Is exercise/physical activity effective at reducing symptoms of post-traumatic stress disorder in adults — a systematic review

Background: Exercise has been used to manage symptoms of post-traumatic stress disorder (PTSD). The effect of exercise on PTSD outcomes has been previously explored in several studies. However, it still remains unclear what type of exercise/physical activity, intensity and duration is most effective for reducing symptoms of PTSD. A systematic review was conducted to determine which forms of exercise or physical activity have the greatest effect on PTSD outcome scores including an evaluation of exercise frequency and volume. Methods: The following electronic databases were systematically searched from January 1980 to June 2021: MEDLINE, PsycINFO, PubMed and Web of Science. Inclusion criteria were studies investigating adults aged 18 or over, reporting the effect of exercise and physical activities on PTSD symptom outcome scores. Two reviewers independently extracted information on study characteristics, exposure and outcomes. In total of 3,217 articles were screened and 23 full text articles further assessed, with 13 RCT's included in the review, covering seven exercise/physical activity interventions. The study protocol was registered prospectively with PROSPERO (CRD42021255131). Results: Thirteen studies from four countries involving a total of 531 patients were selected for inclusion. Individual forms of exercise/physical activity examined showed some effect on reducing PTSD symptoms but combined exercises (resistance training, aerobic, strength and yoga) administered over a 12 week period, three times a week for 30–60 min showed greater effects on PTSD symptoms. Conclusion: The limited evidence suggests that a combined exercise intervention has the best evidence for a having a beneficial effect on PTSD symptoms. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=255131

Immune Activation in Amyloid-β-Related Angiitis Correlates with Decreased Parenchymal Amyloid-β Plaque Load

Background: Primary angiitis of the central nervous system (PACNS) is a rare but serious condition. A fraction of patients suffering from PACNS concurrently exhibit pronounced cerebral amyloid angiopathy (CAA) which is characterized by deposits of amyloid-β (Aβ) in and around the walls of small and medium-sized arteries of the brain. PACNS with CAA has been identified as a distinct disease entity, termed Aβ-related angiitis (ABRA). Evidence points to an immune reaction to vessel wall Aβ as the trigger of vasculitis. Objective: To investigate whether the inflammatory response to Aβ has (1) any effect on the status of immune activation in the brain parenchyma and (2) leads to clearance of Aβ from brain parenchyma. Methods: We studied immune activation and Aβ load by quantitative immunohistochemical analysis in brain parenchyma adjacent to affected vessels in 11 ABRA patients and 10 matched CAA controls. Results: ABRA patients showed significantly increased immune activation and decreased Aβ loads in the brain parenchyma adjacent to affected vessels. Conclusion: Our results are in line with the hypothesis of ABRA being the result of an excessive immune response to Aβ and show that this can lead to enhanced clearance of Aβ from the brain parenchyma by immune-mediated mechanisms

Lower Neutrino Mass Bound from SN1987A Data and Quantum Geometry

A lower bound on the light neutrino mass $m_\nu$ is derived in the framework of a geometrical interpretation of quantum mechanics. Using this model and the time of flight delay data for neutrinos coming from SN1987A, we find that the neutrino masses are bounded from below by $m_\nu\gtrsim 10^{-4}-10^{-3}$eV, in agreement with the upper bound $m_\nu\lesssim$ $({\cal O}(0.1) - {\cal O} (1))$ eV currently available. When the model is applied to photons with effective mass, we obtain a lower limit on the electron density in intergalactic space that is compatible with recent baryon density measurements.Comment: 22 pages, 3 figure

Estimating risk of chronic pain and disability following musculoskeletal trauma in the United Kingdom

Importance Serious traumatic injury is a leading cause of death and disability globally, with most survivors known to develop chronic pain. Objective To describe early variables associated with poor long-term outcome for posttrauma pain and create a clinical screening tool for this purpose. Design, Setting, and Participants This was a prospective cohort study at a major trauma center hospital in England. Recruitment commenced in December 2018 and ceased in March 2020. Participants were followed up for 12 months. Patients aged 16 years or older who were hospitalized because of acute musculoskeletal trauma within the preceding 14 days were included. Data were analyzed from March to December 2021. Exposure Acute musculoskeletal trauma requiring admittance to a major trauma center hospital. Main Outcomes and Measures A poor outcome was defined as Chronic Pain Grade II or higher and measured at both 6 months (primary time point) and 12 months. A broad range of candidate variables potentially associated with outcomes were used, including surrogates for pain mechanisms, quantitative sensory testing, and psychosocial factors. Univariable models were used to identify the variables most likely to be associated with poor outcome, which were entered into multivariable models. A clinical screening tool (nomogram) was derived from 6-month results. Results In total, 1590 consecutive patients were assessed for eligibility, of whom 772 were deemed eligible and 124 (80 male [64.5%]; mean [SD] age, 48.9 [18.8] years) were recruited. At 6 months, 19 of 82 respondents (23.2%) reported a good outcome, whereas at 12 months 27 of 44 respondents (61.4%) reported a good outcome. At 6 months on univariable analysis, an increase in total posttraumatic stress symptoms (odds ratio [OR], 2.09; 95% CI, 1.33-3.28), pain intensity average (OR, 2.87; 95% CI, 1.37-6.00), number of fractures (OR, 2.79; 95% CI, 1.02-7.64), and pain extent (OR, 4.67; 95% CI, 1.57-13.87) were associated with worse outcomes. A multivariable model including those variables had a sensitivity of 0.93, a specificity of 0.54, and C-index of 0.92. Conclusions and Relevance A poor long-term pain outcome from musculoskeletal traumatic injuries may be estimated by measures recorded within days of injury. These findings suggest that posttraumatic stress symptoms, pain spatial distribution, perceived average pain intensity, and number of fractures are good candidates for a sensitive multivariable model and derived clinical screening tool

Does Pain Extent Predict Ongoing Pain and Disability in Patients with Chronic Whiplash-Associated Disorders?

This study investigates whether baseline pain extent, extracted from an electronic pain drawing, is an independent predictive factor of pain and disability measured 1 year and 2 years later in people with chronic WAD. Participants completed questionnaires assessing neck pain intensity, disability via the Neck Disability Index (NDI), psychological features, and work ability. Participants also completed electronic pain drawings from which their pain extent was extracted. A two-step modelling approach was undertaken to identify the crude and adjusted association between pain extent and NDI measured at 1-year and 2-year follow-ups. A total of 205 participants were included in the analysis. The univariate analysis showed that pain extent was significantly associated with the NDI score at the 1-year (p = 0.006, 95% CI: 0.159-0.909) and 2-year (p = 0.029, 0.057-0.914) follow-ups. These associations were not maintained when we introduced perceived disability, psychological health, and work ability into the model after 1 year (p = 0.56, 95%CI: -0.28-0.499) and 2 years (p = 0.401, -0.226-0.544). Pain extent, as an independent factor, was significantly associated with perceived pain and disability in patients with chronic WAD for up to 2 years. This association was masked by neck disability, psychological health, and work ability

Consensus for experimental design in electromyography (CEDE) project:Checklist for reporting and critically appraising studies using EMG (CEDE-Check)

The diversity in electromyography (EMG) techniques and their reporting present significant challenges across multiple disciplines in research and clinical practice, where EMG is commonly used. To address these challenges and augment the reproducibility and interpretation of studies using EMG, the Consensus for Experimental Design in Electromyography (CEDE) project has developed a checklist (CEDE-Check) to assist researchers to thoroughly report their EMG methodologies. Development involved a multi-stage Delphi process with seventeen EMG experts from various disciplines. After two rounds, consensus was achieved. The final CEDE-Check consists of forty items that address four critical areas that demand precise reporting when EMG is employed: the task investigated, electrode placement, recording electrode characteristics, and acquisition and pre-processing of EMG signals. This checklist aims to guide researchers to accurately report and critically appraise EMG studies, thereby promoting a standardised critical evaluation, and greater scientific rigor in research that uses EMG signals. This approach not only aims to facilitate interpretation of study results and comparisons between studies, but it is also expected to contribute to advancing research quality and facilitate clinical and other practical applications of knowledge generated through the use of EMG.</p

Interpretable machine learning models for classifying low back pain status using functional physiological variables.

PURPOSE:To evaluate the predictive performance of statistical models which distinguishes different low back pain (LBP) sub-types and healthy controls, using as input predictors the time-varying signals of electromyographic and kinematic variables, collected during low-load lifting. METHODS:Motion capture with electromyography (EMG) assessment was performed on 49 participants [healthy control (con) = 16, remission LBP (rmLBP) = 16, current LBP (LBP) = 17], whilst performing a low-load lifting task, to extract a total of 40 predictors (kinematic and electromyographic variables). Three statistical models were developed using functional data boosting (FDboost), for binary classification of LBP statuses (model 1: con vs. LBP; model 2: con vs. rmLBP; model 3: rmLBP vs. LBP). After removing collinear predictors (i.e. a correlation of > 0.7 with other predictors) and inclusion of the covariate sex, 31 predictors were included for fitting model 1, 31 predictors for model 2, and 32 predictors for model 3. RESULTS:Seven EMG predictors were selected in model 1 (area under the receiver operator curve [AUC] of 90.4%), nine predictors in model 2 (AUC of 91.2%), and seven predictors in model 3 (AUC of 96.7%). The most influential predictor was the biceps femoris muscle (peak [Formula: see text]  = 0.047) in model 1, the deltoid muscle (peak [Formula: see text] =  0.052) in model 2, and the iliocostalis muscle (peak [Formula: see text] =  0.16) in model 3. CONCLUSION:The ability to transform time-varying physiological differences into clinical differences could be used in future prospective prognostic research to identify the dominant movement impairments that drive the increased risk. These slides can be retrieved under Electronic Supplementary Material

Search for squarks and gluinos in events with isolated leptons, jets and missing transverse momentum at s√=8 TeV with the ATLAS detector

The results of a search for supersymmetry in final states containing at least one isolated lepton (electron or muon), jets and large missing transverse momentum with the ATLAS detector at the Large Hadron Collider are reported. The search is based on proton-proton collision data at a centre-of-mass energy s√=8 TeV collected in 2012, corresponding to an integrated luminosity of 20 fb−1. No significant excess above the Standard Model expectation is observed. Limits are set on supersymmetric particle masses for various supersymmetric models. Depending on the model, the search excludes gluino masses up to 1.32 TeV and squark masses up to 840 GeV. Limits are also set on the parameters of a minimal universal extra dimension model, excluding a compactification radius of 1/R c = 950 GeV for a cut-off scale times radius (ΛR c) of approximately 30