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Objective: The objective of the study is to identify and comprehend the challenges experienced by the undergraduate medical and dental students in enrolled in public sector in Pakistan while conducting research. Methodology: A cross-sectional study was carried out from April to June of 2023 among undergraduate students at public sector medical and dental schools in Khyber Pakhtunkhwa, Pakistan. A customized questionnaire was developed to gather information on the challenges faced by students when undertaking research. The survey was circulated online using Google Forms, and participation was entirely optional. Descriptive statistics were used to analyse the responses. Results: Participants in the study were 58 male and 139 female students who were enrolled in the Bachelor of Medicine & Bachelor of Surgery (MBBS) and Bachelor of Dental Surgery (BDS) programs. The analysis found that 47% of students cited a lack of knowledge and research skills as a major barrier, while 40% cited time restrictions as a major issue. Mentorship and training issues were cited as major barriers by 51% of students, while a lack of institutional support was cited as a significant issue by 53% of students. Language issues made it difficult to produce research papers for 14% of students, while finding research opportunities was challenging for 38% of students. Conclusion: According to the research, undergraduate medical and dentistry students in the public sector encountered a number of challenges when conducting research. It was suggested that these issues be resolved by include research projects in the curriculum, providing specific interventions for enhancing research skills, establishing mentorship programs, and allocating funds for research activities. [ABSTRACT FROM AUTHOR]

For the tertiary health care system to provide adequate care during disasters, willing and able healthcare providers must be available to respond to the abnormal surge of the patients. Health care professionals (HCPs) constantly face a dilemma because of their profession to either respond to disasters or protect themselves. This study was conducted to assess the willingness and ability of HCPs working in the tertiary healthcare system of Khyber Pakhtunkhwa to respond to disasters. This cross-sectional survey was conducted in all the 8 tertiary care hospitals of the Khyber Pakhtunkhwa province of Pakistan. For different disaster scenarios, between 6% and 47% of HCP indicated their unwillingness, and between 3% & 41% of HCPs indicated that they were unable to respond to the given disaster scenarios. HCPs with childcare obligation indicated significantly lower willingness (p<0.05) to respond to earthquakes, MCIs, and an outbreak of Influenza, and SARS. Male HCPs showed a significantly (p<0.05) higher willingness to respond to earthquakes, MCIs, and an outbreak of Influenza as compared to their female counterparts. The overall ability indicated by HCPs for various disaster scenarios ranged between 54.1% [95% CI 0.503,0.578] for responding to victims of nuclear war and 96.4% [95% CI 0.947,0.976] for responding to conventional war. The HCPs who indicated childcare obligation showed a significantly lower ability (p<0.05) to respond to environmental disaster, influenza outbreak, and responding to victims of nuclear war. Female HCPs indicated significantly higher ability (p<0.05) as compared to their male counterparts. This survey provides an opportunity for the tertiary healthcare system to build on the findings and develop disaster mitigation plans to address the barriers to improving the HCPs' availability during disasters. [ABSTRACT FROM AUTHOR]

Introduction: Chronic kidney disease (CKD) is a significant public health challenge due to its rising incidence, mortality, and morbidity. Patients with kidney diseases often suffer from various comorbid conditions, making them susceptible to potential drug-drug interactions (pDDIs) due to polypharmacy and multiple prescribers. Inappropriate prescriptions for CKD patients and their consequences in the form of pDDIs are a major challenge in Pakistan. Aim: This study aimed to compare the incidence and associated risk factors of pDDIs among a public and private sector hospital in Khyber Pakhtunkhwa, Pakistan. Method: A retrospective cross-sectional study design was conducted to compare pDDIs among public and private sector hospitals from January 2023 to February 2023. Patients profile data for the full year starting from January 1 2022 to December 302022, was accessed All adult patients aged 18 years and above, of both genders, who currently have or have previously been diagnosed with end-stage renal disease (ESRD) were included. For assessing pDDIs, patient data was retrieved and checked using Lexicomp UpToDate® for severity and documentation of potential drug-drug interactions. Results: A total of 358 patients' data was retrieved (with n = 179 in each hospital); however, due to incomplete data, n = 4 patients were excluded from the final analysis. The prevalence of pDDIs was found to be significantly higher in private hospitals (84.7%) than in public hospitals (26.6%), with a p-value <0.001. Patients in the age category of 41–60 years (AOR = 6.2; p = 0.008) and those prescribed a higher number of drugs (AOR = 1.2; p = 0.027) were independently associated with pDDIs in private hospitals, while the higher number of prescribed drugs (AOR = 2.9; p = <0.001) was an independent risk factor for pDDIs in public hospitals. The majority of pDDIs (79.0%) were of moderate severity, and a significant number of patients (15.1%) also experienced major pDDIs, with a p-value <0.001. The majority of pDDIs had fair documentation for reliability rating in both public and private hospitals. Conclusion: The prevalence of pDDIs was higher among CKD patients at private hospitals, and most of the pDDIs were of moderate severity. A considerable number of patients also experienced major pDDIs. The risk of experiencing pDDIs was found to be higher in older patients and among those prescribed a higher number of drugs. [ABSTRACT FROM AUTHOR]

In view of the challenges faced by organizations and departments concerned with agricultural capacity observations, we collected In-Situ data consisting of diverse crops (More than 11 consumable vegetation types) in our pilot region of Harichand Charsadda, Khyber Pakhtunkhwa (KP), Pakistan. Our proposed Long Short-Term Memory based Deep Neural network model was trained for land cover land use statistics generation using the acquired ground truth data, for a synergy between Planet-Scope Dove and European Space Agency's Sentinel-2. Total of 4 bands from both sentinel-2 and planet scope including Red, Green, Near-Infrared (NIR) and Normalised Difference Vegetation Index (NDVI) were used for classification purpose. Using short temporal frame of Sentinel-2 comprising 5 date images, we propose an realistic and implementable procedure for generating accurate crop statistics using remote sensing. Our self collected data-set consists of a total number of 107,899 pixels which was further split into 70% and 30% for training and testing purpose of the model respectively. The collected data is in the shape of field parcels, which has been further split for training, validation and test sets, to avoid spatial auto-correlation. To ensure the quality and accuracy 15% of the training data was left out for validation purpose, and 15% for testing. Prediction was also performed on our trained model and visual analysis of the area from the image showed significant results. Further more a comparison between Sentinel-2 time series is performed separately from the fused Planet-Scope and Sentinel-2 time-series data sets. The results achieved shows a weighted average of 93% for Sentinel-2 time series and 97% for fused Planet-Scope and Sentinel-2 time series. [ABSTRACT FROM AUTHOR]

Background: Hepatitis B Virus (HBV) is one of the most common human infectious agents, and the mutations in its genome may cause chronic hepatitis (CH), liver cirrhosis (LC), and hepatocellular carcinoma (HCC). This study was designed to characterize the enhancer-II (Enh-II) region of X gene in HBV positive patients to assess the association of such mutations with CH, LC, and HCC. Methods: HBV positive samples (N = 200) with patients' demographic and clinical data were collected from different regions of Khyber Pakhtunkhwa (KP), Pakistan. The Enh-II region of the HBx gene was sequenced and zanalyzed for polymorphism associated with advanced liver disease. Univariate and logistic regression analyses were performed to evaluate potent mutations associated with a risk for LC and HCC. Results: HBV Enh-II region sequences analysis revealed 25 different mutations. The highest frequency of mutations S101F (62.2%), A102V/R/G/I (56.25%), M103L/A (68.75%)were found in HCC, followed in LC and CH patients as 57.1%, 42.8%, 28.52% 16%, 15.2% and 18.4% respectively. H94 deletion in the α-box of the Enh-II region, associated with a high risk of HCC was found in half of the HCC patients. This deletion was present in 28.5% of LC and 6.5% of CH patients. Importantly, the high frequency of some notable mutations such as E109A/Y, A110S/K, Y111D/E, and F112L was first time reported in the entire study population. The frequencies of these mutations were high in HCC (43.75%, 37.5%, 50% and 43.75% respectively) as compared to LC (14.28%, 14.28%, 28.2% and 42.8%) and CH patients (12.8%, 15.2%, 16.8% and 16% respectively). Conclusion: Mutations associated with LC and HCC are prevalent in the Enh-II region in Pakistani HBV isolates. The mutations found are alarming in CH patients as these may progress to LC and HCC in a large number of patients. [ABSTRACT FROM AUTHOR]

Background: In tropical and subtropical countries, tick infestation causes major public health problems and considerable financial losses to the livestock industry. This study was aimed to assess the species composition of richness and analyze the phylogeny of Rhipicephalus microplus in the District Bannu of Khyber Pakhtunkhwa, Pakistan. Methods: Collected ticks were identified morphologically and DNA extracted from R. microplus was amplified and subjected to sequencing. Results: A total of 3,600 animals were examined among them 1,494 animals were found to be infested with ticks, including 669 cows, 476 buffaloes, 163 goats, and 186 sheep (p = 0.001). Tick infestation was significantly high (43.58%) in animals of age group (<1 year) (p-value = 0.027). Female animals were more (44.05%) infested with ticks than males (34.43%) (p = 0.001). The intensity of infestation was significantly higher in summer (77.49%) (p = 0.001). A total of 5,557 ticks were collected comprising three genera and six species. R. microplus was predominantly prevalent (n = 1,474; 26.52%), followed by Rhipicephalus annulatus (n = 1,215; 21.86%), Hyalomma anatolicum (n = 1,139; 20.49%), Hyalomma marginatum (n = 1,086; 19.54%), and Rhipicephalus turanicus (n = 761; 13.69%), while the least common was Haemaphysalis aciculifer (n = 80; 1.43%) (p = 0.001). Morphologically identified R. microplus species were also analyzed genetically by using two genetic markers 16S ribosomal RNA (16S rRNA) and internal transcribed spacer 2 (ITS2) genes. The phylogenetic study revealed that R. microplus is genetically diversified and clustered in clade B with R. microplus species from China, India, and Pakistan. Conclusion: Ticks infestation was significantly correlated with various factors including age, sex, season, and animal type. R. microplus genetically resembled species reported from India and China. However, major knowledge gaps concerning various species of ticks exist and many areas are still unexplored in Pakistan. Therefore, it is necessary to explore the epidemiological and molecular aspects of various tick species in other regions of southern Khyber Pakhtunkhwa. [ABSTRACT FROM AUTHOR]

A comprehensive life cycle assessment (LCA) was conducted for the matchsticks industry in the Khyber Pakhtunkhwa province of Pakistan to quantify environmental footprint, water footprint, cumulative energy use, and to identify improvement opportunities in the matchsticks manufacturing process. One carton of matchsticks was used as reference unit for this study. Foreground data was collected from the matchsticks industry through questionnaire surveys, personal meetings, and field measurements. The collected data was transformed into potential environmental impacts through the Centre for Environment Studies (CML) 2000 v.2.05 method present by default in the SimaPro v.9.1 software. Water footprint was calculated using methodology developed by Hoekstra et al., 2012 (water scarcity index) V1.02 and cumulative energy demand by SimaPro v.9.1 software. The results showed that transport of primary material (wood logs), sawn wood for matchsticks, red phosphorous, acrylic varnish, and kerosene fuel oil contributed to the overall environmental impacts. Transport of primary materials and sawn timber for matchsticks contributed significantly to abiotic depletion, global warming, eutrophication potential, ozone depletion, corrosion, human toxicity, and aquatic ecotoxicity effects. The total water footprint for manufacturing one carton of matchsticks was 0.265332 m3, whereas the total cumulative energy demand was 715.860 Mega Joules (MJ), mainly sourced from non-renewable fossil fuels (708.979 MJ). Scenario analysis was also conducted for 20% and 30% reduction in the primary material distance covered by trucks and revealed that reducing direct material transport distances could diminish environmental impacts and energy consumption. Therefore, environmental footprint could be minimized through diverting matchsticks industries freight from indigenous routes to high mobility highways and by promoting industrial forestry close to industrial zones in Pakistan. Many industries did not have emissions control systems, exceeding the permissible limit for emissions established by the National Environmental Quality Standards (NEQS) of Pakistan. Thus, installation of emissions control system could also diminish emissions from match industry in Pakistan. [ABSTRACT FROM AUTHOR]

This research work aims to develop a deep learning-based crop classification framework for remotely sensed time series data. Tobacco is a major revenue generating crop of Khyber Pakhtunkhwa (KP) province of Pakistan, with over 90% of the country's Tobacco production. In order to analyze the performance of the developed classification framework, a pilot sub-region named Yar Hussain is selected for experimentation work. Yar Hussain is a tehsil of district Swabi, within KP province of Pakistan, having highest contribution to the gross production of the KP Tobacco crop. KP generally consists of a diverse crop land with different varieties of vegetation, having similar phenology which makes crop classification a challenging task. In this study, a temporal convolutional neural network (TempCNNs) model is implemented for crop classification, while considering remotely sensed imagery of the selected pilot region with specific focus on the Tobacco crop. In order to improve the performance of the proposed classification framework, instead of using the prevailing concept of utilizing a single satellite imagery, both Sentinel-2 and Planet-Scope imageries are stacked together to assist in providing more diverse features to the proposed classification framework. Furthermore, instead of using a single date satellite imagery, multiple satellite imageries with respect to the phenological cycle of Tobacco crop are temporally stacked together which resulted in a higher temporal resolution of the employed satellite imagery. The developed framework is trained using the ground truth data. The final output is obtained as an outcome of the SoftMax function of the developed model in the form of probabilistic values, for the classification of the selected classes. The proposed deep learning-based crop classification framework, while utilizing multi-satellite temporally stacked imagery resulted in an overall classification accuracy of 98.15%. Furthermore, as the developed classification framework evolved with specific focus on Tobacco crop, it resulted in best Tobacco crop classification accuracy of 99%. [ABSTRACT FROM AUTHOR]