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Emergence and clonal expansion of in vitro artemisinin-resistantPlasmodium falciparum kelch13R561H mutant parasites in Rwanda
Artemisinin resistance (delayedP. falciparumclearance following artemisinin-based combination therapy), is widespread across Southeast Asia but to date has not been reported in Africa(1-4). Here we genotyped theP. falciparum K13(Pfkelch13) propeller domain, mutations in which can mediate artemisinin resistance(5,6), in pretreatment samples collected from recent dihydroarteminisin-piperaquine and artemether-lumefantrine efficacy trials in Rwanda(7). While cure rates were >95% in both treatment arms, thePfkelch13R561H mutation was identified in 19 of 257 (7.4%) patients at Masaka. Phylogenetic analysis revealed the expansion of an indigenous R561H lineage. Gene editing confirmed that this mutation can drive artemisinin resistance in vitro. This study provides evidence for the de novo emergence ofPfkelch13-mediated artemisinin resistance in Rwanda, potentially compromising the continued success of antimalarial chemotherapy in Africa. Identification in Rwanda of mutations inPlasmodium falciparumcapable of conferring in vitro resistance to artemisinin, an essential medicine for the treatment of malaria, underscore the crucial need for surveillance in Africa to safeguard efficacy of life-saving therapies.
Journal Article
Stepping in the same river twice : replication in biological research
An international team of biologists, philosophers, and historians of science explores the critically important process of replication in biological and biomedical research. Without replication, the trustworthiness of scientific research remains in doubt. Although replication is increasingly recognized as a central problem in many scientific disciplines, repeating the same scientific observations of experiments or reproducing the same set of analyses from existing data is remarkably difficult. In this important volume, an international team of biologists, philosophers, and historians of science addresses challenges and solutions for valid replication of research in medicine, ecology, natural history, agriculture, physiology, and computer science. After the introduction to important concepts and historical background, the book offers paired chapters that provide theoretical overviews followed by detailed case studies. These studies range widely in topics, from infectious-diseases and environmental monitoring to museum collections, meta-analysis, bioinformatics, and more. The closing chapters explicate and quantify problems in the case studies, and the volume concludes with important recommendations for best practices. -- Provided by publisher.
Book
Plasma p-tau231 and p-tau217 as state markers of amyloid-β pathology in preclinical Alzheimer’s disease
Blood biomarkers indicating elevated amyloid-β (Aβ) pathology in preclinical Alzheimer’s disease are needed to facilitate the initial screening process of participants in disease-modifying trials. Previous biofluid data suggest that phosphorylated tau231 (p-tau231) could indicate incipient Aβ pathology, but a comprehensive comparison with other putative blood biomarkers is lacking. In the ALFA+ cohort, all tested plasma biomarkers (p-tau181, p-tau217, p-tau231, GFAP, NfL and Aβ42/40) were significantly changed in preclinical Alzheimer’s disease. However, plasma p-tau231 reached abnormal levels with the lowest Aβ burden. Plasma p-tau231 and p-tau217 had the strongest association with Aβ positron emission tomography (PET) retention in early accumulating regions and associated with longitudinal increases in Aβ PET uptake in individuals without overt Aβ pathology at baseline. In summary, plasma p-tau231 and p-tau217 better capture the earliest cerebral Aβ changes, before overt Aβ plaque pathology is present, and are promising blood biomarkers to enrich a preclinical population for Alzheimer’s disease clinical trials.
A comprehensive comparison of Alzheimer’s disease blood biomarkers in cognitively unimpaired individuals reveals that plasma p-tau231 and p-tau217 capture very early Aβ changes, showing promise as markers to enrich a preclinical population for Alzheimer’s disease clinical trials
Journal Article
Human–computer collaboration for skin cancer recognition
The rapid increase in telemedicine coupled with recent advances in diagnostic artificial intelligence (AI) create the imperative to consider the opportunities and risks of inserting AI-based support into new paradigms of care. Here we build on recent achievements in the accuracy of image-based AI for skin cancer diagnosis to address the effects of varied representations of AI-based support across different levels of clinical expertise and multiple clinical workflows. We find that good quality AI-based support of clinical decision-making improves diagnostic accuracy over that of either AI or physicians alone, and that the least experienced clinicians gain the most from AI-based support. We further find that AI-based multiclass probabilities outperformed content-based image retrieval (CBIR) representations of AI in the mobile technology environment, and AI-based support had utility in simulations of second opinions and of telemedicine triage. In addition to demonstrating the potential benefits associated with good quality AI in the hands of non-expert clinicians, we find that faulty AI can mislead the entire spectrum of clinicians, including experts. Lastly, we show that insights derived from AI class-activation maps can inform improvements in human diagnosis. Together, our approach and findings offer a framework for future studies across the spectrum of image-based diagnostics to improve human–computer collaboration in clinical practice.
A systematic evaluation of the value of AI-based decision support in skin tumor diagnosis demonstrates the superiority of human–computer collaboration over each individual approach and supports the potential of automated approaches in diagnostic medicine.
Journal Article
Multidisciplinary research on teaching and learning
\"Educational research encompasses different scientific cultures with different tools, practices, views, and languages, which frequently makes communication difficult. This collection indicates how research on teaching and learning from multiple scientific disciplines such as educational science, psychology, and various domain-specific instructional sciences can be successfully pursued by a co-operation between researchers and experienced school teachers. Each chapter aims at process-oriented rather than only outcome-oriented research. The contributors promote analyses from multiple perspectives and adopt different methodological approaches, ranging from field research to laboratory experiments. \"-- Provided by publisher.
Book
Plasma P-tau181 in Alzheimer’s disease: relationship to other biomarkers, differential diagnosis, neuropathology and longitudinal progression to Alzheimer’s dementia
Plasma phosphorylated tau181 (P-tau181) might be increased in Alzheimer’s disease (AD), but its usefulness for differential diagnosis and prognosis is unclear. We studied plasma P-tau181 in three cohorts, with a total of 589 individuals, including cognitively unimpaired participants and patients with mild cognitive impairment (MCI), AD dementia and non-AD neurodegenerative diseases. Plasma P-tau181 was increased in preclinical AD and further increased at the MCI and dementia stages. It correlated with CSF P-tau181 and predicted positive Tau positron emission tomography (PET) scans (area under the curve (AUC) = 0.87–0.91 for different brain regions). Plasma P-tau181 differentiated AD dementia from non-AD neurodegenerative diseases with an accuracy similar to that of Tau PET and CSF P-tau181 (AUC = 0.94–0.98), and detected AD neuropathology in an autopsy-confirmed cohort. High plasma P-tau181 was associated with subsequent development of AD dementia in cognitively unimpaired and MCI subjects. In conclusion, plasma P-tau181 is a noninvasive diagnostic and prognostic biomarker of AD, which may be useful in clinical practice and trials.
Plasma P-tau18 level increased with progression of Alzheimer’s disease (AD) and differentiated AD dementia from other neurodegenerative diseases, supporting its further development as a blood-based biomarker for AD.
Journal Article
Microbiome and metabolome features of the cardiometabolic disease spectrum
Previous microbiome and metabolome analyses exploring non-communicable diseases have paid scant attention to major confounders of study outcomes, such as common, pre-morbid and co-morbid conditions, or polypharmacy. Here, in the context of ischemic heart disease (IHD), we used a study design that recapitulates disease initiation, escalation and response to treatment over time, mirroring a longitudinal study that would otherwise be difficult to perform given the protracted nature of IHD pathogenesis. We recruited 1,241 middle-aged Europeans, including healthy individuals, individuals with dysmetabolic morbidities (obesity and type 2 diabetes) but lacking overt IHD diagnosis and individuals with IHD at three distinct clinical stages—acute coronary syndrome, chronic IHD and IHD with heart failure—and characterized their phenome, gut metagenome and serum and urine metabolome. We found that about 75% of microbiome and metabolome features that distinguish individuals with IHD from healthy individuals after adjustment for effects of medication and lifestyle are present in individuals exhibiting dysmetabolism, suggesting that major alterations of the gut microbiome and metabolome might begin long before clinical onset of IHD. We further categorized microbiome and metabolome signatures related to prodromal dysmetabolism, specific to IHD in general or to each of its three subtypes or related to escalation or de-escalation of IHD. Discriminant analysis based on specific IHD microbiome and metabolome features could better differentiate individuals with IHD from healthy individuals or metabolically matched individuals as compared to the conventional risk markers, pointing to a pathophysiological relevance of these features.
By studying individuals along a spectrum of cardiometabolic disease and adjusting for effects of lifestyle and medication, this investigation identifies alterations of the metabolome and microbiome from dysmetabolic conditions, such as obesity and type 2 diabetes, to ischemic heart disease.
Journal Article