Which exercise for low back pain? (WELBack trial) Predicting response to exercise treatments for patients with low back pain : a validation randomized controlled trial protocol

Introduction Exercise therapy is the most recommended treatment for chronic low back pain (LBP). Effect sizes for exercises are usually small to moderate and could be due to the heterogeneity of people presenting with LBP. Thus, if patients could be better matched to exercise based on individual factors, then the effects of treatment could be greater. A recently published study provided evidence of better outcomes when patients are matched to the appropriate exercise type. The study demonstrated that a 15-item questionnaire, the Lumbar Spine Instability Questionnaire (LSIQ), could identify patients who responded best to one of the two exercise approaches for LBP (motor control and graded activity). The primary aim of the current study isill be to evaluate whether preidentified baseline characteristics, including the LSIQ, can modify the response to two of the most common exercise therapies for non-specific LBP. Secondary aims include an economic evaluations with a cost-effectiveness analysis. Methods and analysis Participants (n=414) will be recruited by primary care professionals and randomised (1:1) to receive motor control exercises or graded activity. Participants will undergo 12 sessions of exercise therapy over an 8-week period. The primary outcome will be physical function at 2 months using the Oswestry Disability Index. Secondary outcomes will be pain intensity, function and quality of life measured at 2, 6 and 12 months. Potential effect modifiers will be the LSIQ, self-efficacy, coping strategies, kinesiophobia and measures of nociceptive pain and central sensitisation. We will construct linear mixed models with terms for participants (fixed), treatment group, predictor (potential effect modifier), treatment group×predictor (potential effect modifier), physiotherapists, treatment group×physiotherapists and baseline score for the dependent variable

Controlling the self-assembly and material properties of β-sheet peptide hydrogels by modulating intermolecular interactions

Self-assembling peptides are a promising biomaterial with potential applications in medical devices and drug delivery. In the right combination of conditions, self-assembling peptides can form self-supporting hydrogels. Here, we describe how balancing attractive and repulsive intermolecular forces is critical for successful hydrogel formation. Electrostatic repulsion is tuned by altering the peptide’s net charge, and intermolecular attractions are controlled through the degree of hydrogen bonding between specific amino acid residues. We find that an overall net peptide charge of +/−2 is optimal to facilitate the assembly of self-supporting hydrogels. If the net peptide charge is too low then dense aggregates form, while a high molecular charge inhibits the formation of larger structures. At a constant charge, altering the terminal amino acids from glutamine to serine decreases the degree of hydrogen bonding within the assembling network. This tunes the viscoelastic properties of the gel, reducing the elastic modulus by two to three orders of magnitude. Finally, hydrogels could be formed from glutamine-rich, highly charged peptides by mixing the peptides in combinations with a resultant net charge of +/−2. These results illustrate how understanding and controlling self-assembly mechanisms through modulating intermolecular interactions can be exploited to derive a range of structures with tuneable properties

A Panchromatic Study of Massive Stars in the Extremely Metal-poor Local Group Dwarf Galaxy Leo A*

We characterize massive stars (M > 8 M⊙) in the nearby (D ∼ 0.8 Mpc) extremely metal-poor (Z ∼ 5% Z⊙) galaxy Leo A using Hubble Space Telescope ultraviolet (UV), optical, and near-infrared (NIR) imaging along with Keck/Low-Resolution Imaging Spectrograph and MMT/Binospec optical spectroscopy for 18 main-sequence OB stars. We find that: (a) 12 of our 18 stars show emission lines, despite not being associated with an H ii region, suggestive of stellar activity (e.g., mass loss, accretion, binary star interaction), which is consistent with previous predictions of enhanced activity at low metallicity; (b) six are Be stars, which are the first to be spectroscopically studied at such low metallicity—these Be stars have unusual panchromatic SEDs; (c) for stars well fit by the TLUSTY nonlocal thermodynamic equilibrium models, the photometric and spectroscopic values of $\mathrm{log}({T}_{\mathrm{eff}})$ and $\mathrm{log}(g)$ agree to within ∼0.01 dex and ∼0.18 dex, respectively, indicating that near-UV/optical/NIR imaging can be used to reliably characterize massive (M ∼ 8–30 M⊙) main-sequence star properties relative to optical spectroscopy; (d) the properties of the most-massive stars in H II regions are consistent with constraints from previous nebular emission line studies; and (e) 13 stars with M > 8M⊙ are >40 pc from a known star cluster or H II region. Our sample comprises ∼50% of all known massive stars at Z ≲ 10% Z⊙with derived stellar parameters, high-quality optical spectra, and panchromatic photometry

CMB-S4 Science Book, First Edition

This book lays out the scientific goals to be addressed by the next-generation ground-based cosmic microwave background experiment, CMB-S4, envisioned to consist of dedicated telescopes at the South Pole, the high Chilean Atacama plateau and possibly a northern hemisphere site, all equipped with new superconducting cameras. CMB-S4 will dramatically advance cosmological studies by crossing critical thresholds in the search for the B-mode polarization signature of primordial gravitational waves, in the determination of the number and masses of the neutrinos, in the search for evidence of new light relics, in constraining the nature of dark energy, and in testing general relativity on large scales

Consistency, completeness and external validity of ethnicity recording in NHS primary care records: a cohort study in 25 million patients’ records at source using OpenSAFELY

Background: Ethnicity is known to be an important correlate of health outcomes, particularly during the COVID-19 pandemic, where some ethnic groups were shown to be at higher risk of infection and adverse outcomes. The recording of patients’ ethnic groups in primary care can support research and efforts to achieve equity in service provision and outcomes; however, the coding of ethnicity is known to present complex challenges. We therefore set out to describe ethnicity coding in detail with a view to supporting the use of this data in a wide range of settings, as part of wider efforts to robustly describe and define methods of using administrative data. Methods: We describe the completeness and consistency of primary care ethnicity recording in the OpenSAFELY-TPP database, containing linked primary care and hospital records in > 25 million patients in England. We also compared the ethnic breakdown in OpenSAFELY-TPP with that of the 2021 UK census. Results: 78.2% of patients registered in OpenSAFELY-TPP on 1 January 2022 had their ethnicity recorded in primary care records, rising to 92.5% when supplemented with hospital data. The completeness of ethnicity recording was higher for women than for men. The rate of primary care ethnicity recording ranged from 77% in the South East of England to 82.2% in the West Midlands. Ethnicity recording rates were higher in patients with chronic or other serious health conditions. For each of the five broad ethnicity groups, primary care recorded ethnicity was within 2.9 percentage points of the population rate as recorded in the 2021 Census for England as a whole. For patients with multiple ethnicity records, 98.7% of the latest recorded ethnicities matched the most frequently coded ethnicity. Patients whose latest recorded ethnicity was categorised as Other were most likely to have a discordant ethnicity recording (32.2%). Conclusions: Primary care ethnicity data in OpenSAFELY is present for over three quarters of all patients, and combined with data from other sources can achieve a high level of completeness. The overall distribution of ethnicities across all English OpenSAFELY-TPP practices was similar to the 2021 Census, with some regional variation. This report identifies the best available codelist for use in OpenSAFELY and similar electronic health record data

Microbial Community Structure and Functional Potential Along a Hypersaline Gradient

Salinity is one of the strongest environmental drivers of microbial evolution and community composition. Here we aimed to determine the impact of salt concentrations (2.5, 7.5, and 33.2%) on the microbial community structure of reclaimed saltern ponds near San Francisco, California, and to discover prospective enzymes with potential biotechnological applications. Community compositions were determined by 16S rRNA amplicon sequencing revealing both higher richness and evenness in the pond sediments compared to the water columns. Co-occurrence network analysis additionally uncovered the presence of microbial seed bank communities, potentially primed to respond to rapid changes in salinity. In addition, functional annotation of shotgun metagenomic DNA showed different capabilities if the microbial communities at different salinities for methanogenesis, amino acid metabolism, and carbohydrate-active enzymes. There was an overall shift with increasing salinity in the functional potential for starch degradation, and a decrease in degradation of cellulose and other oligosaccharides. Further, many carbohydrate-active enzymes identified have acidic isoelectric points that have potential biotechnological applications, including deconstruction of biofuel feedstocks under high ionic conditions. Metagenome-assembled genomes (MAGs) of individual halotolerant and halophilic microbes were binned revealing a variety of carbohydrate-degrading potential of individual pond inhabitants

OpenSAFELY: A platform for analysing electronic health records designed for reproducible research

Electronic health records (EHRs) and other administrative health data are increasingly used in research to generate evidence on the effectiveness, safety, and utilisation of medical products and services, and to inform public health guidance and policy. Reproducibility is a fundamental step for research credibility and promotes trust in evidence generated from EHRs. At present, ensuring research using EHRs is reproducible can be challenging for researchers. Research software platforms can provide technical solutions to enhance the reproducibility of research conducted using EHRs. In response to the COVID‐19 pandemic, we developed the secure, transparent, analytic open‐source software platform OpenSAFELY designed with reproducible research in mind. OpenSAFELY mitigates common barriers to reproducible research by: standardising key workflows around data preparation; removing barriers to code‐sharing in secure analysis environments; enforcing public sharing of programming code and codelists; ensuring the same computational environment is used everywhere; integrating new and existing tools that encourage and enable the use of reproducible working practices; and providing an audit trail for all code that is run against the real data to increase transparency. This paper describes OpenSAFELY's reproducibility‐by‐design approach in detail

Validity of Verbal Autopsy Procedures for Determining Malaria Deaths in Different Epidemiological Settings in Uganda

BACKGROUND: Verbal autopsy (VA) procedures can be used to estimate cause of death in settings with inadequate vital registries. However, the sensitivity of VA for determining malaria-specific mortality may be low, and may vary with transmission intensity. We assessed the diagnostic accuracy of VA procedures as compared to hospital medical records for determining cause of death in children under five in three different malaria transmission settings in Uganda, including Tororo (high), Kampala (medium), and Kisoro (low). METHODS AND FINDINGS: Caretakers of children who died in participating hospitals were interviewed using a standardized World Health Organization questionnaire. Medical records from the child's hospitalization were also reviewed. Causes of death based on the VA questionnaires and the medical records were assigned independently by physician reviewers and then compared. A total of 719 cases were included in the final analysis, 67 in Tororo, 600 in Kampala, and 52 in Kisoro. Malaria was classified as the underlying or contributory cause of death by review of medical records in 33 deaths in Tororo, 60 in Kampala, and 0 in Kisoro. The sensitivity of VA procedures for determining malaria deaths in Tororo was 61% (95% CI 44-78%) and 50% in Kampala (95% CI 37-63%). Specificity for determining malaria deaths in Tororo and Kampala was high (>88%), but positive predictive value varied widely, from 83% in Tororo to 34% in Kampala (difference 49%, 95% CI 31-67, p<0.001). The difference between the cause-specific mortality fraction for malaria as determined by VA procedures and medical records was -11% in Tororo, +5% in Kampala, and +14% in Kisoro. CONCLUSIONS: Our results suggest that these VA methods have an acceptable level of diagnostic accuracy for determining malaria deaths at the population level in high and medium transmission areas, but not in low transmission areas