Unraveling the impact of high arsenic, fluoride and microbial population in community tubewell water around coal mines in a semiarid region: Insight from health hazards, and geographic information systems.

High arsenic (As), fluoride (F-), and microbial pathogens coexist in semiarid conditions afflicting > 240 million people worldwide including Pakistan. Groundwater quality has declined due to geogenic and manmade activities providing suitable ground for ubiquity, bioavailability, and toxicity of contaminants. We tested the health hazard, distribution, and apportionment of As, F-, and microbes in groundwater around coal mines in Quetta, Pakistan. The range of As, and F- concentrations in groundwater were 0.2-16.6 µg/L, 0.4-18.5 mg/L. Both, As and F- correlate with high HCO3-, pH, Na+, SO42-, Fe, and Mn, and negatively with Ca2+ water. The coalfield showed many folds higher As 15.8-28.5 µg/L, and F- 10.8-34.5 mg/L compared to groundwater-wells. Geochemical phases revealed saturation of groundwater with calcite, dolomite, fluorite, gypsum, and undersaturation with halite-mirabilite, and arsenopyrite minerals. The positive matrix factorization (PMF) model assessed five-factor solutions: geogenic, industrial, coal mining, sulfide & fluoride-bearing mineral-dissolution, and agriculture pollution delivered As, F-, and microbial contamination. About 24.6 % and 64.4 % of groundwater samples exceeded the WHO guidelines of As 10 µg/L, F- 1.5 mg/L. The carcinogenicity, and non-carcinogenicity of As, and F- were higher in children than adults. Therefore, health hazards in children are of great concern in achieving sustainable management goals.

Efficacy evaluation of a bivalent subunit vaccine against epidemic PEDV heterologous strains with low cross-protection.

Variant Porcine epidemic diarrhea virus (PEDV), which causes diarrhea and high mortality in piglets, has become a major pathogen, and co-epidemics of different subtypes of the virus have become a very thorny problem for the clinical prevention and control of PEDV. However, cross-protection between epidemic G2a and G2b subtype strains has not been observed, and there is currently no vaccine against both G2a and G2b strains. In this study, we demonstrate the low cross-protection between G2a and G2b strains with piglet immunization and challenge tests. The trimeric full-length S proteins of G2a and G2b variants were purified and a bivalent subunit vaccine against PEDV G2a/G2b-S was developed. In active and passive immune protection tests, the bivalent subunit vaccine produced high neutralizing antibody titers and S-specific immunoglobulin G (IgG) and IgA titers against both the G2a and G2b strains in piglets and sows. In the attack phase of the viruses, the clinical symptoms and microscopic lesions in the immunized groups were significantly alleviated. Importantly, the PEDV G2a/G2b-S bivalent subunit vaccine conferred effective passive immunity against PEDV G2a and G2b challenges in the form of colostrum-derived antibodies from the immunized sows. In conclusion, our data demonstrate the low cross-protection of PEDV epidemic G2a and G2b strains and show that the G2a/G2b-S bivalent subunit vaccine is protective against both G2a and G2b strains. It is therefore a candidate vaccine for PEDV prevention. IMPORTANCE: The detection rate of PEDV G2a subtype strains is currently increasing. Although commercial vaccines are available, most vaccines do not exert an ideal protective effect against these strains. Furthermore, there is no definitive research into the cross-protection between G2a and G2b strains, and no bivalent vaccine provides joint protection against both. Therefore, in this study, we investigated the cross-protection between PEDV G2a and G2b strains and designed a candidate bivalent subunit vaccine combining the trimeric S proteins of the G2a and G2b subtypes. We demonstrate that the cross-protection between strains G2a and G2b is poor and that this bivalent subunit vaccine protects piglets from viral attack by inducing both active and passive immunity. This study emphasizes the effectiveness of the PEDV G2a/G2b-S bivalent subunit vaccine and provides a feasible method for the development of efficient PEDV vaccines.

Sterile water and regional citrate anticoagulation: A simple CRRT strategy for safe correction of severe hyponatraemia.

BACKGROUND: Hyponatraemia is a prevalent electrolyte disturbance observed in critically ill patients. The rapid correction of low plasma sodium levels by continuous renal replacement therapy (CRRT) carries the risk of developing osmotic demyelination syndrome (ODS), which can be prevented by implementing an individualized CRRT method. AIM: This study aims to introduce a CRRT protocol for the safe and gradual correction of severe hyponatraemia. STUDY DESIGN: This retrospective case series study was conducted in an intensive care unit (ICU). All four patients with severe hyponatraemia (<125 mmol/L) and renal failure between October 1, 2022, and September 30, 2023, were treated by CRRT with sterile water and regional citrate anticoagulation (RCA). Data on patient demographics, laboratory biochemical parameters, urine outputs and CRRT-related adverse events were collected. Laboratory parameters and urine outputs were compared by paired t-tests before and after CRRT. RESULTS: After CRRT, sodium levels were significantly increased (112.7 ± 6.7 vs. 141.9 ± 2.8 mmol/L, p = .005). Abnormal urine outputs, potassium, creatinine and bicarbonate were corrected (p for all <.05). Safe and gradual correction of hyponatraemia and internal environmental dysregulation was achieved in all patients without any complications related to CRRT, particularly ODS. CONCLUSION: It is a novel and simple strategy to correct severe hyponatraemia effectively while ensuring the safety of patients that can be easily implemented by experienced nurse staff. RELEVANCE TO CLINICAL PRACTICE: The sterile water-based protocol for postfilter dilution is safe to correct severe hyponatraemia with RCA and can be easily performed by experienced critical care nurses according to the precalculated formula. CRRT-trained, experienced ICU nurses are competent to initiate and adjust sterile water infusion discretely to prevent overcorrection of hyponatraemia.

Interactions at the Oviposition Scar: Molecular and Metabolic Insights into Elaeagnus angustifolia's Resistance Response to Anoplophora glabripennis.

The Russian olive (Elaeagnus angustifolia), which functions as a "dead-end trap tree" for the Asian long-horned beetle (Anoplophora glabripennis) in mixed plantations, can successfully attract Asian long-horned beetles for oviposition and subsequently kill the eggs by gum. This study aimed to investigate gum secretion differences by comparing molecular and metabolic features across three conditions-an oviposition scar, a mechanical scar, and a healthy branch-using high-performance liquid chromatography and high-throughput RNA sequencing methods. Our findings indicated that the gum mass secreted by an oviposition scar was 1.65 times greater than that secreted by a mechanical scar. Significant differences in gene expression and metabolism were observed among the three comparison groups. A Kyoto Encyclopedia of Genes and Genomes annotation and enrichment analysis showed that an oviposition scar significantly affected starch and sucrose metabolism, leading to the discovery of 52 differentially expressed genes and 7 differentially accumulated metabolites. A network interaction analysis of differentially expressed metabolites and genes showed that EaSUS1, EaYfcE1, and EaPGM1 regulate sucrose, uridine diphosphate glucose, α-D-glucose-1P, and D-glucose-6P. Although the polysaccharide content in the OSs was 2.22 times higher than that in the MSs, the sucrose content was lower. The results indicated that the Asian long-horned beetle causes Russian olive sucrose degradation and D-glucose-6P formation. Therefore, we hypothesized that damage caused by the Asian long-horned beetle could enhance tree gum secretions through hydrolyzed sucrose and stimulate the Russian olive's specific immune response. Our study focused on the first pair of a dead-end trap tree and an invasive borer pest in forestry, potentially offering valuable insights into the ecological self-regulation of Asian long-horned beetle outbreaks.

A smartphone-based immunochromatographic strip platform for on-site quantitative detection of antigenic targets.

To report the testing signal of an immunochromatographic assay for on-site quantitative detection, a portable and user-friendly smartphone-based biosensing platform is developed in this study. This innovative system is composed of an ambient light sensor inherent smartphone reader and a 3D-printed handhold device, a quantitative tool capable of directly interpreting carbon nanoparticle (CNP)-conjugated immunochromatographic strips. To showcase the platform capability, the smartphone-based immunochromatography system (SPICS) reader and device were successfully used in CNP strips for rapid detection of the early pregnancy marker human chorionic gonadotropin in female urine (HCG; limit of detection [LOD]: 0.30 mIU mL-1), prostate-specific antigen in patient blood (PSA; LOD: 0.28 ng mL-1) and ampicillin residue in animal milk (AMP; LOD: 0.23 ng mL-1). The results were fully correlated with conventional commercial instruments (R2 = 0.99). The SPICS platform exhibits significant advantages, including portability, cost-effectiveness, easy operation, and rapid and quantitative detection, making it a valuable on-site diagnosis tool for use in home and community healthcare facilities.

Spatial effects of township health centers' health resource allocation efficiency in China.

Introduction: China is a large agricultural nation with the majority of the population residing in rural areas. The allocation of health resources in rural areas significantly affects the basic rights to life and health for rural residents. Despite the progress made by the Chinese government in improving rural healthcare, there is still room for improvement. This study aims to assess the spatial spillover effects of rural health resource allocation efficiency in China, particularly focusing on township health centers (THCs), and examine the factors influencing this efficiency to provide recommendations to optimize the allocation of health resources in rural China. Methods: This study analyzed health resource allocation efficiency in Chinese rural areas from 2012 to 2021 by using the super-efficiency SBM model and the global Malmquist model. Additionally, the spatial auto-correlation of THC health resource allocation efficiency was verified through Moran test, and three spatial econometric models were constructed to further analyze the factors influencing efficiency. Results: The key findings are: firstly, the average efficiency of health resource allocation in THCs was 0.676, suggesting a generally inefficient allocation of health resources over the decade. Secondly, the average Malmquist productivity index of THCs was 0.968, indicating a downward trend in efficiency with both non-scale and non-technical efficient features. Thirdly, Moran's Index analysis revealed that efficiency has a significant spatial auto-correlation and most provinces' values are located in the spatial agglomeration quadrant. Fourthly, the SDM model identified several factors that impact THC health resource allocation efficiency to varying degrees, including the efficiency of total health resource allocation, population density, PGDP, urban unemployment rate, per capita disposable income, per capita healthcare expenditure ratio, public health budget, and passenger traffic volume. Discussion: To enhance the efficiency of THC healthcare resource allocation in China, the government should not only manage the investment of health resources to align with the actual demand for health services but also make use of the spatial spillover effect of efficiency. This involves focusing on factors such as total healthcare resource allocation efficiency, population density, etc. to effectively enhance the efficiency of health resource allocation and ensure the health of rural residents.

Activity of OSBPI fungicide fluoxapiprolin against plant-pathogenic oomycetes and its systemic translocation in plants.

Fluoxapiprolin, a novel piperidinyl thiazole isoxazoline fungicide, was developed by Bayer Crop Science in 2012. Despite its well-documented inhibitory activity against plant pathogenic oomycetes such as Phytophthora capsici and Phytophthora infestans, limited information regarding its antifungal spectrum and protective and curative activity is available. Fluoxapiprolin exhibited strong inhibitory activity against Phytophthora spp. and several Pythium spp., with EC50 values ranging from 2.12 × 10-4 to 2.92 µg/mL. It was much more effective against P. capsici in inhibiting mycelial growth, sporangium production, and cystospore germination than at reducing zoospore release. Moreover, fluoxapiprolin displayed both protective and curative activity against P. capsici infection in pepper plants under greenhouse conditions, with systemic translocation capability confirmed by High Performance Liquid Chromatography (HPLC) analysis. The results demonstrated the strong inhibitory activity of fluoxapiprolin against economically important plant oomycete pathogens, including Phytophthora spp. and several Pythium spp., and its certain translocation activity in pepper plants.

Sublethal Effects of Pyridaben on the Predatory Function of Neoseiulus womersleyi.

Pyridaben is a widely utilized, broad-spectrum contact acaricide, which has notable sublethal effects that impair the predatory capabilities of predatory mites, but the specific mechanisms that affect the predatory functions remain underexplored. When predatory mites hunt for prey, they may rely on Niemann-Pick-type C2 (NPC2) proteins to collect herbivore-induced plant volatiles (HIPVs) and other odor molecules to locate and pursue their prey. This study elucidated that pyridaben significantly diminished the predatory efficiency and searching behavior of the predatory mite Neoseiulus womersleyi. Key metrics, including predatory capacity (a/Th) and predation rate (a) on various developmental stages of Tetranychus urticae, were markedly reduced in treated mites compared to controls. The searching efficiency (S) also declined proportionally with the increased sublethal dose of pyridaben. A gene linked to olfactive functions, NwNPC2a, was cloned from N. womersleyi. Post-treatment with pyridaben at LC30 and LC50 concentrations resulted in a substantial downregulation of NwNPC2a expression by 60.15% and 58.63%, respectively. Silencing NwNPC2a in N. womersleyi females led to significant reductions in the attack rate (a), handling time (Th), predation efficiency (a/Th), and maximum predation rate (1/Th). The searching efficiency (S) was also lower than that of the control group, displaying a slight decline with the increasing prey density. The findings revealed that pyridaben exerted inhibitory effects on both the predatory function and searching efficiency of N. womersleyi populations. The decrease in predatory performance at LC30 and LC50 concentrations was attributable to the suppression of NwNPC2a gene expression. RNA interference (RNAi) studies corroborated that the NwNPC2a gene plays a critical role in the predation process of N. womersleyi. Thus, the underlying molecular mechanism through which pyridaben compromises the predatory function of N. womersleyi likely involves the downregulation of NwNPC2a expression.

Predicting ICU Readmission from Electronic Health Records via BERTopic with Long Short Term Memory Network Approach.

Background: The increasing rate of intensive care unit (ICU) readmissions poses significant challenges in healthcare, impacting both costs and patient outcomes. Predicting patient readmission after discharge is crucial for improving medical quality and reducing expenses. Traditional analyses of electronic health record (EHR) data have primarily focused on numerical data, often neglecting valuable text data. Methods: This study employs a hybrid model combining BERTopic and Long Short-Term Memory (LSTM) networks to predict ICU readmissions. Leveraging the MIMIC-III database, we utilize both quantitative and text data to enhance predictive capabilities. Our approach integrates the strengths of unsupervised topic modeling with supervised deep learning, extracting potential topics from patient records and transforming discharge summaries into topic vectors for more interpretable and personalized predictions. Results: Utilizing a comprehensive dataset of 36,232 ICU patient records, our model achieved an AUROC score of 0.80, thereby surpassing the performance of traditional machine learning models. The implementation of BERTopic facilitated effective utilization of unstructured data, generating themes that effectively guide the selection of relevant predictive factors for patient readmission prognosis. This significantly enhanced the model's interpretative accuracy and predictive capability. Additionally, the integration of importance ranking methods into our machine learning framework allowed for an in-depth analysis of the significance of various variables. This approach provided crucial insights into how different input variables interact and impact predictions of patient readmission across various clinical contexts. Conclusions: The practical application of BERTopic technology in our hybrid model contributes to more efficient patient management and serves as a valuable tool for developing tailored treatment strategies and resource optimization. This study highlights the significance of integrating unstructured text data with traditional quantitative data to develop more accurate and interpretable predictive models in healthcare, emphasizing the importance of individualized care and cost-effective healthcare paradigms.

Regional differences, dynamic evolution, and influencing factors of high-quality medical resources in China's ethnic minority areas.

Background: In China, as people's standard of living improves and the medical service system becomes more sophisticated, the demand for higher-quality and improved healthcare services is steadily rising. Inequality in health resource allocation (HRA) is more pronounced in ethnic minority areas (EMAs) than in developed regions. However, little research exists on high-quality medical resources (HQMRs) in China's EMAs. Hence, we examined the spatiotemporal dynamic evolution of HQMRs in China's EMAs from 2007 to 2021 and identified the main factors affecting their respective HQMR levels. Methods: We selected tertiary hospitals to represent the quality of healthcare resources. We employed descriptive statistical techniques to analyze changes in the distribution of HQMRs from 2007 to 2021. We used the Dagum Gini coefficient and kernel density approach to analyze the dynamic evolution of HQMRs in China's EMAs. We utilized the least squares dummy variable coefficient (LSDVC) to identify key factors affecting HQMR. Results: The number of HQMRs in each EMA has risen annually. The average number of tertiary hospitals increased from 175 in 2007 to 488 in 2021. The results of the Dagum Gini coefficient revealed that the differences in the HQMR level in China's EMAs have slowly declined, and intra-regional disparities have now become the primary determining factor influencing overall variations. The kernel density plot indicated that the HQMR level improved significantly during the study period, but bifurcation became increasingly severe. Using the LSDVC for analysis, we found that gross domestic product (GDP) per capita, the size of the resident population, and the number of students enrolled in general higher education exhibited a significant negative correlation with HQMR levels, while GDP and urbanization rate had a significant promoting effect. Conclusion: The HQMR level in EMAs has risen rapidly but remains inadequate. The differences in HQMR between regions have continued to narrow, but serious bifurcation has occurred. Policymakers should consider economic growth, education, and population size rather than simply increasing the number of HQMRs everywhere.

MTCH2 promotes the malignant progression of ovarian cancer through the upregulation of AIMP2 expression levels, mitochondrial dysfunction and by mediating energy metabolism.

Ovarian cancer (OC) is a gynecological malignancy that ranks among the most common female cancers worldwide and notably reduces a patient's quality of life. Mitochondrial carrier homology 2 (MTCH2) is a mitochondrial outer membrane protein that serves a regulatory role in mitochondrial metabolism and cell death. The precise contribution and underlying molecular pathways of MTCH2 in the context of OC development is currently unclear. The present study aimed to investigate the roles of MTCH2 in the energy metabolism, cell proliferation and metastatic potential of OC cells and evaluate the regulatory relationship between MTCH2, aminoacyl transfer RNA synthetase-interacting multifunctional protein 2 (AIMP2) and claudin-3. An analysis of 67 patients with high-grade serous OC demonstrated increased expression levels of MTCH2, AIMP2 and claudin-3 in OC tumor tissue samples compared with in corresponding normal tissues adjacent to OC tissue samples. MTCH2 overexpression was significantly associated with the International Federation of Gynecology and Obstetrics stage and tumor differentiation of the OC tumor samples. In vitro experiments using the SK-OV-3 OC cell line demonstrated that MTCH2 exerts a regulatory effect on the cell proliferation, invasion and migratory capabilities of these cells. Knockdown of MTCH2 reduced ATP production, induced mitochondrial dysfunction and promoted cytoskeleton remodeling and apoptosis in SK-OV-3 OC cells. In addition, MTCH2 knockdown downregulated the expression levels of both claudin-3 and AIMP2 proteins. Knockdown of AIMP2 inhibited the regulatory effect of MTCH2. Co-immunoprecipitation experiments demonstrated that MTCH2 interacts with AIMP2 and claudin-3. The present study provides novel insights into the treatment of OC metastasis, as MTCH2 was demonstrated to serve roles in the progression of OC cells through the regulation of claudin-3 via AIMP2, which could provide novel insights into the treatment of ovarian cancer metastasis.

Bioinspired multifunctional cellulose film: In situ bacterial capturing and killing for managing infected wounds.

Bacterial infection of cutaneous wounds can easily lead to occurrence of chronic wounds and even more serious diseases. Therefore, multifunctional, biodegradable, and reusable wound dressings that can quickly manage wound infection and promote wound healing are urgently desired. Herein, inspired by the "capturing and killing" action of Drosera peltata Thunb., a biomimetic cellulose film was constructed to capture the bacteria (via the rough structure of the film) and kill them (via the combination of photodynamic therapy and chemotherapy) to promote wound tissue remodeling. The film (termed OBC-PR) was simply prepared by chemically crosslinking the oxidized bacterial cellulose (OBC) with polyhexamethylene guanidine hydrochloride (PHGH) and rose bengal (RB). Notably, it could effectively capture Escherichia coli and Staphylococcus aureus bacterial cells with capture efficiencies of ∼99 % and ∼96 %, respectively, within 10 min. Furthermore, the in vivo experiments showed that OBC-PR could effectively promote the macrophage polarization toward the M2 phenotype and adequately induce the reconstruction of blood vessels and nerves, thus promoting wound healing. This study provides a potential direction for designing multifunctional wound dressings for managing infected skin wounds in the future.

Development and validation of an integrated system for lung cancer screening and post-screening pulmonary nodules management: a proof-of-concept study (ASCEND-LUNG).

Background: In order to address the low compliance and dissatisfied specificity of low-dose computed tomography (LDCT), efficient and non-invasive approaches are needed to complement its limitations for lung cancer screening and management. The ASCEND-LUNG study is a prospective two-stage case-control study designed to evaluate the performance of a liquid biopsy-based comprehensive lung cancer screening and post-screening pulmonary nodules management system. Methods: We aimed to develop a comprehensive lung cancer system called Peking University Lung Cancer Screening and Management System (PKU-LCSMS) which comprises a lung cancer screening model to identify specific populations requiring LDCT and an artificial intelligence-aided (AI-aided) pulmonary nodules diagnostic model to classify pulmonary nodules following LDCT. A dataset of 465 participants (216 cancer, 47 benign, 202 non-cancer control) were used for the two models' development phase. For the lung cancer screening model development, cancer participants were randomly split at a ratio of 1:1 into the train and validation cohorts, and then non-cancer controls were age-matched to the cancer cases in a 1:1 ratio. Similarly, for the AI-aided pulmonary nodules model, cancer and benign participants were also randomly divided at a ratio of 2:1 into the train and validation cohorts. Subsequently, during the model validation phase, sensitivity and specificity were validated using an independent validation cohort consisting of 291 participants (140 cancer, 25 benign, 126 non-cancer control). Prospectively collected blood samples were analyzed for multi-omics including cell-free DNA (cfDNA) methylation, mutation, and serum protein. Computerized tomography (CT) images data was also obtained. Paired tissue samples were additionally analyzed for DNA methylation, DNA mutation, and messenger RNA (mRNA) expression to further explore the potential biological mechanisms. This study is registered with ClinicalTrials.gov, NCT04817046. Findings: Baseline blood samples were evaluated for the whole screening and diagnostic process. The cfDNA methylation-based lung cancer screening model exhibited the highest area under the curve (AUC) of 0.910 (95% CI, 0.869-0.950), followed by the protein model (0.891 [95% CI, 0.845-0.938]) and lastly the mutation model (0.577 [95% CI, 0.482-0.672]). Further, the final screening model, which incorporated cfDNA methylation and protein features, achieved an AUC of 0.963 (95% CI, 0.942-0.984). In the independent validation cohort, the multi-omics screening model showed a sensitivity of 99.2% (95% CI, 0.957-1.000) at a specificity of 56.3% (95% CI, 0.472-0.652). For the AI-aided pulmonary nodules diagnostic model, which incorporated cfDNA methylation and CT images features, it yielded a sensitivity of 81.1% (95% CI, 0.732-0.875), a specificity of 76.0% (95% CI, 0.549-0.906) in the independent validation cohort. Furthermore, four differentially methylated regions (DMRs) were shared in the lung cancer screening model and the AI-aided pulmonary nodules diagnostic model. Interpretation: We developed and validated a liquid biopsy-based comprehensive lung cancer screening and management system called PKU-LCSMS which combined a blood multi-omics based lung cancer screening model incorporating cfDNA methylation and protein features and an AI-aided pulmonary nodules diagnostic model integrating CT images and cfDNA methylation features in sequence to streamline the entire process of lung cancer screening and post-screening pulmonary nodules management. It might provide a promising applicable solution for lung cancer screening and management. Funding: This work was supported by Science, Science, Technology & Innovation Project of Xiongan New Area, Beijing Natural Science Foundation, CAMS Innovation Fund for Medical Sciences (CIFMS), Clinical Medicine Plus X-Young Scholars Project of Peking University, the Fundamental Research Funds for the Central Universities, Research Unit of Intelligence Diagnosis and Treatment in Early Non-small Cell Lung Cancer, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, Peking University People's Hospital Research and Development Funds, National Key Research and Development Program of China, and the fundamental research funds for the central universities.

A flexible glucose biosensor modified by reduced-swelling and conductive zwitterionic hydrogel enzyme membrane.

This paper reports a flexible glucose biosensor which is modified by a reduced-swelling and conductive zwitterionic hydrogel enzyme membrane that contains two forms of chemical cross-links. One chemical cross-linking is induced by thermal initiators and forms the basal network of the hydrogel. Another cross-linking is achieved by the coordination interactions between the multivalent metal ion Al3+ and anionic group -COO- of zwitterionic poly-carboxy betaine (pCBMA), which significantly increase the cross-linking density of the zwitterionic hydrogel, improving the reduced-swelling property and reducing the pore size. The better reduced-swelling property and reduced diameters of pores within the zwitterionic hydrogel make less glucose oxidase (GOx) leakage, thus significantly improving the enzyme membrane's service life. By introducing the Al3+ and Cl-, the conductivity of the zwitterionic hydrogel is enhanced approximately 10.4-fold. According to the enhanced conductivity, the reduced-swelling property, and the high GOx loading capacity of the zwitterionic hydrogel, the sensitivity of the biosensor with GOx/pCBMA-Al3+ is significantly improved by 5 times and has a long service life. Finally, the proposed GOx/pCBMA-Al3+ biosensor was applied in non-invasive blood glucose detection on the human body, verifying the capability in practice.

Integrated analysis of differentially m6A modified and expressed lncRNAs for biomarker identification in coronary artery disease.

N6-methyladenosine (m6A) is the most prevalent internal RNA modification in mammals. However, limited research has been conducted on the role of m6A in coronary artery disease (CAD). We conducted methylated RNA immunoprecipitation sequencing and RNA sequencing to obtain a genome-wide profile of m6A-modified long noncoding RNAs (lncRNAs) in human coronary artery smooth muscle cells either exposed to oxidized low-density lipoprotein treatment or not, and the characteristics of the expression profiles were explored using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. The predictive effects of seven selected lncRNAs on CAD were evaluated in peripheral blood mononuclear cells (PBMCs). The differentially m6A-modified and expressed lncRNAs related genes were predominantly enriched in small GTPase-mediated signal transduction, ErbB signaling, and Rap1 signaling. Additionally, the expression levels of uc003pes.1, ENST00000422847, and NR_110155 were significantly associated with CAD, with uc003pes.1 identified as an independent risk factor and NR_110155 as an independent protective factor for CAD. NR_110155 and uc003pes.1 in PBMCs have the potential to serve as biomarkers for predicting CAD.

Biohybrid Nanorobots Carrying Glycoengineered Extracellular Vesicles Promote Diabetic Wound Repair through Dual-Enhanced Cell and Tissue Penetration.

Considerable progress has been made in the development of drug delivery systems for diabetic wounds. However, underlying drawbacks, such as low delivery efficiency and poor tissue permeability, have rarely been addressed. In this study, a multifunctional biohybrid nanorobot platform comprising an artificial unit and several biological components is constructed. The artificial unit is a magnetically driven nanorobot surface modified with antibacterial 2-hydroxypropyltrimethyl ammonium chloride chitosan, which enables the entire platform to move and has excellent tissue penetration capacity. The biological components are two-step engineered extracellular vesicles that are first loaded with mangiferin, a natural polyphenolic compound with antioxidant properties, and then glycoengineered on the surface to enhance cellular uptake efficiency. As expected, the platform is more easily absorbed by endothelial cells and fibroblasts and exhibits outstanding dermal penetration performance and antioxidant properties. Encouraging results are also observed in infected diabetic wound models, showing improved wound re-epithelialization, collagen deposition, angiogenesis, and accelerated wound healing. Collectively, a biohybrid nanorobot platform that possesses the functionalities of both artificial units and biological components serves as an efficient delivery system to promote diabetic wound repair through dual-enhanced cell and tissue penetration and multistep interventions.

Knockdown of S100A2 inhibits the aggressiveness of endometrial cancer by activating STING pathway.

BACKGROUND: Endometrial cancer is a kind of gynaecological cancer. S100A2 is a newfound biomarker to diagnose endometrial cancer. This study was to investigate the role of S100A2 on regulating migration and invasion of endometrial cancer. METHODS: The mRNA and protein levels of S100A2 were obtained by quantitative real-time polymerase chain reaction, immunohistochemistry and western blot methods. Cell viability was measured by the Cell Counting Kit-8 assay. Cell migration and invasion were quantified using transwell assays. Western blot assay was conducted to quantify protein expressions of epithelial to mesenchymal transition-related proteins (N-cadherin and E-cadherin). Furthermore, in vivo tumour formation experiments were performed to evaluate the role of S100A2 on tumour xenografts. RESULTS: S100A2 was significantly up-regulated in endometrial cancer tissues. Knockdown of S100A2 inhibited cell viability, migration and invasion of endometrial cancer cells. Meanwhile, STING pathway was activated by the inhibited S100A2. STING inhibitor C-176 significantly reversed the effects of S100A2 knockdown on aggressive behaviours of endometrial cancer cells. Inhibition of S100A2 dramatically suppresses the tumour growth in vivo. CONCLUSIONS: S100A2 functions as an oncogene in endometrial cancer. Targeting S100A2 may be a promising therapeutic method to treat endometrial carcinoma.

This study was to investigate the role of S100A2 on regulating migration and invasion of endometrial cancer. S100A2 was significantly up-regulated in endometrial cancer tissues. Knockdown of S100A2 inhibited cell viability, migration and invasion of endometrial cancer cells. Meanwhile, STING pathway was activated by the inhibited S100A2. STING inhibitor C-176 significantly reversed the effects of S100A2 knockdown on aggressive behaviours of endometrial cancer cells. Inhibition of S100A2 dramatically suppresses the tumour growth in vivo. S100A2 functions as an oncogene in endometrial cancer. Targeting S100A2 may be a promising therapeutic method to treat endometrial carcinoma.

Iodine/soluble starch cryogel: An iodine-based antiseptic with instant water-solubility, improved stability, and potent bactericidal activity.

Iodine (I2) as a broad-spectrum antiseptic has been widely used for treating bacterial infections. However, I2 has low water-solubility and sublimes under ambient conditions, which limits its practical antibacterial applications. The highly specific and sensitive reaction between I2 and starch discovered 200 years ago has been extensively applied in analytical chemistry, but the antibacterial activity of the I2-starch complex is rarely investigated. Herein, we develop a novel type of iodine-based antiseptics, iodine-soluble starch (I2-SS) cryogel, which can dissolve in water instantly and almost completely kill bacteria in 10 min at 2 µg/mL of I2. Although KI3 and the commercially available povidone­iodine (I2-PVP) solutions show similar antibacterial efficacy, the high affinity of I2 to SS largely enhances the shelf stability of the I2-SS solution with ∼73 % I2 left after one-week storage at room temperature. In sharp contrast, ∼8.5 % and âˆ¼2.5 % I2 are detected in KI3 and I2-PVP solutions, respectively. Mechanistic study reveals that the potent antibacterial effect of I2-SS originates from its attack on multiple bacterial targets. The outstanding antibacterial activity, capability of accelerating wound healing, and good biocompatibility of I2-SS are verified through further in vivo experiments. This work may promote the development of next-generation iodine-based antiseptics for clinical use.

Hyperbaric oxygen enhances tumor penetration and accumulation of engineered bacteria for synergistic photothermal immunotherapy.

Bacteria-mediated cancer therapeutic strategies have attracted increasing interest due to their intrinsic tumor tropism. However, bacteria-based drugs face several challenges including the large size of bacteria and dense extracellular matrix, limiting their intratumoral delivery efficiency. In this study, we find that hyperbaric oxygen (HBO), a noninvasive therapeutic method, can effectively deplete the dense extracellular matrix and thus enhance the bacterial accumulation within tumors. Inspired by this finding, we modify Escherichia coli Nissle 1917 (EcN) with cypate molecules to yield EcN-cypate for photothermal therapy, which can subsequently induce immunogenic cell death (ICD). Importantly, HBO treatment significantly increases the intratumoral accumulation of EcN-cypate and facilitates the intratumoral infiltration of immune cells to realize desirable tumor eradication through photothermal therapy and ICD-induced immunotherapy. Our work provides a facile and noninvasive strategy to enhance the intratumoral delivery efficiency of natural/engineered bacteria, and may promote the clinical translation of bacteria-mediated synergistic cancer therapy.

Effective analysis of job satisfaction among medical staff in Chinese public hospitals: a random forest model.

Objective: This study explored the factors and influence degree of job satisfaction among medical staff in Chinese public hospitals by constructing the optimal discriminant model. Methods: The participant sample is based on the service volume of 12,405 officially appointed medical staff from different departments of 16 public hospitals for three consecutive years from 2017 to 2019. All medical staff (doctors, nurses, administrative personnel) invited to participate in the survey for the current year will no longer repeat their participation. The importance of all associated factors and the optimal evaluation model has been calculated. Results: The overall job satisfaction of medical staff is 25.62%. The most important factors affecting medical staff satisfaction are: Value staff opinions (Q10), Get recognition for your work (Q11), Democracy (Q9), and Performance Evaluation Satisfaction (Q5). The random forest model is the best evaluation model for medical staff satisfaction, and its prediction accuracy is higher than other similar models. Conclusion: The improvement of medical staff job satisfaction is significantly related to the improvement of democracy, recognition of work, and increased employee performance. It has shown that improving these five key variables can maximize the job satisfaction and motivation of medical staff. The random forest model can maximize the accuracy and effectiveness of similar research.