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Lassa fever is a viral haemorrhagic disease endemic to west Africa. No large-scale studies exist from Nigeria, where the Lassa virus (LASV) is most diverse. LASV diversity, coupled with host genetic and environmental factors, might cause differences in disease pathophysiology. Small-scale studies in Nigeria suggest that acute kidney injury is an important clinical feature and might be a determinant of survival. We aimed to establish the demographic, clinical, and laboratory factors associated with mortality in Nigerian patients with Lassa fever, and hypothesised that LASV was the direct cause of intrinsic renal damage for a subset of the patients with Lassa fever. We did a retrospective, observational cohort study of consecutive patients in Nigeria with Lassa fever, who tested positive for LASV with RT-PCR, and were treated in Irrua Specialist Teaching Hospital. We did univariate and multivariate statistical analyses, including logistic regression, of all demographic, clinical, and laboratory variables available at presentation to identify the factors associated with patient mortality. Of 291 patients treated in Irrua Specialist Teaching Hospital between Jan 3, 2011, and Dec 11, 2015, 284 (98%) had known outcomes (died or survived) and seven (2%) were discharged against medical advice. Overall case-fatality rate was 24% (68 of 284 patients), with a 1·4 times increase in mortality risk for each 10 years of age (p=0·00017), reaching 39% (22 of 57) for patients older than 50 years. Of 284 patients, 81 (28%) had acute kidney injury and 104 (37%) had CNS manifestations and thus both were considered important complications of acute Lassa fever in Nigeria. Acute kidney injury was strongly associated with poor outcome (case-fatality rate of 60% [49 of 81 patients]; odds ratio [OR] 15, p<0·00001). Compared with patients without acute kidney injury, those with acute kidney injury had higher incidence of proteinuria (32 [82%] of 39 patients) and haematuria (29 [76%] of 38) and higher mean serum potassium (4·63 [SD 1·04] mmol/L) and lower blood urea nitrogen to creatinine ratio (8·6 for patients without clinical history of fluid loss), suggesting intrinsic renal damage. Normalisation of creatinine concentration was associated with recovery. Elevated serum creatinine (OR 1·3; p=0·046), aspartate aminotransferase (OR 1·5; p=0·075), and potassium (OR 3·6; p=0·0024) were independent predictors of death. Our study presents detailed clinical and laboratory data for Nigerian patients with Lassa fever and provides strong evidence for intrinsic renal dysfunction in acute Lassa fever. Early recognition and treatment of acute kidney injury might significantly reduce mortality. German Research Foundation, German Center for Infection Research, Howard Hughes Medical Institute, US National Institutes of Health, and World Bank.

\"Discover 5 facts a day, 5 days a week with this exciting science book for children aged 8-12. With five facts a day, every day of the year, that's more than 1,825 nuggets of knowledge! From rocks to robots, and cells to solar systems, this eye-opening book covers more than 250 different science topics in an easy-to-read, entertaining, and bite-sized way to build on your knowledge as you go. Enjoy learning something new every day or just dip in and out for fun\"-- Provided by publisher.

Assessment of the response to the 2014-15 Ebola outbreak indicates the need for innovations in data collection, sharing, and use to improve case detection and treatment. Here we introduce a Machine Learning pipeline for Ebola Virus Disease (EVD) prognosis prediction, which packages the best models into a mobile app to be available in clinical care settings. The pipeline was trained on a public EVD clinical dataset, from 106 patients in Sierra Leone. We used a new tool for exploratory analysis, Mirador, to identify the most informative clinical factors that correlate with EVD outcome. The small sample size and high prevalence of missing records were significant challenges. We applied multiple imputation and bootstrap sampling to address missing data and quantify overfitting. We trained several predictors over all combinations of covariates, which resulted in an ensemble of predictors, with and without viral load information, with an area under the receiver operator characteristic curve of 0.8 or more, after correcting for optimistic bias. We ranked the predictors by their F1-score, and those above a set threshold were compiled into a mobile app, Ebola CARE (Computational Assignment of Risk Estimates). This method demonstrates how to address small sample sizes and missing data, while creating predictive models that can be readily deployed to assist treatment in future outbreaks of EVD and other infectious diseases. By generating an ensemble of predictors instead of relying on a single model, we are able to handle situations where patient data is partially available. The prognosis app can be updated as new data become available, and we made all the computational protocols fully documented and open-sourced to encourage timely data sharing, independent validation, and development of better prediction models in outbreak response.

Although the Human Genome Project was completed 4 years ago, the catalog of human protein-coding genes remains a matter of controversy. Current catalogs list a total of [almost equal to]24,500 putative protein-coding genes. It is broadly suspected that a large fraction of these entries are functionally meaningless ORFs present by chance in RNA transcripts, because they show no evidence of evolutionary conservation with mouse or dog. However, there is currently no scientific justification for excluding ORFs simply because they fail to show evolutionary conservation: the alternative hypothesis is that most of these ORFs are actually valid human genes that reflect gene innovation in the primate lineage or gene loss in the other lineages. Here, we reject this hypothesis by carefully analyzing the nonconserved ORFs--specifically, their properties in other primates. We show that the vast majority of these ORFs are random occurrences. The analysis yields, as a by-product, a major revision of the current human catalogs, cutting the number of protein-coding genes to [almost equal to]20,500. Specifically, it suggests that nonconserved ORFs should be added to the human gene catalog only if there is clear evidence of an encoded protein. It also provides a principled methodology for evaluating future proposed additions to the human gene catalog. Finally, the results indicate that there has been relatively little true innovation in mammalian protein-coding genes.

Background People living in rural and remote communities in Canada are often disproportionately impacted by opioid use disorder. When compared to urban centres, rural and remote populations face additional barriers to treatment, including geographical distance as well as chronic shortages of health care professionals. This integrative review of the literature was conducted to explore the facilitators and barriers of OAT in rural and remote Canadian communities. Methods A search of the literature identified relevant studies published between 2001 and 2021. Results The search strategy yielded 26 scholarly peer-reviewed publications, which explored specific barriers and facilitators to rural and remote OAT in Canada, along with two reports and one fact sheet from the grey literature. Most of the scholarly articles were descriptive studies ( n  = 14) or commentaries ( n  = 9); there were only three intervention studies. Facilitators and barriers to OAT programs were organized into six themes: intrapersonal/patient factors, social/non-medical program factors, family/social context factors (including community factors), infrastructure/environmental factors, health care provider factors, and system/policy factors. Conclusions Although themes in the literature resembled the social-ecological framework, most of the studies focused on the patient-provider dyad. Two of the most compelling studies focused on community factors that positively impacted OAT success and highlighted a holistic approach to care, nested in a community-based holistic model. Further research is required to foster OAT programs in rural and remote communities.

Amid COVID-19, many institutions deployed vast resources to test their members regularly for safe reopening. This self-focused approach, however, not only overlooks surrounding communities but also remains blind to community transmission that could breach the institution. To test the relative merits of a more altruistic strategy, we built an epidemiological model that assesses the differential impact on case counts when institutions instead allocate a proportion of their tests to members’ close contacts in the larger community. We found that testing outside the institution benefits the institution in all plausible circumstances, with the optimal proportion of tests to use externally landing at 45% under baseline model parameters. Our results were robust to local prevalence, secondary attack rate, testing capacity, and contact reporting level, yielding a range of optimal community testing proportions from 18 to 58%. The model performed best under the assumption that community contacts are known to the institution; however, it still demonstrated a significant benefit even without complete knowledge of the contact network.

While investigating a signal of adaptive evolution in humans at the gene LARGE, we encountered an intriguing finding by Dr. Stefan Kunz that the gene plays a critical role in Lassa virus binding and entry. This led us to pursue field work to test our hypothesis that natural selection acting on LARGE—detected in the Yoruba population of Nigeria—conferred resistance to Lassa Fever in some West African populations. As we delved further, we conjectured that the “emerging” nature of recently discovered diseases like Lassa fever is related to a newfound capacity for detection, rather than a novel viral presence, and that humans have in fact been exposed to the viruses that cause such diseases for much longer than previously suspected. Dr. Stefan Kunz’s critical efforts not only laid the groundwork for this discovery, but also inspired and catalyzed a series of events that birthed Sentinel, an ambitious and large-scale pandemic prevention effort in West Africa. Sentinel aims to detect and characterize deadly pathogens before they spread across the globe, through implementation of its three fundamental pillars: Detect, Connect, and Empower. More specifically, Sentinel is designed to detect known and novel infections rapidly, connect and share information in real time to identify emerging threats, and empower the public health community to improve pandemic preparedness and response anywhere in the world. We are proud to dedicate this work to Stefan Kunz, and eagerly invite new collaborators, experts, and others to join us in our efforts.

The C-C chemokine receptor 5, 32 base-pair deletion (CCR5-Delta32) allele confers strong resistance to infection by the AIDS virus HIV. Previous studies have suggested that CCR5-Delta32 arose within the past 1,000 y and rose to its present high frequency (5%-14%) in Europe as a result of strong positive selection, perhaps by such selective agents as the bubonic plague or smallpox during the Middle Ages. This hypothesis was based on several lines of evidence, including the absence of the allele outside of Europe and long-range linkage disequilibrium at the locus. We reevaluated this evidence with the benefit of much denser genetic maps and extensive control data. We find that the pattern of genetic variation at CCR5-Delta32 does not stand out as exceptional relative to other loci across the genome. Moreover using newer genetic maps, we estimated that the CCR5-Delta32 allele is likely to have arisen more than 5,000 y ago. While such results can not rule out the possibility that some selection may have occurred at C-C chemokine receptor 5 (CCR5), they imply that the pattern of genetic variation seen at CCR5-Delta32 is consistent with neutral evolution. More broadly, the results have general implications for the design of future studies to detect the signs of positive selection in the human genome.