bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cross-cultural Adaptation of the Safety Attitudes Questionnaire Short Form in Spanish and Italian Operating Rooms: Psychometric Properties
Authors: Bernalte-Martí Vicente 
Published: January 2022

Objectives
The aims of the study were to translate the Safety Attitudes Questionnaire Short Form (SAQ-SF) in Spanish and Italian surgical settings and to assess its psychometric properties.

Method
The cross-cultural adaptation process was performed following the internationally recognized guidelines. A panel of 30 experts evaluated the content validity. Test-retest reliability and internal consistency were evaluated using a cross-sectional design.

Results
The translation process was carried out without relevant difficulties. In Spain, 29 of the 36 SAQ-SF items showed excellent content validity index. In Italy, there were 33 items with an excellent rating. The SAQ-SF’s overall Cronbach α was 0.8 for both countries. Test-retest reliability showed good to very good stability in both in countries.

Conclusions
Italian and Spanish researchers rate differently the same scale, demonstrating the diversity of relevance of the same questions in different countries. A validated questionnaire is now accessible to the Spanish and Italian hospital managements of the National Health Service to measure the safety climate in day-to-day practice in the operating rooms.
Artificial Intelligence in Diagnostic Radiology: Where Do We Stand, Challenges, and Opportunities
Authors: Moawad Ahmed W. , Fuentes David T. , ElBanan Mohamed G. , Shalaby Ahmed S. , Guccione Jeffrey , Kamel Serageldin , Jensen Corey T. , Elsayes Khaled M. 
Published: January 2022

Abstract
Artificial intelligence (AI) is the most revolutionizing development in the health care industry in the current decade, with diagnostic imaging having the greatest share in such development. Machine learning and deep learning (DL) are subclasses of AI that show breakthrough performance in image analysis. They have become the state of the art in the field of image classification and recognition. Machine learning deals with the extraction of the important characteristic features from images, whereas DL uses neural networks to solve such problems with better performance. In this review, we discuss the current applications of machine learning and DL in the field of diagnostic radiology.
Deep learning applications can be divided into medical imaging analysis and applications beyond analysis. In the field of medical imaging analysis, deep convolutional neural networks are used for image classification, lesion detection, and segmentation. Also used are recurrent neural networks when extracting information from electronic medical records and to augment the use of convolutional neural networks in the field of image classification. Generative adversarial networks have been explicitly used in generating high-resolution computed tomography and magnetic resonance images and to map computed tomography images from the corresponding magnetic resonance imaging. Beyond image analysis, DL can be used for quality control, workflow organization, and reporting.
In this article, we review the most current AI models used in medical imaging research, providing a brief explanation of the various models described in the literature within the past 5 years. Emphasis is placed on the various DL models, as they are the most state-of-art in imaging analysis.
Updated Prevalence of Urinary Incontinence in Women: 2015–2018 National Population-Based Survey Data
Authors: Patel Ushma J. , Godecker Amy L. , Giles Dobie L. , Brown Heidi W. 
Published: January 2022

Objectives
This study aimed to update estimates of urinary incontinence (UI) prevalence and associated risk factors for adult women in the United States, using the National Health and Nutrition Examination Survey (NHANES).

Methods
We used descriptive analysis of 2015–2018 NHANES weighted data for women to estimate prevalence and characterize UI types and severity. Logistic regression modeling determined adjusted associations with UI.

Results
Complete data were available for 5,006 women. In weighted analyses, 61.8% had UI, corresponding to 78,297,094 adult U.S. women, with 32.4% of all women reporting symptoms at least monthly. Of those with UI, 37.5% had stress urinary incontinence, 22.0% had urgency urinary incontinence, 31.3% had mixed symptoms, and 9.2% had unspecified incontinence. The prevalence of moderate or more severe UI by Sandvik Severity Index was 22.1%, corresponding to 28,454,778 adult U.S. women. In multivariate models, increasing age, body mass index ≥25, prior vaginal birth, anxiety, depression, functional dependence, and non-Hispanic White ethnicity and race were associated with any and moderate UI. Urinary incontinence was not associated with diabetes, education level, prior hysterectomy, smoking status, physical activity level, or current pregnancy status.

Conclusions
More than 60% of community-dwelling adult women in the United States experience any UI and an increase from prior estimates (38%–49%) using NHANES data from 1999 to 2004; more than 20% experience moderate or more severe UI. Increases in UI prevalence may be related to population aging and increasing obesity prevalence. Age greater than 70 years, body mass index >40, and vaginal birth had the strongest association with UI in multivariate modeling.
Absolute Agranulocytosis After 9 Weeks of Clozapine 25 mg Daily
Authors: Friedman Joseph H. 
Published: January 2022

Background
Clozapine has been shown to be an effective and well-tolerated treatment for Parkinson disease (PD) psychosis as well as for refractory tremor in PD. Doses used are generally less than one tenth those used in treating schizophrenia. While the risk of leukopenia and agranulocytosis are reported to be independent of dose, that belief is based on the use of doses used in refractory schizophrenia. There are no published data on the risk of agranulocytosis in patients taking extremely low doses of clozapine.

Case Report
This 87-year-old man with diabetes and PD experienced a granulocyte count drop from normal, 3900, at dose initiation, to 0, at the ninth week of treatment taking clozapine 12.5 mg twice daily for refractory tremor. He recovered without developing an infection.

Conclusions
This is the first known reported case of agranulocytosis due to clozapine used at an extremely low dose. This report underscores the importance of blood monitoring, even at extremely low doses, although the exact risk remains unknown.
β-Blockers for the Treatment of Misophonia and Misokinesia
Authors: Webb Jadon 
Published: January 2022

AbstractMisophonia is an adverse physical and emotional reaction to certain repetitive trigger sounds, usually generated by other people. Misokinesia refers to visual triggers that are sometimes (but not always) related to trigger sounds. Despite how common and disabling these conditions can be, medication treatment of misophonia and misokinesia is largely unexplored. We present the first case of using a β-blocker (propranolol) to successfully treat a patient experiencing misophonia and misokinesia. A moderate dose (60 mg) of propranolol completely eliminated multiple auditory and visual trigger symptoms related to other people eating. His trigger response symptoms included overwhelming negative emotions and prominent sympathetic overactivity (fight-or-flight response). These symptoms were so severe that he had avoided most meals with friends and family for the past several years. Propranolol eliminated the emotional and physiological effects of both the auditory and visual triggers, with an Amsterdam Misophonia Scale score reduction from 15 to 2. This enabled him to resume eating meals with family and friends with no distress. The medication was well tolerated. In summary, we report the novel finding that β-blockers were markedly effective at treating the physical and emotional symptoms of a patient with misophonia and misokinesia. This suggests a novel treatment approach for these conditions.
Variation in US Drug Overdose Mortality Within and Between Hispanic/Latine Subgroups: A Disaggregation of National Data
Authors: Cano Manuel , Gelpí-Acosta Camila 
Published: January 2022

AbstractThis study examined differences across Latine heritage groups (i.e., Mexican, Puerto Rican, Cuban, Dominican, Central American, South American) in rates of US drug overdose mortality. The study utilized 2015-2019 mortality data from the National Center for Health Statistics for 29,137 Hispanic individuals who died of drug overdose. Using population estimates from the American Community Survey, age-standardized drug overdose mortality rates were calculated by specific Latine heritage and sex, nativity, educational attainment, and geographic region. Standardized rate ratios (SRRs), incidence rate ratios (IRRs) from negative binomial regression models, and 95% Confidence Intervals (CIs) were calculated, and multiple imputation was used for missing Latine heritage group in select models.Drug overdose mortality rates in the Puerto Rican heritage population were more than three times as high as in the Mexican heritage population (IRR 3.61 [95% CI 3.02-4.30] in unadjusted model; IRR 3.70 [95% CI 3.31-4.15] in model adjusting for age, sex, nativity, educational attainment, and region; SRR 3.23 [95% CI, 3.15-3.32] in age-standardized model with missing Hispanic heritage imputed). Higher age-standardized rates of drug overdose mortality were observed in males than females across all Latine groups, yet the magnitude of the sex differential varied by Latine heritage. The relationship between drug overdose mortality and nativity differed by Latine heritage; in all groups except Puerto Rican, overdose mortality rates were significantly higher in the US-born than those not US-born. In contrast, overdose mortality rates were significantly lower in US-born Puerto Ricans than in Puerto Ricans who were not US-born (e.g., born in Puerto Rico; SRR, 0.84 [95% CI 0.80-0.88]). The relationship between drug overdose mortality and educational attainment (for ages 25+) also varied between Latine groups.The diverse subgroups comprising the US Latine population vary not only in rates of drug overdose mortality, but also in demographic risk factors for fatal drug overdose.
An ensemble prediction model for COVID-19 mortality risk
Authors: Li Jie , Li Xin , Hutchinson John , Asad Mohammad , Wang Yadong , Wang Edwin 
Published: January 2022

AbstractBackgroundIt’s critical to identify COVID-19 patients with a higher death risk at early stage to give them better hospitalization or intensive care. However, thus far, none of the machine learning models has been shown to be successful in an independent cohort. We aim to develop a machine learning model which could accurately predict death risk of COVID-19 patients at an early stage in other independent cohorts.MethodsWe used a cohort containing 4711 patients whose clinical features associated with patient physiological conditions or lab test data associated with inflammation, hepatorenal function, cardiovascular function and so on to identify key features. To do so, we first developed a novel data preprocessing approach to clean up clinical features and then developed an ensemble machine learning method to identify key features.ResultsFinally, we identified 14 key clinical features whose combination reached a good predictive performance of AUC 0.907. Most importantly, we successfully validated these key features in a large independent cohort containing 15,790 patients.ConclusionsOur study shows that 14 key features are robust and useful in predicting the risk of death in patients confirmed SARS-CoV-2 infection at an early stage, and potentially useful in clinical settings to help in making clinical decisions.
qEEG Analysis in the Diagnosis of Alzheimer’s Disease; a Comparison of Functional Connectivity and Spectral Analysis
Authors: Frangopoulou Maria Semeli , Alimardani Maryam 
Published: January 2022

AbstractAlzheimer’s disease (AD) is a brain disorder that is mainly characterized by a progressive degeneration of neurons in the brain, causing a decline in cognitive abilities and difficulties in engaging in day-to-day activities. This study compares an FFT-based spectral analysis against a functional connectivity analysis based on phase synchronization, for finding known differences between AD patients and Healthy Control (HC) subjects. Both of these quantitative analysis methods were applied on a dataset comprising bipolar EEG montages’ values from 20 diagnosed AD patients and 20 age-matched HC subjects. Additionally, an attempt was made to localize the identified AD-induced brain activity effects in AD patients. The obtained results showed the advantage of the functional connectivity analysis method compared to a simple spectral analysis. Specifically, while spectral analysis could not find any significant differences between the AD and HC groups, the functional connectivity analysis showed statistically higher synchronization levels in the AD group in the lower frequency bands (delta and theta), suggesting that the AD patients’ brains are in a ‘phase-locked’ state. Further comparison of functional connectivity between the homotopic regions confirmed that the traits of AD were localized in the centro-parietal and centro-temporal areas in the theta frequency band (4-8 Hz). The contribution of this study is that it applies a neural metric for Alzheimer’s detection from a data science perspective rather than from a neuroscience one. The study shows that the combination of bipolar derivations with phase synchronization yields similar results to comparable studies employing alternative analysis methods.
Post-traumatic stress symptoms in cancer patients during the COVID-19 pandemic: a one-year longitudinal study
Authors: Bastien Etienne , Lefèvre-Arbogast Sophie , Lequesne Justine , Gernier François , Cherifi François , Rigal Olivier , Guittet Lydia , Grellard Jean-Michel , Binarelli Giulia , Lange Marie , Fernette Marie , Tron Laure , Morel Adeline , Richard Doriane , Griffon Bénédicte , Leconte Alexandra , Quilan Florian , Pépin Louis-Ferdinand , Jardin Fabrice , Leheurteur Marianne , Faveyrial Audrey , Clarisse Bénédicte , Joly Florence 
Published: January 2022

ABSTRACTBackgroundCancer patients may be particularly vulnerable to psychological consequences of the COVID-19 pandemic and successive lockdowns. We studied the prevalence and evolution of post-traumatic stress disorder (PTSD) symptoms in cancer patients during the pandemic waves, and investigated factors associated with high symptoms.MethodsCOVIPACT is a one-year longitudinal prospective study of French patients with solid/hematologic malignancy receiving treatment during the first nationwide lockdown. PTSD symptoms were measured every 3 months from April 2020 using the Impact of Event Scale-Revised. Patients also completed validated questionnaires on quality of life (QoL), cognitive complaints and insomnia, and a survey on their COVID-19 lockdown experience.ResultsLongitudinal analyses involved 386 patients with at least one PTSD assessment after baseline (median age 63, 76% female). Among them, 21.5% had moderate/severe PTSD symptoms during the first lockdown. The rate of patients reporting PTSD symptoms decreased at lockdown release (13.6%), increased again at second lockdown (23.2%), and slightly declined from the second release period (22.7%) to the third lockdown (17.5%). Patients were grouped into three trajectories of evolution. Most patients had stable low symptoms throughout the period, 6% had high baseline symptoms slowly decreasing over time, and 17.6% had moderate symptoms worsening during second lockdown. Female sex, feeling socially isolated, worrying about COVID-19 infection, and using psychotropic drugs were associated with PTSD symptoms. PTSD symptoms were associated with impaired QoL, sleep and cognition.ConclusionsAround a quarter of cancer patients presented high and persistent PTSD symptoms over the first year of the COVID-19 pandemic and may benefit from psychological support.
Extremely potent monoclonal antibodies neutralize Omicron and other SARS-CoV-2 variants
Authors: Chen Zhaochun , Zhang Peng , Matsuoka Yumiko , Tsybovsky Yaroslav , West Kamille , Santos Celia , Boyd Lisa F. , Nguyen Hanh , Pomerenke Anna , Stephens Tyler , Olia Adam S. , De Giorgi Valeria , Holbrook Michael R. , Gross Robin , Postnikova Elena , Garza Nicole L. , Johnson Reed F. , Margulies David H. , Kwong Peter D. , Alter Harvey J. , Buchholz Ursula J. , Lusso Paolo , Farci Patrizia 
Published: January 2022

SummaryThe ongoing coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has triggered a devastating global health, social and economic crisis. The RNA nature and broad circulation of this virus facilitate the accumulation of mutations, leading to the continuous emergence of variants of concern with increased transmissibility or pathogenicity1. This poses a major challenge to the effectiveness of current vaccines and therapeutic antibodies1, 2. Thus, there is an urgent need for effective therapeutic and preventive measures with a broad spectrum of action, especially against variants with an unparalleled number of mutations such as the recently emerged Omicron variant, which is rapidly spreading across the globe3. Here, we used combinatorial antibody phage-display libraries from convalescent COVID-19 patients to generate monoclonal antibodies against the receptor-binding domain of the SARS-CoV-2 spike protein with ultrapotent neutralizing activity. One such antibody, NE12, neutralizes an early isolate, the WA-1 strain, as well as the Alpha and Delta variants with half-maximal inhibitory concentrations at picomolar level. A second antibody, NA8, has an unusual breadth of neutralization, with picomolar activity against both the Beta and Omicron variants. The prophylactic and therapeutic efficacy of NE12 and NA8 was confirmed in preclinical studies in the golden Syrian hamster model. Analysis by cryo-EM illustrated the structural basis for the neutralization properties of NE12 and NA8. Potent and broadly neutralizing antibodies against conserved regions of the SARS-CoV-2 spike protein may play a key role against future variants of concern that evade immune control.
Ocimum sanctum, OscWRKY1, regulates phenylpropanoid pathway genes and promotes resistance to pathogen infection in Arabidopsis
Authors: Joshi Ashutosh , Jeena Gajendra Singh , Shikha  , Kumar Ravi , Pandey Alok , Shukla Rakesh Kumar 
Published: January 2022

AbstractWRKY transcription factor (TF) family regulates various developmental and physiological functions in plants. PAL genes encode enzymes which are involved in plant defense responses, but the direct regulation of PAL genes and phenylpropanoid pathway through WRKY TF’s is not well characterized. In the present study, we have characterized an OscWRKY1 gene from O. sanctum which shows induced expression after methyl jasmonate (MeJA), salicylic acid (SA), and wounding. Recombinant OscWRKY1 protein binds to the W-box cis-element TTGAC[C/T] and activates the reporter gene in yeast. Overexpression of OscWRKY1 enhances Arabidopsis resistance towards Pseudomonas syringae pv. tomato Pst DC3000. Upstream activator sequences of PAL and C4H have identified the conserved W-box cis-element (TTGACC) in both O. sanctum and Arabidopsis. OscWRKY1 was found to interact with W-box cis-element present in the PAL and C4H promoters. Silencing of OscWRKY1 using VIGS resulted in reduced expression of PAL, C4H, COMT, F5H and 4CL transcripts. OscWRKY1 silenced plants exhibit reduced PAL activity, whereas, the overexpression lines of OscWRKY1 in Arabidopsis exhibit increased PAL activity. These results revealed that OscWRKY1 positively regulates the phenylpropanoid pathway genes and enhances the resistance against bacterial pathogen in Arabidopsis.
matOptimize: A parallel tree optimization method enables online phylogenetics for SARS-CoV-2
Authors: Ye Cheng , Thornlow Bryan , Hinrichs Angie , Torvi Devika , Lanfear Robert , Corbett-Detig Russell , Turakhia Yatish 
Published: January 2022

AbstractPhylogenetic tree optimization is necessary for precise analysis of evolutionary and transmission dynamics, but existing tools are inadequate for handling the scale and pace of data produced during the COVID-19 pandemic. One transformative approach, online phylogenetics, aims to incrementally add samples to an ever-growing phylogeny, but there are no previously-existing approaches that can efficiently optimize this vast phylogeny under the time constraints of the pandemic. Here, we present matOptimize, a fast and memory-efficient phylogenetic tree optimization tool based on parsimony that can be parallelized across multiple CPU threads and nodes, and provides orders of magnitude improvement in runtime and peak memory usage compared to existing state-of-the-art methods. We have developed this method particularly to address the pressing need during the COVID-19 pandemic for daily maintenance and optimization of a comprehensive SARS-CoV-2 phylogeny. Thus, our approach addresses an important need for daily maintenance and refinement of a comprehensive SARS-CoV-2 phylogeny.Significance StatementPhylogenetic trees have been central to genomic surveillance, epidemiology, and contact tracing efforts during the COVD-19 pandemic. With over 6 million SARS-CoV-2 genome sequences now available, maintaining an accurate, comprehensive phylogenetic tree of all available SARS-CoV-2 sequences is becoming computationally infeasible with existing software, but is essential for getting a detailed picture of the virus’ evolution and transmission. Our novel phylogenetic software, matOptimize, is helping refine possibly the largest-ever phylogenetic tree, containing millions of SARS-CoV-2 sequences, thus providing an unprecedented resolution for studying the pathogen’s evolutionary and transmission dynamics.
Role of Yap1 in adult neural stem cell activation
Authors: Fan Wenqiang , Jurado-Arjona Jerónimo , Alanis-Lobato Gregorio , Péron Sophie , Berger Christian , Andrade-Navarro Miguel A. , Falk Sven , Berninger Benedikt 
Published: January 2022

AbstractMost adult hippocampal neural stem cells (NSCs) remain quiescent with only a minor portion undergoing active proliferation and neurogenesis. The molecular mechanisms that trigger eventually the transition from quiescence to activation are still poorly understood. Here, we found the activity of the transcriptional activator Yap1 to be enriched in active NSCs. Genetic deletion of Yap1 led to a significant reduction in the relative proportion of active NSCs supporting a physiological role of Yap1 in regulating the transition from quiescence to activation. Overexpression of wild type Yap1 in adult NSCs did not induce NSC activation suggesting tight upstream control mechanisms, but overexpression of a gain-of-function mutant (Yap1-5SA) elicited cell cycle entry in NSCs and hilar astrocytes. Consistent with a role of Yap1 in NSC activation, single cell RNA sequencing revealed the partial induction of an activated NSC gene expression program. Yet, Yap1-5SA expression also induced Taz and other key components of the Yap/Taz regulon previously identified in glioblastoma stem cell-like cells. Consequently, dysregulated Yap1 activity led to repression of hippocampal neurogenesis, promoting aberrant differentiation instead.