bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparing the stress physiology of hard- and soft-released juvenile Atlantic Salmon after transportation for reintroduction
Authors: Roberts D. , Madliger C. L. , Mokdad A. I. , Pitcher T. E. 
Published: November 2024

Abstract

Objective
We examined whether an extended acclimatization period prior to release (soft release) can allow transported fish to recover from the physiological stress associated with transport compared with conventional release methods, which provide fish with no acclimatization period prior to release (hard release).

Methods
We monitored an Atlantic Salmon Salmo salar stocking team during a standard reintroduction operation and compared their conventional hard-release method (i.e., immediate release after transport with no acclimatization period) to a soft-release method (i.e., 2 and 4 days in-river acclimatization prior to release). Following a 2.5-h transport event, hard-release fish were immediately blood-sampled for their physiological stress response (cortisol, glucose, and lactate). Soft-release fish were blood-sampled for their physiological stress response following 2 or 4 days of in-river acclimatization.

Result
While hard- and soft-release fish demonstrated significantly higher cortisol, glucose, and lactate concentrations compared with control fish, cortisol concentrations remained elevated for both the hard- and soft-release groups. However, glucose and lactate concentrations were significantly lower in soft-release fish compared with hard-release fish.

Conclusion
Soft-release provides fish an extended acclimatization period that was found to impact transport-related physiological stress in fish. Our findings will inform management agencies and practitioners focused on improving the success of salmonid stocking and reintroduction programs.
Training of Nurse Interventionists to Optimize Intervention Fidelity in a Telehealth Pilot Study
Authors: Côté‐Arsenault Denise , Kobler Kathie , Denney‐Koelsch Erin M. , Hawsawi Samah , Schwob Melanie , Spence Kimberly 
Published: November 2024

ABSTRACTInterventionist training and on‐going guidance by the research team are essential in psychosocial interventional research to ensure fidelity. Consistency in delivering an intervention requires recruiting interventionists with well‐aligned clinical experience, developing a replicable training process, and reassessing ongoing intervention fidelity using an assessment tool of observable behaviors that are essential to the intervention. This paper describes one research team's experience of hiring and training nurse interventionists to deliver a theory‐based, telehealth psychosocial intervention for a single‐arm pilot study. The training methods used to foster the nurses' integration of theory into intervention delivery are discussed, along with approaches adopted to optimize and measure fidelity. The research team and interventionist trainees in this pilot study overcame learning challenges through establishing mutual trust and promoting effective communication throughout the training process. Fostering connections between cognitive and affective learning during the nurse interventionists' training was critical to establishing and maintaining intervention fidelity.
Mitapivat for Acquired Pyruvate Kinase Deficiency
Authors: Al‐Samkari Hanny 
Published: November 2024

ABSTRACTPyruvate kinase (PK) activation is emerging as a promising treatment modality for numerous congenital hemolytic anemias of diverse pathophysiology, and one agent, mitapivat, is already licensed to treat patients with congenital PK deficiency. However, PK deficiency may also be acquired in the setting of clonal myeloid disorders and other pathologies, where it may result in severe hemolytic anemia and remains without known therapies. This case report describes the novel application of mitapivat therapy in a patient with acquired PK deficiency causing red cell transfusion dependence, liberating the patient from transfusions and resulting in marked improvement in symptoms and quality of life.
Screening Inhibitors of α‐Amylase in PolygalaRadix Based on an Online Targeted Detection System and Molecular Docking
Authors: Su Zenghu , Xu Hongbo , Chen Shizhong , Li Shuming , Weng Jingyu , Yang Yuangui 
Published: November 2024

ABSTRACTIntroductionTargeted screening of inhibitors of key enzymes in the progression of diabetes from natural products is one of the effective methods for the treatment of diabetes. Polygala has been proved to reduce glucose levels; however, the bioactive compounds in Polygalae Radix (PR) that have anti‐diabetic properties are unknown.ObjectiveThe purpose of this study was to explore the material basis of the anti‐diabetic effect of PR by inhibiting α‐amylase through an online detection system and molecular docking.MethodsAn online analysis platform was established and optimized for the screening of potent enzyme inhibitors from complex mixtures based on ultra‐performance liquid chromatography‐photodiode array‐quadrupole‐time‐of‐flight‐mass spectrometry‐α‐amylase‐fluorescence detector (UHPLC‐PDA‐Q‐TOF‐MSn‐α‐amylase‐FLD) detection system and molecular docking, which could efficiently separate extracts, quickly detect α‐amylase inhibitors, and determine their structures. Molecular docking confirms the inhibition of these compounds. The molecular interaction between α‐amylase and the active compound was evaluated.ResultsAmong the 101 compounds identified, 28 compounds had a strong inhibitory effect on α‐amylase. Molecular docking screening confirmed the inhibition of these compounds and evaluated the molecular interactions between α‐amylase and 30 active compounds, which strongly supported the experimental results. Among the evaluated compounds, onjisaponin R (83) and polygalaxanthone III (11) have the strongest inhibitory activity to α‐amylase (the binding energies were −9.639 and −8.972 kcal/mol, respectively) and are potential lead compounds against diabetes.ConclusionThis study proved the feasibility of using the existing platform to screen the active ingredients in PR extract, and provided a practical method for the rapid screening of potential anti‐diabetic active ingredients in traditional Chinese medicine.
E‐Cigarette Addiction in Adolescents—How Do We Get Them to Stop?
Authors: Watt Elizabeth , Bush Andy , Gardner‐Medwin Janet , Langley Ross J. 
Published: November 2024

ABSTRACTBackgroundE‐cigarette use in adolescents is increasing and the addictive potential of these devices is well recognised. Most health authorities have no E‐cigarette cessation programmes. We reviewed randomised control trials evaluating prevention strategies for adolescent E‐cigarette use and identified any successful components.MethodsSearch terms were created in accordance with the main objective (vaping/E‐cigarette use prevention/cessation/adolescents). Search was conducted via Ovid MedLine for English‐language randomised control trials published from 2020 to 2023 containing keywords relating to adolescent E‐cigarette use. Seven U.S. studies were included in the review. We established common themes of qualitative outcomes and identification of successful components of prevention programmes.ResultsInterventions showed significant improvement in general knowledge and perceived risk of E‐cigarettes, and lower risk of using other tobacco products. Other consequences showed lower susceptibility to vaping uptake and higher abstinence rates although future studies are required to see if these were sustained long‐term.ConclusionFocus groups aid development of cessation and prevention campaigns. Messages should be digital and relatable. Messages should contain health “harm” warnings. Furthermore, support services should be well‐signposted for adolescents. Social media is a low‐cost and important tool to halt teenage E‐cigarette addiction.
Reactive Stroma and Acinar Morphology in Prostate Cancer: Implications for Progression and Prognostic Assessment
Authors: Júnior Eduardo P. , Gomes Egleidson F. do Amaral , de Lima Mário F. R. , Raimundo João V. S. , Marinho Matheus L. , Soares Yuri V. C. , Machado Alexei M. C. , Silva Gabriel H. C. , Longford Francis G. J. , Frey Jeremy G. , de Paula Ana M. , Mamede Marcelo 
Published: November 2024

ABSTRACTIntroductionProstate cancer (PC) remains a significant global health concern, with prognostic assessments largely reliant on the Gleason Classification System. While it has proven effective, subjectivity in interpretation persists, prompting the need for complementary approaches. Reactive stroma (RS) has emerged as a potential candidate for enhancing PC characterization, as it reflects intricate interactions among stromal, epithelial, and extracellular matrix components. To shed light on this, we conducted a comprehensive study.MethodsTwo expert pathologists independently analyzed consecutive prostate biopsies (n = 120 patients), categorized into four groups based on Gleason scores. Four acinar patterns were described, denoted as A, B, C, and D. Our study uncovered a noteworthy presence of RS, predominantly within poorly differentiated tumors. Stromogenic tumors, characterized by high RS content, were particularly associated with Gleason scores of 4 + 3 and ≥ 8. Intriguingly, acinar patterns, including the distinctive B and D patterns, exhibited strong correlations with stromogenic tumors. Incorporating quantitative imaging techniques (Second Harmonic Generation and Two‐Photon Excitation Fluorescence Microscopy), we examined collagen fiber density within the stroma.ResultsOur analysis revealed a direct relationship between RS intensity and collagen fiber counts, particularly prominent in patterns B and D. These findings suggest that the stromal reaction in PC is closely linked to acinar morphology and collagen deposition. Moreover, rudimentary microacini at the tumor periphery, associated with intense RS and patterns B and D, may signify an unfavorable prognosis.ConclusionOur study highlights the potential of RS as an additional prognostic factor in PC. It underscores the intricate interplay between acinar patterns, RS intensity, and collagen fiber density, providing valuable insights for future prognostic assessments and therapeutic strategies. Further exploration of these relationships is essential for a comprehensive understanding of PC progression and management.
Role of warming trend in occurrence of record‐breaking high‐temperature events in China during the past 40 years
Authors: Kuang Xueyuan , Zhang Yaocun , Huang Ying , Cheng Kemeng 
Published: November 2024

AbstractRecord high temperatures and heatwaves are increasingly being reported worldwide, sparking significant public concern. In a stable climate, occurrences of record‐breaking events (RBEs) should naturally decrease over time. Therefore, the increasing occurrence of record high temperatures signifies significant instability in the current climate change, potentially attributed to global warming. In this study, we aim to quantitatively investigate the impact of the warming trend on RBE occurrence by examining high‐temperature RBEs based on observations in China over the past 40 years. Additionally, we introduce statistical theory based on random processes to assess its applicability to real‐world scenarios. By comparing the frequency, intensity, and waiting time for RBEs derived from the original and detrended high‐temperature series‐, we find that approximately 10% of RBE frequency in Nanjing station over the past 40 years can be linked to the warming trend. Furthermore, the intensity of RBEs weakens and the occurrence time advances for the same reason. Especially, the increase in high‐temperature RBE frequency attributed to the upward temperature trend in the southwest region of China is estimated to be around 10%–20%, significantly surpassing that in other regions. Meanwhile, the observed RBE occurrence probability and intensity align with the theoretical results, while notable discrepancies exist in RBE prediction, highlighting the need for improvement in theory and skill for RBE forecasting given its complexity and uncertainty.
Adaptive Dynamic Programming for a Nonlinear Two‐Player Non‐Zero‐Sum Differential Game With State and Input Constraints
Authors: Zhou Yinglu , Li Yinya , Sheng Andong , Qi Guoqing 
Published: November 2024

ABSTRACTThis paper investigates a nonlinear two‐player non‐zero‐sum differential game with state and input constraints. To solve this problem, this paper constructs a neural network (NN) framework to approximate the solution of the Hamilton‐Jacobi‐Isaacs (HJI) equation. The adaptive dynamic programming (ADP) method is utilized where each player only needs one critic NN. To solve the issue of state and input saturations, this paper develops a novel constrained system for the differential game, firstly to make the states within the predetermined constraint set. Then, the non‐quadratic expression is used to substitute the traditional quadratic expression for the two‐player non‐zero‐sum differential game, and both of the inputs of the two players are constrained. With these treatments, the control input and the system are more in line with real‐world applications. Moreover, the stability of the system is also analyzed using the Lyapunov theorem. Two numerical examples are presented to illustrate that the critic NN weights estimation errors and the system are uniformly ultimately bounded (UUB), and the state and input constraints can be achieved.
A New XPS Test Material for More Reliable Analysis of Microstructures
Authors: Stockmann Jörg M. , Radnik Jörg , Bütefisch Sebastian , Weimann Thomas , Hodoroaba Vasile‐Dan 
Published: November 2024

ABSTRACTA reference material is required for small‐area XPS because it has been used more frequently for surface control in recent years and many operators use incorrect field of views. To address this problem, we developed a test material starting in 2019. We optimised this XPS test material dedicated to the control of analysis position on the sample, with respect to the following factors: type of XPS instruments available on the market, the manufacturing process and sample handling. Test structures are now aligned along lines instead of on a circle radius, so that the individual structures can be accessed more quickly and easily. In addition, a larger test structure of 300 μm and another one in an intermediate size of 18 μm were added. Smaller test structures under 50 μm have been annotated with finder grids/arrows around them so that they are easier to find. Further, the manufacturing process was changed from e‐beam lithography to a mask process to be able to offer the test material at a favourable price. The use of masks also had to be adapted for the new manufacturing process so that the smallest square structures are also realised as such and do not show any distortion of the structure boundaries. The quality control using a metrological SEM confirmed a very reproducible manufacturing process. It is demonstrated that the test material can be successfully employed to find the most suitable beam size of the XPS system used for the analysis of small (μm range) surface features.
The Interaction of Polygenic Susceptibility to Stress and Childhood Adversity Dimensions Predicts Longitudinal Trajectories of Stress‐Sensitivity
Authors: Barrantes‐Vidal N. , Gizdic A. , Torrecilla P. , Mas‐Bermejo P. , Sheinbaum T. , Papiol S. , Lafit G. , Myin‐Germeys I. , Rosa A. , Kwapil T. R. 
Published: November 2024

ABSTRACTStress‐sensitivity (SS) is considered a psychobiological trait possibly resulting from the interaction of genetic and environmental factors (GxE). This study examined whether the interaction of SS‐related genetic markers with interview‐based dimensions of childhood adversity predicted longitudinal trajectories of low versus high SS. Participants were nonclinically‐ascertained young adults comprising normative and elevated scores on schizotypy. SS trajectories were defined in a previous report based on three prospective assessments (23.5, 25, 28 years‐old) of both retrospective (Perceived Stress Scale; PSS) and momentary (Experience Sampling Methodology; ESM) stress ratings. A total of n = 177 and n = 165 participants with PSS and ESM stress‐sensitivity trajectories, respectively, as well as genetic data, were included in the study. GxE effects between a SS Polygenic Risk Score (PRS‐SS) and a Genetic Risk Score of the Hypothalamic Pituitary Adrenal axis (GRS‐HPA) with childhood adversity dimensions (Intrafamilial Adversity, Threat and Deprivation) on SS trajectories were examined. Threat was the most consistent predictor of persistently high SS. PRS‐SS moderated the association of Threat with high‐PSS. GRS‐HPA moderated the effects of all adversity dimensions on high‐PSS. The interaction of PRS‐SS with Deprivation and GRS‐HPA with Intrafamilial Adversity predicted trajectories of momentary social stress, but the effects were driven by those with lower genetic susceptibility. Genetic‐HPA‐axis moderates the effects of all adversity dimensions on persistent SS trajectories, as well as PRS‐SS and Threat, particularly for retrospective stress measure. The findings highlight the complex interplay between GxE factors and suggest that PSS may better capture SS trait. Including biologically‐meaningful GRS indexing SS and adversity dimensions in future studies using comprehensive stress measures would enhance our knowledge on high SS susceptibility and its relationship with diverse psychopathological outcomes.
A novel deep learning‐based technique for efficient characterization of engineered cementitious composites cracks for durability assessment
Authors: Das Avik Kumar , Leung Christopher K. Y. 
Published: November 2024

AbstractEngineered Cementitious Composites also known as Strain‐hardening cementitious composites (SHCCs) has unique cracking patterns like cracks that have tiny widths and showcase high density. All of this makes it difficult and laborious to compute crack parameters from crack patterns. Unfortunately, this is an essential part of assessing durability and micromechanical modeling. SHSnet is developed to perform end‐to‐end semantic segmentation of SHCC cracks. SHSnet is efficient, attention based deep encoder‐decoder network with large receptive field. Loss function based on Tversky function were used for training the model. SHSnet with loss function shows promising result with mPrecision, mF1Score and mIoU of 0.87, 0.84 and 0.83 respectively for complex SHCC cracks while requiring at least an order of fewer computational parameters than those in the literature. An image processing unit is then used to estimate the width, number, and length of the cracks from the segmentation mask. Test results show that the computed crack parameters with SHSnet are exactly the same as that computed with an optical microscope but require ~100× less time. Results demonstrate that SHSnet works equally well in SHCCs with different surface textures, crack density, and widths; the final result was far superior to a conventional technique. This technique also shows promising results in an automatic evaluation of crack parameters relevant to durability and visualizing crack patterns even in the presence of artifacts during progressive testing. The results also demonstrate the necessity to accurately and densely calculate crack length and maximum crack width; else the durability results are expected to be significantly more conservative than the actual value.
Translanguaging in US K–12 science and engineering education: A review of the literature through the lens of equity
Authors: Grapin Scott E. , Ramos Borrego Marisleydi , Navarro Vijay Gallardo 
Published: November 2024

AbstractResearch on translanguaging in science and engineering education has grown rapidly. Studies carried out across diverse contexts converge in their commitment to fostering equity in science and engineering learning for linguistically marginalized learners. However, the rapid growth of this research area has exposed different approaches to conceptualizing “equity” itself. The purpose of this review of literature was to examine what equity approaches have undergirded research on translanguaging in US K–12 science and engineering education and whether these approaches vary over time and across contexts. We systematically analyzed studies (N = 15) using the four equity approaches articulated in a recent report by the National Academies of Sciences, Engineering, and Medicine (2022). Findings of our review indicate that, while studies aimed at increasing opportunity and access to high‐quality science and engineering learning (Approach 1) and, to a lesser extent, identification and representation with science and engineering (Approach 2) were the two most prevalent equity approaches, studies focused on expanding what constitutes science and engineering (Approach 3) and seeing science and engineering as part of justice movements (Approach 4) were somewhat less common. Furthermore, justice‐oriented approaches to equity (Approaches 3 and 4) were increasingly visible in the literature since 2020 as well as in research carried out in nontraditional educational contexts (e.g., out‐of‐school programs, classes outside of the core school subjects). Based on these findings, we propose the need for future research that (a) explicitly conceptualizes and operationalizes constructs related to equity (e.g., what is meant by “achievement” and how it is measured), (b) examines the possibilities and tensions associated with expanding what constitutes science and engineering in traditional educational contexts, (c) leverages the affordances of multiple STEM subjects for addressing justice issues impacting linguistically marginalized communities, and (d) iterates on the equity approaches themselves.
Electrochemical Nanosensor‐Based Emerging Point‐Of‐Care Tools: Progress and Prospects
Authors: Pena‐Zacarias Jaqueline , Zahid Md Ikhtiar , Nurunnabi Md 
Published: November 2024

ABSTRACTEarly detection of disease remains a crucial challenge in medicine. Delayed diagnosis often leads to limited treatment options, increased disease progression, and unfortunately, even death in some cases. To address this, the need for rapid, cost‐effective, and noninvasive diagnostic tools is paramount. In recent years, electrochemical nanosensor‐based point‐of‐care diagnostic tools have emerged as promising tools for various fields, with significant interest in their biological and chemical applications. These tiny sensors, utilizing nanoparticles and chemical agents, can detect and monitor physical components like disease biomarkers at the nanoscale, offering a unique advantage rarely found in other diagnostic methods. This unprecedented sensitivity has made them highly sought‐after tools for biological applications, particularly in disease diagnosis. This review focuses specifically on electrochemical nanosensors and their potential as diagnostic tools in medicine. We will delve into their properties, applications, current advancements, and existing limitations.