bluuebunny/crossref_metadata_2025_split huggingface dataset:
How parties can shape their competence reputations: Issue attention, position and performance
Authors: STIERS DIETER , DASSONNEVILLE RUTH 
Published: October 2024

AbstractIssue ownership is an important determinant of the vote, and it is electorally beneficial for parties to build a strong reputation on their core issues. Even though issue ownership has already been studied extensively in the party literature, we know less about how citizens form ownership perceptions. We contribute to this literature by means of two studies on the connection between party behaviour and perceptions of issue ownership, with an empirical focus on issue competence reputations of parties. In Study 1, we combine party‐level information about issue attention, positions and performance with data on competence perceptions from a wide range of national election studies. Study 2 is a pre‐registered conjoint experiment designed to examine the causal link between party behaviour and perceived competence. Our results point to significant effects for all three hypothesised sources of competence reputations. Moving beyond previous work that has argued that competence reputations are mostly stable over time, after accounting for the variation due to parties' popularity, our results show that they fluctuate in the short term and that parties have some level of control over how they are perceived.
Supporting clinicians post exposure to potentially traumatic events: Emergency department peer support program evaluation
Authors: Carne Belinda , Furyk Jeremy 
Published: October 2024

AbstractObjectiveWorkers in EDs are regularly exposed to potentially traumatic events. Since the COVID‐19 pandemic, there has been exponential interest in peer support programs (PSPs) in a range of settings. We describe a PSP implemented in 2017 at University Hospital Geelong (UHG) ED together with results of a survey.MethodsTo describe the program such that others can replicate it in their settings in addition to feedback evaluation. Method involved a survey emailed to the ED doctors.ResultsThirty responses from 96 emails with a range of feedback.ConclusionED Doctors place high value on the PSP.
The climate change–pollution–aerobiome nexus: A ‘systems thinking’ mini‐review
Authors: Robinson Jake M. , Liddicoat Craig , Sun Xin , Ramesh Sunita , Hawken Scott , Lee Kevin , Brame Joel , Fickling Nicole W. , Kuhn Emma , Hayward Claire , Deshmukh Sonali , Robinson Kate , Cando‐Dumancela Christian , Breed Martin F. 
Published: October 2024

AbstractThe interrelationship between climate change, pollution and the aerobiome (the microbiome of the air) is a complex ecological dynamic with profound implications for human and ecosystem health. This mini‐review explores the multifaceted relationships among these factors. By synthesising existing research and integrating interdisciplinary perspectives, we examine the mechanisms driving interactions within the climate change–pollution–aerobiome nexus. We also explore synergistic and cascading effects and potential impacts on human health (including both communicable and non‐communicable diseases) and that of wider ecosystems. Based on our mini‐review results, climate change influences air pollution and, independently, air pollution affects the composition, diversity and activity of the aerobiome. However, we apply a ‘systems thinking’ approach and create a set of systems diagrams to show that climate change likely influences the aerobiome (including bacteria and fungi) via climate change–pollution interactions in complex ways. Due to the inherent complexity of these systems, we emphasise the importance of holistic and/or interdisciplinary approaches and collaborative efforts in understanding this nexus to safeguard planetary health in an era of rapid environmental change.
Archaeological Geology of Jurash, ʿAsīr Province, Southwestern Saudi Arabia
Authors: Harrell James A. 
Published: October 2024

ABSTRACTThe Jurash archaeological site is located on Wādī Bīshah near the city of Khamīs Mushayt in southwestern Saudi Arabia. It has a fort and other remains from the pre‐Islamic period (third century bc to early seventh century ad) and a settlement with two mosques from the Early Islamic period (early seventh to early 11th centuries ad). A survey was conducted for the purposes of identifying the building materials and determining their geographic sources, and also investigating the building methods. It was found that all materials were locally derived and that the fort's outer wall is a typical example of South Arabian fortifications of the first millennium bc. An examination of the site stratigraphy revealed that Jurash has been repeatedly inundated by destructive flash floods from Wādī Bīshah. The timing of these events was largely controlled by global climatic fluctuations, including the Medieval Climate Anomaly and the Little Ice Age.
Digital phenotyping in bipolar disorder: Using longitudinal Fitbit data and personalized machine learning to predict mood symptomatology
Authors: Lipschitz Jessica M. , Lin Sidian , Saghafian Soroush , Pike Chelsea K. , Burdick Katherine E. 
Published: October 2024

AbstractBackgroundEffective treatment of bipolar disorder (BD) requires prompt response to mood episodes. Preliminary studies suggest that predictions based on passive sensor data from personal digital devices can accurately detect mood episodes (e.g., between routine care appointments), but studies to date do not use methods designed for broad application. This study evaluated whether a novel, personalized machine learning approach, trained entirely on passive Fitbit data, with limited data filtering could accurately detect mood symptomatology in BD patients.MethodsWe analyzed data from 54 adults with BD, who wore Fitbits and completed bi‐weekly self‐report measures for 9 months. We applied machine learning (ML) models to Fitbit data aggregated over two‐week observation windows to detect occurrences of depressive and (hypo)manic symptomatology, which were defined as two‐week windows with scores above established clinical cutoffs for the Patient Health Questionnaire‐8 (PHQ‐8) and Altman Self‐Rating Mania Scale (ASRM) respectively.ResultsAs hypothesized, among several ML algorithms, Binary Mixed Model (BiMM) forest achieved the highest area under the receiver operating curve (ROC‐AUC) in the validation process. In the testing set, the ROC‐AUC was 86.0% for depression and 85.2% for (hypo)mania. Using optimized thresholds calculated with Youden's J statistic, predictive accuracy was 80.1% for depression (sensitivity of 71.2% and specificity of 85.6%) and 89.1% for (hypo)mania (sensitivity of 80.0% and specificity of 90.1%).ConclusionWe achieved sound performance in detecting mood symptomatology in BD patients using methods designed for broad application. Findings expand upon evidence that Fitbit data can produce accurate mood symptomatology predictions. Additionally, to the best of our knowledge, this represents the first application of BiMM forest for mood symptomatology prediction. Overall, results move the field a step toward personalized algorithms suitable for the full population of patients, rather than only those with high compliance, access to specialized devices, or willingness to share invasive data.
Ureteroscopy and lasertripsy for lower pole stones <2 cm, in situ vs displacement? A systematic review and meta‐analysis
Authors: Dingwall Arran , Leighton James , Luk Angus , Chambers Mark , Somani Bhaskar , Geraghty Robert 
Published: October 2024

ObjectiveTo investigate the outcomes of ureteroscopy and lasertripsy in lower pole renal stones <2 cm when treated in situ compared to displacement to the upper pole.Patients and MethodsUsing the Medical Literature Analysis and Retrieval System Online (MEDLINE)/PubMed, the Excerpta Medica dataBASE (EMBASE), Cumulative Index to Nursing and Allied Health Literature (CINAHL), the Cochrane Library, and Clinicaltrials.gov we identified adult population, English language, studies published until March 2023 comparing surgical outcomes and stone‐free rates (SFRs) in relation to lower pole stones <2 cm managed in situ vs those displaced (International Prospective Register of Systematic Reviews [PROSPERO] identifier: CRD42023432750). Analysis was performed using R with the ‘meta’ package. Bias analysis was performed using the Cochrane Risk of Bias 2 tool for randomised trials and the Newcastle–Ottawa scale for observational studies. The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach was used to ascertain the certainty of evidence.ResultsA total of five studies were included, comprising two retrospective cohort studies, three randomised trials, with a total of 408 patients. Meta‐analysis demonstrated SFRs are significantly higher in those patients undergoing displacement vs those managed in situ (risk ratio 1.21, 95% confidence interval [CI] 1.10–1.34, P < 0.001). There was no significant difference in complication rates. Operative time was significantly longer in the displacement group (mean difference 5.62 min, 95% CI 0.40–10.83 min; P = 0.03). Overall risk of bias was moderate. Certainty of evidence was moderate for stone‐free status, and very low for all other outcomes.ConclusionsThis systematic review and meta‐analysis demonstrates that for lower pole stones <2 cm displacement strategies have significantly higher SFRs than treatment in situ, with no significant difference in complications. There is significantly increased operative time in the displaced group, but an additional 6 min is unlikely to be clinically significant.
Apelin‐13's Actions in Controlling Hypertension‐Related Cardiac Hypertrophy and the Expressions of Inflammatory Cytokines
Authors: Wei Xiaoliang , Luo Liyun , Lu Huifang , Li Songbiao , Deng Xinlian , Li Zhihui , Gong Dong , Chen Bairong 
Published: October 2024

ABSTRACTAs a key molecule for improving cardiovascular diseases, Apelin‐13 was surveyed in this work to explain its actions in controlling inflammation, pyroptosis, and myocardial hypertrophy. First, mouse models with myocardial hypertrophy were established. Then, assessments were made on the pathological variation in the heart of mouse, on the cardiac functions, as well as on the expressions of cardiac hypertrophy markers (β‐MHC, ANP, and BNP), inflammatory factors (TNF‐α, COX2, IL‐6, ICAM‐1, and VCAM‐1), myocardial cell pyroptosis markers (NLRP3, ASC, c‐caspase‐1, and GSDMD‐N), and Hippo pathway proteins (p‐YAP, YAP, LATS1, and p‐LATS1) by HE staining, echocardiography scanning, and western blot tests separately. The expressions of such inflammatory factors as in myocardial tissue were acquired by ELISA. After inducing the phenotype of H9c2 cell hypertrophy by noradrenaline, we used CCK‐8 kits to know about the activity of H9c2 cells treated with Apelin‐13, and performed ɑ‐actinin staining to measure the changes in volumes of such cells. As unraveled through this work, Apelin‐13 refrained the activation of the Hippo pathway, which in turn attenuated the hypertrophy, inflammation, and pyroptosis of myocardial tissue and H9c2 cells. Hence, Apelin‐13 can be considered as a target for hypertension treatment.
Oleic Acid Inhibits SDC4 and Promotes Ferroptosis in Lung Cancer Through GPX4/ACSL4
Authors: Dong Jingfei , Qi Fei , Qie Huiqing , Du Shibu , Li Li , Zhang Yan , Xu Kaiyue , Li Dehui , Xu Yapei 
Published: October 2024

ABSTRACTIntroductionAs a common malignancy, lung cancer has a relatively poor prognosis and a low survival rate. In recent years, ferroptosis, as an emerging filed, has great promise in the potential treatment of cancer. Brucea javanica oil (BJO) is often used to treat various cancers. Oleic acid (OA) is the main ingredient of BJO. In this study, we investigated the role and molecular mechanism of OA in lung cancer treatment by promoting ferroptosis.MethodsIn this study, A549 cells and H1299 cells were used for in vitro experiments, and a CCK‐8 test, scratch test, and MTT experiment were carried out. We examined reactive oxygen species (ROS), the JC‐1 probe, glutathione (GSH) expression, lipid peroxidation, SDC4 mRNA levels, and ACSL4, SLC7A11, GPX4, and SDC4 protein levels.ResultsThe results showed that OA could inhibit the proliferation and migration of A549 cells and H1299 cells, SDC4 was a potential therapeutic target of OA against lung cancer, and OA treatment significantly inhibited the expression of SDC4 in A549 cells and H1299 cells. OA induces ferroptosis in A549 cells and H1299 cells, decreases GSH levels, increases lipid peroxidation levels, and decreases SDC4 mRNA expression; in addition, OA upregulates ACSL4 expression and decreases SLC7A11, GPX4, and SDC4 expression.ConclusionThis study confirmed that OA could inhibit SDC4 expression and promote the occurrence of ferroptosis in A549 cells and H1299 cells through the GPX4/ACSL4 pathway, providing an effective basis for the use of drugs targeting ferroptosis in lung cancer treatment.
Exploring omics signature in the cardiovascular response to semaglutide: Mechanistic insights and clinical implications
Authors: Vitorino Rui 
Published: October 2024

AbstractBackgroundSemaglutide, a glucagon‐like peptide‐1 (GLP‐1) receptor agonist, is a widely used drug for the treatment of type 2 diabetes that offers significant cardiovascular benefits.ResultsThis review systematically examines the proteomic and metabolomic indicators associated with the cardiovascular effects of semaglutide. A comprehensive literature search was conducted to identify relevant studies. The review utilizes advanced analytical technologies such as mass spectrometry and nuclear magnetic resonance (NMR) to investigate the molecular mechanisms underlying the effects of semaglutide on insulin secretion, weight control, anti‐inflammatory activities and lipid metabolism. These “omics” approaches offer critical insights into metabolic changes associated with cardiovascular health. However, challenges remain such as individual variability in expression, the need for comprehensive validation and the integration of these data with clinical parameters. These issues need to be addressed through further research to refine these indicators and increase their clinical utility.ConclusionFuture integration of proteomic and metabolomic data with artificial intelligence (AI) promises to improve prediction and monitoring of cardiovascular outcomes and may enable more accurate and effective management of cardiovascular health in patients with type 2 diabetes. This review highlights the transformative potential of integrating proteomics, metabolomics and AI to advance cardiovascular medicine and improve patient outcomes.
Therapy‐Related Acute Promyelocytic Leukemia: Case Series and Current Insights
Authors: Bruzzese Antonella , Martino Enrica Antonia , Labanca Caterina , Mendicino Francesco , Lucia Eugenio , Olivito Virginia , Morelli Rosellina , Rossi Teresa , Neri Antonino , Morabito Fortunato , Gentile Massimo , Vigna Ernesto 
Published: October 2024

ABSTRACTTherapy‐related acute promyelocytic leukemia (t‐APL) is rare and often linked to previous treatment with alkylating agents or topoisomerase II inhibitors. This report describes three cases of t‐APL treated at the Haematology Department of Cosenza Hospital between 2022 and 2024, which occurred after alkylating agents and exemestane, alkylating agents and radiation therapy, alkylating agents, taxane, and checkpoint inhibitor, respectively. Each case was managed with a different therapeutic approach. The first case involved a 71‐year‐old man with colorectal and breast cancer, who developed low‐risk t‐APL and achieved complete remission (CR) with ATRA alone. A second 71‐year‐old man case with colorectal cancer developed high‐risk t‐APL with PML/RARA and FLT3‐ITD fusion transcripts; he achieved CR with idarubicin and ATRA despite severe sepsis and acute heart failure. The third case involved a 74‐year‐old man with lung squamous cell carcinoma who developed intermediate‐risk t‐APL following chemoimmunotherapy but unfortunately succumbed to pseudotumor cerebri complications during induction therapy.
Do Sex Ratio Distorting Microbes Inhibit the Evolution of Pesticide Resistance? An Experimental Test
Authors: Fisher Adam M. , McKenzie Amelia‐Rose V. , Price Tom A. R. , Bonsall Michael B. , Knell Robert J. 
Published: October 2024

ABSTRACTWe are still largely reliant on pesticides for the suppression of arthropod pests which threaten human health and food production, but the recent rise of evolved resistance among important pest species has reduced pesticide efficacy. Despite this, our understanding of strategies that effectively limit the evolution of resistance remains weak. Male‐killing sex ratio distorting microbes (SRDMs), such as Wolbachia and Spiroplasma, are common among arthropod species. Previous theoretical work has suggested that they could limit adaptive potential in two ways: first, because by distorting sex ratios they reduce the effective population size, and second, because infected females produce no male offspring which restricts gene flow. Here we present the results of a novel experiment in which we test the extent by which these two mechanisms limit the adaptive response of arthropods to pesticide. Using a fully factorial design, we manipulated the adult sex ratio of laboratory populations of Drosophila melanogaster, both in the presence and absence of SRDMs, and exposed these populations to six generations of pesticide poisoning. This design allows the effects of SRDMs on sex ratio and their effects on gene flow to be estimated separately. After six generations, individuals from populations with even sex ratios displayed a higher resistance to pesticide relative to individuals from female‐biased populations. By contrast, we found no effect of the presence of SRDMs in host populations on pesticide resistance independent of sex ratio. In addition, males were more susceptible to pesticide than females—this was true of flies from both naïve and previously exposed populations. These findings provide the first empirical proof of concept that sex ratio distortion arising from SRDMs can limit adaptation to pesticides, but cast doubt on the theoretical effect of male‐killers limiting adaptation by disrupting gene flow.
Prevalence and Predictors of Inflammatory Arthritis in Hidradenitis Suppurativa
Authors: Sy Sheena Maureen T. , Eder Lihi , Jerome Dana , Obetta Chikaodili , McKee Hayley , Mirza Reza , Pek Elisabeth , Piguet Vincent , Alhusayen Raed 
Published: October 2024

ABSTRACTHidradenitis Suppurativa (HS) is a chronic, debilitating, auto‐inflammatory condition often associated with inflammatory arthritis, significantly impacting patients' quality of life. Early diagnosis of both conditions is crucial for optimal management. The objective of this study was to determine the prevalence and factors associated with the development of inflammatory arthritis among HS patients. A cross‐sectional study was conducted between November 2021 and February 2023 at an academic dermatology centre in Canada. Adult patients with HS were consecutively sampled, and 52 patients consented to participate and completed assessments. Variables examined included age, sex, HS severity, treatment, ethnicity, family history, lifestyle factors and comorbidities. The main outcomes were rheumatologist‐confirmed inflammatory arthritis diagnosis and associated risk factors. Among 52 patients (24 males, 28 females; mean age: 37.4 years), 12 had inflammatory arthritis. Multivariate analysis revealed that Blacks (OR = 0.10, p < 0.001, CI: 0.026–0.343) and Asians (OR = 0.02, p < 0.001, CI: 0.005–0.109) had lower inflammatory arthritis odds compared to Whites. Every 1‐year increase in age at HS onset correlated with a 1.17‐fold increase in the odds of developing inflammatory arthritis (OR: 1.17, p < 0.001, CI: 1.12–1.24). Smoking (OR = 0.01, p < 0.001, CI: 0.002–0.49), hypertension (OR: 0.23, p = 0.04, CI: 0.057–0.930) and depression (OR: 0.12, p < 0.001, CI: 0.041–0.330) reduced inflammatory arthritis odds. White ethnicity and older age at HS onset were positively associated with inflammatory arthritis, while smoking, hypertension and depression were negatively associated. These findings suggest a distinct subset of HS patients with inflammatory arthritis that warrant further prospective studies. This study contributes to the understanding of inflammatory arthritis in HS patients and emphasises the importance of rheumatology referral during dermatologic clinic visits.
BENN: Balanced Ensemble Neural Network for Handling Class Imbalance in Big Data
Authors: Ramesh Sneha Halebeedu , Basava Annappa , Perumal Sankar Pariserum 
Published: October 2024

ABSTRACTClass imbalance is a critical challenge in big data analytics, often leading to biased predictive models. This imbalance can lead to biased models that perform well on the majority class but poorly on the minority class. Many machine learning models tend to be biased towards the majority class because they aim to minimise overall error, often leading to poor performance on the minority class. This paper presents the balanced ensemble neural network, a novel solution to effectively address class imbalance in big data. Balanced ensemble neural network combines the robust capabilities of neural networks with the power of ensemble learning, incorporating class balancing strategies to ensure fair representation of minority classes. The methodology involves integrating multiple neural networks, each trained on balanced subsets of data using techniques like Synthetic Minority Over‐sampling Technique and Random Undersampling. This integration aims to leverage the strengths of individual networks while reducing their inherent biases. Our extensive experiments across various datasets reveal that BENN achieves an AUC‐ROC score of 0.94, surpassing other models such as random forest (0.88), support vector (0.84) and single neural net (0.80). It was also observed that BENN's performance is better compared to traditional neural network models and standard ensemble methods in key metrics like accuracy, precision, recall, F1‐score and AUC‐ROC. The results specifically highlight BENN's effectiveness in accurately classifying instances of minority classes, a notable challenge in many existing models. These findings underscore BENN's potential as a substantial advancement in handling class imbalance within big data environments, offering a promising direction for future research and application in machine learning.
Control risk premium: Dual‐class shares, family ownership, and minority investor returns
Authors: Anderson Ronald , Ottolenghi Ezgi , Reeb David , Savor Pavel 
Published: October 2024

AbstractDespite exhibiting significant valuation discounts, dual‐class shares surged from 1% of initial public offerings in 1980 to nearly half in recent years. This study investigates the potential harm of such structures by examining the identity and returns of minority shareholders. We find that sophisticated investors predominantly hold low‐voting shares. Furthermore, outside shareholders earn a positive risk premium rather than suffering low returns, consistent with the hypothesis that market prices compensate for the risk associated with dual‐class structures. Our analysis reveals that such structures are confounded with family control, which is present in 89% of dual‐class firms in the Russell 3000. Interestingly, single‐class firms with family shareholders also enjoy positive abnormal returns, implying minority shareholders care more about the presence of a controlling shareholder than a specific voting structure. This research contributes to the ongoing debate on restricting dual‐class structures by highlighting the complex relationship between ownership, control, and shareholder returns.