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Diarrhoea is the second leading cause of mortality in children worldwide, but establishing the cause can be complicated by diverse diagnostic approaches and varying test characteristics. We used quantitative molecular diagnostic methods to reassess causes of diarrhoea in the Global Enteric Multicenter Study (GEMS). GEMS was a study of moderate to severe diarrhoea in children younger than 5 years in Africa and Asia. We used quantitative real-time PCR (qPCR) to test for 32 enteropathogens in stool samples from cases and matched asymptomatic controls from GEMS, and compared pathogen-specific attributable incidences with those found with the original GEMS microbiological methods, including culture, EIA, and reverse-transcriptase PCR. We calculated revised pathogen-specific burdens of disease and assessed causes in individual children. We analysed 5304 sample pairs. For most pathogens, incidence was greater with qPCR than with the original methods, particularly for adenovirus 40/41 (around five times), Shigella spp or enteroinvasive Escherichia coli (EIEC) and Campylobactor jejuni o C coli (around two times), and heat-stable enterotoxin-producing E coli ([ST-ETEC] around 1·5 times). The six most attributable pathogens became, in descending order, Shigella spp, rotavirus, adenovirus 40/41, ST-ETEC, Cryptosporidium spp, and Campylobacter spp. Pathogen-attributable diarrhoeal burden was 89·3% (95% CI 83·2–96·0) at the population level, compared with 51·5% (48·0–55·0) in the original GEMS analysis. The top six pathogens accounted for 77·8% (74·6–80·9) of all attributable diarrhoea. With use of model-derived quantitative cutoffs to assess individual diarrhoeal cases, 2254 (42·5%) of 5304 cases had one diarrhoea-associated pathogen detected and 2063 (38·9%) had two or more, with Shigella spp and rotavirus being the pathogens most strongly associated with diarrhoea in children with mixed infections. A quantitative molecular diagnostic approach improved population-level and case-level characterisation of the causes of diarrhoea and indicated a high burden of disease associated with six pathogens, for which targeted treatment should be prioritised. Bill & Melinda Gates Foundation.

Despite increased understanding of how viral infection is involved in asthma exacerbations, it is less clear which viruses are involved and to what extent they contribute to asthma exacerbations. Here, we sought to determine the prevalence of different respiratory viruses during asthma exacerbations. Systematic computerized searches of the literature up to June 2017 without language limitation were performed. The primary focus was on the prevalence of respiratory viruses, including AdV (adenovirus), BoV (bocavirus), CoV (coronavirus), CMV (cytomegalovirus), EnV (enterovirus), HSV (herpes simplex virus), IfV (influenza virus), MpV (metapneumovirus), PiV (parainfluenzavirus), RV (rhinovirus) and RSV (respiratory syncytial virus) during asthma exacerbations. We also examined the prevalence of viral infection stratified by age, geographic region, type of respiratory secretion, and detection method. Sixty articles were included in the final analysis. During asthma exacerbations, the mean prevalence of AdV, BoV, CoV, CMV, EnV, HSV, IfV, MpV, PiV, RV and RSV was 3.8%, 6.9%, 8.4%, 7.2%, 10.1%, 12.3%, 10.0%, 5.3%, 5.6%, 42.1% and 13.6%, respectively. EnV, MPV, RV and RSV were more prevalent in children, whereas AdV, BoV, CoV, IfV and PiV were more frequently present in adults. RV was the major virus detected globally, except in Africa. RV could be detected in both the upper and lower airway. Polymerase chain reaction was the most sensitive method for detecting viral infection. Our findings indicate the need to develop prophylactic polyvalent or polyvirus (including RV, EnV, IfV and RSV) vaccines that produce herd immunity and reduce the healthcare burden associated with virus-induced asthma exacerbations.

\"The real story of AIDS--how it originated with a virus in a chimpanzee, jumped to one human, and then infected more than 60 million people--is very different from what most of us think we know. Recent research has revealed dark surprises and yielded a radically new scenario of how AIDS began and spread. Excerpted and adapted from the book Spillover, with a new introduction by the author, Quammen's ... investigation tracks the virus from chimp populations in the jungles of southeastern Cameroon to laboratories across the globe, as he unravels the mysteries of when, where, and under what circumstances such a consequential 'spillover' can happen\"--Page 4 of cover.

The source, timing, and geographical origin of the 1918–1920 pandemic influenza A virus have remained tenaciously obscure for nearly a century, as have the reasons for its unusual severity among young adults. Here, we reconstruct the origins of the pandemic virus and the classic swine influenza and (postpandemic) seasonal H1N1 lineages using a host-specific molecular clock approach that is demonstrably more accurate than previous methods. Our results suggest that the 1918 pandemic virus originated shortly before 1918 when a human H1 virus, which we infer emerged before ∼1907, acquired avian N1 neuraminidase and internal protein genes. We find that the resulting pandemic virus jumped directly to swine but was likely displaced in humans by ∼1922 by a reassortant with an antigenically distinct H1 HA. Hence, although the swine lineage was a direct descendent of the pandemic virus, the post-1918 seasonal H1N1 lineage evidently was not, at least for HA. These findings help resolve several seemingly disparate observations from 20th century influenza epidemiology, seroarcheology, and immunology. The phylogenetic results, combined with these other lines of evidence, suggest that the high mortality in 1918 among adults aged ∼20 to ∼40 y may have been due primarily to their childhood exposure to a doubly heterosubtypic putative H3N8 virus, which we estimate circulated from ∼1889–1900. All other age groups (except immunologically naive infants) were likely partially protected by childhood exposure to N1 and/or H1-related antigens. Similar processes may underlie age-specific mortality differences between seasonal H1N1 vs. H3N2 and human H5N1 vs. H7N9 infections.

Key Points This Review focuses on the mechanisms and clinical importance of the bacterial–fungal interactions that occur on or in the human body. Bacteria and fungi can interact in several ways, including physical interactions by direct cell–cell contact, chemical interaction through the secretion of small molecules that are often involved in quorum sensing, environmental modifications such as pH changes, use of metabolic by-products and alterations in host responses. A range of mammalian and non-mammalian models of infection are now available for the study of mixed bacterial–fungal infections. Several Gram-negative pathogens are capable of killing Candida albicans and inhibiting filament formation, including Pseudomonas aeruginosa , Acinetobacter baumannii , Burkholderia cepacia and Salmonella enterica subsp. enterica serovar Typhimurium. This is predominantly mediated through the secretion of small molecules, such as quorum-sensing molecules and other known secretory virulence factors (namely, phospholipase C and phenazines for P. aeruginosa ). Oral streptococci have adapted to adhere to C. albicans in the human mouth, and this seems to be mediated through polysaccharide receptors on the bacterial surface. Such co-aggregation is important in the pathogenesis of many oral diseases. C. albicans mounts a defence against these bacterial predators through the secretion of its quorum-sensing molecule farnesol. This molecule can affect bacterial production of virulence factors, viability and susceptibility to antibacterials. Limited study has been dedicated to understanding the host responses to polymicrobial infections. Recent work in mice suggests that immune responses to a bacterial–fungal infection may be directed preferentially towards a bacterial-type response mediated by T helper 1 cells. The human body plays host to interactions between a diverse range of microorganisms, including bacteria and fungi. In this Review, Mylonakis and colleagues describe the characteristics of medically important bacterial–fungal interactions and highlight how imbalances in these interactions can contribute to human disease. Whether it is in the setting of disease or in a healthy state, the human body contains a diverse range of microorganisms, including bacteria and fungi. The interactions between these taxonomically diverse microorganisms are highly dynamic and dependent on a multitude of microorganism and host factors. Human disease can develop from an imbalance between commensal bacteria and fungi or from invasion of particular host niches by opportunistic bacterial and fungal pathogens. This Review describes the clinical and molecular characteristics of bacterial–fungal interactions that are relevant to human disease.

Worldwide, ticks are important vectors of human and animal pathogens. Besides Lyme Borreliosis, a variety of other bacterial and protozoal tick-borne infections are of medical interest in Europe. In this study, 553 questing and feeding Ixodes ricinus (n = 327) and Dermacentor reticulatus ticks (n = 226) were analysed by PCR for Borrelia, Rickettsia, Anaplasma, Coxiella, Francisella and Babesia species. Overall, the pathogen prevalence in ticks was 30.6% for I. ricinus and 45.6% for D. reticulatus. The majority of infections were caused by members of the spotted-fever group rickettsiae (24.4%), 9.4% of ticks were positive for Borrelia burgdorferi sensu lato, with Borrelia afzelii being the most frequently detected species (40.4%). Pathogens with low prevalence rates in ticks were Anaplasma phagocytophilum (2.2%), Coxiella burnetii (0.9%), Francisella tularensis subspecies (0.7%), Bartonella henselae (0.7%), Babesia microti (0.5%) and Babesia venatorum (0.4%). On a regional level, hotspots of pathogens were identified for A. phagocytophilum (12.5-17.2%), F. tularensis ssp. (5.5%) and C. burnetii (9.1%), suggesting established zoonotic cycles of these pathogens at least at these sites. Our survey revealed a high burden of tick-borne pathogens in questing and feeding I. ricinus and D. reticulatus ticks collected in different regions in Belarus, indicating a potential risk for humans and animals. Identified hotspots of infected ticks should be included in future surveillance studies, especially when F. tularensis ssp. and C. burnetii are involved.

Pneumonia may be caused by a wide range of pathogens and is considered the most common infectious cause of death in humans. Murine acute lung infection models mirror human pathologies in many aspects and contribute to our understanding of the disease and the development of novel treatment strategies. Despite progress in other fields of tissue imaging, histopathology remains the most conclusive and practical read out tool for the descriptive and semiquantitative evaluation of mouse pneumonia and therapeutic interventions. Here, we systematically describe and compare the distinctive histopathological features of established models of acute pneumonia in mice induced by Streptococcus (S.) pneumoniae, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Legionella pneumophila, Escherichia coli, Middle East respiratory syndrome (MERS) coronavirus, influenza A virus (IAV) and superinfection of IAV-incuced pneumonia with S. pneumoniae. Systematic comparisons of the models revealed striking differences in the distribution of lesions, the characteristics of pneumonia induced, principal inflammatory cell types, lesions in adjacent tissues, and the detectability of the pathogens in histological sections. We therefore identified core criteria for each model suitable for practical semiquantitative scoring systems that take into account the pathogen- and model-specific patterns of pneumonia. Other critical factors that affect experimental pathologies are discussed, including infectious dose, time kinetics, and the genetic background of the mouse strain. The substantial differences between the model-specific pathologies underscore the necessity of pathogen- and model-adapted criteria for the comparative quantification of experimental outcomes. These criteria also allow for the standardized validation and comparison of treatment strategies in preclinical models.

Many pathogens are transmitted by tick bites, including Anaplasma spp., Ehrlichia spp., Rickettsia spp., Babesia and Theileria sensu stricto species. These pathogens cause infectious diseases both in animals and humans. Different types of immune effector mechanisms could be induced in hosts by these microorganisms, triggered either directly by pathogen-derived antigens or indirectly by molecules released by host cells binding to these antigens. The components of innate immunity, such as natural killer cells, complement proteins, macrophages, dendritic cells and tumor necrosis factor alpha, cause a rapid and intense protection for the acute phase of infectious diseases. Moreover, the onset of a pro-inflammatory state occurs upon the activation of the inflammasome, a protein scaffold with a key-role in host defense mechanism, regulating the action of caspase-1 and the maturation of interleukin-1β and IL-18 into bioactive molecules. During the infection caused by different microbial agents, very similar profiles of the human innate immune response are observed including secretion of IL-1α, IL-8, and IFN-α, and suppression of superoxide dismutase, IL-1Ra and IL-17A release. Innate immunity is activated immediately after the infection and inflammasome-mediated changes in the pro-inflammatory cytokines at systemic and intracellular levels can be detected as early as on days 2–5 after tick bite. The ongoing research field of “inflammasome biology” focuses on the interactions among molecules and cells of innate immune response that could be responsible for triggering a protective adaptive immunity. The knowledge of the innate immunity mechanisms, as well as the new targets of investigation arising by bioinformatics analysis, could lead to the development of new methods of emergency diagnosis and prevention of tick-borne infections.