Objective: This study characterizes the demographic and clinical profiles of patients undergoing unilateral biportal endoscopic spine surgery (UBE ESS) for lumbar decompression/discectomy at a tertiary hospital in Singapore. It examines service implementation across multiple senior surgeons, evaluates preliminary clinical outcomes, and describes the learning curve observed during early adoption among surgeons already experienced in minimally invasive spine surgery, benchmarked against international standards. In the context of increasing global uptake of endoscopic techniques, this work provides evidence to inform institutional adoption and surgeon training. This analysis forms part of a multi-paper series comparing surgeon experience and patient outcomes between conventional minimally invasive approaches and UBE ESS for lumbar decompression/discectomy. Methods: We conducted a retrospective review of 111 patients who underwent UBE lumbar decompression/discectomy at a public tertiary hospital between October 2022 and April 2024. Data on patient demographics, comorbidities, presenting symptoms, operative details, and clinical outcomes, including visual analogue scale (VAS) scores and 36-Item Short Form Health Survey (SF-36) health domains, were analyzed using appropriate statistical methods. Results: The mean patient age was 56.8 years, with a slight female predominance (54.1%). Statistically significant improvements were observed in VAS scores for both back and leg pain (p<0.05), alongside significant gains in SF-36 domains including physical functioning, bodily pain, vitality, and social functioning. Operative times decreased progressively with increasing case volume, consistent with the presence of a procedural learning curve. Conclusion UBE ESS for lumbar decompression/discectomy is a safe and efficacious technique that can be successfully adopted by spinal surgeons with prior minimally invasive surgical experience. Operative time demonstrates a meaningful reduction once the initial learning curve has been overcome. ESS provides a reproducible option for the treatment of degenerative lumbar spine disease in the tertiary hospital setting in Singapore, with outcomes comparable to established international benchmarks. Future work will include long-term follow-up of this patient cohort and direct comparison with conventional minimally invasive techniques in subsequent studies.

Objective: To analyze the current status and influencing factors for latent tuberculosis infection (LTBI) among the elderly in Nanchuan District, Chongqing Municipality, so as to provide a reference for developing targeted prevention and control measures and reducing the risk of tuberculosis incidence. Methods: From June to December 2024, a multi-stage random cluster sampling method combined with probability proportional to population size sampling was used to select residents aged ≥65 years from four townships (streets) in Nanchuan District as study participants. Demographic information, disease history, and history of close contact with tuberculosis were collected through a questionnaire survey. Tuberculin skin test (TST) was used to detect Mycobacterium tuberculosis infection. LTBI was defined as a mean induration diameter of ≥10 mm on the TST, with active pulmonary tuberculosis excluded. Factors affecting LTBI among the elderly were identified using a multivariable logistic regression model. Results: A total of 3 699 participants were surveyed, including 1 707 males (46.15%) and 1 992 females (53.85%). The median age was 71.00 (interquartile range, 8.00) years. There were 285 participants (7.70%) with pulmonary disease, 18 (0.49%) with immune system disease, 47 (1.27%) with a history of tuberculosis, and 17 (0.46%) with a history of close contact with tuberculosis. LTBI was detected in 628 participants, with a detection rate of 16.98%. Multivariable logistic regression analysis showed that elderly participants with senior high school education or above (OR=2.292, 95%CI: 1.508-3.484), those with immune system disease (OR=3.226, 95%CI: 1.240-8.393), and those with a history of tuberculosis (OR=4.797, 95%CI: 2.436-9.447) were significantly associated with a higher risk of LTBI. Conclusions The detection rate of LTBI among the elderly in Nanchuan District was relatively low. Educational level, immune system disease, and history of tuberculosis were influencing factors for LTBI risk in this population. It is necessary to strengthen health education, screening, and preventive interventions.

AIM To optimize the extraction process for total polyphenols from Conioselinum vaginatu(Spreng.)Thell.,make component analysis,and evaluate their anti-oxidant,hypoglycemic activities.METHODS The effects of ultrasound,enzymatic hydrolysis,acid hydrolysis,alcohol extraction and hydrolysis processes on the extraction quantity of total polyphenols were investigated,respectively.With extraction temperature,extraction time,ethanol concetration and liquid-solid ratio as influencing factors,extraction quantity of total polyphenols as an evaluation index,the extraction process was optimized by response surface method.HPLC was adopted in the identification of polyphenolic composition and determination of their contents.Subsequently,total polyphenols' scavenging capacities on DPPH,ABTS,OH free radicals,total reducing power and inhibitory capacity on α-glucosidase were determined.RESULTS The highest extraction quantity of total polyphenols was observable when extraction process was employed.The optimal conditions were determined to be 62 ℃ for extraction temperature,54 min for extraction time,69％for ethanol concentration,and 50∶1 for liquid-solid ratio,the extraction quantity of total polyphenols was(9.51±0.2)mg GAE/g.Seven constituents existed in C.vaginatu,among which ferulic acid demonstrated the highest content,followed by that of myricetin,while D-tryptophan content was the lowest.At the concentration of 7.61 mg/L,total polyphenols displayed the scavenging rates on DPPH,ABTS,OH free radicals of 80.70％,85.97％,28.60％,total reducing power of 0.22,and inhibition rate on α-glucosidase of 77.23％,respectively.CONCLUSION This stable and reliable method can be used for the extraction of total polyphenols from C.vaginatum with strong anti-oxidant,hypoglycemic activities.

AIM To prepare the borneol-menthol eutectic mixture-loaded nanoemulsion gel of tetramethylpyrazine.METHODS The equilibrium solubilities of tetramethylpyrazine in different oil phases,emulsifiers and co-emulsifiers were determined,after which compatibility experiment was performed,and pseudo-ternary phase diagram was drawn.With Km value,oil phase proportion and water phase consumption as influencing factors,particle size,PDI and saturated drug loading as evaluation indices,the formulation was optimized by central composite design-response surface method.The drug-loaded nanoemulsion was dispersed into carbomer 940 gel matrix to prepare nanoemulsion gel,then the physicochemical properties,in vitro drug release and transdermal absorption properties were investigated.RESULTS The optimal formulation was determined to be 3.31∶6.16∶1.56∶88.97 for eutectic mixture-EL-40-1,2-propylene glycol-water ratio,the particle size,PDI and saturated drug loading were 37.85 nm,23.04 and 5.82 mg/g,respectively.The obtained white,semi-solid nanoemulsion gel demonstrated the average pH value and viscosity of 6.68±0.07 and(289.69±1.06)mPa·s,respectively,whose in vitro drug release accorded with Higuchi equation,and the accumulative permeability per unit area was(2 048.23±55.6)μg/cm2 within 24 h,which were 3.72 and 1.21 times higher than those of hydrogel and aqueous solution,respectively.CONCLUSION The borneol-menthol eutectic mixture-loaded nanoemulsion gel of tetramethylpyrazine meets preparation requirements,thus can achieve the effective transdermal delivery of raw medicine.

″Boundarics in biomedicine″(or″Biomedical boundarics″)is an emerging frontier interdisciplinary subject that focuses on addressing key scientific issues related to the formation,identification,and evolution of biological boundaries within living organisms.In this field,the study of tumor boundaries is of particular importance.Imaging tumor boundaries not only helps to reveal the molecular mechanisms of tumor boundary evolution and interaction with the microenvironment,tumor invasion and metastasis,but is also crucial for clinical tumor diagnosis,treatment decision-making,efficacy monitoring and prognosis evaluation.Molecular probes,as functional substances that enhance imaging signals,play a crucial role in tumor boundary recognition.In this article,the basic concepts and research significance of boundarics in biomedicine and tumor boundarics in biomedicine were summarized firstly.Then a comprehensive review of the research progress in tumor boundary imaging molecular probes was provided,covering areas such as magnetic imaging,optical imaging,acoustic imaging,nuclear imaging,and multimodal imaging.The strategies to regulate the sensitivity,specificity,and safety of molecular probes through chemical structure modifications,conjugation with targeting ligands,and tumor microenvironment-responsive designs were emphasized.Finally,the research trends of molecular probes for tumor boundary imaging were analyzed,and the challenges faced in this field and the future research directions were discussed.

Under the current situation of "low prevalence and low infection" of schistosomiasis in China, and to provide a basis for achieving the goal of eliminating schistosomiasis by 2030 proposed by the Healthy China Action (2019 - 2030) as scheduled, the Hunan Provincial Corps Hospital of the Chinese People's Armed Police Force established a schistosomiasis monitoring and early warning index system based on the previous studies on schistosomiasis early warning index system and the recent literature analysis, combined with the current potential risk factors affecting the transmission and prevalence of schistosomiasis, and organized two rounds of expert consultation and carried out project promotion meetings. The experts reached a consensus on the comprehensiveness and practicability of the index system, aiming to lay a solid foundation for construction of China's schistosomiasis prevention and control early warning system.

Recent innovations in endoscopic techniques have dramatically transformed the landscape of biliary and pancreatic disease management,particularly through the synergistic integration of peroral choledochoscope-assisted cholangioscopy and endoscopic retrograde cholangiopancreatography(ERCP).This article delves into the clinical utility of peroral choledochoscope within the ERCP framework,highlighting its pivotal role in enhancing diagnostic precision.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

OBJECTIVE To analyze the blood components of Suanzaoren Decoction after oral administration using UHPLC-Q Exactive Orbitrap-MS technology.METHODS Female Sprague-Dawley(SD)rats were used as experimental subjects,and Suanza-oren Decoction was administered orally.Serum samples were collected,and the aqueous extract of Suanzaoren Decoction and the serum were analyzed using UHPLC-Q Exactive Orbitrap-MS technology to identify the prototype components and metabolites absorbed into the blood by comparing and analyzing with the LuMet-TCM database.RESULTS It showed that a total of 458 components were iden-tified in the aqueous extract of Suanzaoren Decoction,and 26 chemical components were identified in the blood,including 23 prototype components and 3 metabolites.CONCLUSION The prototype components absorbed into the blood discovered in this study may be the active ingredients of Suanzaoren Decoction,providing a reference for the research on the pharmacodynamic material basis of Suanza-oren Decoction.

Objective:To develop habitat radiomics models to predict early treatment responses to the hepatic arterial infusion chemotherapy (HAIC) combined with targeted therapy or immunotherapy in advanced hepatocellular carcinoma (HCC) patients, and to guide clinical diagnosis and treatment.Methods:From October 2021 to Decemeber 2023, at Army Characteristic Medical Center of PLA (Chongqing Daping Hospital) and the First Affiliated Hospital of Chongqing Medical University, 94 patients with advanced HCC who received HAIC combined with targeted therapy or immunotherapy were retrospectively enrolled. According to the treatment results, the patients were divided into response group and non-response group. Univariate and multivariate logistic regression were performed to analyze the clinical data of the patients. Based on contrast-enhanced CT images, tumor habitats were delineated and habitat features were extracted with k-means clustering, and the imaging features of arterial and venous phases were also extracted. The least absolute shrinkage and selection operator (LASSO) was used for dimensionality reduction. Feature selection was performed using LASSO to reduce dimensions, and then the selected features were further refined through stepwise logistic regression analysis.Binary logistic regression models were conducted to develop the habitat radiomics model, arterial phase radiomics model (APRM), venous phase radiomics model (VPRM), clinical data model, as well as the combination of radiomics model and clinical data model to predict early treatment (after 2 treatment cycles) response. Receiver operating characteristic curves (ROC) were plotted, and model performance was evaluated by the area under the curve (AUC), calibration curves, and decision curve. The models were validated through Bootstrap methods (1 000 times). DeLong test was used to compare AUC values.Results:The results of cluster analysis identified 3 characteristic habitats in HCC imaging: low-, medium-, and high-enhancement tumor habitats. The proportion of high-enhancement habitats was higher than that in the non-response group. A predictive model was established based on the proportions of these 3 habitats. Based on the proportion of low-, medium-, and high-enhancement habitats within the tumor, a habitat radiomics model was constructed. After LASSO selection and logistic regression analysis, 3 arterial phase and 3 venous phase radiomic features were selected to build the APRM and VPRM, respectively. Logistic regression analysis identified the following factors for the clinical data model: comorbidities ( OR=0.275, P=0.031), maximum tumor diameter ( OR=1.149, P=0.019), red blood cell count ( OR=0.463, P=0.022), alpha fetoprotein >400 μg/L ( OR=3.452, P=0.017), and tyrosine kinase inhibitor therapy ( OR=3.072, P=0.048). Among the single predictive model′s comparison, the AUC of habitat radiomics model was 0.860 (95% confidence interval(95% CI): 0.789 to 0.932), while those of the APRM、VPRM and clinical data model were 0.850 (95% CI: 0.773 to 0.926), 0.855 (95% CI: 0.782 to 0.928), and 0.774 (95% CI: 0.681 to 0.867), respectively, and there were no statistically significant among these models (all P>0.05). Among the combination models, the AUC of the habitat rediomic-clinical data combination model was 0.881 (95% CI: 0.814 to 0.947); the AUC of arterial phase rediomic-clinical data combination model was 0.897 (95% CI: 0.833 to 0.961); and the AUC of venous phase rediomic-clinical data combination model was 0.888 (95% CI: 0.826 to 0.951), but there were no statistically significant among the 3 models (all P>0.05). The calibration curve showed that the habitat rediomic-clinical data combination model had the most accurate predictive probability. Internal validation showed that the AUC of habitat rediomic-clinical data combination model was 0.848 (95% CI: 0.772 to 0.922), and the predictive performance was better than that of the clinical-data model (0.733 (95% CI: 0.670 to 0.863)). Conclusion:The habitat radiomics model based on enhanced CT can effectively predict early treatment responses to the HAIC combined with targeted therapy or immunotherapy in advanced HCC patients, which provides theoretical basis for individualized treatment in advanced HCC.