bluuebunny/crossref_metadata_2025_split huggingface dataset:
Engaging communities in therapeutics clinical research during pandemics: Experiences and lessons from the ACTIV COVID-19 therapeutics research initiative
Authors: Wohl David A. , Adam Stacey J. , Gibbs Kevin W. , Moskowitz Ari L. , Ortel Thomas L. , Singh Upinder , Jilg Nikolaus , Evering Teresa H. , Fischer William A. , Taiwo Babafemi O. , Daar Eric S. , Lindsell Christopher J. , Naggie Susanna , Rothman Russell L. , Dunsmore Sarah E. , McAdams M. Patricia , Vail Julia , Jayaweera Dushyantha 
Published: October 2024

Abstract
This manuscript addresses a critical topic: navigating complexities of conducting clinical trials during a pandemic. Central to this discussion is engaging communities to ensure diverse participation. The manuscript elucidates deliberate strategies employed to recruit minority communities with poor social drivers of health for participation in COVID-19 trials. The paper adopts a descriptive approach, eschewing analysis of data-driven efficacy of these efforts, and instead provides a comprehensive account of strategies utilized. The Accelerate COVID-19 Treatment Interventions and Vaccines (ACTIV) public–private partnership launched early in the COVID-19 pandemic to develop clinical trials to advance SARS-CoV-2 treatments. In this paper, ACTIV investigators share challenges in conducting research during an evolving pandemic and approaches selected to engage communities when traditional strategies were infeasible. Lessons from this experience include importance of community representatives’ involvement early in study design and implementation and integration of well-developed public outreach and communication strategies with trial launch. Centralization and coordination of outreach will allow for efficient use of resources and the sharing of best practices. Insights gleaned from the ACTIV program, as outlined in this paper, shed light on effective strategies for involving communities in treatment trials amidst rapidly evolving public health emergencies. This underscores critical importance of community engagement initiatives well in advance of the pandemic.
Return of individual research results to participants with and at risk for Parkinson’s disease
Authors: Lettenberger Samantha E. , Hartman Emily A. , Tam Kali , Auinger Peggy , Pawlik Meghan E. , Wilson Renee , Banda Elizabeth T. , Valdovinos Blanca , Kinel Daniel , Alcalay Roy N. , Dorsey E. Ray , Norcliffe-Kaufmann Lucy , Sharma Saloni , Holloway Robert G. , Schneider Ruth B. 
Published: October 2024

Abstract
In a prospective, remote natural history study of 277 individuals with (60) and genetically at risk for (217) Parkinson’s disease (PD), we examined interest in the return of individual research results (IRRs) and compared characteristics of those who opted for versus against the return of IRRs. Most (n = 180, 65%) requested sharing of IRRs with either a primary care provider, neurologist, or themselves. Among individuals without PD, those who requested sharing of IRRs with a clinician reported more motor symptoms than those who did not request any sharing (mean (SD) 2.2 (4.0) versus 0.7 (1.5)). Participant interest in the return of IRRs is strong.
Judicial Populism and Corruption Prosecutions in the Mani Pulite Operation
Authors: Manzi Lucia 
Published: October 2024

Abstract
I provide a new analytical framework to understand the effectiveness of corruption prosecutions in the so-called Mani Pulite (Clean Hands) operation by showing how this operation was rooted in a populist interpretation of criminal rules and criminal procedure. The Clean Hands operation represented a successful breakthrough against the vast and complex corruption system that had sustained Italian politics for decades. I show that prosecutors in the Clean Hands operation interpreted legal rules through the lens of a deep-seated hostility between a vague conglomerate of “corrupt elites” and “virtuous citizens.” This populist interpretation of criminal and procedural rules introduced significant legal innovations that empowered judicial actors against systemic corruption by creating unprecedented incentives for defendants to cooperate with legal authorities. Consequently, the judicial professionals leading the Clean Hands operation also felt the need to shield themselves against retaliation for the use of these novel approaches to corruption prosecution by bringing their fight before the court of public opinion. To this end, the Clean Hands prosecutors made use of targeted media interventions to rally public support around their investigation and protect their work from political interference.
Application of neural network for automatic symbol recognition in production of electronic navigation charts from paper charts
Authors: Gunathilaka Malavige Don Eranda Kanchana , Perera Amarasinghege Nihal Dinasiri , Weerasingha Pavithra Lakshan 
Published: October 2024

Abstract
This research boarded on a novel initiative to replace the error-prone and labour-intensive process of converting Paper Nautical Chart (PNC) symbols to Electronic Navigational Chart (ENC) symbols with a more efficient and automated manner using Artificial Intelligence (AI). The proposed method applies the Convolutional Neural Network and YOLOv5 model to recognise and convert symbols from PNC into their corresponding ENC formats. The model's competence was evaluated with performance metrics including Precision, Recall, Average Precision, and mean Average Precision. Among the different variations of the YOLOv5 models tested, the YOLOv5m version revealed the best performance achieving a mean Average Precision of 0 ⋅ 837 for all features. A confusion matrix was used to visualise the model's classification accuracy for various chart symbols, underlining strengths and identifying areas for improvements. While the model has demonstrated high ability in identifying symbols like ‘Obstruction’ and ‘Major/Minor Lights’, it exhibited lesser accuracy with ‘Visible Wreck’ and ‘Background’ categories. Further, the developed graphical user interface (GUI) allowed users to interact with the artificial neural network model without demanding detailed knowledge of the underlying programming or model architecture.
The Vibes Are Off: Did Elon Musk Push Academics Off Twitter?
Authors: Bisbee James , Munger Kevin 
Published: October 2024

ABSTRACTTwitter has been a prominent forum for academics communicating online, both among themselves and with policy makers and the broader public. Elon Musk’s takeover of the company brought sweeping changes to many aspects of the platform, including public access to its data; Twitter’s approach to censorship and mis/disinformation; and tweaks to the affordances of the platform. This article addresses a narrower empirical question: What did Elon Musk’s takeover of the platform mean for this academic ecosystem? Using a snowball sample of more than 15,700 academic accounts from the fields of economics, political science, sociology, and psychology, we show that academics in these fields reduced their “engagement” with the platform, measured by either the number of active accounts (i.e., those registering any behavior on a given day) or the number of tweets written (including original tweets, replies, retweets, and quote tweets). We further tested whether this decrease in engagement differed by account type; we found that verified users were significantly more likely to reduce their production of content (i.e., writing new tweets and quoting others’ tweets) but not their engagement with the platform writ large (i.e., retweeting and replying to others’ content).
Forecasting the 2024 Republican Presidential Nomination: Can the Former Heavyweight Champ Win Another Title Shot?
Authors: Dowdle Andrew J. , Adkins Randall E. , Sebold Karen , Steger Wayne P. 
Published: October 2024

ABSTRACT
Donald Trump’s bid for the 2024 Republican presidential nomination is unique in that no former president since Theodore Roosevelt in 1912 has sought the nomination of their political party, nor has a candidate sought the nomination while facing multiple criminal indictments. With data from previous nomination cycles, we use presidential nominations from 1980 to 2020 to create a forecast for the 2024 Republican primaries. The variables in the equations consist of data from the pre-primary period (e.g., money raised, cash reserves, elite endorsements, and polling results) and a second model with results of the Iowa caucuses and the New Hampshire primary to forecast the remaining primary vote. The models accurately predict Trump’s victory despite the unique nature of his candidacy.
The PollyVote Forecast for the 2024 US Presidential Election
Authors: Graefe Andreas 
Published: October 2024

ABSTRACT
Originally founded in 2004 to improve election forecasting accuracy through evidence-based methods, the PollyVote project applies the principle of combining forecasts to predict the outcome of US presidential elections. The 2024 forecast uses the same methodology as in previous elections by combining forecasts from four methods: polls, expectations, models, and naive forecasts. By averaging within and across these methods, PollyVote predicts a close race, giving Kamala Harris a slight edge over Donald Trump in both the two-party popular vote (50.8 vs. 49.2%) and the Electoral College (276 vs. 262 votes). The forecast gives Harris a 65% chance of winning the popular vote and a 56% chance of winning the Electoral College, making both outcomes toss-ups. Compared to the combined PollyVote, component forecasts that rely on trial-heat polls tend to favor Harris, whereas methods that rely on alternative measures are less optimistic about the Democratic candidate’s chances. The polls may be overestimating Harris’s lead.
Housing wealth and political outcomes: a multi-dimensional analysis at the local level in South Korea
Authors: Han Seungwoo 
Published: October 2024

AbstractThe current study explores the relationship between housing wealth and political outcomes at the regional level in South Korea, providing insights that extend beyond the scope of previous research, which has primarily concentrated on individual or macro levels. It focuses specifically on district-level dynamics within the unique context of South Korea to uncover the underlying mechanisms of housing politics. The findings indicate a clear trend: as the average price of apartments – a key indicator of housing wealth – rises in a district, there is an increased tendency for residents to support candidates from the conservative party. Furthermore, the data-driven analysis highlights the significance of housing wealth amidst various regional characteristic variables, particularly in its capacity to distinguish the target regions. By employing comprehensive data and a multi-dimensional analytical approach, this study unravels the intricate relationship between housing wealth and political outcomes within a regional context. In doing so, it greatly enhances our understanding of the impact of housing wealth on political outcomes, bridging the gap between individual behaviours and national trends, and underscoring the pivotal role of housing wealth in shaping regional political dynamics.
You Are Safe Here: Community Sponsorship Policy and Refugee Integration in the UK
Authors: Hassan Sara , Phillimore Jenny , D’Avino Gabriella 
Published: October 2024

Abstract
Globally, resettlement is considered one of the most durable solutions for refugees. The UK has introduced a Community Sponsorship Scheme that enables communities to resettle refugee families providing them with enhanced integration support aided by volunteers. This paper investigates the nature of integration support that sponsored refugees receive utilising the analytical framework of UK’s Indicators of Integration (IoI). Data was collected from interviews with refugee adults resettled in diverse and less diverse areas. Our findings illustrate the importance of support given by volunteer groups to enable access to resources and connections. We establish that there is much potential for sponsorship programmes to add value to refugee support suggesting that the current expansion of sponsorship from its Canadian roots may help facilitate refugee integration. However, further research is needed to uncover the long-term experiences of sponsored refugees and to compare their outcomes to those of forced migrants arriving via different mechanisms.
Highly DUV to NIR-II responsive broadband quantum dots heterojunction photodetectors by integrating quantum cutting luminescent concentrators
Authors: Ding Nan , Xu Wen , Liu Hailong , Jing Yuhan , Wang Zewen , Ji Yanan , Wu Jinlei , Shao Long , Zhu Ge , Dong Bin 
Published: October 2024

AbstractLow-cost, high-performance, and uncooled broadband photodetectors (PDs) have potential applications in optical communication etc., but it still remains a huge challenge to realize deep UV (DUV) to the second near-infrared (NIR-II) detection for a single broadband PD. Herein, a single PD affording broadband spectral response from 200 to 1700 nm is achieved with a vertical configuration based on quantum dots (QDs) heterojunction and quantum cutting luminescent concentrators (QC–LC). A broadband quantum dots heterojunction as absorption layer was designed by integrating CsPbI3:Ho3+ perovskite quantum dots (PQDs) and PbS QDs to realize the spectral response from 400 to 1700 nm. The QC–LC by employing CsPbCl3:Cr3+, Ce3+, Yb3+, Er3+ PQDs as luminescent conversion layer to collect and concentrate photon energy for boosting the DUV–UV (200–400 nm) photons response of PDs by waveguide effect. Such broadband PD displays good stability, and outstanding sensitivity with the detectivity of 3.19 × 1012 Jones at 260 nm, 1.05 × 1013 Jones at 460 nm and 2.23 × 1012 Jones at 1550 nm, respectively. The findings provide a new strategy to construct broadband detector, offering more opportunities in future optoelectronic devices.
USP7 depletion potentiates HIF2α degradation and inhibits clear cell renal cell carcinoma progression
Authors: Tu Rongfu , Ma Junpeng , Chen Yule , Kang Ye , Ren Doudou , Cai Zeqiong , Zhang Ru , Pan Yiwen , Liu Yijia , Da Yanyan , Xu Yao , Yu Yahuan , Wang Donghai , Wang Jingchao , Dong Yang , Lu Xinlan , Zhang Chengsheng 
Published: October 2024

AbstractClear cell renal cell carcinoma (ccRCC) is characterized by Von Hippel Lindau (VHL) gene loss of function mutation, which leads to the accumulation of hypoxia-inducible factor 2α (HIF2α). HIF2α has been well-established as one of the major oncogenic drivers of ccRCC, however, its therapeutic targeting remains a challenge. Through an analysis of proteomic data from ccRCCs and adjacent non-tumor tissues, we herein revealed that Ubiquitin-Specific Peptidase 7 (USP7) was upregulated in tumor tissues, and its depletion by inhibitors or shRNAs caused significant suppression of tumor progression in vitro and in vivo. Mechanistically, USP7 expression is activated by the transcription factors FUBP1 and FUBP3, and it promotes tumor progression mainly by deubiquitinating and stabilizing HIF2α. Moreover, the combination of USP7 inhibitors and afatinib (an ERBB family inhibitor) coordinately induce cell death and tumor suppression. In mechanism, afatinib indirectly inhibits USP7 transcription and accelerates the degradation of HIF2α protein, and the combination of them caused a more profound suppression of HIF2α abundance. These findings reveal a FUBPs-USP7-HIF2α regulatory axis that underlies the progression of ccRCC and provides a rationale for therapeutic targeting of oncogenic HIF2α via combinational treatment of USP7 inhibitor and afatinib.
Retinal detachment in Type IX collagen recessive Stickler syndrome
Authors: Maghsoudi Daniel , Nixon Thomas RW , Martin Howard , Richards Allan J , McNinch Annie M , Alexander Philip , Poulson Arabella V , Snead Martin P 
Published: October 2024

Abstract

Objective
Stickler Syndrome (SS) is associated with eye, joint and orofacial abnormalities. Most cases are dominantly inherited through COL2A1/COL11A1 variants encoding type-II/XI collagen, with patients having up to 78% retinal detachment (RD) risk. Rarer cases of recessive SS have also been identified, associated with pathogenic variants of genes including COL9A1, COL9A2 & COL9A3 encoding type-IX collagen, but there is limited published data on patients’ phenotype or RD risk. Our study aimed to investigate RD risk in type-IX recessive SS, determining whether patients would benefit from prophylactic retinopexy. A secondary objective was to explore patient phenotypes, identifying key features which clinicians should identify, leading to earlier diagnosis.

Methods
We report 13 cases from 11 families with Type-IX recessive SS, identified from the cohort attending the NHS England Highly Specialised Stickler Syndrome Service (1/1/15-31/12/22). Patients underwent multidisciplinary assessment by ophthalmology, rheumatology and audiology.

Results
6/11 families exhibited previously undescribed genetic variants, and 7 had consanguineous parents. Clinical findings included abnormal vitreous architecture and high myopia. 15.4% of patients developed RD secondary to horseshoe retinal tears, with no cases of bilateral RD or giant retinal tears (GRTs). No patients had cleft palate, and 30.8% had midfacial hypoplasia. Hearing loss was more prevalent (91.7%) than in dominant SS. Arthropathy was uncommon but variable in manifestation.

Conclusions
Ours results do not point to high RD nor GRT incidence in recessive SS, although given the rarity, our numbers are small. Prophylactic retinopexy should only be offered case-by-case for fellow eyes of patients presenting with GRT detachments in their first eye.
An automatic tracking method to measure the mandibula movement during real time MRI
Authors: Mouchoux Jérémy , Sojka Florian , Kauffmann Philipp , Dechent Peter , Meyer-Marcotty Philipp , Quast Anja 
Published: October 2024

AbstractMandibular movement is complex and individual due to variations in the temporomandibular joint (TMJ). Consequently, patient-centered dentistry should incorporate patients’ specific anatomy and condylar function in treatment planning. Real-time magnetic resonance imaging (rt-MRI) visualizes relevant structures and tracks mandibular movement. However, current assessments rely on qualitative observations or time-consuming manual tracking, lacking reliability. This study developed an automatic tracking algorithm for mandibular movement in rt-MRI using least mean square registration (LMS) and compared it to manual tracking (MT) during mouth opening. Ten participants with skeletal class I underwent rt-MRI (10 frames/s). The same operator tracked the condylar pathway for the two methods, setting 2000 landmarks (2 landmarks x100 frames x10 participants) for MT and 210 landmarks (3 landmarks x7 frames x10 participants) for LMS. Time required, superimposition error, and the distance between tracked condylar pathways were compared between methods. LMS tracking was 76% faster and showed significantly better superimposition (0.0289 ± 0.0058) than MT (0.059 ± 0.0145) (p = 0.002). During one-third of the movement, the pathways tracked by both methods were more than 1 mm and 1° apart. These findings highlight the benefits of automatic condylar movement tracking in rt-MRI, laying the groundwork for more objective and quantitative observation of TMJ function.
Association between uric acid and the risk of depressive symptoms in US adults: results from NHANES 2005–2018
Authors: Wang Jinhua , Yang Ming , Lin Haiyan , Wang Jiao 
Published: October 2024

Abstract
Background
This study explores the relationship between serum uric acid(UA) levels and depression. UA is the final product of purine metabolism in the human body, possessing certain physiological functions such as blood pressure regulation, antioxidation, DNA protection, and anti-aging, thereby drawing attention for its potential role in preventing and treating depression.

Methods
This cross-sectional study includes 32,424 participants aged ≥ 20 years from the National Health and Nutrition Examination Survey (NHANES) conducted between 2005 and 2018, generating a nationally representative database. Depressive symptoms were assessed using the Patient Health Questionnaire-9. Serum uric acid concentration was measured using the uricase-peroxidase coupled method, and participants were divided into quartiles of serum uric acid concentration. Weighted data were calculated according to analysis guidelines. The association between serum uric acid and depressive symptoms was analyzed using weighted multivariable logistic regression models and restricted cubic spline regression analyses. Subgroup analyses were also performed.

Results
Among 32,424 participants, 3,421 were defined as having depressive symptoms. The crude prevalence of depressive symptoms was 10.5% (weighted prevalence: 9.086% [95% confidence interval: 9.032–9.139%]). Compared with the first quartile, individuals with higher UA levels had a decreased risk of depressive symptoms by 9% (OR: 0.910, 95% CI: 0.797–10.40), 14.6% (OR: 0.854, 95% CI: 0.741–0.983), and 20.5% (OR: 7795, 95% CI: 0.680–0.930), respectively. Further restricted cubic spline regression analysis revealed a nonlinear association between UA and depressive symptoms, with an inflection point of 319.72 µmol/L. Subgroup multivariable weighted logistic regression analysis found that the association between UA and the risk of depressive symptoms remained consistent across all subgroups, demonstrating high stability and reliability.

Conclusion
This study emphasizes a significant nonlinear negative correlation between serum uric acid and depressive symptoms. This suggests that proper control of serum uric acid levels may play a role in preventing and treating depression.
Self-rated health in late adolescence as a predictor for mortality between 46 and 70 years of age
Authors: Andreasson Anna , Thern Emelie , Hemmingsson Tomas 
Published: October 2024

AbstractSelf-rated health is a common assessment used in epidemiological research and an independent predictor of morbidity and mortality. We investigate if a single measure of self-rated health in late adolescence predict mortality between 46 and 70 years of age. This study was based on 47 286 Swedish men that conscribed 1969–1970 at age 18–20 and that were still alive in 1997. Self-rated health and data on potential explanatory factors (psychological factors, health status markers and health behaviors) were collected at conscription. Adult socioeconomic position in 1990 was derived from registries. Death and cause of death (cancer, cardiovascular disease, violent and alcohol abuse related disorders) were derived from the Causes of Death Register between 1997 and 2019. Conscripts that rated their health as fair or poor/very poor had significantly higher hazard of all-cause mortality than conscript that rated their health as very good (HRfair = 1.27, 95%CI:1.18–1.37 and HRpoor = 1.25, 95%CI:1.11–1.41) and disease-specific mortality. Adjusting for all explanatory factors attenuated the risk estimates by 9–100%. In conclusion, poor self-rated health reported in late adolescence predicts all-cause and disease-specific mortality between the ages of 46 and 70 years. Psychological factors and health behaviors measured at conscription may serve as potential explanatory factors underlying the predictive ability of self-rated health in late adolescence.