Predicting microRNAs as Anti-viral Agents in SARS-CoV-2 Infection Based on the Bioinformatics Approach: A Systematic Review

Purpose: The beginning of 2020, the World health organization (WHO) declared severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as responsible for the coronavirus disease 2019 (COVID-19) outbreak. Previous studies showed that microRNAs (miRNAs) are able to inhibit pathogenesis of DNA or RNA viruses by binding the genome. The purpose of the current study is an overview of the anti-viral role of cellular miRNAs against the COVID-19 infection. Methods: Our search was limited to all published original papers in the English language from 2019 to 2021 using several databases including PubMed, Google scholar, Scopus, and Science Direct. A manual search of references for included articled was also performed. Among 66 electronically searched citations, 17 papers met the inclusion criteria. Results: The presence of miRNAs during the COVID-19 infection, reported by several studies, predicts the possibility of using miRNAs as potential tools to eradicate the SARS-CoV-2 infection. In some studies, miRNAs have presented as a tool for targeting SARS-CoV-2 encoded genes which are essential in viral biogenesis, entrance, replication, and infection. Conclusion: The comparison of miRNA between SARS-CoV-2 with other human coronaviruses will help the better understanding of distinct clinical characteristics of them

Frequency of methicillin resistant Staphylococcus aureus in the noses of Malaysian chicken farmers and their chicken

The prevalence of methicillin resistant Staphylococcus aureus (MRSA) and methicillin sensitive Staphylococcus aureus (MSSA) carriage among poultry and poultry farmers in Malaysia is largely unknown. In the current investigation, chickens and chicken farmers from 30 chicken farms were screened for MRSA and S. aureus carriage. The genetic characteristics of the isolates were determined through multi locus sequence typing (MLST), Staphylococcus protein A (spa) typing and virulent gene profiling. The outcome of the study showed lack of MRSA and extremely low S. aureus prevalence (n=7 of 503, 1.4%) among chicken flocks and the poultry farmers in Malaysia. Staphylococcus aureus isolates belonged to 4 sequence types (ST): ST97 (spa type t359), ST1179 (t359), ST 692 (t2247) and ST188 (t189). It can be concluded that MRSA/MSSA prevalence is very low among chicken and chicken farmers, human and chicken cross transmission of S. aureus does not seem to be a threat in Malaysia

Methicillin-susceptible and -resistant Staphylococcus aureus with high-level antiseptic and low-level mupirocin resistance in Malaysia

The prevalence and spread of mupirocin and antiseptic resistance among colonizing and infectious Staphylococcus aureus were determined. S. aureus isolated from anterior nares and infection sites of patients hospitalized in the largest tertiary care referral hospital in Malaysia was investigated for mupirocin and antiseptic susceptibility testing, and for PCR detection of mupA, qacA/B, and smr genes. Twelve isolates showed resistance to mupirocin by disk diffusion, of which 10 (3.8%) harbored the mupA gene. Minimum inhibitory concentrations (MICs) ranged from 64 to 768 μg/ml for mupA positive and below 46 μg/ml for negative isolates. The mupA was more common among ST239 isolates (70%). The qacA/B was carried in 67 out of 95 methicillin-resistant Staphylococcus aureus (MRSA) (70.5%) and 3 out of 164 methicillin-susceptible Staphylococcus aureus (MSSA) (1.8%), while smr was carried in 6 out of 95 MRSA (6.3%) strains. MICs ranged from 3.9 to 15.6 μg/ml for benzethonium chloride (BTC) and benzalkonium chloride (BKC), and from 10.3 to 20.7 μg/ml for chlorhexidine digluconate (CHG). Isolates with qacA/B and smr or qacA/B alone showed higher MIC (20.7 μg/ml for CHG and 15.6 μg/ml for BTC and BKC) than the isolates that lacked antiseptic resistance genes (10.3 μg/ml for CHG and 3.9 μg/ml for BTC and BKC). In 16 cases, ST239 was isolated from the infection site and the nares simultaneously, and shared identical resistance patterns (qacAB or qacAB+smr), suggesting possible endogenous infection. Spread of low-level mupirocin resistance expressing ST239 MRSA and high-level resistance expressing emerging ST1, co-existing with antiseptic-resistant genes showing elevated MICs, should be monitored for effective infection control

A low prevalence of inducible macrolide, lincosamide, and streptogramin B Resistance phenotype among methicillin-susceptible staphylococcus aureus isolated from Malaysian patients and healthy individuals

Background: Antibiotic resistance among Staphylococcus aureus is of great concern worldwide. This resistance is further complicated by the ability of S. aureus to confer cross-resistance to other antibiotics due to the presence of resistance genes, such as erythromycin resistance methylase (erm) genes, which render the bacterium resistant to macrolide-lincosamide-streptogramin B (MLSB) antibiotics. Resistance to these antibiotics can lead to therapeutic failure, resulting in significant morbidity and mortality in patients with S. aureus infections. Objectives: This study was performed to examine the distribution of MLSB-resistant strains of methicillin-susceptible S. aureus (MSSA), which were obtained from hospitalized patients and normal healthy individuals (carriers) using phenotypic methods, such as the double-disk diffusion (D-test) and the genotypic method by polymerase chain reaction (PCR). Methods: A total of 183 nonduplicative MSSA isolates obtained from hospitalized patients (133) and carriers (50) in our previous studies were randomly selected for the D-test. The guidelines of the Clinical and Laboratory Standards Institute (CLSI) were used for the interpretation of the results of this test. The detection of ermA, ermB, ermC and msrA genes by PCR was performed for isolates that had positive D-test results and that were resistant to erythromycin. Results: Of the 183 MSSA isolates, 97.2% and 98.4% were highly susceptible to erythromycin and clindamycin, respectively. MSLB resistance was detected in four isolates (2.2%). Of the 133 MSSA isolated from hospitalized patients, only 3.0% (4/133) and 2.3% (3/133) exhibited resistance to erythromycin and clindamycin, respectively. With regard to the MLSB resistance phenotypes, only 1.6% and 0.6% exhibited inducible MLSB (iMLSB) and MS phenotypes, respectively. The ermC gene was detected in all three iMLSB phenotypes, and the msrA gene was detected in the MS phenotype. Surprisingly, all MSSA isolates (100%) from carriers exhibited extremely high susceptibility to both antibiotics. Conclusions: The prevalence rates of iMLSB MSSA isolates vary according to geographical locations and the local antibiotic policy. The low prevalence rate of iMLSB MSSA isolates could probably be related to the judicious use of antibiotics for treating S. aureus infections in our studied population. Nonetheless, continuous antibiotic surveillance is still necessary to control any emergence of resistance isolates so that targeted therapy and effective control can be implemented accordingly

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

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

Seroprevalence of Leptospira infection in occupational risk groups in North Khorasan province, Iran

Leptospirosis is an important zoonotic bacterial disease caused by Leptospira spp. Earlier studies from North Khorasan province (Iran) reported the presence of Leptospira in wild canines and rodents. To date, there is no data on the seroprevalence of leptospirosis among humans in this province. This study was performed to determine the prevalence of human leptospiral infection among people with different occupations. The study was conducted in urban and rural areas of the province. Among the serum samples collected from 278 subjects, 3 (1.1%) showed positive reaction with titer of 1:100 by the microscopic agglutination test (MAT). Positive reactions were detected against Leptospira interrogans Canicola and L. interrogans icterohemorrhagic and all these samples were from livestock farmers (n = 3/106, 2.7%). The current study revealed that, though Leptospira infection is low in North Khorasan province, regular monitoring of the livestock and the farmers are important