Fitness barriers to spread of colistin resistance overcome by first establishing niche in patients with enhanced colistin exposure There is an urgent need to improve our understanding of how new antibiotic resistant organisms emerge and spread. A high-priority resistance threat is the ST258 lineage of carbapenem-resistant Klebsiella pneumoniae. Here, we studied resistance to the last-line drug colistin among ST258 by tracking its evolution across 21 U.S. hospitals over the course of a year. Phylogenetic analysis supported a significant fitness cost being associated with resistance, as resistance emergence was common but resistance variants were rarely transmitted. Furthermore, several resistance variants that were transmitted had acquired secondary variants that reverted the strain to susceptible. The exceptions to the general pattern of instability associated with resistance were two large clusters of resistant strains in one sublineage (clade IIB) present across Southern California hospitals. Quantification of transmission fitness in the healthcare environment indicated that, while resistant isolates from other clades were less fit than their susceptible counterparts, clade IIB resistant isolates were more fit, despite having similar resistance variants. Additional analyses supported the increased fitness of colistin-resistant clade IIB isolates being driven by a lineage-defining variant that increased clade IIBs association with patient subpopulations with enhanced colistin exposure. These results show that a favorable genetic background and sustained selective pressure led to the emergence and spread of a colistin-resistant ST258 sublineage across a regional healthcare network. These findings highlight the utility of integrating pathogen genomic and corresponding clinical data from regional healthcare networks to detect emerging antibiotic resistance threats and understand the clinical practices and patient populations that drive their spread.

Significance StatementSelective pressure in hospitals leads to frequent antibiotic resistance evolution. However, emergent resistance alleles are often not transmitted to other individuals because of fitness costs associated with resistance. Due to the difficulty of studying pathogen fitness in humans, our understanding of how resistant organisms circumvent these costs is limited. We integrate genomic and clinical data to understand the evolutionary trajectories leading to transmissible resistance for the last-line antibiotic colistin. While colistin resistance is generally associated with a fitness cost that hinders transmission, this cost was mitigated in a sublineage that had previously acquired mutations increasing its association with patient populations more likely to receive colistin, suggesting a key role for historical contingency in the emergence and spread of stable resistance.
Immuno-fibrotic drivers of impaired lung function in post-acute sequelae of SARS-CoV-2 infection (PASC) IntroductionSubjects recovering from COVID-19 frequently experience persistent respiratory ailments; however, little is known about the underlying biological factors that may direct lung recovery and the extent to which these are affected by COVID-19 severity.

MethodsWe performed a prospective cohort study of subjects with persistent symptoms after acute COVID-19, collecting clinical data, pulmonary function tests, and plasma samples used for multiplex profiling of inflammatory, metabolic, angiogenic, and fibrotic factors.

ResultsSixty-one subjects were enrolled across two academic medical centers at a median of 9 weeks (interquartile range 6-10) after COVID-19 illness: n=13 subjects (21%) mild/non-hospitalized, n=30 (49%) hospitalized/non-critical, and n=18 subjects (30%) hospitalized/intensive care ("ICU"). Fifty-three subjects (85%) had lingering symptoms, most commonly dyspnea (69%) and cough (58%). Forced vital capacity (FVC), forced expiratory volume in 1 second (FEV1), and diffusing capacity for carbon monoxide (DLCO) declined as COVID-19 severity increased (P<0.05), but did not correlate with respiratory symptoms. Partial least-squares discriminant analysis of plasma biomarker profiles clustered subjects by past COVID-19 severity. Lipocalin 2 (LCN2), matrix metalloproteinase-7 (MMP-7), and hepatocyte growth factor (HGF) identified by the model were significantly higher in the ICU group (P<0.05) and inversely correlated with FVC and DLCO (P<0.05), and were confirmed in a separate validation cohort (n=53).

ConclusionsSubjective respiratory symptoms are common after acute COVID-19 illness but do not correlate with COVID-19 severity or pulmonary function. Host response profiles reflecting neutrophil activation (LCN2), fibrosis signaling (MMP-7), and alveolar repair (HGF) track with lung impairment and may be novel therapeutic or prognostic targets.

FundingThe study was funded in part by the NHLBI (K08HL130557 to BDK and R01HL142818 to HJC), the DeLuca Foundation Award (AP), a donation from Jack Levin to the Benign Hematology Program at Yale, and Divisional/Departmental funds from Duke University.
Hairpin structure facilitates multiplex high-fidelity DNA amplification in real-time PCR Clinically and biologically, it is essential to detect rare DNA-sequence variants for early cancer diagnosis or drug-resistance mutations identification. Some of the common quantitative PCR (qPCR)-based variant detection methods are restricted in the limit of detection (LoD) because the DNA polymerases used have a high polymerase misincorporation rate, thus the detection sensitivity is sometimes unsatisfactory. With the proofreading activity, high-fidelity (HiFi) DNA polymerases have a 50- to 250-fold higher fidelity. However, there are currently no proper probe-based designs as the fluorescence indicator allowing multiplexed HiFi qPCR reactions, thus restricting the application of HiFi DNA polymerases like the variant detection. We presented the Occlusion System, composed of a 5-overhanged primer with fluorophore modification and a probe with a short-stem hairpin and a 3 quencher modification. We demonstrated that the Occlusion System allowed multiplexing HiFi qPCR reaction, and it was compatible with the current variant-enrichment method to improve the LoD up to 10-fold. Thus, the Occlusion System satisfactorily functioned as efficient fluorescence indicator in HiFi qPCR reactions and allowed application of HiFi DNA polymerases in variant detection methods to improve detection sensitivity. "What do you mean I can't have a doctor? This is Canada!" - A Qualitative Study of the Myriad Consequences for Unattached Patients Awaiting Primary Care Attachment BackgroundPatient access to primary healthcare (PHC) is the foundation of a strong healthcare system and healthy populations. Attachment to a regular PHC provider, a key to healthcare access, has seen a decline in some jurisdictions. This study explored the consequences of unattachment from a patient perspective, an under-studied phenomenon to date.

MethodsA realist-informed qualitative study was conducted with unattached patients in Nova Scotia, Canada. Semi-structured interviews with nine participants were conducted and transcribed for analysis. The framework method was used to carry out analysis, which was guided by Donabedians model of assessing healthcare access and quality.

ResultsFive key findings were noted in this study: 1) Participants experienced a range of consequences from not having a regular PHC provider. Participants used creative strategies to 2) attempt to gain attachment to a regular PHC provider, and, to 3) address their health needs in the absence of a regular PHC provider. 4) Participants experienced negative feelings about themselves and the healthcare system, and 5) stress related to the consequences and added work of being unattached and lost care.

ConclusionsUnattached patients experienced a burden of care related to lost care and managing their own health and related information, due to the download of medical record management and system navigation to them. These findings may underestimate the consequences for further at-risk populations who would not have been included in our recruitment. This may result in poorer health outcomes, which could be mitigated by interventions at the structural level, such as enhanced centralized waitlists to promote attachment. Such waitlists may benefit from a triage approach to appropriately attach patients based on need. Development of machine learning models for the prediction of complications after colonic, colorectal and small intestine anastomosis in psychiatric and non-psychiatric patient collectives (PSTUDY) Psychiatric and psychosomatic diseases are an increasingly cumbersome burden for the medical system. Indeed, hospital costs associated with mental health conditions have been constantly on the rise in recent years. Moreover, psychiatric conditions are likely to have a negative effect on the treatment of other medical conditions and surgical outcomes, in addition to their direct effects on the overall quality of life. Our study aims to investigate the impact of preoperative Risk factor, psychiatric and psychosomatic diseases on the outcomes of colorectal surgery and length of hospital stay via predictive modeling techniques.

MethodPatient data will be collected from several participating national and international surgical centers The machine learning models will be calculated and coded, but also published according to the TRIPOD guidelines (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis).

ResultIt is conceivable to arrive at generalizable models predicting the abovementioned endpoints through large amounts of data from several centers. The models will be subsequently deployed as a free-to-use web-based prediction tool using the Shiny environment [47]. The cost for the hosting server and digital infrastructure will be covered by Dr. Anas Taha. The sponsor will store the data for ten years. Signals of significantly increased vaccine breakthrough, decreased hospitalization rates, and less severe disease in patients with COVID-19 caused by the Omicron variant of SARS-CoV-2 in Houston, Texas Genetic variants of SARS-CoV-2 continue to dramatically alter the landscape of the COVID-19 pandemic. The recently described variant of concern designated Omicron (B.1.1.529) has rapidly spread worldwide and is now responsible for the majority of COVID-19 cases in many countries. Because Omicron was recognized very recently, many knowledge gaps exist about its epidemiology and clinical severity and disease course. A comprehensive genome sequencing study of SARS-CoV-2 in the Houston Methodist healthcare system identified 862 symptomatic patients with infections caused by Omicron from late November 2021 through December 18, 2021. Omicron very rapidly increased in only three weeks to cause 90% of all new COVID-19 cases. Compared to patients infected with either Alpha or Delta variants in our healthcare system, Omicron patients were significantly younger, had significantly increased vaccine breakthrough rates, and were significantly less likely to be hospitalized. Omicron patients required less intense respiratory support and had a shorter length of hospital stay, consistent with decreased disease severity. Although the number of Omicron patients we studied is relatively small, in the aggregate the data document the unusually rapid spread and increased occurrence of COVID-19 caused by the Omicron variant in metropolitan Houston, and provide information about disease character. 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. Machine Learning Approaches for Binary Classification to Discover Liver Diseases using Clinical Data For a medical diagnosis, health professionals use different kinds of pathological ways to make a decision for medical reports in terms of patients medical condition. In the modern era, because of the advantage of computers and technologies, one can collect data and visualize many hidden outcomes from them. Statistical machine learning algorithms based on specific problems can assist one to make decisions. Machine learning data driven algorithms can be used to validate existing methods and help researchers to suggest potential new decisions. In this paper, Multiple Imputation by Chained Equations was applied to deal with missing data, and Principal Component Analysis to reduce the dimensionality. To reveal significant findings, data visualizations were implemented. We presented and compared many binary classifier machine learning algorithms (Artificial Neural Network, Random Forest, Support Vector Machine) which were used to classify blood donors and non-blood donors with hepatitis, fibrosis and cirrhosis diseases. From the data published in UCI-MLR, all mentioned techniques were applied to find one better method to classify blood donors and non-blood donors (hepatitis, fibrosis, and cirrhosis) that can help health professionals in a laboratory to make better decisions. Our proposed ML-method showed a better accuracy score (e.g. 98.23% for SVM). Thus, it improved the quality of classification. 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. Diffusion Kurtosis Imaging of neonatal Spinal Cord in clinical routine Diffusion Kurtosis Imaging (DKI) has undisputed advantages over more classical diffusion Magnetic Resonance Imaging (dMRI), as witnessed by a fast-increasing number of clinical applications and software packages widely adopted in brain imaging. However, in the neonatal setting, DKI is still largely underutilized in Spinal Cord (SC) imaging because of its inherently demanding technological requirements.

Due to its extreme sensitivity to non-gaussian diffusion, DKI proves particularly suitable for detecting complex, subtle, fast microstructural changes occurring in this area at this early and critical stage of development, and not identifiable with only DTI. Given the multiplicity of congenital anomalies of the spinal canal, their crucial effect on later developmental outcome, and the close interconnection between SC region and the above brain, managing to apply such a method to neonatal cohort becomes of utmost importance.

This study will (i) review the current methodological challenges associated with application of advanced dMRI methods like DKI in early infancy, (ii) illustrate the first semi-automated pipeline built on Spinal Cord Toolbox (SCT) for handling with DKI data of neonatal SC, from acquisition setting to estimation of diffusion measures, through accurate adjustment of processing algorithms customized for adult SC, and (iii) present preliminary results of its application in a pilot clinical case study.

Results of this application agree with findings achieved in a corresponding adult survey, thus confirming validity of adopted pipeline and diagnostic value of DKI in pediatrics. The Acute Treatment of Migraine with Low-Dose Naltrexone/Acetaminophen Combinations and Each Component: Findings of a Small, Randomized, Double-Blind, and Placebo-Controlled Clinical Trial We tested two low-dose naltrexone and acetaminophen combinations and each component in the acute treatment of migraine. The patients use a single-dose of the study medication for a moderate or severe pain intensity migraine attack. Patients were adults with migraine with or without aura experiencing 2 to 20 (average 6.4) monthly migraine days. The co-primary endpoints were pain-freedom and absence of prospectively-identified most bothersome migraine-associated symptom 2 hours after dosing. We randomized 92 patients; 72 completed the study (mean age, 43 years; 75% women). Pain-freedom at 2 hours was 10.2% higher than placebo with naltrexone 2.25 mg/acetaminophen 325 mg, 10.9% with naltrexone 3.25 mg/acetaminophen 325 mg, 17.3% with naltrexone 2.25 mg, and 31.3% with acetaminophen 325 mg. The treatment groups migraine burden at baseline was unbalanced due to randomized patients uneven study completion. The acetaminophen group had the lowest migraine burden, giving its results lower credibility.

Saliently, Low-dose naltrexone alone (n=19) had a 17.3% higher response rate for headache pain-freedom at 2 hours than placebo (n=17). The naltrexone and the placebo groups were the largest and had a balanced disease burden, implying higher credibility to the naltrexone group results. We found low-dose naltrexone and acetaminophen combination, low-dose naltrexone, and acetaminophen had higher response rates than placebo in treating headache pain. The most commonly reported adverse events were sedation, nausea, and dizziness. We postulate that naltrexones toll-like receptor (TLR4) antagonism properties prevent pro-inflammatory cytokines production in the trigeminal ganglion averting "overactive nerves" (laymans term) and migraine. Although this trial used low-dose naltrexone (defined as 1 - 5 mg/day), future phase 3 studies will test a range of naltrexone and acetaminophen combination doses. 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. The Addiction Risk Factor: A Unitary Genetic Vulnerability Characterizes Substance Use Disorders and Their Associations with Common Correlates Substance use disorders commonly co-occur with one another and with other psychiatric disorders. They share common features including high impulsivity, negative affect, and lower executive function. We tested whether a common genetic factor undergirds liability to problematic alcohol use (PAU), problematic tobacco use (PTU), cannabis use disorder (CUD), and opioid use disorder (OUD) by applying genomic structural equation modelling to genome-wide association study summary statistics for individuals of European ancestry (Total N = 1,019,521; substance specific Ns range: 82,707-435,563), while adjusting for the genetics of substance use (Ns = 184,765-632,802). We also tested whether shared liability across SUDs is associated with behavioral constructs (risk taking, executive function, neuroticism; Ns = 328,339-427,037) and non-substance use psychopathology (psychotic, compulsive, and early neurodevelopmental disorders). Shared genetic liability to PAU, PTU, CUD, and OUD was characterized by a unidimensional addiction risk factor (termed The Addiction-Risk-Factor, independent of substance use. OUD and CUD demonstrated the largest loadings, while problematic tobacco use showed the lowest loading. The Addiction-Risk-Factor was associated with risk taking, neuroticism, executive function, and non-substance psychopathology, but retained specific variance before and after accounting for genetics of substance use. Thus, a common genetic factor partly explains susceptibility for alcohol, tobacco, cannabis, and opioid use disorder. The Addiction-Risk-Factor has a unique genetic architecture that is not shared with normative substance use or non-substance psychopathology, suggesting that addiction is not the linear combination of substance use and psychopathology. Elevated Levels of IL-6 in IgA Nephropathy patients are induced by an Epigenetically Driven Mechanism Triggered by Viral and Bacterial RNA Recently, a several models has been proposed to describe the pathogenesis of Immunoglobulin A nephropathy (IgAN), and among them the multihit and the gut-microbiota. These models explain the pathogenesis of IgAN caused by the production of aberrant IgA, but it is believed further predisposing factors are present, including immunological, genetic, environmental, or nutritional factors that can influence the pathogenesis and that could be useful for development of precision nephrology and personalized therapy.

Newly, the role of IL-6 in pathogenesis is becoming increasingly important. It is essential for glomerular immunoglobulin A deposition and the development of renal pathology in Cd37-deficient mice, even if the reason why levels of IL-6 are elevated in IgAN patients is not well understood. One attainable hypothesis on high levels of IL-6 in IgAN comes out from our recent whole genome DNA methylation screening in IgAN patients, that identified, among others, a hypermethylated region comprising Vault RNA 2-1 (VTRNA2-1), a non-coding RNA also known as precursor of miR-886 (pre-mi-RNA). Consistently, the VTRNA2-1 expression was found down-regulated in IgAN patients.

Here we confirm that VTRNA2-1 is low expressed in IgAN subjects compared to HS and we found that also in transplanted IgAN patients (TP-IgAN), compared to non IgAN transplanted patients (TP), the VTRNA2-1 transcript was expressed at level very low. We found that in IgAN patients with downregulated VTRNA2-1, PKR is overactivated, coherently with the role of the VTRNA2-1 that binds to PKR and inhibits its phosphorylation. The loss of the VTRNA2-1 natural restrain causes, in turn, the activation of CREB by PKR. We found CREB, a classical cAMP-inducible CRE-binding factor interacting with a region of the IL-6 promoter and leading to IL-6 production, overactivated both in IgAN and in TP-IgAN patients. Effectively, in the same patients, we found elevated levels of IL-6 correlating with CREB and PKR phosphorylation.

Since PKR is normally activated by bacterial and viral RNA we hypothesized that these microrganisms can further activate the PKR/CREB/IL-6 pathway leading to an excess of IL-6 production, explaining both the high levels of IL-6, both infection involvement in the disease, both cases of IgAN associated with COVID-19 infection and with COVID-19 RNA-vaccination, and recent data showing microbiota involvment in IgAN.

Effectively, we found that Effectively, we sfound that both the RNA poly(I:C) and the COVID-19 RNA-vaccine stimulation significantly increase the IL-6 levels in IgAN patient PBMCs.

The PKR/CREB/IL-6 pathway may be very important also in the setting of renal transplantation. We found that this pathway is upregulated also in IgAN transplanted patients. Recent studies showed that the cumulative risk of IgA nephropathy recurrence increases after transplant and is associated with a 3.7-fold greater risk of graft loss. Finally, we showed that the IL-6 secretion can be reduced by the PKR inhibitor imoxin.

In conclusion, the discovery of the upregulated VTRNA2-1/PKR/CREB/IL-6 pathway in IgAN patients may provide novel approach to treat the disease and may be useful for development of precision nephrology and personalized therapy, possibly by checking the VTRNA2-1 methylation level in IgAN patients. Effects of Glucagon-like Peptide-1 Receptor Agonists on Cardiovascular and Renal Outcomes: A Meta-analysis and Meta-regression Analysis AimsCardiovascular and renal effects of glucagon-like peptide-1 receptor agonists (GLP-1RAs) have been inconsistent in cardiovascular outcome trials, and factors associated with the efficacy of GLP-1RAs remain to be clarified. Here, we evaluate the cardiovascular and renal outcomes with GLP-1RAs and associations between these outcomes and HbA1c or weight reduction.

Materials and MethodsWe searched PubMed/MEDLINE, EMBASE, and CENTRAL for randomized, placebo-controlled trials of GLP1-RAs reporting major adverse cardiovascular events (MACE; a composite of cardiovascular mortality, stroke, and myocardial infarction) as the primary outcome. We conducted a meta-regression analysis of primary and secondary outcomes with HbA1c or weight reduction following a meta-analysis with a random-effects model for these outcomes.

ResultsWe extracted data of 60,800 individuals from eight eligible studies (ELIXA, LEADER, SUSTAIN-6, EXSCEL, HARMONY, PIONEER 6, REWIND, and AMPLITUDE-O). GLP-1RAs reduced MACE (hazard ratio [HR] 0.86; 95% CI: 0.80-0.93; P < 0.001) and secondary outcomes including the composite renal outcome (0.80; 0.73-0.87; P < 0.001). In meta-regression analysis, every 1% reduction in HbA1c was associated with 26% and 35% decreases in the logarithm of HR of MACE (P = 0.044; R2 = 0.65) and the composite renal outcome (P = 0.040; R2 = 0.85), respectively. On the contrary, weight reduction was not associated with any outcome, including MACE (P = 0.390).

ConclusionsThe reduction in HbA1c, but not body weight, is associated with cardiovascular and renal outcomes. The magnitude of HbA1c reduction can be a surrogate for cardiovascular and renal benefits of treatment with GLP-1RAs. Patterns of brain degeneration in early-stage relapsing-remitting multiple sclerosis Recurrent neuroinflammation in relapsing-remitting MS (RRMS) is thought to lead to neurodegeneration, resulting in progressive disability. Repeated magnetic resonance imaging (MRI) of the brain provides non-invasive measures of atrophy over time, a key marker of neurodegeneration. This study investigates regional neurodegeneration of the brain in early-stage RRMS using volumetry and voxel-based morphometry (VBM).

RRMS patients (N=354) underwent 3T structural MRI at diagnosis and 1-year follow-up, as part of the Scottish multicentre  FutureMS study. MRI data were processed using FreeSurfer to derive volumetrics, and FSL for VBM (grey matter (GM) only), to establish patterns of change in GM and normal-appearing white matter (NAWM) over time throughout the cerebrum, cerebellum and brainstem.

Volumetric analyses showed a decrease over time (q<0.05) in bilateral cortical GM and NAWM, multiple subcortical structures, cerebellar GM and the brainstem. Additionally, NAWM and GM volume decreased respectively in the following cortical regions, frontal: 14 out of 28 regions and 17/28; temporal: 18/18 and 15/18; parietal: 14/14 and 11/14; occipital: 7/8 and 8/8. Left GM and NAWM asymmetry was observed in the frontal lobe. GM VBM analysis showed three major clusters of decrease over time: 1) temporal lobe and subcortical areas, 2) cerebellum, 3) anterior cingulum and supplementary motor cortex; and four smaller clusters within the occipital lobe.

Widespread neurodegeneration was observed in early-stage RRMS; particularly in the brainstem, cerebellar GM, and subcortical and occipital-temporal regions. Volumetric and VBM results emphasise different as well as overlapping patterns of longitudinal change, and provide potential response markers for existing therapies and trials of neuroprotective agents. Prognostic implications of structural heart disease and premature ventricular contractions in recovery of exercise BackgroundPremature ventricular contractions (PVCs) during recovery of exercise stress testing are associated with increased cardiovascular mortality, but the cause remains unknown. We aimed to evaluate the association of PVCs during recovery with echocardiographic abnormalities, and their combined prognostic performance.

MethodsEchocardiographic abnormalities (reduced left ventricular (LV) ejection fraction, valvular heart disease, LV dilatation, LV hypertrophy, or increased filling pressures) and PVCs during recovery ([&ge;]1/min) were identified among patients having undergone echocardiography within median [interquartile range] 0 [0-2] days of an exercise stress test. The association between such changes and cardiovascular mortality was analyzed using Cox regression adjusted for age, sex, clinical and exercise variables.

ResultsAmong included patients (n=3,106), PVCs during recovery were found in 1,327 (43%) patients, among which the prevalence of echocardiographic abnormalities was increased (58% vs. 44%, p<0.001). Overall, PVCs during recovery were associated with increased cardiovascular mortality (219 total events, 7.9 [5.4-11.1] years follow-up; adjusted hazard ratio (HR [95% confidence interval]) 1.6 [1.2-2.1], p<0.001). When combined with echocardiographic abnormalities, PVCs during recovery were associated with increased risk when such were present (HR 3.3 [1.9-5.5], p<0.001) but not when absent (HR 1.5 [0.8-2.8], p=0.22), in reference to those with neither.

ConclusionPVCs during recovery were associated with increased prevalence of echocardiographic abnormalities. Increased risk of cardiovascular mortality was observed only for subjects with PVCs if concomitant echocardiographic abnormalities were present. Our findings provide mechanistic insights to the increased CV risk reported in patients with PVCs during recovery. Hyperreflective foci, OCT progression indicators in age-related macular degeneration, include transdifferentiated retinal pigment epithelium PurposeBy optical coherence tomography (OCT) imaging, hyperreflective foci (HRF) indicate progression risk for advanced age-related macular degeneration (AMD) and are in part attributable to ectopic retinal pigment epithelium (RPE). We hypothesized that ectopic RPE are molecularly distinct from in-layer cells and that their cross-retinal course follows Muller glia.

MethodIn clinical OCT (61 eyes, 44 AMD patients, 79.4 {+/-} 7.7 years; 29 female; follow-up = 4.7 {+/-} 0.9 years) one HRF type, RPE plume, was reviewed. Twenty eyes of 20 donors characterized by ex vivo OCT were analyzed by histology (normal, 4; early/intermediate AMD, 7; geographic atrophy (GA), 6; 3 neovascular AMD (nvAMD). Cryosections were stained with antibodies to retinoid (RPE65, CRALPB) and immune (CD68, CD163) markers. In published RPE cellular phenotypes, red immunoreactivity was assessed semi-quantitatively by one observer (none, some cells, all cells).

ResultsTrajectories of RPE plume and cellular debris paralleled Muller glia, whether ordered or subsident, near atrophy borders. RPE corresponding to HRF lost immunoreactivity for retinoid markers and gained immunoreactivity for immune markers. Aberrant immunoreactivity appeared in individual in-layer RPE cells and extended to all abnormal phenotypes. Muller glia remained CRALBP-positive. Plume cells approached and contacted retinal capillaries.

ConclusionGain- and loss-of-function starts with individual in-layer RPE cells and extends to all abnormal phenotypes. Down-regulated RPE retinoid handling may impair rod vision while Muller glia sustain cone vision. Evidence for RPE transdifferentiation, possibly due to ischemia, supports a proposed process of epithelial-mesenchyme transition. Data can propel new biomarkers and therapeutic strategies for AMD.

PrecisHyperreflective foci (HRF) are OCT progression risk indicators in age-related macular degeneration. Abnormal RPE cells including some that correspond to HRF lose immunoreactivity for retinoid markers and gain immunoreactivity for immune markers, indicating molecular transdifferentiation. 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. Machine Learning with Objective Serum Markers and Algorithmic Deep Learning CT Scan Analysis Predicts Brain Death Due to Trauma and Hypoxia BackgroundPrediction of which traumatic and hypoxic brain injuries will progress to brain death is currently based predominantly on history, physical examination and radiographic findings. We investigated how accurately purely objective measures including three neurologic serum markers and algorithmic CT (computed tomograph) scan analysis can predict brain death and differentiate its etiology.

MethodsThis prospective observational study enrolled 51 isolated trauma subjects and 19 clinically brain dead subjects that were further divided by mechanism of injury into high-velocity trauma with presumed diffuse axonal injury, cardiopulmonary/respiratory arrest, and found down groups. Levels of glial fibrillary acidic protein (GFAP), ubiquitin carboxy-terminal hydrolase L1 (UCH-L1), and S100 Calcium-Binding Protein B (S100B) were compared, and algorithmic analysis of CT scan imaging was performed using an open-source deep learning software (BLAST-CT).

FindingsThe prognostic value of various biomarker combinations in identifying subjects progressing to brain death was assessed using machine learning. Prediction accuracy for GFAP, UCH-L1, and S100B and algorithmic CT analysis in combination to predict brain death from among all other cohorts yielded an area under the receiver operator curve of 0.98 versus all other brain injury subjects. This model was also able to distinguish brain death attributed to cardiopulmonary/respiratory arrest from combined non-trauma controls and diffuse axonal injury with an area under the curve of 0.99.

InterpretationSerum concentrations of GFAP, UCH-L1, and S100B measured within 32 hours of traumatic and hypoxic brain injury (cardiopulmonary/respiratory arrest) and algorithmic CT analysis have utility in prognosticating brain death and predicting its mechanism of injury as either hypoxic or traumatic/unknown (diffuse axonal injury/found down).

FundingAbbott Labs and the Minnesota State Office of Higher Education. Exploration of interethnic variation in the ibuprofen metabolizing enzyme CYP2C9: a genetic-based cautionary guide for treatment of COVID-19 symptoms Coronavirus disease 2019 (COVID-19), is a rapidly spreading infectious illness that causes a debilitating respiratory syndrome. While non-steroidal anti-inflammatory drugs (NSAIDs), may be prescribed for the management of pain and fever, there was early controversy on the use of ibuprofen for symptomatic treatment of COVID-19. P450 enzyme CYP2C9 are known to be involved in the metabolism of NSAIDs. Although no study has been conducted in the setting of population genetics in patients with COVID-19 yet, there are plausible mechanisms by which genetic determinants may play a role in adverse drug reactions (ADRs). In this work, we adjusted expected phenotype frequencies based on racial demographic models dependent on population ancestry in drug responses and toxicity events associated with ibuprofen treatment. A cohort of 101 Jordanian Arab samples retrospectively were selected and genotyped using Affymetrix DMET Plus Premier Package, within the context of over 100,000 global subjects in 417 published reports. European populations are 7.2x more likely to show impaired ibuprofen metabolism than Sub-Saharan populations, and 4.5x more likely than East Asian ancestry populations. Hence, a proactive assessment of the most likely gene-drug candidates will lead to more effective treatments and a better understanding of the role of pharmacogenetics for COVID-19. Poor neutralization and rapid decay of antibodies to SARS-CoV-2 variants in vaccinated dialysis patients Patients on dialysis are at risk of severe course of SARS-CoV-2 infection. Understanding the neutralizing activity and coverage of SARS-CoV-2 variants of vaccine-elicited antibodies is required to guide prophylactic and therapeutic COVID-19 interventions in this frail population. By analyzing plasma samples from 130 hemodialysis and 13 peritoneal dialysis patients after two doses of BNT162b2 or mRNA-1273 vaccines, we found that 35% of the patients had low-level or undetectable IgG antibodies to SARS-CoV-2 Spike (S). Neutralizing antibodies against the vaccine-matched SARS-CoV-2 and Delta variant were low or undetectable in 49% and 77% of patients, respectively, and were further reduced against other emerging variants. The fraction of non-responding patients was higher in SARS-CoV-2-naive hemodialysis patients immunized with BNT162b2 (66%) than those immunized with mRNA-1273 (23%). The reduced neutralizing activity correlated with low antibody avidity. Patients followed up to 7 months after vaccination showed a rapid decay of the antibody response with an average 21- and 10-fold reduction of neutralizing antibodies to vaccine-matched SARS-CoV-2 and Delta variant, which increased the fraction of non-responders to 84% and 90%, respectively. These data indicate that dialysis patients should be prioritized for additional vaccination boosts. Nevertheless, their antibody response to SARS-CoV-2 must be continuously monitored to adopt the best prophylactic and therapeutic strategy. CD19+IgD+CD27- naive B Cells as predictors of humoral response to COVID 19 mRNA vaccination in immunocompromised patients Immunocompromised patients are considered high-risk and prioritized for vaccination against COVID-19. We aimed to analyze B-cell subsets in these patients to identify potential predictors of humoral vaccination response. Patients (n=120) suffering from hematologic malignancies or other causes of immunodeficiency and healthy controls (n=79) received a full vaccination series with an mRNA vaccine. B-cell subsets were analyzed prior to vaccination. Two independent anti-SARS-CoV-2 immunoassays targeting the receptor-binding domain (RBD) or trimeric S protein (TSP) were performed three to four weeks after the second vaccination. Seroconversion occurred in 100% of healthy controls, in contrast to 67% (RBD) and 82% (TSP) of immunocompromised patients, while only 32% (RBD) and 22% (TSP) achieved antibody levels comparable to those of healthy controls. The number of circulating CD19+IgD+CD27- naive B cells was strongly associated with antibody levels ({rho}=0.761, P<0.001) and the only independent predictor for achieving antibody levels comparable to healthy controls (OR 1.07 per 10-{micro}l increase, 95%CI 1.02-1.12, P=0.009). Receiver operating characteristic analysis identified a cut-off at [&ge;]61 naive B cells per {micro}l to discriminate between patients with and without an optimal antibody response. Consequently, measuring naive B cells in immunocompromised hematologic patients could be useful in predicting their humoral vaccination response. The incidence of delirium in an acute geriatric community hospital: an observational cohort feasibility study. ObjectivesDelirium in hospitalised older adults is associated with negative health outcomes. Admission to an alternative care setting may lower the incidence of delirium. The Acute Geriatric Community Hospital (AGCH) was recently opened in the Netherlands and uses a multi-component non-pharmacological intervention strategy to prevent delirium. The objective of this study was to describe the incidence of delirium at the AGCH and compare this incidence to existing rates from literature. If a possible effect on delirium is seen in this comparison this would support conducting a larger prospectively controlled study on delirium in this new care setting.

DesignProspective cohort feasibility study; exploratory meta-analysis of proportions.

Setting and ParticipantsThe AGCH is an acute geriatric unit in a skilled nursing facility for patients aged >65 years with acute medical conditions.

MethodsDelirium assessment using the Confusion Assessment Method (CAM) upon admission and on day one, two and three or until delirium had resolved. Patients charts were reviewed if CAM was missing. In an linear mixed-effects model, the delirium incidence rate in AGCH was compared to pooled delirium incidence rates from six studies found in a high-quality review.

Results214 patients from the AGCH (mean age 81.9 years, 47% male, 12% with a history of dementia) were included in the analysis. Delirium developed in 8% (18/214) (95% confidence interval [CI] 5-13%) of patients during AGCH admission compared to 16% (95% CI 12-21%) in hospitals. Admission to the AGCH was associated with a decreased delirium incidence rate compared to the hospital control group (OR[odds ratio]= 0.49, 95% CI 0.24-0.98, p-value=0.044).

Conclusions and implicationsThe delirium incidence in the AGCH was low compared to those incidences found in general hospitals in literature. Based on these findings a controlled observational or randomized study measuring delirium in this care setting is recommended. 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.