bluuebunny/crossref_metadata_2025_split huggingface dataset:
Informing the risk assessment related to lactation and drug exposure: A physiologically based pharmacokinetic lactation model for pregabalin
Authors: Humerickhouse Cameron , Pressly Michelle , Lin Zhoumeng , Guinn Daphne , Samuels Sherbet , Pfuma Fletcher Elimika , Schmidt Stephan 
Published: October 2024

AbstractBreastfeeding is important in childhood development, and medications are often necessary for lactating individuals, yet information on the potential risk of infant drug exposure through human milk is limited. Establishing a lactation modeling framework can advance our understanding of this topic and potentiate clinical decision making. We expanded the modeling framework previously developed for sotalol using pregabalin as a second prototypical probe compound with similar absorption, distribution, metabolism, and elimination (ADME) properties. Adult oral models were developed in PK‐Sim® and used to build a lactation model in MoBi® to simulate drug transfer into human milk. The adult model was applied to breastfeeding pediatrics (ages 1 to 23 months) and subsequently integrated with the lactation model to simulate infant drug exposure according to age, size, and breastfeeding frequency. Physiologically based pharmacokinetic (PBPK) model simulations captured the data used for verification both in adults and pediatrics. Lactation simulations captured observed milk and plasma data corresponding to doses of 150 mg administered twice daily to lactating individuals, and estimated a relative infant dose (RID) of approximately 7% of the maternal dose. The infant drug exposure simulations showed peak plasma concentrations of 0.44 μg/mL occurring within the first 2 weeks of life, followed by gradual decline with age after week four. The modeling framework performs well for this second prototypical drug and warrants expansion to other drugs for further validation. PBPK modeling and simulation approaches together with clinical lactation data could ultimately help inform infant drug exposure risk assessments to guide clinical decision making.
A learning theory‐based exploratory analysis of teacher professional development interventions for formative assessment
Authors: de Vries J. A. , Visscher A. J. , Schildkamp K. 
Published: October 2024

AbstractThere is substantial evidence in cognitive psychology for the effectiveness of learning theory‐based principles, such as activating prior knowledge or retrieval practice, for learning. In this exploratory study, we analysed to what degree such learning theory‐based principles are applied in teacher professional development (TPD) interventions for formative assessment and how, and whether differences in the use of these principles between TPD interventions explain differences in the effectiveness of such interventions. We found that the impact of TPD interventions for formative assessment on student achievement was evaluated rigorously in very few studies, with only five in our sample. Our results also showed that most learning theory‐based principles were applied only to a very limited degree, and not deliberately. Both findings imply that no patterns relating the application of learning theory‐based principles and intervention effectiveness were discernible. However, given the general evidence for the principles, there is probably much to gain by applying the learning theory‐based principles when developing TPD interventions for formative assessment.
Context and implicationsRationale for this studyStudies in cognitive psychology have resulted in clear principles to promote learning. It is unknown whether these have been used to improve teacher professional development (for formative assessment).Why the new findings matterThe limited use of learning theory‐based principles in TPD development is remarkable, as there is strong evidence that these principles are effective.Implications for researchersOnly 5 of 44 evaluated studies adhered to high standards for randomised controlled trials set by Cheung and Slavin (2016) and What Works Clearinghouse (2020), meaning that we ultimately have very little reliable data on the effectiveness of TPD interventions for formative assessment. If we want to know what influences improvement in teacher skills when conducting TPD interventions, then better interventions and evaluations are needed.The learning theory‐based principles themselves are the result of thorough research, and it is therefore worthwhile to further investigate how the learning theory‐based principles can be used to improve TPD interventions for formative assessment.
Soil landscapes of the United States (SOLUS): Developing predictive soil property maps of the conterminous United States using hybrid training sets
Authors: Nauman Travis W. , Kienast‐Brown Suzann , Roecker Stephen M. , Brungard Colby , White David , Philippe Jessica , Thompson James A. 
Published: October 2024

AbstractDetailed soil property maps are increasingly important for land management decisions and environmental modeling. The US Soil Survey is investing in production of the Soil Landscapes of the United States (SOLUS), a new set of national predictive soil property maps. This paper documents initial 100‐m resolution maps of 20 soil properties that include various textural fractions, physical parameters, chemical parameters, carbon, and depth to restrictions. Many of these properties have not been previously mapped at this resolution. A hybrid training strategy helped increase training data by roughly 10‐fold over previous similar studies by combining commonly used laboratory data with underutilized field descriptions tied to soil survey map unit component property estimates (to help represent within polygon variability) as well as randomly selected soil survey map unit weighted average property estimates. Relative prediction intervals were used to help select which training data sources improved model performance. Conventional and spatial cross‐validation strategies yielded generally strong coefficients of determination between 0.5 and 0.7, but with substantial variability and outliers among the various properties, types of training data, and depths. Internal review of the maps highlighted both strengths and weaknesses of the maps, but most of the critical comments were in areas with high model uncertainty that can be used to guide future improvements. Generally, previously glaciated areas and complex large alluvial basins were harder to model. The new SOLUS 100‐m maps will be updated in the future to address identified issues and feedback as users interact with the data.
Working for Jessica or Michael? Implications of gender stereotypes for job application intentions at technology startups
Authors: Tonoyan Vartuhi , Strohmeyer Robert , Jennings Jennifer 
Published: October 2024

AbstractResearch SummaryWe examine a critical yet underexplored aspect of human resource management in nascent technology ventures: employee recruitment. Applying theories of gender stereotyping, we contend that female‐led technology startups face greater obstacles in attracting job applicants than their male counterparts. Evidence from a randomized online experiment conducted in 2020/2021 with 777 US job seekers substantiates this barrier, indicating that the disparities are partly rooted in gender‐stereotypical perceptions of female technology entrepreneurs as less competent, agentic, and warm, which contribute to less favorable assessments of their ventures' economic potential and employee empowerment potential. Startups with gender‐diverse leadership teams appear to overcome these biases. Confirmatory evidence comes from a 2024 replication study with 455 US job seekers, underscoring the need to address gender biases in the technological ecosystem.Managerial SummaryIn the competitive landscape of technology startups, attracting talent is key. Our study reveals that startups with female leaders face gender biases during recruitment, with job candidates perceiving female technology entrepreneurs as less competent, agentic, and warm—and their startup ventures as less likely to have what it takes to grow and to empower employees. Analysis from a randomized online experiment involving 777 US job seekers in 2020/2021 and a follow‐up study with 455 US job seekers in 2024 confirm such biases. Crucially, a gender‐balanced leadership team significantly counters such biases, enhancing the venture's appeal to potential hires. These insights highlight the need for technology startups to promote gender diversity within their leadership to dismantle stereotypes and attract a broader talent pool.
Profiling Breast Tumor Heterogeneity and Identifying Breast Cancer Subtypes Through Tumor‐Associated Immune Cell Signatures and Immuno Nano Sensors
Authors: Ishwar Deeptha , Premachandran Srilakshmi , Das Sunit , Venkatakrishnan Krishnan , Tan Bo 
Published: October 2024

AbstractBreast cancer is a complex and heterogeneous disease with varying cellular, genetic, epigenetic, and molecular expressions. The detection of intratumor heterogeneity in breast cancer poses significant challenges due to its complex multifaceted characteristics, yet its identification is crucial for guiding effective treatment decisions and understanding the disease progression. Currently, there exists no method capable of capturing the full extent of breast tumor heterogeneity. In this study, the aim is to identify and characterize metabolic heterogeneity in breast tumors using immune cells and an ultrafast laser‐fabricated Immuno Nano Sensor. Combining spectral markers from both Natural Killer (NK) and T cells, a machine‐learning approach is implemented to distinguish cancer from healthy samples, identify primary versus metastatic tumors, and determine estrogen receptor (ER)/progesterone receptor (PR) status at the single‐cell level. The platform successfully distinguished heterogeneous breast cancer samples from healthy individuals, achieving 97.8% sensitivity and 92.2% specificity, and accurately identified primary tumors from metastatic tumors. Characteristic spectral signatures allow for discrimination between ER/PR‐positive and negative tumors with 97.5% sensitivity. This study demonstrates the potential of immune cell‐based metabolic profiling in providing a comprehensive assessment of breast tumor heterogeneity and paving the way for minimally invasive liquid biopsy approaches in breast cancer diagnosis and management.
Parallelized Mechanical Stimulation of Neuronal Calcium Through Cell‐Internal Nanomagnetic Forces Provokes Lasting Shifts in the Network Activity State
Authors: Beck Connor L. , Kunze Anja 
Published: October 2024

AbstractNeurons differentiate mechanical stimuli force and rate to elicit unique functional responses, driving the need for further tools to generate various mechanical stimuli. Here, cell‐internal nanomagnetic forces (iNMF) are introduced by manipulating internalized magnetic nanoparticles with an external magnetic field across cortical neuron networks in vitro. Under iNMF, cortical neurons exhibit calcium (Ca2+) influx, leading to modulation of activity observed through Ca2+ event rates. Inhibiting particle uptake or altering nanoparticle exposure time reduced the neuronal response to nanomagnetic forces, exposing the requirement of nanoparticle uptake to induce the Ca2+ response. In highly active cortical networks, iNMF robustly modulates synchronous network activity, which is lasting and repeatable. Using pharmacological blockers, it is shown that iNMF activates mechanosensitive ion channels to induce the Ca2+ influx. Then, in contrast to transient mechanically evoked neuronal activity, iNMF activates Ca2+‐activated potassium (KCa) channels to stabilize the neuronal membrane potential and induce network activity shifts. The findings reveal the potential of magnetic nanoparticle‐mediated mechanical stimulation to modulate neuronal circuit dynamics, providing insights into the biophysics of neuronal computation.
How the Spacer Influences the Stability of 2D Perovskites?
Authors: Gao Xinying , Wu Yilei , Zhang Yehui , Chen Xinyu , Song Zhilong , Zhang Tingbo , Fang Qianglong , Ji Qun , Ju Ming‐Gang , Wang Jinlan 
Published: October 2024

AbstractTwo‐dimensional lead halide perovskites (2D HPs) represent as an emerging class of materials given their tunable optoelectronic properties and long‐term stability in perovskite solar cells. However, the ever‐growing field of optoelectronic devices using 2D HPs requires fundamental understanding of the influence of the spacer on the physiochemical properties and stability of perovskites as well as establish which cation properties are closely related to suppress the halogen ion mobility. This study focuses on investigating the influence of organic spacers with intrinsic properties (e.g., rigidity and flexibility, special groups) and variations of material dimensions on the stability of halogen ions and inorganic frameworks in 2D HPs. It is found that the perovskite structure composed of rigidity molecules owns better stability of halogen ion and inorganic framework than that of flexible molecules. The stability of ions exhibits a negative correlation with the dimensions of perovskite. More importantly, a simple descriptor for measuring the stability of halogen ions in 2D HPs is constructed. By causal discovery algorithms with more physical and chemical significance, the Kappa shape index, number of rotatable bonds, and aromatic carbocycles in organic spacers are identified as causal and important features for the stability of halogen ions in 2D HPs.
G.O.O.S.E.: Introducing a novel five‐stage structured framework for the early phases of teaching and learning ultrasound
Authors: Pascoe Suean 
Published: October 2024

AbstractThe sonography profession faces a critical global workforce shortage, particularly pronounced in Australia, due to insufficient clinical training opportunities and an ageing workforce. The financial burden and increased scan times associated with training exacerbate this issue. Innovative approaches, such as intensive ultrasound courses and pair scanning protocols, have shown promise in addressing these challenges. The GOOSE framework (Get the window, Optimise the view, Optimise the image, Select the image, Explain the findings) offers a structured, step‐by‐step approach to practical sonography training. This framework deconstructs complex ultrasound skills into manageable tasks, optimises cognitive load management, and provides explicit guidance for novice learners. The GOOSE framework is designed to enhance the efficiency of teaching and learning by simplifying complex skills into clear, actionable steps, supported by checklists that guide both instructors and students through the training process. The GOOSE framework offers a systematisation of knowledge transfer that, combined with deliberate practice and structured feedback, ensures learners progressively build their skills with focused, goal‐directed activities. While this model is yet to be validated, initial implementations have shown promising results in improving trainee performance, reducing supervision workload, and standardising instructional methods. This article outlines the principles of the GOOSE framework, its development, and its application in a specialised training facility, proposing it as a standardised model to enhance practical ultrasound education and improve teaching and learning efficiency.
Critical systems thinking for managing complexity of food security
Authors: Hasyimi Valid , Putro Utomo Sarjono , Novani Santi , Hendriadi Agung 
Published: October 2024

AbstractReductionist approaches, conventionally used to address the complexities of food security, successfully addressed production challenges throughout the 20th century. However, this approach met its limitations when addressing broader issues encompassing socio‐economic and sustainability. Additionally, this approach tends to equip us with reactive methods rather than prescriptive, while decision‐makers today are encouraged to take anticipatory plans and act quickly in any situation. This paper tries to manage the complexity of food security using critical system thinking to assist decision‐makers in choosing a system approach relevant to the issue. It started by presenting the evolution of food security complexity by documenting significant historical milestones in the global journey of global food security. Furthermore, we associate the outcomes of each milestone, in this case, the World Food Conference/Summit, in shaping the direction of the global research theme. We also interview stakeholders from government, businesses and NGOs to identify the complexity of food practices based on their perspectives. Lastly, we categorize food security issues into six types of complexity by referring to Jackson. We show how system of systems methodology (SOSM) can enable us to frame the complexity of food security into relevant categories equipped with suggested methods, thereby enabling the allocation of resources and time more effectively and efficiently.
Development and Validation of Trace Level Quantification of Nine Azido Genotoxic Impurities in Losartan Potassium Active Pharmaceutical Ingredients by Liquid Chromatography‐Tandem Mass Spectrometry
Authors: Kondaveti Praveen Kumar , Sanasi Paul Douglas , Saravanan G , Yeruva Koti Reddy , Palla Mahesh 
Published: October 2024

ABSTRACTThe objective of the study is to develop a sensitive and simple liquid chromatography‐tandem mass spectrometry for the determination of nine azido impurities in Losartan potassium active pharmaceutical ingredients. An advanced analytical method should be developed to determine these nine Azido impurities at 0.5 ppm level. Currently, no such method is reported to control these impurities in losartan potassium drug substance. The nine impurities separation was achieved using Hypersil ODS stationary phase with gradient elution and mobile phase of 0.1 M ammonium acetate as mobile phase A and methanol as mobile phase B. The developed method was found to be sensitive to the limit of detection and limit of quantitation levels as per the International Council for Harmonization M7 guidelines. The method was linear from 0.5 ppm to 15 ppm for all nine azido impurities. This is a single method for the simultaneous determination of all azido impurities in the presence of losartan potassium drug substance at 0.5 ppm and the same method used in the quality control laboratory for sample analysis.
Comparison of the Effectiveness of Warmed Versus Room Temperature Intravenous Fluids Administration to Prevent Intraoperative Heat Loss in Anaesthetised Calves Undergoing Umbilical Herniorrhaphy
Authors: Okur Sitkican , Yanmaz Latif Emrah , Senocak Mumin Gökhan , Golgeli Ayse , Turgut Ferda , Orhun Omer Tarik , Kocaman Yakup , Ersoz Ugur 
Published: October 2024

ABSTRACTBackgroundWarmed intravenous (IV) fluids administration to prevent hypothermia provide controversial results in humans, cats and dogs, but its effect on calves is unknown.ObjectivxeTo evaluate the effectiveness of warmed IV fluids administered to prevent intraoperative heat loss in anaesthetised calves undergoing umbilical herniorrhaphy.MethodsThirty Simmental breed calves (aged 10–30 days) were randomly divided between two equal groups, wherein the infusion fluid (Ringer's lactate, 5 mL/kg/h) was administered either at room temperature (Group RoT) or warmed (Group WF). Pulse rate (PR), respiratory rate (fR), peripheral haemoglobin oxygen saturation (SpO2) and rectal temperature (RT) were recorded immediately after the onset of anaesthesia induction (T0) at T5, T10, T15, T30, T45 and T60. Duration of anaesthesia, surgery time and recovery scores were also noted.ResultsThe PR, RT and fR values showed no significant difference between groups over time (p > 0.05). There was no significant difference in duration of anaesthesia, surgery time or recovery score between groups (p > 0.05).ConclusionsThe findings of the current study suggest that warmed IV fluid as the warming method did not prevent intraoperative hypothermia in calves. A constant‐rate infusion of warmed fluid (5 mL/kg/h) is insufficient to prevent intraoperative hypothermia in calves.
Primary primitive neuroectodermal tumour in the orbit of a domestic shorthair cat (Felis catus)
Authors: Zeliger Mirabella , Roberts Jordan K. , Shaw Gillian C. , Taylor Ryan 
Published: October 2024

AbstractA 13‐year‐old, domestic shorthair cat presented for evaluation of left‐sided exophthalmos, epiphora and third eyelid elevation of approximately 4‐month duration. Based on ophthalmic exam findings, a retrobulbar mass was suspected. Computed tomography of the head revealed a fluid to soft‐tissue, non‐contrast‐enhancing mass caudoventral to the left globe. Based on these findings, a retrobulbar abscess was considered the most likely differential, while a neoplastic mass could not be completely excluded. The mass and left globe were surgically excised via a modified lateral orbitotomy and exenteration. Histopathology and special staining of the mass was consistent with an orbital primitive neuroectodermal tumour, while the globe was unremarkable.
Literature Review
Authors: Born Marius 
Published: October 2024

AbstractThis chapter delineates the research space and highlights significant conceptual contributions to the fields of storytelling and argumentation, as these are the primary lenses through which the case study is analyzed. Section 2.1 delves into the concept of trust and explains related terms such as confidence, credibility, image, and reputation. Section 2.2 explores storytelling from a broad historical perspective, discussing influential narrative structures, some of whose origins date back centuries. Section 2.3 examines argumentation with a focus on the pragma-dialectical approach and outlines the steps and tools critical to argumentative reconstruction in case analysis. In addition, it addresses key points of attack relevant to counter argumentation, which are of particular importance for the analysis of the crisis episode in the case study.
Nikola’s Rise
Authors: Born Marius 
Published: October 2024

AbstractChapter 5 traces Nikola’s rapid ascent to becoming a $30 billion corporation, with a stock market value that briefly surpassed that of the Ford Motor Company. This rise was largely driven by founder Trevor Milton, who captivated investors with promises of a sustainable alternative to diesel trucks. Milton’s persuasive communication significantly increased the company’s stock value but also made the startup particularly vulnerable. Using the Nikola Corporation as a cautionary tale, this chapter provides an in-depth examination of the methods and tools necessary for startups to overcome initial skepticism and data limitations while avoiding potential crises. It emphasizes the importance of crafting compelling startup narratives while maintaining trustworthiness and structuring arguments in a way that convincingly meets investors’ information needs.
The State of Agricultural Transformation in Taiwan, China; the Philippines; Ethiopia; and Malawi
Authors: Rohne Till Emelie , Andersson Martin , Tsakok Isabelle 
Published: October 2024

AbstractIn order to gain a nuanced insight into the causal connections between political leadership and agricultural transformation, the book studies four empirical country case studies. The cases include both successful and unsuccessful cases of agricultural transformations. This chapter outlines the first step of our empirical inquiry and takes stock of the state of the agricultural transformation in our four cases. This includes the well-known successful agricultural transformation in Taiwan, China (1950–1980), the failed agricultural transformations in the Philippines (1946–2020) and Malawi (1964–2020), and the mixed record of Ethiopia’s agricultural transformation (1994–2020).