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 explore the safety and feasibility of 5G remote robot-assisted thoracoscopic anatomic lobectomy and segmentectomy. Methods A retrospective analysis was conducted on patients who underwent 5G remote robot-assisted thoracoscopic anatomic lobectomy or segmentectomy between July and September 2024. The surgeries were performed collaboratively by Shanghai Chest Hospital, Affiliated Hospital of Yangzhou University, and The First Affiliated Hospital of Nanchang University. Perioperative outcomes were recorded and analyzed. Results Ten patients were included, comprising 4 anatomic lobectomies and 6 segmentectomies. The median age was 61.0 (56.0, 72.0) years. The median intraoperative bi-directional network latency was 52.5 (39.0, 54.0) ms. There were no instances of network interruption, robot-related adverse events, or conversions to open thoracotomy. The median postoperative chest tube drainage volume was 500.0 (375.0, 600.0) mL, and the median hospital stay was 5.5 (4.0, 6.0) days. No complications of Clavien-Dindo grade Ⅱor higher occurred. All patients were recurrence-free and alive during the 6-month postoperative follow-up period. Conclusion 5G remote robot-assisted thoracoscopic surgery demonstrates high safety and operational stability. This technology shows promising potential for clinical application and is worthy of further development and utilization.

Background: Visceral white adipose tissue (vWAT) inflammation is a critical pathology of obesity-caused heart damage and is closely associated with adipocyte endoplasmic reticulum (ER) dysfunction. Serine (or cysteine) peptidase inhibitor, clade A, member 3C (Serpina3c) has been identified as an adipokine with anti-vWAT inflammatory effects. However, it remains unclear whether Serpina3c deficiency promotion of vWAT inflammation involves adipocyte ER dysfunction and whether it further contributes to heart damage in obesity. Methods: Wild type and Serpina3c knockout (Serpina3c–/–) mice were fed a high-fat diet (HFD) for 12 weeks. An adeno-associated virus (AAV) was injected locally into epididymal white adipose tissue (eWAT) of Serpina3c–/– mice to induce eWAT-adipocyte- specific overexpression of Serpina3c (AAV-Serpina3c) or knockdown of hypoxia-inducible factor 1α (AAV-shHIF1α). In vitro experiments were performed in 3T3-L1 adipocytes. Results: Serpina3c–/– mice exhibited more severe eWAT, serum and heart inflammation after HFD feeding. Consistently, these adverse phenotypes were mitigated in AAV-Serpina3c and AAV-shHIF1α mice. Mechanistically, ER oxidoreductase 1α (Ero1α) and protein disulfide isomerase (PDI) family members PDIA3 and PDIA4 were found to be target genes of HIF1α. In the obese mice, Serpina3c deficiency caused adipocyte more hypertrophy, and activated HIF1α-Ero1α/PDI mediated ER overoxidation and ER stress in eWAT. Subsequently, this led to increased adipocyte apoptosis and chemokine production and decreased adiponectin expression, which promoted macrophage infiltration and M1 polarization in eWAT, thus exacerbating eWAT inflammation and ultimately facilitating serum and distal heart inflammation. Conclusion These findings indicate that Serpina3c is a significant regulator of adipocyte ER redox homeostasis, thus highlighting Serpina3c as a potential therapeutic target for obesity-related eWAT inflammation and heart damage.

To explore the regulatory mechanism of drought stress on the synthesis of chlorogenic acid and luteoloside in Lonicera japonica, we designed five drought gradients (soil water contents of 30%, 24%, 17%, 14%, and 10%) and screened and verified the differentially expressed genes (DEGs) by RNA sequencing (RNA-seq) and reverse transcription quantitative polymerase chain reaction (RT-qPCR). Furthermore, we employed HPLC to systematically measure the content changes of chlorogenic acid and luteoloside. The results revealed that drought significantly reduced the accumulation of secondary metabolites, and severe drought led to more obvious reductions. Under extreme drought (soil water content of 10%), the content of chlorogenic acid and luteoloside decreased significantly to 25.73 mg/g and 11.33 mg/g (with the decrease rates of 37.85% and 9.58%, respectively). A total of 77 454 genes were identified via transcriptome analysis, among which the number of DEGs reached 1 128 under the extraordinary drought. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses revealed that the DEGs were mainly involved in flavonoid synthesis, secondary metabolite biosynthesis, plant hormone signal transduction and the plant-pathogen interaction pathways, and the expression of key genes regulating the synthesis of chlorogenic acid and luteoloside was significantly downregulated. RT-qPCR verified the accuracy of the RNA-seq data. This study revealed that drought stress reduced the content of chlorogenic acid and luteoloside, the main secondary metabolites, by inhibiting the expression of key genes in the secondary metabolism pathways. The findings provide candidate gene resources for molecular breeding of drought-tolerant Lonicera japonica.
Lonicera/physiology* ; Chlorogenic Acid/metabolism* ; Droughts ; Stress, Physiological ; Gene Expression Regulation, Plant ; Glucosides/metabolism* ; Luteolin

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.

OBJECTIVES: Color doppler flow imaging (CDFI) and cone-beam computed tomography (CBCT) were utilized to evaluate changes in mucosal vascular parameters and the osteogenic effects following guided bone regeneration (GBR) in the maxillary anterior region using trapezoidal or modified triangular flaps. METHODS: Patients undergoing single maxillary anterior dental implant surgery with GBR were randomly allocated into two groups: a trapezoidal flap group and a modified triangular flap group. After GBR surgery, the mucosal vascular parameters at the surgical site were assessed at various time intervals (preoperative, 2 h, 1 and 3 days, and 1, 2, and 4 weeks postoperative) using CDFI. In addition, the effects of bone augmentation were evaluated through the analysis of CBCT images obtained preoperatively, 2 h, and 6 months postoperative. RESULTS: The buccal mucosa in the edentulous area had a lower blood flow rate than the corresponding tooth in the same jaw, and the difference was statistically significant (P<0.001). The mucosal blood flow rate in the surgical area increased compared with that in the preoperative period. The peak flow rate was recorded at 2 weeks postoperatively and then decreased to levels comparable to those of the reference tooth. A statistically significant difference was observed between the two groups (P<0.05). The buccal alveolar ridge width of the implant platform was reduced by (1.3±0.9) mm in the trapezoidal flap group and (0.9±0.7) mm in the modified triangular flap group, respectively, at 6 months postoperatively, compared with 2 h postoperative. The buccal alveolar ridge width of the 5 mm from the implant platform was reduced by (0.9±0.6) mm and (0.3±0.6) mm, respectively. The buccal alveolar ridge width of the 10 mm from the implant platform was reduced by (0.6±0.8) mm and (0.2±0.6) mm, respectively. The height of the alveolar ridge was reduced by (1.9±1.4 ) mm and (1.4±1.3) mm. The change in graft volume was (136±78 ) mm³ and (114±85) mm³. However, the differences between the two groups were not statistically significant (P>0.05). CONCLUSIONS When a tooth is missing, blood flow to the buccal mucosa on the side of the missing tooth is reduced. The modified triangular flap group demonstrated superior microcirculation of blood flow in the operative area after GBR of the maxillary anterior teeth. Trapezoidal and modified triangular flaps achieved the anticipated bone augmentation during bone augmentation surgery in the maxillary anterior region, with no considerable effect on the changes in alveolar bone size parameters.
Humans ; Surgical Flaps/blood supply* ; Bone Regeneration ; Mouth Mucosa/blood supply* ; Cone-Beam Computed Tomography ; Osteogenesis ; Maxilla/surgery* ; Male ; Female ; Guided Tissue Regeneration, Periodontal/methods*

Aim To investigate the effect of Senecio scandens Buch.-Ham on inflammatory pain mediated by mast cell P2X7 receptor.Methods Using the ATP-induced foot inflammatory pain,immunofluores-cence and toluidine blue staining techniques were used to investigate whether Senecio scandens has inhibitory effect on P2X7 receptor on mast cells.Using the calci-um ion imaging experimental technology,to explore whether Senecio scandens inhibit the intracellular cal-cium ion enrichment caused by activation of P2X7 re-ceptor on mouse peritoneal mast cell.The whole-cell patch clamp technique was used to investigate whether senecio scandens could inhibit the inward current in-duced by activation of P2X7 receptor on mouse perito-neal mast cell.Results In vivo,Senecio scandens alle-viate ATP induced inflammatory pain(3.9 g·kg-1:P＜0.05),and significantly inhibited the infiltration of P2X7 receptor-positive mast cells(3.9 g·kg-1:P＜0.05).Knockout of mast cell can reduce the analgesic effect of Senecio scandens(3.9 g·kg-1:P=0.645).In vitro.The experiment results show that senecio scandens can significantly inhibit the calcium influx(300 mg·L-1:P＜0.05;1 g·L-1:P＜0.01;3 g·L-1:P＜0.01)and the inward current mediated by P2X7 receptor in mast cell(1 g·L-1:P＜0.01).Conclusion Senecio scandens alleviate inflammatory pain by inhibiting mast cell P2X7 receptor.

Objective:To investigate exercise fear condition and its influencing factors in patients with coronary heart dis-ease(CHD)involving in phase Ⅱ cardiac rehabilitation after percutaneous coronary intervention(PCI).Methods:Conven-ience sampling was performed among cardiac rehabilitation patients from a Shanxi grade-A tertiary hospital between Janu-ary 2023 and June 2023.General data questionnaire,Tampa Scale for Kinesiophobia-Short Version for Heart patients(TSK-SV H),the Multidimensional Scale of Perceived Social Support(MSPSS)and the Post Percutaneous Coronary In-tervention Health Literacy Scale(PPCIHLS)were used for assessment.Pearson and Spearman rank correlation analyses were applied to investigate the relationships between social support factors and health literacy factors with patients'fear of exercise;multivariate linear regression models and quantile regression models were used to analyze the influencing factors of fear of exercise.Results:Among the 118 patients,average TSK-SV H score was(33.78±3.79)points;10.2％patients showed significant fear.The correlation analysis showed that PPCIHLS score was negatively correlated with TSK-SV H score(r=-0.423,P＜0.001).Results from multivariate regression analysis indicated that health literacy,cardiac func-tion class and drinking status affected the average score of exercise fear(P＜0.05 all).The quantile regression model pro-vided additional insights,showing that the impact of factors such as living situation,drinking status,cardiac function class and health literacy on exercise fear varied across different quantiles.Notably,cardiac function class had a consistently posi-tive effect on TSK-SV H score at various quantiles.Conclusion:Improving health literacy and tailored rehabilitation plans are vital to reduce exercise fear and improve cardiac rehabilitation effect.