Molecular and phenotypic characterization of atypical enteropathogenic Escherichia coli serotypes isolated from children with and without diarrhea

BackgroundWe characterized 36 atypical enteropathogenic Escherichia coli (EPEC) serotypes isolated from children with and without diarrhea in Iran. Because the identification of atypical EPEC based on biochemical features is rather difficult and time consuming, we used a combination of three approaches, including a polymerase chain reaction-based method, culture adherence assay, and the restriction analysis of fliC gene (fliC-restriction fragment length polymorphism), to identify E coli serotypes.MethodsTo distinguish typical and atypical EPEC strains, the presence of EPEC attaching effacing A gene (eaeA) gene and EPEC-attaching factor (EAF) plasmid were analyzed. All E coli strains were identified based on the detection of the eaeA+, bundle-forming pili A gene (bfpA−), EAF− or eaeA−, bfpA+, EAF− profiles and the absence of stx (encoded for shiga toxin) gene as atypical EPEC.ResultsAll strains studied belonged to 5 atypical EPEC serogroups and 15 serotypes based on the virulence profiles. Of 36 atypical EPEC serotypes, 22 (61.2%) and 14 (38.8%) strains isolated from diarrheal and healthy cases, respectively. O142:H48 (19.5%) and O111:H21 (11.1%) serotypes were the most prevalent isolates, followed by serotypes O111: H− and O86:H48 (5.6% each).ConclusionsThe characteristics of the atypical EPEC serotypes from children with diarrhea were significantly different from those without diarrhea. The compilation of data on atypical EPEC strains presented here indicates the importance of a combined approach of conventional and molecular tests to study the virulence and epidemiology of EPEC serotypes in human subjects

The evaluation of different hospital equipment microbial contamination in medical training center Hajar of Shahrekord

Results: The finding frame 137 cultures were showed that125 microbial culture was positive (91%) and 12 microbial cultures was negative (9%). The among microbial culture the highest bacterial contamination is related to bacillus bacteria (32.1%). The among different hospital wards highest bacterial contamination is related to heart, neonate, internal, intensive care unit 1 and 2 and dialysis is (96%) labor (95.5%)-neonate (90.5%) operation room (80%)-the among different hospital instrument highest microbial contamination for ..

Nosocomial Infections Caused by Drug-Resistant Bacteria in a Referral University Hospital, Tehran, Iran

Background: The emergence of antimicrobial-resistant pathogens associated with hospital-acquired infections (HAIs) is a major public health problem worldwide. Although being drug resistance is common in some countries and rare in others, the extent of this condition is not precisely known in most parts of Iran.Materials and Methods: Clinical specimens from patients who had been in the hospital for at least 48 hours were included in this study. The pattern of antibiotic resistance was determined by disk diffusion method as recommended by the Clinical Laboratory and Standards Institute (CLSI).Results: Of 11164 patients that were investigated, 369 (3.3%) had nosocomial infections. The most frequently isolated organisms from all sites of infections were Acinetobacter species (14.2%), Escherichia coli (13.7%) and Pseudomonas aeruginosa (9.9%). Among the Gram-negative bacilli, Acinetobacter spp was mostly resistant to ciprofloxacin, ceftriaxon, co-trimoxazole and centamicin, while P. aeruginosa was frequently resistant to ampicillin/sulbactam (87%). Imipenem and piperacillin/tazobactam were the most active antimicrobials against gram-negative microorganisms whereas vancomycin was the antimicrobial agent most consistently active against the Gram-positive cocci.Conclusions: This study highlights the importance of antimicrobial-resistant pathogens associated with nosocomial infection in Tehran, Iran. Using proper diagnostic criteria as well as administering more effective treatment may limit the frequency of drug-resistant bacteria associated with HAIs.

Distribution of ciprofloxacin-resistance genes among ST131 and non-ST131 clones of Escherichia coli isolates with ESBL phenotypes isolated from women with urinary tract infection

Background and Objectives: Escherichia coli (E. coli) sequence type 131 (ST131) is associated with extended-spectrum beta-lactamase (ESBL) production and fluoroquinolone resistance. This study aimed to investigate the prevalence of ST131, ESBL, and plasmid-mediated quinolone resistance (PMQR) genes in the ciprofloxacin-resistant (CIPR) and ESBL producers from women with UTI. Materials and Methods: The CIP-resistant ESBL producing (CIPR/ESBL+) E. coli isolates were screened for ST131-by specific PCR of mdh and gyrB. The ESBL and PMQR genes were screened by single PCR. The ST131 and non-ST131 isolates were selected to determine the mutations of gyrA and parC using PCR and sequencing, and also their genetic background by the Pasteur-MLST scheme. Results: Overall, 55% (33/60) CIPR/ESBL+ isolates were identified as ST131 (94% O25b-ST131). Resistance rate to ampicillin-sulbactam (70%), aztreonam (97%) and gentamicin (61%), the prevalence of aac(6′)-Ib-cr (66%), blaCTX-M-15 (82%), the profile of qnrS+aac(6′)-Ib-cr (30%), and the double mutation in the parC was significantly higher in ST131 than non-ST131 isolates. The coexistence of PMQR and ESBL genes was found in more than 50% of ST131 and non-ST131 isolates. ST131 isolates differentiated into PST43 and PST506. Conclusion: Management of women with UTI caused by the CIPR/ESBL+ isolates (ST131) co-harbored PMQR, ESBL, and chromosomal mutations, is important for their effective therapy

Prevalence of Enteropathogenic and Shiga Toxin-producing Escherichia coli Among Children With and Without Diarrhoea in Iran

The aim of the study was to determine the rates of detection of enteropathogenic Escherichia coli (EPEC) and Shiga toxin-producing E. coli (STEC) strains among children in two randomly-selected populations in Iran. In total, 1,292 randomly-selected faecal samples from children aged less than 10 years were screened for EPEC and STEC. Of the 1,292 cases participated in the study, 184 had diarrhoea, and 1,108 were healthy/asymptomatic children. The conventional culture method and slide agglutination with 12 different commercial EPEC antisera were used for the detection of EPEC. The colony sweep polymyxin- B extraction method, non-sorbitol fermentation (NSF) phenotype, and slide agglutination with O157: H7 antisera were used for the screening and detection of STEC. Of EPEC belonging to 11 different serogroups, O111 and O127 were most commonly found in 36.4% of the diarrhoeal cases and 7.2% of the asymptomatic children. A significant association (p<0.05) was found between isolation of EPEC and diarrhoea. 8.7% of the diarrhoeal cases and 2% of children without diarrhoea were infected with STEC, but none of the isolates belonged to the O157:H7 serotype. A significant association (p<0.05) was found between STEC and diarrhoeal cases. Based on these findings, it can be concluded that different EPEC serogroups may be agents of endemic infantile diarrhoea, and STEC strains are an important enteropathogen among young children

Indoor environment assessment of special wards of educational hospitals for the detection of fungal contamination sources: A multi-center study (2019-2021)

Background and Purpose: The hospital environment was reported as a real habitat for different microorganisms, especially mold fungi. On the other hand, these opportunistic fungi were considered hospital-acquired mold infections in patients with weak immune status. Therefore, this multi-center study aimed to evaluate 23 hospitals in 18 provinces of Iran for fungal contamination sources.Materials and Methods: In total, 43 opened Petri plates and 213 surface samples were collected throughout different wards of 23 hospitals. All collected samples were inoculated into Sabouraud Dextrose Agar containing Chloramphenicol (SC), and the plates were then incubated at 27-30ºC for 7-14 days.Results: A total of 210 fungal colonies from equipment (162, 77.1%) and air (48,22.9%) were identified. The most predominant isolated genus was Aspergillus (47.5%),followed by Rhizopus (14.2%), Mucor (11.7%), and Cladosporium (9.2%). Aspergillus(39.5%), Cladosporium (16.6%), as well as Penicillium and Sterile hyphae (10.4% each), were the most isolates from the air samples. Moreover, intensive care units (38.5%) and operating rooms (21.9%) had the highest number of isolated fungal colonies. Out of 256 collected samples from equipment and air, 163 (63.7%) were positive for fungal growth.The rate of fungal contamination in instrument and air samples was 128/213 (60.1%) and 35/43 (81.2%), respectively. Among the isolated species of Aspergillus, A. flavus complex (38/96, 39.6%), A. niger complex (31/96, 32.3%), and A. fumigatus complex (15/96, 15.6%) were the commonest species.Conclusion: According to our findings, in addition to air, equipment and instrument should be considered among the significant sources of fungal contamination in the indoor environment of hospitals. Airborne fungi, Hospital, Indoor air, Equipment, Sources of fungal contamination in the indoor environment of hospitals

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

Incidence of diarrhoeagenic Escherichia coli isolated from young children with diarrhoea in the west of Iran

Diarrhoeagenic Escherichia coli (DEC) represents a main group of enteric pathogens that cause human diarrhoea. Because it is not simply distinguished from normal flora by simple laboratory methods, modern molecular diagnostic assays are necessary. Although it is neither necessary nor applicable to perform PCR for all patients, it is of many advantages to verify the prevalence of DEC in different areas by this method. Knowing the prevalence of DEC in an area, we can focus on few pathogens and narrow our antimicrobial treatment. The aim of this study is to evaluate the contribution of the different DEC categories in children diarrhoea in the west of Iran.The stool specimens of 251 children with diarrhoea were collected from June to September 2007. Polymerase chain reaction (PCR) was performed to determine the presence of enteropathogenic (EPEC), enterotoxigenic (ETEC), entero-invasive (EIEC), Shiga toxin-producing (STEC) and entero-aggregative (EAEC) strains. ETEC strains were isolated from 13 and EAEC strains from 16 children. STEC was detected in 7 children, and no EIEC was isolated. Finally, EPEC strains were isolated in 41 cases. EAEC and EPEC are the most frequent DECs in children less than 10 years of age in West of Iran

The β‐domain of streptokinase affects several functionalities, including specific/proteolytic activity kinetics

Streptokinase (SK) is a plasminogen activator which converts inactive plasminogen (Pg) to active plasmin (Pm), which cleaves fibrin clots. SK secreted by groups A, C, and G Streptococcus (SKA/SKC/SKG) is composed of three domains: SKα, SKβ and SKγ. Previous domain‐swapping studies between SK1/SK2b‐cluster variants revealed that SKβ plays a major role in the activation of human Pg. Here, we carried out domain‐swapping between skcg‐SK/SK2‐cluster variants to determine the involvement of SKβ in several SK functionalities, including specific/proteolytic activity kinetics, fibrinogen‐bound Pg activation and α2‐antiplasmin resistance. Our results indicate that SKβ has a minor to determining role in these diverse functionalities for skcg‐SK and SK2b variants, which might potentially be accompanied by few critical residues acting as hot spots. Our findings enhance our understanding of the roles of SKβ and hot spots in different functional characteristics of SK clusters and may aid in the engineering of fibrin‐specific variants of SK for breaking down blood clots with potentially higher efficacy and safety