The -786 T/C polymorphism of NOS3 gene is a susceptibility marker of COPD among Tunisians that correlates with nitric oxide levels and airflow obstruction.

OBJECTIVE: The goal of this study was to examine the role of G894T (rs1799983), -786T/C (rs3918161) and a 27 bp variable number of tandem repeats (VNTR) 4B/4A of NOS3 gene on the risk and severity of COPD. METHODS: The study included 194 controls and 138 COPD patients. NOS3 G894T, -786T/C and 4B/4A variants were determined by PCR analysis based on the banding pattern on gel electrophoresis. Pulmonary function was evaluated using body plethysmography. The levels of nitric oxide, peroxynitrite and lipid peroxides (T-BARS) were determined using spectrophotometric methods. Levels of serum IL-6, TNF-α and TGFß were determined by ELISA. RESULTS: In case-control studies, both G894T and -786T/C variants were associated with COPD risk. A significantly increased risk of COPD was found with the NOS3894T and -786C alleles (OR:1.93, P=0.001; OR:2.05, P=0.001, respectively). No significant impact of the G894T and 4B/4A SNPs was found on COPD severity, while a significant correlation was retrieved between the NOS3 -786T/C variation and advanced stages (OR: 1.89, P=0.009). In addition, COPD patients with the -786CC genotype exhibited lower FEV1% values in comparison to -786TT carriers (48±3.28 vs. 58.06±2.3, P=0.01, respectively). Patients having the -786CC genotype presented lower plasma levels of nitric oxide and higher T-BARS in comparison to -786TT individuals (173.22±13.4 vs. 228.93±16.8, P=0.01; 1.8±0.15 vs. 1.22±0.15, P=0.01, respectively). CONCLUSION: This study provides the first evidence for the association of G894T, -786T/C variants with COPD risk among Tunisians. The -786T/C variation correlates with enhanced airflow limitation. This finding could be related to altered levels of nitric oxide and enhanced lipid peroxides among patients carrying the -786CC genotype.

Nitrate concentration analysis and prediction in a shallow aquifer in central-eastern Tunisia using artificial neural network and time series modelling.

Agricultural activities have become a major source of groundwater nitrate contamination. In this context, this study aims to analyse nitrate concentrations in a shallow aquifer of Mahdia-Kssour Essef in central-eastern Tunisia, identify the assignable sources, and predict the future levels using artificial neural network (ANN) and autoregressive integrated moving average (ARIMA) models. The results showed that nitrate concentrations measured in 21 pumping wells across the plain ranged from 17 to 521 mg L-1. A total of 67% of the monitoring points greatly exceed the standard guideline value of 50 mg L-1. The main relevant anthropogenic and natural factors, such as soil texture, land use, fertilizers application rates, livestock waste disposal, and groundwater table, are positively correlated with groundwater nitrate concentration. The ANN model showed good fitting between measured and simulated results with coefficient of determination (R2), root-mean-square error (RMSE), and mean absolute error (MAE) values of 0.88, 53.95, and 39.64, respectively. The ARIMA applied on annual average nitrate concentrations from 1998 to 2017 revealed that the best fitted model (p, d, q) is (1, 2, 1). The R2 value is approximately 0.36, and the Theil inequality coefficient and bias proportion values are small and close to zero. These results proved the ARIMA model's adequacy in forecasting annual average nitrate concentrations of 116 mg L-1 in 2025. These findings may be useful in making groundwater management decisions, particularly in rural and semi-arid areas, and the proposed ARIMA model could be used as a managed tool to monitor and reduce the nitrate intrusion into groundwater.

Hospital preparedness and management of pediatric population during COVID-19 outbreak.

With the recent pandemic of Coronavirus disease-2019 (COVID-19), there has been a higher number of reported cases in children more than to the prior Corona Virus-related diseases, namely, severe acute respiratory syndrome and the Middle East respiratory syndrome. The rate of COVID-19 in children is lower than adults; however, due to high transmission rate, the number of reported cases in children has been increasing. With the rising numbers among children, it is imperative to develop preparedness plans for the pediatric population at the hospital level, departmental level, and patient care areas. This paper summarizes important considerations for pediatric hospital preparedness at the hospital level that includes workforce, equipment, supply; capacity planning, and infection prevention strategies, it also span over the management of COVID-19 pediatric patients in high-risk areas such as critical care areas, Emergency Department and operative rooms.