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Falls after elective inpatient surgical procedures are common and have physical, emotional, and financial consequences. Close interactions between patients and health care teams before and after surgical procedures may offer opportunities to address modifiable risk factors associated with falls. To assess whether a multicomponent intervention that incorporates education, home medication review, and home safety assessment is associated with reductions in the incidence of falls after elective inpatient surgical procedures. This prospective propensity score-matched cohort study was a prespecified secondary analysis of data from the Electroencephalography Guidance of Anesthesia to Alleviate Geriatric Syndromes (ENGAGES) randomized clinical trial, which was conducted at a single academic medical center between January 16, 2015, and May 7, 2018. Patients in the intervention group of the present study were enrolled in either arm of the ENGAGES clinical trial. Patients in the control group were selected from the Systematic Assessment and Targeted Improvement of Services Following Yearly Surgical Outcomes Surveys prospective observational cohort study, which created a registry of patient-reported postoperative outcomes at the same single center. The propensity score-matched cohort in the present study included 1396 patients (698 pairs) selected from a pool of 2013 eligible patients. All patients underwent elective surgical procedures with general anesthesia and had a hospital stay of 2 or more days. Data were analyzed from January 2, 2020, to January 11, 2022. The multicomponent safety intervention (offered to all patients in the ENGAGES clinical trial) included patient education on fall prevention techniques, home medication review by a geriatric psychiatrist (with communication of recommended changes to the surgeon), a self-administered home safety assessment, and targeted occupational therapy home visits with home hazard removal (offered to patients with a preoperative history of falls). The primary outcome was patient-reported falls within 1 year after an elective inpatient surgical procedure. The secondary outcome was quality of life 1 year after an elective surgical procedure, which was measured using the physical and mental composite summary scores on the Veterans RAND 12-item health survey (score range, 0-100 points, with 0 indicating lowest quality of life and 100 indicating highest quality of life). Among 1396 patients, the median age was 69 years (IQR, 64-75 years), and 739 patients (52.9%) were male. With regard to race, 5 patients (0.4%) were Asian, 97 (6.9%) were Black or African American, 2 (0.1%) were Native Hawaiian or Pacific Islander, 1237 (88.6%) were White, 3 (0.2%) were of other race, and 52 (3.7%) were of unknown race; with regard to ethnicity, 12 patients (0.9%) were Hispanic or Latino, 1335 (95.6%) were non-Hispanic or non-Latino, and 49 (3.5%) were of unknown ethnicity. Adherence to individual intervention components was modest (from 22.9% for completion of the self-administered home safety assessment to 28.2% for implementation of the geriatric psychiatrist's recommended medication changes). Falls within 1 year after surgical procedures were reported by 228 of 698 patients (32.7%) in the intervention group and 225 of 698 patients (32.2%) in the control group. No significant difference was found in falls between the 2 groups (standardized risk difference, 0.4%; 95% CI, -4.5% to 5.3%). After adjusting for preoperative quality of life, patients in the intervention group had higher physical composite summary scores (3.8 points; 95% CI, 2.4-5.1 points) and higher mental composite summary scores (5.7 points; 95% CI, 4.7-6.7 points) at 1 year compared with patients in the control group. In this cohort study, a multicomponent safety intervention was not associated with reductions in falls within the first year after an elective surgical procedure; however, an increase in quality of life at 1 year was observed. These results suggest a need for other interventions, such as those designed to increase adherence, to lower the incidence of falls after surgical procedures.

Comprehensive genome annotation is essential to understand the impact of clinically relevant variants. However, the absence of a standard for clinical reporting and browser display complicates the process of consistent interpretation and reporting. To address these challenges, Ensembl/GENCODE 1 and RefSeq 2 launched a joint initiative, the Matched Annotation from NCBI and EMBL-EBI (MANE) collaboration, to converge on human gene and transcript annotation and to jointly define a high-value set of transcripts and corresponding proteins. Here, we describe the MANE transcript sets for use as universal standards for variant reporting and browser display. The MANE Select set identifies a representative transcript for each human protein-coding gene, whereas the MANE Plus Clinical set provides additional transcripts at loci where the Select transcripts alone are not sufficient to report all currently known clinical variants. Each MANE transcript represents an exact match between the exonic sequences of an Ensembl/GENCODE transcript and its counterpart in RefSeq such that the identifiers can be used synonymously. We have now released MANE Select transcripts for 97% of human protein-coding genes, including all American College of Medical Genetics and Genomics Secondary Findings list v3.0 (ref. 3 ) genes. MANE transcripts are accessible from major genome browsers and key resources. Widespread adoption of these transcript sets will increase the consistency of reporting, facilitate the exchange of data regardless of the annotation source and help to streamline clinical interpretation. Matched Annotation from NCBI and EMBL-EBI (MANE) delivers joint transcript sets from Ensembl/GENCODE and RefSeq for standardizing variant reporting in clinical genomics and research.

Task-free functional magnetic resonance imaging (TF-fMRI) has great potential for advancing the understanding and treatment of neurologic illness. However, as with all measures of neural activity, variability is a hallmark of intrinsic connectivity networks (ICNs) identified by TF-fMRI. This variability has hampered efforts to define a robust metric of connectivity suitable as a biomarker for neurologic illness. We hypothesized that some of this variability rather than representing noise in the measurement process, is related to a fundamental feature of connectivity within ICNs, which is their non-stationary nature. To test this hypothesis, we used a large (n = 892) population-based sample of older subjects to construct a well characterized atlas of 68 functional regions, which were categorized based on independent component analysis network of origin, anatomical locations, and a functional meta-analysis. These regions were then used to construct dynamic graphical representations of brain connectivity within a sliding time window for each subject. This allowed us to demonstrate the non-stationary nature of the brain's modular organization and assign each region to a \"meta-modular\" group. Using this grouping, we then compared dwell time in strong sub-network configurations of the default mode network (DMN) between 28 subjects with Alzheimer's dementia and 56 cognitively normal elderly subjects matched 1:2 on age, gender, and education. We found that differences in connectivity we and others have previously observed in Alzheimer's disease can be explained by differences in dwell time in DMN sub-network configurations, rather than steady state connectivity magnitude. DMN dwell time in specific modular configurations may also underlie the TF-fMRI findings that have been described in mild cognitive impairment and cognitively normal subjects who are at risk for Alzheimer's dementia.

Sub-Neptune planets with radii smaller than Neptune (3.9 R ⊕) are the most common type of planet known to exist in the Milky Way, even though they are absent in the solar system. These planets can potentially have a large diversity of compositions as a result of different mixtures of rocky material, icy material, and gas accreted from a protoplanetary disk. However, the bulk density of a sub-Neptune, informed by its mass and radius alone, cannot uniquely constrain its composition; atmospheric spectroscopy is necessary. GJ 1214 b, which hosts an atmosphere that is potentially the most favorable for spectroscopic detection of any sub-Neptune, is instead enshrouded in aerosols (thus showing no spectroscopic features), hiding its composition from view at previously observed wavelengths in its terminator. Here, we present a JWST NIRSpec transmission spectrum from 2.8 to 5.1 μm that shows signatures of CO2 and CH4, expected at high metallicity. A model containing both these molecules is preferred by 3.3σ and 3.6σ as compared to a featureless spectrum for two different data analysis pipelines, respectively. Given the low signal-to-noise of the features compared to the continuum, however, more observations are needed to confirm the CO2 and CH4 signatures and better constrain other diagnostic features in the near-infrared. Further modeling of the planet’s atmosphere, interior structure and origins will provide valuable insights about how sub-Neptunes like GJ 1214 b form and evolve.

Radiation reaction, the force experienced by an accelerated charge due to radiation emission, has long been the subject of extensive theoretical and experimental research. Experimental verification of a quantum, strong-field description of radiation reaction is fundamentally important, and has wide-ranging implications for astrophysics, laser-driven particle acceleration, next-generation particle colliders and inverse-Compton photon sources for medical and industrial applications. However, the difficulty of accessing regimes where strong field and quantum effects dominate inhibited previous efforts to observe quantum radiation reaction in charged particle dynamics with high significance. We report a high significance ( > 5 σ ) observation of strong-field radiation reaction on electron spectra where quantum effects are substantial. We obtain quantitative, strong evidence favouring the quantum-continuous and quantum-stochastic models over the classical model; the quantum models perform comparably. The lower electron energy losses predicted by the quantum models account for their improved performance. Model comparison was performed using a novel Bayesian framework, which has widespread utility for laser-particle collision experiments, including those utilising conventional accelerators, where some collision parameters cannot be measured directly. Radiation reaction (RR) on particles in strong fields is the subject of intense experimental research, but previous efforts lacked statistical significance due to the extreme regimes required. Here, the authors report a 5 σ observation of RR and obtain strong, quantitative evidence favouring quantum models over classical, using an all-optical setup where electrons are accelerated by a laser in a gas jet before colliding with a second, intense pulse.

Adaptive behavior in a changing world requires flexibly adapting one's rate of learning to the rate of environmental change. Recent studies have examined the computational mechanisms by which various environmental factors determine the impact of new outcomes on existing beliefs (i.e., the 'learning rate'). However, the brain mechanisms, and in particular the neuromodulators, involved in this process are still largely unknown. The brain-wide neurophysiological effects of the catecholamines norepinephrine and dopamine on stimulus-evoked cortical responses suggest that the catecholamine systems are well positioned to regulate learning about environmental change, but more direct evidence for a role of this system is scant. Here, we report evidence from a study employing pharmacology, scalp electrophysiology and computational modeling (N = 32) that suggests an important role for catecholamines in learning rate regulation. We found that the P3 component of the EEG-an electrophysiological index of outcome-evoked phasic catecholamine release in the cortex-predicted learning rate, and formally mediated the effect of prediction-error magnitude on learning rate. P3 amplitude also mediated the effects of two computational variables-capturing the unexpectedness of an outcome and the uncertainty of a preexisting belief-on learning rate. Furthermore, a pharmacological manipulation of catecholamine activity affected learning rate following unanticipated task changes, in a way that depended on participants' baseline learning rate. Our findings provide converging evidence for a causal role of the human catecholamine systems in learning-rate regulation as a function of environmental change.

To develop a reliable magnetic resonance elastography (MRE)-based method for measuring regional brain stiffness. First, simulation studies were used to demonstrate how stiffness measurements can be biased by changes in brain morphometry, such as those due to atrophy. Adaptive postprocessing methods were created that significantly reduce the spatial extent of edge artifacts and eliminate atrophy-related bias. Second, a pipeline for regional brain stiffness measurement was developed and evaluated for test-retest reliability in 10 healthy control subjects. This technique indicates high test-retest repeatability with a typical coefficient of variation of less than 1% for global brain stiffness and less than 2% for the lobes of the brain and the cerebellum. Furthermore, this study reveals that the brain possesses a characteristic topography of mechanical properties, and also that lobar stiffness measurements tend to correlate with one another within an individual. The methods presented in this work are resistant to noise- and edge-related biases that are common in the field of brain MRE, demonstrate high test-retest reliability, and provide independent regional stiffness measurements. This pipeline will allow future investigations to measure changes to the brain's mechanical properties and how they relate to the characteristic topographies that are typical of many neurologic diseases.

This trial randomly assigned pregnant women with type 1 diabetes to standard insulin therapy with continuous glucose monitoring or to hybrid closed-loop therapy. The latter significantly improved maternal glycemic control.

Aim Although satellite tracking has yielded much information regarding the migrations and habitat use of threatened marine species, relatively little has been published about the environmental niche for loggerhead sea turtles Caretta caretta in north-west Atlantic waters. Location North Carolina, South Carolina and Georgia, USA. Methods We tracked 68 adult female turtles between 1998 and 2008, one of the largest sample sizes to date, for 372.2 ± 210.4 days (mean ± SD). Results We identified two strategies: (1) 'seasonal' migrations between summer and winter coastal areas (n = 47), although some turtles made oceanic excursions (n = 4) and (2) occupation of more southerly 'year-round' ranges (n = 18). Seasonal turtles occupied summer home ranges of 645.1 km² (median, n = 42; using α-hulls) predominantly north of 35 ° latitude and winter home ranges of 339.0 km² (n = 24) in a relatively small area on the narrow shelf off North Carolina. We tracked some of these turtles through successive summer (n = 8) and winter (n = 3) seasons, showing inter-annual home range repeatability to within 14.5 km of summer areas and 10.3 km of winter areas. For year-round turtles, home ranges were 1889.9 km². Turtles should be tracked for at least 80 days to reliably estimate the home range size in seasonal habitats. The equivalent minimum duration for 'year-round' turtles is more complex to derive. We define an environmental envelope of the distribution of North American loggerhead turtles: warm waters (between 18.2 and 29.2 °C) on the coastal shelf (in depths of 3.0-89.0 m). Main conclusions Our findings show that adult female loggerhead turtles show predictable, repeatable home range behaviour and do not generally leave waters of the USA, nor the continental shelf (< 200m depth). These data offer insights for future marine management, particularly if they were combined with those from the other management units in the USA.

Hypertrophic cardiomyopathy (HCM) is often caused by pathogenic variants in sarcomeric genes and characterized by left ventricular (LV) hypertrophy, myocardial fibrosis and increased risk of heart failure and arrhythmias. There are no existing therapies to modify disease progression. In this study, we conducted a multi-center, double-blind, placebo-controlled phase 2 clinical trial to assess the safety and efficacy of the angiotensin II receptor blocker valsartan in attenuating disease evolution in early HCM. In total, 178 participants with early-stage sarcomeric HCM were randomized (1:1) to receive valsartan (320 mg daily in adults; 80–160 mg daily in children) or placebo for 2 years ( NCT01912534 ). Standardized changes from baseline to year 2 in LV wall thickness, mass and volumes; left atrial volume; tissue Doppler diastolic and systolic velocities; and serum levels of high-sensitivity troponin T and N-terminal pro-B-type natriuretic protein were integrated into a single composite z -score as the primary outcome. Valsartan ( n  = 88) improved cardiac structure and function compared to placebo ( n  = 90), as reflected by an increase in the composite z -score (between-group difference +0.231, 95% confidence interval (+0.098, +0.364); P  = 0.001), which met the primary endpoint of the study. Treatment was well-tolerated. These results indicate a key opportunity to attenuate disease progression in early-stage sarcomeric HCM with an accessible and safe medication. In a randomized phase 2 clinical trial, the angiotensin receptor blocker valsartan improved cardiac structure and function in patients with early-stage hypertrophic cardiomyopathy, a condition for which there are no effective therapies for modifying disease progression.