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Identifying biomarkers for computer-aided diagnosis (CAD) is crucial for early intervention of psychiatric disorders. Multi-site data have been utilized to increase the sample size and improve statistical power, while multi-modality classification offers significant advantages over traditional single-modality based approaches for diagnosing psychiatric disorders. However, inter-site heterogeneity and intra-modality heterogeneity present challenges to multi-site and multi-modality based classification. In this paper, brain functional and structural networks (BFNs/BSNs) from multiple sites were constructed to establish a joint multi-site multi-modality framework for psychiatric diagnosis. To do this we developed a hypergraph based multi-source domain adaptation (HMSDA) which allowed us to transform source domain subjects into a target domain. A local ordinal structure based multi-task feature selection (LOSMFS) approach was developed by integrating the transformed functional and structural connections (FCs/SCs). The effectiveness of our method was validated by evaluating diagnosis of both schizophrenia (SZ) and autism spectrum disorder (ASD). The proposed method obtained accuracies of 92.2 %±2.22 % and 84.8 %±2.68 % for the diagnosis of SZ and ASD, respectively. We also compared with 6 DA, 10 multi-modality feature selection, and 8 multi-site and multi-modality methods. Results showed the proposed HMSDA+LOSMFS effectively integrated multi-site and multi-modality data to enhance psychiatric diagnosis and identify disorder-specific diagnostic brain connections., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

Balloon pulmonary angioplasty continues to gain traction as a treatment option for patients with chronic thromboembolic pulmonary disease with and without pulmonary hypertension. Recent European Society of Cardiology guidelines on pulmonary hypertension now give balloon pulmonary angioplasty a Class 1 recommendation for inoperable and residual chronic thromboembolic pulmonary hypertension. Not surprisingly, chronic thromboembolic pulmonary hypertension centers are rapidly initiating balloon pulmonary angioplasty programs. However, we need a comprehensive, expert consensus document outlining critical concepts, including identifying necessary personnel and expertise, criteria for patient selection, and a standardized approach to preprocedural planning and establishing criteria for evaluating procedural efficacy and safety. Given this lack of standards, the balloon pulmonary angioplasty skill set is learned through peer-to-peer contact and training. This document is a state-of-the-art, comprehensive statement from key thought leaders to address this gap in the current clinical practice of balloon pulmonary angioplasty. We summarize the current status of the procedure and provide a consensus opinion on the role of balloon pulmonary angioplasty in the overall care of patients with chronic thromboembolic pulmonary disease with and without pulmonary hypertension. We also identify knowledge gaps, provide guidance for new centers interested in initiating balloon pulmonary angioplasty programs, and highlight future directions and research needs for this emerging therapy.

Background & Aims: Most of the 11.5 million feeding tubes placed annually in Europe and the USA are placed 'blind'. This carries a 1.6% risk that these tubes will enter the lung and 0.5% cause pneumothorax or pneumonia regardless of whether misplacement is identified prior to feeding. Tube placement by direct vision may reduce the risk of respiratory or oesophageal misplacement. This study externally validated whether an 'operator guide' would enable novice operators to differentiate the respiratory and alimentary tracts., Methods: One IRIS tube was placed in each of 40 patients. Novice operators interpreted anatomical position using the built-in tube camera. Interpretation was checked from recorded images by consultant gastroenterologists and end-of-procedure checks using pH or X-ray checked by Radiologists and a consultant intensivist., Results: The 40 patients were a median of 68y (IQR: 56-75), 70% male, mostly medical (65%), conscious (67.5%) and 70% had no artificial airway. Three tubes were removed due to failed placement. In the remaining 37 placements, novice operators identified the airway in 17 (45.9%) and airway + respiratory tract in 19 (51.4%), but redirected all these tubes into the oesophagus. By using direct vision to reduce the proportion of tubes near the airway or in respiratory tract from 0.514 to 0, operator discrimination between the respiratory and alimentary tracts was highly significant (0.514 vs 0: p < 0.0001, power >99.9% when significance = 0.05). In addition, organ boundaries (respiratory tract vs oesophagus, oesophagus vs stomach, stomach vs intestine) were identified in 100%., Conclusions: Novice operators, trained using the guide, identified all respiratory misplacements and accurately interpreted IRIS tube position. Guide-based training could enable widespread use of direct vision as a means to prevent tube-related complications., Competing Interests: Declaration of competing interest Consultancy for Cortrak (ST, 2007). An audit sponsored by Cortrak 2013–14 (ST). ST: 2010 and 2014 fees regarding Cortrak-related lectures were paid directly to a charity (Tear Fund). Cardinal Health awarded a grant to cover staff and equipment costs but had no part in preparing the plan, execution or publication of the project (all authors)., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Intervention studiescombiningcognitive and motor demands have reported far-transfer cognitive benefits in healthy ageing. This systematic review and meta-analysis evaluated the effects of music and rhythm intervention on cognition in older adulthood. Inclusion criteria specified: 1) musical instrument training; 2) healthy, musically-naïve adults (≥60 years); 3) control group; 4) measure of executive function. Ovid, PubMed, Scopus and the Cochrane Library online databases were searched in August 2023. Data from thirteen studies were analysed (N = 502 participants). Study quality was assessed using the Cochrane Risk of Bias tool (RoB 2; Sterne et al., 2019). Random effects models revealed: a low effect on inhibition (d = 0.27,p = .0335); a low-moderate effect on switching (d = -0.39, p = .0021); a low-moderate effect on verbal category switching (d =0.39,p = .0166); and a moderate effect on processing speed (d = 0.47,p < .0001). No effect was found for selective visual attention, working memory, or verbal memory. With regards to overall bias, three studies were rated as "high", nine studies were rated as having "some concerns" and one was rated "low". The meta-analysis suggests that learning to play a musical instrument enhances attention inhibition, switching and processing speed in ageing., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Introduction: Optimal venous thromboembolism (VTE) enoxaparin prophylaxis dosing remains elusive. Weight-based (WB) dosing safely increases anti-factor Xa levels without the need for routine monitoring but it is unclear if it leads to lower VTE risk. We hypothesized that WB dosing would decrease VTE risk compared with standard fixed dosing (SFD)., Methods: Patients from the prospective, observational CLOTT-1 registry receiving prophylactic enoxaparin (n=5539) were categorized as WB (0.45-0.55 mg/kg two times per day) or SFD (30 mg two times per day, 40 mg once a day). Multivariate logistic regression was used to generate a predicted probability of VTE for WB and SFD patients., Results: Of 4360 patients analyzed, 1065 (24.4%) were WB and 3295 (75.6%) were SFD. WB patients were younger, female, more severely injured, and underwent major operation or major venous repair at a higher rate than individuals in the SFD group. Obesity was more common among the SFD group. Unadjusted VTE rates were comparable (WB 3.1% vs. SFD 3.9%; p=0.221). Early prophylaxis was associated with lower VTE rate (1.4% vs. 5.0%; p=0.001) and deep vein thrombosis (0.9% vs. 4.4%; p<0.001), but not pulmonary embolism (0.7% vs. 1.4%; p=0.259). After adjustment, VTE incidence did not differ by dosing strategy (adjusted OR (aOR) 0.75, 95% CI 0.38 to 1.48); however, early administration was associated with a significant reduction in VTE (aOR 0.47, 95% CI 0.30 to 0.74)., Conclusion: In young trauma patients, WB prophylaxis is not associated with reduced VTE rate when compared with SFD. The timing of the initiation of chemoprophylaxis may be more important than the dosing strategy. Further studies need to evaluate these findings across a wider age and comorbidity spectrum., Level of Evidence: Level IV, therapeutic/care management., Competing Interests: Competing interests: SL reported receiving fees from Oakstone Publishing for completed work. LK reported receiving personal fees from Cerus SAB outside the submitted work. BB reported receiving grants from the US Department of Defense during the conduct of the study. MDC reported receiving grants from the US Army Medical Research Acquisition Activity during the conduct of the study. BC reported receiving grants from the National Trauma Institute during the conduct of the study. ERH reported receiving grants from the US Army Medical Research Acquisition Activity during the conduct of the study and grants from the Agency for Healthcare Research and Quality, the Patient-Centered Outcomes Research Institute, the National Heart, Lung, and Blood Institute, and the Henry M Jackson Foundation for the Advancement of Military Medicine, and speaker fees from Vizient (paid speaker for the Vizient Hospital Improvement Innovation Network VTE Prevention Acceleration Network) outside the submitted work. AJK reported receiving grants from the US Army Medical Research Acquisition Activity during the conduct of the study. LNK reported receiving grants from the Coalition for National Trauma Research of the US Department of Defense during the conduct of the study. MJM reported receiving grants from the US Department of Defense during the conduct of the study. AM reported receiving grants from the National Trauma Institute during the conduct of the study. CEW reported having stock in Decisio and receiving grants from Grifols outside the submitted work. GCV reported receiving grants from the National Institutes of Health during the conduct of the study., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Europe PMC (https://europepmc.org/) is an open access database of life science journal articles and preprints, which contains over 42 million abstracts and over 9 million full text articles accessible via the website, APIs and bulk download. This publication outlines new developments to the Europe PMC platform since the last database update in 2020 (1) and focuses on five main areas. (i) Improving discoverability, reproducibility and trust in preprints by indexing new preprint content, enriching preprint metadata and identifying withdrawn and removed preprints. (ii) Enhancing support for text and data mining by expanding the types of annotations provided and developing the Europe PMC Annotations Corpus, which can be used to train machine learning models to increase their accuracy and precision. (iii) Developing the Article Status Monitor tool and email alerts, to notify users about new articles and updates to existing records. (iv) Positioning Europe PMC as an open scholarly infrastructure through increasing the portion of open source core software, improving sustainability and accessibility of the service., (© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Background: Unguided (blind) tube placement commonly results in lung (1.6%) and oesophageal (5%) misplacement, which can lead to pneumothorax, aspiration pneumonia, death, feeding delays, and increased cost. Use of real-time direct vision may reduce risk. We validated the accuracy of a guide to train new operators in the use of direct vision-guided tube placement., Methods: Using direct vision, operators matched anatomy viewed to anatomical markers in a preliminary operator guide. We examined how accurately the guide predicted tube position, specifically whether respiratory and gastrointestinal placement could be differentiated., Results: A total of 100 patients each had one tube placement. Placement was aborted in 6% because of inability to enter or move beyond the oesophagus. In 15 of 20 placements in which the glottic opening was identified, the tube was maneuvered to avoid entry into the respiratory tract. Of 96 tubes that reached the oesophagus, 17 had entered the trachea; all were withdrawn pre-carina. One or more specific characteristics identified each organ, differentiating the trachea-oesophagus (P < 0.0001), oesophagus-stomach, and stomach-intestine in 100%. End-of-procedure tube position was ascertained by pH ≤4.0 (gastric) of aspirated fluid and/or x-ray (gastric or intestinal). In patients with a trauma risk (13%), it was avoided by identification that the tube remained within the nasal, oesophageal, or gastric lumen., Conclusion: Operators successfully matched anatomy seen by direct vision to images and descriptions of anatomy in the "operator guide." This validated that the operator guide accurately facilitates interpretation of tube position and enabled avoidance of lung trauma and oesophageal misplacement., (© 2023 The Authors. Nutrition in Clinical Practice published by Wiley Periodicals LLC on behalf of American Society for Parenteral and Enteral Nutrition.)

The examination of multivariate brain morphometry patterns has gained attention in recent years, especially for their powerful exploratory capabilities in the study of differences between patients and controls. Among the many existing methods and tools for the analysis of brain anatomy based on structural magnetic resonance imaging data, data-driven source-based morphometry (SBM) focuses on the exploratory detection of such patterns. Here, we implement a semi-blind extension of SBM, called constrained source-based morphometry (constrained SBM), which enables the extraction of maximally independent reference-alike sources using the constrained independent component analysis (ICA) approach. To do this, we combine SBM with a set of reference components covering the full brain, derived from a large independent data set (UKBiobank), to provide a fully automated SBM framework. This also allows us to implement a federated version of constrained SBM (cSBM) to allow analysis of data that is not locally accessible. In our proposed decentralized constrained source-based morphometry (dcSBM), the original data never leaves the local site. Each site operates constrained ICA on its private local data using a common distributed computation platform. Next, an aggregator/master node aggregates the results estimated from each local site and applies statistical analysis to estimate the significance of the sources. Finally, we utilize two additional multisite patient data sets to validate our model by comparing the resulting group difference estimates from both cSBM and dcSBM., (© 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Functional magnetic resonance imaging (fMRI) and structural magnetic resonance imaging (sMRI) are two widely used techniques to analyze longitudinal brain functional and structural change in adolescents. Although longitudinal changes in intrinsic functional and structural changes have been studied separately, most studies focus on univariate change rather than estimating multivariate patterns of functional network connectivity (FNC) and gray matter (GM) changes with increased age. To analyze whole-brain structural and functional changes with increased age, we suggest two complementary techniques (1: linking of functional change pattern (FCP) to voxel-wise ∆GM and 2: the connection between FCP and structural change pattern (SCP)). In this study, we apply our approaches to the functional and GM data from the large-scale Adolescent Brain and Cognitive Development (ABCD) data. We find a significant correlation between FCP and voxel-wise ∆GM for two components. We also investigate the links between FCP and SCP and hypothesize that functional connectivity and GM continue to exhibit linked changes during adolescence.Clinical Relevance- This work captures the whole-brain functional and structural change patterns link by introducing two complementary techniques.

Reliable remote cognitive testing could provide a safer assessment of cognitive impairment in multiple sclerosis (MS) during the COVID-19 pandemic and thereafter. Here we aimed to investigate the reliability and feasibility of administering Brief International Cognitive Assessment for MS (BICAMS) and the Trail-Making Test (TMT) to people with MS online. Between-group differences on BICAMS and the TMT were examined in a sample of 68 participants. Group 1 ( N  = 34) was tested in-person pre-pandemic. Group 2 was tested remotely. Within-group differences for in-person and virtual administrations were examined for Group 1. No significant differences between virtual and in-person administrations of the CVLT-II and SDMT were detected. BVMT-R scores were significantly higher for virtual administrations ( M =  20.59, SD   = 6.65) compared to in-person administrations ( M =  16.35, SD   = 6.05), possibly indicating inter-rater differences. Strong positive correlations were found for in-person and virtual scores within Group 1 on the CVLT-II ( r = . 84), SDMT ( r =  .85), TMT-A ( r =  .88), TMT-B ( r =  .76) and BVMT-R ( r  = .72). No significant differences between in-person and remote administrations of CVLT-II and SDMT in people living with MS were detected. Recommendations for future studies employing the TMT and BVMT-R online are provided.

Attention-deficit/hyperactivity disorder (ADHD) is a highly heritable neurodevelopmental disorder, with onset in childhood and a considerable likelihood to persist into adulthood. Our previous work has identified that across adults and adolescents with ADHD, gray matter volume (GMV) alteration in the frontal cortex was consistently associated with working memory underperformance, and GMV alteration in the cerebellum was associated with inattention. Recent knowledge regarding ADHD genetic risk loci makes it feasible to investigate genomic factors underlying these persistent GMV alterations, potentially illuminating the pathology of ADHD persistence. Based on this, we applied a sparsity-constrained multivariate data fusion approach, sparse parallel independent component analysis, to GMV variations in the frontal and cerebellum regions and candidate risk single nucleotide polymorphisms (SNPs) data from 341 unrelated adult participants, including 167 individuals with ADHD, 47 unaffected siblings, and 127 healthy controls. We identified one SNP component significantly associated with one GMV component in superior/middle frontal regions and replicated this association in 317 adolescents from ADHD families. The association was stronger in individuals with ADHD than in controls, and stronger in adults and older adolescents than in younger ones. The SNP component highlights 93 SNPs in long non-coding RNAs mainly in chromosome 5 and 21 protein-coding genes that are significantly enriched in human neuron cells. Eighteen identified SNPs have regulation effects on gene expression, transcript expression, isoform percentage, or methylation level in frontal regions. Identified genes highlight MEF2C, CADM2, and CADPS2, which are relevant for modulating neuronal substrates underlying high-level cognition in ADHD, and their causality effects on ADHD persistence await further investigations. Overall, through a multivariate analysis, we have revealed a genomic pattern underpinning the frontal gray matter variation related to working memory deficit in ADHD., (© 2023. The Author(s).)

Objective: Overactive bladder (OAB) is a condition that has physical, social, psychosocial, and financial impacts. Transcutaneous tibial nerve stimulation (TTNS) is a modality that stimulates the nerve root fibers of L5-S3, the same spinal segments of the parasympathetic nervous system as the bladder. This scoping review aims to identify current literature available on the feasibility and outcomes of TTNS as a first-line treatment option for OAB., Materials and Methods: A scoping review of six electronic data bases was performed to identify full-text articles from 2015 that explored the impact of TTNS on OAB and bladder dysfunction in people aged >18 years., Results: A total of 15 articles met the inclusion criteria. TTNS was compared with sham treatment, parasacral stimulation, pelvic floor muscle training (PFMT), anticholinergic medication, and percutaneous tibial nerve stimulation (PTNS). Heterogeneity in treatment application and parameters existed, with variations in treatment duration, frequency of use, and treatment settings such as pulse width (μs) and frequency (Hz). Results indicated that TTNS has efficacy equal to PFMT and PTNS in the management of OAB; however, it is not as efficacious as anticholinergic medication., Conclusions: TTNS is a promising first-line management option for people with OAB, particularly in the older population and for those with neurogenic bladder. It can provide symptomatic relief from urinary incontinence, frequency, urgency, and nocturia, while avoiding the bothersome side effects of more invasive or pharmaceutical therapies. Heterogeneity in treatment parameters limits generalizability and translation of the most appropriate clinical application and should be considered in future trials., (Copyright © 2022 International Neuromodulation Society. Published by Elsevier Inc. All rights reserved.)

Performing longitudinal and consistent risk assessments for patients with pulmonary arterial hypertension (PAH) is important to help guide treatment decisions to achieve early on and maintain a low-risk status and improve patient morbidity and mortality. Clinical gestalt or expert perception alone may over or underestimate a patient's risk status. Indeed, regular and continued use of validated risk assessment tools more accurately predict patients' survival. Effective PAH risk assessments are often underutilized even though many seasoned clinicians will attest to using these tools routinely. We present recommendations based on real-world experience in varied clinical practice settings around the United States for overcoming barriers to facilitate regular, serial formal risk assessment. Expert advanced practice provider clinicians from mid to large-size medical centers collaborated to formulate recommendations based on multiple discourses and discussions. Enlisting the help of support staff, such as medical assistants and nurses, to fill in available risk parameters in risk assessment tools can save time for providers and increase efficiency, as can technology-based solutions such as integrating risk assessments into electronic medical records. Modified, abbreviated risk assessment tools can be applied to a patient's clinical scenario when all of a patient's data are not available to complete a more comprehensive assessment. Initial discussions regarding the overall meaning and prognostic importance of risk scores may assist patients to take on a more active role in terms of informed decision-making regarding their care. A collaborative approach can help clinics establish consistent use of risk assessment., Competing Interests: Melisa Wilson is a speaker and consultant for United Therapeutics and Bayer Pharmaceuticals. Melisa Wilson has been an advisor for Janssen. Martha Kingman has been a past advisor to United Therapeutics Corporation, Actelion/Janssen, and Bayer. Susanne McDevitt is a scientific advisor to Acceleron Pharma, Bayer, Janssen Pharmaceuticals, and United Therapeutics Corporation. Jacqueline Brewer is a speaker and consultant for United Therapeutics Corporation. Frances Rogers is a speaker for United Therapeutics Corporation. Zachary Rideman and Meredith Broderick are current employees at United Therapeutics Corporation. Jennifer Keeley is a speaker for Janssen Pharmaceuticals, Bayer Pharmaceuticals, and is an advisor to Janssen Pharmaceuticals., (© 2022 The Authors. Pulmonary Circulation published by Wiley Periodicals LLC on behalf of the Pulmonary Vascular Research Institute.)

Background and Aim: The process of trial recruitment is vital, given its impact on resources, statistical power and the validity of findings. A participant information leaflet (PIL) is often the initial and primary source of information engaged by potential participants during recruitment. Research suggests that a variety of manipulations to a PIL can be made during its development to enhance understanding, readability and accessibility. In light of this, PIL-design led by Public and Patient Involvement (PPI) may also yield positive effects in this respect, as well as consent and retention. This study-within-a-trial (SWAT) compared the effects of a PPI-developed PIL with a standard, researcher-developed PIL on rates of consent, retention, decision certainty, understanding, readability, accessibility, likeability and decision to consent., Method: This SWAT used a double-blind, two-armed randomised design. The SWAT was conducted within a host trial of cognitive rehabilitation in multiple sclerosis., Results: A total of 234 people expressed interest in the trial, of which 94 were retained at 6-month follow up. Results revealed no effects on levels of consent and retention between the two PIL groups., Conclusions: These null effects provide interesting points of discussion and important implications for not only future research on PILs, but also for future research that involves recruitment to health-related interventions., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Authors.)

Background: The incidence of prostate cancer is increasing across the world, with over 1.2 million men diagnosed in 2018. Survival rates have increased significantly however the morbidity remains high. Men do report unmet sexual health needs post prostatectomy, despite this, many do not pursue treatment., Objectives: To explore men's perceptions of the education and support they receive surrounding post-prostatectomy erectile dysfunction and penile rehabilitation., Design: Systematic review and qualitative analysis based on Joanna Briggs Institute's methodology for conducting synthesis., Methods: Based on the protocol registered with PROSPERO, data were collected from the following electronic databases: MEDLINE, Web of Science, CINAHL, Psycinfo, The Cochrane Library and Embase. Titles and abstracts were screened against the inclusion and exclusion criteria, full texts were then screened, and the methodological quality of included studies was assessed using the Joanna Briggs Institutes Critical Appraisal Checklist for Qualitative Research by two independent reviewers., Results: Synthesised findings were extracted from 13 articles; four synthesised findings were identified from nine categories with 57 findings and 108 illustrations. The findings related to a perceived lack of education and support regarding all aspects of sexuality post prostatectomy. Practitioners' knowledge of gay, bisexual and single men's needs was particularly lacking. Nurses and nurse practitioners were considered to contribute positively to educational needs., Conclusions: The synthesised findings demonstrated that men do not receive sufficient education and support to initiate penile rehabilitation post-prostatectomy. Men need a holistic approach to altered sexuality and practitioners should facilitate education and treatment in a non-judgmental and all-inclusive approach., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier Ltd.)

Background: Understanding trends in prevalence and etiology is critical to public health strategies for prevention and management of injury related to high-risk recreation in elderly Americans., Methods: The National Emergency Department Sample from 2010 through 2016 was queried for patients with a principal diagnosis of trauma (ICD-9 codes 800.0-959.9) and who were 55 years and older. High-risk recreation was determined from e-codes a priori. Primary outcome measures were mortality and total hospital charges., Results: Of the 29,491,352 patient cohort, 458,599 (1.56%) engaged in high-risk activity, including those age 85 and older. High-risk cases were younger (median age 61 vs 70) and majority male (71.87% vs 39.24%). The most frequent activities were pedal cycling (45.81%), motorcycling (29.08%), and off-road vehicles (9.13%). Brain injuries (8.82% vs 3.88%), rib/sternal fractures (13.35% vs 3.53%), and cardiopulmonary injury (5.25% vs 0.57%) were more common among high-risk cases. Mortality (0.75% vs 0.40%) and total median hospital charges ($3,360 vs $2,312) were also higher for high-risk admissions, where the odds of mortality increased exponentially per year of age (odds ratio, 1.06; 99.5% CI, 1.05-1.08). High-risk recreation was associated with more than $1 billion in total hospital charges and more than 100 deaths among elderly Americans per year., Conclusion: Morbidity, mortality, and resource utilization due to high-risk recreation extend into the ninth decade of life. The patterns of injury described here offer opportunities for targeted injury prevention education to minimize risk among this growing segment of the United States population., (Copyright © 2021 Elsevier Inc. All rights reserved.)

The BRCA2 germline missense variant, R3052W, resides in the DNA binding domain and has been previously classified as a pathogenic allele. In this study, we sought to determine how R3052W alters the cellular functions of BRCA2 in the DNA damage response. The BRCA2 R3052W mutated protein exacerbates genome instability, is unable to rescue homology-directed repair, and fails to complement cell survival following exposure to PARP inhibitors and crosslinking drugs. Surprisingly, despite anticipated defects in DNA binding or RAD51-mediated DNA strand exchange, the BRCA2 R3052W protein mislocalizes to the cytoplasm precluding its ability to perform any DNA repair functions. Rather than acting as a simple loss-of-function mutation, R3052W behaves as a dominant negative allele, likely by sequestering RAD51 in the cytoplasm., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Jimenez-Sainz, Krysztofiak, Garbarino, Rogers and Jensen.)

Background: The burden of traumatic injury among workers in agriculture is substantial. Surveillance can inform injury prevention efforts to reduce farmworkers' risk. We posited that the regional trauma registry can provide surveillance for agricultural injury requiring trauma-center care., Methods: The Northeast Texas regional trauma registry was queried for patients injured in agricultural settings during 2016-2019 occurring in the 23,580 square mile study area subdivided into 219 US Census Zip Code Tract Area (ZCTA). Population at risk was estimated from the 2017 Census of Agriculture. Kuldorff's SaTScan identified case hot spots. A multivariable, geographically weighted regression model was fit for cases/1000 workers., Results: In total, 273 cases occurred, (mean 68 cases per year [95% confidence interval 55.1-80.9]) among 96 ZCTA. The mean injury rate was 3.9 (95% confidence interval 3.4-4.3) cases per 1000 farmworkers. Animals and farm machinery were the most common injury mechanisms, 52.0% and 20.9%, respectively. Trauma ZCTA demonstrated more farms (median 170 versus 95.5, P < 0.001), greater farm acreage (53,900 acres versus 32,800, P = 0.004), and higher median total product sales ($6.5 million versus $3.9 million, P < 0.001). Six hot spots were identified with relative risks from 2.85 to 5.31. The multivariable model of cases/1000 workers demonstrated significant associations with workers per ZCTA (a mean β-coefficient of 0.004 with P values <0.05 in 145 of 219 [66.5%] ZCTA) and percent rural population (β = -6.62, P values <0.05 in 76.1% of ZCTA)., Conclusions: Regional trauma registry data, combined with census data and spatial analyses, can identify actionable geographic areas of high agriculture-related injury risk., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Advances in imaging acquisition techniques allow multiple imaging modalities to be collected from the same subject. Each individual modality offers limited yet unique views of the functional, structural, or dynamic temporal features of the brain. Multimodal fusion provides effective ways to leverage these complementary perspectives from multiple modalities. However, the majority of current multimodal fusion approaches involving functional magnetic resonance imaging (fMRI) are limited to 3D feature summaries that do not incorporate its rich temporal information. Thus, we propose a novel three-way parallel group independent component analysis (pGICA) fusion method that incorporates the first-level 4D fMRI data (temporal information included) by parallelizing group ICA into parallel ICA via a unified optimization framework. A new variability matrix was defined to capture subject-wise functional variability and then link it to the mixing matrices of the other two modalities. Simulation results show that the three-way pGICA provides highly accurate cross-modality linkage estimation under both weakly and strongly correlated conditions, as well as comparable source estimation under different noise levels. Results using real brain imaging data identified one linked functional-structural-diffusion component associated to differences between schizophrenia and controls. This was replicated in an independent cohort, and the identified components were also correlated with major cognitive domains. Functional network connectivity revealed visual-subcortical and default mode-cerebellum pairs that discriminate between schizophrenia and controls. Overall, both simulation and real data results support the use of three-way pGICA to identify multimodal spatiotemporal links and to pursue the study of brain disorders under a single unifying multimodal framework., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Individuals can be characterized in a population according to their brain measurements and activity, given the inter-subject variability in brain anatomy, structure-function relationships, or life experience. Many neuroimaging studies have demonstrated the potential of functional network connectivity patterns estimated from resting functional magnetic resonance imaging (fMRI) to discriminate groups and predict information about individual subjects. However, the predictive signal present in the spatial heterogeneity of brain connectivity networks is yet to be extensively studied. In this study, we investigate, for the first time, the use of pairwise-relationships between resting-state independent spatial maps to characterize individuals. To do this, we develop a deep Siamese framework comprising three-dimensional convolution neural networks for contrastive learning based on individual-level spatial maps estimated via a fully automated fMRI independent component analysis approach. The proposed framework evaluates whether pairs of spatial networks (e.g., visual network and auditory network) are capable of subject identification and assesses the spatial variability in different network pairs' predictive power in an extensive whole-brain analysis. Our analysis on nearly 12,000 unaffected individuals from the UK Biobank study demonstrates that the proposed approach can discriminate subjects with an accuracy of up to 88% for a single network pair on the test set (best model, after several runs), and 82% average accuracy at the subcortical domain level, notably the highest average domain level accuracy attained. Further investigation of our network's learned features revealed a higher spatial variability in predictive accuracy among younger brains and significantly higher discriminative power among males. In sum, the relationship among spatial networks appears to be both informative and discriminative of individuals and should be studied further as putative brain-based biomarkers., Competing Interests: No authors have competing interests.

Objective: The goal of this study was to develop an approach that can be used where baseline risk estimates that are directly applicable to prioritized patient-important outcomes are not available from published studies., Study Design: The McMaster University GRADE Centre and the ASH guideline panel for the prevention of VTE in surgical patients developed a modeling approach based on explicit assumptions about the distribution of symptoms, anatomical location, and severity of VTE events., Results: We applied the approach to derive modeled estimates of baseline risk. These estimates were used to calculated absolute measures of anticipated effects that informed the discussion of the evidence and the formulation of 30 guideline recommendations., Conclusion: Our approach can assist guideline developers facing a lack of information about baseline risk estimates that directly apply to outcomes of interest. The use of modeled estimates increases transparency in the process and makes the baseline risk used by guideline experts explicit during their decision-making., (Copyright © 2021 Elsevier Inc. All rights reserved.)

In this study, we introduce a method to perform independent vector analysis (IVA) fusion to estimate linked independent sources and apply to a large multimodal dataset of over 3000 subjects in the UK Biobank study, including structural (gray matter), diffusion (fractional anisotropy), and functional (amplitude of low frequency fluctuations) magnetic resonance imaging data from each subject. The approach reveals a number of linked sources showing significant and meaningful covariation with subject phenotypes. One such mode shows significant linear association with age across all three modalities. Robust age-associated reductions in gray matter density were observed in thalamus, caudate, and insular regions, as well as visual and cingulate regions, with covarying reductions of fractional anisotropy in the periventricular region, in addition to reductions in amplitude of low frequency fluctuations in visual and parietal regions. Another mode identified multimodal patterns that differentiated subjects in their time-to-recall during a prospective memory test. In sum, the proposed IVA-based approach provides a flexible, interpretable, and powerful approach for revealing links between multimodal neuroimaging data.

Background: Dysfunctional reward processing is implicated in multiple mental disorders. Novelty seeking (NS) assesses preference for seeking novel experiences, which is linked to sensitivity to reward environmental cues., Methods: A subset of 14-year-old adolescents (IMAGEN) with the top 20% ranked high-NS scores was used to identify high-NS-associated multimodal components by supervised fusion. These features were then used to longitudinally predict five different risk scales for the same and unseen subjects (an independent dataset of subjects at 19 years of age that was not used in predictive modeling training at 14 years of age) (within IMAGEN, n ≈1100) and even for the corresponding symptom scores of five types of patient cohorts (non-IMAGEN), including drinking (n = 313), smoking (n = 104), attention-deficit/hyperactivity disorder (n = 320), major depressive disorder (n = 81), and schizophrenia (n = 147), as well as to classify different patient groups with diagnostic labels., Results: Multimodal biomarkers, including the prefrontal cortex, striatum, amygdala, and hippocampus, associated with high NS in 14-year-old adolescents were identified. The prediction models built on these features are able to longitudinally predict five different risk scales, including alcohol drinking, smoking, hyperactivity, depression, and psychosis for the same and unseen 19-year-old adolescents and even predict the corresponding symptom scores of five types of patient cohorts. Furthermore, the identified reward-related multimodal features can classify among attention-deficit/hyperactivity disorder, major depressive disorder, and schizophrenia with an accuracy of 87.2%., Conclusions: Adolescents with higher NS scores can be used to reveal brain alterations in the reward-related system, implicating potential higher risk for subsequent development of multiple disorders. The identified high-NS-associated multimodal reward-related signatures may serve as a transdiagnostic neuroimaging biomarker to predict disease risks or severity., (Copyright © 2021 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Introduction: Benzodiazepines (BZDs) modulate peripheral γ-amino-butyric acid type A on macrophages causing immunomodulation. They inhibit proinflammatory cytokines increasing infections. Prior studies have also shown that infections can increase thrombotic complications. We sought to examine this relationship in trauma patients. We hypothesized that the presence of BZDs on admission urine drug screen (UDS) would increase rates of both complications., Methods: All patients submitted to the Pennsylvania Trauma Outcome Study database from 2003 to 2018 were queried. Those with a positive UDS for BZDs were analyzed. Infectious complications were defined as pneumonia, urinary tract infection, sepsis, wound, and soft tissue infection, and thrombotic complications were defined as presence of pulmonary embolism or deep vein thrombosis. Logistic regressions controlling for demographic and injury covariates assessed the adjusted impact of BZDs on infectious and thrombotic complications., Results: A total of 3,393 patients (2.08%) had infectious complications, and 3,048 (1.87%) had thrombotic complications. Furthermore, 33,260 patients (20.4%) had a positive UDS for BZDs on admission. Univariate analysis showed that those positive for BZDs had higher rates of infectious (3.33% vs. 1.76%, p < 0.001) and thrombotic (2.84% vs. 1.62%, p < 0.001) complications. Multivariate analysis revealed that BZDs significantly increased the odds of infectious and thrombotic complications. Patients who tested positive for BZDs and subsequently developed infection had increased odds (adjusted odds ratio, 1.65; p < 0.001) of developing thrombotic complications., Conclusion: Trauma patients with a positive UDS for BZDs had higher odds of both infectious and thrombotic complications. Moreover, odds of thrombotic complications were higher in those with infections., Level of Evidence: Epidemiological, level III., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Background: The beneficial effects of acute rehabilitation for trauma patients are well documented but can be limited because of insurance coverage. The Patient Protection and Affordable Care Act (ACA) went into effect on March 23, 2010. The ACA allowed patients who previously did not have insurance to be fully incorporated into the health system. We sought to analyze the likelihood of discharge to rehab for trauma patients before and after the implementation of the ACA. We hypothesized that there would be a higher rate of inpatient rehabilitation hospital (IRH) admission after the ACA was put into effect., Methods: The Pennsylvania Trauma Outcome Study (PTOS) database was retrospectively queried from 2003 to 2017 for all trauma patients admitted to accredited trauma centers in Pennsylvania, who also had a functional status at discharge (FSD). Admission to an IRH was determined using discharge destination. Two categories were created to represent periods before and after ACA was implemented, 2003 to 2009 (pre-ACA) and 2010-2017 (post-ACA). A multilevel mixed-effects logistic regression model controlling for demographics, injury severity, and FSD assessed the adjusted impact of ACA implementation on IRH admissions., Results: From the Pennsylvania Trauma Outcome Study query, 341,252 patients had FSD scores and of these patients, 47,522 (13.9%) were admitted to IRH. Patients who were severely injured were more likely to be admitted to IRH. Compared with FSD scores signifying complete independence at discharge, those with lower FSD had significantly increased odds of IRH admission. The odds of IRH admission post-ACA implementation significantly increased when compared with pre-ACA years (adjusted odds ratio, 1.14; 95% confidence interval, 1.12-1.17; p < 0.001; area under the receiver operating curve, 0.818)., Conclusion: The implementation of the ACA significantly increased the likelihood of discharge to IRH for trauma patients., Level of Evidence: Care management, level III., (Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.)

Europe PMC (https://europepmc.org) is a database of research articles, including peer reviewed full text articles and abstracts, and preprints - all freely available for use via website, APIs and bulk download. This article outlines new developments since 2017 where work has focussed on three key areas: (i) Europe PMC has added to its core content to include life science preprint abstracts and a special collection of full text of COVID-19-related preprints. Europe PMC is unique as an aggregator of biomedical preprints alongside peer-reviewed articles, with over 180 000 preprints available to search. (ii) Europe PMC has significantly expanded its links to content related to the publications, such as links to Unpaywall, providing wider access to full text, preprint peer-review platforms, all major curated data resources in the life sciences, and experimental protocols. The redesigned Europe PMC website features the PubMed abstract and corresponding PMC full text merged into one article page; there is more evident and user-friendly navigation within articles and to related content, plus a figure browse feature. (iii) The expanded annotations platform offers ∼1.3 billion text mined biological terms and concepts sourced from 10 providers and over 40 global data resources., (© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Unsupervised latent variable models-blind source separation (BSS) especially-enjoy a strong reputation for their interpretability. But they seldom combine the rich diversity of information available in multiple datasets, even though multidatasets yield insightful joint solutions otherwise unavailable in isolation. We present a direct, principled approach to multidataset combination that takes advantage of multidimensional subspace structures. In turn, we extend BSS models to capture the underlying modes of shared and unique variability across and within datasets. Our approach leverages joint information from heterogeneous datasets in a flexible and synergistic fashion. We call this method multidataset independent subspace analysis (MISA). Methodological innovations exploiting the Kotz distribution for subspace modeling, in conjunction with a novel combinatorial optimization for evasion of local minima, enable MISA to produce a robust generalization of independent component analysis (ICA), independent vector analysis (IVA), and independent subspace analysis (ISA) in a single unified model. We highlight the utility of MISA for multimodal information fusion, including sample-poor regimes ( N = 600 ) and low signal-to-noise ratio, promoting novel applications in both unimodal and multimodal brain imaging data.

Practice guidelines suggest that treatment decisions in pulmonary arterial hypertension be informed by periodic assessment of patients' clinical risk. Several tools, well validated for risk discrimination, such as the Registry to Evaluate Early and Long-term Pulmonary Arterial Hypertension Disease Management calculator, were developed to assess pulmonary arterial hypertension patients' risk of death based on multiple parameters, including functional class, hemodynamics, biomarkers, comorbidities, and exercise capacity. Using an online survey, we investigated the use of risk assessment tools by pulmonary hypertension healthcare providers in the United States. Of 121 survey respondents who make treatment decisions, 59% reported using risk assessment tools. The use of these tools was lower for non-physicians (48% vs. 65% physicians) and for practitioners at centers with 1 to 100 pulmonary arterial hypertension patients compared with centers with >100 patients (47% vs. 64%). Risk was most frequently assessed by decision makers at the time of diagnosis (cited by 54%) and at the time of worsening symptoms (cited by 42%), suggesting that use of pulmonary arterial hypertension risk assessment tools remains low. In our survey, non-physicians compared with physicians cited two major barriers to increased tool use: lack of education and training (20% vs. 4%) and lack of clarity on the best tool to use (30% vs. 18%). Information technology tools, such as electronic medical record integration and web or phone-based risk calculating applications, were cited most frequently as ways to increase the use of risk assessment tools., (© The Author(s) 2020.)

The precise measurement of cosmic-ray antinuclei serves as an important means for identifying the nature of dark matter and other new astrophysical phenomena, and could be used with other cosmic-ray species to understand cosmic-ray production and propagation in the Galaxy. For instance, low-energy antideuterons would provide a "smoking gun" signature of dark matter annihilation or decay, essentially free of astrophysical background. Studies in recent years have emphasized that models for cosmic-ray antideuterons must be considered together with the abundant cosmic antiprotons and any potential observation of antihelium. Therefore, a second dedicated Antideuteron Workshop was organized at UCLA in March 2019, bringing together a community of theorists and experimentalists to review the status of current observations of cosmic-ray antinuclei, the theoretical work towards understanding these signatures, and the potential of upcoming measurements to illuminate ongoing controversies. This review aims to synthesize this recent work and present implications for the upcoming decade of antinuclei observations and searches. This includes discussion of a possible dark matter signature in the AMS-02 antiproton spectrum, the most recent limits from BESS Polar-II on the cosmic antideuteron flux, and reports of candidate antihelium events by AMS-02; recent collider and cosmic-ray measurements relevant for antinuclei production models; the state of cosmic-ray transport models in light of AMS-02 and Voyager data; and the prospects for upcoming experiments, such as GAPS. This provides a roadmap for progress on cosmic antinuclei signatures of dark matter in the coming years.

As neuroimaging data increase in complexity and related analytical problems follow suite, more researchers are drawn to collaborative frameworks that leverage data sets from multiple data-collection sites to balance out the complexity with an increased sample size. Although centralized data-collection approaches have dominated the collaborative scene, a number of decentralized approaches-those that avoid gathering data at a shared central store-have grown in popularity. We expect the prevalence of decentralized approaches to continue as privacy risks and communication overhead become increasingly important for researchers. In this article, we develop, implement and evaluate a decentralized version of one such widely used tool: dynamic functional network connectivity. Our resulting algorithm, decentralized dynamic functional network connectivity (ddFNC), synthesizes a new, decentralized group independent component analysis algorithm (dgICA) with algorithms for decentralized k-means clustering. We compare both individual decentralized components and the full resulting decentralized analysis pipeline against centralized counterparts on the same data, and show that both provide comparable performance. Additionally, we perform several experiments which evaluate the communication overhead and convergence behavior of various decentralization strategies and decentralized clustering algorithms. Our analysis indicates that ddFNC is a fine candidate for facilitating decentralized collaboration between neuroimaging researchers, and stands ready for the inclusion of privacy-enabling modifications, such as differential privacy., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.)

Multimodal data fusion is a topic of great interest. Several fusion methods have been proposed to investigate coherent patterns and corresponding linkages across modalities, such as joint independent component analysis (jICA), multiset canonical correlation analysis (mCCA), mCCA+jICA, disjoint subspace using ICA (DS-ICA) and parallel ICA. JICA exploits source independence but assumes shared loading parameters. MCCA maximizes correlation linkage across modalities directly but is limited to orthogonal features. While there is no theoretical limit to the number of modalities analyzed together by jICA, mCCA, or the two-step approach mCCA+jICA, these approaches can only extract common features and require the same number of sources/components for all modalities. On the other hand, DS-ICA and parallel ICA can identify both common and distinct features but are limited to two modalities. DS-ICA assumes shared loading parameters among common features, which works well when links are strong. Parallel ICA simultaneously maximizes correlation between modalities and independence of sources, while allowing different number of sources for each modality. However, only a very limited number of modalities and linkage pairs can be optimized. To overcome these limitations, we propose aNy-way ICA, a new model to simultaneously maximize the independence of sources and correlations across modalities. aNy-way ICA combines infomax ICA and Gaussian independent vector analysis (IVA-G) via a shared weight matrix model without orthogonality constraints. Simulation results demonstrate that aNy-way ICA not only accurately recovers sources and loadings, but also the true covariance/linkage patterns, whether different modalities have the same or different number of sources. Moreover, aNy-way ICA outperforms mCCA and mCCA+jICA in terms of source and loading recovery accuracy, especially under noisy conditions.Clinical Relevance-This establishes a model for N-way data fusion of any number of modalities and linkage pairs, allowing different number of non-orthogonal sources for different modalities.

The human brain is asymmetrically lateralized for certain functions (such as language processing) to regions in one hemisphere relative to the other. Asymmetries are measured with a laterality index (LI). However, traditional LI measures are limited by a lack of consensus on metrics used for its calculation. To address this limitation, source-based laterality (SBL) leverages an independent component analysis for the identification of laterality-specific alterations, identifying covarying components between hemispheres across subjects. SBL is successfully implemented with simulated data with inherent differences in laterality. SBL is then compared with a voxel-wise analysis utilizing structural data from a sample of patients with schizophrenia and controls without schizophrenia. SBL group comparisons identified three distinct temporal regions and one cerebellar region with significantly altered laterality in patients with schizophrenia relative to controls. Previous work highlights reductions in laterality (ie, reduced left gray matter volume) in patients with schizophrenia compared with controls without schizophrenia. Results from this pilot SBL project are the first, to our knowledge, to identify covarying laterality differences within discrete temporal brain regions. The authors argue SBL provides a unique focus to detect covarying laterality differences in patients with schizophrenia, facilitating the discovery of laterality aspects undetected in previous work., (© 2020 John Wiley & Sons, Ltd.)

Many brain imaging modalities reveal interpretable patterns after the data dimensionality is reduced and summarized via data-driven approaches. In functional magnetic resonance imaging (fMRI) studies, such summarization is often achieved through independent component analysis (ICA). ICA transforms the original data into a relatively small number of interpretable bases in voxel space (referred to as ICA spatial components, or spatial maps) and corresponding bases in the time domain (referred to as time-courses of corresponding spatial maps) In this work, we use the word "basis" to broadly refer to either of the two factors resulting from the transformation. A precise summarization for fMRI requires accurately detecting co-activation of voxels by measuring temporal dependence. Accurate measurement of dependence requires a proper understanding of the underlying temporal characteristics of the data. One way to understand such characteristics is to study the frequency spectrum of fMRI data. Researchers have argued that information regarding the underlying neuronal activity might be spread over a range of frequencies as a result of the heterogeneous temporal nature of the neuronal activity, which is reflected in its frequency spectrum. Many studies have accounted for heterogeneous characteristics of the frequency of the signal by either directly inspecting the contents of frequency domain-transformed data or augmenting their analyses with such information. For example, studies on fMRI data have investigated brain functional connectivity by leveraging frequency-adjusted measures of dependence (e.g., when a correlation is measured as a function of frequency, as with "coherence"). Although these studies measure dependence as a function of frequency, the formulation does not capture all characteristics of the frequency-based dependence. Incorporating frequency information into a summarization approach would enable the retention of important frequency-related information that exists in the original space but might be lost after performing a frequency-independent summarization. We propose a novel data-driven approach built upon ICA, which is based on measuring dependence as a generalized function of frequency. Applying this approach to fMRI data provides evidence of existing cross-frequency functional connectivity between different areas of the brain., (Copyright © 2020 Yaesoubi, Silva, Iraji and Calhoun.)

Firearm violence in the United States knows no age limit. This study compares the survival of children younger than five years to children and adolescents of age 5-19 years who presented to an ED for gunshot wounds (GSWs) in the United States to test the hypothesis of higher GSW mortality in very young children. A study of GSW patients aged 19 years and younger who survived to reach medical care was performed using the Nationwide ED Sample for 2010-2015. Hospital survival and incidence of fatal and nonfatal GSWs in the United States were the study outcomes. A multilevel logistic regression model estimated the strength of association among predictors of hospital mortality. The incidence of ED presentation for GSW is as high as 19 per 100,000 population per year. Children younger than five years were 2.7 times as likely to die compared with older children (15.3% vs 5.6%). Children younger than one year had the highest hospital mortality, 33.1 per cent. The mortality from GSW is highest among the youngest children compared with older children. This information may help policy makers and the public better understand the impact of gun violence on the youngest and most vulnerable Americans.

Independent component analysis has been widely applied to brain imaging and genetic data analyses for its ability to identify interpretable latent sources. Nevertheless, leveraging source sparsity in a more granular way may further improve its ability to optimize the solution for certain data types. For this purpose, we propose a sparse infomax algorithm based on nonlinear Hoyer projection, leveraging both sparsity and statistical independence of latent sources. The proposed algorithm iteratively updates the unmixing matrix by infomax (for independence) and the sources by Hoyer projection (for sparsity), feeding the sparse sources back as input data for the next iteration. Consequently, sparseness propagates effectively through infomax iterations, producing sources with more desirable properties. Simulation results on both brain imaging and genetic data demonstrate that the proposed algorithm yields improved pattern recovery, particularly under low signal-to-noise ratio conditions, as well as improved sparseness compared to traditional infomax.

The field of neuroimaging has recently witnessed a strong shift towards data sharing; however, current collaborative research projects may be unable to leverage institutional architectures that collect and store data in local, centralized data centers. Additionally, though research groups are willing to grant access for collaborations, they often wish to maintain control of their data locally. These concerns may stem from research culture as well as privacy and accountability concerns. In order to leverage the potential of these aggregated larger data sets, we require tools that perform joint analyses without transmitting the data. Ideally, these tools would have similar performance and ease of use as their current centralized counterparts. In this paper, we propose and evaluate a new Algorithm, decentralized joint independent component analysis (djICA), which meets these technical requirements. djICA shares only intermediate statistics about the data, plausibly retaining privacy of the raw information to local sites, thus making it amenable to further privacy protections, for example via differential privacy. We validate our method on real functional magnetic resonance imaging (fMRI) data and show that it enables collaborative large-scale temporal ICA of fMRI, a rich vein of analysis as of yet largely unexplored, and which can benefit from the larger-N studies enabled by a decentralized approach. We show that djICA is robust to different distributions of data over sites, and that the temporal components estimated with djICA show activations similar to the temporal functional modes analyzed in previous work, thus solidifying djICA as a new, decentralized method oriented toward the frontiers of temporal independent component analysis., (Copyright © 2018 Elsevier Inc. All rights reserved.)

In this paper, our goal is to explore what is known about the role of social touch during development. We first address the neural substrates of social touch and the role of tactile experience in neural development. We discuss natural variation in early exposure to social touch, followed by a discussion on experimental manipulations of social touch during development and "natural experiments", such as early institutionalization. We then consider the role of other developmental and experiential variables that predict social touch in adults. Throughout, we propose and consider new theoretical models of the role of social touch during development on later behavior and neurobiology., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

In the field of neuroimaging, there is a growing interest in developing collaborative frameworks that enable researchers to address challenging questions about the human brain by leveraging data across multiple sites all over the world. Additionally, efforts are also being directed at developing algorithms that enable collaborative analysis and feature learning from multiple sites without requiring the often large data to be centrally located. In this paper, we propose two new decentralized algorithms: (1) A decentralized regression algorithm for performing a voxel-based morphometry analysis on structural magnetic resonance imaging (MRI) data and, (2) A decentralized dynamic functional network connectivity algorithm which includes decentralized group ICA and sliding-window analysis of functional MRI data. We compare results against those obtained from their pooled (or centralized) counterparts on the same data i.e., as if they are at one site. Results produced by the decentralized algorithms are similar to the pooled-case and showcase the potential of performing multi-voxel and multivariate analyses of data located at multiple sites. Such approaches enable many more collaborative and comparative analysis in the context of large-scale neuroimaging studies.

Background: Pulmonary thromboendarterectomy (PTE) is the treatment of choice for eligible patients with chronic thromboembolic pulmonary hypertension (CTEPH). However, access to CTEPH and PTE care is limited. There is a paucity of published data on PTE efficacy and outcomes from alternative, regional centers of excellence in CTEPH and PTE care in the USA, outside a single national and international referral center., Methods: We performed a retrospective review of patients undergoing PTE at our institution from June 2013 to December 2016 (42 months), and collected clinical, echocardiographic and hemodynamic data on our patients pre- and post-PTE (N.=71)., Results: Patients age ranged between 20-83 years (mean±SD: 56±16), with 54% of patients female and 61% Caucasians. The predominant symptom was shortness of breath with a median duration of symptoms of 17 months. Following PTE, clinical improvements included a reduction in NYHA class from 3.1±1.1 to 2.2±1.2. There were major improvements in hemodynamics and echocardiographic parameters pre- versus post-PTE: mean pulmonary artery pressure (mmHg) 45±11 to 24±8, cardiac index (L/min/m2) 2.1±0.5 to 2.8±0.5, pulmonary vascular resistance (mmHg/L/min) 8.9±4.5 to 2.8±1.8, ratio of right ventricle (RV): left ventricle (LV) 1.2±0.3 to 0.9±0.2, RV fractional area change (%) 23±14 to 44±13, reduction in the incidence of RV outflow tract Doppler notching and improved pulmonary artery acceleration time (96% to 30%, and 74±19 to 111±21). In-hospital mortality was 4.2% (3 patients)., Conclusions: Herein, we report for the first time, the improvements in patient functionality, hemodynamics, right heart function and outcomes at a major regional PTE program.

European badgers (Meles meles) are a wildlife reservoir for Mycobacterium bovis (M. bovis) in parts of England, Wales and Ireland, constituting a potential source of tuberculosis (TB) infection for cattle. Vaccination of badgers against TB is one of the tools available for helping reduce the prevalence of bovine TB in badgers, made possible by the licensing in 2010 of Bacillus Calmette-Guérin (BCG) vaccine for intramuscular administration to badgers (BadgerBCG). However, practical limitations associated with administering an injected vaccine to wild animals make an oral, bait-delivered form of the vaccine highly desirable. Evaluation of the safety of oral BCG to badgers and the environment is a mandatory step on the road to licensing an oral vaccine. This study had the following objectives: (a) to determine whether adverse effects followed the oral administration of BCG vaccine to badgers; (b) to measure the quantity and frequency of BCG excreted in the faeces of vaccinated badgers; and (c) to assess whether there was evidence of the vaccine spreading to unvaccinated, 'sentinel' badgers sharing the same environment as vaccinated animals. We report here that the oral administration per badger of ≥6.4 × 10 9  cfu BCG, followed 14 days later by a single oral dose of ≥6.4 × 10 7  cfu BCG caused no adverse physical effects and did not affect the social behaviour and feeding habits of the vaccinated animals. BCG was cultured from the faeces of two of nine vaccinated animals (372 cfu/g and 996 cfu/g, respectively) approximately 48 h after the higher dose of BCG was administered and by one of the nine vaccinated animal (80 cfu/g) approximately 24 h after receiving the lower dose of BCG. We found no evidence for the transmission of BCG to unvaccinated, sentinel, badgers housed with the vaccinated animals despite the occasional excretion of BCG in faeces., (Crown Copyright © 2018. Published by Elsevier Ltd. All rights reserved.)

Background: The Trauma Audit and Research Network (TARN) in the UK publicly reports hospital performance in the management of trauma. The TARN risk adjustment model uses a fractional polynomial transformation of the Injury Severity Score (ISS) as the measure of anatomical injury severity. The Trauma Mortality Prediction Model (TMPM) is an alternative to ISS; this study compared the anatomical injury components of the TARN model with the TMPM., Methods: Data from the National Trauma Data Bank for 2011-2015 were analysed. Probability of death was estimated for the TARN fractional polynomial transformation of ISS and compared with the TMPM. The coefficients for each model were estimated using 80 per cent of the data set, selected randomly. The remaining 20 per cent of the data were used for model validation. TMPM and TARN were compared using calibration curves, measures of discrimination (area under receiver operating characteristic curves; AUROC), proximity to the true model (Akaike information criterion; AIC) and goodness of model fit (Hosmer-Lemeshow test)., Results: Some 438 058 patient records were analysed. TMPM demonstrated preferable AUROC (0·882 for TMPM versus 0·845 for TARN), AIC (18 204 versus 21 163) and better fit to the data (32·4 versus 153·0) compared with TARN., Conclusion: TMPM had greater discrimination, proximity to the true model and goodness-of-fit than the anatomical injury component of TARN. TMPM should be considered for the injury severity measure for the comparative assessment of trauma centres., (© 2018 BJS Society Ltd Published by John Wiley & Sons Ltd.)

Background: Elderly trauma care is challenging owing to the unique physiology and comorbidities prevalent in this population. To improve the care of these patients, two practice management guidelines (PMGs) were implemented: high-risk geriatric protocol (HRGP), which triages patients based on injury patterns and comorbid conditions for occult hypotension, and the anticoagulation and trauma (ACT) alert, which is designed to streamline the care of geriatric trauma patients on anticoagulants. We hypothesized that both HRGP and ACT would decrease mortality and complications in geriatric trauma patients., Methods: Geriatric blunt trauma patients (aged ≥65) presenting to our Level II center from January 2000 to July 2016 were extracted from the trauma registry. Do-not-resuscitate patients were excluded. The study period was divided into three phases: Phase 1, no PMGs in place (2000 to January 2006); Phase 2, HRGP only (February 2006 to February 2012); and Phase 3, HRGP + ACT (March 2012 to July 2016). Multivariate logistic regression models assessed adjusted mortality and complications during these phases to quantify the impact of these protocols. Statistical significance was set at p < 0.05., Results: A total of 8,471 geriatric trauma patients met inclusion criteria. Overall mortality rate was 5.6% (Phase 1, 7.2%; Phase 2, 6.1%; Phase 3, 4.0%). No significant change in mortality was observed during Phase 2 with the HRGP only (adjusted odds ratio (OR), 0.98; 95% confidence interval, 0.73-1.34; p = 0.957); however, a significantly reduced OR of mortality was found during Phase 3 with the combination of both the HRGP and ACT (adjusted OR, 0.67; 95% confidence interval, 0.47-0.94; p = 0.021). No significant changes in incidence of complications was observed over the study duration., Conclusions: Geriatric trauma patients are not simply older adults. Improved outcomes can be realized with specific PMGs tailored to the geriatric trauma patients' needs., Level of Evidence: Epidemiologic study, level III.

Europe PMC (https://europepmc.org) is a comprehensive resource of biomedical research publications that offers advanced tools for search, retrieval, and interaction with the scientific literature. This article outlines new developments since 2014. In addition to delivering the core database and services, Europe PMC focuses on three areas of development: individual user services, data integration, and infrastructure to support text and data mining. Europe PMC now provides user accounts to save search queries and claim publications to ORCIDs, as well as open access profiles for authors based on public ORCID records. We continue to foster connections between scientific data and literature in a number of ways. All the data behind the paper - whether in structured archives, generic archives or as supplemental files - are now available via links to the BioStudies database. Text-mined biological concepts, including database accession numbers and data DOIs, are highlighted in the text and linked to the appropriate data resources. The SciLite community annotation platform accepts text-mining results from various contributors and overlays them on research articles as licence allows. In addition, text miners and developers can access all open content via APIs or via the FTP site., (© The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Electroencephalographic (EEG) oscillations predominantly appear with periods between 1 s (1 Hz) and 20 ms (50 Hz), and are subdivided into distinct frequency bands which appear to correspond to distinct cognitive processes. A variety of blind source separation (BSS) approaches have been developed and implemented within the past few decades, providing an improved isolation of these distinct processes. Within the present study, we demonstrate the feasibility of multi-subject BSS for deriving distinct EEG spatiospectral maps. Multi-subject spatiospectral EEG decompositions were implemented using the EEGIFT toolbox ( http://mialab.mrn.org/software/eegift/ ) with real and realistic simulated datasets (the simulation code is available at http://mialab.mrn.org/software/simeeg ). Twelve different decomposition algorithms were evaluated. Within the simulated data, WASOBI and COMBI appeared to be the best performing algorithms, as they decomposed the four sources across a range of component numbers and noise levels. RADICAL ICA, ERBM, INFOMAX ICA, ICA EBM, FAST ICA, and JADE OPAC decomposed a subset of sources within a smaller range of component numbers and noise levels. INFOMAX ICA, FAST ICA, WASOBI, and COMBI generated the largest number of stable sources within the real dataset and provided partially distinct views of underlying spatiospectral maps. We recommend the multi-subject BSS approach and the selected algorithms for further studies examining distinct spatiospectral networks within healthy and clinical populations.

Background and Objectives: The relationship between self-esteem and paranoia may be influenced by social stress. This study aimed to replicate previous research on the impact ofsocial exclusion on paranoia and self-esteem in a non-clinical sample and to extend this work by examining the effect of exclusion on self-esteem at the 'implicit' level., Methods: Non-clinical participants (N = 85) were randomly allocated to the Inclusion or Exclusion condition of a virtual ball-toss game ('Cyberball'). They completed self-reportmeasures of state paranoia and self-esteem, and two implicit measures of self-esteem - theImplicit Association Task (IAT) and Implicit Relational Assessment Procedure (IRAP) -prior to and after exposure to Cyberball., Results: Social exclusion increased state paranoia. This effect was moderated by distress associated with trait paranoia. Exclusion was also associated with decreased self-reported self-esteem, as well as reduced implicit self-esteem on the IAT. Changes in self-reported self-esteem were associated with state paranoia at post-Cyberball. The IRAP indicated that reductions in implicit self-esteem may be due to increases in 'Me-Negative' and 'Others-Positive' biases (rather than reductions in 'Me-Positive' bias)., Limitations: The current study involved a non-clinical sample and so findings cannot be generalized to clinical paranoia., Conclusions: These findings are consistent with previous evidence that paranoia is associated with negative self-evaluations, whereas positive self-evaluations can persist in paranoia. They also provide support for the suggestion that investigations of self-esteem in paranoia should extend beyond global self-esteem and might benefit from a distinction between positive and negative components., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Introduction: The United States (US) leads all high income countries in gunshot wound (GSW) deaths. However, as a result of two decades of reduced federal support, study of GSW has been largely neglected. In this paper we describe the current state of GSW hospitalizations in the US using population-based data., Patients and Methods: We conducted an observational study of patients hospitalized for GSW in the National (Nationwide) Inpatient Sample (NIS) 2004 -2013. Our primary outcome is mortality after admission and we model its associations with gender, race, age, intent, severity of injury and weapon type, as well as providing temporal trends in hospital charges., Results: Each year approximately 30,000 patients are hospitalized for GSW, and 2500 die in hospital. Men are 9 times as likely to be hospitalized for GSW as women, but are less likely to die. Twice as many blacks are hospitalized for GSW as non-Hispanic whites. In-hospital mortality for blacks and non-Hispanic whites was similar when controlled for other factors. Most GSW (63%) are the result of assaults which overwhelmingly involve blacks; accidents are also common (23%) and more commonly involve non-Hispanic whites. Although suicide is much less common (8.3%), it accounts for 32% of all deaths; most of which are older non-Hispanic white males. Handguns are the most common weapon reported, and have the highest mortality rate (8.4%). During the study period, the annual rate of hospitalizations for GSW remained stable at 80 per 100,000 hospital admissions; median inflation-adjusted hospital charges have steadily increased by approximately 20% annually from $30,000 to $56,000 per hospitalization. The adjusted odds for mortality decreased over the study period. Although extensively reported, GSW inflicted by police and terrorists represent few hospitalizations and very few deaths., Conclusions: The preponderance GSW hospitalizations resulting from assaults on young black males and suicides among older non-Hispanic white males have continued unabated over the last decade with escalating costs. As with other widespread threats to the public wellbeing, federally funded research is required if effective interventions are to be developed., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

In the past decade, numerous advances in the study of the human brain were fostered by successful applications of blind source separation (BSS) methods to a wide range of imaging modalities. The main focus has been on extracting "networks" represented as the underlying latent sources. While the broad success in learning latent representations from multiple datasets has promoted the wide presence of BSS in modern neuroscience, it also introduced a wide variety of objective functions, underlying graphical structures, and parameter constraints for each method. Such diversity, combined with a host of datatype-specific know-how, can cause a sense of disorder and confusion, hampering a practitioner's judgment and impeding further development. We organize the diverse landscape of BSS models by exposing its key features and combining them to establish a novel unifying view of the area. In the process, we unveil important connections among models according to their properties and subspace structures. Consequently, a high-level descriptive structure is exposed, ultimately helping practitioners select the right model for their applications. Equipped with that knowledge, we review the current state of BSS applications to neuroimaging. The gained insight into model connections elicits a broader sense of generalization, highlighting several directions for model development. In light of that, we discuss emerging multi-dataset multidimensional (MDM) models and summarize their benefits for the study of the healthy brain and disease-related changes.

Principal component analysis (PCA) is widely used for data reduction in group independent component analysis (ICA) of fMRI data. Commonly, group-level PCA of temporally concatenated datasets is computed prior to ICA of the group principal components. This work focuses on reducing very high dimensional temporally concatenated datasets into its group PCA space. Existing randomized PCA methods can determine the PCA subspace with minimal memory requirements and, thus, are ideal for solving large PCA problems. Since the number of dataloads is not typically optimized, we extend one of these methods to compute PCA of very large datasets with a minimal number of dataloads. This method is coined multi power iteration (MPOWIT). The key idea behind MPOWIT is to estimate a subspace larger than the desired one, while checking for convergence of only the smaller subset of interest. The number of iterations is reduced considerably (as well as the number of dataloads), accelerating convergence without loss of accuracy. More importantly, in the proposed implementation of MPOWIT, the memory required for successful recovery of the group principal components becomes independent of the number of subjects analyzed. Highly efficient subsampled eigenvalue decomposition techniques are also introduced, furnishing excellent PCA subspace approximations that can be used for intelligent initialization of randomized methods such as MPOWIT. Together, these developments enable efficient estimation of accurate principal components, as we illustrate by solving a 1600-subject group-level PCA of fMRI with standard acquisition parameters, on a regular desktop computer with only 4 GB RAM, in just a few hours. MPOWIT is also highly scalable and could realistically solve group-level PCA of fMRI on thousands of subjects, or more, using standard hardware, limited only by time, not memory. Also, the MPOWIT algorithm is highly parallelizable, which would enable fast, distributed implementations ideal for big data analysis. Implications to other methods such as expectation maximization PCA (EM PCA) are also presented. Based on our results, general recommendations for efficient application of PCA methods are given according to problem size and available computational resources. MPOWIT and all other methods discussed here are implemented and readily available in the open source GIFT software.

Large data sets are becoming more common in fMRI and, with the advent of faster pulse sequences, memory efficient strategies for data reduction via principal component analysis (PCA) turn out to be extremely useful, especially for widely used approaches like group independent component analysis (ICA). In this commentary, we discuss results and limitations from a recent paper on the topic and attempt to provide a more complete perspective on available approaches as well as discussing various issues to consider related to PCA for very large group ICA. We also provide an analysis of computation time, memory use, and number of dataloads for a variety of approaches under multiple scenarios of small and extremely large data sets., (Copyright © 2015 Elsevier Inc. All rights reserved.)