bluuebunny/crossref_metadata_2025_split huggingface dataset:
Better late than never—a single-center review of delayed rib fixation for symptomatic rib fractures and nonunions
Authors: Bauman Zachary M. , Khan Hason , Cavlovic Lindsey , Todd Sydney , Cemaj Samuel , Daubert Trevor , Raposo-Hadley Ashley , Matos Miguel , Sheppard Olabisi , Berning Bennett , Kamien Andrew , Evans Charity H. , Cantrell Emily 
Published: September 2023

BACKGROUND
Surgical stabilization of rib fractures (SSRFs) has become an emerging therapy for treatment of patients with rib fractures. More commonly, it is used in the acute setting; however, delayed SSRF can be utilized for symptomatic rib fracture nonunions. Here, we describe our institution's experience with delayed SSRF, hypothesizing it is safe and resolves patient symptoms.

METHODS
This is a retrospective review of patients presenting to our Level I trauma center to undergo delayed SSRF for symptomatic nonunions from January 2017 to September 2022. Delayed SSRF was defined as SSRF over 2 weeks in the outpatient setting. Basic demographics were obtained. Outcomes of interest included mean pain score (preoperatively and postoperatively), intensive care unit (ICU) and hospital length of stay (LOS), and resolution of preoperative symptoms, specifically chest wall instability, with return to activities of daily living (ADLs).

RESULTS
Forty-four patients met inclusion criteria with a total of 156 symptomatic nonunion rib fractures that received delayed SSRF. The average age was 59.2 ± 11.9 years and median number of days from injury to SSRF was 172.5 (interquartile range, 27.5–200). The average number rib fractures plated per patient 3.5 ± 1.8. Only three patients required ICU admission postoperatively for no longer than 2 days. Median hospital LOS was 2 days (interquartile range 1–3 days). Average preoperative and postoperative pain score was 6.8 ± 1.9 and 2.02 ± 1.5, respectively (p < 0.001). Chest wall instability and preoperative symptoms resolved in 93.2% of patients postoperatively (p < 0.001). Two patients (4.5%) had postoperative complications that resolved after additional surgical intervention. Rib fracture healing was demonstrated on radiographic imaging during postoperative follow-up.

CONCLUSION
Delayed SSRF is safe and demonstrates significant resolution of preoperative symptoms by decreasing pain, improving chest wall stability, and allowing patients to return to activities of daily living.

LEVEL OF EVIDENCE
Therapeutic/Care Management; Level IV.
Academic-Practice Partnership to Prevent and Manage Pressure Injuries
Authors: Otts Jo Ann , Pittman Joyce , Riley Bettina , Mestas Lisa , Hall Heather 
Published: September 2023

PURPOSE:
This evidence-based quality improvement (EBQI) initiative examined the effect of an academic-practice (A-P) partnership on improvement in quality measures in an acute care setting, specifically hospital-acquired pressure injury (HAPI) prevention and management.

DESIGN:
A pre-/postdescriptive design was conducted using the practice-informed active learning program to guide the project.

PARTICIPANTS AND SETTING:
The EBQI initiative was conducted at a Southern Gulf-Coast university college of nursing and clinical nursing practice leaders at its affiliated 406-bed academic health center/level I trauma center, regional burn center, and comprehensive stroke center. Both institutions are located in the Southeastern United States (Mobile, Alabama).

METHODS:
The A-P council used a participatory action research approach and developed a practice-informed active learning program incorporating Melnyk's evidence-based practice (EBP) steps, the Donabedian Model and the Patient-Centered Outcomes Research Institute (PCORI) Stakeholder Engagement in Question Development and Prioritization (SEED).

METHOD:
Hospital-acquired pressure injuries were selected as the quality outcome to address. To identify HAPI prevention/management evidenced-based practices, the A-P council conducted an integrative literature review and developed a concept map and the Pressure Injury Prevention Gap Analysis Instrument. The gap analysis identified significant gaps between EBP and current pressure injury prevention practices, with priority ranking of gaps for action by key stakeholders.

OUTCOME:
Following the practice-informed active learning program objectives, the A-P council identified 79 HAPI best EBPs organized by Donabedian domains of structure, process, and outcome and prioritized 3 gaps for action. Actions to address the HAPI gaps included: restructuring the hospital HAPI program, incorporating appropriate leadership to guide the HAPI program, modifying the HAPI reporting process, hiring specialized experts (WOC nurses) with emphasis on pressure injury prevention, establishing a standardized HAPI prevalence survey, improving electronic documentation, increasing transparency of HAPI reporting, improving HAPI accountability at the unit level, and exploring technology to enhance skin assessment. While HAPIs increased by 6.3% from 2019 (n = 104) to 2021 (n = 111), HAPI severity (Stages 3 and 4) decreased by 9.9% from 2019 (n = 14, or 13.46%) to 2021 (n = 4, or 3.6%).

IMPLICATIONS FOR PRACTICE:
Our experience with this quality improvement initiative indicates that an A-P partnership can provide a model to address complex clinical problems, quality indicators, and quality improvement while advancing a culture of inquiry and scholarship and building nursing capacity.
Predictors of SARS-CoV-2 anti-Spike IgG antibody levels following two COVID-19 vaccine doses among children and adults in the Canadian CHILD Cohort
Authors: Azeez Rilwan , Lotoski Larisa , Winsor Geoffrey L. , Arnold Corey R. , Galipeau Yannick , Pelchat Martin , Goguen Stephanie , Simons Elinor , Moraes Theo J. , Mandhane Piush J. , Turvey Stuart E. , Bolotin Shelly , Patrick David M. , Bullard Jared , Lix Lisa M. , Doucas Natasha , Rodriguez Natalie , Brinkman Fiona S.L. , Subbarao Padmaja , Langlois Marc-André , Azad Meghan B. 
Published: September 2023

AbstractBackgroundVaccination helps prevent SARS-CoV-2 infection and severe COVID-19. However, vaccine-induced humoral immune responses vary among individuals and wane over time. We aimed to describe the SARS-CoV-2 anti-spike IgG antibody response to vaccination and identify health and demographic factors associated with this response among children and adults.MethodsWe studied a subset of double-vaccinated children (n= 151; mean age: 12 ±1.5 years, 46% female) and adults (n= 995; 44 ±6.0 years, 60% female) from the Canadian CHILD Cohort. Dried blood spots were collected over two time periods (March 2021 to September 2021; October 2021 to January 2022). Antibody levels were quantified using automated chemiluminescent ELISAs. Demographic, vaccination, and health data were collected via online questionnaires. Associations were determined using multivariable regression.ResultsOur cohort had SARS-CoV-2 anti-spike seropositivity rate of 97% following two COVID-19 vaccine doses. In both children and adults, the highest antibody levels were observed around three months post-vaccination and did not differ by biological sex. Higher antibody levels were associated with: prior SARS-CoV-2 infection (β=0.15 scaled luminescence units, 95%CI, 0.06-0.24), age <18 years (β=0.15, 95%CI 0.05-0.26) and receiving the Moderna mRNA (β=0.23, 95%CI 0.11-0.34) or Pfizer-BioNTech mRNA vaccines (β= 0.10, 95%CI, 0.02-0.18) vs. a combination of mRNA and Oxford-AstraZeneca viral vector vaccines. There were no differences in antibody levels when comparing a 3-8 vs. 9-16-week interval between vaccine doses.InterpretationWe identified key factors associated with post-vaccination antibody responses in children and adults, which could help improve future vaccine development and deployment among different population subgroups.
Prediction of mycotoxin response of DNA-wrapped nanotube sensor with machine learning
Authors: Rabbani Y. , Behjati S. , Lambert B. P. , Sajjadi S. H. , Shariaty-Niassar M. , Boghossian A. A. 
Published: September 2023

AbstractDNA-wrapped single-walled carbon nanotubes (DNA-SWCNTs) have demonstrated great versatility as optical sensors. SWCNTs emit a near-infrared fluorescence that is responsive to the slightest changes in their environment, enabling the creation of sensors that can respond to single-molecule fluctuations within the vicinity of their surfaces. The fluorescence response and surface interactions of these sensors are determined by the DNA wrapping sequence. However, the lack of information on the relationship between the DNA sequence and its effect on the SWCNT fluorescence remains a bottleneck for designing sensors specific to analytes of interest. The use of directed evolution was recently demonstrated in order to evolve SWCNT sensors towards mycotoxins through iterative cycles of DNA mutation, screening and selection. In the current work, we use the data acquired during the directed evolution of DNA-SWCNT sensors to train machine learning (ML) algorithms. Artificial neural network (ANN) and support vector machine (SVM) methods were used to predict the response of DNA-SWCNT sensors to the mycotoxin. The reliability of the models was assessed through cross-validation. The cross-validated ANN and SVM models were able to accurately classify the various DNA-SWCNTs as yielding either a high or low fluorescence response with an accuracy of 73 and 81%, respectively. The models were further tested on alternative similar and dissimilar DNA sequences outside of the initial training dataset. The ANN model showed a better ability to predict dissimilar DNA sequences resulting in a high sensor response in comparison with the SVM model. In addition, the possibility to combine the two SVM and ANN models with directed evolution methods was investigated. The experimental results showed that the SVM model was able to predict the response of DNA-SWCNT sensors with 95% accuracy. Finally, the Hierarchy and k-means++ clustering methods were used to examine the similarity and dissimilarity of each DNA sequence at every stage of our investigation. In this work, we show that the application of ML algorithms to directed evolution libraries of DNA allows one to accurately map the performances of DNA-SWCNT sensors within a particular DNA sequence space. Moreover, the computational success of this mapping provides a framework for replacing current empirical approaches with the rational design of DNA sequences for SWCNT sensing.
Combining environmental DNA and remote sensing for efficient, fine-scale mapping of arthropod biodiversity
Authors: Li Yuanheng , Devenish Christian , Tosa Marie I. , Luo Mingjie , Bell David M. , Lesmeister Damon B. , Greenfield Paul , Pichler Maximilian , Levi Taal , Yu Douglas W. 
Published: September 2023

ABSTRACTArthropods contribute importantly to ecosystem functioning but remain understudied. This undermines the validity of conservation decisions. Modern methods are now making arthropods easier to study, since arthropods can be mass-trapped, mass-identified, and semi-mass-quantified into ‘many-row (observation), many-column (species)’ datasets, with homogeneous error, high resolution, and copious environmental-covariate information. These ‘novel community datasets’ let us efficiently generate information on arthropod species distributions, conservation values, uncertainty, and the magnitude and direction of human impacts. We use a DNA-based method (barcode mapping) to produce an arthropod-community dataset from 121 Malaise-trap samples, and combine it with 29 remote-imagery layers within a joint species distribution model. With this approach, we generate distribution maps for 76 arthro-pod species across a 225 km2temperate-zone forested landscape. We combine the maps to visualise the fine-scale spatial distributions of species richness, community composition, and site irreplaceability. Old-growth forests show distinct community composition and higher species richness, and stream courses have the highest site-irreplaceability values. With this ‘sideways biodiversity modelling’ method, we demonstrate the feasibility of biodiversity mapping at sufficient spatial resolution to inform local management choices, while also being efficient enough to scale up to thousands of square kilometres.
Subchronic exposure to ambient PM2.5impairs novelty recognition and spatial memory
Authors: Kim Sun-Hong , Das Darpan , Sillé Fenna C. M. , Ramachandran Gurumurthy , Biswal Shyam 
Published: September 2023

AbstractAir pollution remains a great challenge for public health, with the detrimental effects of air pollution on cardiovascular, rhinosinusitis, and pulmonary health increasingly well understood. Recent epidemiological associations point to the adverse effects of air pollution on cognitive decline and neurodegenerative diseases. Mouse models of subchronic exposure to PM2.5(ambient air particulate matter < 2.5 µm) provide an opportunity to demonstrate the causality of target diseases. Here, we subchronically exposed mice to concentrated ambient PM2.5for 7 weeks (5 days/week; 8h/day) and assessed its effect on behavior using standard tests measuring cognition or anxiety-like behaviors. Average daily PM2.5concentration was 200 µg/m3in the PM2.5group and 10 µg/m3in the filtered air group. The novel object recognition (NOR) test was used to assess the effect of PM2.5exposure on recognition memory. The increase in exploration time for a novel object versus a familiarized object was lower for PM2.5-exposed mice (42% increase) compared to the filtered air (FA) control group (110% increase). In addition, the calculated discrimination index for novel object recognition was significantly higher in FA mice (67 %) compared to PM2.5exposed mice (57.3%). The object location test (OLT) was used to examine the effect of PM2.5exposure on spatial memory. In contrast to the FA-exposed control mice, the PM2.5exposed mice exhibited no significant increase in their exploration time between novel location versus familiarized location indicating their deficit in spatial memory. Furthermore, the discrimination index for novel location was significantly higher in FA mice (62.6%) compared to PM2.5exposed mice (51%). Overall, our results demonstrate that subchronic exposure to higher levels of PM2.5in mice causes impairment of novelty recognition and spatial memory.
The effect of lactational low protein diet on skeletal muscle during adulthood and ageing in male and female mouse offspring
Authors: Alameddine Moussira , Altinpinar Atilla Emre , Ersoy Ufuk , Kanakis Ioannis , Myrtziou-Kanaki Ioanna , Ozanne Susan E , Goljanek-Whysall Katarzyna , Vasilaki Aphrodite 
Published: September 2023

AbstractSarcopenia is characterised by loss of skeletal muscle mass and function associated with a reduction in muscle fibres. External factors, like exercise and diet, can also influence skeletal muscle mass and contribute to muscle fibre loss. Maternal programming refers to the effect of maternal environmental factors such as nutrition that lead to phenotypic changes in the offspring. Maternal malnutrition has been linked to a reduction in body weight and impaired development of skeletal muscle of the offspring; however, there are no studies that reported the long-term effect of maternal low protein diet on the ageing of skeletal muscles. This study aimed to examine how maternal protein deficiency during lactation affects skeletal muscle development and ageing in the offspring. Pups born from normally fed mothers were lactated by low protein fed mothers. Post-weaning, mice were either maintained on a low protein diet (LPD) or switched to normal protein diet (NPD). Pups born from normally fed mothers and maintained on NPD during lactation and afterwards were used as control. In males, the diet mainly affected the size of the myofibres without major effect on fibre number and led to a reduced grip strength of ageing mice (24 months). Female mice had a lower body and muscle weight at weaning but caught up with control mice at 3 months. During ageing, muscle weight, myofibre number and survival rate of female pups were significantly affected. These findings highlight longitudinal animal research for nutritional programming and the importance of sexual dimorphism in response to challenges.HighlightsPostnatal low protein diet significantly decreases the survival rate of female but not male mice.During ageing, female mice fed a low protein diet during lactation have lower muscle weight.During ageing, female mice fed a low protein diet postnatally maintain their myofibre number.Male mice fed a low protein diet postnatally have lower body weight and muscle weight throughout their lifespan.Low protein diet affects myofibres size ofTAmuscle of male but not female mice at 3 months of age however this effect is lost during ageing.
Spatiospectral image processing workflow considerations for advanced MR spectroscopy of the brain
Authors: Cai Leon Y. , Del Tufo Stephanie N. , Barquero Laura , D’Archangel Micah , Sachs Lanier , Cutting Laurie E. , Glaser Nicole , Ghetti Simona , Jaser Sarah S. , Anderson Adam W. , Jordan Lori C. , Landman Bennett A. 
Published: September 2023

ABSTRACTMagnetic resonance spectroscopy (MRS) is one of the few non-invasive imaging modalities capable of making neurochemical and metabolic measurementsin vivo. Traditionally, the clinical utility of MRS has been narrow. The most common use has been the “single-voxel spectroscopy” variant to discern the presence of a lactate peak in the spectra in one location in the brain, typically to evaluate for ischemia in neonates. Thus, the reduction of rich spectral data to a binary variable has not classically necessitated much signal processing. However, scanners have become more powerful and MRS sequences more advanced, increasing data complexity and adding 2 to 3 spatial dimensions in addition to the spectral one. The result is a spatially- and spectrally-variant MRS image ripe for image processing innovation. Despite this potential, the logistics for robustly accessing and manipulating MRS data across different scanners, data formats, and software standards remain unclear. Thus, as research into MRS advances, there is a clear need to better characterize its image processing considerations to facilitate innovation from scientists and engineers. Building on established neuroimaging standards, we describe a framework for manipulating these images that generalizes to the voxel, spectral, and metabolite level across space and multiple imaging sites while integrating with LCModel, a widely used quantitative MRS peak-fitting platform. In doing so, we provide examples to demonstrate the advantages of such a workflow in relation to recent publications and with new data. Overall, we hope our characterizations will lower the barrier of entry to MRS processing for neuroimaging researchers.
Essential role of an acidic endosomal environment in JAK3-mediated signal transduction
Authors: Amano Yuji , Tanaka Nobuyuki , Takeshita Toshikazu , Kojima Katsuhiko 
Published: September 2023

SummaryThe endosome, an acidic organelle, is a platform for endocytic trafficking and signal transduction. Chloroquine, an intercellular acidic vesicle neutralizer (IAVN), has been used to treat autoimmune diseases. Its immunosuppressive mechanism remains unclear, although several modes of action attributable to lysosomal dysfunction have been postulated. This study found that IAVNs, including chloroquine, can selectively interfere with common cytokine receptor γ chain (γc) cytokine-induced signal transduction. Our data show that JAK3 targets endosomal membranes in an acidic pH-dependent manner, which is essential for γc-cytokine-induced functional signal complex formation and signal activation. Among IAVNs, Monensin and similar ionophores were particularly effective in suppressing γc-cytokine-induced cell proliferation in vitro. Monensin exerted therapeutic effects in a collagen-induced arthritis mouse model by interfering with T helper 17 cells. Our findings help further understand the immunosuppressive mechanism of IAVNs and unveil the spatial regulation of JAK3-mediated signal transduction via endosomes.
Simplicity: web-based visualization and analysis of high-throughput cancer cell line screens
Authors: Ling Alexander L. , Zhang Weijie , Lee Adam , Xia Yunong , Su Mei-Chi , Gruener Robert F. , Jena Sampreeti , Huang Yingbo , Pareek Siddhika , Shan Yuting , Huang R. Stephanie 
Published: September 2023

AbstractHigh-throughput drug screens are a powerful tool for cancer drug development. However, the results of such screens are often made available only as raw data, which is intractable for researchers without informatic skills, or as highly processed summary statistics, which can lack essential information for translating screening results into clinically meaningful discoveries. To improve the usability of these datasets, we developed Simplicity, a robust and user-friendly web interface for visualizing, exploring, and summarizing raw and processed data from high-throughput drug screens. Importantly, Simplicity allows for easy recalculation of summary statistics at user-defined drug concentrations. This allows Simplicity’s outputs to be used with methods that rely on statistics being calculated at clinically relevant doses. Simplicity can be freely accessed athttps://oncotherapyinformatics.org/simplicity/.
Benchmarking Hayai-Annotation Plants: A Re-evaluation Using Standard Evaluation Metrics
Authors: Ghelfi Andrea , Shirasawa Kenta , Isobe Sachiko 
Published: September 2023

AbstractThe rapid growth of next-generation sequencing (NGS) technology has led to a surge in the determination of whole genome sequences in plants. This has created a need for functional annotation of newly predicted gene sequences in the assembled genomes. To address this, “Hayai-Annotation Plants” was developed as a gene functional annotation tool for plant species. In this report, we compared Hayai-Annotation Plants with Blast2GO and TRAPID, focusing on the three primary gene-ontology (GO) domains: Biological Process (BP), Molecular Function (MF), and Cellular Component (CC). Using theArabidopsis thalianaGO annotation as a benchmark, we evaluated each tool using two approaches: the area under the precision-recall curve (AUC-PR) and the metrics used at the critical assessment of functional annotation (CAFA). In the latter case, a CAFA-evaluator, was used to determine the F-score, weighted F-score, and S-score for each domain. Hayai-Annotation Plants showed better performances in all three GO domains. Our results thus reaffirm the effectiveness of Hayai-Annotation Plants for functional gene annotation in plant species. In this era of extensive whole genome sequencing, Hayai-Annotation Plants will serve as a valuable tool that facilitates simplified and accurate gene function annotation for numerous users, thereby making a significant contribution to plant research.