bluuebunny/crossref_metadata_2025_split huggingface dataset:
Statistical Analysis of Radioactivity: Lamprecht Uranium Mine in Texas
Authors: Harvey Mark C. , Glenn Griesinger Nancy L. 
Published: December 2023

Abstract
The former Lamprecht uranium mine facility in Texas ceased operations well before the new millennium. However, decommissioning activities were never completed by the licensee. Consequently, a legal proceeding was authorized between state and licensee representatives. Meanwhile, state funds were used to hire an independent contractor to perform radiological surveys and assess the magnitude of residual radioactivity across the terrain at the site. The purpose of this study was to apply advanced spatial statistical methods to the survey data measured by contractors at the Lamprecht site to precisely predict remaining radioactive hotspot locations post soil remediation activities. To accomplish this, descriptive statistics such as Google maps and boxplots along with inferential spatial statistical techniques, e.g., kriging and semivariograms, were employed. R coding was also used throughout. Specifically, the descriptive statistical methods included geographical mapping of targeted areas at the site coupled with summary statistics. Inferentially, spatial analytical techniques were employed to pinpoint the locations of elevated radiation levels above regulatory limits. Our results suggest that fewer hotspots were identified after remediation activities were completed at the site. This study provides an additional analytical resource for the State of Texas regarding the release of this former in situ leach uranium mine site to landowners for unrestricted use.
Exam Review Versus Categorical Feedback: Which Improves Scores by Doctor of Physical Therapy Students?
Authors: Huebner Bethany , Jackson Barbara , Danzl Megan , Pitt Jason 
Published: December 2023

Introduction.
Feedback after computer-based assessments is essential to the learning process. Options include knowledge of results (KR), knowledge of correct results (KCR), and elaborated feedback (EF). This study aimed to identify whether specific or broader forms of postassessment feedback optimize physical therapist students' computer-based assessment scores.

Review of Literature.
Health care educators have various types of feedback they can provide to students. Educators may consider the need for exam integrity and increasing student engagement when determining what type of feedback to deliver. Elaborated feedback seems to be most effective in higher-order learning objectives than KCR or KR to improve learning outcomes and can be delivered in clear and engaging ways for students while maintaining exam integrity.

Subjects.
Forty-nine first-year Doctor of Physical Therapy students.

Methods.
This study was a quasi-experimental design. Students were given a feedback form postassessment: secure exam review with note sheet (KCR) or Strengths and Opportunities Report (EF). Students repeated assessments on the same content (mix of repeat and related items). Exam scores and question performance were analyzed with linear and logistic regression. Students were surveyed about feedback preferences.

Results.
After adjusting for differences in the initial exam scores and graduate Grade Point Average, KCR improved retake exam scores (confidence interval [CI95] = 0.07–1.82 percentage points). Knowledge of correct results was more effective than EF for repeated questions (RR = 1.53, CI95 = 1.12–2.09, P = .0031). Knowledge of correct results and EF were similarly effective for related questions (RR = 1.01, CI95 = 0.76–1.33, P = .9997). Most students (89.75%) preferred KCR.

Discussion and Conclusion.
Compared with EF, KCR provided modest improvements on follow-up exams, specifically on repeated questions. Because students are unlikely to encounter repeated questions on licensure exams, EF may be an excellent choice to balance exam integrity and feedback quality.
Evaluation of the Performance of a Card Game to Introduce Students to Interprofessional Collaboration
Authors: Joseph Antony R. , Wright Valerie M. , Watkins Susan M. , Goddard Stacy E. , Mast Daniel D. 
Published: December 2023

Background:
Gamification is an approach that can be used to introduce interprofessional collaboration in nursing and health science. Card games are an effective and convenient way to educate students about clinical professions.

Purpose:
We compared the perception of an experimental group of students who played an educational card game to a control group that played an uninstructive card game.

Methods:
College students (n = 148) from nursing and health science majors consented to play a 30-minute card game and complete a 13-item survey.

Results:
Perceptions of the card game were significantly better for students in the experimental group who played the interprofessional collaboration game than for those in the control group (t = 10.33, P < .001). Survey subscales were rated significantly higher for respondents who played the interprofessional card game.

Conclusions:
The use of an innovative card game teaching strategy significantly increased the perception of interprofessional collaboration among college students.
Biparametric Quantitative MRI for Prostate Cancer Detection
Authors: Uyanik Meltem , Vigneswaran Hari T. , Hale Graham R. , Gann Peter , Magin Richard , Abern Michael R. 
Published: December 2023

Abstract:

Objectives:
This study sought to prospectively investigate a novel quantitative biparametric prostate magnetic resonance imaging (MRI) protocol to detect prostate cancer (PCa) in biopsy-naïve men. Secondarily, this study reports the accuracy of fractional order calculus (FROC) diffusion and quantitative T2 compared with the Prostate Imaging Reporting & Data System (PI-RADS).

Methods:
This prospective pilot study (NCT04175730) enrolled 50 prostate biopsy-naïve men who met eligibility criteria. All men received 3T MRI with T2 and diffusion-weighted imaging (DWI) (b-values: 50–4,000 s/mm2). Men with PI-RADS lesions ≥3 underwent targeted and systematic prostate biopsy, omitting systematic biopsy cores in peripheral zone lesions. DWI series images were fit to signal decay to calculate ADC (mm2/s) and the FROC model for coefficient DF (mm2/s). The primary end point was detection of Gleason grade group ≥2 (GG≥2) PCa. Receiver operating characteristic regression and area under the curve (AUC) were reported.

Results:
Forty-eight men underwent MRI and biopsy. Mean age was 61.5 years (56–68), 29% were White, 52% were African American, mean PSA was 6.0 ng/mL (4.9–8.0), and mean PSA density was 0.14 ng/mL2. In total, 61 PI-RADS ≥3 lesions were targeted for biopsy. GG≥2 PC was found in 7% (1/14) of PI-RADS 3 lesions, 28% (10/36) of PI-RADS 4 lesions, and 36% (4/11) of PI-RADS 5 lesions. The AUC for detection of GG≥2 PC was 0.63 (0.5–0.76) for PI-RADS, 0.82 (0.68–0.96) for ADC, and 0.87 (0.77–0.97) for the FROC model.

Conclusion:
This small prospective pilot study demonstrates the feasibility of a novel quantitative biparametic MRI protocol to detect prostate cancer in biopsy-naïve men.
LIRAGLUTIDE ALLEVIATES ACUTE LUNG INJURY AND MORTALITY IN PNEUMONIA-INDUCED SEPSIS THROUGH REGULATING SURFACTANT PROTEIN EXPRESSION AND SECRETION
Authors: Guo Junping , Chen Xinghua , Wang Cole , Ruan Feng , Xiong Yunhe , Wang Lijun , Abdel-Razek Osama , Meng Qinghe , Shahbazov Rauf , Cooney Robert N. , Wang Guirong 
Published: December 2023

ABSTRACT
Glucagon-like peptide 1 (GLP-1) analogs are used to treat type 2 diabetes, and they can regulate insulin secretion, energy homeostasis, inflammation, and immune cell function. This study sought to determine whether the GLP-1 analog liraglutide exerts a beneficial action in an acute lung injury model of pneumonia-induced sepsis. Methods: Wild-type FVB/NJ mice (n = 114) were infected by intratracheal injection with Pseudomonas aeruginosa Xen5 (4 × 104 CFU/mouse) or an equal volume (50 μL) of saline (control) with or without a subcutaneous injection of liraglutide (2 mg/kg, 30 min after infection). Mice were killed 24 h after infection. Lung tissues and BALF were analyzed. In separate experiments, the dynamic growth of bacteria and animal mortality was monitored using in vivo imaging system within 48 h after infection. In addition, primary lung alveolar type II cells isolated from mice were used to study the mechanism of liraglutide action. Result: Liraglutide improved survival (P < 0.05), decreased bacterial loads in vivo, and reduced lung injury scores (P < 0.01) in septic mice. Liraglutide-treated mice showed decreased levels of inflammatory cells (P < 0.01) and proinflammatory cytokines (TNF-α and IL-6) (P < 0.01) in the lung compared with septic controls. Liraglutide significantly increased pulmonary surfactant proteins (SP-A and SP-B) expression/secretion (P < 0.01) and phospholipid secretion (P < 0.01) in vivo. Primary alveolar type II cells pretreated with liraglutide improved SP-A and SP-B expression after LPS exposure (P < 0.01). Conclusion: Liraglutide attenuates mortality and lung inflammation/injury in pneumonia-induced sepsis. The increased surfactant expression/secretion and anti-inflammatory effects of liraglutide represent potential mechanisms by GLP-1 agonists potentiate host defense and maintain alveolar respiratory function in acute lung injury.
Correlations betweenper capitagreen tea consumption and COVID-19 morbidity/mortality: comparing the strength before and after Omicron emergence
Authors: Storozhuk Maksim 
Published: December 2023

AbstractPurposeThere is rapidly growingin vitropharmacological evidence suggesting preventive/therapeutic potential of green tea and its constituent EGCG in battle with COVID-19. The aim of this study was to analyze time course of previously reported correlations betweenper capitagreen tea consumption and COVID-19 morbidity/mortality with a focus on comparing periods of time before (year 2021) and after (years 2022-2024) emergence of Omicron variant.MethodsCorrelations betweenper capitagreen tea consumption and COVID-19 morbidity/mortality were calculated using multiple regression models in a subset (n=84) of countries/territories worldwide with HDI above 0.55. Strength of the correlations for several dates in 2021 - 2024 was compared.ResultsHigherper capitagreen tea consumption was associated with lower COVID-19 morbidity and mortality. Statistically significant correlations were observed in 2021, 2022, 2023 and 2024. As compared to 2021, the strength of both correlations was decreased during 2022-2024 period. On average normalized to 2021 strength of correlation betweenper capitagreen tea consumption and COVID-19 morbidity decreased to 0.60, while normalized strength of correlation betweenper capitagreen tea consumption and COVID-19 mortality decreased to 0.83.ConclusionOverall, the results of this study are in line within vitropharmacological evidence. Though indirectly, these results at epidemiological level support the idea that green tea consumption may have not only preventive, but also therapeutic value in relation to COVID-19. Nevertheless, because of limitations of this study, this idea still should be considered as a hypothesis requiring further assessment.
The Applications of Laser Interstitial Thermal Therapy and Machine Learning in Neurosurgery: A Systematic Review
Authors: Bouras Andrew , Patel Dhruv , Chetla Nitin 
Published: December 2023

AbstractBackgroundThe incorporation of Machine Learning (ML) into Laser Interstitial Thermal Therapy (LITT) represents a significant advancement in minimally invasive neurosurgery, particularly for treating brain tumors, vascular malformations, and epileptogenic foci. This systematic review focuses on evaluating the integration and impact of ML in enhancing the efficacy, precision, and outcomes of LITT in neurosurgical procedures.MethodsAn exhaustive search was conducted in major scientific databases for studies from 2015 to 2023 that specifically focused on the application of ML in LITT. The review assessed the development and implementation of ML algorithms in surgical planning, outcome prediction, and postoperative evaluation in LITT. Rigorous inclusion criteria were applied to select studies, and a combination of meta-analysis and qualitative synthesis was used to analyze the data.ResultsThe review synthesizes findings from a range of studies, including retrospective analyses and initial clinical trials. It highlights the role of ML in enhancing the selection criteria for LITT, optimizing surgical approaches, and improving patient-specific outcome predictions. While LITT showed favorable results in treating non-resectable lesions, the integration of ML was found to potentially refine these outcomes further. However, challenges such as the need for larger sample sizes, standardization of ML algorithms, and validation of these methods in clinical settings were noted.ConclusionsThe integration of ML into LITT procedures marks a promising frontier in neurosurgery, offering potential improvements in surgical accuracy and patient outcomes. The evidence suggests a need for continued development and rigorous testing of ML applications in LITT. Future research should focus on the refinement and validation of ML algorithms for wider clinical adoption, ensuring that technological advancements align with patient safety and treatment efficacy.
A cell type-aware framework for nominating non-coding variants in Mendelian regulatory disorders
Authors: Lee Arthur S. , Ayers Lauren J. , Kosicki Michael , Chan Wai-Man , Fozo Lydia N. , Pratt Brandon M. , Collins Thomas E. , Zhao Boxun , Rose Matthew F. , Sanchis-Juan Alba , Fu Jack M. , Wong Isaac , Zhao Xuefang , Tenney Alan P. , Lee Cassia , Laricchia Kristen M. , Barry Brenda J. , Bradford Victoria R. , Lek Monkol , MacArthur Daniel G. , Lee Eunjung Alice , Talkowski Michael E. , Brand Harrison , Pennacchio Len A. , Engle Elizabeth C. 
Published: December 2023

ABSTRACTUnsolved Mendelian cases often lack obvious pathogenic coding variants, suggesting potential non-coding etiologies. Here, we present a single cell multi-omic framework integrating embryonic mouse chromatin accessibility, histone modification, and gene expression assays to discover cranial motor neuron (cMN)cis-regulatory elements and subsequently nominate candidate non-coding variants in the congenital cranial dysinnervation disorders (CCDDs), a set of Mendelian disorders altering cMN development. We generated single cell epigenomic profiles for ∼86,000 cMNs and related cell types, identifying ∼250,000 accessible regulatory elements with cognate gene predictions for ∼145,000 putative enhancers. Seventy-five percent of elements (44 of 59) validated in anin vivotransgenic reporter assay, demonstrating that single cell accessibility is a strong predictor of enhancer activity. Applying our cMN atlas to 899 whole genome sequences from 270 genetically unsolved CCDD pedigrees, we achieved significant reduction in our variant search space and nominated candidate variants predicted to regulate known CCDD disease genesMAFB, PHOX2A, CHN1,andEBF3– as well as new candidates in recurrently mutated enhancers through peak- and gene-centric allelic aggregation. This work provides novel non-coding variant discoveries of relevance to CCDDs and a generalizable framework for nominating non-coding variants of potentially high functional impact in other Mendelian disorders.
CitySEIRCast: An Agent-Based City Digital Twin for Pandemic Analysis and Simulation
Authors: Bilal Shakir , Zaatour Wajdi , Otano Yilian Alonso , Saha Arindam , Newcomb Kenneth , Soo Kim , Kim Jun , Ginjala Raveena , Groen Derek , Michael Edwin 
Published: December 2023

ABSTRACTThe COVID-19 pandemic has dramatically highlighted the importance of developing simulation systems for quickly characterizing and providing spatio-temporal forecasts of infection spread dynamics that take specific accounts of the population and spatial heterogeneities that govern pathogen transmission in real-world communities. Developing such computational systems must also overcome the cold-start problem related to the inevitable scarce early data and extant knowledge regarding a novel pathogen’s transmissibility and virulence, while addressing changing population behavior and policy options as a pandemic evolves. Here, we describe how we have coupled advances in the construction of digital or virtual models of real-world cities with an agile, modular, agent-based model of viral transmission and data from navigation and social media interactions, to overcome these challenges in order to provide a new simulation tool, CitySEIRCast, that can model viral spread at the sub-national level. Our data pipelines and workflows are designed purposefully to be flexible and scalable so that we can implement the system on hybrid cloud/cluster systems and be agile enough to address different population settings and indeed, diseases. Our simulation results demonstrate that CitySEIRCast can provide the timely high resolution spatio-temporal epidemic predictions required for supporting situational awareness of the state of a pandemic as well as for facilitating assessments of vulnerable sub-populations and locations and evaluations of the impacts of implemented interventions, inclusive of the effects of population behavioral response to fluctuations in case incidence. This work arose in response to requests from county agencies to support their work on COVID-19 monitoring, risk assessment, and planning, and using the described workflows, we were able to provide uninterrupted bi-weekly simulations to guide their efforts for over a year from late 2021 to 2023. We discuss future work that can significantly improve the scalability and real-time application of this digital city-based epidemic modelling system, such that validated predictions and forecasts of the paths that may followed by a contagion both over time and space can be used to anticipate the spread dynamics, risky groups and regions, and options for responding effectively to a complex epidemic.
Machine Learning Based Modelling of Human and Insect Olfaction Screens Millions of compounds to Identify Pleasant Smelling Insect Repellents
Authors: Kowalewski Joel , Boyle Sean M. , Arvidson Ryan , Ejercito Jadrian , Ray Anandasankar 
Published: December 2023

AbstractThe rational discovery of behaviorally active odorants is impeded by a lack of understanding on how the olfactory system generates percept or valence for a volatile chemical. In previous studies we showed that chemical informatics could be used to model prediction of ligands for a large repertoire of odorant receptors inDrosophila(Boyle et al., 2013). However, it remained difficult to predict behavioral valence of volatiles since the activities of a large ensembles of odor receptors encode odor information, and little is known of the complex information processing circuitry. This is a systems-level challenge well-suited for Machine-learning approaches which we have used to model olfaction in two organisms with completely unrelated olfactory receptor proteins: humans (∼400 GPCRs) and insects (∼100 ion-channels). We use chemical structure-based Machine Learning models for prediction of valence in insects and for 146 human odor characters. Using these predictive models, we evaluate a vast chemical space of >10 million compoundsin silico.Validations of human and insect behaviors yield very high success rates. The discovery of desirable fragrances for humans that are highly repulsive to insects offers a powerful integrated approach to discover new insect repellents.
The significance of social interactions in synchronized swarming flight in a termite
Authors: Mizumoto Nobuaki , Nozaki Tomonari 
Published: December 2023

AbstractIn social insect colonies, individuals of working caste coordinate their actions to manage various collective tasks. Such collective behaviors are observed not only in working castes but also in reproductives. During certain seasons, newly emerged winged reproductives (alates) fly from the nest to disperse and find mating partners in a synchronized manner. Although this “swarming” behavior is one of the collective behaviors that involve the greatest number of individuals in social insects, underlying social interactions remain unexplored. Here, we show that synchronized flight among colony members results from collective decision-making. Our simple simulation model suggests that social interactions in a large group of alates enable synchronized flight within a nest under fluctuating environmental conditions. This model is supported by empirical experiments using a termiteReticulitermes kanmonensis. Under the semi-field environment with fluctuating temperatures, alates within the same colony synchronized their dispersal flight under higher air temperatures, while dispersal flight was suppressed under lower temperatures. Furthermore, termites could synchronize their dispersal flights even under laboratory conditions with constant temperature, indicating that environmental cues are not always necessary for synchronization. In either case, higher synchronization happened with a larger number of alates. All these results demonstrate that both environmental and social factors interplay to enable the synchronized swarming flight of social insects.
Refinement of a technique for collecting and evaluating the osmolality of haemolymph fromDrosophilalarvae
Authors: Kurio Misato , Tsukasa Yuma , Uemura Tadashi , Usui Tadao 
Published: December 2023

ABSTRACTex vivophysiological experiments using small insect models such asDrosophilalarvae have become increasingly useful to address fundamental biological questions. To perform such experiments, various artificial saline solutions have been developed, but their osmolality varies significantly from one to the next. Such a variation of osmolality stems, in part, from the difficulty of determining the true value of haemolymph osmolality inDrosophilalarvae. Thus, there is a pressing need to refine protocols for collecting and measuring the osmolality of the larval haemolymph. Two major obstacles are thought to impede the accurate analysis of haemolymph collected from small insects: melanin formation and gut-derived contamination. Here, we greatly refined existing haemolymph collecting methods, evaluated the purity of the collected haemolymph under melanin-free conditions, and concluded that the true value of haemolymph osmolality is close to 306.0 mOsm kg−1inDrosophilalarvae.