bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lessons From the Field: Strategies for Success in Obtaining Grant Funding
Authors: Jennings Mathis Karen , Herbell Kayla , Ali Muhammad Ali Charania Nadia , Williams Kimberly , Mechling Brandy , Ngosa Mumba Mercy , Paun Olimpia , Willis Danny G. 
Published: September 2022

Objective: To summarize a preconference workshop that focused on how to be successful in obtaining funding by making one’s scholarship innovative and significant. Method: In 2021, at the annual American Psychiatric Nurses Association (APNA) Conference, a panel of nurse scholars reflected on and discussed how to make grant proposals innovative and significant. Two moderators posed questions to five panelists at different stages in their research trajectories about four key research concepts: idea conception, framing for the funding agency, significance, and innovation. Results: Conceptualizing an innovative, scholarly idea starts with a passion for the topic, a team of experts and scholarly community, and time to think and delve into the literature. For funding opportunities, start small, read the funding announcements thoroughly and carefully, and make sure it is the right fit. Strategies to illustrate significance include avoiding generalizations, maintaining objectivity, being clear about impact, and using strength-based language. Contemplate the many facets of innovation as well as balance innovation and feasibility. Conclusions: Inclusion of challenges in composing significance and innovation sections of grant proposals offers knowledge for psychiatric nurse researchers to add to their toolkits as they seek funding and conduct research and scholarship.
COVID-19 vaccination rates among healthcare workers by immigrant background: A nation-wide registry study from Norway
Authors: Kraft Kristian Bandlien , Elgersma Ingeborg , Lyngstad Trude Marie , Elstrøm Petter , Telle Kjetil 
Published: September 2022

Aims: Studies have suggested that some minority groups tend to have lower vaccination rates than the overall population. This study aims to examine COVID-19 vaccination rates among healthcare workers in Norway, according to immigrant background. Methods: We used individual-level, nation-wide registry data from Norway to identify all healthcare workers employed full time at 1 December 2020. We examined the relationship between country of birth and COVID-19 vaccination from December 2020 to August 2021, both crude and adjusted for, for example, age, sex, municipality of residence and detailed occupation codes in logistic regression models. Results: Among all healthcare workers in Norway, immigrants had a 9 percentage point lower vaccination rate (85%) than healthcare workers without an immigrant background (94%) at 31 August 2021. The overall vaccination rate varied by country of birth, with immigrants born in Russia (71%), Serbia (72%), Lithuania (72%), Romania (75%), Poland (76%), Eritrea (77%) and Somalia (78%) having the lowest crude vaccination rates. When we adjusted for demographics and detailed occupational codes, immigrant groups that more often worked as healthcare assistants, such as immigrants from Eritrea and Somalia, increased their vaccination rates. Conclusions: Substantial differences in vaccination rates among immigrant groups employed in the healthcare sector in Norway indicate that measures to improve vaccine uptake should focus on specific immigrant groups rather than all immigrants together. Lower vaccination rates in some immigrant groups appear to be largely driven by the occupational composition, suggesting that some of the differences in vaccine rates can be attributed to variation in vaccine access.
The Impact of Baseline User Characteristics on the Benefits of Real-Time Versus Intermittently Scanned Continuous Glucose Monitoring in Adults With Type 1 Diabetes: Moderator Analyses of the ALERTT1 Trial
Authors: Visser Margaretha Martha , Charleer Sara , Fieuws Steffen , De Block Christophe , Hilbrands Robert , Van Huffel Liesbeth , Maes Toon , Vanhaverbeke Gerd , Dirinck Eveline , Myngheer Nele , Vercammen Chris , Nobels Frank , Keymeulen Bart , Mathieu Chantal , Gillard Pieter 
Published: September 2022

Background: ALERTT1 showed that switching from intermittently scanned continuous glucose monitoring (isCGM) without alerts to real-time CGM (rtCGM) with alert functionality improved time in range (TIR; 70-180 mg/dL), glycated hemoglobin (HbA1c), time <54 mg/dL, and Hypoglycemia Fear Survey version II worry subscale (HFS-worry) score after six months in adults with type 1 diabetes (T1D). Moderator analyses aimed to identify certain subgroups that would benefit more from switching to rtCGM than others. Methods: Post hoc analyses of ALERTT1 evaluated the impact of 14 baseline characteristics on the difference (delta) in mean TIR, HbA1c, time <54 mg/dL, and HFS-worry score at six months between rtCGM and isCGM. Therefore, the delta was allowed to depend on each of these variables by including interactions in the moderator analysis model. Analyses were performed separately for each variable; variables with P < .10 in the univariable analysis were combined into a single model. Results: Univariable analyses showed no dependency of delta TIR, HbA1c, or time <54 mg/dL on variables other than CGM type. Only delta HFS-worry score depended on baseline HbA1c ( P = .0059), indicating less worries with rtCGM in people with baseline HbA1c <6.5% or ≥8%. Given P < .10 for dependency of delta TIR on insulin therapy type (favoring multiple daily injections), baseline HbA1c, and baseline TIR, these variables were combined into a multivariable analysis; interactions were not statistically significant. Conclusions: Except for HFS-worry score, no interactions between 14 baseline characteristics and the six-month intervention effect of rtCGM on TIR, HbA1c, or time <54 mg/dL were observed, supporting the conclusion of ALERTT1 that switching from isCGM without alerts to rtCGM with alert functionality is beneficial for a wide range of people with T1D.
Genomic data integration and user-defined sample-set extraction for population variant analysis
Authors: Alfonsi Tommaso , Bernasconi Anna , Canakoglu Arif , Masseroli Marco 
Published: September 2022

Abstract
Background
Population variant analysis is of great importance for gathering insights into the links between human genotype and phenotype. The 1000 Genomes Project established a valuable reference for human genetic variation; however, the integrative use of the corresponding data with other datasets within existing repositories and pipelines is not fully supported. Particularly, there is a pressing need for flexible and fast selection of population partitions based on their variant and metadata-related characteristics.

Results
Here, we target general germline or somatic mutation data sources for their seamless inclusion within an interoperable-format repository, supporting integration among them and with other genomic data, as well as their integrated use within bioinformatic workflows. In addition, we provide VarSum, a data summarization service working on sub-populations of interest selected using filters on population metadata and/or variant characteristics. The service is developed as an optimized computational framework with an Application Programming Interface (API) that can be called from within any existing computing pipeline or programming script. Provided example use cases of biological interest show the relevance, power and ease of use of the API functionalities.

Conclusions
The proposed data integration pipeline and data set extraction and summarization API pave the way for solid computational infrastructures that quickly process cumbersome variation data, and allow biologists and bioinformaticians to easily perform scalable analysis on user-defined partitions of large cohorts from increasingly available genetic variation studies. With the current tendency to large (cross)nation-wide sequencing and variation initiatives, we expect an ever growing need for the kind of computational support hereby proposed.
RTX-KG2: a system for building a semantically standardized knowledge graph for translational biomedicine
Authors: Wood E. C. , Glen Amy K. , Kvarfordt Lindsey G. , Womack Finn , Acevedo Liliana , Yoon Timothy S. , Ma Chunyu , Flores Veronica , Sinha Meghamala , Chodpathumwan Yodsawalai , Termehchy Arash , Roach Jared C. , Mendoza Luis , Hoffman Andrew S. , Deutsch Eric W. , Koslicki David , Ramsey Stephen A. 
Published: September 2022

AbstractBackgroundBiomedical translational science is increasingly using computational reasoning on repositories of structured knowledge (such as UMLS, SemMedDB, ChEMBL, Reactome, DrugBank, and SMPDB in order to facilitate discovery of new therapeutic targets and modalities. The NCATS Biomedical Data Translator project is working to federate autonomous reasoning agents and knowledge providers within a distributed system for answering translational questions. Within that project and the broader field, there is a need for a framework that can efficiently and reproducibly build an integrated, standards-compliant, and comprehensive biomedical knowledge graph that can be downloaded in standard serialized form or queried via a public application programming interface (API).ResultsTo create aknowledge providersystem within the Translator project, we have developed RTX-KG2, an open-source software system for building—and hosting a web API for querying—a biomedical knowledge graph that uses an Extract-Transform-Load approach to integrate 70 knowledge sources (including the aforementioned core six sources) into a knowledge graph with provenance information including (where available) citations. The semantic layer and schema for RTX-KG2 follow the standard Biolink model to maximize interoperability. RTX-KG2 is currently being used by multiple Translator reasoning agents, both in its downloadable form and via its SmartAPI-registered interface. Serializations of RTX-KG2 are available for download in both the pre-canonicalized form and in canonicalized form (in which synonyms are merged). The current canonicalized version (KG2.7.3) of RTX-KG2 contains 6.4M nodes and 39.3M edges with a hierarchy of 77 relationship types from Biolink.ConclusionRTX-KG2 is the first knowledge graph that integrates UMLS, SemMedDB, ChEMBL, DrugBank, Reactome, SMPDB, and 64 additional knowledge sources within a knowledge graph that conforms to the Biolink standard for its semantic layer and schema. RTX-KG2 is publicly available for querying via its API atarax.rtx.ai/api/rtxkg2/v1.2/openapi.json. The code to build RTX-KG2 is publicly available atgithub:RTXteam/RTX-KG2.
Deep multiview learning to identify imaging-driven subtypes in mild cognitive impairment
Authors: Feng Yixue , Kim Mansu , Yao Xiaohui , Liu Kefei , Long Qi , Shen Li ,   for the Alzheimer’s Disease Neuroimaging Initiative
Published: September 2022

Abstract
Background
In Alzheimer’s Diseases (AD) research, multimodal imaging analysis can unveil complementary information from multiple imaging modalities and further our understanding of the disease. One application is to discover disease subtypes using unsupervised clustering. However, existing clustering methods are often applied to input features directly, and could suffer from the curse of dimensionality with high-dimensional multimodal data. The purpose of our study is to identify multimodal imaging-driven subtypes in Mild Cognitive Impairment (MCI) participants using a multiview learning framework based on Deep Generalized Canonical Correlation Analysis (DGCCA), to learn shared latent representation with low dimensions from 3 neuroimaging modalities.

Results
DGCCA applies non-linear transformation to input views using neural networks and is able to learn correlated embeddings with low dimensions that capture more variance than its linear counterpart, generalized CCA (GCCA). We designed experiments to compare DGCCA embeddings with single modality features and GCCA embeddings by generating 2 subtypes from each feature set using unsupervised clustering. In our validation studies, we found that amyloid PET imaging has the most discriminative features compared with structural MRI and FDG PET which DGCCA learns from but not GCCA. DGCCA subtypes show differential measures in 5 cognitive assessments, 6 brain volume measures, and conversion to AD patterns. In addition, DGCCA MCI subtypes confirmed AD genetic markers with strong signals that existing late MCI group did not identify.

Conclusion
Overall, DGCCA is able to learn effective low dimensional embeddings from multimodal data by learning non-linear projections. MCI subtypes generated from DGCCA embeddings are different from existing early and late MCI groups and show most similarity with those identified by amyloid PET features. In our validation studies, DGCCA subtypes show distinct patterns in cognitive measures, brain volumes, and are able to identify AD genetic markers. These findings indicate the promise of the imaging-driven subtypes and their power in revealing disease structures beyond early and late stage MCI.
Community-based mental health and well-being interventions for older adults in low- and middle-income countries: a systematic review and meta-analysis
Authors: Giebel Clarissa , Shrestha Nipun , Reilly Siobhan , White Ross G. , Zuluaga Maria Isabel , Saldarriaga Gabriel , Liu Ginger , Allen Dawn , Gabbay Mark 
Published: September 2022

AbstractBackgroundMental health support is often scarce in low- and middle-income countries (LMIC), with mental health stigmatised. Older adults are some of the most vulnerable members of society and may require specific types of mental health support. The aim of this mixed-methods systematic review and meta-analysis was to explore the types, components, and efficacy of psychosocial community-based mental health interventions for older adults (aged 60 + years) residing in LMIC.MethodsSix databases were searched in August 2021. Studies published since 2000 were included if they collected primary quantitative or qualitative data on community-based interventions for improving mental health for older adults residing in LMICs, focusing on improving mental health and well-being outcomes. Full texts were screened by two researchers.ResultsFrom 24,378 citations identified, 40 studies met eligibility criteria. Across 12 countries, interventions were categorised into those focusing on (1) Established forms of psychological therapy; (2) Exercise; (3) Education; (4) Social engagement; (5) Multi-component. Most interventions were effective in reducing levels of depression, anxiety, and improving well-being, including reminiscence therapy, different types of socialising, and breathing and laughter exercises. Some interventions reported no benefits and those that did at times failed to report continued benefits at follow-up. Given the variations in intervention type and delivery, cultures, and outcome measures used, underpinning factors of intervention success or failure were difficult to establish.ConclusionsPsychosocial interventions for older adults in LMIC need to be adapted to local contexts depending on culture and population needs. Existing interventions and their components can be used as a foundation to produce adapted and multi-component interventions, to tackle growing and inadequate mental health care provision in LMIC.Trial registrationThe review protocol was registered on PROSPERO [CRD42021271404].
Enhanced disinfection with hybrid hydrogen peroxide fogging in a critical care setting
Authors: Khandelwal Anjay , Lapolla Brian , Bair Tina , Grinstead Frances , Hislop Meaghan , Greene Christine , Bigham Michael T. 
Published: September 2022

Abstract
Background
Environmental contamination contributes to hospital associated infections, particularly those caused by multi-drug resistant organisms (MDRO). This study investigated bioburden presence on surfaces in a critical care center’s patient rooms following typical environmental services (EVS) practices and following intervention with hybrid hydrogen peroxide™ (HHP™) fogging.

Methods
Upon patient discharge, following standard cleaning or cleaning with ultraviolet (UV) light use, patient rooms were sampled by swabbing for adenosine triphosphate (ATP) and aerobic colony counts (ACC) from five preset locations. Rooms were then fogged via HHP technology using chemical indicators and Geobacillus stearothermophilus biological indicators for sporicidal validation monitoring. Following fogging, rooms were sampled again, and results were compared.

Results
A 98% reduction in ACC was observed after fogging as compared to post EVS practices both with and without UV light use. No statistical difference was seen when comparing cleaning to cleaning with UV light use. Methicillin-resistant Staphylococcus aureus (MRSA) and Pseudomonas aeruginosa were identified following EVS practices and not detected following HHP fogging. ATP samples were reduced 88% by fogging application. Chemical and biological indicators confirmed correct application of HHP fogging, as seen through its achievement of a 6-log reduction of bacterial spores.

Conclusion
HHP fogging is a thorough and efficacious technology which, when applied to critical care patient rooms, significantly reduces bioburden on surfaces, indicating potential benefits for implementation as part of infection prevention measures.
Clinical and economic burden of respiratory syncytial virus in Spanish children: the BARI study
Authors: Martinón-Torres F. , Carmo M. , Platero L. , Drago G. , López-Belmonte J. L. , Bangert M. , Díez-Domingo J. , Garcés-Sánchez M. 
Published: September 2022

AbstractRespiratory syncytial virus (RSV) infection is a major cause of morbidity in children. However, its disease burden remains poorly understood, particularly outside of the hospital setting. Our study aimed to estimate the burden of medically attended acute lower respiratory infection (ALRI) cases potentially related to RSV in Spanish children. Longitudinal data from September 2017 to June 2018 of 51,292 children aged < 5 years old from the National Healthcare System (NHS) of two Spanish regions were used. Three case definitions were considered: (a) RSV-specific; (b) RSV-specific and unspecified acute bronchiolitis (RSV-specific and Bronchiolitis), and; (c) RSV-specific and unspecified ALRI (RSV-specific and ALRI). A total of 3460 medically attended ALRI cases potentially due to RSV were identified, of which 257 (7.4%), 164 (4.7%), and 3039 (87.8%) coded with RSV-specific, unspecific bronchiolitis, and unspecific ALRI codes, respectively. Medically attended RSV-specific and ALRI cases per 1000 children was 134.4 in the first year of life, 119.4 in the second, and 35.3 between 2 and 5 years old. Most cases were observed in otherwise healthy children (93.1%). Mean direct healthcare cost per medically attended RSV-specific and ALRI case was €1753 in the first year of life, €896 in the second, and €683 between 2 and 5 years old. Hospitalization was the main driver of these costs, accounting for 55.6%, 38.0% and 33.4%, in each respective age group. In RSV-specific cases, mean direct healthcare cost per medically attended case was higher, mostly due to hospitalization: €3362 in the first year of life (72.9% from hospitalizations), €3252 in the second (72.1%), and €3514 between 2 and 5 years old (74.2%). These findings suggest that hospitalization data alone will underestimate the RSV infections requiring medical care, as will relying only on RSV-specific codes. RSV testing and codification must be improved and preventive solutions adopted, to protect all infants, particularly during the first year of life.
Comparison of the regressive effects of aflibercept and brolucizumab on pigment epithelial detachment
Authors: Mukai Ryo , Matsumoto Hidetaka , Nagai Kazuki , Akiyama Hideo 
Published: September 2022

Abstract
Background
To compare the regressive effects of aflibercept and brolucizumab on pigment epithelial detachment (PED) in age-related macular degeneration.

Methods
Eighty-three eyes of 83 patients diagnosed with type 1 macular neovascularization were included and retrospectively analysed using multimodal imaging. Forty-nine eyes were treated with intravitreal aflibercept injections (IVA group), and 34 eyes were treated with brolucizumab (IVBr group), with three consecutive injections administered as induction therapy. Before treatment and 1, 2, and 3 months after the first treatment, the maximum height (MH) and maximum diameter (MD) of the PED were measured using optical coherence tomography in each treatment group.

Results
In the IVA group, MH at baseline (228 ± 169 μm) diminished to 180 ± 150 (P = 0.2558), 165 ± 140 (P = 0.0962), and 150 ± 129 µm (P = 0.0284) at 1, 2, and 3 months after treatment, respectively; the reduction at 3 months was significant. In contrast, in the IVBr group, the MH was 307 ± 254 µm before treatment, and it decreased to 183 ± 156 µm (P = 0.0113), 139 ± 114 µm (P = 0.0003), and 125 ± 126 µm (P < 0.0001) at 1, 2, and 3 months after treatment, respectively, and the reduction at 1 month was significant. In both groups, the MD did not regress significantly.

Conclusions
The results suggested that the MH of PED after IVBr treatment regressed faster than that after IVA treatment.
The psychometric properties and the factorial structure of COVID-19 Vaccines Acceptance scale (VAC-COVID-19) within the Arabic language in a Palestinian contex
Authors: Mahamid Fayez , Veronese Guido 
Published: September 2022

Abstract
Background
The COVID-19 Vaccines Acceptance scale (VAC-COVID-19) is an international measure designed to evaluate vaccination acceptance against the COVID-19 virus. The current scale was translated from English to Arabic and validated within the Palestinian context.

Aims
Our study aimed to test the factorial structure and the psychotic properties of the VAC-COVID-19 within the Palestinian context using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) through 484 participants selected using online method techniques.

Findings
The VAC-COVID-19 was a reliable and valid method in assessing COVID-19 vaccine acceptance among Palestinians. Results of CFA indicated a stable construct of a two-factor solution in assessing COVID-19 vaccination acceptance in a Palestinian context. (1) Reasons for not receiving the vaccination, and (2) for receiving the vaccination.

Conclusion
The VAC-COVID-19 was a valid method to assess vaccination acceptance in the Arabic language within the Palestinian context. Therefore, it is recommended to conduct similar studies with diverse samples in Palestinian society; it would be prudent to target at-risk populations needed to develop the scale and its factorial structure. The VAC-COVID-19 can be a useful measure to assess vaccination acceptance among Palestinians, enabling health providers to implement interventions to modify negative attitudes toward not receiving vaccinations.