bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of Core Stabilization Exercises on Pulmonary Function, Respiratory Muscle Strength, Peripheral Muscle Strength, Functional Capacity, and Perceived Appearance in Children With Adolescent Idiopathic Scoliosis
Authors: Yildirim Sefa , Ozyilmaz Semiramis , Elmadag Nuh Mehmet , Yabaci Aysegul 
Published: February 2022

Objective
The aim of the study was to investigate the effects of core stabilization exercises on pulmonary function, respiratory muscle strength, peripheral muscle strength, walking capacity, and perceived appearance in children with adolescent idiopathic scoliosis.

Design
This is an evaluator-blinded, randomized controlled trial. A total of 30 patients were randomly allocated to either a training group (n = 15, age = 13.8 ± 2.8 yrs, Cobb angle = 19.3 ± 6 degrees, Risser sign: n
(1) = 1; n
(2–4) = 14) or a control group (n = 15, age = 15.8 ± 3.4 yrs, Cobb angle = 20.8 ± 7.9 degrees, Risser sign: n
(1) = 1; n
(2–4) = 14). The training group received core stabilization exercises in addition to the traditional scoliosis exercises for 8 wks. The control group only received the traditional scoliosis exercises for 8 wks. Spirometry, maximal inspiratory and expiratory pressures, 6-min walking test, peripheral muscle strength, and the Walter Reed Visual Assessment Scale were assessed at the beginning and end of the study.

Results
The training group showed statistically significant improvements in maximal inspiratory pressure, maximum expiratory pressure, and Walter Reed Visual Assessment Scale score (respectively, mean changes = 17.4 ± 5.2 cmH2O; 10.6 ± 4.3 cmH2O; 2.4 ± 1.6), which were significantly larger compared with the control group (P < 0.05).

Conclusions
Core stabilization exercises given in addition to the traditional scoliosis exercise can improve respiratory muscle strength and perceived appearance in patients with adolescent idiopathic scoliosis.

To Claim CME Credits
Complete the self-assessment activity and evaluation online at http://www.physiatry.org/JournalCME

CME Objectives
Upon completion of this article, the reader should be able to: (1) Determine the evaluation methods required for scoliosis patients; (2) Evaluate respiratory parameters in scoliosis patients; and (3) Plan and implement an exercise program for scoliosis patients.

Level
Advanced

Accreditation
The Association of Academic Physiatrists is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.
The Association of Academic Physiatrists designates this Journal-based CME activity for a maximum of 1.0 AMA PRA Category 1 Credit(s)™. Physicians should only claim credit commensurate with the extent of their participation in the activity.
A Comparative Study Measuring the Difference of Healthcare Workers Reactions Among Those Involved in a Patent Safety Incident and Healthcare Professionals While Working During COVID-19
Authors: Seys Deborah , De Decker Evelien , Waelkens Hadi , Claes Stephan , Panella Massimiliano , Danckaerts Marina , Vanhaecht Kris 
Published: February 2022

Objectives
This study aimed to describe the differences and similarities in the reaction of the healthcare worker involved in a patient safety incident or during the COVID-19 pandemic. We also compared the differences in support they need.

Methods
A secondary data analysis was performed based on 2 cross-sectional survey studies. One study evaluated the impact of patient safety incidents on healthcare professionals, and the other evaluated the impact of COVID-19. Measurements on mental health reactions and an evaluation of the experienced support system were compared between 883 doctors and 1970 nurses working in different hospitals.

Results
Anxiety, difficulties concentrating, doubting knowledge and skills, feeling on their own, feeling unhappy and dejected, feeling uncertain in team, flashbacks, hypervigilance, sleep deprivation, stress and wanting to quit profession were statistically higher in the COVID-19–related groups. Second victims tend to speak about it with their own/close colleagues, whereas healthcare workers working during the COVID-19 pandemic talk more often to their partner and friends. Only a small number talked to a psychologist, but the number who needed to talk to a psychologist but did not is higher than the number who did talk to a psychologist or used professional support in all 5 groups.

Conclusions
The impact of the COVID-19 pandemic on the mental health of healthcare workers is larger than after being involved in a patient safety incident. There is the need for an adequate support system, and the mental health of all healthcare workers needs to be considered. Partners and friend play a more important role in the support experienced during the COVID-19 pandemic, and there is an important need for professional help.
An analysis of police transport in an Eastern Association for the Surgery of Trauma multicenter trial examining prehospital procedures in penetrating trauma patients
Authors: Taghavi Sharven , Maher Zoe , Goldberg Amy J. , Haut Elliott R. , Raza Shariq , Chang Grace , Tatebe Leah C. , Toraih Eman , Mendiola Michelle , Anderson Christofer , Ninokawa Scott , Maluso Patrick , Keating Jane , Burruss Sigrid , Reeves Matthew , Coleman Lauren E. , Shatz David V. , Goldenberg-Sandau Anna , Bhupathi Apoorva , Spalding M. Chance , LaRiccia Aimee , Bird Emily , Noorbakhsh Matthew R. , Babowice James , Nelson Marsha C. , Jacobson Lewis E. , Williams Jamie , Vella Michael , Dellonte Kate , Hayward Thomas Z. , Holler Emma , Lieser Mark J. , Berne John D. , Mederos Dalier R. , Askari Reza , Okafor Barbara , Etchill Eric , Fang Raymond , Roche Samantha L. , Whittenburg Laura , Bernard Andrew C. , Haan James M. , Lightwine Kelly L. , Norwood Scott H. , Murry Jason , Gamber Mark A. , Carrick Matthew M. , Bugaev Nikolay , Tatar Antony , Tatum Danielle 
Published: February 2022

BACKGROUND
Police transport (PT) of penetrating trauma patients in urban locations has become routine in certain metropolitan areas; however, whether it results in improved outcomes over prehospital Advanced life support (ALS) transport has not been determined in a multicenter study. We hypothesized that PT would not result in improved outcomes.

METHODS
This was a multicenter, prospective, observational study of adults (18+ years) with penetrating trauma to the torso and/or proximal extremity presenting at 25 urban trauma centers. Police transport and ALS patients were allocated via nearest neighbor, propensity matching. Transport mode also examined by Cox regression.

RESULTS
Of 1,618 total patients, 294 (18.2%) had PT and 1,324 (81.8%) were by ALS. After matching, 588 (294/cohort) remained. The patients were primarily Black (n = 497, 84.5%), males (n = 525, 89.3%, injured by gunshot wound (n = 494, 84.0%) with 34.5% (n = 203) having Injury Severity Score of 16 or higher. Overall mortality by propensity matching was not different between cohorts (15.6% ALS vs. 15.0% PT, p = 0.82). In severely injured patients (Injury Severity Score ≥16), mortality did not differ between PT and ALS transport (38.8% vs. 36.0%, respectively; p = 0.68). Cox regression analysis controlled for relevant factors revealed no association with a mortality benefit in patients transported by ALS.

CONCLUSION
Police transport of penetrating trauma patients in urban locations results in similar outcomes compared with ALS. Immediate transport to definitive trauma care should be emphasized in this patient population.

LEVEL OF EVIDENCE
Prognostic and Epidemiologic; Level III.
Reinstating olfactory bulb derived limbic gamma oscillations alleviates depression
Authors: Li Qun , Takeuchi Yuichi , Wang Jiale , Barcsai Livia , Pedraza Lizeth K , Kozák Gábor , Nakai Shinya , Kato Shigeki , Kobayashi Kazuto , Ohsawa Masahiro , Lőrincz Magor L , Devinsky Orrin , Buzsaki Gyorgy , Berényi Antal 
Published: February 2022

AbstractAlthough the etiology of major depressive disorder remains poorly understood, impairment of gamma oscillations recently emerged as a potential biomarker for major depression. The olfactory bulb (OB) is a major source of brain wide gamma oscillations and bulbectomy is an animal model for depression. Here we demonstrate that chemogenetic suppression of OB neuronal activity or temporally suppressing the OB to pyriform cortex synaptic transmission decreased gamma oscillation power in multiple brain areas associated with depression-like behaviors. To assess the hypothesized link between depression and diffuse depression of gamma oscillations, we employed gamma phase-dependent closed loop neuromodulation of cortical areas, paced by the native OB output. This procedure alleviated depressive-like behaviors in animals and suggests that restoring gamma oscillations may improve depression in humans.One Sentence SummaryRole of limbic gamma oscillations in depression
Evidence for Independent Processing of Shape by Vision and Touch
Authors: Miller Ryan L. , Sheinberg David L. 
Published: February 2022

AbstractAlthough visual object recognition is well-studied and relatively well understood, much less is understood about how shapes are recognized by touch and how such haptic stimuli might be compared to visual shapes. One might expect that the processes of visual and haptic object recognition engage identical brain structures given the similarity of the problem and the advantages of avoiding redundant brain circuitry, but it has not yet been established the extent to which this is true. We recruited human participants to perform a one-back same-different visual and haptic shape comparison task both within (i.e., comparing two visual shapes or two haptic shapes) and across (i.e., comparing visual with haptic shapes) modalities. Participants saw or felt a shape and responded according to whether they thought the shape was the same or different from the previously felt or seen shape. We then used various shape metrics to predict performance based on the shape, orientation, and modality of the two stimuli which were being compared on each trial. We found that the fixed orientation of the shape stimuli was an important factor for predicting within-modal behavior, but the orientation of shapes compared across modality did not depend on knowing the presented orientation. We also found that the metrics which best predict shape comparison behavior heavily depended on the modality of the two shapes. We take these results as evidence that object recognition is not necessarily performed in a single, modality-agnostic region.
New Functions Identified for HIV gp120 with the New ProtSub Sequence Matching
Authors: Litterer Benjamin , Shome Sayane , Jia Kejue , Jernigan Robert L. 
Published: February 2022

ABSTRACTThe reduced cost of sequencing is leading to an explosive growth in the number of available sequences across diverse genomes, and for individual patients. Inferring meaningful functions of individual genes/proteins is lagging, which hinders the deeper understanding of biological function and evolution. Traditionally, protein function has been determined by time consuming experimental methods or by sequence matching that often does not agree with the experimental findings. We have significantly improved protein sequence matching, by accounting for inter-dependent amino acid substitutions observed within densely packed protein structures, which yields additional substitutions beyond those usually seen, with good matches to additional proteins, some having new functions, not identified by conventional sequence matching. In the current study, we have applied this approach to predict novel functions for the proteins from HIV. These newly found functional annotations are then manually reviewed and many are validated from the literature, here for the HIV envelope protein gp120. These new functions are both more specific as well as some being entirely novel functions. We also show statistically that on average our new functional annotations are more informative than those given by conventional substitution matrices such as BLOSUM62. These results suggest that the new ProtSub protein sequence matching that incorporates structural information generally yields better identifications of related proteins, which can have broader and often gains in identifying more specific functions
IDSL.CCDB: a database for exploring inter-chemical correlations in metabolomics and exposomics datasets
Authors: Barupal Dinesh Kumar , Mahajan Priyanka , Baygi Sadjad Fakouri , Wright Robert O , Arora Manish , Teitelbaum Susan L. 
Published: February 2022

AbstractInter-chemical correlations in metabolomics and exposomics datasets provide valuable information for studying relationships among reported chemicals measured in human specimens. With an increase in the size of these datasets, a network graph analysis and visualization of the correlation structure is difficult to interpret. While co-regulatory genes databases have been developed, a similar database for metabolites and chemicals have not been developed yet. We have developed the Integrated Data Science Laboratory for Metabolomics and Exposomics - Chemical Correlation Database (IDSL.CCDB), as a systematic catalogue of inter-chemical correlation in publicly available metabolomics and exposomics studies. The database has been provided via an online interface to create single compound-centric views that are clear, readable and meaningful. We have demonstrated various applications of the database to explore: 1) the chemicals from a chemical class such as Per- and Polyfluoroalkyl Substances (PFAS), polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), phthalates and tobacco smoke related metabolites; 2) xenobiotic metabolites such as caffeine and acetaminophen; 3) endogenous metabolites (acyl-carnitines); and 4) unannotated peaks for PFAS. The database has a rich collection of 36 human studies, including the National Health and Nutrition Examination Survey (NHANES) and high-quality untargeted metabolomics datasets. IDSL.CCDB is supported by a simple, interactive and user-friendly web-interface to retrieve and visualize the inter-chemical correlation data. The IDSL.CCDB has the potential to be a key computational resource in metabolomics and exposomics facilitating the expansion of our understanding about biological and chemical relationships among metabolites and chemical exposures in the human body. The database is available atwww.ccdb.idsl.mesite.
Development of machine learning models for the prediction of complications after colorectal and small intestine surgery in psychiatric and non-psychiatric patient collectives (P-Study)
Authors: Taha-Mehlitz Stephanie , Enodien Bassey , Ochs Vincent , Hendie Ahmad , Taha Anas 
Published: February 2022

AbstractIntroductionPsychiatric and psychosomatic diseases are an increasingly cumbersome burden for the medical system. Indeed, hospital costs associated with mental health conditions have been constantly on the rise in recent years. Moreover, psychiatric conditions are likely to have a negative effect on the treatment of other medical conditions and surgical outcomes, in addition to their direct effects on the overall quality of life. Our study aims to investigate the impact of preoperative risk factors, psychiatric and psychosomatic diseases, and non-psychiatric and non-psychosomatic diseases on the outcomes of small and large bowel surgery and length of hospital stay via predictive modeling techniques.Methods and AnalysisPatient data will be collected from several participating national and international surgical centers. The machine learning models will be calculated and coded, but also published in respect to the TRIPOD guidelines (transparent reporting of a multivariable prediction model for individual prognosis or diagnosis).Expected ResultsIt is conceivable to arrive at generalizable models predicting the above-mentioned endpoints through large amounts of data from several centers. The models will be subsequently deployed as a free-to-use web-based prediction tool.Ethics and DisseminationThe ethical is approved by Cantonal Ethics Committee Zurich, Switzerland BASEC Nr. 2021-02105.
OraSure InteliSwab® Rapid Antigen Test performance with the SARS-CoV-2 Variants of Concern Alpha, Beta, Gamma, Delta, and Omicron
Authors: Weishampel Zachary A. , Young Janean , Fischl Mark , Fischer Robert J. , Donkor Irene Owusu , Riopelle Jade C. , Schulz Jonathan E. , Port Julia R. , Saturday Taylor A. , van Doremalen Neeltje , Berry Jody D. , Munster Vincent J. , Yinda Claude Kwe 
Published: February 2022

AbstractThe emergence of SARS-CoV-2 in the human population and the resulting COVID-19 pandemic has led to the development of various diagnostic tests. The OraSure InteliSwab® COVID-19 Rapid Test is a recently developed and FDA emergency use authorized rapid antigen-detecting test that functions as a lateral flow device targeting the nucleocapsid protein. Due to SARS-CoV-2 evolution, there is a need to evaluate the sensitivity of rapid antigen-detecting tests for new variants, especially variants of concern like Omicron. In this study, the sensitivity of the OraSure InteliSwab® Test was investigated using cultured strains of the known variants of concern (VOCs, Alpha, Beta, Gamma, Delta, and Omicron) and the ancestral lineage (lineage A). Based on dilution series in cell culture medium, an approximate limit of detection for each variant was determined. The OraSure InteliSwab® Test showed an overall comparable performance using recombinant nucleocapsid protein and different cultured variants with recorded limits of detection ranging between 3.77 × 105 and 9.13 × 105 RNA copies/mL. Finally, the sensitivity was evaluated using oropharyngeal swabs from Syrian golden hamsters inoculated with the 6 VOCs. Ultimately, the OraSure InteliSwab® COVID-19 Rapid Test showed no decrease in sensitivity between the ancestral SARS-CoV-2 strain and any VOCs including Omicron.
COMPARATIVE PERFORMANCE OF TWO AUTOMATED MACHINE LEARNING PLATFORMS FOR COVID-19 DETECTION BY MALDI-TOF-MS
Authors: Rashidi Hooman H. , Pepper John , Howard Taylor , Klein Karina , May Larissa , Albahra Samer , Phinney Brett , Salemi Michelle R. , Tran Nam K. 
Published: February 2022

ABSTRACTThe 2019 novel coronavirus infectious disease (COVID-19) pandemic has resulted in an unsustainable need for diagnostic tests. Currently, molecular tests are the accepted standard for the detection of SARS-CoV-2. Mass spectrometry (MS) enhanced by machine learning (ML) has recently been postulated to serve as a rapid, high-throughput, and low-cost alternative to molecular methods. Automated ML is a novel approach that could move mass spectrometry techniques beyond the confines of traditional laboratory settings. However, it remains unknown how different automated ML platforms perform for COVID-19 MS analysis. To this end, the goal of our study is to compare algorithms produced by two commercial automated ML platforms (Platforms A and B). Our study consisted of MS data derived from 361 subjects with molecular confirmation of COVID-19 status including SARS-CoV-2 variants. The top optimized ML model with respect to positive percent agreement (PPA) within Platforms A and B exhibited an accuracy of 94.9%, PPA of 100%, negative percent agreement (NPA) of 93%, and an accuracy of 91.8%, PPA of 100%, and NPA of 89%, respectively. These results illustrate the MS method’s robustness against SARS-CoV-2 variants and highlight similarities and differences in automated ML platforms in producing optimal predictive algorithms for a given dataset.
A Utility-Based Machine Learning-Driven Personalized Lifestyle Recommendation for Cardiovascular Disease Prevention
Authors: Dogan Ayse , Li Yuxuan , Odo Chiwetalu Peter , Sonawane Kalyani , Lin Ying , Liu Chenang 
Published: February 2022

AbstractIn recent decades, cardiovascular disease (CVD) has become the leading cause of death in most countries of the world. Since many types of CVD are preventable by modifying lifestyle behaviors, the objective of this paper is to develop an effective personalized lifestyle recommendation algorithm for reducing the risk of common types of CVD. However, in practice, the underlying relationships between the risk factors (e.g., lifestyles, blood pressure, etc.) and disease onset is highly complex. It is also challenging to identify the effective modification recommendations for different individuals due to the uncertainties in individuals’ preference to change and disease progression. Therefore, to address these challenges, this study developed a novel data-driven approach for personalized lifestyle behaviors recommendation based on machine learning and a personalized exponential utility function model. The contributions of this work can be summarized into three aspects: (1) a classification-based prediction model is implemented to accurately predict the CVD risk based on the condition of risk factors; (2) the generative adversarial network (GAN) is incorporated to learn the underlying relationship between risk factors, as well as quantifying the uncertainty of disease progression under lifestyle modifications; and (3) a novel personalized exponential utility function model is proposed to evaluate the modifications’ utilities with respect to CVD risk reduction, individual’s preference to change and disease progression uncertainty, and identify the optimal modification for each individual. The effectiveness of the proposed method is validated through an open-access CVD dataset. The results demonstrate that the personalized lifestyle modification recommended by the proposed methodology can significantly reduce the potential CVD risk. Thus, it is very promising to be further applied to real-world cases for CVD prevention.