Report of 267 Cases of Scorpion Bite Referring to an Emergency Department during One Year

Scorpion bite is a common health problem in many parts of the world, including the Iran’s tropics. There are thousands of cases and a number of deaths due to scorpion bite every year in the country. The present study aims to provide further data regarding the details, complications and outcomes of scorpion bite cases referring to Razi Hospital, Ahwaz, from March 2011 to April 2012. A total of 267 patients (56.3% females) with a mean age of 35.2±15.8 years, were included in the study. The most common genus of scorpion involved was Hemiscorpius (69.3%) and the most frequent body part involved was the lower limb (38.9%). The frequency of hemolysis-induced renal insufficiency and death after scorpion bite were 1.9% and 1.1%, respectively. Of all the factors evaluated in this series only the old age was associated with higher possibility of renal insufficiency (P<0.001).

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions

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

An enhanced similarity measure for utilizing site structure in web personalization systems

The need for recommendation systems to ease user navigations has become evident by growth of information on the Web. There exist many approaches of learning for Web usage-based recommendation systems. In hybrid recommendation systems, other knowledge resources, like content, semantics, and hyperlink structure of the Web site, have been utilized to enhance usage-based personalization systems. In this study, we introduce a new structure-based similarity measure for user sessions. We also apply two clustering algorithms on this similarity measure to compare it to cosine and another structure-based similarity measures. Our experiments exhibit that adding structure information, leveraging the proposed similarity measure, enhances the quality of recommendations in both methods

Applying and comparing hidden Markov model and fuzzy clustering algorithms to Web usage data for recommender systems

In this study, we apply and compare some of the methods of usage pattern discovery, like simple k-means clustering algorithm, fuzzy relational subtractive clustering algorithm, fuzzy mean field annealing (MFA) clustering and Hidden Markov Model (HMM), for recommender systems. We use metrics like prediction strength, hit ratio, precision, prediction ability and F-Score to compare the applied methods on the Web usage data. Fuzzy MFA and HMM acted better than other methods due to fuzzy nation of human behavior in navigation and extra information utilized in sequence analysis

Is responsiveness to weight loss diets affected by family history of diabetes?

BACKGROUND: Obesity is associated with many metabolic and chronic diseases, such as diabetes and cardiovascular disease. Family history of diabetes (FHD) is also an important risk factor for type 2 diabetes. Furthermore, the presence of FHD and obesity has a synergic effect on risk of diabetes incidence. The aim of this study was to determine whether FHD influence the weight loss induced by weight loss diet. METHODS: This study was an intervention between individuals with or without FHD. Seventy-eight positive FHD and 74 negative FHD individuals were participated in this study. Two groups were matched for age, gender, and body mass index (BMI). In the present study, expert interviewers collected socio-demographic data and prescribed dietary recommendations in a face-to-face method. RESULTS: Dietary intervention significantly reduces the body weight and BMI in both groups, but these reductions were not different between negative and positive FHD groups. This study could not find any significant association between FHD and responsiveness to weight loss diets (&beta; = &minus;0.058; 95% confidence interval, &minus;1.618 to 0.832; P = 0.526). CONCLUSION: Individuals with FHD have higher risk for obesity and chronic diseases, but in the current study there was no difference in responsiveness to weight loss in individuals with a positive family history and those without a family history. &nbsp; Keywords: Body Weight, Body Mass Index, Weight Loss Diet, Family History of Diabetes&nbsp;</div

Cancer chemotherapy resistance: Mechanisms and recent breakthrough in targeted drug delivery

Conventional chemotherapy, one of the most widely used cancer treatment methods, has serious side effects, and usually results in cancer treatment failure. Drug resistance is one of the primary reasons for this failure. The most significant drawbacks of systemic chemotherapy are rapid clearance from the circulation, the drug's low concentration in the tumor site, and considerable adverse effects outside the tumor. Several ways have been developed to boost neoplasm treatment efficacy and overcome medication resistance. In recent years, targeted drug delivery has become an essential therapeutic application. As more mechanisms of tumor treatment resistance are discovered, nanoparticles (NPs) are designed to target these pathways. Therefore, understanding the limitations and challenges of this technology is critical for nanocarrier evaluation. Nano-drugs have been increasingly employed in medicine, incorporating therapeutic applications for more precise and effective tumor diagnosis, therapy, and targeting. Many benefits of NP-based drug delivery systems in cancer treatment have been proven, including good pharmacokinetics, tumor cell-specific targeting, decreased side effects, and lessened drug resistance. As more mechanisms of tumor treatment resistance are discovered, NPs are designed to target these pathways. At the moment, this innovative technology has the potential to bring fresh insights into cancer therapy. Therefore, understanding the limitations and challenges of this technology is critical for nanocarrier evaluation.Ministerio de Ciencia e Innovación (MICIN)Agencia Estatal de InvestigaciónUnión EuropeaUniversidad Complutense de MadridDepto. de Bioquímica y Biología MolecularFac. de Ciencias BiológicasTRUEpu

Evaluation of antibiotic resistance changes in Acinetobacter baumannii in the era of COVID-19 in Northern Iran

Background and Objectives: During the coronavirus pandemic, the overuse of antibiotics to reduce coinfections and mortality may be contributing to the rise of antimicrobial resistance. In this study, we aim to investigate the antibiotic resistance changes of Acinetobacter baumannii post-COVID-19 pandemic in Northern Iran. Materials and Methods: The current study is a cross-sectional study. Between 2022 and 2023, 2190 clinical samples were collected from patients with healthcare-associated infections (HAIs) at four hospitals in Sari, which served as corona centers after the COVID-19 pandemic. Antimicrobial sensitivity was determined using standard broth macro-dilution, and resistance genes were detected using multiplex PCR. Results: Based on the results co-amoxiclav had a resistance rate of 100%, while piperacillin/tazobactam showed the least resistance rate of 29.82%. In terms of GM MIC values, colistin was the most potent against multi-drug resistant isolates. The frequency of blaOXA-51, ampC, aphA6, and blaNDM genes were 100%, 99.12%, 90.35%, and 69.30% respectively. Conclusion: Our study revealed high multi-drug resistance rates. Piperacillin/tazobactam recommended for treating multidrug resistant Acinetobacter baumannii infections in Northern Iran

Familial Hypercholesterolemia (FH) in Iran: Findings from the Four-Year FH Registry

Background. Familial hypercholesterolemia (FH) is a common autosomal dominant disease. Its diagnosis in Iran was uncommon. Iran registry of FH (IRFH) has been started from 2017 from Isfahan. In this study, we report the four-year FH registry. Methods. The Iran FH registry is an ongoing study which is followed by a dynamic cohort. It has been started from 2017. The patients are selected from laboratories due to high cholesterol level and who have history of premature cardiovascular disease. The Dutch Lipid Clinic Network (DLCN) criteria are used for the detection of FH. Cascade screening is performed for detection of first-degree relative of patients. Results. Among the 997 individuals included in this registry, they were 522 (mean age 51.41±12.91 year), 141 (mean age 51.66±8.3 year), and 129 (mean age 41±16.5 year) patients from laboratories, premature cardiovascular disease, and relatives, respectively. In total, 263 patients were diagnosed with probable or definite FH, and others were in the possible group. Low-density lipoprotein cholesterol (LDL) level was 141.42±45.27 mg/dl in the laboratory group and 54.9% of patients were on LLT treatment. In patients with premature cardiovascular disease and FH, the LDL level was 91.93±32.58 and was on LLT treatment. The LDL concentration in the first relative of FH patients was 152.88±70.77 and 45.7% of them are on LLT therapy. Conclusions. Most of FH patients were underdiagnosed and undertreated before their inclusion in the IRFH. Cascade screening helps in the improvement of diagnosis