Interpersonal Violence-Related Trauma Among South African Children.

INTRODUCTION: Injuries account for a major portion of disability-adjusted life years in children globally, and low-and middle-income countries are disproportionally affected. While injuries due to motor vehicle collisions and self-harm have been well-characterized in pediatric populations in South Africa, injuries related to interpersonal violence (IPV) are less understood. Our study aims to characterize patterns of injury, management, and outcomes for pediatric patients presenting with IPV-related injuries in a South African trauma center. METHODS: We performed a retrospective review of trauma patients ≤18 y of age presenting to the Pietermaritzburg Metropolitan Trauma Service in Gray's Hospital in South Africa from 2012 to 2022, comparing those with injuries resulting from IPV to those with non-IPV injuries. Patients' and injury pattern characteristics and outcomes were descriptively analyzed. RESULTS: Out of 2155 trauma admissions, 500 (23.2%) had IPV-related injuries. Among patients with IPV-related injuries, the median age was 16.0 y. 407 (81.4%) patients were male. 271 (54.2%) patients experienced blunt trauma, 221 (44.2%) had penetrating trauma, and 3 (0.6%) suffered both. The most common weapons were knives (21.6%), stones (11.2%), and firearms (11.0%). The most commonly injured regions were the head (56.4%), abdomen (20.8%), and thorax (19.2%). 19.6% underwent surgical intervention, and 14.4% were referred out for subspecialty care. 1.4% patients died, and 1.2% returned to Pietermaritzburg Metropolitan Trauma Service within 30 d of discharge. CONCLUSIONS: IPV patients are a distinctive subgroup of pediatric trauma patients with different demographics, patterns of injury, and clinical needs. Further research is needed to better understand the unique needs of this neglected population.

Constructing a signature based on the SIRT family to help the prognosis and treatment sensitivity in glioma patients.

Enzymes of the silent information regulator (SIRT) family exert crucial roles in basic cellular physiological processes including apoptosis, metabolism, ageing, and cell cycle progression. They critically contribute to promoting or inhibiting cancers such as glioma. In the present study, a new gene signature of this family was identified for use in risk assessment and stratification of glioma patients. To this end, the transcriptome and relevant clinical records of patients diagnosed with glioma were obtained from the Cancer Genomic Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). LASSO regression and multivariate Cox analyses were used to establish the signature. Using Kaplan-Meier analyses, overall survival (OS) was assessed and compared between a training and an external test datasets which showed lower OS in patients with high risk of glioma compared to those with low risk. Further, ROC curve analyses indicated that the SIRT-based signature had the desired accuracy and universality for evaluating the prognosis of glioma patients. Using univariate and multivariate Cox regression analyses, the SIRT-based signature was confirmed as an independent prognostic factor applicable to subjects in the TCGA and CGGA databases. We also developed an OS nomogram including gender, age, risk score, pathological grade, and IDH status for clinical decision-making purposes. ssGSEA analysis showed a higher score for various immune subgroups (e.g., CD8+ T cells, DC, and TIL) in samples from high-risk patients, compared to those of low-risk ones. qPCR and western blotting confirmed the dysregulated expression of SIRTs in gliomas. Taken together, we developed a new signature on the basis of five SIRT family genes, which can help accurately predict OS of glioma patients. In addition, the findings of the present study suggest that this characteristic is associated with differences in immune status and infiltration levels of various immune cells in the tumor microenvironment.

Insights into the day-night sources and optical properties of coastal organic aerosols in southern China.

Organic aerosols (OAs) in particulate matter with an aerodynamic diameter of smaller than 2.5 µm (PM2.5) can affect the atmospheric radiation balance through varying molecular structure and light absorption of the aerosols. In this study, daytime and nighttime PM2.5 mass, and contents of OA including nitrated aromatic compounds (NACs), polycyclic aromatic hydrocarbons (PAHs), n-alkanes, and hopanes were measured from April 11th to May 15th, 2017, at the coastal Sanya, China. The average concentration of 18 total quantified PAHs (∑PAHs) was 2.08 ± 1.13 ng·m-3, which was 2.8 and 12 times higher than that of ∑NACs and hopanes, while was 7.5 times lower that of n-alkanes. Combustion-derived PAHs contributed 74% to the ∑PAHs. This finding, in addition to a high benzo[a]pyrene/(benzo[a]pyrene+benzo[e]pyrene) ratio, indicates that the PAHs mainly derived from fresh fuel combustion during the sampling periods. Furthermore, dramatic day-night differences were observed in the loadings of total NACs, PAHs, and n-alkanes, which had a high coefficient of divergence values of 0.67, 0.47, and 0.32, respectively. Moreover, hopanes exhibited similar variation as well. The proportion of dimethyl-nitrophenol (DM-NP), dinitrophenol (DNP), and nitrosalicylic acid (NSA) in PM2.5 were higher in the daytime than at nighttime, suggesting the co-influence of primary emissions and secondary formation related to biomass combustion. The positive matrix factorization (PMF) model revealed that motor vehicle and biomass burning emissions were the two main pollution sources in the daytime, contributing 51.7% and 24.6%, respectively, of the total quantified OAs. The proportion of industrial coal combustion emissions was higher at nighttime (20.6%) than in daytime (10%). Both the PAHs and NACs displayed light absorbing capacities among OAs compounds over Sanya City, and thus their influence on solar radiation must be considered in the future control policies.

Chemical characterization of PM2.5 from a southern coastal city of China: applications of modeling and chemical tracers in demonstration of regional transport.

An intensive sampling campaign of airborne fine particles (PM2.5) was conducted at Sanya, a coastal city in Southern China, from January to February 2012. Chemical analyses and mass reconstruction were used identify potential pollution sources and investigate atmospheric reaction mechanisms. A thermodynamic model indicated that low ammonia and high relative humidity caused the aerosols be acidic and that drove heterogeneous reactions which led to the formation of secondary inorganic aerosol. Relationships among neutralization ratios, free acidity, and air-mass trajectories suggest that the atmosphere at Sanya was impacted by both local and regional emissions. Three major transport pathways were identified, and flow from the northeast (from South China) typically brought the most polluted air to Sanya. A case study confirmed strong impact from South China (e.g., Pearl River Delta region) (contributed 76.8% to EC, and then this result can be extended to primary pollutants) when the northeast winds were dominant. The Weather Research Forecasting Black carbon model and trace organic markers were used to apportion local pollution versus regional contributions. Results of the study offer new insights into the atmospheric conditions and air pollution at this coastal city.

Characteristics and major sources of carbonaceous aerosols in PM2.5 from Sanya, China.

PM2.5 samples were collected in Sanya, China in summer and winter in 2012/2013. Organic carbon (OC), elemental carbon (EC), and non-polar organic compounds including n-alkanes (n-C14-n-C40) and polycyclic aromatic hydrocarbons (PAHs) were quantified. The concentrations of these carbonaceous matters were generally higher in winter than summer. The estimated secondary organic carbon (OCsec) accounted for 38% and 54% of the total organic carbon (TOC) in winter and summer, respectively. The higher value of OCsec in addition to the presences of photochemically-produced PAHs in summer supports that photochemical conversions of organics are much active at the higher air temperatures and with stronger intense solar radiation. Carbon preference index (CPI) and percent contribution of wax n-alkanes suggest that anthropogenic sources were more dominant than derivation from terrestrial plants in Sanya. Diagnostic ratios of atmospheric PAHs further indicate that there was a wide mix of pollution sources in winter while fossil fuel combustion was the most dominant in summer. Positive Matrix Factorization (PMF) analysis with 18 PAHs in the winter samples found that motor vehicle emissions and biomass burning were the two main pollution sources, contributing 37.5% and 24.6% of the total quantified PAHs, respectively.