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Abstract Longitudinal studies that continuously generate data enable the capture of temporal variations in experimentally observed parameters, facilitating the interpretation of results in a time-aware manner. We propose IL-VIS (incrementally learned visualizer), a new machine learning pipeline that incrementally learns and visualizes a progression trajectory representing the longitudinal changes in longitudinal studies. At each sampling time point in an experiment, IL-VIS generates a snapshot of the longitudinal process on the data observed thus far, a new feature that is beyond the reach of classical static models. We first verify the utility and correctness of IL-VIS using simulated data, for which the true progression trajectories are known. We find that it accurately captures and visualizes the trends and (dis)similarities between high-dimensional progression trajectories. We then apply IL-VIS to longitudinal multi-electrode array data from brain cortical organoids when exposed to different levels of quinolinic acid, a metabolite contributing to many neuroinflammatory diseases including Alzheimer’s disease, and its blocking antibody. We uncover valuable insights into the organoids’ electrophysiological maturation and response patterns over time under these conditions.

BackgroundOlder adults are at an increased risk of falls with the consequent impacts on the health of the individual and health expenditure for the population. Smartwatch apps have been developed to detect a fall, but their sensitivity and specificity have not been subjected to blinded assessment nor have the factors that influence the effectiveness of fall detection been fully identified. ObjectiveThis study aims to assess accuracy metrics for a novel fall detection smartwatch algorithm. MethodsWe performed a cross-sectional study of 22 healthy adults comparing the detection of induced forward, side (left and right), and backward falls and near falls provided by a smartwatch threshold-based algorithm, with a video record of induced falls serving as the gold standard; a blinded assessor compared the two. Three different smartwatches with two different operating systems were used. There were 226 falls: 64 were backward, 51 forward, 55 left sided, and 56 right sided. ResultsThe overall smartwatch app sensitivity for falls was 77%, the specificity was 99%, the false-positive rate was 1.7%, and the false-negative rate was 16.4%. The positive and negative predictive values were 98% and 84%, respectively, while the accuracy was 89%. There were 249 near falls: the sensitivity was 89%, the specificity was 100%, there were no false positives, 11% were false negatives, the positive predictive value was 100%, the false-negative predictive value was 83%, and the accuracy was 93%. ConclusionsFalls were more likely to be detected if the fall was on the same side as the wrist with the smartwatch. There was a trend toward some smartwatches and operating systems having superior sensitivity, but these did not reach statistical significance. The effectiveness data and modifying factors pertaining to this smartwatch app can serve as a reference point for other similar smartwatch apps.

Background Neurological COVID-19 disease has been reported widely, but published studies often lack information on neurological outcomes and prognostic risk factors. We aimed to describe the spectrum of neurological disease in hospitalised COVID-19 patients; characterise clinical outcomes; and investigate factors associated with a poor outcome. Methods We conducted an individual patient data (IPD) meta-analysis of hospitalised patients with neurological COVID-19 disease, using standard case definitions. We invited authors of studies from the first pandemic wave, plus clinicians in the Global COVID-Neuro Network with unpublished data, to contribute. We analysed features associated with poor outcome (moderate to severe disability or death, 3 to 6 on the modified Rankin Scale) using multivariable models. Results We included 83 studies (31 unpublished) providing IPD for 1979 patients with COVID-19 and acute new-onset neurological disease. Encephalopathy (978 [49%] patients) and cerebrovascular events (506 [26%]) were the most common diagnoses. Respiratory and systemic symptoms preceded neurological features in 93% of patients; one third developed neurological disease after hospital admission. A poor outcome was more common in patients with cerebrovascular events (76% [95% CI 67–82]), than encephalopathy (54% [42–65]). Intensive care use was high (38% [35–41]) overall, and also greater in the cerebrovascular patients. In the cerebrovascular, but not encephalopathic patients, risk factors for poor outcome included breathlessness on admission and elevated D-dimer. Overall, 30-day mortality was 30% [27–32]. The hazard of death was comparatively lower for patients in the WHO European region. Interpretation Neurological COVID-19 disease poses a considerable burden in terms of disease outcomes and use of hospital resources from prolonged intensive care and inpatient admission; preliminary data suggest these may differ according to WHO regions and country income levels. The different risk factors for encephalopathy and stroke suggest different disease mechanisms which may be amenable to intervention, especially in those who develop neurological symptoms after hospital admission.

HIV-associated neurocognitive disorders (HAND) remain prevalent despite plasma viral suppression by antiretroviral agents. In fact, the prevalence of milder subtypes of cognitive impairment is increasing. Neuropsychologic testing remains the “gold standard” of diagnosis; however, this is time consuming and costly in a resource-poor environment. Recently developed screening tools, such as CogState and the revised HIV dementia scale, have very good sensitivity and specificity in the more severe stages of HAND. However, questions remain regarding the utility of, optimal population for, and insensitivity of tests in mild HAND. Recognition of ongoing viral persistence and the inflammatory milieu in the central nervous system (CNS) has advanced our understanding of the pathogenesis of HAND and facilitated the development of biomarkers of CNS disease. The importance of the monocyte-macrophage lineage cell and the astrocyte as viral reservoirs, HIV viral proteins, self-perpetuating CNS inflammation, and CCR5 chemokine receptor neurotropism has been identified. Whilst biomarkers demonstrate monocyte activation, inflammation, and neuronal injury, they remain limited in their clinical utility. The improved understanding of pathogenic mechanisms has led to novel approaches to the treatment of HAND; however, despite these advances, the optimal management is still undefined.

Some systems were recently put forth by Nguyen et al. as models for studying the interaction of long and short waves in dispersive media. These systems were shown to possess synchronized Jacobi elliptic solutions as well as synchronized solitary wave solutions under certain constraints, i.e., vector solutions, where the two components are proportional to one another. In this paper, the exact periodic traveling wave solutions to these systems in general were found to be given by Jacobi elliptic functions. Moreover, these cnoidal wave solutions are unique. Thus, the explicit synchronized solutions under some conditions obtained by Nguyen et al. are also indeed unique.

Abstract There has been a drastic decline in the number of cheetahs in the past century. Illegal pet trade poses a critical threat to the survival of the species and demands more attention. Genetic analysis of 55 cheetahs confiscated in Somaliland shows 100% as Acinonyx jubatus soemmeringii, suggesting that illegal trade subjects A. j. soemmeringii to significant pressure. Continued decline of the estimated 260–590 mature individuals qualifies this subspecies as “endangered” versus currently “vulnerable,” under criterion C2a(i) of the International Union for Conservation of Nature Red List. A population decline of ≥80% over the next 10 years or 3 generations would even fulfill criterion A3 of “critically endangered.” We urge reclassification of A. j. soemmeringii, as endangered, and appeal to the cheetah community to investigate further uplisting to critically endangered to reflect the likely extinction risk exacerbated by the illegal trade.

Abstract Bush encroachment affects much of the Namibian woodland landscape, causing significant loss of open savannah habitat and farm profits. Thinning of the trees/shrubs is recommended; however, research is required to identify the overall efficacy and effects of this method on the woodland habitat. We aimed to examine the effect of the thinning strategy applied on the vegetation structure of encroaching tree/shrub species, as well as the sighting lines of the habitat. Vegetation surveys were done on three freehold farms in north-central Namibia. The study utilised a combination of a blocked and split-plot study design: each block consisted of a pair of thinned and non-thinned plots with multiple subplots. Thinned plots had been manually thinned, with a post-thinning age of three years or more. Results revealed that tree/shrub abundance differed between species; thinned areas had the least abundance and overall species-treatment interactions were significant. Thinning caused a significant reduction in overall tree/shrub densities, settling within the recommended range for the area. Thinning also significantly reduced the average tree/shrub height, canopy area, medium-sized trees/shrubs, and increased sighting lines. This confirms a bush encroachment mitigation strategy that favours grass cover, and wildlife that rely on longer sighting lines for safety or when hunting.