Influencing factors of residents' environmental health literacy in Shaanxi province, China: a cross-sectional study.

BACKGROUND: This study comprehensively analyzed the basic conditions and influencing factors of the residents' environmental health literacy (EHL) level in Shaanxi Province, China in 2020, and provided a scientific basis for exploring new ideas and new methods to improve the EHL level of the whole people. METHODS: In the cross-sectional study with a multi-stage random sampling method, 1320 participants were recruited in 6 neighborhood committees (administrative villages) from the Shaanxi province of China between 15-69 years old. The Core Questions for Assessment of EHL of Chinese Citizens (Trial Implementation) was adopted to measure the EHL of the respondents. RESULTS: The survey showed the level of EHL of residents is 17.6% in Shaanxi in 2020. Among them, the basic concepts, basic knowledge, and basic skills classification literacy levels are 34.7%, 6.89%, and 37.95% respectively. The EHL ratio of rural residents is significantly lower than that of urban residents (12.38 vs. 29.02%). A noticeable difference was shown in various aspects and environmental health issues of EHL between urban and rural populations. CONCLUSIONS: Many factors are affecting the level of EHL. Education and science popularization of basic environmental and health knowledge in key areas and populations should be strengthened, and behavioral interventions should be carried out according to the characteristics of the population.

Pyroptosis-related gene signature: A predictor for overall survival, immunotherapy response, and chemosensitivity in patients with pancreatic adenocarcinoma.

Background: Pancreatic adenocarcinoma (PAAD) is a lethal malignancy with high levels of heterogeneity. Pyroptosis is thought to influence the development of various tumors. Nevertheless, the role of pyroptosis-related genes (PRGs) in prognostic risk stratification and therapeutic guidance for PAAD remains ambiguously. Methods: Transcriptome profile and clinical information of PAAD patients were retrieved from The Cancer Genome Atlas (TCGA) as well as Gene Expression Omnibus (GEO) databases, followed by differential analysis. Patients were divided into distinct pyroptosis phenotype subtypes based on the characteristic of differently expressed PRGs (DEPRGs). Then a PRG signature was established through univariate analysis and LASSO algorithm in the training set to assess the prognostic risk, and its reliability was verified in the validation set using receiver operating characteristic(ROC) curve. The correlation of risk score with tumor microenvironment(TME), TMB and chemotherapeutic drug sensitivity were also analyzed. In addition, a nomogram was constructed to promote better clinical application. Results: A total of 28 DEPRGs were determined in the integrated TCGA-GEO datasets. Patients were divided into three pyroptosis phenotype subtypes, Kaplan-Meier curve suggested patients in cluster B had a worse prognosis than those in cluster A and C. Then a price signature comprised of 8 PRGs was generated. TME analysis suggested that the low-risk subgroup displayed potential stronger antitumor immune effect and might respond better to immune checkpoint inhibitors (ICIs) therapy. Furthermore, PRG signature exhibited favorable discriminatory ability for TMB status and the sensitivity of multiple conventional chemotherapeutic agents including paclitaxel. Ultimately, we constructed a promising nomogram according to the risk score and N stage with good predictive accuracy compared with the actual overall survival (OS) probabilities. Conclusion: We established an 8-gene signature that could be regarded as an independent prognostic risk factor for PAAD patients. The 8-gene signature could provide rationale for immunotherapy and chemotherapy, which might help clinicians make precise individualized treatment regimens.

The Real-World Clinical Impact of Plasma mNGS Testing: an Observational Study.

Plasma metagenomic next-generation sequencing (mNGS) testing is a promising diagnostic modality for infectious diseases, but its real-world clinical impact is poorly understood. We reviewed patients who had undergone plasma mNGS at a general hospital to evaluate the clinical utility of plasma mNGS testing. A total of 76.9% (113/147) of plasma mNGS tests had a positive result. A total of 196 microorganisms (58) were identified and reported, of which 75.6% (148/196) were clinically relevant. The median stringent mapped read number (SMRN) of clinically relevant organisms was 88 versus 22 for irrelevant organisms (P = 0.04). Based on the clinically adjudicated diagnosis, the positive and negative percent agreements of plasma mNGS testing for identifying a clinically defined infection were 95.2% and 67.4%, respectively. The plasma mNGS results led to a positive impact in 83 (57.1%) patients by diagnosing or ruling out infection and initiating targeted therapy. However, only 32.4% (11/34) of negative mNGS tests showed a positive impact, suggesting that plasma mNGS testing alone may not be a powerful tool to rule out infection in clinical practice. In the subset of 37 patients positive for both plasma mNGS and conventional testing, mNGS identified the pathogen(s) 2 days (IQR = 0.75 to 4.25) earlier than conventional testing. mNGS enables pathogen identification within 24 h, but given that the detection of clinically irrelevant organisms and nearly half of the tests result in no or a negative clinical impact, more clinical practice and studies are required to better understand who and when to test and how to optimally integrate mNGS into the infectious disease diagnostic workup. IMPORTANCE In this study, we show that although plasma mNGS testing significantly improved the detection rate of tested samples, nearly one in four (24.5%, 48/196) mNGS tests reported organisms were not clinically relevant, emphasizing the importance of cautious interpretation and infectious disease consultation. Moreover, based on clinical adjudication, plasma mNGS testing resulted in no or a negative impact in nearly half (43.5%, 64/147) of patients in the current study, indicating that how best to integrate this advanced method into current infectious disease diagnostic frameworks to maximize its clinical utility in real-world practice is an important question. Therefore, recommending plasma mNGS testing as a routine supplement to first-line diagnostic tests for infectious diseases faces great challenges. The decision to conduct mNGS testing should take into account the diagnostic performance, turnaround time and cost-effectiveness of mNGS, as well as the availability of conventional tests.

Secondary Infection Surveillance with Metagenomic Next-Generation Sequencing in COVID-19 Patients: A Cross-Sectional Study.

Background: Metagenomic next-generation sequencing (mNGS) is a promising tool for improving antimicrobial therapy and infection control decision-making in complex infections. Secondary infection surveillance using mNGS in COVID-19 patients has rarely been reported. Methods: Respiratory pathogen and antibiotic resistance prediction were evaluated by BALF mNGS for 192 hospitalized COVID-19 patients between December 2022 and February 2023. Results: Secondary infection was confirmed in 83.3% (160/192) of the COVID-19 patients, with bacterial infections (45%, 72/160) predominating, followed by mixed bacterial and fungal infections (20%, 32/160), and fungal infections (17.5%, 28/160). The incidence of bacterial or viral secondary infection was significantly higher in patients who were admitted to the ICU, received mechanical ventilation, or developed severe pneumonia (all p<0.05). Klebsiella pneumoniae (n=30, 8.4%) was the most prevalent pathogen associated with secondary infection followed by Acinetobacter baumannii (n=29, 8.1%), Candida albicans (n=29, 8.1%), Aspergillus fumigatus (n=27, 7.6%), human herpes simplex virus type 1 (n=23, 6.4%), Staphylococcus aureus (n=20, 5.6%) and Pneumocystis jiroveci (n=14, 3.9%). The overall concordance between the resistance genes detected by mNGS and the reported phenotypic resistance in 69 samples containing five clinically important pathogens (ie, K. pneumoniae, A. baumannii, S. aureus, P. aeruginosa and E. coli) that caused secondary infection was 85.5% (59/69). Conclusion: mNGS can detect pathogens causing secondary infection and predict antimicrobial resistance for COVID19 patients. This is crucial for initiating targeted treatment and rapidly detect unsuspected spread of multidrug-resistant pathogens.

Alterations of IL-1beta and TNF-alpha expression in RAW264.7 cell damage induced by two samples of PM2.5 with different compositions.

Fine particulate matter 2.5 (PM2.5) has been demonstrated by previous studies to be associated with cell damage. To explore the impact of the composition of PM2.5 on PM2.5-mediated inflammation, this study investigated the composition of PM2.5 collected during the wintertime indoor heating season and observed its inflammatory effect. Samples were collected during the heating season from December 5, 2017, to January 8, 2018, in Xi'an. Compositions of organic carbon (OC), elemental carbon (EC), and water-soluble ions were analysed. Two representative samples (sample 1 and 2) were selected with significant differences in compositions. They were configured into four concentrations (0.1 µg/mL, 1 µg/mL, 10 µg/mL, 20 µg/mL) and used as interventions on RAW264.7 cells for 4 h and 24 h separately. Cell viability was detected by CCK-8. Tumour necrosis factor-α (TNF-α) and interleukin-1ß (IL-1ß) gene and protein expression levels were detected by real-time quantitative real-time polymerase chain reaction (RT-qPCR) and western blotting. The results showed that the cell viability of sample 1 intervened cells at 4 h and 24 h was lower than that of sample 2. IL-1ß gene in most PM2.5 intervention groups was lower than in the control group. Protein expression was higher at 4 h than at 24 h. In conclusion, PM2.5 components influence cell viability and expression of IL-1ß and TNF-α, while high concentrations of NO3-, Cl-, Na+, K+, Mg2+, Ca2+, and others in the PM2.5 composition have a significant harmful effect.

Study on GIS Visualization in Evaluation of the Human Living Environment in Shenyang-Dalian Urban Agglomeration.

Analysis of human living environmental quality of Shenyang-Dalian urban agglomerations has important theoretical and practical significance in rapid development region. A lot of investigations have been carried for Shenyang-Dalian urban agglomerations, including 38 counties. Based on the carrying capacity of resources, natural and socioeconomic environmental factors and regional changes of human living environmental evaluation are analyzed with the application of geographic information systems (GIS) software. By using principal component analysis (PCA) model and natural breaks classification (NBC) method, the evaluation results are divided into five categories. The results show that the human living environmental evaluation (HLEE) indexes of Dalian, Shenyang, and Liaoyang are higher than other counties. Among these counties, the human living environmental evaluation (HLEE) indexes of coastal counties are significantly higher than inland counties. The range of the human living environmental evaluation index in most of the study area is at III, IV, and V levels, accounting for 80.01%. Based on these results, it could illustrate the human living environment is in relatively suitable condition in Shenyang-Dalian urban agglomeration.

Identifying risk factors of avian infectious diseases at household level in Poyang Lake region, China.

Poultry kept in backyard farms are susceptible to acquiring and spreading infectious diseases because of free ranging and poor biosecurity measures. Since some of these diseases are zoonoses, this is also a significant health concern to breeders and their families. Backyard farms are common in rural regions of China. However, there is lack of knowledge of backyard poultry in the country. To obtain first-hand information of backyard poultry and identify risk factors of avian infectious diseases, a cross-sectional study was carried out at household level in rural regions around Poyang Lake. A door-to-door survey was conducted to collect data on husbandry practices, trading practices of backyard farmers, and surrounding environments of backyard farms. Farms were categorized into cases and controls based on their history of poultry death. Data were collected for 137 farms, and the association with occurrence of poultry death event was explored by chi-square tests. Results showed that vaccination implementation was a protective factor (odds ratio OR=0.40, 95% confidence interval CI: 0.20-0.80, p=0.01), while contact with other backyard flocks increased risk (OR=1.72, 95% CI: 0.79-3.74, p=0.16). A concept of "farm connectivity" characterized by the density of particular land-use types in the vicinity of the farm was proposed to characterize the degree of contact between poultry in one household farm and those in other household farms. It was found that housing density in a 20-m buffer zone of the farmhouse was most significantly associated with poultry death occurrence (OR=1.08, 95% CI: 1.02-1.17, p=0.03), and was in agreement with observation of villagers. Binary logistic regression was applied to evaluate the relationship between poultry death event and density of land-use types in all buffer zones. When integrated with vaccination implementation for poultry, prediction accuracy of poultry death event reached 72.0%. Results combining questionnaire survey with geographical approaches indicated that occurrence of poultry death event among backyard farms within a village was heavily impacted by farm connectivity. This study provides new insight for the study and help to develop more targeted prevention and countermeasure in a typical rural environment of China.