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Background: BI 836880 is a humanized bispecific nanobody® that binds to and blocks vascular endothelial growth factor (VEGF) and angiopoietin-2 (Ang-2). A comprehensive biomarker and modeling approach is presented here that supported dose finding for BI 836880. Methods: Two Phase I dose-escalation studies (1336.1 [NCT02674152], 1336.6 [NCT02689505]) assessed BI 836880 in adults with confirmed locally advanced or metastatic solid tumors, refractory to standard therapy or for which standard therapy was not reliably effective. Two dosing schedules were investigated, 3 weeks (q3w) or once weekly (qw), starting at a dose of 40 mg. In a comprehensive biomarker approach, soluble pharmacodynamic markers (free and total plasma VEGF-A and Ang-2), as well as circulating angiogenic factors (soluble VEGF3, soluble Tie2 and placenta growth factor, amongst others) were analyzed to assess target engagement in peripheral blood for q3w doses. A Population based pharmacokinetics/pharmacodynamics (PopPK/PD) model was built using the limited Phase I dataset to support dose finding by simulations. In order to demonstrate drug activity in the tumor, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was applied. Results: DCE-MRI scans supported target engagement in the tumor. Free VEGF-A was depleted at all doses, whereas free Ang-2 decreased dose-dependently, reaching depletion in most patients from 360 mg q3w onwards. While total VEGF-A levels increased in a dose-dependent manner, reaching saturation at 360 mg q3w, total Ang-2 levels increased, but did not plateau. Angiogenic biomarkers showed changes from doses ≥ 360 mg q3w. PopPK/PD modeling showed that doses ≥ 360 mg q3w led to > 90% inhibition of free Ang-2 at steady-state in most patients. By increasing the dose to ≥ 500 mg q3w, > 90% of patients are expected to achieve this level. Conclusions: The comprehensive analyses of multiple target engagement markers support BI 836880 720 mg q3w as a biologically relevant monotherapy dose schedule. Trial registration: NCT02674152 and NCT02689505. [ABSTRACT FROM AUTHOR]

We consider data-driven approaches that integrate a machine learning prediction model within distributionally robust optimization (DRO) given limited joint observations of uncertain parameters and covariates. Our framework is flexible in the sense that it can accommodate a variety of regression setups and DRO ambiguity sets. We investigate asymptotic and finite sample properties of solutions obtained using Wasserstein, sample robust optimization, and phi-divergence-based ambiguity sets within our DRO formulations, and explore cross-validation approaches for sizing these ambiguity sets. Through numerical experiments, we validate our theoretical results, study the effectiveness of our approaches for sizing ambiguity sets, and illustrate the benefits of our DRO formulations in the limited data regime even when the prediction model is misspecified. [ABSTRACT FROM AUTHOR]

Individualizing treatment assignment can improve outcomes for diseases with patient-to-patient variability in comparative treatment effects. When a clinical trial demonstrates that some patients improve on treatment while others do not, it is tempting to assume that treatment effect heterogeneity exists. However, if outcome variability is mainly driven by factors other than variability in the treatment effect, investigating the extent to which covariate data can predict differential treatment response is a potential waste of resources. Motivated by recent meta-analyses assessing the potential of individualizing treatment for major depressive disorder using only summary statistics, we provide a method that uses summary statistics widely available in published clinical trial results to bound the benefit of optimally assigning treatment to each patient. We also offer alternate bounds for settings in which trial results are stratified by another covariate. Our upper bounds can be especially informative when they are small, as there is then little benefit to collecting additional covariate data. We demonstrate our approach using summary statistics from a depression treatment trial. Our methods are implemented in the rct2otrbounds R package. [ABSTRACT FROM AUTHOR]

We present a reduced-order model to calculate response matrices rapidly for filter stack spectrometers (FSSs). The reduced-order model allows response matrices to be built modularly from a set of pre-computed photon and electron transport and scattering calculations through various filter and detector materials. While these modular response matrices are not appropriate for high-fidelity analysis of experimental data, they encode sufficient physics to be used as a forward model in design optimization studies of FSSs, particularly for machine learning approaches that require sampling and testing a large number of FSS designs. [ABSTRACT FROM AUTHOR]

We propose a new method for separating valid inequalities for the epigraph of a function of binary variables. The proposed inequalities are disjunctive cuts defined by disjunctive terms obtained by enumerating a subset I of the binary variables. We show that by restricting the support of the cut to the same set of variables I, a cut can be obtained by solving a linear program with 2 | I | constraints. While this limits the size of the set I used to define the multi-term disjunction, the procedure enables generation of multi-term disjunctive cuts using far more terms than existing approaches. We present two approaches for choosing the subset of variables. Experience on three MILP problems with block diagonal structure using |I| up to size 10 indicates the sparse cuts can often close nearly as much gap as the multi-term disjunctive cuts without this restriction and in a fraction of the time. We also find that including these cuts within a cut-and-branch solution method for these MILP problems leads to significant reductions in solution time or ending optimality gap for instances that were not solved within the time limit. Finally, we describe how the proposed approach can be adapted to optimally "tilt" a given valid inequality by modifying the coefficients of a sparse subset of the variables. [ABSTRACT FROM AUTHOR]

Purpose of Review: Physiotherapy interventions for headache mostly include exercise and manual therapy. Yet, the complex nature of headache, sometimes characterized by symptoms of facilitated central pain mechanisms, demands an individualized approach in which therapeutic patient education could be supportive. This scoping review aimed to summarize the position of therapeutic patient education within the physiotherapy management of adults with headache. PubMed, EMBASE, Web of Science, and Scopus were searched. The search-query comprised terminology relating to "headache", "education", and "physiotherapy". Eligibility criteria were: adults with headache, interventions including education within the domain of physiotherapy, reviews, clinical trials, cohort, case report, case–control studies. Recent Findings: Eleven publications were included from the 281 retrieved publications. These publications were clinical trials (n = 4), reviews (n = 4), case-reports (n = 2), and a guideline (n = 1). Type of headaches studied were migraine (n = 3), post-traumatic headache (n = 2), tension-type headache (n = 2), cervicogenic headache (n = 1), primary headaches (n = 1), chronic daily headache (n = 1), and mixed migraine-cervicogenic headache (n = 1). Education seems an umbrella-term for postural education, lifestyle advice, and pain education. Three themes emerged across the publications: handling headache triggers (migraine, post-traumatic headache), promoting active lifestyle (post-traumatic headache, chronic daily headache, migraine), evaluating posture (post-traumatic headache, chronic daily headache, tension-type headache, cervicogenic headache). All publications recommended education in the management of headache. Only one (of the 11 included) publication described the educational program and determined its efficacy. Summary: Based on this scoping review, therapeutic patient education seems supported within physiotherapy management of headache. However, it is unclear how such education is tailored to the specific needs of the individual, the headache subtype, or when it should be added to physiotherapy management of headache. [ABSTRACT FROM AUTHOR]

Musculoskeletal disorders (MSDs) impact people globally, cause occupational illness and reduce productivity. Exercise therapy is the gold standard treatment for MSDs and can be provided by physiotherapists and/or also via mobile apps. Apart from the obvious differences between physiotherapists and mobile apps regarding communication, empathy and physical touch, mobile apps potentially offer less personalized exercises. The use of artificial intelligence (AI) may overcome this issue by processing different pain parameters, comorbidities and patient-specific lifestyle factors and thereby enabling individually adapted exercise therapy. The aim of this study is to investigate the risks of AI-recommended strength, mobility and release exercises for people with MSDs, using physiotherapist risk assessment and retrospective consideration of patient feedback on risk and non-risk exercises. 80 patients with various MSDs received exercise recommendations from the AI-system. Physiotherapists rated exercises as risk or non-risk, based on patient information, e.g. pain intensity (NRS), pain quality, pain location, work type. The analysis of physiotherapists' agreement was based on the frequencies of mentioned risk, the percentage distribution and the Fleiss- or Cohens-Kappa. After completion of the exercises, the patients provided feedback for each exercise on an 11-point Likert scale., e.g. the feedback question for release exercises was "How did the stretch feel to you?" with the answer options ranging from "painful (0 points)" to "not noticeable (10 points)". The statistical analysis was carried out separately for the three types of exercises. For this, an independent t-test was performed. 20 physiotherapists assessed 80 patient examples, receiving a total of 944 exercises. In a three-way agreement of the physiotherapists, 0.08% of the exercises were judged as having a potential risk of increasing patients' pain. The evaluation showed 90.5% agreement, that exercises had no risk. Exercises that were considered by physiotherapists to be potentially risky for patients also received lower feedback ratings from patients. For the 'release' exercise type, risk exercises received lower feedback, indicating that the patient felt more pain (risk: 4.65 (1.88), non-risk: 5.56 (1.88)). The study shows that AI can recommend almost risk-free exercises for patients with MSDs, which is an effective way to create individualized exercise plans without putting patients at risk for higher pain intensity or discomfort. In addition, the study shows significant agreement between physiotherapists in the risk assessment of AI-recommended exercises and highlights the importance of considering individual patient perspectives for treatment planning. The extent to which other aspects of face-to-face physiotherapy, such as communication and education, provide additional benefits beyond the individualization of exercises compared to AI and app-based exercises should be further investigated. Trial registration: 30.12.2021 via OSF Registries, https://doi.org/10.17605/OSF.IO/YCNJQ. [ABSTRACT FROM AUTHOR]

Culture-based microbial natural product discovery strategies fail to realize the extraordinary biosynthetic potential detected across earth's microbiomes. Here we introduce Small Molecule In situ Resin Capture (SMIRC), a culture-independent method to obtain natural products directly from the environments in which they are produced. We use SMIRC to capture numerous compounds including two new carbon skeletons that were characterized using NMR and contain structural features that are, to the best of our knowledge, unprecedented among natural products. Applications across diverse marine habitats reveal biome-specific metabolomic signatures and levels of chemical diversity in concordance with sequence-based predictions. Expanded deployments, in situ cultivation, and metagenomics facilitate compound discovery, enhance yields, and link compounds to candidate producing organisms, although microbial community complexity creates challenges for the later. This compound-first approach to natural product discovery provides access to poorly explored chemical space and has implications for drug discovery and the detection of chemically mediated biotic interactions. Environmental analyses predict extensive, yet to be realized natural product diversity. Herein, the authors report an approach that directly captures natural products from the environment, circumventing previous challenges and yielding compounds with unusual structures and activities. [ABSTRACT FROM AUTHOR]

In the absence of data from a randomized trial, researchers may aim to use observational data to draw causal inference about the effect of a treatment on a time-to-event outcome. In this context, interest often focuses on the treatment-specific survival curves, that is, the survival curves were the population under study to be assigned to receive the treatment or not. Under certain conditions, including that all confounders of the treatment-outcome relationship are observed, the treatment-specific survival curve can be identified with a covariate-adjusted survival curve. In this article, we propose a novel cross-fitted doubly-robust estimator that incorporates data-adaptive (e.g., machine learning) estimators of the conditional survival functions. We establish conditions on the nuisance estimators under which our estimator is consistent and asymptotically linear, both pointwise and uniformly in time. We also propose a novel ensemble learner for combining multiple candidate estimators of the conditional survival estimators. Notably, our methods and results accommodate events occurring in discrete or continuous time, or an arbitrary mix of the two. We investigate the practical performance of our methods using numerical studies and an application to the effect of a surgical treatment to prevent metastases of parotid carcinoma on mortality. for this article are available online. [ABSTRACT FROM AUTHOR]

Background: According to the German Physiotherapy Education and Qualification Regulations, teaching of anatomical structures is one of the fundamental subjects of physiotherapy education. Besides exhibits and models, anatomy atlases are usually used as teaching and learning tools. These are available in both analog form such as printed books or in digital form as a mobile application. Furthermore, the use of digital teaching and learning tools is steadily increasing within the education of health professionals. Aim: To assess the efficacy of a digital educational tool in contrast to an analog anatomical atlas in acquiring knowledge about anatomical structures. Material and method: The data collection took place in the context of an anatomy tutorial for students of the bachelor's degree program in physiotherapy. In a cross-over design, the students completed two learning assignments, each, with different learning materials provided, either with an anatomy app on a tablet or with an anatomy atlas as a book. The tests to assess the newly acquired knowledge immediately after the task, consisted of questions about the anatomical structures of the knee as well as the shoulder. In addition, the students' satisfaction with the learning materials provided was surveyed using a questionnaire. The survey assessed their satisfaction, their assessment of learning success, and their affinity to digital learning materials. This was done using a 5-point Likert scale and a free-text field. The data was analyzed descriptively, and group differences were calculated using a t-tests. Results: Thirty students participated. The group comparison showed a significantly better outcome for the group that prepared with the analog anatomy atlas for the questions on the knee than the comparison group that used the anatomy app (t(28) = 2.6; p = 0.007). For the questions concerning the shoulder, there was no significant difference between the digital and analog groups (t(28) = 1.14; p = 0.26). The questionnaire revealed that satisfaction with the analog anatomy atlas was significantly higher than with the anatomy app. A total of 93.34% rated their experience with the analog learning tool at least "somewhat satisfied". In contrast, 72.67% of students partially or fully agreed that they "enjoyed learning with digital learning tools". Discussion: Learning anatomical structures with the Human Anatomy Atlas 2023 + app did not show a clear advantage when compared to an anatomy book in these two cohorts of physiotherapy students. The results of the questionnaire also showed greater satisfaction with the analog anatomy atlas than with the anatomy app, whereas most students stated that they frequently use digital learning tools, including some for anatomical structures. Satisfaction with the learning tool seems to play a central role in their effectiveness. In addition, sufficient time must be provided for users to familiarize themselves with the user interface of digital applications to use them effectively. Registration: Diese klinische Studie wurde nicht in einem Studienregister registriert. [ABSTRACT FROM AUTHOR]

Purpose: The study validates a rule-based system for identifying contraindications to exercise therapy in a medical context. It evaluates accuracy and performance by comparing it with physical therapists' assessments and patients' characteristics. Method: The dataset included 80 patient cases with clinical characteristics assessed by 20 physical therapists for contraindications to exercise therapy. Fleiss kappa and pooled kappa values measured agreement between physical therapists and AI. AI performance was assessed by sensitivity, specificity, accuracy and F1 score. Clinical characteristics were compared between therapists' votes using ANOVA and Bonferroni post-hoc test. Results: The physical therapists had a mean age of 40.85 (8.23) years and a mean experience of 14.53 (8.20) years. Out of 64 patient cases, there was consensus on 35 cases with no contraindication and 29 cases with a consensus on "contraindication exists" for exercise therapy. In 16 cases there was no consensus between therapists. Overall, therapists had 87.5% agreement with Fleiss Kappa κπ =.43. The pooled kappa value between therapists and AI was κpooled =.63. AI achieved perfect values (1) for sensitivity, specificity, accuracy and F1 score. Statistically, consensus-based comparisons by therapists revealed significant differences in pain intensity, duration, timing, and quality. Conclusion: The study shows significant agreement between physical therapists and the AI, consistent with similar musculoskeletal studies. Various clinical characteristics highlight the importance of clinical reasoning and contraindication detection. In conclusion, advanced technologies such as decision support and expert systems could have a profound impact on clinical practice, improving accuracy, personalized exercises and telemedicine referrals for efficient care and improved patient decisions. Trial registration: 30.12.2021 via OSF Registries, https://doi.org/10.17605/OSF.IO/YCNJQ. [ABSTRACT FROM AUTHOR]

Background: Balance alterations are prevalent among pain conditions, including migraine. The mechanisms explaining the association between pain and balance are unclear, as well as whether levels of pain sensitivity correlate with impaired balance. Our aim was therefore to investigate the association between balance, central sensitization symptoms and pain sensitivity in patients with migraine. Methods: This cross‐sectional study included 50 patients and demographic, clinical information, central sensitization inventory (CSI) and pain catastrophizing (PCS) scores were obtained. Patients underwent a standardized protocol evaluating balance and pain thresholds for cold (CPT), heat (HPT), mechanical (MPT) and pressure (PPT) in trigeminal (V1) and extra‐trigeminal (C6) dermatomes. Data were analysed using Person's correlation, linear regression models and contrasting the presence and absence of central sensitization symptoms through T‐tests. Results: Mild‐to‐moderate correlations were observed between balance and MPT in V1 (r = −0.24, p = 0.046) and C6 (r = −0.41, p = 0.002), CPT in V1 (r = 0.31, p = 0.026), CSI scores (r = 0.27, p = 0.029) and migraine frequency (r = 0.25, p = 0.040). Balance was explained by CPT and MPT (R2 = 0.32, p = 0.001). The variance of CSI was explained by PCS scores and balance (R2 = 0.28, p = 0.001). Patients with symptoms of central sensitization presented an increased balance impairment (p = 0.044) and higher catastrophizing levels (p = 0.001) in contrast to patients without symptoms. Conclusion: Balance impairment is associated with reduced pain thresholds and higher CSI scores. These results may help to elucidate the aetiology of balance alterations among chronic pain conditions. Significance: For the first time, it has been shown that balance alterations can reflect greater pain sensitivity and signs of central sensitization in patients with migraine. This opens up perspectives for future studies to understand the mechanisms and further factors associated with balance and pain sensitivity in migraine. [ABSTRACT FROM AUTHOR]

Introduction: Dopamine D3 receptor (D3R) ligands have been studied for the possible treatment of neurological and neuropsychiatric disorders. However, selective D3R radioligands for in vitro binding studies have been challenging to identify due to the high structural similarity between the D2R and D3R. In a prior study, we reported a new conformationally-flexible benzamide scaffold having a high affinity for D3R and excellent selectivity vs. D2R. In the current study, we characterized the in vitro binding properties of a new radioiodinated ligand, [125I]HY-3-24. Methods: In vitro binding studies were conducted in cell lines expressing D3 receptors, rat striatal homogenates, and rat and non-human primate (NHP) brain tissues to measure regional brain distribution of this radioligand. Results: HY-3-24 showed high potency at D3R (Ki = 0.67 ± 0.11 nM, IC50 = 1.5 ± 0.58 nM) compared to other D2-like dopamine receptor subtypes (D2R Ki = 86.7 ± 11.9 nM and D4R Ki > 1,000). The Kd (0.34 ± 0.22 nM) and Bmax (38.91 ± 2.39 fmol/mg) values of [125I]HY-3-24 were determined. In vitro binding studies in rat striatal homogenates using selective D2R and D3R antagonists confirmed the D3R selectivity of [125I]HY-3-24. Autoradiography results demonstrated that [125I]HY-3-24 specifically binds to D3Rs in the nucleus accumbens, islands of Calleja, and caudate putamen in rat and NHP brain sections. Conclusion: These results suggest that [125I]HY-3-24 appears to be a novel radioligand that exhibits high affinity binding at D3R, with low binding to other D2-like dopamine receptors. It is anticipated that [125I]HY-3-24 can be used as the specific D3R radioligand. [ABSTRACT FROM AUTHOR]

Correlated color temperature (CCT) is one of the primary metrics used to characterize the visual appearance of light and is most informative when coupled with distance from the Planckian locus (Duv). Given a set of chromaticity coordinates—which are calculated from a light source's spectral power distribution—it is possible to compute CCT and Duv with varying levels of accuracy. Over the last six decades at least a dozen methods have been proposed to compute CCT while balancing accuracy with calculation complexity. CCT values become inconsistent at some level of precision when calculated using different methods, which in turn can lead to discrepancies in dependent or subsequent calculations used by lighting professionals and may be problematic in software. Although methods are now documented that can provide extremely high accuracy, no consensus body has recommended a preferred method. This analysis examines both the calculation speed and the CCT and Duv accuracy of previously proposed and new methods. With consideration of the calculation accuracy, computational burden, calculation complexity, and considerations of practical implementation, we recommend a recent modification of the Robertson method. [ABSTRACT FROM AUTHOR]

This commentary discusses the revised Department of Veterans Affairs (VA)/Department of Defense (DoD) Clinical Practice Guideline (CPG) for posttraumatic stress disorder (PTSD) and acute stress disorder, specifically focusing on couple- and family-based treatment. The authors raise concerns about the lack of guidance regarding the role of intimate partners and families in the treatment and assessment of PTSD, as well as issues with defining specific treatments in the CPG evidence rubric. They also highlight the importance of honoring patient preferences for family-inclusive treatment and suggest that family-inclusive therapies with demonstrated efficacy should be considered as an optimal choice. [Extracted from the article]

In the ENSEMBLE randomized, placebo-controlled phase 3 trial (NCT04505722), estimated single-dose Ad26.COV2.S vaccine efficacy (VE) was 56% against moderate to severe–critical COVID-19. SARS-CoV-2 Spike sequences were determined from 484 vaccine and 1,067 placebo recipients who acquired COVID-19. In this set of prespecified analyses, we show that in Latin America, VE was significantly lower against Lambda vs. Reference and against Lambda vs. non-Lambda [family-wise error rate (FWER) p < 0.05]. VE differed by residue match vs. mismatch to the vaccine-insert at 16 amino acid positions (4 FWER p < 0.05; 12 q-value ≤ 0.20); significantly decreased with physicochemical-weighted Hamming distance to the vaccine-strain sequence for Spike, receptor-binding domain, N-terminal domain, and S1 (FWER p < 0.001); differed (FWER ≤ 0.05) by distance to the vaccine strain measured by 9 antibody-epitope escape scores and 4 NTD neutralization-impacting features; and decreased (p = 0.011) with neutralization resistance level to vaccinee sera. VE against severe–critical COVID-19 was stable across most sequence features but lower against the most distant viruses.SARS-CoV-2 variants with mutations in spike have emerged during the pandemic. Magaret et al. show that in Latin America, efficacy of the Ad26.COV2.S vaccine against moderate to severe–critical COVID-19 varied by sequence features, antibody escape scores, and neutralization impacting features of the SARS-CoV-2 variant. [ABSTRACT FROM AUTHOR]

On Decision Rules for Multistage Stochastic Programs with Mixed-Integer Decisions Multistage stochastic programming is a field of stochastic optimization for addressing sequential decision-making problems defined over a stochastic process with a given probability distribution. The solution to such a problem is a decision rule (policy) that maps the history of observations to the decisions. Design of the decision rules in the presence of mixed-integer decisions is quite challenging. In "Lagrangian Dual Decision Rules for Multistage Stochastic Mixed-Integer Programming," Daryalal, Bodur, and Luedtke introduce Lagrangian dual decision rules, where linear decision rules are applied to dual multipliers associated with Lagrangian duals of a multistage stochastic mixed-integer programming (MSMIP) model. The restricted decisions are then used in the development of new primal- and dual-bounding methods. This yields a new general-purpose approximation approach for MSMIP, free of strong assumptions made in the literature, such as stagewise independence or existence of a tractable-sized scenario-tree representation. Multistage stochastic programs can be approximated by restricting policies to follow decision rules. Directly applying this idea to problems with integer decisions is difficult because of the need for decision rules that lead to integral decisions. In this work, we introduce Lagrangian dual decision rules (LDDRs) for multistage stochastic mixed-integer programming (MSMIP), which overcome this difficulty by applying decision rules in a Lagrangian dual of the MSMIP. We propose two new bounding techniques based on stagewise (SW) and nonanticipative (NA) Lagrangian duals, where the Lagrangian multiplier policies are restricted by LDDRs. We demonstrate how the solutions from these duals can be used to drive primal policies. Our proposal requires fewer assumptions than most existing MSMIP methods. We compare the theoretical strength of the restricted duals and show that the restricted NA dual can provide relaxation bounds at least as good as the ones obtained by the restricted SW dual. In our numerical study on two problem classes, one traditional and one novel, we observe that the proposed LDDR approaches yield significant optimality-gap reductions compared with existing general-purpose bounding methods for MSMIP problems. Funding: Financial support from the Natural Sciences and Engineering Research Council of Canada [Grant RGPIN-2018-04984]; the National Science Foundation [Grant CMMI-1634597]; and the Department of Energy, Office of Science, Office of Advanced Scientific Computing Research, Applied Mathematics [Contract Number DE-AC02- 06CH113] is gratefully acknowledged. Supplemental Material: The e-companion is available at https://doi.org/10.1287/opre.2022.2366. [ABSTRACT FROM AUTHOR]

External validity is an important parameter that needs to be considered for decision making in health research, but no widely accepted measurement tool for the assessment of external validity of randomized controlled trials (RCTs) exists. One of the most limiting factors for creating such a tool is probably the substantial heterogeneity and lack of consensus in this field. The objective of this study was to reach consensus on a definition of external validity and on criteria to assess the external validity of RCTs included in systematic reviews. A three‐round online Delphi study was conducted. The development of the Delphi survey was based on findings from a previous systematic review. Potential panelists were identified through a comprehensive web search. Consensus was reached when at least 67% of the panelists agreed to a proposal. Eighty‐four panelists from different countries and various disciplines participated in at least one round of this study. Consensus was reached on the definition of external validity ("External validity is the extent to which results of trials provide an acceptable basis for generalization to other circumstances such as variations in populations, settings, interventions, outcomes, or other relevant contextual factors"), and on 14 criteria to assess the external validity of RCTs in systematic reviews. The results of this Delphi study provide a consensus‐based reference standard for future tool development. Future research should focus on adapting, pilot testing, and validating these criteria to develop measurement tools for the assessment of external validity. [ABSTRACT FROM AUTHOR]

Objective The aim of this study was to assess the efficacy of physical therapist interventions on the intensity, frequency, and duration of headaches, as well as on the quality of life of patients with cervicogenic headache. Methods The following databases were searched up to October 2022: Physiotherapy Evidence Database, Web of Science, Pubmed, and Cochrane Library. Randomized controlled trials assessing the effect of physical therapist interventions on adults with cervicogenic headache were included. Quality appraisal was conducted using the Cochrane risk of bias 2.0 tool and the Confidence in Network Meta-analysis web app. Synthesis methods were conducted in accordance with the Cochrane Handbook. Results Of the 28 identified reports, 23 were included in the quantitative synthesis. Manipulation plus dry needling was the highest-ranked intervention to reduce the short-term headache intensity (mean difference [MD] = −4.87; 95% CI = −8.51 to −1.24) and frequency (MD = −3.09; 95% CI = −4.93 to −1.25) when compared to a control intervention. Other high-ranked and clinically effective interventions (when compared to a control intervention) were muscle–energy technique plus exercise (MD = 4.37; 95% CI = −8.01 to −0.74), as well as soft tissue techniques plus exercise (MD = −3.01; 95% CI = −5.1 to −0.92) to reduce short-term headache intensity, and dry needling plus exercise (MD = −2.92; 95% CI = −4.73 to −1.11) to reduce short-term headache frequency. These results were based on a low certainty of evidence. Conclusion The 4 most highly ranked interventions can be considered in clinical practice. However, no conclusive recommendation can be made due to the low certainty of evidence. Impact Combined interventions such as spinal joint manipulation plus dry needling and muscle–energy technique or soft tissue techniques or dry needling plus exercises seem to be the best interventions to reduce short-term cervicogenic headache intensity and/or frequency. [ABSTRACT FROM AUTHOR]

Key Points: Question: Can development of an individualized treatment rule identify patients presenting to emergency departments/urgent care with suicidal ideation or suicide attempts who are likely to benefit from psychiatric hospitalization? Findings: A decision analytic model found that hospitalization was associated with reduced suicide attempt risk among patients who attempted suicide in the past day but not among others with suicidality. Accounting for heterogeneity, suicide attempt risk was found to increase with hospitalization in 24% of patients and decrease in 28%. Meaning: Results of this study suggest that implementing an individualized treatment rule could identify many additional patients who may benefit from or be harmed by hospitalization. Importance: Psychiatric hospitalization is the standard of care for patients presenting to an emergency department (ED) or urgent care (UC) with high suicide risk. However, the effect of hospitalization in reducing subsequent suicidal behaviors is poorly understood and likely heterogeneous. Objectives: To estimate the association of psychiatric hospitalization with subsequent suicidal behaviors using observational data and develop a preliminary predictive analytics individualized treatment rule accounting for heterogeneity in this association across patients. Design, Setting, and Participants: A machine learning analysis of retrospective data was conducted. All veterans presenting with suicidal ideation (SI) or suicide attempt (SA) from January 1, 2010, to December 31, 2015, were included. Data were analyzed from September 1, 2022, to March 10, 2023. Subgroups were defined by primary psychiatric diagnosis (nonaffective psychosis, bipolar disorder, major depressive disorder, and other) and suicidality (SI only, SA in past 2-7 days, and SA in past day). Models were trained in 70.0% of the training samples and tested in the remaining 30.0%. Exposures: Psychiatric hospitalization vs nonhospitalization. Main Outcomes and Measures: Fatal and nonfatal SAs within 12 months of ED/UC visits were identified in administrative records and the National Death Index. Baseline covariates were drawn from electronic health records and geospatial databases. Results: Of 196 610 visits (90.3% men; median [IQR] age, 53 [41-59] years), 71.5% resulted in hospitalization. The 12-month SA risk was 11.9% with hospitalization and 12.0% with nonhospitalization (difference, −0.1%; 95% CI, −0.4% to 0.2%). In patients with SI only or SA in the past 2 to 7 days, most hospitalization was not associated with subsequent SAs. For patients with SA in the past day, hospitalization was associated with risk reductions ranging from −6.9% to −9.6% across diagnoses. Accounting for heterogeneity, hospitalization was associated with reduced risk of subsequent SAs in 28.1% of the patients and increased risk in 24.0%. An individualized treatment rule based on these associations may reduce SAs by 16.0% and hospitalizations by 13.0% compared with current rates. Conclusions and Relevance: The findings of this study suggest that psychiatric hospitalization is associated with reduced average SA risk in the immediate aftermath of an SA but not after other recent SAs or SI only. Substantial heterogeneity exists in these associations across patients. An individualized treatment rule accounting for this heterogeneity could both reduce SAs and avert hospitalizations. This predictive analytics model develops a preliminary individualized treatment rule to estimate the association between psychiatric hospitalization and subsequent suicidal behaviors in patients at risk for suicide. [ABSTRACT FROM AUTHOR]

We present an inversion method capable of robustly unfolding MeV x-ray spectra from filter stack spectrometer (FSS) data without requiring an a priori specification of a spectral shape or arbitrary termination of the algorithm. Our inversion method is based upon the perturbative minimization (PM) algorithm, which has previously been shown to be capable of unfolding x-ray transmission data, albeit for a limited regime in which the x-ray mass attenuation coefficient of the filter material increases monotonically with x-ray energy. Our inversion method improves upon the PM algorithm through regular smoothing of the candidate spectrum and by adding stochasticity to the search. With these additions, the inversion method does not require a physics model for an initial guess, fitting, or user-selected termination of the search. Instead, the only assumption made by the inversion method is that the x-ray spectrum should be near a smooth curve. Testing with synthetic data shows that the inversion method can successfully recover the primary large-scale features of MeV x-ray spectra, including the number of x-rays in energy bins of several-MeV widths to within 10%. Fine-scale features, however, are more difficult to recover accurately. Examples of unfolding experimental FSS data obtained at the Texas Petawatt Laser Facility and the OMEGA EP laser facility are also presented. [ABSTRACT FROM AUTHOR]

The purpose of this study was to reproduce the previously observed spatial summation of pain effect (SSp) using non-laboratory procedures and commercial equipment. An additional aim was to explore the association between expectations and SSp. The Cold Pressor Task (CPT) was used to induce SSp. Healthy participants (N = 68) immersed their non-dominant hands (divided into 5 segments) into cold water (CPT). Two conditions were used 1) gradual hand immersion (ascending condition) and 2) gradual hand withdrawal (descending condition). Pain intensity was measured on a Visual Analogue Scale (VAS). Psychological factors, such as the participants' expectations of pain intensity were also measured on a VAS. Results showed significant SSp (χ2(4) = 116.90, p < 0.001), reproduced with non-laboratory equipment in a home-based set-up. Furthermore, two novel findings were observed: i) there was a significant correlation between expectations and perceived pain, indicating a link between pain expectations and SSp, ii) spatial summation increased with the increase in duration exposure to the noxious stimulus (Wald χ2(8) = 80.80, p < 0.001). This study suggests that SSp is associated with pain expectations and can be formed by a mixture of excitatory and inhibitory mechanisms potentially driven by temporal characteristics of neural excitation. Moreover, this study proposes a new feasible way to induce SSp using a home-based set-up. [ABSTRACT FROM AUTHOR]

Alkylation at the O6 position of guanine is a common and highly mutagenic form of DNA damage. Direct repair of O6-alkylguanines by the "suicide" enzyme O6-methylguanine DNA methyltransferase (MGMT, AGT, AGAT) maintains genome stability and inhibits carcinogenesis. In this study, a fluorescent analogue of thymidine containing trans-stilbene (tsT) is quenched by O6-methylguanine residues in the opposite strand of DNA by molecular dynamics that propagate through the duplex with as much as ∼9 Å of separation. Increased fluorescence of tsT or the cytosine analogue tsC resulting from MGMT-mediated DNA repair were distinguishable from non-covalent DNA–protein binding following protease digest. To our knowledge, this is the first study utilizing molecular rotor base analogues to detect DNA damage and repair activities in duplex DNA. [ABSTRACT FROM AUTHOR]

A series of bitopic ligands based on Fallypride with a flexible secondary binding fragment (SBF) were prepared with the goal of preparing a D3R-selective compound. The effect of the flexible linker ((R,S)-trans-2a–d), SBFs ((R,S)-trans-2h–j), and the chirality of orthosteric binding fragments (OBFs) ((S,R)-trans-d, (S,R)-trans-i, (S,S)-trans-d, (S,S)-trans-i, (R,R)-trans-d, and (R,R)-trans-i) were evaluated in in vitro binding assays. Computational chemistry studies revealed that the interaction of the fragment binding to the SBF increased the distance between the pyrrolidine nitrogen and ASP1103.32 of the D3R, thereby reducing the D3R affinity to a suboptimal level. [ABSTRACT FROM AUTHOR]

An intense laser pulse focused onto a plasma can excite nonlinear plasma waves. Under appropriate conditions, electrons from the background plasma are trapped in the plasma wave and accelerated to ultra-relativistic velocities. This scheme is called a laser wakefield accelerator. In this work, we present results from a laser wakefield acceleration experiment using a petawatt-class laser to excite the wakefields as well as nanoparticles to assist the injection of electrons into the accelerating phase of the wakefields. We find that a 10-cm-long, nanoparticle-assisted laser wakefield accelerator can generate 340 pC, 10 ± 1.86 GeV electron bunches with a 3.4 GeV rms convolved energy spread and a 0.9 mrad rms divergence. It can also produce bunches with lower energies in the 4–6 GeV range. [ABSTRACT FROM AUTHOR]

Vigorous discussions are ongoing about future efficacy trial designs of candidate human immunodeficiency virus (HIV) prevention interventions. The study design challenges of HIV prevention interventions are considerable given rapid evolution of the prevention landscape and evidence of multiple modalities of highly effective products; future trials will likely be 'active-controlled', i.e., not include a placebo arm. Thus, novel design approaches are needed to accurately assess new interventions against these highly effective active controls. To discuss active control design challenges and identify solutions, an initial virtual workshop series was hosted and supported by the International AIDS Enterprise (October 2020-March 2021). Subsequent symposia discussions continue to advance these efforts. As the non-inferiority design is an important conceptual reference design for guiding active control trials, we adopt several of its principles in our proposed design approaches. We discuss six potential study design approaches for formally evaluating absolute prevention efficacy given data from an active-controlled HIV prevention trial including using data from: 1) a registrational cohort, 2) recency assays, 3) an external trial placebo arm, 4) a biomarker of HIV incidence/exposure, 5) an anti-retroviral drug concentration as a mediator of prevention efficacy, and 6) immune biomarkers as a mediator of prevention efficacy. Our understanding of these proposed novel approaches to future trial designs remains incomplete and there are many future statistical research needs. Yet, each of these approaches, within the context of an active-controlled trial, have the potential to yield reliable evidence of efficacy for future biomedical interventions. [ABSTRACT FROM AUTHOR]

We created a database of lost and rediscovered tetrapod species, identified patterns in their distribution and factors influencing rediscovery. Tetrapod species are being lost at a faster rate than they are being rediscovered, due to slowing rates of rediscovery for amphibians, birds and mammals, and rapid rates of loss for reptiles. Finding lost species and preventing future losses should therefore be a conservation priority. By comparing the taxonomic and spatial distribution of lost and rediscovered tetrapod species, we have identified regions and taxa with many lost species in comparison to those that have been rediscovered—our results may help to prioritise search effort to find them. By identifying factors that influence rediscovery, we have improved our ability to broadly distinguish the types of species that are likely to be found from those that are not (because they are likely to be extinct). Some lost species, particularly those that are small and perceived to be uncharismatic, may have been neglected in terms of conservation effort, and other lost species may be hard to find due to their intrinsic characteristics and the characteristics of the environments they occupy (e.g. nocturnal species, fossorial species and species occupying habitats that are more difficult to survey such as wetlands). These lost species may genuinely await rediscovery. However, other lost species that possess characteristics associated with rediscovery (e.g. large species) and that are also associated with factors that negatively influence rediscovery (e.g. those occupying small islands) are more likely to be extinct. Our results may foster pragmatic search protocols that prioritise lost species likely to still exist. [ABSTRACT FROM AUTHOR]

Aims: Surgical Antibiotic Prophylaxis (SAP) in Nigeria is often not evidence based. The aim of this study is to test if the GADSA application can change prescription behaviour of surgeons in Nigeria. In addition, the study aims to identify AMS strategies and policies for the future. Methods: The GADSA gamified decision support app uses WHO and Sanford prescribing guidelines to deliver real-time persuasive technology feedback to surgeons through an interactive mentor. The app can advise on whether clinician's decisions align with SAP recommendations and provides the opportunity for clinicians to make adjustments. Twenty surgeons actively participated in a 6-month pilot study in three hospitals in Nigeria. The surgeons determined the risk of infection of a surgical procedure, and the need, type and duration of SAP. The study used a longitudinal approach to test whether the GADSA app significantly changed prescribing behaviour of participating surgeons by analysing the reported prescription decisions within the app. Results: 321 SAP prescriptions were recorded. Concerning the surgical risk decision, 12% of surgeons changed their decision to be in line with guidelines after app feedback (p < 0.001) and 10% of surgeons changed their decision about the need for SAP (p = 0.0035) to align with guidelines. The change in decision making for SAP use in terms of "type" and "duration" to align with guidelines was similar with 6% and 5% respectively (both p-values < 0.001). Conclusion: This study suggests that the GADSA app, with its game based and feedback feature, could significantly change prescribing behaviour at the point of care in an African setting, which could help tackle the global challenge of antibiotic resistance. [ABSTRACT FROM AUTHOR]

We aim to make inferences about a smooth, finite-dimensional parameter by fusing together data from multiple sources. Previous works have studied the estimation of a variety of parameters in similar data fusion settings, including estimation of the average treatment effect and average reward under a policy, with the majority of them merging one historical data source with covariates, actions and rewards, and one data source of the same covariates. In this article, we consider the general case where one or more data sources align with each part of the distribution of the target population, such as the conditional distribution of the reward given actions and covariates. We describe potential gains in efficiency that can arise from fusing these data sources together in a single analysis, which we characterize by a reduction in the semiparametric efficiency bound. We also provide a general means of constructing estimators that achieve these bounds. Numerical simulations demonstrate marked improvements in efficiency from using the proposed estimators rather than their natural alternatives. Finally, we illustrate the magnitude of efficiency gains that can be realized in vaccine immunogenicity studies by fusing data from two HIV vaccine trials. [ABSTRACT FROM AUTHOR]

Background: Cutaneous allodynia is highly prevalent among migraineurs and is associated with a poor prognosis. The Allodynia Symptom Checklist (ASC-12) is a comprehensive questionnaire to identify the presence and severity of allodynia. Our aim was to translate and adapt the ASC-12 to German and evaluate its measurement properties. Methods: Following the COSMIN guidelines, 80 migraine patients were enrolled in the study to evaluate the stages of translation (n=30) and measurement propriety assessment (n=50), respectively. After reaching a final version, the German ASC-12 was assessed for structural validity, internal consistency, test-retest reliability, construct validity and absolute agreement, using mechanical and thermal pain thresholds as reference method. Results: The German version of the ASC-12 presented an adequate structural validity compatible with the original version of the questionnaire. Its internal consistency ranged from 0.70 to 0.80 considering the total score and the thermic, static and dynamic mechanic subdomains. The total score presented excellent reliability (ICC: 0.85) with a standard error of measurement of 1.15 points and smallest detectable change of 3.40 points. ASC-12 total scores were correlated with headache intensity (r=0.38, p=0.004), headache disability (r=0.37, p=0.004) and cold pain thresholds (r=0.28, p=0.025). The thermic allodynia ASC-12 scores were correlated with cold (r=0.36, p=0.005) and heat (r=-0.30, p=0.010) pain thresholds, while the static mechanical allodynia ASC-12 scores correlated with mechanical pain threshold (r=0.29, p=0.019) and with mechanical pain sensitivity (r=0.24 to 0.28, p< 0.045). Despite no significant bias between methods, quantitative sensory testing (QST) results and ASC-12 scores tend to disagree. Conclusion: The German version of the ASC-12 is available for research and clinical settings and presented adequate measurement proprieties, as the original version. Despite the correlation between the ASC-12 and QST, one method cannot be replaced by the other. [ABSTRACT FROM AUTHOR]

Background: Risk of suicide-related behaviors is elevated among military personnel transitioning to civilian life. An earlier report showed that high-risk U.S. Army soldiers could be identified shortly before this transition with a machine learning model that included predictors from administrative systems, self-report surveys, and geospatial data. Based on this result, a Veterans Affairs and Army initiative was launched to evaluate a suicide-prevention intervention for high-risk transitioning soldiers. To make targeting practical, though, a streamlined model and risk calculator were needed that used only a short series of self-report survey questions. Methods: We revised the original model in a sample of n = 8335 observations from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS) who participated in one of three Army STARRS 2011–2014 baseline surveys while in service and in one or more subsequent panel surveys (LS1: 2016–2018, LS2: 2018–2019) after leaving service. We trained ensemble machine learning models with constrained numbers of item-level survey predictors in a 70% training sample. The outcome was self-reported post-transition suicide attempts (SA). The models were validated in the 30% test sample. Results: Twelve-month post-transition SA prevalence was 1.0% (s.e. = 0.1). The best constrained model, with only 17 predictors, had a test sample ROC-AUC of 0.85 (s.e. = 0.03). The 10–30% of respondents with the highest predicted risk included 44.9–92.5% of 12-month SAs. Conclusions: An accurate SA risk calculator based on a short self-report survey can target transitioning soldiers shortly before leaving service for intervention to prevent post-transition SA. [ABSTRACT FROM AUTHOR]

Systematic assessments of species extinction risk at regular intervals are necessary for informing conservation action1,2. Ongoing developments in taxonomy, threatening processes and research further underscore the need for reassessment3,4. Here we report the findings of the second Global Amphibian Assessment, evaluating 8,011 species for the International Union for Conservation of Nature Red List of Threatened Species. We find that amphibians are the most threatened vertebrate class (40.7% of species are globally threatened). The updated Red List Index shows that the status of amphibians is deteriorating globally, particularly for salamanders and in the Neotropics. Disease and habitat loss drove 91% of status deteriorations between 1980 and 2004. Ongoing and projected climate change effects are now of increasing concern, driving 39% of status deteriorations since 2004, followed by habitat loss (37%). Although signs of species recoveries incentivize immediate conservation action, scaled-up investment is urgently needed to reverse the current trends.The second Global Amphibian Assessment finds that the status of amphibians is continuing to deteriorate globally, driven predominantly by climate change, disease and habitat loss. [ABSTRACT FROM AUTHOR]

Objective The goal of this study was to reach consensus about the best exercise prescription parameters, the most relevant considerations, and other recommendations that could be useful for prescribing exercise to patients with migraine. Methods This was an international study conducted between April 9, 2022 and June 30, 2022. An expert panel of health care and exercise professionals was assembled, and a 3-round Delphi survey was performed. Consensus was reached for each item if an Aiken V Validity Index ≥ 0.7 was obtained. Results The study included 14 experts who reached consensus on 42 items by the third round. The most approved prescription parameters were 30 to 60 minutes of exercise per session, 3 days per week of moderate-intensity continuous aerobic exercise, and relaxation and breathing exercises for 5 to 20 minutes every day. When considering an exercise prescription, initial exercise supervision should progress to patient self-regulation; catastrophizing, fear-avoidance beliefs, headache-related disability, anxiety, depression, physical activity baseline level, and self-efficacy could influence the patients' exercise participation and efficacy; and gradual exposure to exercise could help improve these psychological variables and increase exercise efficacy. Yoga and concurrent exercise were also included as recommended interventions. Conclusion From the experts in the study, exercise prescriptions should be adapted to patients with migraine considering different exercise modalities, such as moderate-intensity aerobic exercise, relaxation, yoga, and concurrent exercise, based on the patients' preferences and psychological considerations, level of physical activity, and possible adverse effects. Impact The consensus reached by the experts can help prescribe exercise accurately to patients with migraine. Offering various exercise modalities can improve exercise participation in this population. The evaluation of the patients' psychological and physical status can also facilitate the adaptation of the exercise prescription to their abilities and diminish the risk of adverse events. [ABSTRACT FROM AUTHOR]

Multiple attempts to quantify pain objectively using single measures of physiological body responses have been performed in the past, but the variability across participants reduces the usefulness of such methods. Therefore, this study aims to evaluate whether combining multiple autonomic parameters is more appropriate to quantify the perceived pain intensity of healthy subjects (HSs) and chronic back pain patients (CBPPs) during experimental heat pain stimulation. HS and CBPP received different heat pain stimuli adjusted for individual pain tolerance via a CE-certified thermode. Different sensors measured physiological responses. Machine learning models were trained to evaluate performance in distinguishing pain levels and identify key sensors and features for the classification task. The results show that distinguishing between no and severe pain is significantly easier than discriminating lower pain levels. Electrodermal activity is the best marker for distinguishing between low and high pain levels. However, recursive feature elimination showed that an optimal subset of features for all modalities includes characteristics retrieved from several modalities. Moreover, the study's findings indicate that differences in physiological responses to pain in HS and CBPP remain small. [ABSTRACT FROM AUTHOR]

Though platform trials have been touted for their flexibility and streamlined use of trial resources, their statistical efficiency is not well understood. We fill this gap by establishing their greater efficiency for comparing the relative efficacy of multiple interventions over using several separate, 2-arm trials, where the relative efficacy of an arbitrary pair of interventions is evaluated by contrasting their relative risks as compared to control. In theoretical and numerical studies, we demonstrate that the inference of such a contrast using data from a platform trial enjoys identical or better precision than using data from separate trials, even when the former enrolls substantially fewer participants. This benefit is attributed to the sharing of controls among interventions under contemporaneous randomization. We further provide a novel procedure for establishing the noninferiority of a given intervention relative to the most efficacious of the other interventions under evaluation, where this procedure is adaptive in the sense that it need not be a priori known which of these other interventions is most efficacious. Our numerical studies show that this testing procedure can attain substantially better power when the data arise from a platform trial rather than multiple separate trials. Our results are illustrated using data from two monoclonal antibody trials for the prevention of HIV. [ABSTRACT FROM AUTHOR]

Access to financial education courses makes a difference in high school students' future financial lives. However, little data have been available to assess the access students have to these classes and what types of financial education are offered throughout the United States. We describe a novel dataset of over 19,000 hand-coded high school personal finance courses for over 7,400 high schools across the United States. These data cover the academic years from 2019-2020 to 2022-2023. The most common type of financial education offered is a semester-long course focused entirely on financial education, rather than, for example, a course on another topic that builds in a section on financial education. Schools that are in rural areas, schools with a higher percentage of Black students and schools that are geographically isolated from peers with high financial education requirements are less likely to require financial education courses for graduation. [ABSTRACT FROM AUTHOR]

Key Points: Question: Can an individualized treatment rule identify patients who benefit as much or more from self-guided internet-delivered cognitive behavioral therapy (i-CBT) as from guided i-CBT? Findings: In this secondary analysis of a randomized clinical trial of 1319 university students with anxiety and/or depression, guided i-CBT optimized the probability of (1) joint remission of anxiety and depression for 91.7% of participants, (2) remission of anxiety for 100% of participants, and (3) remission of depression for 71.5% of participants. Self-guided i-CBT, in comparison, optimized the probability of remission of depression for the remaining 28.5% of participants. Meaning: Self-guided i-CBT is sometimes equally or more effective than guided i-CBT for depression but not anxiety. Importance: Guided internet-delivered cognitive behavioral therapy (i-CBT) is a low-cost way to address high unmet need for anxiety and depression treatment. Scalability could be increased if some patients were helped as much by self-guided i-CBT as guided i-CBT. Objective: To develop an individualized treatment rule using machine learning methods for guided i-CBT vs self-guided i-CBT based on a rich set of baseline predictors. Design, Setting, and Participants: This prespecified secondary analysis of an assessor-blinded, multisite randomized clinical trial of guided i-CBT, self-guided i-CBT, and treatment as usual included students in Colombia and Mexico who were seeking treatment for anxiety (defined as a 7-item Generalized Anxiety Disorder [GAD-7] score of ≥10) and/or depression (defined as a 9-item Patient Health Questionnaire [PHQ-9] score of ≥10). Study recruitment was from March 1 to October 26, 2021. Initial data analysis was conducted from May 23 to October 26, 2022. Interventions: Participants were randomized to a culturally adapted transdiagnostic i-CBT that was guided (n = 445), self-guided (n = 439), or treatment as usual (n = 435). Main Outcomes and Measures: Remission of anxiety (GAD-7 scores of ≤4) and depression (PHQ-9 scores of ≤4) 3 months after baseline. Results: The study included 1319 participants (mean [SD] age, 21.4 [3.2] years; 1038 women [78.7%]; 725 participants [55.0%] came from Mexico). A total of 1210 participants (91.7%) had significantly higher mean (SE) probabilities of joint remission of anxiety and depression with guided i-CBT (51.8% [3.0%]) than with self-guided i-CBT (37.8% [3.0%]; P =.003) or treatment as usual (40.0% [2.7%]; P =.001). The remaining 109 participants (8.3%) had low mean (SE) probabilities of joint remission of anxiety and depression across all groups (guided i-CBT: 24.5% [9.1%]; P =.007; self-guided i-CBT: 25.4% [8.8%]; P =.004; treatment as usual: 31.0% [9.4%]; P =.001). All participants with baseline anxiety had nonsignificantly higher mean (SE) probabilities of anxiety remission with guided i-CBT (62.7% [5.9%]) than the other 2 groups (self-guided i-CBT: 50.2% [6.2%]; P =.14; treatment as usual: 53.0% [6.0%]; P =.25). A total of 841 of 1177 participants (71.5%) with baseline depression had significantly higher mean (SE) probabilities of depression remission with guided i-CBT (61.5% [3.6%]) than the other 2 groups (self-guided i-CBT: 44.3% [3.7%]; P =.001; treatment as usual: 41.8% [3.2%]; P <.001). The other 336 participants (28.5%) with baseline depression had nonsignificantly higher mean (SE) probabilities of depression remission with self-guided i-CBT (54.4% [6.0%]) than guided i-CBT (39.8% [5.4%]; P =.07). Conclusions and Relevance: Guided i-CBT yielded the highest probabilities of remission of anxiety and depression for most participants; however, these differences were nonsignificant for anxiety. Some participants had the highest probabilities of remission of depression with self-guided i-CBT. Information about this variation could be used to optimize allocation of guided and self-guided i-CBT in resource-constrained settings. Trial Registration: ClinicalTrials.gov Identifier: NCT04780542 This prespecified secondary analysis of a randomized clinical trial discusses the development of an individualized treatment rule using machine learning methods for guided vs self-guided internet-delivered cognitive behavioral therapy based on a rich set of baseline predictors. [ABSTRACT FROM AUTHOR]

Background: Only a limited number of patients with major depressive disorder (MDD) respond to a first course of antidepressant medication (ADM). We investigated the feasibility of creating a baseline model to determine which of these would be among patients beginning ADM treatment in the US Veterans Health Administration (VHA). Methods: A 2018–2020 national sample of n = 660 VHA patients receiving ADM treatment for MDD completed an extensive baseline self-report assessment near the beginning of treatment and a 3-month self-report follow-up assessment. Using baseline self-report data along with administrative and geospatial data, an ensemble machine learning method was used to develop a model for 3-month treatment response defined by the Quick Inventory of Depression Symptomatology Self-Report and a modified Sheehan Disability Scale. The model was developed in a 70% training sample and tested in the remaining 30% test sample. Results: In total, 35.7% of patients responded to treatment. The prediction model had an area under the ROC curve (s.e.) of 0.66 (0.04) in the test sample. A strong gradient in probability (s.e.) of treatment response was found across three subsamples of the test sample using training sample thresholds for high [45.6% (5.5)], intermediate [34.5% (7.6)], and low [11.1% (4.9)] probabilities of response. Baseline symptom severity, comorbidity, treatment characteristics (expectations, history, and aspects of current treatment), and protective/resilience factors were the most important predictors. Conclusions: Although these results are promising, parallel models to predict response to alternative treatments based on data collected before initiating treatment would be needed for such models to help guide treatment selection. [ABSTRACT FROM AUTHOR]

Background: The effectiveness of physiotherapy to reduce low back pain depends on patient adherence to treatment. Facilitators and barriers to patient adherence are multifactorial and include patient and therapist-related factors. This Delphi study aimed to identify an expert consensus on aspects facilitating the adherence of patients with back pain to physiotherapy. Method: International experts were invited to participate in a three-round standard Delphi survey. The survey contained 49 items (32 original and 17 suggested by experts) which were rated on 5-point Likert scales. The items were assigned to six domains. The consensus level was defined as 60%. Results: Of 38 invited experts, 15 followed the invitation and completed all three rounds. A positive consensus was reached on 62% of the 49 proposed items to facilitate adherence. The highest consensus was achieved in the domains "Influence of biopsychosocial factors" (89%) and "Influence of cooperation between physiotherapists and patients" (79%). Additional important domains were the "Influence of competencies of physiotherapists" (71%) and "Interdisciplinary congruence" (78%). "Administration aspects" and the "Use of digital tools" did not reach expert consensus. Conclusions: Biopsychosocial factors, therapeutic skills, and patient-physiotherapist collaboration should be considered in physiotherapy practice to facilitate adherence in patients with LBP. Future studies should prospectively evaluate the effectiveness of individual or combined identified aspects for their influence on patient adherence in longitudinal study designs. [ABSTRACT FROM AUTHOR]

Background Young adults with chronic pain and symptoms experience disruptions to their social, emotional, physical, and vocational functioning. Interdisciplinary pain rehabilitation programs for pediatric and adult populations are not designed specifically to address the developmental needs of young adults. Methods This article describes the development of a novel intensive interdisciplinary outpatient rehabilitation program tailored to the unique needs of young adults with chronic pain and symptoms. Tailored content included vocational assessment and consultation, financial literacy education, and sexual health education. Results Outcome data demonstrate treatment gains, with reductions in pain interference, pain severity, pain catastrophizing, and depressive symptoms, as well as improvements in mental and physical quality of life, perceived performance, perceived satisfaction with performance, and objective measures of physical functioning. Conclusions The article concludes with clinical recommendations for the management of chronic pain and symptoms in young adults, applicable across multiple treatment settings. [ABSTRACT FROM AUTHOR]

D3 receptors, a key component of the dopamine system, have emerged as a potential target of therapies to improve motor symptoms across neurodegenerative and neuropsychiatric conditions. In the present work, we evaluated the effect of D3 receptor activation on the involuntary head twitches induced by 2,5-dimethoxy-4-iodoamphetamine (DOI) at behavioral and electrophysiological levels. Mice received an intraperitoneal injection of either a full D3 agonist, WC 44 [4-(2-fluoroethyl)-N-[4-[4-(2-methoxyphenyl)piperazin 1-yl]butyl]benzamide] or a partial D3 agonist, WW-III-55 [N-(4-(4-(4-methoxyphenyl)piperazin-1-yl)butyl)-4-(thiophen-3-yl)benzamide] five minutes before the intraperitoneal administration of DOI. Compared to the control group, both D3 agonists delayed the onset of th induced head-twitch response and reduced the total number and frequency of the head twitches. Moreover, the simultaneous recording of neuronal activity in the motor cortex (M1) and dorsal striatum (DS) indicated that D3 activation led to slight changes in a single unit activity, mainly in DS, and increased its correlated firing in DS or between presumed cortical pyramidal neurons (CPNs) and striatal medium spiny neurons (MSNs). Our results confirm the role of D3 receptor activation in controlling induced involuntary movements and suggest that this effect involves, at least in part, an increase in correlated corticostriatal activity. A further understanding of the underlying mechanisms may provide a suitable target for treating neuropathologies in which involuntary movements occur. [ABSTRACT FROM AUTHOR]

This article presents and discusses the available studies on utilization of waste wood (WW) resource for wood-based panel production. The cited literature indicated that the majority of WW research was from Europe and conducted mainly on recycled material from particleboard. In addition, particleboard was presented as the first option of wood-based panel product manufactured from waste wood. There was a lack of research on the recycling of plywood. Physical and chemical contaminants fluctuated strongly between low- and high-quality recycled wood mixes depending on their origins. Findings from studies also noticed that wood-based panels (e.g., particleboard) could be produced from 100% WW. However, the physical and mechanical properties of wood-based panel drop with the high proportion of WW content due to the decrease in slenderness ratio and increase in contaminants. Moreover, formaldehyde emission content of particleboard and Oriented Strand Board (OSB) manufactured from WW particles increases when the WW percentage increases. Contrary, the formaldehyde amount decreases with the increase in recycled fiber content in fiberboards. Notably, the properties and emission of recycled wood composite products could be improved by applying high-tech sorting technologies, appropriate chipping techniques, pretreatment steps and formaldehyde-free binders during waste wood handling and production process. [ABSTRACT FROM AUTHOR]

Background: Revision rates after total ankle replacements (TARs) are higher compared with other total joint replacements. The present study aimed to establish a new patient-specific implantation (PSI) technique for TAR. Material and methods: A total of 10 complete Caucasian cadaver legs had whole leg computed tomography scans. The individual geometrical ankle joint axis was determined, and based on this axis, the position of the prosthesis was planned. We assessed prosthesis placement, guiding block position, and preoperative and postoperative ankle rotational axes. Results: The guiding block position interobserver reliability was 0.37 mm 0.45 (mean ± SD) for the tibial guiding block. The value for the first talar guiding block was 1.72 ± 1.3 mm and for the second talar guiding block, 0.61 ± 0.39 mm. The tibial slope as well as the frontal angles of the anatomical tibial axis compared to the tibial and talar articular surfaces showed no statistically relevant differences with numbers available. The deviation of the assessed preoperative joint axis to the postoperative joint axis was 14.6° ± 7.8. Conclusion: The present study describes the results of an establishing process of a new PSI technique for TAR. The reliability of guiding block positioning and, thereby, prosthesis placement is sufficient. Level of Evidence: Biomechanical study [ABSTRACT FROM AUTHOR]

Background: Fewer than half of patients with major depressive disorder (MDD) respond to psychotherapy. Pre-emptively informing patients of their likelihood of responding could be useful as part of a patient-centered treatment decision-support plan. Methods: This prospective observational study examined a national sample of 807 patients beginning psychotherapy for MDD at the Veterans Health Administration. Patients completed a self-report survey at baseline and 3-months follow-up (data collected 2018–2020). We developed a machine learning (ML) model to predict psychotherapy response at 3 months using baseline survey, administrative, and geospatial variables in a 70% training sample. Model performance was then evaluated in the 30% test sample. Results: 32.0% of patients responded to treatment after 3 months. The best ML model had an AUC (SE) of 0.652 (0.038) in the test sample. Among the one-third of patients ranked by the model as most likely to respond, 50.0% in the test sample responded to psychotherapy. In comparison, among the remaining two-thirds of patients, <25% responded to psychotherapy. The model selected 43 predictors, of which nearly all were self-report variables. Conclusions: Patients with MDD could pre-emptively be informed of their likelihood of responding to psychotherapy using a prediction tool based on self-report data. This tool could meaningfully help patients and providers in shared decision-making, although parallel information about the likelihood of responding to alternative treatments would be needed to inform decision-making across multiple treatments. [ABSTRACT FROM AUTHOR]