Objective:To prepare pullulan-spermine (PS)-poly (lactic-co-glycolic acid) (PLGA) nanoparticles (NPs) conjugated with CD3 antibody, and to investigate their effects on T cell proliferation and cytokine secretion.Methods:Purulan polysaccharide was sperminized to synthesize PS, hydrophobically modified, and then grafted with PLGA to synthesize PS-PLGA. Infrared spectroscopy and nuclear magnetic resonance hydrogen spectrum were used to characterize the structure of PS-PLGA. PS-PLGA NPs were prepared by ultrasonic dialysis method and then coupled with CD3 antibody to prepare PS-PLGA-CD3 NPs. The morphological features of PS-PLGA-CD3 NPs were observed by the transmission electron microscope. The particle sizes, Zeta potential and dispersive coefficient of the NPs were measured using the dynamic laser particle size analyzer. The amount of coupled CD3 antibody on the surface of the NPs was determined using quantitative fluorescence analysis method. The effects of 1, 10, 50, 100, and 200 μg/ml PS-PLGA-CD3 NPs on T-cell proliferation were determined using cell counting kit-8 method. The effects of 1, 10, 50, 100, 200 μg/ml PS-PLGA-CD3 NPs on secretion of interferon-γ (IFN-γ), interleukin-2 (IL-2), and tumor necrosis factor-β (TNF-β) by T cell were determined by enzyme-linked immunosorbent assay. Comparisons were made using independent sample t-test or one-factor analysis of variance. Results:Pullulan and PS showed strong absorption at 2 939 cm ?1, and PS had a weaker absorption peak at 3 384 cm ?1 than pullulan. The proton peaks of spermine appeared at chemical shifts of 1.25 to 1.50, 1.63, and 2.25 to 2.75. The characteristic peaks of PLGA appeared at chemical shifts of 1.50, 3.40, and 4.80 to 5.30. Compared to pullulan, the characteristic peaks of both PS and PLGA appeared in the corresponding intervals for PS-PLGA. The morphology of PS-PLGA-CD3 NPs with spermine substitution at 9.7% was all regular and circular, with a mean particle size of (173.3±24.5) nm, a Zeta potential of (?12.78±3.68) mV, the dispersive coefficient of 0.254±0.101, and the CD3 antibody mass fraction of (52.1±9.4) μg/mg. The differences in cell survival were statistically significant for PS-PLGA-CD3 NPs and PS-PLGA NPs, respectively, after co-incubation with T cell after 24, 48, and 72 h at concentrations of 50, 100, and 200 μg/ml, respectively (all P<0.05). The results of the three concentration comparisons after 24 h of co-incubation were [(129.8±23.1)% vs (95.5±8.9)%, (137.5±22.7)% vs (95.1±15.8)%, and (142.3±25.6)% vs (93.2±9.2)%]; and the results after 48 h were [(145.9±23.7)% vs (95.8±10.6)%, (149.3±23.5)% vs (94.9±16.3)%, and (161.2±26.9)% vs (91.5±8.3)%]; and the results after 72 h were [(147.6±20.1)% vs (95.9±17.8)%, (152.4±22.3)% vs (92.7±16.5)%, and (167.7±25.4)% vs (90.8±17.4)%]. The differences in the levels of IFN-γ, IL-2 and TNF-β were statistically significant (all P<0.05 or 0.01) at 50, 100 and 200 μg/ml concentrations for PS-PLGA-CD3 NPs and PS-PLGA NPs, respectively. For IFN-γ, the results of the comparison of the three concentrations were [(35.7±3.1) ng/ml vs (16.4±6.9) ng/ml, (67.3±5.2) ng/ml vs (19.6±2.8) ng/ml, and (79.0±4.2) ng/ml vs (19.3±2.3) ng/ml]; and for IL-2, the results were [(43.5±8.2) ng/ml vs (12.6±1.9) ng/ml, (53.5±7.8) ng/ml vs (15.8±3.3) ng/ml, and (64.0±8.2) ng/ml vs (17.4±3.8) ng/ml]; and for TNF-β, the results were [(108.4±18.9) pg/ml vs (40.8±1.3) pg/ml, (152.3±28.3) pg/ml vs (56.4±3.7) pg/ml and (185.0±33.6) pg/ml vs (81.6±10.2) pg/ml]. Conclusions:PS-PLGA-CD3 NPs are successfully prepared, which have the function of effectively promoting T cell proliferation and cytokine sectetion.

Proteolysis-targeting chimeras(PROTACs)represent a promising class of drugs that can target disease-causing proteins more effectively than traditional small molecule inhibitors can,potentially revolu-tionizing drug discovery and treatment strategies.However,the links between in vitro and in vivo data are poorly understood,hindering a comprehensive understanding of the absorption,distribution,metabolism,and excretion(ADME)of PROTACs.In this work,14C-labeled vepdegestrant(ARV-471),which is currently in phase Ⅲ clinical trials for breast cancer,was synthesized as a model PROTAC to characterize its preclinical ADME properties and simulate its clinical pharmacokinetics(PK)by estab-lishing a physiologically based pharmacokinetics(PBPK)model.For in vitro-in vivo extrapolation(IVIVE),hepatocyte clearance correlated more closely with in vivo rat PK data than liver microsomal clearance did.PBPK models,which were initially developed and validated in rats,accurately simulate ARV-471's PK across fed and fasted states,with parameters within 1.75-fold of the observed values.Human models,informed by in vitro ADME data,closely mirrored postoral dose plasma profiles at 30 mg.Furthermore,no human-specific metabolites were identified in vitro and the metabolic profile of rats could overlap that of humans.This work presents a roadmap for developing future PROTAC medications by elucidating the correlation between in vitro and in vivo characteristics.

Objective:To evaluate preoperative high-resolution thin-layer cervical enhanced CT used to predict the venous route of the submental flap reflux vein and its relationship with adjacent structures in order to guide the anatomical understanding and protection of submental flap in pharyngeal cancer surgery.Methods:Sixty consecutive patients with pharyngeal cancer who underwent submental flap repair surgery in our department from March 2022 to December 2024, as well as 60 patients who were accepted neck dissection suffering other cancers, were selected. Before surgery, high-resolution cervical enhanced CT scans were performed, and the position of the transverse section of the facial vein in the venous phase horizontal image gradually variation tendency was focused layer by layer. The direction and adjacent relationship of the submental flap reflux veins were determined and recorded. Combined with 60 patients with other head and neck tumors who underwent neck dissection in our department during the same period (a total of 120 cases, 240 sides), the classification and management of the draining veins of Fang′s mental flap were conducted. Type Ⅰ mainly drains into the internal jugular vein; Type Ⅱ mainly drains into the external jugular vein and Type Ⅲ mainly drains into the anterior jugular vein (often accompanied by an external jugular draining branch). The status and proportion of venous drainage were analyzed.Results:Vascular predictive coincidence rate was 98.3% (59/60) among the 60 patients with pharyngeal cancer. Only one patient was predicted to have a simple return to the external jugular vein. However, during the operation, in addition to the main return to the external jugular vein, a small portion also returned to the internal jugular vein. Submental flap reflux vessels were classified into three types based on intraoperative submental flap venous return in 60 cases of laryngopharyngeal cancer, in conjunction with the analysis of venous return patterns from 240 cervical CT scans. Type Ⅰ mainly refluxed to the internal jugular vein, accounting for 42.1%. Type Ⅱ mainly refluxed to the external jugular vein (47.9%). Type Ⅲ mainly refluxed to the anterior jugular vein (10.0%). The total detection rate of CT reading of 240 venous reflux was 98.7% (237/240). Vascular predictive coincidence rate was 97.9%(235/240).Conclusion:The detailed analysis of submental venous return vessels can accurately predict the direction of reflux veins and its surrounding areas by preoperative high-resolution enhanced CT scan. This provides reliable guidance for the anatomy and protection of the submental flap reflux veins during surgery.

Objective:To compare the survival outcomes of different subsequent treatment regimens in patients with locally advanced hypopharyngeal squamous cell carcinoma (HPSCC) who achieved partial response (PR) after neoadjuvant chemotherapy based on the gross tumor volume regression rate (GTVRR).Methods:This retrospective study included patients with locally advanced HPSCC treated at the Department of Head and Neck Surgery, Beijing Tongren Hospital, from January 2011 to December 2023. The cohort included 135 males and 3 females, aged from 35 to 77 years. All patients received 2-3 cycles of TPF regimen (paclitaxel+cisplatin+5-fluorouracil) neoadjuvant chemotherapy. Subsequent treatments included concurrent chemoradiotherapy or surgery combined with postoperative adjuvant radiotherapy. The impacts of different subsequent treatment modalities on the survivals and prognoses of patients were compared based on GTVRR thresholds of 50% and 70%. The χ 2 test was used to analyze influencing factors; survival analysis and intergroup comparisons were performed using the Kaplan-Meier method and Log-rank test; prognostic factors were assessed using univariate and multivariate Cox regression analyses. Results:The 5-year OS and PFS rates were 56.5% and 47.9%, respectively, while, the 10-year OS and PFS rates were 25.8% and 21.2%, respectively. The median OS was 75 months, and the median PFS was 48 months. The laryngeal function preservation rate for the entire cohort was 83.3%. The patients who underwent surgery combined with postoperative radiotherapy had significantly better OS and PFS outcomes than those treated with concurrent chemoradiotherapy ( P<0.05). Stratification based on GTVRR revealed that the surgery plus postoperative radiotherapy regimen was particularly effective for PR patients with a GTVRR of 30%-70%, showing significantly better OS and PFS compared to the concurrent chemoradiotherapy group ( P<0.05). Conclusion:The optimal subsequent treatment for PR-HPSCC may be surgery-based comprehensive treatment, particularly for patients with a GTVRR of 30%-70%. This study offers valuable insights for the stratified treatment of HPSCC, which could contribute to improving overall patient prognosis.

Malnutrition is one of the main complications for gastric cancer patients, with an incidence rate as high as 65% to 85%, severely affecting their quality of life and survival rate. This issue is particularly prominent during out-of-hospital treatment, as patients often lack nutritional knowledge and do not receive continuous nutritional management. Therefore, ensuring that patients continue to receive effective nutritional management after discharge is crucial. This study explored three primary models of nutritional management for gastric cancer patients after discharge: the multidisciplinary team collaboration model, three-level nutritional management model, and the Internet+ model. It also analyzed the shortcomings and challenges these models face in practice, with the aim of providing a reference for clinical work.

Objective To explore the correlation between systemic inflammatory response index(SIRI)and the prognosis of elderly heart failure(HF)patients.Methods A retrospective study was conducted on 300 elderly HF patients with complete medical records hospitalized in our de-partment from January to December 2022.During the follow-up period for 1 year in different ways,46 of them were lost,and 254 were finally included.Baseline data,complete blood count at admission,and results of auxiliary examinations,and medicine adherence after discharge were col-lected and recorded.According to the occurrence of major adverse cardiovascular events(MACE),the subjected patients were divided into a MACE group(96 cases)and a non-MACE group(158 cases).The baseline data and relevant examination indicators were compared between the two groups,and the relevant factors for the occurrence were analyzed by using logistic regression.ROC curve analysis was employed to assess the predictive value of SIRI for MACE occurrence.Results The MACE group had significantly advanced age,larger proportion of diabetes mellitus,higher neutrophil and platelet counts,and elevated D-dimer level,but lower standardized medication rate when compared with the non-MACE group(P＜0.05,P＜0.01).The SIRI level was obviously higher in the MACE group than the non-MACE group[1.70(1.13,2.33)vs 1.29(0.85,2.06),P=0.002].Multivariate logistic regression analysis showed that atrial fibrillation,standardized medi-cation,mononuclear cells,and SIRI were independent risk factors for the occurrence of MACE in elderly HF patients(P＜0.05,P＜0.01).ROC curve analysis indicated that the AUC value of SIRI in predicting the occurrence of MACE was 0.614(95％CI:0.544-0.683),with a sensitivity of 0.813 and a specificity of 0.437.Conclusion SIRI is significantly correlated with the occurrence of MACE in elderly HF patients,and has a certain predictive value for their prognosis.

In recent years，the incidence and prevalence of non-tuberculous mycobacterial（NTM）infections have been on the rise，posing a serious threat to public health and presenting significant challenges for disease management. Currently，the treatment outcomes for NTM disease are poor，one of the main reasons being the high resistance of NTM pathogens to various anti-mycobacterial drugs. Novel therapeutic strategies targeting the host rather than the NTM pathogens themselves may help improve cure rates and reduce mortality. This article summarizes the latest research findings on host factors related to the incidence of NTM disease，including age，pulmonary diseases，immune function，genetic factors and lifestyle，which aids in the early identification of high-risk populations and provides a theoretical basis for developing targeted prevention and treatment strategies and optimizing treatment plans.

Objective To investigate the correlation between platelet-to-albumin ratio(PAR)and occurrence of cerebral infarction after left atrial appendage closure(LAAC)in patients with non-valvular atrial fibrillation(NVAF).Methods A retrospective study was conducted on 259 NVAF patients undergoing LAAC in our department between 2019 and 2023.According to occurrence of cerebral infarction after LAAC or not,they were divided into a control group(241 cases)and a study group(18 cases).Their general data were collected,and Cox proportional hazards regression model was used to identify the risk factors for cerebral infarction.ROC curve was plotted to assess the predictive value of PAR for cerebral infarction in NVAF patients after LAAC,and the AUC value was calculated.Kaplan-Meier survival curve was drawn to analyze the incidence of cerebral infarction after LAAC in NVAF patients with different PAR values.Results The study group had significantly advanced age,higher SBP at admission,increased WBC,neutrophil,monocyte and platelet counts,longer thrombin time,elevated international normalized ratio(INR)and high-sensitivity C-reactive protein(hs-CRP)level,and higher PAR than the control group(P＜0.05,P＜0.01).Multivariate Cox regression analysis showed that PAR(HR=2.286,95％CI:1.182-4.420,P＜0.05)was an independent risk factor for cerebral infarction in NVAF patients after LAAC.ROC curve indicated that the AUC value of PAR in predicting cerebral infarction after LAAC in NVAF patients was 0.721(95％CI:0.586-0.856,P＜0.01),with an optimal cut-off value of 4.137,a sensitivity of 66.39％,and a specificity of 77.78％.Kaplan-Meier survival curve revealed that the higher the PAR value was,the higher the risk of cerebral infarction was(P＜0.01).Conclusion PAR is significantly correlated with cerebral infarction in NVAF patients after LAAC.The higher the PAR,the higher the risk of cerebral infarction,demonstrating its predictive value and being worthy of clinical promotion.

As an important setting for the administration of vaccinations, the reasonable setting up and standardized management of vaccination clinics will enhance immunization service quality, public satisfaction, and improve the vaccination rate to protect people′s health. In recent years, various provinces in China are continuously promoting the standardized construction and management of vaccination clinics. However, the level of standardization management remains unbalanced, and the capacity of vaccination services needs to be further improved. This paper reviews the standardized management process of vaccination clinics, summarizes the practice and achievements in various regions, and analyzes the challenges and issues during these processes, to provide reference for improving the standardized management level of vaccination clinics in the future.

Objective:To develop an artificial intelligence-based model for automated recognition of serum indices using machine vision and deep learning.Methods:This study was a cross-sectional study.Serum sample images were collected fromWest China Hospital of Sichuan University from September 21, 2020 to January 20, 2023 using the imaging device of the fully automated sample pre-processing system. A computer random number generator was used to randomly select one whole hour each day, and all serum sample images processed within that hour were included. After excluding samples with unqualified images and missing serum index results, a total of 5, 534 samples were included. These were divided into a training set and a test set in an 8∶2 ratio using Python random shuffle function, and 4, 458 samples were in the training set and 1, 076 samples were in the test set. After manual inspection, the serum regions were annotated using the MATLAB Image Labeler tool and converted into YOLO format, and a YOLO v5-based model was constructed for automatic serum region extraction. The actual values of lipemia index (L-index), hemolysis index (H-index), and icterus index (I-index) were measured using the automatic biochemical analyzerwith matched reagent kits. A serum index regression model was constructed based on the MobileNet v2 network using the PyTorch 1.10.0 framework. The grading performance of the model was evaluated using accuracy, Kappa coefficient, sensitivity, specificity, positive predictive value, and negative predictive value. Regression performance was assessed using root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R2), and Bland-Altman analysis.Results:The overall accuracy rates for grading L-index, H-index, and I-index were 98.88%, 95.26%, and 92.47%, respectively, with Kappa coefficients of 0.72, 0.72, and 0.59. For L-index, MAE was 5.11, RMSE was 9.77, and R2 was 0.78. For H-index, MAE was 5.18, RMSE was 8.99, and R2 was 0.89. For I-index, MAE was 1.13, RMSE was 3.01, and R2 was 0.71. Bland-Altman analysis showed that 95.5%, 95.1%, and 95.7% of the data points fell within the consistency intervals for L-index, H-index, and I-index, respectively.Conclusion:The study developed an artificial intelligence-based serum index regression modelto estimate serum indices with high efficiency and accuracy. It shows great potential for reducing laboratory costs, improving clinical testing efficiency, and promoting intelligent development in laboratory medicine.