Analysis and forecasting of road traffic mortalities in Azad Jammu and Kashmir.

OBJECTIVE: To analyse road traffic accident mortalities in a geographical region. Method: The retrospective study was conducted in Azad Jammu and Kashmir based on secondary data from 2004 to 2017 collected from the police department. Duncan's multiple range test was used to assess the trends in road traffic accident fatalities with respect to districts and divisions. Different goodness-of-fit criteria were used to compare the performance of different regression models to analyse road traffic accident mortalities with respect to vehicle ownership. The parsimonious time series model was used to forecast the future trends of road traffic accident mortalities. R 3.6.0 software was used for data analysis. RESULTS: There were 5263 major road traffic accidents during the period studied, causing 2317 deaths and 12963 injuries. The number of mortalities in Mirpur division was 923(39.8%), in Muzaffarabad 794(34.3%), and inss Poonch 600(25.9%). The rates of road traffic accident mortalities per 100,000 population increased up to year 2010 and dropped slowly afterwards (Figure 1C). Some disparities were noted among different districts and divisions with respect to road traffic accident mortalities. Based on different goodness-of-fit criteria, the Smeed's model was found to be the most efficient model to analyse the trends of road traffic accident mortalities with respect to vehicle ownership (Table 1). The forecast for road traffic accident mortalities exhibited some fluctuations in the start and a uniform trend afterwards (Figure 6). CONCLUSIONS: Disparities in road traffic accident fatalities across different districts and divisions of Azad Jammu and Kashmir were observed. Though the rate of road traffic accident mortality was seen to be decreasing since 2010, the situation is for behind compared to the global Sustainable Development Goals.

Gender and occupation wise knowledge, Awareness and prevention of tuberculosis among people of district Muzaffarabad AJ & K.

To assess the awareness about the spread and control of tuberculosis as well as to investigate the gender and occupation wise differences among people regarding knowledge and attitude towards tuberculosis in the State of AJ & K. A cross-sectional descriptive study was conducted in district Muzaffarabad and a sample of 4000 respondents was selected by using stratified random sampling technique. The stratification was done with respect to gender and occupation. The occupation wise classification includes households, labors, and shop keepers, government employers, under graduate students of social and natural sciences, medical students and doctors. A close ended structured questionnaire was developed to collect the data and data were analyzed by using SPSS (Statistical Package for Social Sciences). Chi-Square test was used for association and Logistic Regression model was used to find out the most significant risk factors with gender. Majority of the males were more aware of tuberculosis than females regarding different aspects related to tuberculosis. The respondents from household, labors and shopkeepers have less awareness and knowledge than those who belong to other professions. The doctors and medical students have almost 100% awareness and knowledge of tuberculosis. It was examined that all the variables were associated with gender except threat, curable and transmissible. Only three variables mentioned above showed non- significant result, while all other variables were strongly associated with gender. Males were found more aware about TB than females. Moreover, the literate people were more conscious concerning the prevalence and threats of the disease.

Marinobufagenin regulates permeability and gene expression of brain endothelial cells.

Marinobufagenin (MBG) is a cardiotonic steroid that increases in the circulation in preeclampsia. Preeclampsia and eclampsia are associated with cerebral edema. Therefore, we examined the effects of MBG on human brain microvascular endothelial cells (HBMEC) in vitro. MBG enhanced the permeability of HBMEC monolayers at 1-, 10-, and 100-nM doses, but had no effect at 0.1 nM. Agilent Human Gene Expression microarrays were utilized in these studies. MBG treatment (10 nM for 12 h) downregulated concentrations of the soluble VEGFR transcript sFLT by 59% but did not alter those of FLTv3 mRNA (determined by quantitative PCR). When treated and control HBMEC transcriptomes were interrogated on microarrays, 1,069 genes appeared to be regulated by MBG. Quantitative RT-PCR confirmed that MBG treatment upregulated ENKUR mRNA concentrations by 57%. Its protein product interacts with calmodulin and calcium channel proteins. MBG treatment downregulated several genes whose protein products are involved in cell adhesion (ITGA2B, FERMT1, CLDN16, and TMEM207) and cell signaling (GRIN2C, SLC8A1, and ESR1). The level of downregulation ranged from 22 to 66%. Altogether, MBG actively enhanced the permeability of HBMEC monolayers while downregulating genes involved in adhesion. MBG treatment had variable effects on ENKUR, GRIN2C, and SLC8A1 genes, all associated with calcium transport. These studies provide the basis for future investigations of MBG actions in normal physiology and disease.

Linkage study of DFNB3 responsible for hearing loss in human.

BACKGROUND: Hearing disorders represent a significant health problem worldwide. Recessive inherited cases of the deafness are more prevalent in Pakistan due to consanguineous marriages. Deafness caused by DFNB3 is due to mutation in the gene MYO XVA and its prevalence among Pakistani population is about 5%. MATERIALS AND METHODS: Families with at least two or more individual affected with deafness were selected from different areas of District Okara of Pakistan. Six consanguineous families of different ethnic groups having deaf individuals were studied. All these families had three or more deaf individuals in either two or more sib ships. Family history was taken to minimize the chances of other abnormalities. Pedigrees drawn by using Cyrillic software (version 2.1) showed that all the marriages were consanguineous and the families have recessive mode of inheritance. Three STR markers were selected and amplified on all the samples of six families through PCR. The PCR products were then genotyped on non denaturing polyacrylamide gel electrophoresis (PAGE). Haplotypes were constructed to determine the pattern of inheritance and also to determine whether a family was linked or unlinked with known DFNB3 locus. RESULTS: One out of six families showed linkage to the DFNB3 while rest of the families remained unlinked. Carriers of deafness genes were identified and information was provided to the families on request. CONCLUSION: Knowledge about the genetic causes of deafness provide insight into the variable expression of genes involved in this hereditary problem and may allow the prediction and prevention of associated health problems.

Indigenous cattle of Sri Lanka: Genetic and phylogeographic relationship with Zebu of Indus Valley and South Indian origin.

The present study reports the population structure, genetic admixture and phylogeography of cattle breeds of Sri Lanka viz. Batu Harak, Thawalam and White cattle. Moderately high level of genetic diversity was observed in all the three Sri Lankan zebu cattle breeds. Estimates of inbreeding for Thawalam and White cattle breeds were relatively high with 6.1% and 7.2% respectively. Genetic differentiation of Sri Lankan Zebu (Batu Harak and White cattle) was lowest with Red Sindhi among Indus Valley Zebu while it was lowest with Hallikar among the South Indian cattle. Global F statistics showed 6.5% differences among all the investigated Zebu cattle breeds and 1.9% differences among Sri Lankan Zebu breeds. The Sri Lankan Zebu cattle breeds showed strong genetic relationships with Hallikar cattle, an ancient breed considered to be ancestor for most of the Mysore type draught cattle breeds of South India. Genetic admixture analysis revealed high levels of breed purity in Lanka White cattle with >97% Zebu ancestry. However, significant taurine admixture was observed in Batu Harak and Thawalam cattle. Two major Zebu haplogroups, I1 and I2 were observed in Sri Lankan Zebu with the former predominating the later in all the three breeds. A total of 112 haplotypes were observed in the studied breeds, of which 50 haplotypes were found in Sri Lankan Zebu cattle. Mismatch analysis revealed unimodal distribution in all the three breeds indicating population expansion. The sum of squared deviations (SSD) and raggedness index were non-significant in both the lineages of all the three breeds except for I1 lineage of Thawalam cattle (P<0.01) and I2 lineage of Batu Harak cattle (P<0.05). The results of neutrality tests revealed negative Tajima's D values for both the lineages of Batu Harak (P>0.05) and White cattle (P>0.05) indicating an excess of low frequency polymorphisms and demographic expansion. Genetic dilution of native Zebu cattle germplasm observed in the study is a cause for concern. Hence, it is imperative that national breeding organizations consider establishing conservation units for the three native cattle breeds to maintain breed purity and initiate genetic improvement programs.

Sociodemographic and genetic determinants of nonalcoholic fatty liver disease in type 2 diabetes mellitus patients.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) showed significant association with PNPLA3 rs738409 polymorphism in unrelated individuals. However, it is still unknown whether the relationship of NAFLD with PNPLA3 variant exists or not among subjects with type 2 diabetes mellitus (T2DM). Therefore, the study aimed to evaluate sociodemographic and genetic determinants of NAFLD in type 2 diabetics. METHODS: The cross-sectional analytical study was conducted at the Department of Molecular Biology, Virtual University of Pakistan, Lahore, Pakistan, during 2019-2020. A total of 153 known cases of T2DM were enrolled using convenience sampling. After excluding patients (n = 24) with HCV, alcoholism, or missing information, data from 129 eligible diabetics with and without NAFLD were analyzed using SPSS. Odds ratios using crosstabs and adjusted odds ratios using binary and multinomial logistic regression were calculated to measure the risk of NAFLD. RESULTS: Adults 18-35 years were 7.0%, 36-55 years were 64.3%, ≥ 56 years were 28.7%, and females were 66.7%. A total of 41.1% of patients had obesity, 52.7% had NAFLD, and 29.05% carried mutant G allele of rs738409 polymorphism. Among overall diabetics, NAFLD showed association with female (OR = 2.998, p = 0.007), illiterate (OR = 3.067, p = 0.005), and obese (OR = 2.211, p = 0.046) but not with PNPLA3 genotype under any model (all p = > 0.05). Among obese diabetics, NAFLD showed association with female (AOR = 4.010, p = 0.029), illiterate (AOR = 3.506, p = 0.037), GG + CG/CC (AOR = 3.303, p = 0.033), and GG/CG + CC (AOR = 4.547, p = 0.034) using binary regression and with female (AOR = 3.411, p = 0.051), illiterate (AOR = 3.323, p = 0.048), GG + CG/CC (AOR = 3.270, p = 0.029), and GG/CG + CC (AOR = 4.534, p = 0.024) using multinomial regression. CONCLUSIONS: NAFLD and obesity were the most common comorbid diseases of T2DM. Gender female, being illiterate, and PNPLA3 rs738409 polymorphism were significant risk factors of NAFLD among obese diabetic patients.

Analysis and forecasts for trends of COVID-19 in Pakistan using Bayesian models.

BACKGROUND: COVID-19 is currently on full flow in Pakistan. Given the health facilities in the country, there are serious threats in the upcoming months which could be very testing for all the stakeholders. Therefore, there is a need to analyze and forecast the trends of COVID-19 in Pakistan. METHODS: We have analyzed and forecasted the patterns of this pandemic in the country, for next 30 days, using Bayesian structural time series models. The causal impacts of lifting lockdown have also been investigated using intervention analysis under Bayesian structural time series models. The forecasting accuracy of the proposed models has been compared with frequently used autoregressive integrated moving average models. The validity of the proposed model has been investigated using similar datasets from neighboring countries including Iran and India. RESULTS: We observed the improved forecasting accuracy of Bayesian structural time series models as compared to frequently used autoregressive integrated moving average models. As far as the forecasts are concerned, on August 10, 2020, the country is expected to have 333,308 positive cases with 95% prediction interval [275,034-391,077]. Similarly, the number of deaths in the country is expected to reach 7,187 [5,978-8,390] and recoveries may grow to 279,602 [208,420-295,740]. The lifting of lockdown has caused an absolute increase of 98,768 confirmed cases with 95% interval [85,544-111,018], during the post-lockdown period. The positive aspect of the forecasts is that the number of active cases is expected to decrease to 63,706 [18,614-95,337], on August 10, 2020. This is the time for the concerned authorities to further restrict the active cases so that the recession of the outbreak continues in the next month.

Descriptive analysis and earthquake prediction using boxplot interpretation of soil radon time series data.

Correlation of radon anomalies with meteorological parameters and earthquake occurrence has been reported in many studies. This paper reports descriptive statistical analysis and boxplot contingent earthquake prediction based upon soil radon time series data. Data has been collected over a fault line, passing beneath the Muzaffarabad, for the period of one year. Soil radon gas (SRG) was measured using RTM 1688-2 radiometric instrument (made by SARAD GmbH). The range of radon in soil was found to be 14349 Bqm-3, whereas the ranges of temperature, pressure and relative humidity were found as 38.50 C0, 29 mbar and 67% respectively. SRG data shows that time series follows normal distribution. Values of coefficient of variation (CV) indicate the consistency of the recorded values of radon in soil and metrological parameters. Variance inflation factor (VIF) and Durbin Watson test (d) indicate a moderate multicollinearity and autocorrelation between variables. The analysis of radon time series using boxplots and meteorological parameters show specific patterns in radon concentrations (outliers, variant IQRs, first quartile values, and median values) due to pre-earthquake underground seismic activities. On the basis of these patterns earthquake may be more early predicted without using complicated predictive systems. Boxplots also predicted that there is no significant pattern found in dispersion of meteorological factors measured in this study. To the best of our knowledge this is first ever attempt to predict earthquake using boxplot explanation.

Sample size issues in multilevel logistic regression models.

Educational researchers, psychologists, social, epidemiological and medical scientists are often dealing with multilevel data. Sometimes, the response variable in multilevel data is categorical in nature and needs to be analyzed through Multilevel Logistic Regression Models. The main theme of this paper is to provide guidelines for the analysts to select an appropriate sample size while fitting multilevel logistic regression models for different threshold parameters and different estimation methods. Simulation studies have been performed to obtain optimum sample size for Penalized Quasi-likelihood (PQL) and Maximum Likelihood (ML) Methods of estimation. Our results suggest that Maximum Likelihood Method performs better than Penalized Quasi-likelihood Method and requires relatively small sample under chosen conditions. To achieve sufficient accuracy of fixed and random effects under ML method, we established ''50/50" and ''120/50" rule respectively. On the basis our findings, a ''50/60" and ''120/70" rules under PQL method of estimation have also been recommended.

Bayesian Analysis of Three-Parameter Frechet Distribution with Medical Applications.

The medical data are often filed for each patient in clinical studies in order to inform decision-making. Usually, medical data are generally skewed to the right, and skewed distributions can be the appropriate candidates in making inferences using Bayesian framework. Furthermore, the Bayesian estimators of skewed distribution can be used to tackle the problem of decision-making in medicine and health management under uncertainty. For medical diagnosis, physician can use the Bayesian estimators to quantify the effects of the evidence in increasing the probability that the patient has the particular disease considering the prior information. The present study focuses the development of Bayesian estimators for three-parameter Frechet distribution using noninformative prior and gamma prior under LINEX (linear exponential) and general entropy (GE) loss functions. Since the Bayesian estimators cannot be expressed in closed forms, approximate Bayesian estimates are discussed via Lindley's approximation. These results are compared with their maximum likelihood counterpart using Monte Carlo simulations. Our results indicate that Bayesian estimators under general entropy loss function with noninformative prior (BGENP) provide the smallest mean square error for all sample sizes and different values of parameters. Furthermore, a data set about the survival times of a group of patients suffering from head and neck cancer is analyzed for illustration purposes.

Comparison of Neurocognitive Testing and the Measurement of Marinobufagenin in Mild Traumatic Brain Injury: A Preliminary Report.

The evaluation of concussed athletes, including testing to determine if and when they may return to play, has become an important task of athletic trainers and team physicians. Currently, concussion protocols are in place, which depend largely upon assessments based upon neurocognitive testing (NCT). The authors have evaluated the use of a biomarker of brain trauma, marinobufagenin (MBG), and compared its application in concussed athletes with the performance of NTC. We found a disparity between these two testing procedures. In this communication, the findings of these comparative data are presented. We noted that athletes whose NCT evaluations had returned to baseline and who were allowed to again participate in play then showed a recurrence of elevated urinary MBG excretion. These observations raise concern as to the processes currently in effect with regard to the decision as to returning athletes to the full activity. They suggest a need for further evaluation.

Fast-track laparoscopic gastric bypass surgery: outcomes and lessons from a bariatric surgery service in the United Kingdom.

BACKGROUND: Laparoscopic Roux-en-Y gastric bypass (LRYGB) is a potentially complicated surgery with significant hospitalisation, especially during the learning curve. There are inadequate data on fast-track LRYGB in relation to learning curve. This study highlights the outcomes of a fast-track LRYGB service. METHODS: This observational study examined the perioperative outcome data of 406 consecutive LRYGB patients over a 4-year period. Perioperative outcome data were analysed and compared between severe obesity, morbid obesity and super obesity groups. RESULTS: Mean BMI was 48.6 ± 8.3, mean age was 42 years and male to female ratio was 1:4. About 4% of patients had concurrent ventral hernia repair. Median duration of combined LRYGB and ventral hernia repair was 115 min, compared to 95 min for LRYGB alone (p = 0.09). Intraoperative complication rate was 0.5%. Postoperative complications occurred in 3.4% of patients with 60% within 24 h. The complication rate per obesity group was <7% and similar between groups (p = 0.4). There was no perioperative mortality. More super obese patients received postoperative intensive care compared to others (p = 0.001). Mean length of hospital stay was similar between obesity groups and decreased from 2 to 1 day over 2 years. There was a learning curve of 109 cases over 2 years. CONCLUSION: LRYGB is a safe technique of bariatric surgery with low risk of perioperative complications. Establishing a fast-track LRYGB service requires a learning curve of 100 cases, and a good indicator is length of hospital stay, which decreases as the service matures. Most LRYGB patients can be safely discharged by 24 h.