Drinking water quality of various sources in Peshawar, Mardan, Kohat and Swat districts of Khyber Pakhtunkhwa province, Pakistan / Qualidade de água potável de váris fontes dos distritos de Peshawar, Mardan, Kohat e Swat da província de Khyber Pakhtunkhwa, Paquistão

Abstract The present study involves the chemical and bacteriological analysis of water from different sources i.e., bore, wells, bottle, and tap, from Peshawar, Mardan, Swat and Kohat districts of Khyber Pakhtunkhwa (KP) province, Pakistan. From each district, 50 water samples (10 samples from each source), regardless of urban and rural status, were collected from these sources and analysed for sulphates, nitrates, nitrites, chlorides, total soluble solids and coliforms (E. coli). Results indicated that majority of the water sources had unacceptable E. coli count i.e.> 34 CFU/100mL. E. coli positive samples were high in Mardan District, followed by Kohat, Swat and Peshawar district. Besides this, the some water sources were also chemically contaminated by different inorganic fertilizers (nitrates/nitrites of sodium, potassium) but under safe levels whereas agricultural and industrial wastes (chloride and sulphate compounds) were in unsafe range. Among all districts, the water quality was found comparatively more deteriorated in Kohat and Mardan districts than Peshawar and Swat districts. Such chemically and bacteriologically unfit water sources for drinking and can cause human health problems.

Resumo O presente estudo envolve a análise química e bacteriológica de água de diferentes fontes, ou seja, furo, poços, garrafa e torneira, dos distritos de Peshawar, Mardan, Swat e Kohat da província de Khyber Pakhtunkhwa (KP), Paquistão. De cada distrito, 50 amostras de água (10 amostras de cada fonte), independentemente do status urbano e rural, foram coletadas dessas fontes e analisadas para sulfatos, nitratos, nitritos, cloretos, sólidos solúveis totais e coliformes (E. coli). Os resultados indicaram que a maioria das fontes de água tinha uma contagem inaceitável de E. coli, ou seja, > 34 UFC / 100 mL. As amostras positivas para E. coli foram elevadas no distrito de Mardan, seguido por Kohat, Swat e distrito de Peshawar. Além disso, algumas fontes de água também foram contaminadas quimicamente por diferentes fertilizantes inorgânicos (nitratos/nitritos de sódio, potássio), mas em níveis seguros, enquanto os resíduos agrícolas e industriais (compostos de cloreto e sulfato) estavam em níveis inseguros. Entre todos os distritos, a qualidade da água foi considerada comparativamente mais deteriorada nos distritos de Kohat e Mardan do que nos distritos de Peshawar e Swat. Essas fontes de água química e bacteriologicamente impróprias para beber podem causar problemas à saúde humana.

Drinking water quality of various sources in Peshawar, Mardan, Kohat and Swat districts of Khyber Pakhtunkhwa province, Pakistan

Abstract The present study involves the chemical and bacteriological analysis of water from different sources i.e., bore, wells, bottle, and tap, from Peshawar, Mardan, Swat and Kohat districts of Khyber Pakhtunkhwa (KP) province, Pakistan. From each district, 50 water samples (10 samples from each source), regardless of urban and rural status, were collected from these sources and analysed for sulphates, nitrates, nitrites, chlorides, total soluble solids and coliforms (E. coli). Results indicated that majority of the water sources had unacceptable E. coli count i.e.> 34 CFU/100mL. E. coli positive samples were high in Mardan District, followed by Kohat, Swat and Peshawar district. Besides this, the some water sources were also chemically contaminated by different inorganic fertilizers (nitrates/nitrites of sodium, potassium) but under safe levels whereas agricultural and industrial wastes (chloride and sulphate compounds) were in unsafe range. Among all districts, the water quality was found comparatively more deteriorated in Kohat and Mardan districts than Peshawar and Swat districts. Such chemically and bacteriologically unfit water sources for drinking and can cause human health problems.

Resumo O presente estudo envolve a análise química e bacteriológica de água de diferentes fontes, ou seja, furo, poços, garrafa e torneira, dos distritos de Peshawar, Mardan, Swat e Kohat da província de Khyber Pakhtunkhwa (KP), Paquistão. De cada distrito, 50 amostras de água (10 amostras de cada fonte), independentemente do status urbano e rural, foram coletadas dessas fontes e analisadas para sulfatos, nitratos, nitritos, cloretos, sólidos solúveis totais e coliformes (E. coli). Os resultados indicaram que a maioria das fontes de água tinha uma contagem inaceitável de E. coli, ou seja, > 34 UFC / 100 mL. As amostras positivas para E. coli foram elevadas no distrito de Mardan, seguido por Kohat, Swat e distrito de Peshawar. Além disso, algumas fontes de água também foram contaminadas quimicamente por diferentes fertilizantes inorgânicos (nitratos/nitritos de sódio, potássio), mas em níveis seguros, enquanto os resíduos agrícolas e industriais (compostos de cloreto e sulfato) estavam em níveis inseguros. Entre todos os distritos, a qualidade da água foi considerada comparativamente mais deteriorada nos distritos de Kohat e Mardan do que nos distritos de Peshawar e Swat. Essas fontes de água química e bacteriologicamente impróprias para beber podem causar problemas à saúde humana.

Prediction of COVID-19 severity from clinical and biochemical markers: a single-center study from Saudi Arabia.

OBJECTIVE: It is known that the severity of COVID-19 is linked to the prognosis of patients; therefore, an early identification is required for patients who are likely to develop severe or critical COVID-19 disease. The purpose of this study is to propose a statistical method for identifying the severity of COVID-19 disease by using clinical and biochemical laboratory markers. PATIENTS AND METHODS: A total of 48 clinically and laboratory-confirmed cases of COVID-19 were obtained from King Fahad Hospital, Medina (KFHM) between 27th April 2020 to 25th May 2020. The patients' demographics and severity of COVID-19 disease were assessed using 39 clinical and biochemical features. After excluding the demographics, 35 predicting features were included in the analysis (diabetes, chronic disease, viral and bacterial co-infections, PCR cycle number, ICU admission, clot formation, cardiac enzymes elevation, hematology profile, sugar levels in the blood, as well as liver and kidney tests, etc.). Logistic regression, stepwise logistic regression, L-2 logistic regression, L-2 stepwise logistic regression, and L-2 best subset logistic regression were applied to model the features. The consistency index was used with kernel Support-Vector Machines (SVM) for the identification of associated markers. RESULTS: L-2 best subset logistic regression technique outperformed all other fitted models for modeling COVID-19 disease severity by achieving an accuracy of 88% over the test data. Consistency index over L-2 best subset logistic regression identified 14 associated markers that can best predict the COVID-19 severity among COVID-19 patients. CONCLUSIONS: By combining a variety of laboratory markers with L-2 best subset logistic regression, the current study has proposed a highly accurate and clinically interpretable model of predicting COVID-19 severity.

Drinking water quality of various sources in Peshawar, Mardan, Kohat and Swat districts of Khyber Pakhtunkhwa province, Pakistan.

The present study involves the chemical and bacteriological analysis of water from different sources i.e., bore, wells, bottle, and tap, from Peshawar, Mardan, Swat and Kohat districts of Khyber Pakhtunkhwa (KP) province, Pakistan. From each district, 50 water samples (10 samples from each source), regardless of urban and rural status, were collected from these sources and analysed for sulphates, nitrates, nitrites, chlorides, total soluble solids and coliforms (E. coli). Results indicated that majority of the water sources had unacceptable E. coli count i.e.> 34 CFU/100mL. E. coli positive samples were high in Mardan District, followed by Kohat, Swat and Peshawar district. Besides this, the some water sources were also chemically contaminated by different inorganic fertilizers (nitrates/nitrites of sodium, potassium) but under safe levels whereas agricultural and industrial wastes (chloride and sulphate compounds) were in unsafe range. Among all districts, the water quality was found comparatively more deteriorated in Kohat and Mardan districts than Peshawar and Swat districts. Such chemically and bacteriologically unfit water sources for drinking and can cause human health problems.

Automated detection of diabetic retinopathy using machine learning classifiers.

OBJECTIVE: Diabetic Retinopathy (DR) is a highly threatening microvascular complication of diabetes mellitus. Diabetic patients must be screened annually for DR; however, it is practically not viable due to the high volume of patients, lack of resources, economic burden, and cost of the screening procedure. The use of machine learning (ML) classifiers in medical science is an emerging frontier and can help in assisted diagnosis. The few available proposed models perform best when used in similar population cohorts and their external validation has been questioned. Therefore, the purpose of our research is to classify the DR using different ML methods on Saudi diabetic data, propose the best method based on accuracy and identify the most discriminative interpretable features using the socio-demographic and clinical information. PATIENTS AND METHODS: This cross-sectional study was conducted among 327 diabetic patients in Almajmaah, Saudi Arabia. Socio-demographic and clinical data were collected using a systematic random sampling technique. For DR classification, ML algorithm including, linear discriminant analysis, support vector machine, K nearest neighbor, random forest and its variate ranger random forest classifiers were used through cross-validation resampling procedure. RESULTS: In classifying DR, ranger random forest outperforms the other methods by accurately classifying 86% of the DR patients on the test data. HbA1c (p<0.001) and duration of diabetes (p<0.001) were the most influential risk factor that best discriminated the DR patients. Other influential risk factors were the body mass index (p<0.001), age-onset (p<0.001), age (p<0.001), systolic blood pressure (p<0.05), and the use of medication (p<0.05) that significantly discriminated the DR patients. CONCLUSIONS: Based on the present study findings, integrating ophthalmology and ML can transform diagnosing the disease pattern that can help generate a compelling clinical effect. ML can be used as an added tool for clinical decision-making and must not be the sole substitute for a clinician. We will work to examine the classification performance of multi-class data using more sophisticated ML methods.

Effects of Varying Levels of Fungal (Arachniotus sp.) Treated Wheat Straw as an Ingredient of Total Mixed Ration on Growth Performance and Nutrient Digestibility in Nili Ravi Buffalo Calves.

The study was carried out to explore the effects of replacing wheat straw with fungal treated wheat straw as an ingredient of total mixed ration (TMR) on the growth performance and nutrient digestibility in Nili Ravi buffalo male calves. Fungal treated wheat straw was prepared using Arachniotus sp. Four TMRs were formulated where wheat straw was replaced with 0 (TMR1), 33 (TMR2), 67 (TMR3), and 100% (TMR4) fungal treated wheat straw in TMR. All TMRs were iso-caloric and iso-nitrogenous. The experimental TMRs were randomly assigned to four groups of male calves (n = 6) according to completely randomized design and the experiment continued for four months. The calves fed TMR2 exhibited a significant improve in dry matter intake, average daily weight gain, feed conversion ratio and feed economics compared to other groups. The same group also showed higher digestibility of dry matter, crude protein, neutral-, and acid detergent fibers than those fed on other TMRs. It is concluded that TMR with 33% fungal-treated wheat straw replacement has a potential to give an enhanced growth performance and nutrient digestibility in male Nili Ravi buffalo calves.

Clinical outcome of primary non-metastatic breast cancer: A single institution experience.

BACKGROUND: We report on prognostic factors and long-term survival of non-metastatic breast cancer patients treated at Shaukat Khanum Memorial Cancer Hospital and Research Centre (SKMCH and RC) in Pakistan. MATERIALS AND METHODS: This retrospective cohort study is based on a review of 2829 pathologically confirmed non-metastatic breast cancer patients managed from January 1995 to May 2009. Median age was 45 years. Stage at presentation: Stage I (9%), stage II (59%), and stage III (32%). Infiltrating ductal carcinoma (92%) constituted the most prevalent histological subtype. Estrogen (ER), progesterone (PR) and Her2-neu were positive in 49%, 50%, and 26%, respectively. A mastectomy was performed in 67% and conservative surgery in 33% of the patients. Post-operative radiotherapy was delivered in 85% of the cases. Ninety percent of the patients received chemotherapy and mainly consisted of anthracycline-based regimens + taxanes. Hormonal manipulation was done in ER/PR positive patients. RESULTS: The 5- and 10-year overall survival (OS) was 70% (95% confidence interval [CI]: 68.2-71.8%) and 54% (95%CI: 51.2-56.8%), while disease free survival (DFS) was 65% (95% CI: 63-67%) and 52% (95% CI: 49.2-54.8%), respectively. Recurrence following primary treatment was seen in 35% of the patients. On multivariate analysis T stage, number of axillary nodal involvement, tumor grade, ER status and family history, were found to be independent predictors for OS and DFS. CONCLUSIONS: Over 90% of non-metastatic breast cancer patients present with stagesII and III disease and a significant proportion develop distant metastasis accounting for overall long-term outcome inferior to developed countries. Efforts should be directed to raise the level of health awareness and screening programs to improve early detection in Pakistan.

First Report of Papaya Leaf Curl Disease in Pakistan.

Papaya plants with virus-disease-like symptoms were observed in back yards and commercial groves in Multan, Pakistan. Leaves of the diseased plants displayed downward curling and thickened, dark green veins. Leaf-like enations grew from the base of the diseased leaves. These symptoms are similar to those of cotton leaf curl disease. In addition, diseased papayas were stunted and distorted. Leaf extracts from 3 diseased and 2 healthy papayas were tested in enzyme-linked immunosorbent assay against antibodies to geminiviruses. SCRI-52 and SCRI-60, two monoclonal antibodies to Indian cassava mosaic virus (2), reacted positively (more than 7× healthy background) with the diseased samples but not with the healthy ones. Total nucleic acids from the papaya samples were used as templates in polymerase chain reaction with primers F500 and R1800 (1), which are capable of amplifying a region of DNA A component of the whitefly-transmitted geminiviruses. A DNA fragment of approximately 1.4 kb was amplified from the nucleic acids of the diseased but not the healthy papayas. Under high stringency conditions (1), cloned DNA A fragments of both cotton leaf curl virus and cotton leaf crumple virus cross-hybridized with the amplified DNA fragment, but the hybridization signals were much weaker than those of the homologous hybridization. This is the first report of the papaya leaf curl disease in Pakistan. These data demonstrated that a geminivirus may be the causative agent of this papaya disease. We are currently determining the relationship between the geminivirus infecting papaya and cotton leaf curl virus. References: (1) A. Nadeem et al. Mol. Plant Pathol. (On-line: /1997/0612nadeem). (2) M. M. Swanson et al. Ann. Appl. Biol. 211:285, 1992.