Identification and validation of cuproptosis-related molecular clusters in non-alcoholic fatty liver disease.

Non-alcoholic fatty liver disease (NAFLD) is a major chronic liver disease worldwide. Cuproptosis has recently been reported as a form of cell death that appears to drive the progression of a variety of diseases. This study aimed to explore cuproptosis-related molecular clusters and construct a prediction model. The gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database. The associations between molecular clusters of cuproptosis-related genes and immune cell infiltration were investigated using 50 NAFLD samples. Furthermore, cluster-specific differentially expressed genes were identified by the WGCNA algorithm. External datasets were used to verify and screen feature genes, and nomograms, calibration curves and decision curve analysis (DCA) were performed to verify the performance of the prediction model. Finally, a NAFLD-diet mouse model was constructed to further verify the predictive analysis, thus providing new insights into the prediction of NAFLD clusters and risks. The role of cuproptosis in the development of non-alcoholic fatty liver disease and immune cell infiltration was explored. Non-alcoholic fatty liver disease was divided into two cuproptosis-related molecular clusters by unsupervised clustering. Three characteristic genes (ENO3, SLC16A1 and LEPR) were selected by machine learning and external data set validation. In addition, the accuracy of the nomogram, calibration curve and decision curve analysis in predicting NAFLD clusters was also verified. Further animal and cell experiments confirmed the difference in their expression in the NAFLD mouse model and Mouse hepatocyte cell line. The present study explored the relationship between non-alcoholic fatty liver disease and cuproptosis, providing new ideas and targets for individual treatment of the disease.

Ion-Molecule Co-Confining Ammonium Vanadate Cathode for High-Performance Aqueous Zinc-Ion Batteries.

Vanadium-based cathode materials have attracted great attention in aqueous zinc-ion batteries (AZIBs). However, the inferior ion transport and cyclic stability due to the strong Coulomb interaction between Zn2+ and the lattice limit their further application. In this work, CO2 molecules are in situ embedded in the interlayer structure of NH4V4O10 by decomposing excess H2C2O4·2H2O in the main framework, obtaining an ion-molecule co-confining NH4V4O10 for AZIB cathode material. The introduced CO2 molecules expanded the interlayer spacing of NH4V4O10, broadened the diffusion channel of Zn2+, and stabilized the structure of NH4V4O10 as the interlayer pillars together with NH 4 + ${\mathrm{NH}}_4^ + $ , which effectively improved the Zn2+ diffusion kinetics and cycle stability of the electrode. In addition, the binding between NH 4 + ${\mathrm{NH}}_4^ + $ and the host framework is stabilized via hydrogen bonds with CO2 molecules. NVO-CO2-0.8 exhibited excellent specific capacity (451.1 mAh g-1 at 2 A g-1), cycle stability (214.0 mAh g-1 at 10 A g-1 after 1000 cycles) and rate performance. This work provides new ideas and approaches for optimizing vanadium-based materials with high-performance AZIBs.

Directed Self-Assembly of Polystyrene-Block-Polyhedral Oligomeric Silsesquioxane Monolayer by Nano-Trench for Nanopatterning.

This work pioneers to combine fast self-assembly of polyhedral oligomeric silsesquioxanes (POSS) nanocage-based giant surfactants with high etching contrast and directed self-assembly for reliable long-range lateral order to create well-aligned sub-10 nm line nanopatterns via reactive ion etching (RIE). Polystyrene-block-oligo(dimethylsiloxane) substituted POSS (PS-b-oDMS7POSS) with seven oligo(dimethylsiloxane) at the corners of the POSS nanocage and one polystyrene (PS) tail is designed and synthesized as a giant surfactant with self-assembly behaviors like block copolymer (BCP). In contrast to BCP, oDMS7POSS gives a volume-persistent "nanoatom" particle with higher mobility for fast self-assembly and higher segregation strength with PS for smaller feature size. By taking advantage of directed self-assembly using nano-trench fabricated by electron beam lithography, well-ordered nanostructured monolayer with well-aligned parallel oDMS7POSS cylinders can be formed by confined self-assembly within the nano-trench. With the optimization of the RIE treatment using O2 as an etchant, the high etching contrast from the oDMS7POSS and PS gives the formation of well-defined line nanopatterns with sub-10 nm critical dimension that can serve as a mask for pattern transfer in lithography. These results demonstrate a cost-effective approach for nanopatterning by utilizing a creatively designed giant surfactant with sub-10 nm feature size and excellent etching contrast for modern lithographic applications.

Insight into the Types of Alkanolamines on the Properties of Copper(II) Formate-Based Conductive Ink.

Conductive inks are one of the most important functional materials for printed flexible electronic devices, and their properties determine the methods of subsequent patterning and metallization. In comparison with copper nanoparticle or nanowire inks, copper particle-free inks employing copper(II) formate (Cuf) as a precursor have attracted the interest of researchers due to their flexibility in preparation, excellent stability, and lower conversion temperature. Alkanolamines can provide Cuf with excellent solubility in alcohols while being less toxic and having a certain reducibility, making them preferable ligands in comparison with aliphatic amines and pyridine. However, there have been few studies on the effects of the alkanolamine types on the performance of Cuf inks. Also, the decomposition mechanism of copper-alkanolamine complex inks is not clear. In this work, different kinds of alkanolamines were chosen as ligands to formulate Cuf inks to address the mentioned issues. The influences of amine types on the stability, wettability, thermal decomposition behavior, and electrical performance of the formulated Cuf particle-free inks were investigated in detail. The results show that the utilization of alkanolamines could provide Cuf with excellent solubility in alcohols, resulting in an ink with good stability and favorable wetting properties. The thermal decomposition temperature and electrical performance of the formulated copper ink are largely dependent on the amine used. When amines with a longer carbon chain and more branches were utilized to prepare the ink, a decreased decomposition temperature was observed on the derived inks because of the steric hindrance effect. Copper films with good morphology and conductivity could be obtained at low temperatures by selecting the appropriate alkanolamine. Copper particle-free conductive ink from 2-amino-2-methyl-1-propanol demonstrated better morphology and electrical performance (16.09 µΩ·cm) and was successfully used for conductive circuits by direct-writing.

A meta-analysis reveals increases in soil organic carbon following the restoration and recovery of croplands in Southwest China.

In China, the Grain for Green Program (GGP) is an ambitious project to convert croplands into natural vegetation, but exactly how changes in vegetation translate into changes in soil organic carbon remains less clear. Here we conducted a meta-analysis using 734 observations to explore the effects of land recovery on soil organic carbon and nutrients in four provinces in Southwest China. Following GGP, the soil organic carbon content (SOCc) and soil organic carbon stock (SOCs) increased by 33.73% and 22.39%, respectively, compared with the surrounding croplands. Similarly, soil nitrogen increased, while phosphorus decreased. Outcomes were heterogeneous, but depended on variations in soil and environmental characteristics. Both the regional land use and cover change indicated by the landscape type transfer matrix and net primary production from 2000 to 2020 further confirmed that the GGP promoted the forest area and regional mean net primary production. Our findings suggest that the GGP could enhance soil and vegetation carbon sequestration in Southwest China and help to develop a carbon-neutral strategy.

Association between asthma and COVID-19 severity during Omicron epidemic: a retrospective cohort study using real-world data.

BACKGROUND: The available evidence presented inconsistencies and inconclusive findings regarding the associations between co-existing asthma and mortality among COVID-19 patients. The objective of the current study is to investigate the relationship between asthma and severe outcomes after SARS-CoV-2 Omicron infection in an infection-naïve population. METHODS: A retrospective cohort study using propensity score matching was conducted. The COVID-19 patients requiring hospitalisation in Hong Kong from January 1, 2022, to November 13, 2022, an Omicron-predominated period, were identified. Severe clinical outcomes were defined as ICU admission and inpatient death after the first positive PCR results as well as a composite outcome of both. RESULTS: Of the 74,396 hospitalised COVID-19 patients admitted, 1,290 asthma patients and 18,641 non-asthma patients were included in the matched cohort. The rates of death and the composite outcome were 15·3% and 17·2%, respectively, among the non-asthma patients,12·2% and 13·6%, respectively, among the asthma patients, with adjusted hazard ratios equal to 0·775 (95% CI: 0·660-0·909) and 0·770 (95% CI: 0·662-0·895), respectively. The negative association was more apparent in the elderly and female groups. Asthma remained a factor that lowered the risk of disease severity even though the patients were not fully vaccinated with at least two doses. CONCLUSIONS: We used real-world data to demonstrate that asthma was not a risk factor for COVID-19 severity of the infections of Omicron variant, even though the patients were not fully vaccinated.

Recent advances in microbial synthesis of free heme.

Heme is an iron-containing porphyrin compound widely used in the fields of healthcare, food, and medicine. Compared to animal blood extraction, it is more advantageous to develop a microbial cell factory to produce heme. However, heme biosynthesis in microorganisms is tightly regulated, and its accumulation is highly cytotoxic. The current review describes the biosynthetic pathway of free heme, its fermentation production using different engineered bacteria constructed by metabolic engineering, and strategies for further improving heme synthesis. Heme synthetic pathway in Bacillus subtilis was modified utilizing genome-editing technology, resulting in significantly improved heme synthesis and secretion abilities. This technique avoided the use of multiple antibiotics and enhanced the genetic stability of strain. Hence, engineered B. subtilis could be an attractive cell factory for heme production. Further studies should be performed to enhance the expression of heme synthetic module and optimize the expression of heme exporter and fermentation processes, such as iron supply. KEY POINTS: • Strengthening the heme biosynthetic pathway can significantly increase heme production. • Heme exporter overexpression helps to promote heme secretion, thereby further promoting excessive heme synthesis. • Engineered B. subtilis is an attractive alternative for heme production.

The role of endoplasmic reticulum stress-related genes in the diagnosis and subtyping of non-alcoholic fatty liver disease.

Non-alcoholic fatty liver disease (NAFLD) is the most prevalent liver disease worldwide. Chronic activation of endoplasmic reticulum stress (ERS) in hepatocytes may promote the development of NAFLD, yet endoplasmic reticulum stress-related genes (ERSGs) have not been studied in NAFLD. Our aim is to study the relationship between ERSGs and the immune microenvironment of NAFLD patients and to construct predictive models. We screened 48 endoplasmic reticulum stress-related differentially expressed genes (ERSR-DEGs) using data from two GEO datasets and the GeneCards database. Enrichment analysis revealed that ERSR-DEGs are closely associated with immune-related pathways and functions. The immune infiltration profile of NAFLD was obtained by single sample gene set enrichment analysis (ssGSEA). There were significant differences in immune cell infiltration and immune function between NAFLD group and control group. Using 113 NAFLD samples, we explored two molecular clusters based on ERSR-DEGs. A five-gene SVM model was selected as the best machine learning model, and a nomogram based on five-gene SVM model showed good predictive efficiency. The mRNA expression levels of POR, PPP1R15A, FOS and FAS were significantly different between NAFLD mice and healthy mice. In conclusion, ERS is closely associated with the development of NAFLD. We established a promising and SVM-based predictive model to assess the risk of disease in patients with ERS subtypes and NAFLD.

Bioinformatics analysis of potential ferroptosis and non-alcoholic fatty liver disease biomarkers.

Ferroptosis plays a crucial role in the development of non-alcoholic fatty liver disease (NAFLD). In this study, we aimed to use a comprehensive bioinformatics approach and experimental validation to identify and verify potential ferroptosis-related genes in NAFLD. We downloaded the microarray datasets for screening differentially expressed genes (DEGs) and identified the intersection of these datasets with ferroptosis-related DEGs from the Ferroptosis database. Subsequently, ferroptosis-related DEGs were obtained using SVM analysis; the LASSO algorithm was then used to identify six marker genes. Furthermore, the CIBERSORT algorithm was used to estimate the proportion of different types of immune cells. Subsequently, we constructed drug regulatory networks and ceRNA regulatory networks. We identified six genes as marker genes for NAFLD, demonstrating their robust diagnostic abilities. Subsequent functional enrichment analysis results revealed that these marker genes were associated with multiple diseases and play a key role in NAFLD via the regulation of immune response and amino acid metabolism, among other pathways. The expression of hepatic EGR1, IL-6, SOCS1, and NR4A1 was significantly downregulated in the NAFLD model. Our findings provide new insights and molecular clues for understanding and treating NAFLD. Further studies are needed to assess the diagnostic potential of these markers for NAFLD.

Synthesis of Unsymmetrical Trisulfides from S-Substituted Sulphenylthiosulphates.

Trisulfide unit is widely found in natural products and has garnered attention due to the unique pharmacological and physiochemical properties. However, despite limited progress, widely applicable approaches for constructing unsymmetrical trisulfides have so far remain scarce. In this work, an easy-to-prepare, solid-state and scalable reagent, S-substituted sulphenylthiosulphate, has been developed for the divergent synthesis of unsymmetrical trisulfides. Alkyl electrophile substrates, including bromides, chlorides, iodides and tosylates, with diverse substituents are smoothly converted to the corresponding trisulfides with S-substituted sulphenylthiosulphates and thiourea as another sulfur source. Furthermore, the late-stage modification of drug molecules was successfully achieved through this method.

Synthesis of N-Difluoromethyl Carbonyl Compounds from N-Difluoromethylcarbamoyl Fluorides.

Fluorinated small molecules are commonly used in functional small-molecule chemistry, and N-difluoromethyl (N-CF2H) compounds are particularly intriguing due to their unique and unexplored physiochemical properties. However, despite limited progress, a general methodological approach to the synthesis of N-CF2H compounds remains elusive. Here, guided by computation, we present a simple and practical protocol to access N-CF2H amides and related carbonyl derivatives. The protocol involves a one-pot conversion of thioformamides through desulfurization-fluorination and acylation, providing N-difluoromethylcarbamoyl fluoride building blocks that can be further diversified to a variety of unexplored N-CF2H carbonyl compounds with rich functionality. Additionally, preliminary studies on their properties and stability showcased their potential application in pharmaceuticals and agrochemicals.

Estimation of the serial interval of monkeypox during the early outbreak in 2022.

With increased transmissibility and novel transmission mode, monkeypox poses new threats to public health globally in the background of the ongoing COVID-19 pandemic. Estimates of the serial interval, a key epidemiological parameter of infectious disease transmission, could provide insights into the virus transmission risks. As of October 2022, little was known about the serial interval of monkeypox due to the lack of contact tracing data. In this study, public-available contact tracing data of global monkeypox cases were collected and 21 infector-infectee transmission pairs were identified. We proposed a statistical method applied to real-world observations to estimate the serial interval of the monkeypox. We estimated a mean serial interval of 5.6 days with the right truncation and sampling bias adjusted and calculated the reproduction number of 1.33 for the early monkeypox outbreaks at a global scale. Our findings provided a preliminary understanding of the transmission potentials of the current situation of monkeypox outbreaks. We highlighted the need for continuous surveillance of monkeypox for transmission risk assessment.

Comparing the incubation period, serial interval, and infectiousness profile between SARS-CoV-2 Omicron and Delta variants.

In January 2022, the SARS-CoV-2 Omicron variants initiated major outbreaks and dominated the transmissions in Hong Kong, displacing an earlier outbreak seeded by the Delta variants. To provide insight into the transmission potential of the emerging variants, we aimed to compare the epidemiological characteristics of the Omicron and Delta variants. We analyzed the line-list clinical and contact tracing data of the SARS-CoV-2 confirmed cases in Hong Kong. Transmission pairs were constructed based on the individual contact history. We fitted bias-controlled models to the data to estimate the serial interval, incubation period and infectiousness profile of the two variants. Viral load data were extracted and fitted to the random effect models to investigate the potential risk modifiers for the clinical viral shedding course. Totally 14 401 confirmed cases were reported between January 1 and February 15, 2022. The estimated mean serial interval (4.4 days vs. 5.8 days) and incubation period (3.4 days vs. 3.8 days) were shorter for the Omicron than the Delta variants. A larger proportion of presymptomatic transmission was observed for the Omicron (62%) compared to the Delta variants (48%). The Omicron cases had higher mean viral load over an infection course than the Delta cases, with the elder cases appearing more infectious than the younger cases for both variants. The epidemiological features of Omicron variants were likely an obstacle to contact tracing measures, imposed as a major intervention in settings like Hong Kong. Continuously monitoring the epidemiological feature for any emerging SARS-CoV-2 variants in the future is needed to assist officials in planning measures for COVID-19 control.

Effectiveness of the booster dose of inactivated COVID-19 vaccine against Omicron BA.5 infection: a matched cohort study of adult close contacts.

BACKGROUND: Although COVID-19 vaccines and their booster regimens protect against symptomatic infections and severe outcomes, there is limited evidence about their protection against asymptomatic and symptomatic infections in real-world settings, particularly when considering that the majority of SARS-CoV-2 Omicron infections were asymptomatic. We aimed to assess the effectiveness of the booster dose of inactivated vaccines in mainland China, i.e., Sinopharm (BBIBP-CorV) and Sinovac (CoronaVac), against Omicron infection in an Omicron BA.5 seeded epidemic. METHODS: Based on an infection-naive but highly vaccinated population in Urumqi, China, the study cohort comprised all 37,628 adults who had a contact history with individuals having SARS-CoV-2 infections, i.e., close contacts, between August 1 and September 7, 2022. To actively detect SARS-CoV-2 infections, RT-PCR tests were performed by local authorities on a daily basis for all close contacts, and a testing-positive status was considered a laboratory-confirmed outcome. The cohort of close contacts was matched at a ratio of 1:5 with the fully vaccinated (i.e., 2 doses) and booster vaccinated groups (i.e., 3 doses) according to sex, age strata, calendar date, and contact settings. Multivariate conditional logistic regression models were adopted to estimate the marginal effectiveness of the booster dose against Omicron BA.5 infection after adjusting for confounding variables. Subgroup analyses were performed to assess vaccine effectiveness (VE) in different strata of sex, age, the time lag from the last vaccine dose to exposure, and the vaccination status of the source case. Kaplan-Meier curves were employed to visualize the follow-up process and testing outcomes among different subgroups of the matched cohort. FINDINGS: Before matching, 37,099 adult close contacts were eligible for cohort enrolment. After matching, the 2-dose and 3-dose groups included 3317 and 16,051 contacts, and the proportions with Omicron infections were 1.03% and 0.62% among contacts in the 2-dose and 3-dose groups, respectively. We estimated that the adjusted effectiveness of the inactivated booster vaccine versus 2 doses against Omicron infection was 35.5% (95% CI 2.0, 57.5). The booster dose provided a higher level of protection, with an effectiveness of 60.2% (95% CI 22.8, 79.5) for 15-180 days after vaccination, but this VE decreased to 35.0% (95% CI 2.8, 56.5) after 180 days. Evidence for the protection of the booster dose was detected among young adults aged 18-39 years, but was not detected for those aged 40 years or older. INTERPRETATION: The receipt of the inactivated vaccine booster dose was associated with a significantly lower Omicron infection risk, and our findings confirmed the vaccine effectiveness (VE) of booster doses against Omicron BA.5 variants. Given the rapid evolution of SARS-CoV-2, we highlight the importance of continuously monitoring the protective performance of vaccines against the genetic variants of SARS-CoV-2, regardless of existing vaccine coverage.

Fluorine-Containing Functional Group-Based Energetic Materials.

Molecules featuring fluorine-containing functional groups exhibit outstanding properties with high density, low sensitivity, excellent thermal stability, and good energetic performance due to the strong electron-withdrawing ability and high density of fluorine. Hence, they play a pivotal role in the field of energetic materials. In light of current theoretical and experimental reports, this review systematically focuses on three types of energetic materials possessing fluorine-containing functional groups F- and NF2 - substituted trinitromethyl groups (C(NO2 )2 F, C(NO2 )2 NF2 ), trifluoromethyl group (CF3 ), and difluoroamino and pentafluorosulfone groups (NF2 , SF5 ) and investigates the synthetic methods, physicochemical parameters, and energetic properties of each. The incorporation of fluorine-containing functional moieties is critical for the development of novel high energy density materials, and is rapidly being adopted in the design of energetic materials.

Characterizing superspreading potential of infectious disease: Decomposition of individual transmissibility.

In the context of infectious disease transmission, high heterogeneity in individual infectiousness indicates that a few index cases can generate large numbers of secondary cases, a phenomenon commonly known as superspreading. The potential of disease superspreading can be characterized by describing the distribution of secondary cases (of each seed case) as a negative binomial (NB) distribution with the dispersion parameter, k. Based on the feature of NB distribution, there must be a proportion of individuals with individual reproduction number of almost 0, which appears restricted and unrealistic. To overcome this limitation, we generalized the compound structure of a Poisson rate and included an additional parameter, and divided the reproduction number into independent and additive fixed and variable components. Then, the secondary cases followed a Delaporte distribution. We demonstrated that the Delaporte distribution was important for understanding the characteristics of disease transmission, which generated new insights distinct from the NB model. By using real-world dataset, the Delaporte distribution provides improvements in describing the distributions of COVID-19 and SARS cases compared to the NB distribution. The model selection yielded increasing statistical power with larger sample sizes as well as conservative type I error in detecting the improvement in fitting with the likelihood ratio (LR) test. Numerical simulation revealed that the control strategy-making process may benefit from monitoring the transmission characteristics under the Delaporte framework. Our findings highlighted that for the COVID-19 pandemic, population-wide interventions may control disease transmission on a general scale before recommending the high-risk-specific control strategies.

Clinical Data based XGBoost Algorithm for infection risk prediction of patients with decompensated cirrhosis: a 10-year (2012-2021) Multicenter Retrospective Case-control study.

OBJECTIVES: To appraise effective predictors for infection in patients with decompensated cirrhosis (DC) by using XGBoost algorithm in a retrospective case-control study. METHODS: Clinical data were retrospectively collected from 6,648 patients with DC admitted to five tertiary hospitals. Indicators with significant differences were determined by univariate analysis and least absolute contraction and selection operator (LASSO) regression. Further multi-tree extreme gradient boosting (XGBoost) machine learning-based model was used to rank importance of features selected from LASSO and subsequently constructed infection risk prediction model with simple-tree XGBoost model. Finally, the simple-tree XGBoost model is compared with the traditional logical regression (LR) model. Performances of models were evaluated by area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity. RESULTS: Six features, including total bilirubin, blood sodium, albumin, prothrombin activity, white blood cell count, and neutrophils to lymphocytes ratio were selected as predictors for infection in patients with DC. Simple-tree XGBoost model conducted by these features can predict infection risk accurately with an AUROC of 0.971, sensitivity of 0.915, and specificity of 0.900 in training set. The performance of simple-tree XGBoost model is better than that of traditional LR model in training set, internal verification set, and external feature set (P < 0.001). CONCLUSIONS: The simple-tree XGBoost predictive model developed based on a minimal amount of clinical data available to DC patients with restricted medical resources could help primary healthcare practitioners promptly identify potential infection.

Solvent-Free Templated Synthesis of Core-Crosslinked Star-Shaped Polymers in Supramolecular Body-Centered Cubic Phase.

This study reports the exploration of a solvent-free supramolecular templated synthesis strategy toward highly core-cross-linked star-shaped polymers (CSPs). To achieve this, a kind of cross-linkable giant surfactant, based on a functionalized polyhedral oligomeric silsesquioxanes (POSS) head tethered with a diblock copolymer tail containing reactive benzocyclobutene groups, is designed and prepared. By varying the volume fraction of linear block copolymer tail, these giant surfactants can self-assemble into a body-centered cubic (BCC) structure in bulk, in which the supramolecular spheres are composed of a core of POSS cages, a middle shell of crosslinkable poly(4-vinylbenzocyclobutene) (PBCB) blocks, and a corona of inert polystyrene (PS) blocks. The solvent-free thermally induced cross-linking reaction of the benzocyclobutene groups can be finished in 5 min upon heating, resulting in well-defined polymeric spheres with over 90 linear chains surrounding the cross-linked cores. The outer PS blocks serve as the protection corona to ensure that cross-linking of giant surfactants occurs in each supramolecular spherical domain. Given the modular design and diversity of the POSS-based giant surfactants, it is believed that the strategy may enable access to a wide range of CSPs.

Astaxanthin alleviates PM2.5-induced cardiomyocyte injury via inhibiting ferroptosis.

BACKGROUND: Long-term exposure of humans to air pollution is associated with an increasing risk of cardiovascular diseases (CVDs). Astaxanthin (AST), a naturally occurring red carotenoid pigment, was proved to have multiple health benefits. However, whether or not AST also exerts a protective effect on fine particulate matter (PM2.5)-induced cardiomyocyte damage and its underlying mechanisms remain unclear. METHODS: In vitro experiments, the H9C2 cells were subjected to pretreatment with varying concentrations of AST, and then cardiomyocyte injury model induced by PM2.5 was established. The cell viability and the ferroptosis-related proteins expression were measured in different groups. In vivo experiments, the rats were pretreated with different concentrations of AST for 21 days. Subsequently, a rat model of myocardial PM2.5 injury was established by intratracheal instillation every other day for 1 week. The effects of AST on myocardial tissue injury caused by PM2.5 indicating by histological, serum, and protein analyses were examined. RESULTS: AST significantly ameliorated PM2.5-induced myocardial tissue injury, inflammatory cell infiltration, the release of inflammatory factors, and cardiomyocyte H9C2 cell damage. Mechanistically, AST pretreatment increased the expression of SLC7A11, GPX4 and down-regulated the expression of TfR1, FTL and FTH1 in vitro and in vivo. CONCLUSIONS: Our study suggest that ferroptosis plays a significant role in the pathogenesis of cardiomyocyte injury induced by PM2.5. AST may serve as a potential therapeutic agent for mitigating cardiomyocyte injury caused by PM2.5 through the inhibition of ferroptosis.

Functional Polythioamides Derived from Thiocarbonyl Fluoride.

Polythioamide is a unique type of sulfur-containing polymer with advanced functionalities. Nonetheless, the elemental sulfur commonly used in their synthesis tends to react readily with unsaturated functional groups, thereby limiting the scope of eligible substrates. Inspired by the highly efficient sulfur-fluoride exchange (SuFEx) polymerization through discrete hubs, we present herein a pioneering and versatile approach to the synthesis of polythioamides from diboronic acids, secondary diamines, and thiocarbonyl fluoride as the central connective hub. Well-defined structures, including previously inaccessible unsaturated substrates, were realized. These newly devised polythioamides can efficiently and selectively bind to metal ions and were applied in precious-metal recovery. Further development resulted in PdII -crosslinked single-chain nanoparticles serving as recyclable homogeneous catalysts, thus demonstrating the vast potential of these unprecedented polythioamides. We anticipate that thiocarbonyl fluoride could emerge as a potent hub for facilitating the intricate synthesis of sulfur-containing polymers.