Immunohistochemical Expression of Nkx3.1 in Prostatic Adenocarcinoma and Benign Prostatic Hyperplasia at a Tertiary Care Hospital in Karachi

OBJECTIVES To determine NKX3.1 expression in prostatic adenocarcinoma and benign prostate hyperplasia on Immunohistochemistry at a tertiary care hospital in Karachi. METHODOLOGY 74 prostatic specimens were recruited in this comparative cross-sectional study at the Department of Pathology, Pakistan Navy Station Shifa Hospital, Karachi, from January 2018 to February 2019. Of these, 37 specimens were of prostatic adenocarcinoma, and 37 were benign prostate hyperplasia. All specimens were subjected to immunohistochemical staining with NKX3.1. Statistical analysis was done by using SPSS version 23.0. The association of the extent of NKX3.1 staining between the adenocarcinoma and hyperplasia group was assessed using the Chi-square test x2. RESULTSOf the 37 cases of benign prostatic hyperplasia subjected to NKX3.1 staining, 32 showed positive staining with strong to moderate intensity. No staining was observed in 5 cases. 37 cases of adenocarcinoma prostate stained for NKX3.1 revealed positive staining in 30 cases with strong to moderate intensity. Negative staining was seen in 7 cases. The prostatic adenocarcinoma showed a statistically significant association of NKX3.1 positivity compared to benign prostatic hyperplasia cases. The p-value was found to be 0.03. CONCLUSION NKX3.1 staining was highly specific for prostate epithelium, as it was positive in most cases. This immune marker was useful for distinguishing prostatic origin in the context of metastatic lesions. Adding NKX3.1 protein staining to a panel of features may add value to the diagnosis if applied in the appropriate clinicopathologic context

Bacterial Profile and Antimicrobial Susceptibility Pattern in Septicemia Suspected Children and Available Treatment Options

OBJECTIVES Septicaemia (blood poisoning) is one of the chief sources of global morbidity and mortality in pediatric patients and presents with multidrug and extensive drug resistance. This study aims to detect the major causative agents, antimicrobial susceptibility patterns and associated factors of bacteraemia among pediatric patients.METHODOLOGY This retrospective cross-sectional study was done at National Medical Center, Karachi microbiology laboratory. Clinical specimens consist of blood. Blood samples were processed in BACTEC's automated blood culture system, and positive samples were sub-cultured on blood, Mac-Conkey. Final identification was done by API 20E and API 20NE (Biomerieux) and confirmed by MicroScan (Beckman coulter)®. The antimicrobial susceptibility was performed by using Bauer– Kirby disk diffusion method.RESULTS A total of 395 pediatric patients were taken in the study. Out of these patients, 226 (57.2 %) were female. The children with age 1-4 years were highly affected. Almost 50% were handled in emergency and transferred for admission. 36.2% of patients were exposed to intravenous devices. 89 (22.5%) patients had a history of prolonged use of antibiotics. Most patients with pneumonia presented with septicemia as a complication, and were detected by Klebsiella pneumonia (35.4%), Acinetobacter bauminii (25.3%) and Pseudomonas aeruginosa (20.3%).  CONCLUSION The study revealed that gram-negative organisms are the predominant causative organisms of septicaemia. Antibiotic resistance to Carbapenem is gradually increased in the case of Acinetobacter bauminii and Escherichia coli. These issues can be overcome by early detection of microorganisms and establishing antibiotic stewardship

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

The McDonald’s Inverse Weibull Distribution

We have proposed a new Inverse Weibull distribution by using the generalized Beta distribution of McDonald (1984). Basic properties of the proposed distribution has been studied. Parameter estimation has been discussed alongside an illustrative example

A CLASS OF WEIGHTED WEIBULL DISTRIBUTION

The weighted Weibull model is proposed following the method of Azzalini (1985). Basic properties of the distribution; including moments, generating function, hazard rate function and estimation of parameters; have been studied

The Kumaraswamy–Inverse Weibull Distribution

In this paper we have proposed a new four parameter Inverse Weibull distribution that is based upon the cumulative distribution function of Kumaraswamy (1980) distribution. The distributional properties of the proposed distribution have been studied. Special cases of the proposed distribution have also been explored

Rapid detection of ceftriaxone resistance in clinical isolates of extensively drug resistant Salmonella enterica serovar Typhi

Objective: To see the efficacy of rapid color test for the sensitivity of ceftriaxone against clinical isolates of Salmonella Typhi. Methods: This descriptive cross sectional study was carried out at the department of Microbiology, Pakistan Navy Ship (PNS) Shifa Hospital, Karachi from Nov 2018 through April 2019.We tested 97 clinical isolates of Salmonella Typhi by this rapid color test. All the isolates were also test by conventional disc diffusion method and MICs by Vitek-2 system. Results: Out of these isolates, 83 were ceftriaxone resistant while 14 isolates were ceftriaxone sensitive. Sensitivity and specificity of rapid color test were 100% when compared with results of disc diffusion, E-test and Vitek 2 system. All the results were readable within 2 hours on color test. Conclusion: This color test is rapid, accurate and inexpensive and can be used as a screening test for ceftriaxone resistance in typhoid endemic areas. Keywords: Ceftriaxone; drug resistance; meropenem Continuous..

Preventing the Cloud Networks through Semi-Supervised Clustering from Both Sides Attacks

Cloud computing is a centralized data storage system providing various services worldwide. Different organizations are using the cloud for other purposes. As the number of users on the cloud server increases, so does the rate of attacks on the cloud. Various researchers have devised different solutions to solve these problems, the most widely used being the Intrusion Detection System (IDS). In this paper, a network architecture has been designed in which an efficient technique, semi-supervised clustering, has been used. In this technique, users’ responses inside and outside the cloud server have been observed, and various rules and mechanisms have been enforced based on these responses. The network is divided into three different scenarios. In the first scenario, attacks outside the cloud server have been detected, and then ways to prevent these attacks are discussed. The second scenario uses Cloud Shell, allowing authentic users to access the cloud server through authentic queries. In the third scenario, this tool’s performance and detection rate have been measured by applying different results to the confusion matrix. A comparative analysis has been done with other papers at the end of the paper, and conclusions have been drawn based on different results

Preventing the Cloud Networks through Semi-Supervised Clustering from Both Sides Attacks

Cloud computing is a centralized data storage system providing various services worldwide. Different organizations are using the cloud for other purposes. As the number of users on the cloud server increases, so does the rate of attacks on the cloud. Various researchers have devised different solutions to solve these problems, the most widely used being the Intrusion Detection System (IDS). In this paper, a network architecture has been designed in which an efficient technique, semi-supervised clustering, has been used. In this technique, users’ responses inside and outside the cloud server have been observed, and various rules and mechanisms have been enforced based on these responses. The network is divided into three different scenarios. In the first scenario, attacks outside the cloud server have been detected, and then ways to prevent these attacks are discussed. The second scenario uses Cloud Shell, allowing authentic users to access the cloud server through authentic queries. In the third scenario, this tool’s performance and detection rate have been measured by applying different results to the confusion matrix. A comparative analysis has been done with other papers at the end of the paper, and conclusions have been drawn based on different results