from January 2020 to December 2023. All patients underwent percutaneous biopsy, and were categorized into benign group (n＝36) and malignant group (n＝33). 25 patients were HIV-positive and 44 patients were HIV-negative. The clinical features and CEUS parameters in patients were compared across these groups. Results Patients with malignant masses were significantly older than those with benign masses (P＜0.05). In the malignant group, HIV-negative patients exhibited significantly larger tumor diameters compared to HIV-positive patients (P＜0.05); in the HIV-positive patients, no significant difference in tumor size was observed between benign and malignant masses. 19 patients underwent CEUS. 10 malignant masses, irrespective of HIV status (10 positive and 9 negative), commonly presented with indistinct margins, delayed enhancement, heterogeneous perfusion, and delayed peak enhancement on CEUS. 9 benign masses showed earlier peak enhancement compared to 10 malignant masses (P＜0.05); no significant differences were observed in the initiation and washout time of enhancement between benign and malignant masses. In HIV-positive patients, 5 benign masses frequently demonstrated discrepancies between CEUS findings and pathological results. Conclusions The clinical and CEUS characteristics were different between benign and malignant PLMs. However, CEUS shows limited accuracy in distinguishing benign and malignant PLMs, underscoring the need for pathological confirmation.

BackgroundAttention deficit hyperactivity disorder （ADHD） is a neurodevelopmental disorder characterized by age-inappropriate inattention， excessive activities incongruous with setting， and emotional impulsivity. Subthreshold ADHD （sADHD） is clinically defined as the presence of ADHD symptoms that do not meet the full diagnostic criteria for ADHD. Children with sADHD exhibit deficits in executive function， demonstrate more conduct， learning， and anxiety-related problems compared to typically developing children， and show even poorer working memory performance than children diagnosed with ADHD. Currently， there is limited epidemiological research on sADHD in China， with few studies simultaneously investigating the prevalence of both ADHD and sADHD in children. ObjectiveTo investigate the prevalence of ADHD and sADHD among children aged 6–13 years in Chongqing， analyzing their distribution characteristics within this population， with the aim of providing references for developing preventive measures against both ADHD and sADHD. MethodsFrom October to November 2023， a total of 3 398 students in grades 1–6 from six primary schools in Jiangbei District， Chongqing were selected using a stratified cluster random sampling method. The occurrence of ADHD and sADHD was evaluated by using the short version （18-item version） of the Swanson， Nolan， and Pelham IV rating scales （SNAP-IV） and the Chinese vision of Schedule for Affective Disorder and Schizophrenia for School-aged Children-Present and Lifetime Version （K-SADS-PL）. ResultsThe ADHD detection rate among children in Chongqing was 1.90% （95% CI： 0.014–0.024）. Boys showed a significantly higher ADHD detection rate than girls （χ²=7.733， P=0.005）. No statistically significant differences were found in ADHD detection rates across different grades or age groups （χ²=7.347， 12.362， P>0.05）. The sADHD detection rate was 6.32% （95% CI： 0.054–0.072）. Similarly， boys exhibited significantly higher sADHD detection rates than girls （χ²=21.005， P<0.01）. Significant differences emerged across different grades （χ²=20.559， P=0.001）， while no statistically significant difference was observed in age groups （χ²=12.070， P=0.060）. ConclusionThe ADHD detection rates were comparable across all grade levels and age groups from 6–13 years old. Second-grade children demonstrated notably higher sADHD rates compared to other grades， while boys demonstrated higher prevalence rates than girls for both ADHD and sADHD. ［Funded by Science and Health Joint Medical Research Project in Jiangbei District， Chongqing City in the Second Half of 2023 （number， 2023JBKWLH022）］

This research study focuses on addressing the limitations of current neuropathic pain(NP)treatments by developing a novel dual-target modulator,E0199,targeting both Nav1.7,Nay1.8,and Nay1.9 and Kv7 channels,a crucial regulator in controlling NP symptoms.The objective of the study was to synthesize a compound capable of modulating these channels to alleviate NP.Through an experimental design involving both in vitro and in vivo methods,E0199 was tested for its efficacy on ion channels and its therapeutic potential in a chronic constriction injury(CCI)mouse model.The results demonstrated that E0199 significantly inhibited Nav1.7,Nav1.8,and Nav1.9 channels with a particularly low half maximal inhibitory concentration(ICs0)for Nay1.9 by promoting sodium channel inactivation,and also effectively increased Kv7.2/73,Kv7.2,and Kv7.5 channels,excluding Kv7.1 by promoting potassium channel acti-vation.This dual action significantly reduced the excitability of dorsal root ganglion neurons and alle-viated pain hypersensitivity in mice at low doses,indicating a potent analgesic effect without affecting heart and skeletal muscle ion channels critically.The safety of E0199 was supported by neurobehavioral evaluations.Conclusively,E0199 represents a ground-breaking approach in NP treatment,showcasing the potential of dual-target small-molecule compounds in providing a more effective and safe thera-peutic option for NP.This study introduces a promising direction for the future development of NP therapeutics.

Ferroptosis of chondrocytes is a significant contributor to osteoarthritis(OA),for which there is still a lack of safe and effective therapeutic drugs targeting ferroptosis.Here,we screen for anti-ferroptotic drugs in Food and Drug Administration(FDA)-approved drug library via a high-throughput manner in chondrocytes.We identified a group of FDA-approved anti-ferroptotic drugs,among which vitamin K showed the most powerful protective effect.Further study demonstrated that vitamin K effectively inhibited ferroptosis and alleviated the extracellular matrix(ECM)degradation in chondrocytes.Intra-articular injection of vitamin K inhibited ferroptosis and alleviated OA phenotype in destabilization of the medial meniscus(DMM)mouse model.Mechanistically,transcriptome sequencing and knockdown experiments revealed that the anti-ferroptotic effects of vitamin K depended on growth arrest-specific 6(Gas6).Furthermore,exogenous expression of Gas6 was found to inhibit ferroptosis through the AXL receptor tyrosine kinase(AXL)/phosphatidylinositol 3-kinase(PI3K)/AKT serine/threonine kinase(AKT)axis.Together,we demonstrate that vitamin K inhibits ferroptosis and alleviates OA progression via enhancing Gas6 expression and its downstream pathway of AXL/PI3K/AKT axis,indicating vitamin K as well as Gas6 to serve as a potential therapeutic target for OA and other ferroptosis-related diseases.

Liposomes serve as critical carriers for drugs and vaccines,with their biological effects influenced by their size.The microfluidic method,renowned for its precise control,reproducibility,and scalability,has been widely employed for liposome preparation.Although some studies have explored factors affecting liposomal size in microfluidic processes,most focus on small-sized liposomes,predominantly through experimental data analysis.However,the production of larger liposomes,which are equally significant,remains underexplored.In this work,we thoroughly investigate multiple variables influencing liposome size during microfluidic preparation and develop a machine learning(ML)model capable of accurately predicting liposomal size.Experimental validation was conducted using a staggered herringbone micromixer(SHM)chip.Our findings reveal that most investigated variables significantly influence liposomal size,often interrelating in complex ways.We evaluated the predictive performance of several widely-used ML algorithms,including ensemble methods,through cross-validation(CV)for both lipo-some size and polydispersity index(PDI).A standalone dataset was experimentally validated to assess the accuracy of the ML predictions,with results indicating that ensemble algorithms provided the most reliable predictions.Specifically,gradient boosting was selected for size prediction,while random forest was employed for PDI prediction.We successfully produced uniform large(600 nm)and small(100 nm)liposomes using the optimised experimental conditions derived from the ML models.In conclusion,this study presents a robust methodology that enables precise control over liposome size distribution,of-fering valuable insights for medicinal research applications.