pH-Responsive Amphiphilic Triblock Fluoropolymers as Assemble Oxygen Nanoshuttles for Enhancing PDT against Hypoxic Tumor.

Photodynamic therapy (PDT) is a cancer treatment strategy that utilizes photosensitizers to convert oxygen within tumors into reactive singlet oxygen (1O2) to lyse tumor cells. Nevertheless, pre-existing tumor hypoxia and oxygen consumption during PDT can lead to an insufficient oxygen supply, potentially reducing the photodynamic efficacy. In response to this issue, we have devised a pH-responsive amphiphilic triblock fluorinated polymer (PDP) using copper-mediated RDRP. This polymer, composed of poly(ethylene glycol) methyl ether acrylate, 2-(diethylamino)ethyl methacrylate, and (perfluorooctyl)ethyl acrylate, self-assembles in an aqueous environment. Oxygen, chlorine e6 (Ce6), and doxorubicin (DOX) can be codelivered efficiently by PDP. The incorporation of perfluorocarbon into the formulation enhances the oxygen-carrying capacity of PDP, consequently extending the lifetime of 1O2. This increased lifetime, in turn, amplifies the PDT effect and escalates the cellular cytotoxicity. Compared with PDT alone, PDP@Ce6-DOX-O2 NPs demonstrated significant inhibition of tumor growth. This study proposes a novel strategy for enhancing the efficacy of PDT.

Prognostic Utility of Left Atrial Strain From MRI Feature Tracking in Ischemic and Nonischemic Dilated Cardiomyopathy: A Multicenter Study.

BACKGROUND. MRI-based prognostic evaluation in patients with dilated cardiomyopathy (DCM) has historically used markers of late gadolinium enhancement (LGE) and feature tracking (FT)-derived left ventricular global longitudinal strain (LVGLS). Early data indicate that FT-derived left atrial strain (LAS) parameters, including reservoir, conduit, and booster, may also have prognostic roles in such patients. OBJECTIVE. The purpose of our study was to evaluate the prognostic utility of LAS parameters, derived from MRI FT, in patients with ischemic or nonischemic DCM, including in comparison with the traditional parameters of LGE and LVGLS. METHODS. This retrospective study included 811 patients with ischemic or nonischemic DCM (median age, 60 years; 640 men, 171 women) who underwent cardiac MRI at any of five centers. FT-derived LAS parameters and LVGLS were measured using two- and four-chamber cine images. LGE percentage was quantified. Patients were assessed for a composite outcome of all-cause mortality or heart failure hospitalization. Multivariable Cox regression analyses including demographic characteristics, cardiovascular risk factors, medications used, and a wide range of cardiac MRI parameters were performed. Kaplan-Meier analyses with log-rank tests were also performed. RESULTS. A total of 419 patients experienced the composite outcome. Patients who did, versus those who did not, experience the composite outcome had larger LVGLS (-6.7% vs -8.3%, respectively; p < .001) as well as a smaller LAS reservoir (13.3% vs 19.3%, p < .001), LAS conduit (4.7% vs 8.0%, p < .001), and LAS booster (8.1% vs 10.3%, p < .001) but no significant difference in LGE (10.1% vs 11.3%, p = .51). In multivariable Cox regression analyses, significant independent predictors of the composite outcome included LAS reservoir (HR = 0.96, p < .001) and LAS conduit (HR = 0.91, p < .001). LAS booster and LGE were not significant independent predictors in the models. LVGLS was a significant independent predictor only in a model that initially included LAS booster but not the other LAS parameters. In Kaplan-Meier analysis, all three LAS parameters were significantly associated with the composite outcome (p < .001). CONCLUSION. In this multicenter study, LAS reservoir and LAS conduit were significant independent prognostic markers in patients with ischemic or nonischemic DCM, showing greater prognostic utility than the currently applied markers of LVGLS and LGE. CLINICAL IMPACT. FT-derived LAS analysis provides incremental prognostic information in patients with DCM.

Differential expression of FSTL1 and its correlation with the pathological process of periodontitis.

AIMS: This study aimed to elucidate the alterations in Follistatin-like protein 1 (FSTL1) and its association with the pathological process of periodontitis. METHODS: This study included 48 patients with periodontitis and 42 healthy controls. The expression level of FSTL1 in the gingiva was determined by RT-qPCR, validated using the dataset GSE16134, and subsequently examined by western blotting. Bioinformatics analysis revealed a single-cell distribution of FSTL1, characteristic of angiogenesis and immune cell infiltration. The expression and distribution of FSTL1, vascular endothelial marker protein CD31 and myeloperoxidase (MPO), the indicator of neutrophil activity, were determined by immunohistochemistry (IHC). A series of correlation analyses was performed to determine the associations between FSTL1 and clinical parameters, including probing depth (PD) and clinical attachment loss (CAL), and their potential role in angiogenesis (CD31) and neutrophil infiltration (MPO). RESULTS: FSTL1 was significantly upregulated in the gingiva of patients with periodontitis compared to their healthy counterparts. In addition, FSTL1 was positively correlated with the clinical parameters PD (r = .5971, p = .0005) and CAL (r = .6078, p = .0004). Bioinformatic analysis and IHC indicated that high FSTL1 expression was significantly correlated with angiogenesis and neutrophil infiltration in periodontitis. Moreover, receiver operating characteristic (ROC) analysis demonstrated that FSTL1 could serve as an independent indicator for evaluating the severity of periodontitis (area under the curve [AUC] = 0.9011, p < .0001). CONCLUSION: This study demonstrated FSTL1 upregulation in periodontitis and its potential contribution to the disease via angiogenesis and neutrophil infiltration.

Development and validation of a prediction nomogram for sleep disorders in hospitalized patients with acute myocardial infarction.

PURPOSE: Sleep disorders are becoming more prevalent in hospitalized patients with acute myocardial infarction (AMI). We aimed to investigate the risk factors for sleep disorders in hospitalized patients with AMI, then develop and validate a prediction nomogram for the risk of sleep disorders. METHODS: Clinical data were collected from patients with AMI hospitalized in our hospital from January 2020 to June 2023. All patients were divided into the training group and the validation group with a ratio of 7:3 in sequential order. The LASSO regression analysis and multivariate logistic regression analysis were used to screen potential risk factors for sleep disorders. The concordance index (C-index), calibration curves, and decision curve analysis (DCA) were plotted. RESULTS: A total of 256 hospitalized patients with AMI were enrolled. Patients were divided into the training group (180) and the validation group (76) according to a scale of 7:3. Of the 256 patients, 90 patients (35.16%) suffered from sleep disorders, and 33 patients (12.89%) needed hypnotics. The variables screened by LASSO regression included age, smoking, NYHA class, anxiety status at admission, depression status at admission, and strangeness of environment. A nomogram model was established by incorporating the risk factors selected. The C-index, calibration curve, and DCA showed good predictive performance. CONCLUSIONS: We identified six clinical characteristics as predictors of sleep disorders in hospitalized patients with AMI. It helps nurses make appropriate decisions in clinical practice.

Insight into the role of mitochondrion-related gene anchor signature in mitochondrial dysfunction of neutrophilic asthma.

OBJECTIVE: At present, targeting molecular-pharmacological therapy is still difficult in neutrophilic asthma. The investigation aims to identify and validate mitochondrion-related gene signatures for diagnosis and specific targeting therapeutics in neutrophilic asthma. METHODS: Bronchial biopsy samples of neutrophilic asthma and healthy people were identified from the GSE143303 dataset and then matched with human mitochondrial gene data to obtain mitochondria-related differential genes (MitoDEGs). Signature mitochondria-related diagnostic markers were jointly screened by support vector machine (SVM) analysis, least absolute shrinkage, and selection operator (LASSO) regression. The expression of marker MitoDEGs was evaluated by validation datasets GSE147878 and GSE43696. The diagnostic value was evaluated by receiver operating characteristic (ROC) curve analysis. Meanwhile, the infiltrating immune cells were analyzed by the CIBERSORT. Finally, oxidative stress level and mitochondrial functional morphology for asthmatic mice and BEAS-2B cells were evaluated. The expression of signature MitoDEGs was verified by qPCR. RESULTS: 67 MitoDEGs were identified. Five signature MitoDEGs (SOD2, MTHFD2, PPTC7, NME6, and SLC25A18) were further screened out. The area under the curve (AUC) of signature MitoDEGs presented a good diagnostic performance (more than 0.9). There were significant differences in the expression of signature MitoDEGs between neutrophilic asthma and non-neutrophilic asthma. In addition, the basic features of mitochondrial dysfunction were demonstrated by in vitro and in vivo experiments. The expression of signature MitoDEGs in the neutrophilic asthma mice presented a significant difference from the control group. CONCLUSIONS: These MitoDEGs signatures in neutrophilic asthma may hold potential as anchor diagnostic and therapeutic targets in neutrophilic asthma.

Assumption-free analysis for amplification-based quantitative nucleic acid detection.

The accurate detection and quantification of biological species that are rarely present but potentially devastating is of paramount importance for the life sciences, biosecurity, food safety, and environmental monitoring. Consequently, there has been significant interest in the sensitive and accurate detection of nucleic acids, leveraging both chemical and biological methods. Among these, quantitative polymerase chain reaction (qPCR) is regarded as the gold standard due to its sensitivity and precision in identifying specific nucleic acid targets. Despite the widespread adoption of qPCR for nucleic acid detection, the analysis of qPCR data typically depends on the use of calibrated standard curves and a threshold method to interpret signal measurements. In this study, we use a stochastic simulation to show the limitations of the threshold method due to its assumptions on amplification kinetics. We propose a new approach for the absolute quantification of nucleic acids that overcomes these limitations by reconstructing the efficiency profile across amplification cycles and using cumulative amplification folds to build a standard curve, thus avoiding the constant efficiency assumption. Our method, validated through experiments with nucleic acid amplification in the presence of potent inhibitors, demonstrates improved accuracy in quantifying nucleic acids, avoiding the systematic errors of the threshold method. This innovation enhances the reliability of nucleic acid quantification, especially where traditional methods struggle with kinetic variability.

Development and validation of a deep learning model for predicting postoperative survival of patients with gastric cancer.

BACKGROUND: Deep learning (DL), a specialized form of machine learning (ML), is valuable for forecasting survival in various diseases. Its clinical applicability in real-world patients with gastric cancer (GC) has yet to be extensively validated. METHODS: A combined cohort of 11,414 GC patients from the Surveillance, Epidemiology and End Results (SEER) database and 2,846 patients from a Chinese dataset were utilized. The internal validation of different algorithms, including DL model, traditional ML models, and American Joint Committee on Cancer (AJCC) stage model, was conducted by training and testing sets on the SEER database, followed by external validation on the Chinese dataset. The performance of the algorithms was assessed using the area under the receiver operating characteristic curve, decision curve, and calibration curve. RESULTS: DL model demonstrated superior performance in terms of the area under the curve (AUC) at 1, 3, and, 5 years post-surgery across both datasets, surpassing other ML models and AJCC stage model, with AUCs of 0.77, 0.80, and 0.82 in the SEER dataset and 0.77, 0.76, and 0.75 in the Chinese dataset, respectively. Furthermore, decision curve analysis revealed that the DL model yielded greater net gains at 3 years than other ML models and AJCC stage model, and calibration plots at 3 years indicated a favorable level of consistency between the ML and actual observations during external validation. CONCLUSIONS: DL-based model was established to accurately predict the survival rate of postoperative patients with GC.

Exploring Ribosomal Genes as Potential Biomarkers of the Immune Microenvironment in Respiratory Syncytial Virus Infection.

Respiratory syncytial virus (RSV) is the most common pathogen causing acute lower respiratory tract infection in infants and children. Due to limited knowledge of the pathological and molecular mechanisms of immunodeficiency underlying RSV disease, there is currently a lack of an approved and effective RSV vaccine to combat RSV infections. This study aimed to identify genes associated with immune dysfunction using bioinformatics methods to gain insights into the role of dysregulated immune genes in RSV disease progression, and to predict potential therapeutic drugs by targeting dysregulated immune-related genes. 423 immune-related differential genes (DEIRGs) were filtered from the blood samples of 87 healthy individuals and 170 RSV patients. According to CIBERSORT analysis, the blood of RSV patients showed increased infiltration of various immune cells. Subsequently, ten immune-related hub genes were screened via Protein-Protein Interaction Networks. Six signature immune-related genes (RPS2, RPS5, RPS13, RPS14, RPS18, and RPS4X) as candidate characteristic genes for the diagnostic model were identified by Lasso regression. The AUC value of the ROC curve of the six signature genes was 0.884. This result, intriguingly, suggested that all six immune-related genes with a good internal validation effect were ribosome family genes. Finally, through molecular docking analyses targeting these differential immune genes, ADO and fluperlapine were found to have high stable binding to major proteins of important immune-related genes in nine drug-protein interactions. Overall, the present study screened immune-related genes that are dysregulated in the development of RSV disease to investigate the pathogenesis of RSV infection from the standpoint of immune disorders. Unexpectedly, bioinformatics analysis revealed that ribosome family genes may be involved in the immune dysregulation of RSV disease, and these genes as targets formed the basis for potential drug modification candidates in RSV disease.

Inorganic salt starvation improves the polysaccharide production and CO2 fixation by Porphyridium purpureum.

The microalgae industry shows a promising future in the production of high-value products such as pigments, phycoerythrin, polyunsaturated fatty acids, and polysaccharides. It was found that polysaccharides have high biomedical value (such as antiviral, antibacterial, antitumor, antioxidative) and industrial application prospects (such as antioxidants). This study aimed to improve the polysaccharides accumulation of Porphyridium purpureum CoE1, which was effectuated by inorganic salt starvation strategy whilst supplying rich carbon dioxide. At a culturing temperature of 25 °C, the highest polysaccharide content (2.89 g/L) was achieved in 50% artificial seawater on the 12th day. This accounted for approximately 37.29% of the dry biomass, signifying a 25.3% increase in polysaccharide production compared to the culture in 100% artificial seawater. Subsequently, separation, purification and characterization of polysaccharides produced were conducted. Furthermore, the assessment of CO2 fixation capacity during the cultivation of P. purpureum CoE1 was conducted in a 10 L photobioreactor. This indicated that the strain exhibited an excellent CO2 fixation capacity of 1.66 g CO2/g biomass/d. This study proposed an efficient and feasible approach that not only increasing the yield of polysaccharides by P. purpureum CoE1, but also fixing CO2 with a high rate, which showed great potential in the microalgae industry and Bio-Energy with Carbon Capture and Storage.

Role of αENaC in root resorption of adjacent teeth due to entirely impacted mandibular third molars.

BACKGROUND: Entirely impacted mandibular third molar (EIM3M) concerns the pathological external root resorption (ERR) of the adjacent mandibular second molar (M2M) and formation of granulation tissue between two molars. The study aimed to clarify the effect of αENaC, a mechano-sensitive molecule, to explore the mechanical mechanism in this scenario. METHODS: The force EIM3M exerted on M2M was proved by finite element analysis. αENaC expressions were tested by real-time polymerase chain reaction (PCR), immunoblotting and immunofluorescence. Inflammatory and epithelial-mesenchymal transition (EMT)-related molecules expressions were also detected by real-time PCR. The correlation was analyzed by Spearman's correlation analysis, and receiver-operator characteristic (ROC) curve was further exhibited. RESULTS: The force was concentrated in the ERR area. αENaC was upregulated, positively correlated with ERR degree and localized to the fibroblasts in ERR granulation tissues. Moreover, αENaC was respectively and positively associated with elevated TNF-α and N-cadherin in ERR granulation tissues. More importantly, ROC analysis verified αENaC as a novel indication of the incidence of this disease. CONCLUSIONS: Our finding revealed the force from EIM3M causing ERR of M2M, and elucidated the expression and localization of αENaC and its positive correlation with inflammation, EMT and disease severity, suggesting a novel indication in this disease.

Expression patterns of mechanosensitive ion channel PIEZOs in irreversible pulpitis.

BACKGROUND: Mechanosensitive ion channel PIEZOs have been widely reported to involve inflammation and pain. This study aimed to clarify expression patterns of PIEZOs and their potential relations to irreversible pulpitis. MATERIALS AND METHODS: Normal pulp tissues (n = 29) from patients with impacted third molars and inflamed pulp tissues (n = 23) from patients with irreversible pulpitis were collected. Pain levels were assessed using a numerical rating scale. PIEZO expressions were measured using real-time PCR and then confirmed using GEO datasets GSE77459, immunoblot, and immunohistochemistry staining. Correlations of PIEZO mRNA expression with inflammatory markers, pain markers, or clinical pain levels were evaluated using Spearman's correlation analysis. Univariate analysis was conducted to analyze PIEZO expressions based on pain description and clinical examinations of cold test, percussion, palpation, and bite test. RESULTS: Compared with normal pulp tissues, mRNA expression levels of PIEZO1 were significantly increased in inflamed pulp tissues, while PIEZO2 was significantly decreased, which was further confirmed in GSE77459 and on a protein and histological level. The positive correlation of the mRNA expression levels between PIEZO1 and inflammatory markers, as well as between PIEZO2 and pain markers, was verified. PIEZO2 expression was also positively correlated with pain levels. Besides, irreversible pulpitis patients who reported continuous pain and who detected a positive response to cold stimulus exhibited a higher expression level of PIEZO2 in the inflamed pulp tissues. By contrast, patients reporting pain duration of more than one week showed a higher expression level of PIEZO1. CONCLUSIONS: This study demonstrated the upregulation of PIEZO1 and the downregulation of PIEZO2 in irreversible pulpitis and revealed the potential relation of PIEZO1 and PIEZO2 to inflammation and pain. These findings suggested that PIEZOs might play critical roles in the progression of irreversible pulpitis and paved the way for further investigations aimed at novel therapies of irreversible pulpitis by targeting PIEZOs.

Radical Fluorosulfonamidation: A Facile Access to Sulfamoyl Fluorides.

Recently, the introduction of fluorosulfonyl (-SO2F) groups have attracted considerable research interests, as this moiety could often afford enhanced activities and new functions in the context of chemical biology and drug discovery. Herein, we report the design and synthesis of 1-fluorosulfamoyl-pyridinium (FSAP) salts, which could serve as an effective photoredox-active precursor to fluorosulfamoyl radicals and enable the direct radical C-H fluorosulfonamidation of a variety of (hetero)arenes. This method features mild conditions, visible light, broad substrate scope, good group tolerance, etc., and a metal-free protocol is also viable by using organic photocatalysts. Further, FSAP can also be applied to the radical functionalization of alkenes via 1,2-difunctionalization, radical distal migration, tandem radical-polar crossover reactions, etc. In addition, a formal C-H methylamination of (hetero)arenes by combining this radical C-H fluorosulfonamidation with subsequent hydrolysis as well as product derivatization are also demonstrated.

[Identification of Q-markers for Schisandrae Sphenantherae Fructus in treating drug-induced liver injury based on network pharmacology, fingerprint and quantitative analysis].

This study aims to establish the ultra-performance liquid chromatography(UPLC) fingerprint and multi-indicator quantitative analysis method for Schisandrae Sphenantherae Fructus(SSF) and to screen out the potential quality markers(Q-markers) of hepatoprotection based on network pharmacology. The similarity analysis was performed using the Chinese Medicine Chromatographic Fingerprint Similarity Evaluation System, which showed that the similarity of the fingerprints of 15 samples from different regions ranged from 0.981 to 0.998. Eighteen common components were identified, from which 3 differential components were selected by cluster analysis and principal component analysis. The "component-target-pathway" network was built to predict the core components related to the hepatoprotective effects. Fourteen core components were screened by network pharmacology. They acted on the targets such as AKT1, CCND1, CYP1A1, CYP3A4, MAPK1, MAPK3, NOS2, NQO1, and PTGS2 to regulate the signaling pathways of lipid metabolism and atherosclerosis, hepatitis B, interleukin-17, and tumor necrosis factor. Considering the chemical measurability, characteristics, and validity, schisantherin A, anwulignan, and schisandrin A were identified as the Q-markers. The content of schisantherin A, anwulignan, and schisandrin A in the test samples were 0.20%-0.57%, 0.13%-0.33%, and 0.42%-0.70%, respectively. Combining the fingerprint, network pharmacology, and content determination, this study predicted that schisantherin A, anwulignan, and schisandrin A were the Q-markers for the hepatoprotective effect of SSF. The results can provide reference for improving the quality evaluation standard and exploring the hepatoprotective mechanism of SSF.

Disorder-induced spiky phonon transmission of harmonic lattices.

In this article, we find that impurity in a one-dimensional harmonic chain leads to spikes in the phonon transmission. Using the Langevin equations and Green's function method (LEGF), we find the underlying mechanism of spikes, which comes from the fact that the wave energy can be transferred through uniform subchains laid between impurities without loss. Both the position and magnitude of spikes can be analytically obtained. By employing these results, we provide an analytical approach to transmission in the thermodynamic limit, thereby compensating for the limitation of LEGF that are practically confined to finite system size. Finally, we determine an expression for the localization length based on LEGF, demonstrating the equivalence between mass disorder and spatial disorder in low impurity concentration.

Infection with COVID-19 Complicated by Sinus Arrest.

As a respiratory tract-transmitted disease, coronavirus disease 2019 (COVID-19) exerts a profound immune injury effect, leading not only to pulmonary impairment but also to cardiac complications. We present a case of a 79-year-old woman, who had previously contracted COVID-19 and subsequently developed sinus arrest (SA) following her second infection. The longest asystole time detected by Holter monitoring was 7.2 seconds. Although the patient met criteria for permanent pacemaker implantation, her family declined this intervention and conservative management was pursued instead. However, after a period of observation, the patient's SA resolved. The present case study describes a patient who experienced SA upon reinfection with COVID-19, which was not present during the initial infection. It emphasizes the impact of COVID-19 on cardiac health, particularly its potential to induce arrhythmias. In addition, it is worth noting that the arrhythmia induced by a COVID-19 infection may show reversibility, suggesting that a permanent pacemaker might not be the priority option if further pacing therapy is being considered.

Harnessing oleaginous yeast to produce omega fatty acids.

Omega fatty acids are important for human health. They are traditionally extracted from animals or plants but can be alternatively produced using oleaginous yeast. Current efforts are producing yeast strains with similar fatty acid distributions and powerful lipogenesis capacity. The next step is to further make the process more competitive.

Effects of extreme temperatures on public sentiment in 49 Chinese cities.

The rising sentiment challenges of the metropolitan residents may be attributed to the extreme temperatures. However, nationwide real-time empirical studies that examine this claim are rare. In this research, we construct a daily extreme temperature index and sentiment metric using geotagged posts on one of China's largest social media sites, Weibo, to verify this hypothesis. We find that extreme temperatures causally decrease individuals' sentiment, and extremely low temperature may decrease more than extremely high temperature. Heterogeneity analyses reveal that individuals living in high levels of PM2.5, existing new COVID-19 diagnoses and low-disposable income cities on workdays are more vulnerable to the impact of extreme temperatures on sentiment. More importantly, the results also demonstrate that the adverse effects of extremely low temperatures on sentiment are more minor for people living in northern cities with breezes. Finally, we estimate that with a one-standard increase of extremely high (low) temperature, the sentiment decreases by approximately 0.161 (0.272) units. Employing social media to monitor public sentiment can assist policymakers in developing data-driven and evidence-based policies to alleviate the adverse impacts of extreme temperatures.

Identification of potential biomarkers for diabetic cardiomyopathy using LC-MS-based metabolomics.

Diabetic cardiomyopathy (DCM) is a serious complication of type 2 diabetes mellitus (T2DM) that contributes to cardiovascular morbidity and mortality. However, the metabolic alterations and specific biomarkers associated with DCM in T2DM remain unclear. In this study, we conducted a comprehensive metabolomic analysis using liquid chromatography-mass spectrometry (LC-MS) to investigate the plasma metabolite profiles of T2DM patients with and without DCM. We identified significant differences in metabolite levels between the groups, highlighting the dysregulation of various metabolic pathways, including starch and sucrose metabolism, steroid hormone biosynthesis, tryptophan metabolism, purine metabolism, and pyrimidine metabolism. Although several metabolites showed altered abundance in DCM, they also shared characteristics of DCM and T2DM rather than specific to DCM. Additionally, through biomarker analyses, we identified potential biomarkers for DCM, such as cytidine triphosphate, 11-ketoetiocholanolone, saccharopine, nervonic acid, and erucic acid. These biomarkers demonstrated distinct patterns and associations with metabolic pathways related to DCM. Our findings provide insights into the metabolic changes associated with DCM in T2DM patients and highlight potential biomarkers for further validation and clinical application. Further research is needed to elucidate the underlying mechanisms and validate the diagnostic and prognostic value of these biomarkers in larger cohorts.

The health and welfare effects of environmental governance: Evidence from China.

Environmental regulations aim to reduce pollution and improve air quality and the health of residents. However, there is a lack of research focusing on the health and welfare effects of low-carbon city pilot policies. In this context, this study takes China's low-carbon city pilot policy as an entry point, focuses on the health effects of public environmental governance, and systematically investigates the effects and mechanisms of low-carbon city development on the health of middle-aged and elderly people by applying the difference-in-differences method. The study finds that low-carbon city (LCC) policy significantly improves the physical and mental health of middle-aged and elderly people, and the main transmission mechanism is the reduction in air pollution and improvement in social capital. These results hold following a series of robustness tests. Furthermore, low-carbon city construction can reduce hospitalization and outpatient costs for people over 45 years old by up to 3 % and 15.5 %, respectively. The findings of this study provide useful policy insights for ensuring sustainable improvement in environmental quality and public health.