Feasibility of using intermittent active monitoring of vital signs by smartphone users to predict SARS-CoV-2 PCR positivity.

Early detection of highly infectious respiratory diseases, such as COVID-19, can help curb their transmission. Consequently, there is demand for easy-to-use population-based screening tools, such as mobile health applications. Here, we describe a proof-of-concept development of a machine learning classifier for the prediction of a symptomatic respiratory disease, such as COVID-19, using smartphone-collected vital sign measurements. The Fenland App study followed 2199 UK participants that provided measurements of blood oxygen saturation, body temperature, and resting heart rate. Total of 77 positive and 6339 negative SARS-CoV-2 PCR tests were recorded. An optimal classifier to identify these positive cases was selected using an automated hyperparameter optimisation. The optimised model achieved an ROC AUC of 0.695 ± 0.045. The data collection window for determining each participant's vital sign baseline was increased from 4 to 8 or 12 weeks with no significant difference in model performance (F(2) = 0.80, p = 0.472). We demonstrate that 4 weeks of intermittently collected vital sign measurements could be used to predict SARS-CoV-2 PCR positivity, with applicability to other diseases causing similar vital sign changes. This is the first example of an accessible, smartphone-based remote monitoring tool deployable in a public health setting to screen for potential infections.

The Oxidation of Oxygen and Sulfur-Containing Heterocycles by Cytochrome P450 Enzymes.

The cytochrome P450 (CYP) superfamily of monooxygenase enzymes play important roles in the metabolism of molecules which contain heterocyclic, aromatic functional groups. Here we study how oxygen- and sulfur-containing heterocyclic groups interact with and are oxidized using the bacterial enzyme CYP199A4. This enzyme oxidized both 4-(thiophen-2-yl)benzoic acid and 4-(thiophen-3-yl)benzoic acid almost exclusively via sulfoxidation. The thiophene oxides produced were activated towards Diels-Alder dimerization after sulfoxidation, forming dimeric metabolites. Despite X-ray crystal structures demonstrating that the aromatic carbon atoms of the thiophene ring were located closer to the heme than the sulfur, sulfoxidation was still favoured with 4-(thiophen-3-yl)benzoic acid. These results highlight a preference of this cytochrome P450 enzyme for sulfoxidation over aromatic hydroxylation. Calculations predict a strong preference for homodimerization of the enantiomers of the thiophene oxides and the formation of a single major product, in broad agreement with the experimental data. 4-(Furan-2-yl)benzoic acid was oxidized to 4-(4'-hydroxybutanoyl)benzoic acid using a whole-cell system. This reaction proceeded via a γ-keto-α,ß-unsaturated aldehyde species which could be trapped in vitro using semicarbazide to generate a pyridazine species. The combination of the enzyme structures, the biochemical data and theoretical calculations provides detailed insight into the formation of the metabolites formed from these heterocyclic compounds.

Systematic, comprehensive, evidence-based approach to identify neuroprotective interventions for motor neuron disease: using systematic reviews to inform expert consensus.

OBJECTIVES: Motor neuron disease (MND) is an incurable progressive neurodegenerative disease with limited treatment options. There is a pressing need for innovation in identifying therapies to take to clinical trial. Here, we detail a systematic and structured evidence-based approach to inform consensus decision making to select the first two drugs for evaluation in Motor Neuron Disease-Systematic Multi-arm Adaptive Randomised Trial (MND-SMART: NCT04302870), an adaptive platform trial. We aim to identify and prioritise candidate drugs which have the best available evidence for efficacy, acceptable safety profiles and are feasible for evaluation within the trial protocol. METHODS: We conducted a two-stage systematic review to identify potential neuroprotective interventions. First, we reviewed clinical studies in MND, Alzheimer's disease, Huntington's disease, Parkinson's disease and multiple sclerosis, identifying drugs described in at least one MND publication or publications in two or more other diseases. We scored and ranked drugs using a metric evaluating safety, efficacy, study size and study quality. In stage two, we reviewed efficacy of drugs in MND animal models, multicellular eukaryotic models and human induced pluripotent stem cell (iPSC) studies. An expert panel reviewed candidate drugs over two shortlisting rounds and a final selection round, considering the systematic review findings, late breaking evidence, mechanistic plausibility, safety, tolerability and feasibility of evaluation in MND-SMART. RESULTS: From the clinical review, we identified 595 interventions. 66 drugs met our drug/disease logic. Of these, 22 drugs with supportive clinical and preclinical evidence were shortlisted at round 1. Seven drugs proceeded to round 2. The panel reached a consensus to evaluate memantine and trazodone as the first two arms of MND-SMART. DISCUSSION: For future drug selection, we will incorporate automation tools, text-mining and machine learning techniques to the systematic reviews and consider data generated from other domains, including high-throughput phenotypic screening of human iPSCs.

Soluble adenylyl cyclase coordinates intracellular pH homeostasis and biomineralization in calcifying cells of a marine animal.

Biomineralizing cells concentrate dissolved inorganic carbon (DIC) and remove protons from the site of mineral precipitation. However, the molecular regulatory mechanisms that orchestrate pH homeostasis and biomineralization of calcifying cells are poorly understood. Here, we report that the acid-base sensing enzyme soluble adenylyl cyclase (sAC) coordinates intracellular pH (pHi) regulation in the calcifying primary mesenchyme cells (PMCs) of sea urchin larvae. Single-cell transcriptomics, in situ hybridization, and immunocytochemistry elucidated the spatiotemporal expression of sAC during skeletogenesis. Live pHi imaging of PMCs revealed that the downregulation of sAC activity with two structurally unrelated small molecules inhibited pHi regulation of PMCs, an effect that was rescued by the addition of cell-permeable cAMP. Pharmacological sAC inhibition also significantly reduced normal spicule growth and spicule regeneration, establishing a link between PMC pHi regulation and biomineralization. Finally, increased expression of sAC mRNA was detected during skeleton remineralization and exposure to CO2-induced acidification. These findings suggest that transcriptional regulation of sAC is required to promote remineralization and to compensate for acidic stress. This work highlights the central role of sAC in coordinating acid-base regulation and biomineralization in calcifying cells of a marine animal.

Sleep-deprived new mothers gave their infants a higher priority than themselves.

AIM: To understand why some parents are less sensitive to infant cues than others, we need to understand how healthy parents respond, and how this is influenced by factors such as sleep deprivation. Here, we examined whether sleep deprivation alters the self-infant-prioritisation effect in a population of first-time mothers within their first year of motherhood. METHODS: The study took place at Aarhus University Hospital in Denmark from August 2018 until February 2020. First-time mothers were recruited through Midwife clinics, national and social media. All women completed a perceptual matching task including an infant category. The mothers were divided into two groups depending on their sleep status: below or above 7 h of average night-time sleep, measured with actigraphy. RESULTS: Forty-eight first-time mothers at the age of 29.13 ± 3.87 years were included. In the sleep-deprived group, the infant category was statistically significantly higher in accuracy (p = 0.005) and faster in reaction time (p < 0.001) than all other categories. In contrast, in the non-sleep-deprived group, there was no statistically significant difference between self and infant, neither in accuracy, nor reaction time. CONCLUSION: Sleep-deprived new mothers strongly prioritised infants over self, while non-sleep-deprived new mothers showed no prioritisation of the self over the infant.

Cibalackrot Dendrimers for Hyperfluorescent Organic Light-Emitting Diodes.

Hyperfluorescent organic light-emitting diodes (HF-OLEDs) enable a cascading Förster resonance energy transfer (FRET) from a suitable thermally activated delayed fluorescent (TADF) assistant host to a fluorescent end-emitter to give efficient OLEDs with relatively narrowed electroluminescence compared to TADF-OLEDs. Efficient HF-OLEDs require optimal FRET with minimum triplet diffusion via Dexter-type energy transfer (DET) from the TADF assistant host to the fluorescent end-emitter. To hinder DET, steric protection of the end-emitters has been proposed to disrupt triplet energy transfer. In this work, the first HF-OLEDs based on structurally well-defined macromolecules, dendrimers is reported. The dendrimers contain new highly twisted dendrons attached to a Cibalackrot core, resulting in high solubility in organic solvents. HF-OLEDs based on dendrimer blend films are fabricated to show external quantum efficiencies of >10% at 100 cd m-2 . Importantly, dendronization with the bulky dendrons is found to have no negative impact to the FRET efficiency, indicating the excellent potential of the dendritic macromolecular motifs for HF-OLEDs. To fully prevent the undesired triplet diffusion, Cibalackrot dendrimers HF-OLEDs are expected to be further improved by adding additional dendrons to the Cibalackrot core and/or increasing dendrimer generations.

Chemoselective and Diastereoselective Intramolecular (3+2) Cycloadditions of Epoxy and Aziridinyl Enolsilanes.

Epoxy and aziridinyl enolsilanes react as oxyallylic cation equivalents in highly chemo- and diastereoselective intramolecular (3+2) cycloadditions with a range of dienes and olefins. With acyclic dienes, the (3+2) cycloaddition outcompetes the (4+3) pathway traditionally observed in this kind of system almost exclusively. With both conjugated dienes and isolated olefins, excellent diastereoselectivities are observed, and cycloadducts can be obtained in optically-enriched forms. Computational studies indicate that the stepwise (3+2) cycloaddition involves an activated epoxy/aziridinyl intermediate and the conformational flexibility of the intermediate determines the preference for (3+2) cycloadduct formation. Further transformations of the (3+2) cycloadducts produce densely functionalized trans-hydrindane scaffolds.

A Rhesus channel in the coral symbiosome membrane suggests a novel mechanism to regulate NH3 and CO2 delivery to algal symbionts.

Reef-building corals maintain an intracellular photosymbiotic association with dinoflagellate algae. As the algae are hosted inside the symbiosome, all metabolic exchanges must take place across the symbiosome membrane. Using functional studies in Xenopus oocytes, immunolocalization, and confocal Airyscan microscopy, we established that Acropora yongei Rh (ayRhp1) facilitates transmembrane NH3 and CO2 diffusion and that it is present in the symbiosome membrane. Furthermore, ayRhp1 abundance in the symbiosome membrane was highest around midday and lowest around midnight. We conclude that ayRhp1 mediates a symbiosomal NH4+-trapping mechanism that promotes nitrogen delivery to algae during the day-necessary to sustain photosynthesis-and restricts nitrogen delivery at night-to keep algae under nitrogen limitation. The role of ayRhp1-facilitated CO2 diffusion is less clear, but it may have implications for metabolic dysregulation between symbiotic partners and bleaching. This previously unknown mechanism expands our understanding of symbioses at the immediate animal-microbe interface, the symbiosome.

V-type H+-ATPase in the symbiosome membrane is a conserved mechanism for host control of photosynthesis in anthozoan photosymbioses.

In reef-building corals (order Scleractinia) and giant clams (phylum Molluca), V-type H+-ATPase (VHA) in host cells is part of a carbon concentrating mechanism (CCM) that regulates photosynthetic rates of their symbiotic algae. Here, we show that VHA plays a similar role in the sea anemone Anemonia majano, a member of the order Actinaria and sister group to the Scleractinia, which in contrast to their colonial calcifying coral relatives is a solitary, soft-bodied taxa. Western blotting and immunofluorescence revealed that VHA was abundantly present in the host-derived symbiosome membrane surrounding the photosymbionts. Pharmacological inhibition of VHA activity in individual anemones resulted in an approximately 80% decrease of photosynthetic O2 production. These results extend the presence of a host-controlled VHA-dependent CCM to non-calcifying cnidarians of the order Actiniaria, suggesting it is widespread among photosymbiosis between aquatic invertebrates and Symbiodiniaceae algae.

Neural correlates of the inverse base rate effect.

The inverse base rate effect (IBRE) is a nonrational behavioral phenomenon in predictive learning. Canonically, participants learn that the AB stimulus compound leads to one outcome and that AC leads to another outcome, with AB being presented three times as often as AC. When subsequently presented with BC, the outcome associated with AC is preferentially selected, in opposition to the underlying base rates of the outcomes. The current leading explanation is based on error-driven learning. A key component of this account is prediction error, a concept previously linked to a number of brain areas including the anterior cingulate, the striatum, and the dorsolateral prefrontal cortex. The present work is the first fMRI study to directly examine the IBRE. Activations were noted in brain areas linked to prediction error, including the caudate body, the anterior cingulate, the ventromedial prefrontal cortex, and the right dorsolateral prefrontal cortex. Analyzing the difference in activations for singular key stimuli (B and C), as well as frequency matched controls, supports the predictions made by the error-driven learning account.

The benefits of impossible tests: Assessing the role of error-correction in the pretesting effect.

Relative to studying alone, guessing the meanings of unknown words can improve later recognition of their meanings, even if those guesses were incorrect - the pretesting effect (PTE). The error-correction hypothesis suggests that incorrect guesses produce error signals that promote memory for the meanings when they are revealed. The current research sought to test the error-correction explanation of the PTE. In three experiments, participants studied unfamiliar Finnish-English word pairs by either studying each complete pair or by guessing the English translation before its presentation. In the latter case, the participants also guessed which of two categories the word belonged to. Hence, guesses from the correct category were semantically closer to the true translation than guesses from the incorrect category. In Experiment 1, guessing increased subsequent recognition of the English translations, especially for translations that were presented on trials in which the participants' guesses were from the correct category. Experiment 2 replicated these target recognition effects while also demonstrating that they do not extend to associative recognition performance. Experiment 3 again replicated the target recognition pattern, while also examining participants' metacognitive recognition judgments. Participants correctly judged that their memory would be better after small than after large errors, but incorrectly believed that making any errors would be detrimental, relative to study-only. Overall, the data are inconsistent with the error-correction hypothesis; small, within-category errors produced better recognition than large, cross-category errors. Alternative theories, based on elaborative encoding and motivated learning, are considered.

COVID-19 in Pregnant Women With Rheumatic Disease: Data From the COVID-19 Global Rheumatology Alliance.

OBJECTIVE: To describe coronavirus disease 2019 (COVID-19) and pregnancy outcomes in patients with rheumatic disease who were pregnant at the time of infection. METHODS: Since March 2020, the COVID-19 Global Rheumatology Alliance has collected cases of patients with rheumatic disease with COVID-19. We report details of pregnant women at the time of COVID-19 infection, including obstetric details separately ascertained from providers. RESULTS: We report on 39 patients, including 22 with obstetric detail available. The mean and median age was 33 years, range 24-45 years. Rheumatic disease diagnoses included rheumatoid arthritis (n = 9), systemic lupus erythematosus (n = 9), psoriatic arthritis/other inflammatory arthritides (n = 8), and antiphospholipid syndrome (n = 6). Most had a term birth (16/22), with 3 preterm births, 1 termination, and 1 miscarriage; 1 woman had yet to deliver at the time of report. One-quarter (n = 10/39) of pregnant women were hospitalized following COVID-19 diagnosis. Two of 39 (5%) required supplemental oxygen (both hospitalized); no patients died. The majority did not receive specific medication treatment for their COVID-19 (n = 32/39, 82%), and 7 patients received some combination of antimalarials, colchicine, anti-interleukin 1ß, azithromycin, glucocorticoids, and lopinavir/ritonavir. CONCLUSION: Women with rheumatic diseases who were pregnant at the time of COVID-19 had favorable outcomes. These data have limitations due to the small size and methodology; however, they provide cautious optimism for pregnancy outcomes for women with rheumatic disease particularly in comparison to the increased risk of poor outcomes that have been reported in other series of pregnant women with COVID-19.

Endo Selectivity in the (4 + 3) Cycloaddition of Oxidopyridinium Ions.

The (4 + 3) cycloaddition of 2-trialkylsilyl-4-alkylbutadienes with an N-methyloxidopyridinium ion affords cycloadducts with high regioselectivity and excellent endo selectivity.

Machine learning approach to dynamic risk modeling of mortality in COVID-19: a UK Biobank study.

The COVID-19 pandemic has created an urgent need for robust, scalable monitoring tools supporting stratification of high-risk patients. This research aims to develop and validate prediction models, using the UK Biobank, to estimate COVID-19 mortality risk in confirmed cases. From the 11,245 participants testing positive for COVID-19, we develop a data-driven random forest classification model with excellent performance (AUC: 0.91), using baseline characteristics, pre-existing conditions, symptoms, and vital signs, such that the score could dynamically assess mortality risk with disease deterioration. We also identify several significant novel predictors of COVID-19 mortality with equivalent or greater predictive value than established high-risk comorbidities, such as detailed anthropometrics and prior acute kidney failure, urinary tract infection, and pneumonias. The model design and feature selection enables utility in outpatient settings. Possible applications include supporting individual-level risk profiling and monitoring disease progression across patients with COVID-19 at-scale, especially in hospital-at-home settings.

Association of baseline hematoma and edema volumes with one-year outcome and long-term survival after spontaneous intracerebral hemorrhage: A community-based inception cohort study.

BACKGROUND: Hospital-based studies have reported variable associations between outcome after spontaneous intracerebral hemorrhage and peri-hematomal edema volume. AIMS: In a community-based study, we aimed to investigate the existence, strength, direction, and independence of associations between intracerebral hemorrhage and peri-hematomal edema volumes on diagnostic brain CT and one-year functional outcome and long-term survival. METHODS: We identified all adults, resident in Lothian, diagnosed with first-ever, symptomatic spontaneous intracerebral hemorrhage between June 2010 and May 2013 in a community-based, prospective inception cohort study. We defined regions of interest manually and used a semi-automated approach to measure intracerebral hemorrhage volume, peri-hematomal edema volume, and the sum of these measurements (total lesion volume) on first diagnostic brain CT performed at ≤3 days after symptom onset. The primary outcome was death or dependence (scores 3-6 on the modified Rankin Scale) at one-year after intracerebral hemorrhage. RESULTS: Two hundred ninety-two (85%) of 342 patients (median age 77.5 y, IQR 68-83, 186 (54%) female, median time from onset to CT 6.5 h (IQR 2.9-21.7)) were dead or dependent one year after intracerebral hemorrhage. Peri-hematomal edema and intracerebral hemorrhage volumes were colinear (R2 = 0.77). In models using both intracerebral hemorrhage and peri-hematomal edema, 10 mL increments in intracerebral hemorrhage (adjusted odds ratio (aOR) 1.72 (95% CI 1.08-2.87); p = 0.029) but not peri-hematomal edema volume (aOR 0.92 (0.63-1.45); p = 0.69) were independently associated with one-year death or dependence. 10 mL increments in total lesion volume were independently associated with one-year death or dependence (aOR 1.24 (1.11-1.42); p = 0.0004). CONCLUSION: Total volume of intracerebral hemorrhage and peri-hematomal edema, and intracerebral hemorrhage volume alone on diagnostic brain CT, undertaken at three days or sooner, are independently associated with death or dependence one-year after intracerebral hemorrhage, but peri-hematomal edema volume is not. DATA ACCESS STATEMENT: Anonymized summary data may be requested from the corresponding author.

Machine learning approach to dynamic risk modeling of mortality in COVID-19: a UK Biobank cohort study

The COVID-19 pandemic has created an urgent need for robust, scalable monitoring tools supporting stratification of high-risk patients. This research aims to develop and validate prediction models, using the UK Biobank, to estimate COVID-19 mortality risk in confirmed cases. From the 11,245 participants testing positive for COVID-19, we develop a data-driven random forest classification model with excellent performance (AUC: 0.91), using baseline characteristics, pre-existing conditions, symptoms, and vital signs, such that the score could dynamically assess mortality risk with disease deterioration. We also identify several significant novel predictors of COVID-19 mortality with equivalent or greater predictive value than established high-risk comorbidities, such as detailed anthropometrics and prior acute kidney failure, urinary tract infection, and pneumonias. The model design and feature selection enables utility in outpatient settings. Possible applications include supporting individual-level risk profiling and monitoring disease progression across patients with COVID-19 at-scale, especially in hospital-at-home settings.

Accelerometer-derived sleep onset timing and cardiovascular disease incidence: a UK Biobank cohort study.

Aims: Growing evidence suggests that poor sleep health is associated with cardiovascular risk. However, research in this area often relies upon recollection dependent questionnaires or diaries. Accelerometers provide an alternative tool for measuring sleep parameters objectively. This study examines the association between wrist-worn accelerometer-derived sleep onset timing and cardiovascular disease (CVD). Methods and results: We derived sleep onset and waking up time from accelerometer data collected from 103 712 UK Biobank participants over a period of 7 days. From this, we examined the association between sleep onset timing and CVD incidence using a series of Cox proportional hazards models. A total of 3172 cases of CVD were reported during a mean follow-up period of 5.7 (±0.49) years. An age- and sex-controlled base analysis found that sleep onset time of 10:00 p.m.-10:59 p.m. was associated with the lowest CVD incidence. An additional model, controlling for sleep duration, sleep irregularity, and established CVD risk factors, did not attenuate this association, producing hazard ratios of 1.24 (95% confidence interval, 1.10-1.39; P < 0.005), 1.12 (1.01-1.25; P = 0.04), and 1.25 (1.02-1.52; P = 0.03) for sleep onset <10:00 p.m., 11:00 p.m.-11:59 p.m., and ≥12:00 a.m., respectively, compared to 10:00 p.m.-10:59 p.m. Importantly, sensitivity analyses revealed this association with increased CVD risk was stronger in females, with only sleep onset <10:00 p.m. significant for males. Conclusions: Our findings suggest the possibility of a relationship between sleep onset timing and risk of developing CVD, particularly for women. We also demonstrate the potential utility of collecting information about sleep parameters via accelerometry-capable wearable devices, which may serve as novel cardiovascular risk indicators.

Development of an accessible 10-year Digital CArdioVAscular (DiCAVA) risk assessment: a UK Biobank study.

Aims: Cardiovascular diseases (CVDs) are among the leading causes of death worldwide. Predictive scores providing personalized risk of developing CVD are increasingly used in clinical practice. Most scores, however, utilize a homogenous set of features and require the presence of a physician. The aim was to develop a new risk model (DiCAVA) using statistical and machine learning techniques that could be applied in a remote setting. A secondary goal was to identify new patient-centric variables that could be incorporated into CVD risk assessments. Methods and results: Across 466 052 participants, Cox proportional hazards (CPH) and DeepSurv models were trained using 608 variables derived from the UK Biobank to investigate the 10-year risk of developing a CVD. Data-driven feature selection reduced the number of features to 47, after which reduced models were trained. Both models were compared to the Framingham score. The reduced CPH model achieved a c-index of 0.7443, whereas DeepSurv achieved a c-index of 0.7446. Both CPH and DeepSurv were superior in determining the CVD risk compared to Framingham score. Minimal difference was observed when cholesterol and blood pressure were excluded from the models (CPH: 0.741, DeepSurv: 0.739). The models show very good calibration and discrimination on the test data. Conclusion: We developed a cardiovascular risk model that has very good predictive capacity and encompasses new variables. The score could be incorporated into clinical practice and utilized in a remote setting, without the need of including cholesterol. Future studies will focus on external validation across heterogeneous samples.

Enhanced axonal response of mitochondria to demyelination offers neuroprotection: implications for multiple sclerosis.

Axonal loss is the key pathological substrate of neurological disability in demyelinating disorders, including multiple sclerosis (MS). However, the consequences of demyelination on neuronal and axonal biology are poorly understood. The abundance of mitochondria in demyelinated axons in MS raises the possibility that increased mitochondrial content serves as a compensatory response to demyelination. Here, we show that upon demyelination mitochondria move from the neuronal cell body to the demyelinated axon, increasing axonal mitochondrial content, which we term the axonal response of mitochondria to demyelination (ARMD). However, following demyelination axons degenerate before the homeostatic ARMD reaches its peak. Enhancement of ARMD, by targeting mitochondrial biogenesis and mitochondrial transport from the cell body to axon, protects acutely demyelinated axons from degeneration. To determine the relevance of ARMD to disease state, we examined MS autopsy tissue and found a positive correlation between mitochondrial content in demyelinated dorsal column axons and cytochrome c oxidase (complex IV) deficiency in dorsal root ganglia (DRG) neuronal cell bodies. We experimentally demyelinated DRG neuron-specific complex IV deficient mice, as established disease models do not recapitulate complex IV deficiency in neurons, and found that these mice are able to demonstrate ARMD, despite the mitochondrial perturbation. Enhancement of mitochondrial dynamics in complex IV deficient neurons protects the axon upon demyelination. Consequently, increased mobilisation of mitochondria from the neuronal cell body to the axon is a novel neuroprotective strategy for the vulnerable, acutely demyelinated axon. We propose that promoting ARMD is likely to be a crucial preceding step for implementing potential regenerative strategies for demyelinating disorders.