1.Polypeptide-based Nanocarriers for Oral Targeted Delivery of CAR Genes to Pancreatic Cancer
Feng XIN ; Jian REN ; Zhao-Zhen LI ; Quan FANG ; Rui-Jing LIANG ; Lan-Lan LIU ; Lin-Tao CAI
Progress in Biochemistry and Biophysics 2026;53(2):431-441
ObjectivePancreatic ductal adenocarcinoma (PDAC) exhibits a limited response to current treatments due to its dense fibrotic stroma and highly immunosuppressive tumor microenvironment. In recent years, advancements in cellular immunotherapy, particularly chimeric antigen receptor macrophage (CAR-M) therapy, have offered new hope for pancreatic cancer treatment. Although CAR-M therapy demonstrates dual potential in directly killing tumor cells and remodeling the immune microenvironment, it still faces challenges such as complex in vitro preparation processes and low in vivo targeting and delivery efficiency. Therefore, developing strategies for efficient and targeted in vivo delivery of CAR genes has become crucial for overcoming current therapeutic limitations. This study aims to develop an orally administrable nano-gene delivery system for the targeted delivery of CAR genes to pancreatic tumor sites. MethodsCore nano-gene particles (PNP/pCAR) were constructed by loading plasmid DNA encoding CAR (pCAR) with cationic polypeptides (PNP). Subsequently, PNP/pCAR was surface-modified with β-glucan to prepare the targeted nanoparticles (βGlus-PNP/pCAR). The loading efficiency of PNP for pCAR was quantitatively assessed by gel retardation assay. The particle size, Zeta potential, morphology, and storage stability of PNP/pCAR were characterized using a Malvern particle size analyzer and transmission electron microscopy. At the cellular level, RAW 264.7 macrophages were selected. The cytotoxicity of PNP/pCAR was evaluated using the CCK-8 assay. The cellular uptake efficiency and lysosomal escape ability of the nanoparticles were assessed via flow cytometry and confocal microscopy. Transfection efficiency was quantitatively evaluated by detecting the expression of the reporter gene GFP using flow cytometry. At the in vivo level, an orthotopic pancreatic cancer mouse model was established. Cy7-labeled βGlus-PNP/pCAR nanoparticles were administered orally, and the fluorescence distribution in mice was dynamically monitored at 1, 2, 4, 8, and 16 h post-administration using a small animal in vivo imaging system. Forty-eight hours after oral gavage, the mice were euthanized, and pancreatic tumor tissues were collected for further analysis of intratumoral fluorescence signals using the imaging system. Additionally, βGlus-PNP/pCAR-GFP nanoparticles loaded with the reporter gene (GFP) were administered orally. Forty-eight hours post-administration, pancreatic tumor tissues were harvested to prepare frozen sections, and GFP expression was observed and analyzed under a fluorescence microscope. ResultsThe PNP carrier exhibited a high loading capacity for pCAR. The successfully prepared PNP/pCAR nanoparticles were regular spheres with a hydrodynamic diameter of approximately (120±10) nm and a Zeta potential of about +(6±1) mV. They maintained good structural stability after incubation in PBS buffer for 7 d. Cell experiments demonstrated that PNP/pCAR exhibited no significant cytotoxicity in RAW 264.7 cells while being efficiently internalized and effectively escaping lysosomal degradation. The transfection positive rate of PNP/pCAR-GFP in RAW 264.7 cells reached (25±3)%, surpassing that of Lipofectamine 2000-loaded pCAR-GFP (Lipo/pCAR-GFP), which was (20±1)%.In vivo experiments revealed that, compared to unmodified PNP/pCAR, βGlus-PNP/pCAR exhibited strongerin situ pancreatic tumor targeting ability after oral administration. Furthermore, oral administration of βGlus-PNP/pCAR-GFP resulted in significant GFP protein expression detectable within pancreatic tumor tissues. ConclusionThis study successfully constructed and validated an orally administrable, pancreatic cancer-targeting polypeptide-based nano-gene delivery system. It provides an important technological foundation in delivery systems and experimental basis for the subsequent development of in situ CAR-M-based therapeutic strategies for pancreatic cancer.
2.Polypeptide-based Nanocarriers for Oral Targeted Delivery of CAR Genes to Pancreatic Cancer
Feng XIN ; Jian REN ; Zhao-Zhen LI ; Quan FANG ; Rui-Jing LIANG ; Lan-Lan LIU ; Lin-Tao CAI
Progress in Biochemistry and Biophysics 2026;53(2):431-441
ObjectivePancreatic ductal adenocarcinoma (PDAC) exhibits a limited response to current treatments due to its dense fibrotic stroma and highly immunosuppressive tumor microenvironment. In recent years, advancements in cellular immunotherapy, particularly chimeric antigen receptor macrophage (CAR-M) therapy, have offered new hope for pancreatic cancer treatment. Although CAR-M therapy demonstrates dual potential in directly killing tumor cells and remodeling the immune microenvironment, it still faces challenges such as complex in vitro preparation processes and low in vivo targeting and delivery efficiency. Therefore, developing strategies for efficient and targeted in vivo delivery of CAR genes has become crucial for overcoming current therapeutic limitations. This study aims to develop an orally administrable nano-gene delivery system for the targeted delivery of CAR genes to pancreatic tumor sites. MethodsCore nano-gene particles (PNP/pCAR) were constructed by loading plasmid DNA encoding CAR (pCAR) with cationic polypeptides (PNP). Subsequently, PNP/pCAR was surface-modified with β-glucan to prepare the targeted nanoparticles (βGlus-PNP/pCAR). The loading efficiency of PNP for pCAR was quantitatively assessed by gel retardation assay. The particle size, Zeta potential, morphology, and storage stability of PNP/pCAR were characterized using a Malvern particle size analyzer and transmission electron microscopy. At the cellular level, RAW 264.7 macrophages were selected. The cytotoxicity of PNP/pCAR was evaluated using the CCK-8 assay. The cellular uptake efficiency and lysosomal escape ability of the nanoparticles were assessed via flow cytometry and confocal microscopy. Transfection efficiency was quantitatively evaluated by detecting the expression of the reporter gene GFP using flow cytometry. At the in vivo level, an orthotopic pancreatic cancer mouse model was established. Cy7-labeled βGlus-PNP/pCAR nanoparticles were administered orally, and the fluorescence distribution in mice was dynamically monitored at 1, 2, 4, 8, and 16 h post-administration using a small animal in vivo imaging system. Forty-eight hours after oral gavage, the mice were euthanized, and pancreatic tumor tissues were collected for further analysis of intratumoral fluorescence signals using the imaging system. Additionally, βGlus-PNP/pCAR-GFP nanoparticles loaded with the reporter gene (GFP) were administered orally. Forty-eight hours post-administration, pancreatic tumor tissues were harvested to prepare frozen sections, and GFP expression was observed and analyzed under a fluorescence microscope. ResultsThe PNP carrier exhibited a high loading capacity for pCAR. The successfully prepared PNP/pCAR nanoparticles were regular spheres with a hydrodynamic diameter of approximately (120±10) nm and a Zeta potential of about +(6±1) mV. They maintained good structural stability after incubation in PBS buffer for 7 d. Cell experiments demonstrated that PNP/pCAR exhibited no significant cytotoxicity in RAW 264.7 cells while being efficiently internalized and effectively escaping lysosomal degradation. The transfection positive rate of PNP/pCAR-GFP in RAW 264.7 cells reached (25±3)%, surpassing that of Lipofectamine 2000-loaded pCAR-GFP (Lipo/pCAR-GFP), which was (20±1)%.In vivo experiments revealed that, compared to unmodified PNP/pCAR, βGlus-PNP/pCAR exhibited strongerin situ pancreatic tumor targeting ability after oral administration. Furthermore, oral administration of βGlus-PNP/pCAR-GFP resulted in significant GFP protein expression detectable within pancreatic tumor tissues. ConclusionThis study successfully constructed and validated an orally administrable, pancreatic cancer-targeting polypeptide-based nano-gene delivery system. It provides an important technological foundation in delivery systems and experimental basis for the subsequent development of in situ CAR-M-based therapeutic strategies for pancreatic cancer.
3.Sex-specific effects of Semen Cuscutae aqueous extract on behavior, proteomics, and gut microbiota in rats
Zihan ZHAO ; Yaling YANG ; Junhui ZHOU ; Jie REN ; Zhiqiang LUO ; Ruibin BAI ; Jian YANG
Science of Traditional Chinese Medicine 2026;4(1):50-61
Background: Sex-based differences often influence the therapeutic efficacy and safety of medications. Semen Cuscutae is a traditional tonic botanical drug with sex-specific characteristics, traditionally indicated for conditions such as impotence (exclusive to males) and restless fetus (exclusive to pregnant females). However, most existing studies have focused on a single sex. Objective: To evaluate the sex-specific biological effects of Semen Cuscutae in rats and explore its molecular mechanisms, with the aim of uncovering its pharmacological characteristics through a multiomics approach. Methods: A traditional aqueous extract of Semen Cuscutae (SCA) was used as the experimental material. Forty adult Sprague-Dawley rats (equal numbers of males and females) were randomly divided into 4 groups: male control, male SCA treatment (240 mg/kg), female control, and female SCA treatment (240 mg/kg), with 10 rats in each group. The biological effects were comprehensively evaluated using a combination of open field test, biochemical analyses, proteomics, and gut microbiota profiling. Results: As a tonic botanical drug, SCA appeared to directly affect the mental and behavioral state of rats. It significantly altered the time spent by rats in the center area during the open field test, showing a sex-dependent reversal of behaviors. Proteomic analysis of brain tissue identified 624 differentially expressed proteins across the groups, with 10 key differentially expressed proteins related to sex differences, including fibroblast growth factor receptor 3, transcription elongation factor A protein-like 1, 40S ribosomal protein S25, neural cell adhesion molecule, and anion exchange protein 2 (SLC4A2). Enrichment analysis revealed that in male rats, SCA upregulated proteins involved in biological processes such as ribosome function and energy derivation, supporting protein synthesis and enhancing energy supply, showing an overall gain effect. In contrast, in female rats, SCA downregulated proteins associated with processes such as positive regulation of target of rapamycin (TOR) signaling and vesicle transport, suggesting suppression of neuronal signaling and material transport, indicative of a shift toward a more restrained physiological state. Furthermore, SCA reduced gut microbiota diversity in female rats but increased it in males, including the abundance of Akkermansia, which may serve as a crucial mediator. Conclusion: Overall, the biological effects of SCA differ significantly between male and female rats, with evidence suggesting greater health benefits in males. These findings help elucidate the scientific basis of its traditional applications and provide guidance for the precise application of SCA as a functional health food.
4.The Association of Iodixanol With Renal and Cardiovascular Safety in Patients With ST-Elevation Myocardial Infarction Undergoing Primary Percutaneous Coronary Intervention:A Prospective Cohort Study
Zhaoping LIU ; Jian AN ; Aijie HOU ; Yanqin REN ; Lei QIN ; Xiaojie CHEN ; Guozhen HAO ; Xi SU ; Ping YANG ; Guidong SHEN ; Shenghuang WANG ; In-ho CHAE ; Yong HUO
Journal of Cardiovascular Intervention 2026;5(1):38-48
Background:
This study was performed to characterize the incidence, costs, and risk factors associated with renal and cardiovascular adverse outcomes following primary percutaneous coronary intervention (pPCI) in patients with ST-elevation myocardial infarction (STEMI).
Methods:
Patients with STEMI who underwent pPCI using iso-osmolar contrast were enrolled at 39 centers. The incidence of acute kidney injury (AKI) and major adverse renal and cardiovascular events (MARCE) was analyzed, as well as inpatient costs. Logistic regression analysis was performed to identify risk factors.
Results:
Among 2,293 patients, the incidence of AKI and MARCE within 72 hours post-pPCI was 4.14% (n = 95) and 4.40% (n = 101), respectively. AKI and/or MARCE were associated with systolic blood pressure (AKI: odds ratio [OR], 1.009; 95% confidence interval [CI], 1.000–1.018), hypertension (AKI: OR, 1.815; 95% CI, 1.133–2.906; MARCE: OR, 1.760;95% CI, 1.118–2.769), anterior wall infarction (AKI: OR, 1.895; 95% CI, 1.196–3.004; MARCE:OR, 1.939; 95% CI, 1.240–3.032), Killip class (AKI: OR, 1.465; 95% CI, 1.117–1.922; MARCE:OR, 1.467; 95% CI, 1.131–1.903), and serum creatinine (SCr; MARCE: OR, 1.006; 95% CI, 1.000–1.012). Hospitalization costs for patients with STEMI who developed AKI or MARCE were significantly higher than for those without AKI (9,595 ± 5,795 vs. 8,279 ± 3,872 USD, P = 0.003) or without MARCE (9,890 ± 5,616 vs. 8,255 ± 3,859 USD, P < 0.001).
Conclusions
In patients with STEMI undergoing pPCI with iso-osmolar contrast, the incidence of AKI and MARCE was associated with higher hospitalization costs. Systolic blood pressure, hypertension, anterior wall infarction, Killip class, and SCr were identified as risk factors for these outcomes.
5.Dynamic prediction of JC polyomavirus reactivation after kidney transplantation
Mengyao LI ; Chengfeng ZHANG ; Difei REN ; Xin LIANG ; Shuyu CHEN ; Yushi PENG ; Yanjie WANG ; Meng ZHANG ; Jian XU ; Zheng CHEN ; Yun MIAO ; Yibin WANG
Organ Transplantation 2026;17(4):635-643
Objective To construct a dynamic prediction model for JC polyomavirus (JCV) reactivation after kidney transplantation. Methods A retrospective analysis was conducted on the clinical data of 128 recipients who met the inclusion criteria and received kidney transplantation in Nanfang Hospital, Southern Medical University, from June 2021 to December 2024. Dynamic Cox regression and dynamic restricted mean survival time (RMST) regression based on the landmark method were adopted to establish the dynamic prediction models, and Monte Carlo cross-validation was used to evaluate model performance. Results The dynamic models could predict the incidence and onset time of JCV reactivation within the subsequent 3 months according to covariates at each landmark time point from the 1st to the 6th month after transplantation. Remuzzi score, body mass index and warm ischemia time were independent risk factors for JCV reactivation, while a history of urinary BK polyomavirus reactivation served as a protective factor. The median values of the area under the curve, C-index and Brier score of the dynamic Cox model were 0.873, 0.851 and 0.065 respectively, and the C-index of the dynamic RMST model was 0.829, all of which were superior to those of the static model. Conclusions The landmark-based dynamic models exhibit excellent predictive performance, which may integrate baseline data and post-transplant follow-up information to realize dynamic assessment of the risk and time window of JCV reactivation, thereby providing evidence for optimizing post-operative monitoring and individualized intervention strategies.
6.Investigation of latent tuberculosis infection among the elderly in rural areas of Changxing County, Zhejiang Province
Jian ZHANG ; Yufang SONG ; Feilin REN ; Xuejing LI ; Jiasheng QIN ; Bin SHAO
Shanghai Journal of Preventive Medicine 2025;37(6):503-506
ObjectiveTo investigate the current status of latent tuberculosis infection (LTBI) among the elderly population in rural areas of Changxing County, Zhejiang Province, and to provide an evidence for the development of LTBI prevention and control measures. MethodsBetween January and May 2024, elderly individuals participating in urban and rural residents’ health checkups were screened for Mycobacterium tuberculosis infection using a domestically produced interferon-γ release assay (IGRA) kit. Individuals tested positive by IGRA but without active tuberculosis were classified as LTBI cases. The prevalence of LTBI among the participants was subsequently analyzed. ResultsAmong the 6 765 subjects, 637 tested positive by IGRA, including one identified active tuberculosis patient, resulting in a LTBI prevalence rate of 9.40%. There was a statistically significant difference in positivity rates across different IGRA methodologies (χ2=35.530, P<0.001). Higher LTBI rate was observed in males, individuals with a history of diabetes mellitus, and those with a history of pulmonary tuberculosis, exhibiting statistically significant differences (χ2=32.401, P<0.001; χ2=5.789, P=0.020; χ2=39.248, P<0.001, respectively.) No statistically significant difference in LTBI rate was found across different age groups (χ2=0.238, P=0.971). ConclusionThe prevalence of LTBI among the elderly rural residents in Changxing County is relatively low. Male, individuals with a history of diabetes mellitus, and those with a history of pulmonary tuberculosis have an increased risk of LTBI, warranting targeted risk monitoring and timely interventions.
7.tRF Prospect: tRNA-derived Fragment Target Prediction Based on Neural Network Learning
Dai-Xi REN ; Jian-Yong YI ; Yong-Zhen MO ; Mei YANG ; Wei XIONG ; Zhao-Yang ZENG ; Lei SHI
Progress in Biochemistry and Biophysics 2025;52(9):2428-2438
ObjectiveTransfer RNA-derived fragments (tRFs) are a recently characterized and rapidly expanding class of small non-coding RNAs, typically ranging from 13 to 50 nucleotides in length. They are derived from mature or precursor tRNA molecules through specific cleavage events and have been implicated in a wide range of cellular processes. Increasing evidence indicates that tRFs play important regulatory roles in gene expression, primarily by interacting with target messenger RNAs (mRNAs) to induce transcript degradation, in a manner partially analogous to microRNAs (miRNAs). However, despite their emerging biological relevance and potential roles in disease mechanisms, there remains a significant lack of computational tools capable of systematically predicting the interaction landscape between tRFs and their target mRNAs. Existing databases often rely on limited interaction features and lack the flexibility to accommodate novel or user-defined tRF sequences. The primary goal of this study was to develop a machine learning based prediction algorithm that enables high-throughput, accurate identification of tRF:mRNA binding events, thereby facilitating the functional analysis of tRF regulatory networks. MethodsWe began by assembling a manually curated dataset of 38 687 experimentally verified tRF:mRNA interaction pairs and extracting seven biologically informed features for each pair: (1) AU content of the binding site, (2) site pairing status, (3) binding region location, (4) number of binding sites per mRNA, (5) length of the longest consecutive complementary stretch, (6) total binding region length, and (7) seed sequence complementarity. Using this dataset and feature set, we trained 4 distinct machine learning classifiers—logistic regression, random forest, decision tree, and a multilayer perceptron (MLP)—to compare their ability to discriminate true interactions from non-interactions. Each model’s performance was evaluated using overall accuracy, receiver operating characteristic (ROC) curves, and the corresponding area under the ROC curve (AUC). The MLP consistently achieved the highest AUC among the four, and was therefore selected as the backbone of our prediction framework, which we named tRF Prospect. For biological validation, we retrieved 3 high-throughput RNA-seq datasets from the gene expression omnibus (GEO) in which individual tRFs were overexpressed: AS-tDR-007333 (GSE184690), tRF-3004b (GSE197091), and tRF-20-S998LO9D (GSE208381). Differential expression analysis of each dataset identified genes downregulated upon tRF overexpression, which we designated as putative targets. We then compared the predictions generated by tRF Prospect against those from three established tools—tRFTar, tRForest, and tRFTarget—by quantifying the number of predicted targets for each tRF and assessing concordance with the experimentally derived gene sets. ResultsThe proposed algorithm achieved high predictive accuracy, with an AUC of 0.934. Functional validation was conducted using transcriptome-wide RNA-seq datasets from cells overexpressing specific tRFs, confirming the model’s ability to accurately predict biologically relevant downregulation of mRNA targets. When benchmarked against established tools such as tRFTar, tRForest, and tRFTarget, tRF Prospect consistently demonstrated superior performance, both in terms of predictive precision and sensitivity, as well as in identifying a higher number of true-positive interactions. Moreover, unlike static databases that are limited to precomputed results, tRF Prospect supports real-time prediction for any user-defined tRF sequence, enhancing its applicability in exploratory and hypothesis-driven research. ConclusionThis study introduces tRF Prospect as a powerful and flexible computational tool for investigating tRF:mRNA interactions. By leveraging the predictive strength of deep learning and incorporating a broad spectrum of interaction-relevant features, it addresses key limitations of existing platforms. Specifically, tRF Prospect: (1) expands the range of detectable tRF and target types; (2) improves prediction accuracy through multilayer perceptron model; and (3) allows for dynamic, user-driven analysis beyond database constraints. Although the current version emphasizes miRNA-like repression mechanisms and faces challenges in accurately capturing 5'UTR-associated binding events, it nonetheless provides a critical foundation for future studies aiming to unravel the complex roles of tRFs in gene regulation, cellular function, and disease pathogenesis.
8.Curcumae Rhizoma: An anti-cancer traditional Chinese medicine.
Yu LUO ; Lin ZHU ; Zhengyu REN ; Jian XIAO ; Erwei HAO ; Jiahong LU ; Jinmin ZHAO ; Chun YAO ; Yitao WANG ; Hua LUO
Chinese Herbal Medicines 2025;17(3):428-447
Curcumae Rhizoma, derived from the rhizome of Curcuma phaeocaulis, Curcuma kwangsiensis and Curcuma wenyujin, was called Ezhu in China. In the past, Curcumae Rhizoma extracts were obtained through water decoction or alternative methods, which showed significant anti-cancer effects. However, the mixed extracts contain various compound components of Curcumae Rhizoma, leading to an ambiguous mechanism of action for Curcumae Rhizoma extracts anti-cancer. Contemporary researchers have extracted the chemical components of Curcumae Rhizoma separately for experimental verification of its active ingredients in the anti-cancer field. Numerous studies demonstrated that curcumol, germacrone, β-elemene, and curcumin in Curcumae Rhizoma extracts have significant governing effects in anti-cancer activities. Pharmacological studies have shown that Curcumae Rhizoma suppresses cancer cell proliferation, invasion, and migration, triggering apoptosis and regulating cellular autophagy to achieve anticancer effects. Here, we summarized the research progress of Curcumae Rhizoma on anti-cancer effects from 2013 to 2022, aiming to explore the deeper molecular mechanisms of Curcumae Rhizoma's active components in cancer treatment.
9.(+)-Strebloside induces Non-Hodgkin lymphoma cell death through the STEAP3-Mediated Ferroptosis and MAPK pathway.
Yu ZHAO ; Jing CAI ; Ying YANG ; Dongmei ZHANG ; Jiayi REN ; Shuyun XIAO ; Jian XU ; Feng FENG ; Rong WU ; Jie ZHANG
Chinese Journal of Natural Medicines (English Ed.) 2025;23(10):1221-1231
(+)-Strebloside, a significant bioactive compound isolated from the roots of Streblus asper Lour., demonstrates inhibitory effects against multiple malignancies. However, its specific function and underlying mechanistic pathways in Non-Hodgkin lymphoma (NHL) remain unexplored. This investigation sought to elucidate the role and potential mechanisms of (+)-strebloside-induced NHL cell death. The results demonstrated that (+)-strebloside significantly induced apoptosis and ferroptosis in NHL cells, including those from Raji cell-derived xenograft models. Mechanistic analyses revealed that (+)-strebloside enhanced six-transmembrane epithelial antigen of prostate 3 (STEAP3)-induced ferroptosis in NHL, and STEAP3 inhibition reduced the proliferation-inhibitory effects of (+)-strebloside. Furthermore, (+)-strebloside suppressed NHL proliferation through the mitogen-activated protein kinase (MAPK) pathway, and extracellular signal-regulated kinase (ERK) inhibition diminished the proliferation-inhibitory activity induced by (+)-strebloside. These findings indicate that (+)-strebloside presents promising therapeutic potential for NHL treatment.
Humans
;
Ferroptosis/drug effects*
;
Lymphoma, Non-Hodgkin/physiopathology*
;
Cell Line, Tumor
;
MAP Kinase Signaling System/drug effects*
;
Animals
;
Cell Proliferation/drug effects*
;
Mice
;
Apoptosis/drug effects*
;
Membrane Proteins/genetics*
;
Xenograft Model Antitumor Assays
;
Male
;
Mice, Nude
10.Independent and Interactive Effects of Air Pollutants, Meteorological Factors, and Green Space on Tuberculosis Incidence in Shanghai.
Qi YE ; Jing CHEN ; Ya Ting JI ; Xiao Yu LU ; Jia le DENG ; Nan LI ; Wei WEI ; Ren Jie HOU ; Zhi Yuan LI ; Jian Bang XIANG ; Xu GAO ; Xin SHEN ; Chong Guang YANG
Biomedical and Environmental Sciences 2025;38(7):792-809
OBJECTIVE:
To assess the independent and combined effects of air pollutants, meteorological factors, and greenspace exposure on new tuberculosis (TB) cases.
METHODS:
TB case data from Shanghai (2013-2018) were obtained from the Shanghai Center for Disease Control and Prevention. Environmental data on air pollutants, meteorological variables, and greenspace exposure were obtained from the National Tibetan Plateau Data Center. We employed a distributed-lag nonlinear model to assess the effects of these environmental factors on TB cases.
RESULTS:
Increased TB risk was linked to PM 2.5, PM 10, and rainfall, whereas NO 2, SO 2, and air pressure were associated with a reduced risk. Specifically, the strongest cumulative effects occurred at various lags: PM 2.5 ( RR = 1.166, 95% CI: 1.026-1.325) at 0-19 weeks; PM 10 ( RR = 1.167, 95% CI: 1.028-1.324) at 0-18 weeks; NO 2 ( RR = 0.968, 95% CI: 0.938-0.999) at 0-1 weeks; SO 2 ( RR = 0.945, 95% CI: 0.894-0.999) at 0-2 weeks; air pressure ( RR = 0.604, 95% CI: 0.447-0.816) at 0-8 weeks; and rainfall ( RR = 1.404, 95% CI: 1.076-1.833) at 0-22 weeks. Green space exposure did not significantly impact TB cases. Additionally, low temperatures amplified the effect of PM 2.5 on TB.
CONCLUSION
Exposure to PM 2.5, PM 10, and rainfall increased the risk of TB, highlighting the need to address air pollutants for the prevention of TB in Shanghai.
China/epidemiology*
;
Humans
;
Air Pollutants/analysis*
;
Tuberculosis/epidemiology*
;
Incidence
;
Meteorological Concepts
;
Particulate Matter/adverse effects*
;
Environmental Exposure
;
Male
;
Female
;
Adult
;
Air Pollution
;
Middle Aged

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