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"Fowler, J. E. (James E.)"
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New essays on Diderot
\"The great eighteenth-century French thinker Denis Diderot (1713-1784) once compared himself to a weathervane, by which he meant that his mind was in constant motion. In an extraordinarily diverse career he produced novels, plays, art criticism, works of philosophy and poetics, and also reflected on music and opera. Perhaps most famously, he ensured the publication of the Encyclopâedie, which has often been credited with hastening the onset of the French Revolution. Known as one of the three greatest philosophes of the Enlightenment, Diderot rejected the Christian ideas in which he had been raised. Instead, he became an atheist and a determinist. His radical questioning of received ideas and established religion led to a brief imprisonment, and for that reason, no doubt, some of his subsequent works were written for posterity. This collection of essays celebrates the life and work of this extraordinary figure as we approach the tercentenary of his birth\"-- Provided by publisher.
Book
Prediction of Susceptibility to First-Line Tuberculosis Drugs by DNA Sequencing
Proper treatment of tuberculosis requires a combination of drugs to which the causative organism is susceptible. In this report, genotypic assessment of antimicrobial susceptibility of more than 10,000
M. tuberculosis
isolates was correlated with phenotypic test results.
Journal Article
Digital detection of dementia (D3): a study protocol for a pragmatic cluster-randomized trial examining the application of patient-reported outcomes and passive clinical decision support systems
Background
Early detection of Alzheimer’s disease and related dementias (ADRD) in a primary care setting is challenging due to time constraints and stigma. The implementation of scalable, sustainable, and patient-driven processes may improve early detection of ADRD; however, there are competing approaches; information may be obtained either directly from a patient (e.g., through a questionnaire) or passively using electronic health record (EHR) data. In this study, we aim to identify the benefit of a combined approach using a pragmatic cluster-randomized clinical trial.
Methods
We have developed a Passive Digital Marker (PDM), based on machine learning algorithms applied to EHR data, and paired it with a patient-reported outcome (the Quick Dementia Rating Scale or QDRS) to rapidly share an identified risk of impairment to a patient’s physician. Clinics in both south Florida and Indiana will be randomly assigned to one of three study arms: 1200 patients in each of the two populations will be administered either the PDM, the PDM with the QDRS, or neither, for a total of 7200 patients across all clinics and populations. Both incidence of ADRD diagnosis and acceptance into ADRD diagnostic work-up regimens is hypothesized to increase when patients are administered both the PDM and QDRS. Physicians performing the work-up regimens will be blind to the study arm of the patient.
Discussion
This study aims to test the accuracy and effectiveness of the two scalable approaches (PDM and QDRS) for the early detection of ADRD among older adults attending primary care practices. The data obtained in this study may lead to national early detection and management program for ADRD as an efficient and beneficial method of reducing the current and future burden of ADRD, as well as improving the annual rate of newly documented ADRD in primary care practices.
Trial registration
ClinicalTrials.gov Identifier:
NCT05231954
. Registered February 9, 2022.
Journal Article
Multicriteria decisions and portfolio analysis
Resource allocation for land acquisition is a common multiobjective problem that involves complex trade-offs. The National Wildlife Refuge System (NWRS) of the U.S. Fish and Wildlife Service currently uses the Targeted Resource Acquisition Comparison Tool (TRACT) to allocate funds from the Migratory Bird Conservation Fund (MBCF; established through the Migratory Bird Hunting and Conservation Act of 1934) for land acquisition based on cost–benefit analysis, regional priority rankings of candidate land parcels available for acquisition, and the overall biological contribution to duck population objectives. However, current policy encourages decision makers to consider societal and economic benefits of lands acquired, in addition to their biological benefits to waterfowl. These decisions about portfolio elements (i.e., individual land parcels) require an analysis of the difficult trade-offs among multiple objectives. In the last decade the application of multicriteria decision analysis (MCDA) methods has been instrumental in aiding decision makers with complex multiobjective decisions. In this study, we present an alternative approach to developing land-acquisition portfolios using MCDA and modern portfolio theory (MPT). We describe the development of a portfolio decision analysis tool using constrained optimization for land-acquisition decisions by the NWRS. We outline the decision framework, describe development of the prototype tool in Microsoft Excel, and test the results of the tool using land parcels submitted as candidates for MBCF funding in 2019. Our results indicate that the constrained optimization outperformed the traditional TRACT method and ad hoc portfolios developed using current NWRS criteria.
Journal Article
Prediction of pyrazinamide resistance in Mycobacterium tuberculosis using structure-based machine-learning approaches
Abstract
Background
Pyrazinamide is one of four first-line antibiotics used to treat tuberculosis; however, antibiotic susceptibility testing for pyrazinamide is challenging. Resistance to pyrazinamide is primarily driven by genetic variation in pncA, encoding an enzyme that converts pyrazinamide into its active form.
Methods
We curated a dataset of 664 non-redundant, missense amino acid mutations in PncA with associated high-confidence phenotypes from published studies and then trained three different machine-learning models to predict pyrazinamide resistance. All models had access to a range of protein structural-, chemical- and sequence-based features.
Results
The best model, a gradient-boosted decision tree, achieved a sensitivity of 80.2% and a specificity of 76.9% on the hold-out test dataset. The clinical performance of the models was then estimated by predicting the binary pyrazinamide resistance phenotype of 4027 samples harbouring 367 unique missense mutations in pncA derived from 24 231 clinical isolates.
Conclusions
This work demonstrates how machine learning can enhance the sensitivity/specificity of pyrazinamide resistance prediction in genetics-based clinical microbiology workflows, highlights novel mutations for future biochemical investigation, and is a proof of concept for using this approach in other drugs.
Journal Article
Information technology measurement and testing activities at NIST
Our high technology society continues to rely more and more upon sophisticated measurements, technical standards, and associated testing activities. This was true for the industrial society of the 20th century and remains true for the information society of the 21st century. Over the last half of the 20th century, information technology (IT) has been a powerful agent of change in almost every sector of the economy. The complexity and rapidly changing nature of IT have presented unique technical challenges to the National Institute of Standards and Technology (NIST) and to the scientific measurement community in developing a sound measurement and testing infrastructure for IT. This measurement and testing infrastructure for the important non-physical and non-chemical properties associated with complex IT systems is still in an early stage of development. This paper explains key terms and concepts of IT metrology, briefly reviews the history of the National Bureau of Standards/National Institute of Standards and Technology (NBS/NIST) in the field of IT, and reviews NIST's current capabilities and work in measurement and testing for IT. It concludes with a look at what is likely to occur in the field of IT over the next ten years and what metrology roles NIST is likely to play.
Journal Article
Using social and behavioural science to support COVID-19 pandemic response
The COVID-19 pandemic represents a massive global health crisis. Because the crisis requires large-scale behaviour change and places significant psychological burdens on individuals, insights from the social and behavioural sciences can be used to help align human behaviour with the recommendations of epidemiologists and public health experts. Here we discuss evidence from a selection of research topics relevant to pandemics, including work on navigating threats, social and cultural influences on behaviour, science communication, moral decision-making, leadership, and stress and coping. In each section, we note the nature and quality of prior research, including uncertainty and unsettled issues. We identify several insights for effective response to the COVID-19 pandemic and highlight important gaps researchers should move quickly to fill in the coming weeks and months.
Forty-three experts highlight some key insights from the social and behavioural sciences for effective response to the COVID-19 pandemic and point out important gaps researchers should move quickly to fill in the coming weeks and months.
Journal Article
Inferring Tie Strength from Online Directed Behavior
Some social connections are stronger than others. People have not only friends, but also best friends. Social scientists have long recognized this characteristic of social connections and researchers frequently use the term tie strength to refer to this concept. We used online interaction data (specifically, Facebook interactions) to successfully identify real-world strong ties. Ground truth was established by asking users themselves to name their closest friends in real life. We found the frequency of online interaction was diagnostic of strong ties, and interaction frequency was much more useful diagnostically than were attributes of the user or the user's friends. More private communications (messages) were not necessarily more informative than public communications (comments, wall posts, and other interactions).
Journal Article
Astrocyte-oligodendrocyte interaction regulates central nervous system regeneration
Failed regeneration of myelin around neuronal axons following central nervous system damage contributes to nerve dysfunction and clinical decline in various neurological conditions, for which there is an unmet therapeutic demand. Here, we show that interaction between glial cells – astrocytes and mature myelin-forming oligodendrocytes – is a determinant of remyelination. Using in vivo/ ex vivo/ in vitro rodent models, unbiased RNA sequencing, functional manipulation, and human brain lesion analyses, we discover that astrocytes support the survival of regenerating oligodendrocytes, via downregulation of the Nrf2 pathway associated with increased astrocytic cholesterol biosynthesis pathway activation. Remyelination fails following sustained astrocytic Nrf2 activation in focally-lesioned male mice yet is restored by either cholesterol biosynthesis/efflux stimulation, or Nrf2 inhibition using the existing therapeutic Luteolin. We identify that astrocyte-oligodendrocyte interaction regulates remyelination, and reveal a drug strategy for central nervous system regeneration centred on targeting this interaction.
The mechanisms regulating central nervous system remyelination efficiency are poorly understood. Here, the authors show that remyelination is driven by astrocytes supporting oligodendrocyte survival, regulated by the Nrf2 and cholesterol pathways.
Journal Article
Critical assessment of Thalassia testudinum (turtle grass) aging techniques: implications for demographic inferences
Variability in the time interval between the formation of successive leaves (i.e. the plastochron) directly influences estimates of seagrass shoot age. Age-frequency distributions were constructed for Thalassia testudinum short shoots from a shallow and a deep site in the Lower Laguna Madre, Texas, during the summers of 1995 and 1996. In each year the ages of 200 to 250 shoots, collected by coring, were estimated from leaf scars and annual leaf production rates. Two years of monthly leaf production measurements were used to calculate annual leaf production. The leaf production rate was site-specific: plants at the shallow site produced about 13 leaves yr–1 while plants from the deep site produced about 10 leaves yr–1; the 95% confidence limits around the mean were ±20 to 25%. At the shallow site, the mean annual leaf formation rate during 1996 was 15% higher than during 1995, indicating substantial interannual variability. Age-frequency distributions were adjusted to account for misclassification errors as a result of age-specific leaf initiation rates. The oldest shoot was estimated to be between 8 and 12 yr. Long-term leaf marking indicates that the seagrass T. testudinum in Lower Laguna Madre violates the assumption that the leaf production rate is constant and successive plastochrons are of equal duration. Reduced leaf formation rates during summer were likely caused by resource allocation to developing fruits and seeds. As a result of site-specific, seasonal, and interannual variability in annual leaf formation rates, the application of the plastochron method to estimate T. testudinum short shoot age is limited. Furthermore, a review of the literature indicates that age-frequency distributions cannot be used to predict population growth. Predicting population growth requires traditional demographic methods (e.g. mapping individuals through time).
Journal Article