bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Quality Initiative to Decrease Time Until Analgesic for Fracture-associated Pain in the Pediatric Emergency Department
Authors: Davis Justin , Kappler Kristin , Stoker Skye 
Published: September 2021

Introduction:
Long bone fractures are a common cause of pain in the pediatric emergency department (PED), and ensuring timely delivery of analgesic medications is essential for these children. We aimed to decrease the median time to the first dose of analgesic for long bone fracture–associated pain in our PED to 36 minutes or less by July 1, 2015.

Methods:
A series of 4 initiatives were implemented in successive “plan, do, study, act” rapid cycles. Initiatives consisted of educational interventions for staff regarding Emergency Severity Index procedures for triaging pain, transition to in-room triage, enhanced communication about quality goals using a “quality board,” and ongoing staff educational sessions on outlier cases as well as biases and barriers to quality.

Results:
We implemented the initiatives from April through July of 2015. The monthly median time to analgesic delivery for long bone fracture–associated pain in the PED decreased from 72 minutes in April to 33.5 minutes in July of 2015. For 12 months following the first intervention, the average monthly median time to the first analgesic dose was 48.5 versus 66.3 minutes for the prior 12 months.

Conclusions:
A series of 4 interventions led to a decrease in the median time to the first dose of analgesic for long bone fracture–associated pain in the PED.
Improving Physical Abuse Documentation and Photography through a Remote Peer Review Intervention
Authors: Moles Rebecca L. , Melville John , Martinez Kim , Palusci Vincent 
Published: September 2021

Introduction:
Child Abuse Pediatrics is a small and geographically dispersed specialty. This article reports on an intervention to improve written and photodocumentation quality and uniformity in suspected child physical abuse cases, using a remote, de-identified case review system.

Methods:
In each cycle, participants submitted de-identified medical reports and photographs for review by a child abuse pediatrics expert. Experts evaluated 3 cycles of 5 cases using a novel rubric and assigned quality interventions for the participants based on their scores.

Results:
15 of 16 participants improved scores between cycles 1 and 3 (78% versus 89%, P < 0.001). All participants rated the program as helpful and would recommend it to a colleague.

Conclusion:
A quality improvement project administered via the internet improves the quality and uniformity of written and photographic documentation in child physical abuse evaluations.
Demographic changes in pelvic fracture patterns at a Swiss academic trauma center from 2007 to 2017
Authors: Villiger Karin , Meier Malin Kristin , Hasler Rebecca Maria , Bastian Johannes Dominik , Tannast Moritz , Exadaktylos Aristomenis Konstantinos , Steppacher Simon Damian 
Published: September 2021

BACKGROUND
Increasing life expectancy has led to higher incidence of fragility fractures of the pelvis. These demographic changes may have a direct impact on fracture patterns. The goal of this study was (1) to evaluate demographical trends in patients with pelvic ring injuries at a tertiary Swiss trauma center and (2) to analyze the influence on fracture patterns.

METHODS
We performed a retrospective cross-sectional study including 958 patients (mean ± SD age, 57 ± 21 years; 48% women) with a pelvic ring injury between 2007 and 2017. Fractures were classified according to Tile, Young and Burgess or Rommens and Hofmann (fragility fractures) using conventional and computer tomography imaging. Low-energy fractures were defined as fractures resulting from fall from standing height or less. Fracture classifications, age, sex, Injury Severity Score, and trauma mechanism were compared using analysis of variance or χ2 test. Cluster analysis was performed to identify groups with similarities in fracture patterns and demographic parameters.

RESULTS
From 2007 to 2017, the frequency of pelvic ring injuries increased by 115% (increase per decade), and mean age increased by 15% (p = 0.031). A trimodal age distribution was found; highest increase for fractures occurred in the older (265%) patient group. Low-energy fracture was the most common trauma mechanism (43% of all fractures, an increase of 249%). Changes in fracture pattern showed a disproportioned increase of lateral compression (LC) fractures (LC type 1 in 64%) or partially stable fracture (B2, with 39%). In patient older than 65 years, the strongest increase was found for nondisplaced posterior fractures with an overall prevalence of 62%. Five clusters were found with the most frequent cluster representing older female patients with low-energy fracture (LC, Tile type B) in 30%.

CONCLUSION
The current results corroborate the trend of increasing frequency of fragility fractures in an aging society. The demographic shift has a direct impact on fracture pattern with a disproportionate increase in partially stable compression fracture of the pelvis.

LEVEL OF EVIDENCE
Prognostic/Epidemiologic, Level III.
Effects of iloperidone on hERG 1A/3.1 heterotetrameric channels
Authors: Lee Hong Joon , Choi Bok Hee , Choi Jin-Sung , Hahn Sang June 
Published: September 2021

Objectives
Iloperidone is an atypical antipsychotic drug that is widely used for the treatment of schizophrenia. hERG 3.1, alternatively spliced form of hERG 1A, is considered a potential target for an antipsychotic drug. The present study was designed to study the effects of iloperidone on hERG 1A/3.1 heterotetrameric channels.

Methods
The interactions of iloperidone with hERG 1A/3.1 heterotetrameric channels stably expressed in HEK cells were investigated using the whole-cell patch-clamp technique and western blot analysis.

Results
Iloperidone inhibited the hERG 1A/3.1 tail currents at −50 mV in a concentration-dependent manner with an IC50 value of 0.44 μM. The block of hERG 1A/3.1 currents by iloperidone was voltage-dependent and increased over a range of voltage for channel activation. However, the block by iloperidone was voltage-independent at more depolarized potentials where the channels were fully activated. A fast application of iloperidone inhibited the hERG 1A/3.1 current elicited by a 5-s depolarizing pulse to +60 mV to fully inactivate the hERG 1A/3.1 currents. Iloperidone also induced a rapid and reversible inhibition of hERG 1A/3.1 tail currents during repolarization. However, iloperidone had no effect on either hERG 1A or hERG 1A/3.1 channel trafficking to the cell membrane.

Conclusions
Our results indicated that iloperidone concentration-dependently inhibited hERG 1A/3.1 currents by preferentially interacting with the open states of channels, but not by the disruption of membrane trafficking or surface membrane expression of hERG 1A and hERG 1A/3.1 channel proteins.
SARS-CoV-2 evolved during advanced HIV disease immunosuppression has Beta-like escape of vaccine and Delta infection elicited immunity
Authors: Cele Sandile , Karim Farina , Lustig Gila , San James Emmanuel , Hermanus Tandile , Tegally Houriiyah , Snyman Jumari , Moyo-Gwete Thandeka , Wilkinson Eduan , Bernstein Mallory , Khan Khadija , Hwa Shi-Hsia , Tilles Sasha W. , Singh Lavanya , Giandhari Jennifer , Mthabela Ntombifuthi , Mazibuko Matilda , Ganga Yashica , Gosnell Bernadett I. , Karim Salim Abdool , Hanekom Willem , Van Voorhis Wesley C. , Ndung’u Thumbi ,   COMMIT-KZN Team, Lessells Richard J. , Moore Penny L. , Moosa Mahomed-Yunus S. , de Oliveira Tulio , Sigal Alex 
Published: September 2021

SummaryCharacterizing SARS-CoV-2 evolution in specific geographies may help predict the properties of variants coming from these regions. We mapped neutralization of a SARS-CoV-2 strain that evolved over 6 months from the ancestral virus in a person with advanced HIV disease. Infection was before the emergence of the Beta variant first identified in South Africa, and the Delta variant. We compared early and late evolved virus to the ancestral, Beta, Alpha, and Delta viruses and tested against convalescent plasma from ancestral, Beta, and Delta infections. Early virus was similar to ancestral, whereas late virus was similar to Beta, exhibiting vaccine escape and, despite pre-dating Delta, strong escape of Delta-elicited neutralization. This example is consistent with the notion that variants arising in immune-compromised hosts, including those with advanced HIV disease, may evolve immune escape of vaccines and enhanced escape of Delta immunity, with implications for vaccine breakthrough and reinfections.HighlightsA prolonged ancestral SARS-CoV-2 infection pre-dating the emergence of Beta and Delta resulted in evolution of a Beta-like serological phenotypeSerological phenotype includes strong escape from Delta infection elicited immunity, intermediate escape from ancestral virus immunity, and weak escape from Beta immunityEvolved virus showed substantial but incomplete escape from antibodies elicited by BNT162b2 vaccinationGraphical abstract
Machine learning-supported interpretation of kidney graft elementary lesions in combination with clinical data
Authors: Labriffe Marc , Woillard Jean-Baptiste , Gwinner Wilfried , Braesen Jan-Hinrich , Anglicheau Dany , Rabant Marion , Koshy Priyanka , Naesens Maarten , Marquet Pierre 
Published: September 2021

AbstractBackgroundThe Banff classification standardizes the diagnoses of kidney transplant rejection based on histological criteria. Clinical decisions are generally made after integration of the Banff diagnoses in the clinical context. However, interpretation of the biopsy cases is still heterogeneous among pathologists or clinicians. Machine Learning (ML) algorithms may be trained from expertly assessed cases to provide clinical decision support.MethodsThe ML technique of Extreme Gradient Boosting learned from two large training datasets from the European programs BIOMARGIN and ROCKET (n= 631 and 304), in which biopsies were read centrally and consensually interpreted by a group of experts and used as a reference for untargeted biomarker screenings. The model was then externally validated in three independent datasets (n= 3744, 589 and 360).ResultsIn the three validation datasets, the algorithm yielded a ROC curve AUC of mean (95% CI) 0.97 (0.92-1.00), 0.97 (0.96-0.97) and 0.95 (0.93-0.97) for antibody-mediated rejection (ABMR); 0.94 (0.91-0.96), 0.94 (0.92-0.95) and 0.91 (0.88-0.95) for T cell-mediated rejection; >0.96 (0.90-1.00) in all three for interstitial fibrosis - tubular atrophy (IFTA). Finally, using the largest validation cohort, we developed an additional algorithm to discriminate active and chronic active ABMR with an accuracy of 0.95.ConclusionWe built an Artificial Intelligence algorithm able to interpret histological lesions together with a few routine clinical data with very high sensitivity and specificity. This algorithm should be useful in routine or clinical trials to help pathologists and clinicians and increase biopsy interpretation homogeneity.
Multi-modal single-cell sequencing identifies cellular immunophenotypes associated with juvenile dermatomyositis disease activity
Authors: Neely Jessica , Hartoularos George , Bunis Daniel , Sun Yang , Lee David , Kim Susan , Ye Chun Jimmie , Sirota Marina 
Published: September 2021

ABSTRACTJuvenile dermatomyositis (JDM) is a rare autoimmune condition with insufficient biomarkers and treatments, in part, due to incomplete knowledge of the cell types mediating disease. We investigated immunophenotypes and cell-specific genes associated with disease activity using multiplexed RNA and protein single-cell sequencing applied to PBMCs from 4 treatment-naïve JDM (TN-JDM) subjects at baseline, 2, 4, and 6 months and 4 subjects with inactive disease. Analysis of 55,564 cells revealed separate clustering of TN-JDM cells within monocyte, NK, CD8+ effector T and naïve B populations. The proportion of CD16+ monocytes was reduced in TN-JDM, and naïve B cells were expanded. Cell-type differential gene expression analysis and hierarchical clustering identified a pan-cell-type IFN gene signature over-expressed in TN-JDM in all cell types and correlated with disease activity. TN-JDM monocytes displayed an inflammatory state: CD16+ monocytes expressed the highest IFN gene score and differential protein expression of adhesion molecules, CD49d and CD56, compared to CD14+ inflammatory monocytes. A transitional B cell population expressing higher CD24 and CD5 proteins and an IFN-hi naïve B population were associated with TN-JDM and exhibited less CD39, an immunoregulatory protein. This data provides new insights into JDM immune dysregulation at cellular resolution and novel resource for myositis investigators.
Spatial simulation of COVID-19 new cases development
Authors: Chen Isaac , Liu F. 
Published: September 2021

AbstractThe time dependent SIR model is extended to simulate infection across spatial boundaries. We used New Jersey data as an example to test the extended SIR model. Infection from neighboring counties are modelled by connectivity matrix where each pair of neighboring counties has an element in the connectivity matrix. The magnitude of this matrix element represents the degree to which the infected from one county can affect the susceptible in one of its neighboring counties. Simulated result from the extended spatial SIR model is compared with observed new COVID-19 cases measured in the 21 counties in New Jersey. The extended model has to solve 84 simulated functions simultaneously and the large number of parameters involved in the spatial SIR model are auto tuned using genetic algorithm.
Identifying functional genes and pathways towards a unifying model for atrial fibrillation
Authors: Wass Sojin Youn , Offerman Erik J. , Sun Han , Hsu Jeffrey , Rennison Julie H. , Cantlay Catherine C. , McHale Meghan L. , Gillinov A. Marc , Moravec Christine , Smith Jonathan D. , Van Wagoner David R. , Barnard John , Chung Mina K. 
Published: September 2021

ABSTRACTRationaleGenome wide association studies (GWAS) have associated >100 genetic loci with atrial fibrillation (AF), yet the biological pathways of AF remain elusive.ObjectiveTo determine candidate causal genes associated with AF risk loci and their coexpression partners, modules, biologic and mechanistic pathways.Methods and ResultsCis-expression quantitative trait loci (eQTLs) were identified for candidate genes near AF risk single nucleotide polymorphisms (SNPs) in human left atrial tissues. Genes were categorized into 3 sets according to likelihood of being a causative AF gene: 1) All Candidate Genes (with significant eQTLs or previously prioritized); 2) Any eQTL Genes (with ≥1 significant eQTL); and 3) Top GWAS SNP eQTL Genes (top SNP within the top 10 eQTL SNPs). Coexpression partners were identified for each candidate gene. Weighted gene coexpression network analysis (WGCNA) identified modules and modules with overrepresentation of candidate AF genes. Ingenuity Pathway Analysis (IPA) was applied to the coexpression partners of each candidate gene, and IPA and gene set enrichment analysis (GSEA) to each WGCNA module. 166 AF-risk SNPs were located in 135 distinct loci. The All Candidate Genes group contained 233, the Any eQTL Genes group 131 (83 novel), and the Top GWAS SNP eQTL Genes group 37 genes. IPA identified mitochondrial dysfunction, oxidative stress, epithelial adherens junction signaling, and sirtuin signaling as the most frequent pathways. WGCNA characterized 64 modules; candidate AF genes were overrepresented in 8. Modules were represented by cell injury, death, stress, developmental, metabolic/mitochondrial, transcription/translation, and immune activation/inflammation regulatory pathways.ConclusionsAF candidate gene coexpression analyses suggest significant roles for cellular stress and remodeling in AF. We propose a dual risk model for AF: Genetic susceptibility to AF may not manifest until later in life, when cellular stressors overwhelm adaptive responses. These analyses provide a resource for further functional studies on potential causal AF genes.
Real-time audio processing of real-life soundscapes for EEG analysis: ERPs based on natural sound onsets
Authors: Hölle Daniel , Blum Sarah , Kissner Sven , Debener Stefan , Bleichner Martin G. 
Published: September 2021

AbstractWith smartphone-based mobile electroencephalography (EEG), we can investigate sound perception beyond the lab. To understand sound perception in the real world, we need to relate naturally occurring sounds to EEG data. For this, EEG and audio information need to be synchronized precisely, only then it is possible to capture fast and transient evoked neural responses and relate them to individual sounds. We have developed Android applications (AFEx and Record-a) that allow for the concurrent acquisition of EEG data and audio features, i.e., sound onsets, average signal power (RMS) and power spectral density (PSD) on smartphone. In this paper, we evaluate these apps by computing event-related potentials (ERPs) evoked by everyday sounds. One participant listened to piano notes (played live by a pianist) and to a home-office soundscape. Timing tests showed that the temporal precision of the system is very good. We calculated ERPs to sound onsets and observed the typical P1-N1-P2 complex of auditory processing. Furthermore, we show how to relate information on loudness (RMS) and spectra (PSD) to brain activity. In future studies, we can use this system to study sound processing in everyday life.
ProteInfer: deep networks for protein functional inference
Authors: Sanderson Theo , Bileschi Maxwell L. , Belanger David , Colwell Lucy J. 
Published: September 2021

Predicting the function of a protein from its amino acid sequence is a long-standing challenge in bioinformatics. Traditional approaches use sequence alignment to compare a query sequence either to thousands of models of protein families or to large databases of individual protein sequences. Here we instead employ deep convolutional neural networks to directly predict a variety of protein functions – EC numbers and GO terms – directly from an unaligned amino acid sequence. This approach provides precise predictions which complement alignment-based methods, and the computational efficiency of a single neural network permits novel and lightweight software interfaces, which we demonstrate with an in-browser graphical interface for protein function prediction in which all computation is performed on the user’s personal computer with no data uploaded to remote servers. Moreover, these models place full-length amino acid sequences into a generalised functional space, facilitating downstream analysis and interpretation. To read the interactive version of this paper, please visit https://google-research.github.io/proteinfer/Abstract FigureQR code for the interactive version of this preprint at https://google-research.github.io/proteinfer/
Possible environmental and meteorological factors underlying scaly-breasted munia Lonchura punctulata (L.) mass mortality events in Southeast Asia’s urban and rural areas in September 2021
Authors: Wibowo Andri 
Published: September 2021

AbstractMass bird mortality is a rare event. This event could be happened and could be a combination of numerous factors. It could be something that’s still completely unknown to us. In September 2021 in SE Asia, there were 2 mass bird mortality events of Lonchura punctulata. The first event happens on 9 September in rural area at 08.00 AM and second happens on 14 September at 12.00 PM in urban area. The results show that precipitation combined with the wind gust might be correlated with mass mortality. The results showed precipitation factors have contributed 71.18% (R2 = 0.714, P = 0.008) to the mortality and followed by wind gust with 28.81% contribution (R2 = 0.41, P = 0.08). The meteorological parameter was not the only factors affecting the mortality events. The landscapes in urban and rural areas have experienced fragmentations. Urban areas have severe fragmentation of vegetation covers with remaining vegetation covers were only 17.4% and patch density indices of 0.29. In contrast rural areas still have higher vegetation cover remnants about 21.12% and patch density indices of 0.93. Then severe meteorological events combined with the fragmented habitats of L. punctulata may explain the mass mortality of this bird species.
Plant-host shift, spatial persistence, and the viability of an invasive insect population
Authors: Silva Isabelle Bueno , McGrane-Corrigan Blake , Mason Oliver , de Andrade Moral Rafael , Augusto Conde Godoy Wesley 
Published: September 2021

AbstractAssessing the effects of a plant-host shift is important for monitoring insect populations over long time periods and for interventions in a conservation or pest management framework. In a heterogeneous environment, individuals may disperse between sources and sinks in order to persist. Here we propose a single-species two-patch model that aims to capture the generational movement of an insect that exhibits density-dependent dispersal, to see how shifting between hosts could alter its viability and asymptotic dynamics. We then analyse the stability and persistence properties of the model and further validate it using parameter estimates derived from laboratory experiments. In order to evaluate the potential of this model, we applied it to Drosophila suzukii (Diptera: Drosophilidae), which has become a harmful pest in several countries around the world. Although many studies have investigated the preference and attractiveness of potential hosts on this invasive drosophilid, no studies thus far have investigated whether a shift of fruit host could affect such a species’ ecological viability or spatiotemporal persistence. The model results show that a shift in host choice can significantly affect the growth potential and fecundity of a species such as D. suzukii, which ultimately could aid such invasive populations in their ability to persist within a changing environment.
A Cellular Reference Resource for the Mouse Urinary Bladder
Authors: Baker Dylan , Al-Naggar Iman M. , Sivajothi Santhosh , Flynn William F. , Amiri Anahita , Luo Diane , Hardy Cara C. , Kuchel George A. , Smith Phillip P. , Robson Paul 
Published: September 2021

SUMMARYThe urinary bladder functions as a reservoir to store and extrude liquid bodily waste. Significant debate exists as to this tissue’s cellular composition and genes associated with their functions. We use a repertoire of cell profiling tools to comprehensively define and spatial resolve cell types. We characterize spatially validated, basal-to-luminal gene expression dynamics within the urothelium, the cellular source of most bladder cancers. We define three distinct populations of fibroblasts that spatially organize from the sub-urothelial layer through to the detrusor muscle, clarifying knowledge around these controversial interstitial cells, and associate increased fibroblasts with aging. We overcome challenges of profiling the detrusor muscle, absence from earlier single cell studies, to report on its transcriptome with many novel and neuronal-like features presumably associated with neuromuscular junctions. Our approach provides a blueprint for tissue atlas construction and the data provides the foundation for future studies of bladder function in health and disease.