Comparison of the Validity and Generalizability of Machine Learning Algorithms for the Prediction of Energy Expenditure: Validation Study

Background: Accurate solutions for the estimation of physical activity and energy expenditure at scale are needed for a range of medical and health research fields. Machine learning techniques show promise in research-grade accelerometers, and some evidence indicates that these techniques can be applied to more scalable commercial devices. Objective: This study aims to test the validity and out-of-sample generalizability of algorithms for the prediction of energy expenditure in several wearables (ie, Fitbit Charge 2, ActiGraph GT3-x, SenseWear Armband Mini, and Polar H7) using two laboratory data sets comprising different activities. Methods: Two laboratory studies (study 1: n=59, age 44.4 years, weight 75.7 kg; study 2: n=30, age=31.9 years, weight=70.6 kg), in which adult participants performed a sequential lab-based activity protocol consisting of resting, household, ambulatory, and nonambulatory tasks, were combined in this study. In both studies, accelerometer and physiological data were collected from the wearables alongside energy expenditure using indirect calorimetry. Three regression algorithms were used to predict metabolic equivalents (METs; ie, random forest, gradient boosting, and neural networks), and five classification algorithms (ie, k-nearest neighbor, support vector machine, random forest, gradient boosting, and neural networks) were used for physical activity intensity classification as sedentary, light, or moderate to vigorous. Algorithms were evaluated using leave-one-subject-out cross-validations and out-of-sample validations. Results: The root mean square error (RMSE) was lowest for gradient boosting applied to SenseWear and Polar H7 data (0.91 METs), and in the classification task, gradient boost applied to SenseWear and Polar H7 was the most accurate (85.5%). Fitbit models achieved an RMSE of 1.36 METs and 78.2% accuracy for classification. Errors tended to increase in out-of-sample validations with the SenseWear neural network achieving RMSE values of 1.22 METs in the regression tasks and the SenseWear gradient boost and random forest achieving an accuracy of 80% in classification tasks. Conclusions: Algorithms trained on combined data sets demonstrated high predictive accuracy, with a tendency for superior performance of random forests and gradient boosting for most but not all wearable devices. Predictions were poorer in the between-study validations, which creates uncertainty regarding the generalizability of the tested algorithms

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The validity of two widely used commercial and research-grade activity monitors, during resting, household and activity behaviours

Wearable devices are increasingly prevalent in research environments for the estimation of energy expenditure (EE) and heart rate (HR). The aim of this study was to validate the HR and EE estimates of the Fitbit charge 2 (FC2), and the EE estimates of the Sensewear armband mini (SWA). We recruited 59 healthy adults to participate in walking, running, cycling, sedentary and household tasks. Estimates of HR from the FC2 were compared to a HR chest strap (Polar) and EE to a stationary metabolic cart (Vyntus CPX). The SWA overestimated overall EE by 0.03 kcal/min−1 and was statistically equivalent to the criterion measure, with a mean absolute percentage error (MAPE) of 29%. In contrast, the FC2 was not equivalent overall (MAPE = 44%). In household tasks, MAPE values of 93% and 83% were observed for the FC2 and SWA, respectively. The FC2 HR estimates were equivalent to the criterion measure overall. The SWA is more accurate than the commercial-grade FC2. Neither device is consistently accurate across the range of activities used in this study. The HR data obtained from the FC2 is more accurate than its EE estimates and future research may focus more on this variable

Discovering cell-active BCL6 inhibitors: effectively combining biochemical HTS with multiple biophysical techniques, X-ray crystallography and cell-based assays.

By suppressing gene transcription through the recruitment of corepressor proteins, B-cell lymphoma 6 (BCL6) protein controls a transcriptional network required for the formation and maintenance of B-cell germinal centres. As BCL6 deregulation is implicated in the development of Diffuse Large B-Cell Lymphoma, we sought to discover novel small molecule inhibitors that disrupt the BCL6-corepressor protein-protein interaction (PPI). Here we report our hit finding and compound optimisation strategies, which provide insight into the multi-faceted orthogonal approaches that are needed to tackle this challenging PPI with small molecule inhibitors. Using a 1536-well plate fluorescence polarisation high throughput screen we identified multiple hit series, which were followed up by hit confirmation using a thermal shift assay, surface plasmon resonance and ligand-observed NMR. We determined X-ray structures of BCL6 bound to compounds from nine different series, enabling a structure-based drug design approach to improve their weak biochemical potency. We developed a time-resolved fluorescence energy transfer biochemical assay and a nano bioluminescence resonance energy transfer cellular assay to monitor cellular activity during compound optimisation. This workflow led to the discovery of novel inhibitors with respective biochemical and cellular potencies (IC50s) in the sub-micromolar and low micromolar range

Heterologous expression of cytotoxic sesquiterpenoids from the medicinal mushroom Lignosus rhinocerotis in yeast

Background: Genome mining facilitated by heterologous systems is an emerging approach to access the chemical diversity encoded in basidiomycete genomes. In this study, three sesquiterpene synthase genes, GME3634, GME3638, and GME9210, which were highly expressed in the sclerotium of the medicinal mushroom Lignosus rhinocerotis, were cloned and heterologously expressed in a yeast system. Results: Metabolite profile analysis of the yeast culture extracts by GC-MS showed the production of several sesquiterpene alcohols (C 15 H 26 O), including cadinols and germacrene D-4-ol as major products. Other detected sesquiterpenes include selina-6-en-4-ol, ß-elemene, ß-cubebene, and cedrene. Two purified major compounds namely (+)-torreyol and a-cadinol synthesised by GME3638 and GME3634 respectively, are stereoisomers and their chemical structures were confirmed by 1 H and 13 C NMR. Phylogenetic analysis revealed that GME3638 and GME3634 are a pair of orthologues, and are grouped together with terpene synthases that synthesise cadinenes and related sesquiterpenes. (+)-Torreyol and a-cadinol were tested against a panel of human cancer cell lines and the latter was found to exhibit selective potent cytotoxicity in breast adenocarcinoma cells (MCF7) with IC 50 value of 3.5 ± 0.58 µg/ml while a-cadinol is less active (IC 50 = 18.0 ± 3.27 µg/ml). Conclusions: This demonstrates that yeast-based genome mining, guided by transcriptomics, is a promising approach for uncovering bioactive compounds from medicinal mushrooms

Baculovirus Capsid Display Potentiates OVA Cytotoxic and Innate Immune Responses

Baculoviruses (BV) are DNA viruses that are pathogenic for insects. Although BV infect a range of mammalian cell types, they do not replicate in these cells. Indeed, the potential effects of these insect viruses on the immune responses of mammals are only just beginning to be studied. We show in this paper that a recombinant Autographa californica multiple nuclear polyhedrosis virus carrying a fragment of ovalbumin (OVA) on the VP39 capsid protein (BV-OVA) has the capacity to act as an adjuvant and vector of antigens in mice, thereby promoting specific CD4 and cytotoxic T cell responses against OVA. BV also induced in vivo maturation of dendritic cells and the production of inflammatory cytokines, thus promoting innate and adaptive immune responses. The OVA-specific response induced by BV-OVA was strong enough to reject a challenge with OVA-expressing melanoma cells (MO5 cells) and effectively prolonged survival of MO5 bearing mice. All these findings, together with the absence of pre-existing immunity to BV in humans and the lack of viral gene expression in mammalian cells, make BV a candidate for vaccination

Reducing the Activity and Secretion of Microbial Antioxidants Enhances the Immunogenicity of BCG

BACKGROUND:In early clinical studies, the live tuberculosis vaccine Mycobacterium bovis BCG exhibited 80% protective efficacy against pulmonary tuberculosis (TB). Although BCG still exhibits reliable protection against TB meningitis and miliary TB in early childhood it has become less reliable in protecting against pulmonary TB. During decades of in vitro cultivation BCG not only lost some genes due to deletions of regions of the chromosome but also underwent gene duplication and other mutations resulting in increased antioxidant production. METHODOLOGY/PRINCIPAL FINDINGS:To determine whether microbial antioxidants influence vaccine immunogenicity, we eliminated duplicated alleles encoding the oxidative stress sigma factor SigH in BCG Tice and reduced the activity and secretion of iron co-factored superoxide dismutase. We then used assays of gene expression and flow cytometry with intracellular cytokine staining to compare BCG-specific immune responses in mice after vaccination with BCG Tice or the modified BCG vaccine. Compared to BCG, the modified vaccine induced greater IL-12p40, RANTES, and IL-21 mRNA in the spleens of mice at three days post-immunization, more cytokine-producing CD8+ lymphocytes at the peak of the primary immune response, and more IL-2-producing CD4+ lymphocytes during the memory phase. The modified vaccine also induced stronger secondary CD4+ lymphocyte responses and greater clearance of challenge bacilli. CONCLUSIONS/SIGNIFICANCE:We conclude that antioxidants produced by BCG suppress host immune responses. These findings challenge the hypothesis that the failure of extensively cultivated BCG vaccines to prevent pulmonary tuberculosis is due to over-attenuation and suggest instead a new model in which BCG evolved to produce more immunity-suppressing antioxidants. By targeting these antioxidants it may be possible to restore BCG's ability to protect against pulmonary TB

Changing Bee and Hoverfly Pollinator Assemblages along an Urban-Rural Gradient

The potential for reduced pollination ecosystem service due to global declines of bees and other pollinators is cause for considerable concern. Habitat degradation, destruction and fragmentation due to agricultural intensification have historically been the main causes of this pollinator decline. However, despite increasing and accelerating levels of global urbanization, very little research has investigated the effects of urbanization on pollinator assemblages. We assessed changes in the diversity, abundance and species composition of bee and hoverfly pollinator assemblages in urban, suburban, and rural sites across a UK city.Bees and hoverflies were trapped and netted at 24 sites of similar habitat character (churchyards and cemeteries) that varied in position along a gradient of urbanization. Local habitat quality (altitude, shelter from wind, diversity and abundance of flowers), and the broader-scale degree of urbanization (e.g. percentage of built landscape and gardens within 100 m, 250 m, 500 m, 1 km, and 2.5 km of the site) were assessed for each study site. The diversity and abundance of pollinators were both significantly negatively associated with higher levels of urbanization. Assemblage composition changed along the urbanization gradient with some species positively associated with urban and suburban land-use, but more species negatively so. Pollinator assemblages were positively affected by good site habitat quality, in particular the availability of flowering plants.Our results show that urban areas can support diverse pollinator assemblages, but that this capacity is strongly affected by local habitat quality. Nonetheless, in both urban and suburban areas of the city the assemblages had fewer individuals and lower diversity than similar rural habitats. The unique development histories of different urban areas, and the difficulty of assessing mobile pollinator assemblages in just part of their range, mean that complementary studies in different cities and urban habitats are required to discover if these findings are more widely applicable

A Genetically Hard-Wired Metabolic Transcriptome in Plasmodium falciparum Fails to Mount Protective Responses to Lethal Antifolates

Genome sequences of Plasmodium falciparum allow for global analysis of drug responses to antimalarial agents. It was of interest to learn how DNA microarrays may be used to study drug action in malaria parasites. In one large, tightly controlled study involving 123 microarray hybridizations between cDNA from isogenic drug-sensitive and drug-resistant parasites, a lethal antifolate (WR99210) failed to over-produce RNA for the genetically proven principal target, dihydrofolate reductase-thymidylate synthase (DHFR-TS). This transcriptional rigidity carried over to metabolically related RNA encoding folate and pyrimidine biosynthesis, as well as to the rest of the parasite genome. No genes were reproducibly up-regulated by more than 2-fold until 24 h after initial drug exposure, even though clonal viability decreased by 50% within 6 h. We predicted and showed that while the parasites do not mount protective transcriptional responses to antifolates in real time, P. falciparum cells transfected with human DHFR gene, and adapted to long-term WR99210 exposure, adjusted the hard-wired transcriptome itself to thrive in the presence of the drug. A system-wide incapacity for changing RNA levels in response to specific metabolic perturbations may contribute to selective vulnerabilities of Plasmodium falciparum to lethal antimetabolites. In addition, such regulation affects how DNA microarrays are used to understand the mode of action of antimetabolites