The underlying cause of low response rates to existing immunotherapies is that tumor cells dominate tumor immune escape through surface antigen deficiency and inducing tumor immunosuppressive microenvironment (TIME). Here, we proposed an in situ tumor cell engineering strategy to disrupt tumor immune escape at the root by restoring tumor cell MHC-I/tumor-specific antigen complex (MHC-I/TSA) expression to promote T-cell recognition and by silencing tumor cell CD55 to increase the ICOSL⁺ B-cell proportion and reverse the TIME. A doxorubicin (DOX) and dual-gene plasmid (MAC pDNA, encoding both MHC-I/ASMTNMELM and CD55-shRNA) coloaded drug delivery system (LCPN@ACD) with tumor targeting and charge/size dual-conversion properties was prepared. LCPN@ACD-induced ICD promoted DC maturation and enhanced T-cell activation and infiltration. LCPN@ACD enabled effective expression of MHC-I/TSA on tumor cells, increasing the ability of tumor cell recognition and killing. LCPN@ACD downregulated tumor cell CD55 expression, increased the proportion of ICOSL⁺ B cells and CTLs, and reversed the TIME, thus greatly improving the efficacy of αPD-1 and CAR-T therapies. The application of this in situ tumor cell engineering strategy eliminated the source of tumor immune escape, providing new ideas for solving the challenges of clinical immunotherapy.

Mitochondrial DNA (mtDNA) acts as a damage-associated molecular pattern to activate the stimulator of interferon genes (STING) signaling in macrophages, promoting tissue inflammation. However, its role in acute myocardial infarction (AMI) remains unclear. Macrophage-specific Sting1 knockout mice were used to validate STING's pathological role in AMI. Cardiac and liver mtDNA were used to activate macrophages in co-culture systems with cardiomyocytes to assess fibrosis and hypertrophy. Panaxatriol saponin (PTS) was tested for its ability to block mtDNA-driven macrophage activation and subsequent cardiomyocyte damage. STING-PTS binding ability was analyzed. AMI rats received PTS to evaluate its effects on myocardial inflammation and ventricular remodeling. In vivo, macrophage-specific Sting1 knockout reduced myocardial inflammation and injury after AMI. In vitro, mtDNA-activated macrophages induced cardiomyocyte fibrosis and hypertrophy through STING signaling. PTS suppressed mtDNA-driven macrophage activation by directly binding STING, thereby blocking inflammatory cascades. In AMI rats, PTS treatment attenuated acute inflammation and reversed ventricular remodeling. These findings establish the mtDNA-STING axis in macrophages as a critical driver of post-AMI inflammation and identify pharmacological STING inhibition with PTS as a promising therapeutic strategy. The study bridges genetic validation with translational applications, highlighting macrophage STING as a novel target for ischemic heart disease management.

With the rapid advancement of vaccines, the research and application of vaccine adjuvants have garnered significant attention. Despite the development of numerous vaccine adjuvants, their applications in human vaccines remain limited due to either insufficient efficacy or severe side effects. Consequently, there is growing interest in developing bioactive compounds derived from traditional Chinese medicines (TCMs) as vaccine adjuvants, owing to their natural biocompatibility, diversity, and safety. Here, we systematically review the current application status and potential value of TCM-based bioactive compounds in vaccine adjuvants. Firstly, we elaborate on the types and characteristics of active ingredients, such as polysaccharides, saponins, flavonoids, acids, and alkaloids. The mechanisms by which these compounds function as vaccine adjuvants are then discussed, including their roles in enhancing humoral immunity, cellular immunity, and relieving the immune suppression in the microenvironment. Additionally, we summarize the current strategies for structural modification and platform optimization to adapt to different application scenarios. Finally, we offer insights into the future development directions for these potential adjuvants, highlighting research priorities, technical approaches, and application prospects. In conclusion, natural vaccine adjuvants derived from TCMs present broad application prospects and hold promise for future vaccine development.

OBJECTIVES: We propose a novel deep learning segmentation algorithm (DSRF) based on multi-scale supervision and residual feedback strategy for precise segmentation of the optic chiasm and optic nerves in CT images of nasopharyngeal carcinoma (NPC) patients. METHODS: We collected 212 NPC CT images and their ground truth labels from SegRap2023, StructSeg2019 and HaN-Seg2023 datasets. Based on a hybrid pooling strategy, we designed a decoder (HPS) to reduce small organ feature loss during pooling in convolutional neural networks. This decoder uses adaptive and average pooling to refine high-level semantic features, which are integrated with primary semantic features to enable network learning of finer feature details. We employed multi-scale deep supervision layers to learn rich multi-scale and multi-level semantic features under deep supervision, thereby enhancing boundary identification of the optic chiasm and optic nerves. A residual feedback module that enables multiple iterations of the network was designed for contrast enhancement of the optic chiasm and optic nerves in CT images by utilizing information from fuzzy boundaries and easily confused regions to iteratively refine segmentation results under supervision. The entire segmentation framework was optimized with the loss from each iteration to enhance segmentation accuracy and boundary clarity. Ablation experiments and comparative experiments were conducted to evaluate the effectiveness of each component and the performance of the proposed model. RESULTS: The DSRF algorithm could effectively enhance feature representation of small organs to achieve accurate segmentation of the optic chiasm and optic nerves with an average DSC of 0.837 and an ASSD of 0.351. Ablation experiments further verified the contributions of each component in the DSRF method. CONCLUSIONS The proposed deep learning segmentation algorithm can effectively enhance feature representation to achieve accurate segmentation of the optic chiasm and optic nerves in CT images of NPC.
Humans ; Tomography, X-Ray Computed/methods* ; Optic Chiasm/diagnostic imaging* ; Optic Nerve/diagnostic imaging* ; Algorithms ; Nasopharyngeal Carcinoma ; Deep Learning ; Nasopharyngeal Neoplasms/diagnostic imaging* ; Neural Networks, Computer ; Image Processing, Computer-Assisted/methods*

Objective:To offset the shortage of traditional large-scale population surveillance and provide early-warning signals in the early stage of the outbreak of COVID-19, people in Chongqing had carried out severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) monitoring since 2023.Methods:After COVID-19 was managed with measures against Class B infectious diseases, we selected five sewage treatment plants with automatic sample collection facilities in four districts of the main city. Two samples of sewage from each sewage treatment plant were collected every week. Then SARS-CoV-2 from these samples was concentrated by aluminum hydroxide adsorption-precipitation, detected and analyzed by multiple real-time fluorescent RT-PCR.Results:From January 16 to December 31 of 2023, a total of 496 sewage samples were monitored, of which 285 samples were positive by SARS-CoV-2 nucleic acid assay, with a total detection rate of 57.46%. The detection rate of SARS-CoV-2 in weeks 3-5, 18-21 and 40-47 was 100.00%. The daily mean nucleic acid concentration of SARS-CoV-2 in sewage peaked in the 18th week, and then began to decline, entering a low level and fluctuated in epidemic period. The variable trend of daily mean concentration of SARS-CoV-2 nucleic acid was basically consistent with daily number of SARS-CoV-2 infected patients or SARS-CoV-2 positive rate in fever clinic counted by infectious disease monitoring system.Conclusions:The detection rate of SARS-CoV-2 in sewage of Chongqing is relatively high, especially in April to May, and sewage monitoring can indirectly reflect the status of COVID-19 infection.

Objective:To deeply explore the decision-making experience of patients participating in clinical trials of neoadjuvant immunotherapy for lung cancer.Methods:Using the descriptive and qualitative research, 15 lung cancer patients who participated in clinical trials of neoadjuvant immunotherapy at the Cancer Hospital of the Chinese Academy of Medical Sciences were selected by purposive sampling from April 2021 to August 2022 for semi-structured in-depth interviews. Content analysis method was used for data analysis, summarization, and induction.Results:Three themes were extracted, namely decision-making information dilemma (insufficient or overloaded information, difficulty in understanding professional information, urgent need for decision-making information assistance), complex emotional experience (negative emotional experience, positive emotional experience), and hope for multi-party support (expecting psychological communication, hoping for family understanding, and longing for social recognition) .Conclusions:The decision-making experience of patients in clinical trials of neoadjuvant immunotherapy for lung cancer were summarized and described, which can help strengthen the understanding of the research team and medical and nursing staff on the live experience of such patients when making decisions, provide targeted decision support strategies, and promote good informed consent of patients.

Objective To design a pH-sensitive nintedanib liposomes(Nb-Lips)which targeted the acidic microenvironment of pulmonary fibrosis.The entrapment efficiency(EE%)was optimized by the formulation process.Methods Nintedanib liposomes were prepared by membrane hydration method,and the formulation of nintedanib liposomes were optimized by single factor experiments and response surface method(RSM).The particle size,polymer dispersity index(PDI),Zeta potential and encapsulation rate was investigated by dynamic light scattering technique and microcolumn centrifugation method.The release behavior of nintedanib liposomes in artificial lung fluid with pH 7.4 and artificial lung fluid with pH 5.3 was investigated by dialysis method.Nintedanib liposomes were atomized with a compressed air atomizer and its atomization stability and aerodynamic particle size were investigated.Results The particle size of nintedanib liposomes was(100.651±7.315)nm,the PDI was(0.328±0.026),the zeta potential was(21.633±2.004)mV,and the encapsulation rate was higher than 80%.Compared with nintedanib solution at pH 7.4,the total release of nintedanib liposomes in pH 5.3 artificial lung solution was 60.78%higher,and the release of nintedanib liposomes in pH 5.3 artificial lung solution was 48h delayed,which was much higher than that of nintedanib solution.The data reveals no significant differences in particle size,potential and PDI before and after atomization of nintedanib liposomes,and the encapsulation rate decreased 4.25%.The fine particle fraction of the atomized droplets was 37.49%.Conclusion The response surface method can effectively improve the encapsulation rate of nintedanib liposomes,and successfully prepare nintedanib liposomes that are sensitive to acidic environment,and can be inhaled and released slowly.

Objective To establish diagnostic criteria for dampness syndrome through scientific and normative research methods.Methods The basis for syndrome differentiation of dampness syndrome was comprehensively integrated through literature research and structured tools,and in-depth investigation was carried out on the connotation and extension of dampness syndrome,judgment basis and criteria construction through questionnaire surveys and consensus conference method.Results Thirty-six items for syndrome differentiation of dampness syndrome were obtained through literature research.Through the questionnaire surveys,some experts suggested that the diagnosis mode of dampness syndrome should be in line with the clinical practice requirements.Accordingly,we were deep in thought about the key issue of"how to establish accurate diagnostic criteria".After in-depth investigation,we found that the dampness syndrome had specific and sensitive indicators.And 11 specific and 19 sensitive indicators were determined.Furthermore,according to the experts'suggestions,the specific indicators were classified into three categories based on dampness characteristics.Meanwhile,we investigated the diagnosis attributes of Chinese medicine syndromes and summarized them into four corresponding modes.Based on this,specificity mode and similarity/consistency mode should be adopted for diagnostic criteria for dampness syndrome.In addition,the judgment form in accord with the diagnostic attributes of dampness syndrome was determined.Conclusion This diagnostic criteria can provide a basis for the clinical diagnosis of dampness syndrome.Besides,this study explored the diagnostic attributes of Chinese medicine syndromes,which could provide reference for the development of other Chinese medicine syndrome criteria.

Objective To analyze the distribution characteristics of traditional Chinese medicine(TCM)syndrome types in patients with osteoporosis and the distribution differences of clinical and serological indicators in TCM syndrome types.Meth-ods A total of 69 patients with osteoporosis were collected from the Third Affiliated Hospital of Guangzhou University of Chinese Medicine and Qifu Hospital Affiliated to Jinan University.The general information,bone mineral density T value,fasting periph-eral venous blood in the morning were collected.The expression of telomerase protective factor 1(POT1),telomerase reverse transcriptase(TERT),serum 8-hydroxy-2'-deoxyguanosine(8-OHdG)and superoxide dismutase 2(SOD2)were detected by ELISA.Finally,the above data were statistically analyzed.Results There were significant differences in body weight,height,bone mineral density,POT1,TERT,and 8-OHdG among the four syndromes(P＜0.05).In terms of correlation,the relation-ship between bone mineral density and each parameter in different syndrome types was explored.The bone mineral density of qi stagnation and blood stasis syndrome was positively correlated with SOD2 value.There is a positive correlation between bone min-eral density and 8-OHdG in patients with Yin deficiency of liver and kidney.TERT was positively correlated with qi stagnation and blood stasis syndrome.Liver and kidney Yin deficiency syndrome was positively correlated with weight and bone mineral den-sity,and negatively correlated with TERT value.Weight was negatively correlated with qi and blood stasis syndrome.Conclusion In TCM syndrome differentiation of osteoporosis,there were statistical differences in weight,height,bone mineral density,ser-um POT1,TERT and 8-OHdG among Qi-stagnation and blood stasis,spleen-kidney Yang deficiency,liver-kidney Yin deficiency and Qi-blood-peace syndrome.In different syndrome types,serum SOD2 and 8-OHdG were the influencing factors of bone miner-al density.Serum TERT and 8-OHdG are the main factors affecting the dialectical classification of osteoporosis.

Although a great deal of research has been done on sepsis in children，its pathogenesis remains controversial and unresolved，one of which is immune dysfunction.Immunosuppression is the core part of immune dysfunction，and it is related to the disease progression，treatment options，and prognosis changes in patients with sepsis.Since T lymphocytes play a crucial role in immune function，they have been regarded as an important indicator for judging changes in immune function in clinical practice.This review explained the mechanism of immunosuppression caused by some T lymphocyte subsets and its clinical application value in the evaluation，prognosis and immune intervention of sepsis.