bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhanced phenotypes for identifying opioid overdose in emergency department visit electronic health record data
Authors: Ward Ralph , Obeid Jihad S , Jennings Lindsey , Szwast Elizabeth , Hayes William Garrett , Pipaliya Royal , Bailey Cameron , Faul Skylar , Polyak Brianna , Baker George Hamilton , McCauley Jenna L , Lenert Leslie A 
Published: September 2023

Abstract

Background
Accurate identification of opioid overdose (OOD) cases in electronic healthcare record (EHR) data is an important element in surveillance, empirical research, and clinical intervention. We sought to improve existing OOD electronic phenotypes by incorporating new data types beyond diagnostic codes and by applying several statistical and machine learning methods.

Materials and Methods
We developed an EHR dataset of emergency department visits involving OOD cases or patients considered at risk for an OOD and ascertained true OOD status through manual chart reviews. We developed and validated prediction models using Random Forest, Extreme Gradient Boost, and Elastic Net models that incorporated 717 features involving primary and second diagnoses, chief complaints, medications prescribed, vital signs, laboratory results, and procedural codes. We also developed models limited to single data types.

Results
A total of 1718 records involving 1485 patients were manually reviewed; 541 (36.4%) patients had one or more OOD. Prediction performance was similar for all models; sensitivity varied from 94% to 97%; and area under the receiver operating characteristic curve (AUC) was 98% for all methods. The primary diagnosis and chief complaint were the most important contributors to AUC performance; primary diagnoses and medication class contributed most to sensitivity; chief complaint, primary diagnosis, and vital signs were most important for specificity. Models limited to decision support data types available in real time demonstrated robust prediction performance.

Conclusions
Substantial prediction performance improvements were demonstrated for identifying OODs in EHR data. Our e-phenotypes could be applied in surveillance, retrospective empirical applications, or clinical decision support systems.
Development of the Preschool Life Impact Burn Recovery Evaluation (PS-LIBRE1-5) Profile
Authors: Patel Khushbu F , Ni Pengsheng , Surette Kate E , Rencken Camerin A , Rodríguez-Mercedes Silvanys L , McGwin Madeleine B , Fabia Renata , Tully Carrie , Warner Petra , Romanowski Kathleen S , Palmieri Tina , Stoddard Frederick J , Schneider Jeffrey C , Kazis Lewis E , Ryan Colleen M 
Published: September 2023

Abstract
Physical, social, and psychological outcomes have been identified as relevant to the rehabilitation process of children with burn injuries. Existing legacy measures are limited in item content and only cover a few constructs. Condition-specific outcomes are highly relevant to gauge early growth and development. Computerized adaptive tests (CATs) leveraging advanced psychometric technologies minimize respondent burden. This project developed PS-LIBRE1–5 Profile CAT (Preschool Life Impact Burn Recovery Evaluation) to measure relevant postburn outcomes in children aged one to five. Responses to the field-tested PS-LIBRE1–5 Profile (188 items) were measured on a scale of frequency or ability. Scores were coded from 0 to 4 where higher scores reflected better functioning. Factor analysis identified the items retained in the final item bank of each scale. CAT simulations were conducted to estimate the mean score of each scale. The simulated CAT score and full item bank scores were compared based upon the score range, ceiling and floor effects, and marginal reliabilities. The child mean age was 3.0 ± 1.5 years (n = 500). Average burn size and time since burn injury were 4.2% TBSA and 1.1 years, respectively. Psychometric analysis resulted in eight scales: Physical, Communication and Language, Emotional Wellbeing, Mood, Anxiety, Peer Acceptance, Play, and Peer Relations. Ceiling effects were acceptable at &lt;13% for all scales. Marginal reliabilities of the CATs were credible. The PS-LIBRE1–5 Profile CAT contains 111 items, and is a comprehensive measure that captures physical, communication and language, psychological, and social functioning of preschool burn survivors.
CJEU grapples with the intertwined nature of private copies and retransmission of online television broadcasts
Authors: Priora Giulia , Costa Novaes Amanda 
Published: September 2023

Abstract
In Ocilion, the Court of Justice of the European Union ruled on two intricated aspects of the relationship between copyright law and Internet TV services, clarifying that de-duplication systems of copying of TV broadcasts do not fall within the scope of the private copying exception and that facilitating online retransmission does not amount to a communication to the public.
Semiparametric M-quantile regression with measurement error in spatial covariates: an application to housing price modelling
Authors: Borgoni Riccardo , Schirripa Spagnolo Francesco , Michelangeli Alessandra , Salvati Nicola , Carcagnì Antonella 
Published: September 2023

Abstract
Spatial data are becoming increasingly accessible to urban scientists, but these data are often prone to measurement error. Motivated by the analysis of the Milan (Italy) apartment market heterogeneity, we propose a semiparametric approach to adjust for the presence of measurement error in the covariates when estimating M-quantile regression. The M-quantile approach helps explain the heterogeneity across individual units, preserving robustness and efficiency in the estimates. The model’s parameters are estimated within a penalised likelihood framework and an analytical expression is proposed to estimate standard errors. Asymptotic properties of estimates are also provided.
Interplay between MYZUS PERSICAE-INDUCED LIPASE 1 and OPDA signaling in limiting green peach aphid infestation on Arabidopsis thaliana
Authors: Archer Lani , Mondal Hossain A , Behera Sumita , Twayana Moon , Patel Monika , Louis Joe , Nalam Vamsi J , Keereetaweep Jantana , Chowdhury Zulkarnain , Shah Jyoti 
Published: September 2023

Abstract
MYZUS PERSICAE-INDUCED LIPASE1 (MPL1) encodes a lipase in Arabidopsis thaliana that is required for limiting infestation by the green peach aphid (GPA; Myzus persicae), an important phloem sap-consuming insect pest. Previously, we demonstrated that MPL1 expression was up-regulated in response to GPA infestation, and GPA fecundity was higher on the mpl1 mutant, compared with the wild-type (WT), and lower on 35S:MPL1 plants that constitutively expressed MPL1 from the 35S promoter. Here, we show that the MPL1 promoter is active in the phloem and expression of the MPL1 coding sequence from the phloem-specific SUC2 promoter in mpl1 is sufficient to restore resistance to GPA. The GPA infestation-associated up-regulation of MPL1 requires CYCLOPHILIN 20-3 (CYP20-3), which encodes a 12-oxo-phytodienoic acid (OPDA)-binding protein that is involved in OPDA signaling, and is required for limiting GPA infestation. OPDA promotes MPL1 expression to limit GPA fecundity, a process that requires CYP20-3 function. These results along with our observation that constitutive expression of MPL1 from the 35S promoter restores resistance to GPA in the cyp20-3 mutant, and MPL1 acts in a feedback loop to limit OPDA levels in GPA-infested plants, suggest that an interplay between MPL1, OPDA, and CYP20-3 contributes to resistance to GPA.
Sixty years of conjecture over a urinary biomarker: a step closer to understanding the proposed link between anxiety and urinary pyrroles
Authors: Sherwin Angela , Shaw Ian C 
Published: September 2023

Abstract

Objective
For over 60 years there has been conjecture about the identity of an Ehrlich’s test positive pyrrole (Mauve Factor) reputed to be a biomarker for psychological disorders, including anxiety. We reviewed studies that attempt to identify Mauve Factor and subjected authentic standards of the 2 main candidates, kryptopyrrole and hydroxypyrrole, to the Ehrlich’s reaction.

Methods
Modified Ehrlich’s test for kryptopyrrole and hydroxypyrrole were applied to urine samples from 10 volunteers, anxious and nonanxious.

Results
Based on the mechanistic chemistry of Ehrlich’s reaction and reactions of the 2 compounds, Mauve Factor cannot be hydroxypyrrole. Analyses of urine samples from volunteers, identified by the Generalized Anxiety Disorder - 7 item scale (GAD-7 ≥10; n = 5) and control urine samples (GAD-7 &lt;10; n = 5) using a kryptopyrrole calibration graph, show that concentrations are similar in both groups.

Conclusion
Kryptopyrrole may be the elusive Mauve Factor. Its possible origin from stercobilin via gut microbiome–mediated metabolism, its link to gut-mediated neurological effects via γ-aminobutyric acid (GABA) receptors, and its predicted interaction with Zn2+ and consequent impact on zinc homeostasis are discussed. The GAD-7 scale does not differentiate between state and trait anxiety and as such, the minimal difference in pyrrole levels between volunteer groups requires further study.
The source of electrons at comet 67P
Authors: Stephenson P , Beth A , Deca J , Galand M , Goetz C , Henri P , Heritier K , Lewis Z , Moeslinger A , Nilsson H , Rubin M 
Published: September 2023

ABSTRACT
We examine the origin of electrons in a weakly outgassing comet, using Rosetta mission data and a 3D collisional model of electrons at a comet. We have calculated a new data set of electron-impact ionization (EII) frequency throughout the Rosetta escort phase, with measurements of the Rosetta Plasma Consortium’s Ion and Electron Sensor (RPC/IES). The EII frequency is evaluated in 15-min intervals and compared to other Rosetta data sets. EII is the dominant source of electrons at 67P away from perihelion and is highly variable (by up to three orders of magnitude). Around perihelion, EII is much less variable and less efficient than photoionization at Rosetta. Several drivers of the EII frequency are identified, including magnetic field strength and the outgassing rate. Energetic electrons are correlated to the Rosetta-upstream solar wind potential difference, confirming that the ionizing electrons are solar wind electrons accelerated by an ambipolar field. The collisional test particle model incorporates a spherically symmetric, pure water coma and all the relevant electron-neutral collision processes. Electric and magnetic fields are stationary model inputs, and are computed using a fully kinetic, collision-less Particle-in-Cell simulation. Collisional electrons are modelled at outgassing rates of Q = 1026 s−1 and Q = 1.5 × 1027 s−1. Secondary electrons are the dominant population within a weakly outgassing comet. These are produced by collisions of solar wind electrons with the neutral coma. The implications of large ion flow speed estimates at Rosetta, away from perihelion, are discussed in relation to multi-instrument studies and the new results of the EII frequency obtained in this study.
The spectra of IceCube Neutrino (SIN) candidate sources – IV. Spectral energy distributions and multiwavelength variability
Authors: Karl Martina , Padovani Paolo , Giommi Paolo 
Published: September 2023

ABSTRACT
We present hybrid spectral energy distributions, combining photon, and neutrino fluxes, for a sample of blazars, which are candidate IceCube neutrino sources. We furthermore check for differences in our sources’ variability in the near-infrared, optical, X-ray, and γ-ray bands compared to a sample of non-neutrino source candidate blazars, and investigate the state of each blazar at the arrival time of high-energy neutrinos. We find no significant differences when comparing our sample with control sources, also in terms of their spectral energy distributions, and no correlation between flaring states and neutrino arrival times. Looking for signatures of hadronic production, we check for similar strengths of the γ-ray and neutrino fluxes and find a $2.2\, \sigma$ signal for our source candidates. The hybrid spectral energy distributions assembled here will form the basis of the next step of our project, namely lepto-hadronic modelling of these blazars to assess the physical likelihood of a neutrino connection.
Unraveling the role of ZNF506 as a human PBS-pro-targeting protein for ERVP repression
Authors: Wu Qian , Fang Lu , Wang Yixuan , Yang Peng 
Published: September 2023

Abstract
Krüppel-associated box zinc finger proteins (KZFPs) function as a defense mechanism to maintain the genome stability of higher vertebrates by regulating the transcriptional activities of transposable elements (TEs). While previous studies have characterized ZFP809 as responsible for binding and repressing ERVs containing a proline tRNA primer-binding site (PBS-Pro) in mice, comparable KZFPs have not been identified in humans yet. Here, we identified ZNF506 as a PBS-Pro-binding protein in humans, which functions as a transcriptional repressor of PBS-Pro-utilizing retroviruses by recruiting heterochromatic modifications. Although they have similar functions, the low protein similarities between ZNF506, ZFP809 and KZFPs of other species suggest their independent evolution against the invasion of PBS-Pro-utilizing retroviruses into their respective ancestor genomes after species divergence. We also explored the link between ZNF506 and leukemia. Our findings suggest that ZNF506 is a unique human KZFP that can bind to PBS-Pro, highlighting the diverse evolution of KZFPs in defending against retroviral invasions. Additionally, our study provides insights into the potential role of ZNF506 in leukemia, contributing to the expanding knowledge of KZFPs' crucial function in disease and genome stability.
Large-scale phenogenomic analysis of human cancers uncovers frequent alterations affecting SMC5/6 complex components in breast cancer
Authors: Roy Shamayita , Zaker Arvin , Mer Arvind , D’Amours Damien 
Published: September 2023

Abstract
Cancer cells often experience large-scale alterations in genome architecture because of DNA damage and replication stress. Whether mutations in core regulators of chromosome structure can also lead to cancer-promoting loss in genome stability is not fully understood. To address this question, we conducted a systematic analysis of mutations affecting a global regulator of chromosome biology –the SMC5/6 complex– in cancer genomics cohorts. Analysis of 64 959 cancer samples spanning 144 tissue types and 199 different cancer genome studies revealed that the SMC5/6 complex is frequently altered in breast cancer patients. Patient-derived mutations targeting this complex associate with strong phenotypic outcomes such as loss of ploidy control and reduced overall survival. Remarkably, the phenotypic impact of several patient mutations can be observed in a heterozygous context, hence providing an explanation for a prominent role of SMC5/6 mutations in breast cancer pathogenesis. Overall, our findings suggest that genes encoding global effectors of chromosome architecture can act as key contributors to cancer development in humans.
Identification of experimentally-supported poly(A) sites in single-cell RNA-seq data with SCINPAS
Authors: Moon Youngbin , Burri Dominik , Zavolan Mihaela 
Published: September 2023

Abstract
Alternative polyadenylation is a main driver of transcriptome diversity in mammals, generating transcript isoforms with different 3’ ends via cleavage and polyadenylation at distinct polyadenylation (poly(A)) sites. The regulation of cell type-specific poly(A) site choice is not completely resolved, and requires quantitative poly(A) site usage data across cell types. 3’ end-based single-cell RNA-seq can now be broadly used to obtain such data, enabling the identification and quantification of poly(A) sites with direct experimental support. We propose SCINPAS, a computational method to identify poly(A) sites from scRNA-seq datasets. SCINPAS modifies the read deduplication step to favor the selection of distal reads and extract those with non-templated poly(A) tails. This approach improves the resolution of poly(A) site recovery relative to standard software. SCINPAS identifies poly(A) sites in genic and non-genic regions, providing complementary information relative to other tools. The workflow is modular, and the key read deduplication step is general, enabling the use of SCINPAS in other typical analyses of single cell gene expression. Taken together, we show that SCINPAS is able to identify experimentally-supported, known and novel poly(A) sites from 3’ end-based single-cell RNA sequencing data.
Urinary peptidomic liquid biopsy for non-invasive differential diagnosis of chronic kidney disease
Authors: Mavrogeorgis Emmanouil , He Tianlin , Mischak Harald , Latosinska Agnieszka , Vlahou Antonia , Schanstra Joost P , Catanese Lorenzo , Amann Kerstin , Huber Tobias B , Beige Joachim , Rupprecht Harald D , Siwy Justyna 
Published: September 2023

ABSTRACT

Background and hypothesis
Specific urinary peptides hold information on disease pathophysiology, which, in combination with artificial intelligence, could enable non-invasive assessment of chronic kidney disease (CKD) aetiology. Existing approaches are generally specific for the diagnosis of single aetiologies. We present the development of models able to simultaneously distinguish and spatially visualize multiple CKD aetiologies.

Methods
The urinary peptide data of 1850 healthy control (HC) and CKD [diabetic kidney disease (DKD), immunoglobulin A nephropathy (IgAN) and vasculitis] participants were extracted from the Human Urinary Proteome Database. Uniform manifold approximation and projection (UMAP) coupled to a support vector machine algorithm was used to generate multi-peptide models to perform binary (DKD, HC) and multiclass (DKD, HC, IgAN, vasculitis) classifications. This pipeline was compared with the current state-of-the-art single-aetiology CKD urinary peptide models.

Results
In an independent test set, the developed models achieved 90.35% and 70.13% overall predictive accuracies, respectively, for the binary and the multiclass classifications. Omitting the UMAP step led to improved predictive accuracies (96.14% and 85.06%, respectively). As expected, the HC class was distinguished with the highest accuracy. The different classes displayed a tendency to form distinct clusters in the 3D space based on their disease state.

Conclusion
Urinary peptide data present an effective basis for CKD aetiology differentiation using machine learning models. Although adding the UMAP step to the models did not improve prediction accuracy, it may provide a unique visualization advantage. Additional studies are warranted to further validate the pipeline's clinical potential as well as to expand it to other CKD aetiologies and also other diseases.
Antifungal Therapeutic Drug Monitoring Practices: Results of an Emerging Infections Network Survey
Authors: Benedict Kaitlin , Gold Jeremy A W , Beekmann Susan E , Polgreen Philip M , Toda Mitsuru , Smith Dallas J 
Published: September 2023

Abstract
In a survey of 523 infectious disease specialists, a moderate to high percentage reported using any antifungal therapeutic drug monitoring (TDM) during itraconazole (72%), posaconazole (72%), and voriconazole (90%) treatment, and a low to moderate percentage reported using any antifungal TDM during prophylaxis (32%, 55%, and 65%, respectively). Long turnaround times for send-out TDM testing and logistical difficulties were frequent barriers.
Inductive sensing of magnetic microrobots under actuation by rotating magnetic fields
Authors: Christiansen Michael G , Stöcklin Lucien R , Forbrigger Cameron , Venkatesh Shashaank Abhinav , Schuerle Simone 
Published: September 2023

Abstract
The engineering space for magnetically manipulated biomedical microrobots is rapidly expanding. This includes synthetic, bioinspired, and biohybrid designs, some of which may eventually assume clinical roles aiding drug delivery or performing other therapeutic functions. Actuating these microrobots with rotating magnetic fields (RMFs) and the magnetic torques they exert offers the advantages of efficient mechanical energy transfer and scalable instrumentation. Nevertheless, closed-loop control still requires a complementary noninvasive imaging modality to reveal position and trajectory, such as ultrasound or X-rays, increasing complexity and posing a barrier to use. Here, we investigate the possibility of combining actuation and sensing via inductive detection of model microrobots under field magnitudes ranging from 100 s of microtesla to 10 s of millitesla rotating at 1 to 100 Hz. A prototype apparatus accomplishes this using adjustment mechanisms for both phase and amplitude to finely balance sense and compensation coils, suppressing the background signal of the driving RMF by 90 dB. Rather than relying on frequency decomposition to analyze signals, we show that, for rotational actuation, phase decomposition is more appropriate. We demonstrate inductive detection of a micromagnet placed in two distinct viscous environments using RMFs with fixed and time-varying frequencies. Finally, we show how magnetostatic selection fields can spatially isolate inductive signals from a micromagnet actuated by an RMF, with the resolution set by the relative magnitude of the selection field and the RMF. The concepts developed here lay a foundation for future closed-loop control schemes for magnetic microrobots based on simultaneous inductive sensing and actuation.
The frontline of alternatives to animal testing: novel in vitro skin model application in drug development and evaluation
Authors: Zhao He , Chen Zhaozeng , Kang Xingchen , Yang Bo , Luo Peihua , Li Hui , He Qiaojun 
Published: September 2023

Abstract
The FDA Modernization Act 2.0 has brought nonclinical drug evaluation into a new era. In vitro models are widely used and play an important role in modern drug development and evaluation, including early candidate drug screening and preclinical drug efficacy and toxicity assessment. Driven by regulatory steering and facilitated by well-defined physiology, novel in vitro skin models are emerging rapidly, becoming the most advanced area in alternative testing research. The revolutionary technologies bring us many in vitro skin models, either laboratory-developed or commercially available, which were all built to emulate the structure of the natural skin to recapitulate the skin’s physiological function and particular skin pathology. During the model development, how to achieve balance among complexity, accessibility, capability, and cost-effectiveness remains the core challenge for researchers. This review attempts to introduce the existing in vitro skin models, align them on different dimensions, such as structural complexity, functional maturity, and screening throughput, and provide an update on their current application in various scenarios within the scope of chemical testing and drug development, including testing in genotoxicity, phototoxicity, skin sensitization, corrosion/irritation. Overall, the review will summarize a general strategy for in vitro skin model to enhance future model invention, application, and translation in drug development and evaluation.