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Channa is a critical genus with a large number of species and it has a key importance in aquaculture. Channa marulius (snakehead) is a commercially important food fish of Pakistan. The status of C. marulius is indigenous and acquired near threatened according to the survey of the IUCN. Therefore, in the present study, 15 fish specimens were collected from five rivers (Indus, Chenab, Ravi, Satluj, and Jhelum) of Punjab, Pakistan, and successfully amplified and barcode the short mitochondrial COI gene sequences of 599 base pairs and analyzed by using BLAST. Pairwise genetic distance evaluated the K2P (Kimura 2-parameter) model, and phylogenetic analysis was inferred by constructing the ML (maximum likelihood) tree based on the Tamura-Nei model by using MEGA-X software. BLAST analysis provided a 100% identity match with reference sequences of the GenBank database and confirmed the species as C. marulius. The pairwise K2P distance between species observed (0.0000%) and the maximum distance (0.0067%). The ML tree showed that species lie under the same node because these species have the same genus, and C. marulius species identified from Pakistan have a phylogenetic link with C. marulius species of India. The present study successfully reported the DNA barcode base molecular identification of C. marulius from Pakistan. Moreover, this study proved that mitochondrial COI gene barcoding can be effectively used for the identification of Channa. [ABSTRACT FROM AUTHOR]

In the petroleum reservoir, the secondary oil recovery (SOR) process is employed by injecting water into wells to enhance the moment of oil toward the production wells. The SOR process gives rise to the instability (fingering) phenomena due to the injecting force and the difference in the wettability and viscosity of the oil and water at the common interface. Since the late 1800s, mathematical models of petroleum reservoirs have been extensively used in the oil and gas industry. In this paper, we investigated the saturation of two immiscible fluid (oil and water) flows through homogeneous porous media during the SOR process by solving the modeled partial differential equation using the supervised machine learning algorithm based on feedforward back-propagated neural networks (FFBNNs) and Levenberg–Marquardt (LM) optimization algorithm. The designed scientific computing technique (FFBNN-LMA) is further employed to study the detailed sensitivity analysis of the approximate solutions. Performance measures like average absolute deviations, Theils' inequality measure, regression, and Nash–Sutcliffe model efficiency coefficient. [ABSTRACT FROM AUTHOR]

Pakistan being a tropical country, characterized by poor socioeconomic conditions, is more vulnerable to Mosquito-borne diseases. So, this study was proposed to know the prevalence of mosquito-borne diseases in Faisalabad district, Pakistan. For this, mosquito adults and larvae were collected from different habitats with aspirator and dippers respectively from eight towns of Faisalabad district. These samples were carried alive to laboratory and identified with the help of identification keys. Aedes female mosquitoes were killed and stored at -20°C for RNA extraction. Slides were prepared from blood of female Anopheles mosquitoes for the identification of plasmodium under microscope. The genome RNA from female Aedes mosquitoes were extracted as per commercially available kits according to manufacturer guidelines and stored at -40 0C for further use. Using online software, primers and probes for the known human pathogens were designed in consensus with the help of available genome database for different pathogens such as dengue virus. Plasmodium was detected from the mosquitoes that were mostly collected from rural areas and this was generally detected from the samples collected from Jaranwala and Samundri town. Dengue virus was detected generally from city areas and serotype 2 and 3 was detected from the Aedes mosquitoes. Dengue virus was mostly detected from Lyallpur, Madina and Jinnah towns. Mosquitoes were mostly collected after monsoon season in the months of August-September and in spring (March). The disease pathogens were also detected during these months. Through the surveillance of pathogens, we can focus our attention on the hot spots and apply control measures to control mosquitoes for better management. [ABSTRACT FROM AUTHOR]

This research aimed to study the effects of organophosphate insecticides on biochemical parameters of small farmers who were engaged in the mixing and spraying of pesticides in Punjab, Pakistan. In this context, blood samples of 110 farmers, having similar socio-economic position, in the cotton and mango belt of Rahimyar Khan (RYK), Punjab, Pakistan were collected to detect the levels of the acetyl-cholinesterase, glutathione, and lipid peroxidation in the blood samples of both groups (pesticide exposed and unexposed controls). All of the selected farmers were also interviewed about age, social interests, habits (smoking), genetic diseases, education, marital status, occupation, spraying experience, types of pesticides, use of personal protection equipment, and diseases. The descriptive results of socioeconomic factors were presented in terms of means ± SD, and non-parametric chi-squared test was used to test their association with case-control groups. Student t-test and ANOVA were used to compare the enzymes between and within groups respectively. The mean level for all enzymes was significantly higher in exposed group with p-values <0.001. The impact of all enzymes was different on the farmers in exposed group with p-value <0.001. The farmers were most affected with glutathione. Based on the findings of this study, it is strongly recommended that the rural health workers should visit the farmers regularly to monitor their health conditions. Furthermore, the local governing authorities must send their social mobilizers (SMs) to fields in order to promote the importance of self and environmental protection measures. [ABSTRACT FROM AUTHOR]