Significant Sparse Polygenic Risk Scores across 813 traits in UK Biobank We present a systematic assessment of polygenic risk score (PRS) prediction across more than 1,500 traits using genetic and phenotype data in the UK Biobank. We report 813 sparse PRS models with significant (p < 2.5 x 10-5) incremental predictive performance when compared against the covariate-only model that considers age, sex, types of genotyping arrays, and the principal component loadings of genotypes. We report a significant correlation between the number of genetic variants selected in the sparse PRS model and the incremental predictive performance (Spearmans {rho} = 0.61, p = 2.2 x 10-59 for quantitative traits, {rho} = 0.21, p = 9.6 x 10-4 for binary traits). The sparse PRS model trained on European individuals showed limited transferability when evaluated on non-European individuals in the UK Biobank. We provide the PRS model weights on the Global Biobank Engine (https://biobankengine.stanford.edu/prs).

Author summaryPolygenic risk scores (PRSs), an approach to estimate genetic predisposition on disease liability by aggregating the effects across multiple genetic variants, has attracted increasing research interest. While there have been improvements in the predictive performance of PRS for some traits, the applicability of PRS models across a wide range of human traits has not been clear. Here, applying penalized regression using Batch Screening Iterative Lasso (BASIL) algorithm to more than 269,000 individuals of white British ancestry in UK Biobank, we systematically characterize PRS models across more than 1,500 traits. We report 813 traits with PRS models of statistically significant predictive performance. While the statistical significance does not necessarily directly translate into clinical relevance, we investigate the properties of the 813 significant PRS models and report a significant correlation between predictive performance and estimated SNP-based heritability. We find that the number of genetic variants selected in our sparse PRS model is significantly correlated with the incremental predictive performance in both quantitative and binary traits. Our transferability assessment of PRS models in UK Biobank revealed that the sparse PRS models trained on individuals of European ancestry had a lower predictive performance for individuals of African and Asian ancestry groups.
Unveiling Sex-based Differences in Parkinson's Disease: A Comprehensive Meta-analysis of Transcriptomic Studies In recent decades, increasing longevity (among other factors) has fostered a rise in Parkinsons disease (PD) incidence. Although not exhaustively studied in this devastating disease, the impact of sex represents a critical variable in PD as epidemiological and clinical features differ between males and females. To study sex bias in PD, we conducted a systematic review, tissue-specific meta-analyses of transcriptomic data from the frontal cortex (FC), striatum tissue (ST), and substantia nigra (SN), and a global meta-analysis of all 3 brain regions. We selected 7 PD studies that included sex information, analyzing 267 samples. The tissue-specific meta-analyses linked PD to the enhanced expression of MED31 in the female FC and the dysregulation of 237 genes in the SN. The global meta-analysis detected 15 genes with sex-differential patterns in PD, which participate in mitochondrial function, oxidative stress, neuronal degeneration, and cell death. Furthermore, functional analyses identified pathways, protein-protein interaction networks, and transcription factors that differed by sex. While male PD patients exhibited changes in oxidative stress based on metal ions, inflammation, and angiogenesis, female PD patients exhibited dysfunctions in mitochondrial and lysosomal activity, antigen processing and presentation functions, and glutamic and purine metabolism. Overall, we believe that our findings will provide new insight into the perspective of sex in PD, thereby underscoring the importance of including sex information in future PD studies.
HIV-infected patients on combined antiretroviral treatment had similar level of arterial stiffness to the patients with ST-segment elevation myocardial infarction. PurposeThe cardiovascular disease has become very common among HIV-infected patients. The aim was to compare the arterial stiffness and the endothelial dysfunction in HIV-infected patients to non-HIV-infected patients in week 4 after ST-segment elevation myocardial infarction (STEMI).

MethodsThe arterial stiffness was calculated by Endo-PAT 2000(ITAMAR(R)) and the endothelial function by Peripheral Arterial Tonometry(PAT(R)). The correct endothelial function was defined for natural logarithm of reactive hyperaemia index (lnRHI)>0.51. Arterial stiffness was assessed as the AI and corrected for heart rate of 75 bpm (AI@75).

ResultsSixty-three patients were recruited to this study, n=34 patients with HIV infection (n=18 on cART) and n=29 HIV-negative patients after recent STEMI. No statistically significant differences for AI and AI@75 were found in STEMI and in HIV on cART group. We observed p<0.05 for AI and AI@75 for patients without cART compared to STEMI and on cART patients. The observed lnRHI results were significantly different p<0.05 in STEMI and on cART patients. We get similar endothelial dysfunction p>0.05 for patients without cART compared to STEMI and on cART patients.

ConclusionsAssessing cardiovascular risk also with non-invasive methods among HIV-infected patients is very important especially in HIV-patients on cART. Endothelial dysfunction is connected with HIV infection and can be similar for STEMI and HIV-infected without cART. Population Pharmacokinetic Analysis of Dexmedetomidine in Children using Real World Data from Electronic Health Records and Remnant Specimens AimOur objectives were to perform a population pharmacokinetic analysis of dexmedetomidine in children using remnant specimens and data from electronic health records (EHRs) and explore the impact of patients characteristics and pharmacogenetics on dexmedetomidine clearance.

MethodsDexmedetomidine dosing and patient data were gathered from EHRs and combined with opportunistically sampled remnant specimens. Population pharmacokinetic models were developed using nonlinear mixed-effects modeling. The first stage developed a model without genotype variables; the second stage added pharmacogenetic effects.

ResultsOur final study population included 354 post-cardiac surgery patients age 0 to 22 years (median 16 months). The final two-compartment model included allometric weight scaling and age maturation. Population parameter estimates and 95% confidence intervals were 27.3 L/hr (24.0 - 31.1 L/hr) for total clearance (CL), 161 L (139 - 187 L) for central compartment volume of distribution (V1), 26.0 L/hr (22.5 - 30.0 L/hr) for intercompartmental clearance (Q), and 7903 L (5617 - 11119 L) for peripheral compartment volume of distribution (V2). The estimate for postmenstrual age when 50% of adult clearance is achieved was 42.0 weeks (41.5 - 42.5 weeks) and the Hill coefficient estimate was 7.04 (6.99 - 7.08). Genotype was not statistically or clinically significant.

ConclusionOur study demonstrates the use of real-world EHR data and remnant specimens to perform a population PK analysis and investigate covariate effects in a large pediatric population. Weight and age were important predictors of clearance. We did not find evidence for pharmacogenetic effects of UGT1A4 or UGT2B10 genotype or CYP2A6 risk score.

What is already known about this subject{circ} Previous dexmedetomidine pharmacokinetic (PK) studies in pediatric populations have limited sample size.
{circ}Smaller studies present a challenge for identifying covariates that may impact individual PK profiles.


What this study adds{circ} We performed a dexmedetomidine population PK study with a large pediatric cohort using data obtained from electronic health records and remnant plasma specimens to enable increased sample size.
{circ}xsDifferences in PK due to UGT1A4 or UGT2B10 variants or CYP2A6 risk score are not clinically impactful for this population. Decoding hand and wrist movement intention from chronic stroke survivors with hemiparesis using a user-friendly, wearable EMG-based neural interface Prosthetics and orthotics have been recognized for decades as a potential means to restore hand function and independence to individuals living with impairment due to stroke. However, 75% of stroke survivors, caregivers, and health care professionals (HCP) believe current practices are insufficient, specifically calling out the upper extremity as an area where innovation is needed to develop highly usable prosthetics/orthotics for the stroke population. A promising method for controlling upper limb technologies is to infer movement intent non-invasively from surface electromyography (EMG) activity. While this approach has garnered significant attention in the literature, existing technologies are often limited to research settings and struggle to meet stated user needs. To address these limitations, we have developed the NeuroLife(R) EMG System, which consists of a wearable forearm sleeve with 150 embedded electrodes and associated hardware and software to record and decode surface EMG. Here, we demonstrate accurate decoding of 12 functional hand, wrist, and forearm movements, including multiple types of grasps from participants with varying levels of chronic impairment from stroke, with an overall accuracy of 77.1{+/-}5.6%. Importantly, we demonstrate the ability to decode a subset of 3 fundamental movements in individuals with severe hand impairment at 85.4{+/-}6.4% accuracy, highlighting the potential as a control mechanism for assistive technologies. Feedback from stroke survivors who tested the system indicates that the sleeves design meets various user needs, including being comfortable, portable, and lightweight. The sleeve is in a form factor such that it can be used at home without an expert technician and can be worn for multiple hours without discomfort. Taken together, the NeuroLife EMG System represents a platform technology to record and decode high-definition EMG for the eventual real-time control of assistive devices in a form factor designed to meet user needs. Reflex single-gene non-invasive prenatal testing significantly increases the cost-effectiveness of carrier screening ObjectiveTo evaluate the clinical and cost savings benefits of adoption of a carrier screen with reflex single-gene non-invasive prenatal test (sgNIPT) in prenatal care.

MethodA decision-analytic model was developed to compare carrier screen with reflex sgNIPT (maternal carrier status and fetal risk reported together) as first-line carrier screening to the traditional carrier screening workflow (positive maternal carrier screen followed by paternal screening to evaluate fetal risk). The model compared the clinical outcomes and cost effectiveness between the two screening methods. These results were used to simulate appropriate pricing for reflex sgNIPT.

ResultsReflex sgNIPT carrier screening detected 108 of 110 affected pregnancies per 100,000 births (98.5% sensitivity), whereas traditional carrier screening detected 46 of 110 affected pregnancies (41.5% sensitivity). The cost to identify one affected pregnancy was reduced by 62% in the reflex sgNIPT scenario compared to the traditional scenario. Adding together the testing cost savings and the savings from earlier clinical intervention made possible by reflex sgNIPT, the total cost savings was $37.6 million per 100,000 pregnancies. Based on these cost savings, we simulated appropriate reflex sgNIPT pricing range: if the cost to identify one affected pregnancy is the unit cost, carrier screening with reflex sgNIPT can be priced up to $1,859 per test (or $7,233 if sgNIPT is billed separately); if the cost per 100,000 pregnancies is the unit cost, carrier screening with sgNIPT can be priced up to $1,070 per test (or $2,336 if sgNIPT is billed separately).

ConclusionUsing the carrier screen with reflex sgNIPT as first-line screening improves the detection of affected fetuses by 2.4-fold and can save costs for the healthcare system. A real-life experience will be needed to assess the clinical utility and exact cost savings of carrier screen with reflex sgNIPT. Pausing methotrexate improves immunogenicity of COVID-19 vaccination in elderly patients with rheumatic diseases ObjectiveTo study the effect of methotrexate (MTX) and its discontinuation on the humoral immune response after COVID-19 vaccination in patients with autoimmune rheumatic diseases (AIRD).

MethodsNeutralising SARS-CoV-2 antibodies were measured after second vaccination in 64 rheumatic patients on methotrexate therapy, 31 of whom temporarily paused medication without a fixed regimen. The control group consisted of 21 AIRD patients without immunosuppressive medication.

ResultsMTX patients showed a significantly lower median antibody response compared to AIRD patients without immunosuppressive therapy (p< 0.001). Young age (<60 years) and MTX-hold after vaccination were found to be the main factors influencing antibody response after vaccination, while BMI or MTX dose demonstrated no effect. For patients taking MTX, age correlated negatively with immune response (r=-0.49; p<0.001) and all patients with antibody levels (14 %) below the cut-off were older than 60 years. Patients who held MTX during at least one vaccination showed significantly higher median neutralising antibody levels after second vaccination, compared to patients who continued MTX therapy during both vaccinations (68.82 %, 92.73 %, p=<0.001). This effect was particularly pronounced in patients older than 60 years (p=0.0016). The impact of the time period after vaccination was greater than of the time before vaccination with the critical cut-off being 10 days.

ConclusionMTX reduces the immunogenicity of SARS-CoV-2 vaccination in an age-dependent manner. Our data further suggest that holding MTX for at least 10 days after vaccination significantly improves the antibody response in patients over 60 years of age. Thromboembolism risk among patients with diabetes/stress hyperglycemia and COVID-19 AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSPurposeC_ST_ABSIndividuals with diabetes/stress hyperglycemia carry an increased risk for adverse clinical outcome in case of SARS-CoV-2 infection. The purpose of this study was to evaluate whether this risk is, at least in part, modulated by an increase of thromboembolic complications.

MethodsWe prospectively followed 180 hospitalized patients with confirmed COVID-19 pneumonia admitted to the Internal Medicine Units of San Raffaele Hospital. Data from 11 out of 180 patients were considered incomplete and excluded from the analysis. We analysed inflammation, tissue damage biomarkers, hemostatic parameters, thrombotic events (TEs) and clinical outcome according to the presence of diabetes/stress hyperglycemia.

ResultsAmong 169 patients, 51 (30.2%) had diabetes/stress hyperglycemia. Diabetes/stress hyperglycemia and fasting blood glucose (FBG) were associated with increased inflammation and tissue damage circulating markers, higher D-dimer levels, increased prothrombin time and lower antithrombin III activity. Forty-eight venous and 10 arterial TEs were identified in 49 (29%) patients. Diabetes/stress hyperglycemia (HR 2.71, p=0.001), fasting blood glucose (HR 4.32, p<0.001) and glucose variability (HR 1.6, p < 0.009) were all associated with an increased risk of thromboembolic complication. TEs significantly increased the risk for an adverse clinical outcome only in the presence of diabetes/stress hyperglycemia (HR 3.05, p=0.01) or fasting blood glucose [&ge;] 7 mmol/l (HR 3.07, p=0.015).

ConclusionsThromboembolism risk is higher among patients with diabetes/stress hyperglycemia and COVID-19 pneumonia and is associated to poor clinical outcome. In case of SARS-Cov-2 infection patients with diabetes/stress hyperglycemia could be considered for a more intensive prophylactic anticoagulation regimen. Strain-resolved analysis in a randomized trial of antibiotic pretreatment and maintenance dose delivery mode with fecal microbiota transplant for ulcerative colitis Fecal microbiota transplant is a promising therapy for ulcerative colitis. Parameters maximizing effectiveness and tolerability are not yet clear, and it is not known how import the transmission of donor microbes to patients is. Here (clinicaltrails.gov: NCT03006809) we have tested the effects of antibiotic pretreatment and compared two modes of maintenance dose delivery, capsules versus enema, in a randomized, pilot, open-label, 2x2 factorial design with 22 patients analyzed with mild to moderate UC. Clinically, the treatment was well-tolerated with favorable safety profile. Of patients who received antibiotic pretreatment, 6 of 11 experienced remission after six weeks of treatment, versus 2 of 11 non-pretreated patients (odds ratio: 1.69, 95% confidence interval: -0.25 to 3.62). No significant differences were found between maintenance dosing via capsules versus enema. In exploratory analyses, microbiome turnover at both the species and strain levels was extensive and significantly more pronounced in the pretreated patients. Associations were also revealed between taxonomic turnover and changes in the composition of primary and secondary bile acids. Together these findings suggest that antibiotic pretreatment contributes to microbiome engraftment and possibly clinical effectiveness, and validate longitudinal strain tracking as a powerful way to monitor the dynamics and impact of microbiota transfer. Culture and understanding the role of feedback for health professions students: Realist synthesis protocol. IntroductionClinical education has moved to a "competency-based" model with an emphasis on workplace-based learning and assessment which, in turn, depends on feedback to be effective. Further, the understanding of feedback has changed from information about a performance directed to the learner performing the task, to a dialogue, which enables the learner to act and develop.

In health professional education, feedback is a complex interaction between trainee, supervisor, and the healthcare system. Most published research on feedback in health professional education originates in Europe and North America. Our interest is on the impact of Culture on this process, particularly in the context of Asian cultures.

The (scientific) realist approach of Pawson and Tilley provides a means to examine complex interventions in social situations, and thus is an appropriate lens to use for this study. This is a protocol for a realist synthesis which asks how, why and in what circumstances do Asian Cultures influence health professional trainees to seek, respond to and use feedback given in the clinical environment, if at all.

Methods and analysisAn initial search was performed to help define the scope of the review question and develop our initial program theory. The formal electronic search was carried out in February 2020 and included: CINAHL, ERIC, MEDLINE, and PsycInfo, and repeated in October 2020.

Retrieved articles were imported into Covidence for screening and data extraction, after which components of the Context - Mechanisms - Outcomes configurations will be sought to refine the initial program theory.

Ethics and DisseminationAs this study is a literature review, ethics approval is not required.

The findings will be documented in line with the RAMESES publications standards for Realist syntheses,[41] and we plan to disseminate the findings by means of a peer-reviewed journal article and conference presentation(s).

Strengths and limitations of this studyO_LIThe synthesis aims to identify the how and why Asian Cultures may influence feedback seeking and provision to health professional trainees, if at all.
C_LIO_LITo our knowledge, there are few studies of feedback seeking and provision to health professional trainees in Asia.
C_LIO_LIA Realist approach has the potential to help explain the complex nature of Cultures impact on feedback.
C_LIO_LIOnly studies published in the English language will be included, so transferability of our findings to non-English speaking environments may be lacking.
C_LIO_LIIn addition to formal literature database searches, we will need to conduct citation mining to locate other relevant resources.
C_LI Impact of a Multidisciplinary Nutritional Support Team on Quality Improvement in Home Parenteral Nutrition IntroductionHPN is essential for patients requiring long term nutritional support. This Quality Improvement Project for HPN Patients (QIP-PN) studied the effect of a Physician Nutrition Expert (PNE)- led multidisciplinary nutritional support team (MNST) on HPN care.

ObjectiveTo test the effect of an MNST on adherence to protocols, outcomes and QOL in HPN.

MethodsData review was conducted in phases 1a and 1b, observation in phase 2 and intervention in phase 3. In Phase 3 the MNST made recommendations to treating physicians. All long-term HPN patients were offered study participation. 75 signed consent forms. Treating physician study participation agreements were signed for 42 patients (the study group). A random sample of 30 long-term HPN patients comprised the case-matched control group (control). Data were collected on demographics, treating physicians PNE status, HPN care variables, recommended interventions, quality-of-life assessment, adverse outcomes and hospitalizations. Independent samples t-test was used for continuous data between study group and control group. Paired t-test was used for phase 2 and phase 3 patient data. Comparison between the study and control group utilized a negative binomial regression model. Statistical analysis utilized R (https://www.r-project.org/).

Results34 patients were reviewed retrospectively in phase 1a and 197 prospectively in phase 1b. 40 study patients completed phase 2 and progressed into phase 3, of whom 30 completed [&ge;]60 therapy days. Improvements in weight, BMI and QOL were seen in the study patients during intervention. Recommendations made and accepted by treating physicians differed based on PNE status. Study patients had fewer adverse outcomes and related hospitalizations than case matched controls.

ConclusionMNST recommendations improved clinical, biochemical parameters and patients self-reported overall health. It reduced adverse outcomes, hospitalization and hospital length of stay. MNST input could have a significant impact on the quality and cost of HPN care. Detection of Somatic Copy Number Deletion of CDKN2A Gene for Clinical Practices Based on Discovery of A Base-Resolution Common Deletion Region BackgroundCDKN2A is most frequently inactivated by somatic copy number deletion (SCND) in human cancers. An accurate method to detect CDKN2A SCND is absent.

MethodsTo look for the pattern of CDKN2A SCND in cancer cells, interstitial base-resolution deletion/fusion coordinates for CDKN2A were extracted from published articles and our whole genome sequencing (WGS) datasets. A multiplex PCR assay was setup to quantify CDKN2A copy number and confirmed with WGS and loss of heterozygosity (LOH) assays using gastric carcinoma (GC) samples from two sets of patients (n=156 and 140), respectively.

ResultsWe characterized a 5.1-kb common deletion region (CDR) from the CDKN2A/P16INK4A promoter to intron-2 in >90% (83/92) of cancer cell lines and 100% (18/18) of GC samples by WGS. The CDR includes exon-2 that is shared by P16INK4A and P14ARF genes. Then, a highly reproducible and quantitative assay, P16-Light, targeted to the CDR was setup with a lower limit of detection at 20%. P16-Light was further compared with WGS (gold standard) and LOH assay by denaturing high performance liquid chromatography. The positive rate of CDKN2A SCND by P16-Light was more than two times of that by WGS in GCs from a patients cohort (25.6% vs. 10.9%), and was significantly correlated with each other (p<0.028). While CDKN2A SCND was significantly associated with GC distant metastasis (p=0.023), such association was not observed for CDKN2A LOH.

ConclusionBased on our finding that there is a 5.1-kb CDR within the CDKN2A gene, a vary convenient P16-Light assay was setup to detect CDKN2A SCND for routine clinical applications. Chemosensory dysfunctions induced by COVID-19 can persist up to 7 months: A study of over 700 healthcare workers Several studies have revealed either self-reported chemosensory alterations in large groups or objective quantified chemosensory impairments in smaller populations of patients diagnosed with COVID-19. However, due to the great variability in published results regarding COVID-19-induced chemosensory impairments and their follow-up, prognosis for chemosensory functions in patients with such complaints remains unclear. Our objective is to describe the various chemosensory alterations associated with COVID-19 and their prevalence and evolution after infection. A cross-sectional study of 704 healthcare workers with a RT-PCR confirmed SARS-CoV-2 infection between 28/2/2020 and 14/6/2020 was conducted 3 to 7 months after onset of symptoms. Data were collected with an online questionnaire. Outcomes included differences in reported chemosensory self-assessment of olfactory, gustatory, and trigeminal functions across time points and Chemosensory Perception Test scores from an easy-to-use at-home self-administered chemosensory test. Among the 704 participants, 593 (84.2%) were women, the mean (SD) age was 42 (12) years, and the questionnaire was answered on average 4.8 (0.8) months after COVID-19. During COVID-19, a decrease in olfactory, gustatory, and trigeminal sensitivities were reported by 81.3%, 81.5% and 48.0% respectively. Three to seven months later, reduced sensitivity was still reported by 52.0%, 41.9% and 23.3% respectively. Chemosensory Perception Test scores indicate that 19.5% of participants had objective olfactory impairment. These data suggest a significant proportion of COVID-19 cases have persistent chemosensory impairments at 3 to 7 months after their infection but the majority of those who had completely lost their olfactory, gustatory, and trigeminal sensitivity have improved. Deep learning for caries detection using optical coherence tomography Early detection of dental caries has been one of the most predominant topics studied over the last few decades. Conventional examination through visual-tactile inspection and radiography can be inaccurate and destructive to the tooth structure. The development of optical coherence tomography (OCT) has given dentistry an alternative diagnostic technique, which has been proven by numerous studies, that it has better sensitivity, specificity, and non-invasive characteristics. The growing popularity of artificial intelligence (AI) also contributes to a more efficient and effective way of image-based detection and decision-making. However, previous studies, which have attempted to employ AI for caries assessment, did not incorporate high-quality ground truth data. Therefore, this study aims to bypass this issue and highlights the importance of high-quality data. A two-phase study was carried out to explore different methods for caries detection. Initially, the comparison of caries detection based on OCT and apical radiography by 5 experienced clinicians was conducted. Then, five convolutional neural networks (CNNs), including AlexNet, VGG-16, ResNet-152, Xception, and ResNext-101, in the scope of AI were employed to detect caries and compared with the findings of the 5 clinicians. The data was preprocessed and labeled with the ground truth corresponding to microcomputed tomography (micro-CT) with rigorous definition. The weighted Kappa statistics suggested that OCT ({varkappa}= .699, SD = .090) showed a higher accuracy rate than radiography ({varkappa}= .407, SD = .049), and CNNs ({varkappa}= .860, SD = .049) were rated higher than clinicians ({varkappa}= .679, SD = .113), both at a .05 significance level. The best result was carried out by ResNet-152, which demonstrated a high accuracy rate of 95.21% and a sensitivity of 98.85%. These findings illustrate the importance of ground truth data for AI training and the potential of deep CNN algorithms combined with OCT for diagnosing dental caries. The kidney releases a non-polymerizing form of Uromodulin in the urine and circulation that retains the external hydrophobic patch domain Uromodulin (Tamm-Horsfall protein, THP) is a glycoprotein uniquely produced in the kidney. It is released by cells of the thick ascending limbs (TAL) apically in the urine, and basolaterally in the renal interstitium and systemic circulation. Processing of mature urinary THP, which polymerizes into supra-molecular filaments, requires cleavage of an external hydrophobic patch (EHP) at the C terminus. However, THP in the circulation is not polymerized, and it remains unclear if non-aggregated forms of THP exist natively in the urine. We propose that an alternative processing path, which retains the EHP domain, can lead to a non-polymerizing form of THP. We generated an antibody that specifically recognizes THP with retained EHP (THP+EHP) and established its presence in the urine in a non-polymerized native state. Proteomic characterization of urinary THP+EHP revealed its C-terminus to end at F617. In the human kidney, THP+EHP was not only detected in TAL cells, but also diffusely in the renal parenchyma. Using immunoprecipitation followed by proteomic sequencing and immunoblotting, we then demonstrated that serum THP has also retained EHP. In a small cohort of patients at risk for acute kidney injury (AKI), admission urinary THP+EHP was significantly lower in patients who subsequently developed AKI during hospitalization. Our findings uncover novel insights into uromodulin biology by establishing the presence of an alternative path for cellular processing, which could explain the release of non-polymerizing THP in the circulation. Larger studies are needed to establish the utility of urinary THP+EHP as a sensitive biomarker of kidney health and susceptibility to injury. In depth analysis of patients with severe SARS-CoV-2 in sub-Saharan Africa demonstrates distinct clinical and immunological profiles Although the COVID-19 pandemic has left no country untouched there has been limited research to understand clinical and immunological responses in African populations. Here we comprehensively characterise patients hospitalised with suspected or confirmed COVID-19, and healthy community controls. PCR-confirmed COVID-19 participants were more likely to receive dexamethasone and a beta-lactam antibiotic, and survive to hospital discharge than PCR-/IgG+ and PCR-/IgG-participants. PCR-/IgG+ participants exhibited a nasal and systemic cytokine signature analogous to PCR-confirmed COVID-19 participants, but increased propensity for Staphylococcus aureus and Streptococcus pneumoniae colonisation. We did not find evidence that HIV co-infection in COVID-19 participants was associated with mortality or altered cytokine responses. The nasal immune signature in PCR-/IgG+ and PCR-confirmed COVID-19 participants was distinct and predominated by chemokines and neutrophils. In addition, PCR-/IgG+ individuals with high COVID-19 clinical suspicion had inflammatory profiles analogous to PCR-confirmed disease and potentially represent a target population for COVID-19 treatment strategies. Substance Use Onset in High-Risk 9-13 Year-Olds in the ABCD Study AimA key aim of the Adolescent Brain Cognitive DevelopmentSM (ABCD) Study is to document substance use onset, patterns, and sequelae across adolescent development. However, substance use misreporting obscures accurate drug use characterization. Hair toxicology tests provide objective historical substance use data, but are rarely investigated in youth. Here, we compare objective hair toxicology results with self-reported substance use in youth.

MethodsA literature-based substance use risk algorithm identified 696 ABCD Study(R) participants for hair sample collections between baseline and 2-year follow-up (spanning ages 9-13) for laboratory analysis. Chi-square and t-tests assessed differences between participants demographics, positive and negative hair tests, risk algorithm scores, and self-reported substance use.

ResultsHair testing confirmed that 17% of at-risk 9-13 year-olds had evidence of past 3-month use of one (n=99), two (n=17), three (n=3), or four (n=2) drug classes. After considering prescribed medication use, 11% had a positive test incongruent with self- or parent-report. No participant with a positive result self-reported substance use consistent with their toxicology results. Participants with positive tests under-reported use (p<.001), reported less sipping of alcohol (p<.001), and scored higher on the risk algorithm (p<.001) than those with negative hair toxicology.

ConclusionsAn alarming 11% of tested samples in at-risk 9-13 year-olds were positive for at least one unreported substance, suggesting underreporting in this population when participating in a national healthy development study. The degree of underreporting cannot yet be calculated, as at-risk samples were prioritized for assays. Expanded toxicology testing is key to characterize substance use in youth. Development and validation of a multimodal neuroimaging biomarker for electroconvulsive therapy outcome in depression: a multicenter machine learning analysis BackgroundElectroconvulsive therapy (ECT) is the most effective intervention for patients with treatment resistant depression. A clinical decision support tool could guide patient selection to improve the overall response rate and avoid ineffective treatments with adverse effects. Initial small-scale, mono-center studies indicate that both structural magnetic resonance imaging (sMRI) and functional MRI (fMRI) biomarkers may predict ECT outcome, but it is not known whether those results can generalize to data from other centers.

ObjectiveTo develop and validate neuroimaging biomarkers for ECT outcome in a multi-center setting.

MethodsMultimodal data (i.e., clinical, sMRI and resting-state fMRI) was collected from seven centers of the Global ECT-MRI Research Collaboration (GEMRIC). We used data from 189 depressed patients to evaluated which data modalities or combinations thereof could provide the best predictions for treatment response ([&ge;]50% symptom reduction) or remission (HAM-D score [&le;]7) using a support vector machine classifier.

ResultsRemission classification using a combination of gray matter volume and functional connectivity led to good performing models with average 0.82-0.83 area under the curve (AUC) when trained and tested on samples coming from the three largest centers, and remained acceptable when validated using leave-one-site-out cross-validation (0.70-0.73 AUC).

ConclusionsThese results show that multimodal neuroimaging data is able to provide good prediction of remission with ECT for individual patients across different treatment centers, despite significant variability in clinical characteristics across centers. This suggests that these biomarkers are robust, indicating that future development of a clinical decision support tool applying these biomarkers may be feasible. Complementary frailty and mortality prediction models on older patients as a tool for assessing palliative care needs BackgroundPalliative care (PC) has demonstrated benefits for life-limiting illnesses. Cancer patients have mainly accessed these services, but there is growing consensus about the importance of promoting access for patients with non-malignant disease. Bad survival prognosis and patients frailty are usual dimensions to decide PC inclusion.

ObjectivesThe main aim of this work is to design and evaluate three quantitative models based on machine learning approaches to predict frailty and mortality on older patients in the context of supporting PC decision making: one-year mortality, survival regression and one-year frailty classification.

MethodsThe dataset used in this study is composed of 39,310 hospital admissions for 19,753 older patients (age >= 65) from January 1st, 2011 to December 30th, 2018. All prediction models were based on Gradient Boosting Machines. From the initial pool of variables at hospital admission, 20 were selected by a recursive feature elimination algorithm based on the random forests GINI importance criterion. Besides, we run an independent grid search to find the best hyperparameters in each model. The evaluation was performed by 10-fold cross-validation and area under the receiver operating characteristic curve and mean absolute error were reported. The Cox proportional-hazards model was used to compare our proposed approach with classical survival methods.

ResultsThe one-year mortality model achieved an AUC ROC of 0.87 {+/-} 0.01; the mortality regression model achieved an MAE of 329.97 {+/-} 5.24 days. The one-year frailty classification reported an AUC ROC of 0.9 {+/-} 0.01. The Spearmans correlation between the admission frailty index and the survival time was -0.1, while the point-biserial correlation between one-year frailty index and survival time was -0.16.

ConclusionsOne-year mortality model performance is at a state-of-the-art level. Frailty Index used in this study behaves coherently with other works in the literature. One-year frailty classifier demonstrated that frailty status within the year could be predicted accurately. To our knowledge, this is the first study predicting one-year frailty status based on a frailty index. We found mortality and frailty as two weakly correlated and complementary PC needs assessment criteria. Predictive models are available online at http://demoiapc.upv.es. Using explainable machine learning to identifypatients at risk of reattendance at discharge from emergency departments Short-term reattendances to emergency departments are a key quality of care indicator. Identifying patients at increased risk of early reattendance could help reduce the number of missed critical illnesses and could reduce avoidable utilization of emergency departments by enabling targeted post-discharge intervention. In this manuscript we present a retrospective, single-centre study where we created and evaluated an extreme gradient boosted decision tree model trained to identify patients at risk of reattendance within 72 hours of discharge from an emergency department (University Hospitals Southampton Foundation Trust, UK). Our model was trained using 35,447 attendances by 28,945 patients and evaluated on a hold-out test set featuring 8,847 attendances by 7,237 patients. The set of attendances from a given patient appeared exclusively in either the training or the test set. Our model was trained using both visit level variables (e.g., vital signs, arrival mode, and chief complaint) and a set of variables available in a patients electronic patient record, such as age and any recorded medical conditions. On the hold-out test set, our highest performing model obtained an AUROC of 0.747 (95% CI : 0.722-0.773) and an average precision of 0.233 (95% CI : 0.194-0.277). These results demonstrate that machine-learning models can be used to classify patients, with moderate performance, into low and high-risk groups for reattendance. We explained our models predictions using SHAP values, a concept developed from coalitional game theory, capable of explaining predictions at an attendance level. We demonstrated how clustering techniques can be used to investigate the different sub-groups of explanations present in our patient cohort. How Informative Were Early SARS-CoV-2 Treatment and Prevention Trials? A longitudinal cohort analysis of trials registered on clinicaltrials.gov BackgroundEarly in the SARS-CoV-2 pandemic, commentators warned that some COVID trials were inadequately conceived, designed and reported. Here, we retrospectively assess the prevalence of informative COVID trials launched in the first 6 months of the pandemic.

MethodsWe created a cohort of SARS-CoV-2 treatment and prevention efficacy trials that were initiated from 2020-01-01 to 2020-06-30 using ClinicalTrials.gov registration records. We evaluated trials on 3 criteria of informativeness: potential redundancy, design quality and feasibility of patient-participant recruitment. The study protocol was prospectively registered with the Open Science Framework (https://osf.io/fp726/).

ResultsWe included 500 trials in our cohort, 58% of which were Phase 2 and 84.8% were directed towards the treatment of SARS-CoV-2. Close to one third of trials met all three criteria and were deemed informative (29.0% (95% Confidence Interval 23.7 - 36.9)). The proportion of potentially redundant trials in our cohort was 4.1%. Over half of the trials in our cohort (56.2%) did not meet our criteria for high quality trial design. The proportion of trials with infeasible patient-participant recruitment was 22.6%.

ConclusionsLess than one third of COVID-19 trials registered on ClinicalTrials.gov during the first six months met all three criteria for informativeness. Shortcomings in trial design, recruitment feasibility and redundancy reflect longstanding weaknesses in the clinical research enterprise that were likely amplified by the exceptional circumstances of a pandemic. Deceased donor kidney degradomics indicates cytoskeletal proteolytic alterations impacting post-transplant function. BackgroundIn brain death, cerebral injury contributes to systemic biological dysregulation, causing significant cellular stress in donor kidneys that adversely impacts the quality of grafts. Here, we hypothesized that DBD kidneys may undergo proteolytic processes that renders grafts susceptible to post-transplant dysfunction.

Material & MethodsUsing mass spectrometry and immunoblotting analyses, we profiled degradation patterns of cytoskeletal proteins in deceased (n=55) and living (n=10) donor kidneys.

ResultsWe found that in DBD kidneys, key podocyte cytoskeletal proteins had been proteolytically cleaved. Generated degradation profiles were not associated to donor related demographic and clinical factors but were associated to suboptimal post-transplant function. Strikingly, -actinin -4 and Talin-1 degradation profiles were not observed in circulatory-death or living-donor kidneys. As Talin-1 is a specific proteolytic target of Calpain-1, we investigated a potential trigger of Calpain activation and Talin-1 degradation using ex-vivo precision-cut human kidney slices and in-vitro immortalised human podocytes. Notably, we found that Transforming-Growth Factor-{beta} (TGF-{beta}) activated Calpain-1 and proteolytically cleaved Talin-1 to generate distinct peptide fragments. These peptide fragments were of similar size and matched the degradation patterns observed in DBD kidneys. Talin-1 degradation was prevented in vitro by Calpain-1 inhibition.

ConclusionsHere, we provide initial evidence that DBD kidneys are susceptible to cytoskeletal protein degradation that impacts posttransplant kidney function. Subsequent studies should aim to further investigate the link between brain death and activation of proteolytic pathways exploring new therapeutic opportunities. Transdiagnostic Profiles of Behaviour and Communication Relate to Academic and Socioemotional Functioning and Neural White Matter Organisation BackgroundBehavioural and language difficulties co-occur in multiple neurodevelopmental conditions. Our understanding of these problems has arguably been slowed by an overreliance on study designs that compare deficit/diagnostic groups and fail to capture the overlap across different neurodevelopmental disorders and the heterogeneity within them.

MethodsWe recruited a large transdiagnostic cohort of children with complex needs (N = 805) to identify distinct subgroups of children with common profiles of behavioural and language strengths and difficulties. We then investigated whether and how these data-driven groupings could be distinguished from a comparison sample (N = 158) on measures of academic and socioemotional functioning and patterns of global and local white matter connectome organisation. Academic skills were assessed via standardised measures of reading and maths. Socioemotional functioning was captured by the parent-rated version of the Strengths and Difficulties Questionnaire.

ResultsWe identified three distinct subgroups of children, each with different levels of difficulties in structural language, pragmatic communication, and hot and cool executive functions. All three subgroups struggled with academic and socioemotional skills relative to the comparison sample, potentially representing three alternative but related developmental pathways to difficulties in these areas. The children with the weakest language skills had the most widespread difficulties with learning, whereas those with more pronounced difficulties with hot executive skills experienced the most severe difficulties in the socioemotional domain. Each data-driven subgroup could be distinguished from the comparison sample based on both shared and subgroup-unique patterns of neural white matter organisation. Children with the most pronounced deficits in language, cool executive, or hot executive function were differentiated from the comparison sample by altered connectivity in predominately thalamocortical, temporal-parietal-occipital, and frontostriatal circuits, respectively.

ConclusionThese findings advance our understanding of commonly co-morbid behavioural and language problems and their relationship to behavioural outcomes and neurobiological substrates. Transdiagnostic Profiles of Behaviour and Communication Relate to Academic and Socioemotional Functioning and Neural White Matter Organisation A cross-sectional study of infection control measures against COVID-19 and psychological distress among Japanese workers ObjectivesThis study examined the relationship between the status of infection control efforts against COVID-19 in the workplace and workers mental health using a large-scale Internet-based study.

MethodsThis cross-sectional study was based on an Internet monitoring survey conducted during the third wave of the COVID-19 epidemic in Japan. Of the 33,302 people who participated in the survey, 27,036 were included in the analyses. Participants answered whether or not each of 10 different infection control measures were in place at their workplace (e.g. wearing masks at all times during working hours). A Kessler 6 (K6) score of [&ge;]13 was defined as mild psychological distress. The odds ratios (ORs) of psychological distress associated with infection control measures at the workplace were estimated using a multilevel logistic model nested in the prefectures of residence.

ResultsThe OR of subjects working at facilities with 4 or 5 infection control measures for psychological distress was 1.19 (95% confidence interval [CI]: 1.05-1.34, p=0.010), that in facilities with 2 or 3 infection control measures was 1.43 (95% CI: 1.25-1.64, p<0.001), and that in facilities with 1 or no infection control measures was 1.87 (95% CI: 1.63-2.14, p<0.001) compared to subjects whose workplaces had [&ge;]6 infection control measures.

ConclusionOur findings suggest that proactive COVID-19 infection control measures can influence the mental health of workers. S-ketamine in patient-controlled analgesia reduces opioid consumption in a dose-dependent manner after major lumbar fusion surgery: a randomized, double-blind, placebo-controlled clinical trial BACKGROUNDSpinal fusion surgery causes severe pain. Strong opioids, commonly used as postoperative analgesics, may have unwanted side effects. S-ketamine may be an effective analgesic adjuvant in opioid patient-controlled analgesia (PCA). However, the optimal adjunct S-ketamine dose to reduce postoperative opioid consumption is still unknown.

METHODSWe randomized 107 patients at two tertiary hospitals in a double-blinded, placebo-controlled clinical trial of adults undergoing major lumbar spinal fusion surgery. Patients were randomly allocated to four groups in order to compare the effects of three different doses of adjunct S-ketamine (0.25, 0.5, and 0.75 mg ml-1) or placebo on postoperative analgesia in oxycodone PCA. Study drugs were administered for 24 hours postoperative after which oxycodone-PCA was continued for further 48 hours. Our primary outcome was cumulative oxycodone consumption at 24 hours after surgery.

RESULTSOf the 100 patients analyzed, patients receiving 0.75 mg ml-1 S-ketamine in oxycodone PCA needed 25% less oxycodone at 24 h postoperatively (61.2 mg) compared with patients receiving 0.5 mg ml-1 (74.7 mg) or 0.25 mg ml-1 (74.1 mg) S-ketamine in oxycodone or oxycodone alone (81.9 mg) (mean difference: -20.6 mg; 95% confidence interval [CI]: -41 to -0.20; P = 0.048). A beneficial effect in mean change of pain intensity at rest was seen in the group receiving 0.75 mg ml-1 S-ketamine in oxycodone PCA compared with patients receiving lower ketamine doses or oxycodone alone (standardized effect size: 0.17, 95% CI: 0.013-0.32, P = 0.033). The occurrence of adverse events was similar among the groups.

CONCLUSIONSOxycodone PCA containing S-ketamine as an adjunct at a ratio of 1: 0.75 decreased cumulative oxycodone consumption at 24 h after major lumbar spinal fusion surgery without additional adverse effects. Empirical networks for localized COVID-19 interventions using WiFi infrastructure at university campuses Infectious diseases, like COVID-19, pose serious challenges to university campuses, which typically adopt closure as a non-pharmaceutical intervention to control spread and ensure a gradual return to normalcy. Intervention policies, such as remote instruction (RI) where large classes are offered online, reduce potential contact but also have broad side-effects on campus by hampering the local economy, students learning outcomes, and community wellbeing. In this paper, we demonstrate that university policymakers can mitigate these tradeoffs by leveraging anonymized data from their WiFi infrastructure to learn community mobility --- a methodology we refer to as WiFi mobility models (WO_SCPLOWIC_SCPLOWMO_SCPLOWOBC_SCPLOW). This approach enables policymakers to explore more granular policies like localized closures (LC). WO_SCPLOWIC_SCPLOWMO_SCPLOWOBC_SCPLOW can construct contact networks that capture behavior in various spaces, highlighting new potential transmission pathways and temporal variation in contact behavior. Additionally, WO_SCPLOWIC_SCPLOWMO_SCPLOWOBC_SCPLOW enables us to design LC policies that close super-spreader locations on campus. By simulating disease spread with contact networks from WO_SCPLOWIC_SCPLOWMO_SCPLOWOBC_SCPLOW, we find that LC maintains the same reduction in cumulative infections as RI while showing greater reduction in peak infections and internal transmission. Moreover, LC reduces campus burden by closing fewer locations, forcing fewer students into completely online schedules, and requiring no additional isolation. WO_SCPLOWIC_SCPLOWMO_SCPLOWOBC_SCPLOW can empower universities to conceive and assess a variety of closure policies to prevent future outbreaks. A Randomised Trial of a Wearable UV dosimeter for Skin Cancer Prevention BackgroundNon-melanoma skin cancer (NMSC) is the most prevalent cancer in the United States, affecting 5 million people and costing $8.1 billion per year. Despite well-defined guidelines on ultraviolet radiation (UVR) avoidance, it remains difficult for people to assess their individual exposure, as UVR is invisible and the onset of symptoms due to UVR damage are delayed.

MethodsIn a prospective, randomized-controlled trial, 97 patients with a history of actinic keratoses were enrolled from March 2018 to July 2018 and followed over 6 months. 50 patients were given a wearable device that measured UV exposure and a smartphone application that provided both real-time and cumulative UV exposure information, and 47 patients were provided with UV protection counseling by a dermatologist.

ResultsWe observed a significant decrease in the incidence rate of NMSC in the intervention group compared to the control group over 3 months (p = 0.02). We did not observe a significant decrease in the incidence rate of actinic keratoses (AK) in the intervention group compared to the control group. The observed clinical benefit was not accompanied by psychological side effects such as anxiety and depression.

ConclusionsThis study suggests that providing real-time UV exposure data using a wearable UV dosimeter is a safe and effective behavioral change strategy to prevent NMSC. (Funded by the National Cancer Institute, contract HHSN261201700005C; ClinicalTrials.gov number NCT03315286.)