bluuebunny/crossref_metadata_2025_split huggingface dataset:
Risk factor analysis and risk prediction study of obesity in steelworkers: model development based on an occupational health examination cohort dataset
Authors: Zhao Zekun , Lu Haipeng , Meng Rui , Si Zhikang , Wang Hui , Wang Xuelin , Chen Jiaqi , Zheng Yizhan , Wang Huan , Hu Jiaqi , Zhao Ziqi , Zhu Hongmin , Wu Jianhui , Li Xiaoming , Xue Ling 
Published: January 2024

Abstract
Background
Obesity is increasingly recognized as a grave public health concern globally. It is associated with prevalent diseases including coronary heart disease, fatty liver, type 2 diabetes, and dyslipidemia. Prior research has identified demographic, socioeconomic, lifestyle, and genetic factors as contributors to obesity. Nevertheless, the influence of occupational risk factors on obesity among workers remains under-explored. Investigating risk factors specific to steelworkers is crucial for early detection, prediction, and effective intervention, thereby safeguarding their health.

Methods
This research utilized a cohort study examining health impacts on workers in an iron and steel company in Hebei Province, China. The study involved 5469 participants. By univariate analysis, multifactor analysis, and review of relevant literature, predictor variables were found. Three predictive models—XG Boost, Support Vector Machine (SVM), and Random Forest (RF)—were employed.

Results
Univariate analysis and cox proportional hazard regression modeling identified age, gender, smoking and drinking habits, dietary score, physical activity, shift work, exposure to high temperatures, occupational stress, and carbon monoxide exposure as key factors in the development of obesity in steelworkers. Test results indicated accuracies of 0.819, 0.868, and 0.872 for XG Boost, SVM, and RF respectively. Precision rates were 0.571, 0.696, and 0.765, while recall rates were 0.333, 0.592, and 0.481. The models achieved AUCs of 0.849, 0.908, and 0.912, with Brier scores of 0.128, 0.105, and 0.104, log losses of 0.409, 0.349, and 0.345, and calibration-in-the-large of 0.058, 0.054, and 0.051, respectively. Among these, the Random Forest model demonstrated superior performance.

Conclusions
The research indicates that obesity in steelworkers results from a combination of occupational and lifestyle factors. Of the models tested, the Random Forest model exhibited superior predictive ability, highlighting its significant practical application.
Planning, implementing and governing systems-based co-creation: the DISCOVER framework
Authors: Smith Niamh , Georgiou Michail , Jalali Mohammad S. , Chastin Sebastien 
Published: January 2024

Abstract
Background
Increasingly, public health faces challenges requiring complex, multifaceted and multi-sectoral responses. This calls for systems-based approaches that facilitate the kind of collective and collaborative thinking and working required to address complexity. While the literature on systems thinking, system dynamics and the associated methodologies is extensive, there remains little clear guidance on how to plan, govern and implement participatory systems approaches within a co-creation process.

Methods
We used a three-step process to develop DISCOVER, a framework for implementing, and governing systems-based co-creation:

Stage 1: We conducted a literature analysis of key texts to identify well-documented methods and phases for co-creation using a systems approach, as well as areas where gaps existed.

Stage 2: We looked for the most appropriate methods and approaches to fill the gaps in the knowledge production chain.

Stage 3: We developed the framework, identifying how the different tools and approaches fit together end-to-end, from sampling and recruiting participants all the way through to responding with an action plan.

Results
We devised DISCOVER to help guide researchers and stakeholders to collectively respond to complex social, health and wider problems. DISCOVER is a strategic research planning and governance framework that provides an actionable, systematic way to conceptualise complex problems and move from evidence to action, using systems approaches and co-creation. In this article, we introduce the eight-step framework and provide an illustrative case study showcasing its potential. The framework integrates complementary approaches and methods from social network analysis, systems thinking and co-creation literature. The eight steps are followed sequentially but can overlap.

Conclusions
DISCOVER increases rigour and transparency in system approaches to tackling complex issues going from planning to action. It is being piloted in environmental health research but may be suitable to address other complex challenges and could be incorporated into research proposals and protocols for future projects.
Trajectories of physical activity from mid to older age in women: 21 years of data from the Australian Longitudinal Study on Women’s Health
Authors: Nemoto Yuta , Brown Wendy J. , Mielke Gregore Iven 
Published: January 2024

Abstract
Background
Women’s physical activity varies across the adult lifespan. However, changes in physical activity among mid-aged women are not well understood. We analysed 21 years of data from women born in 1946–51 to identify: (1) trajectories of physical activity in the transition from mid- to old-age and (2) determinants of different physical activity trajectories.

Methods
Data were from the 1946–51 cohort of the Australian Longitudinal Study on Women’s Health (N = 10,371). Surveys were mailed at three-year intervals from 1998 (age 47–52) to 2019 (age 68–73) to collect data on physical activity, sociodemographic factors (country of birth, area of residence, educational attainment, marital status, income management, paid work hours, living with children age < 18, providing care), health indicators (menopause status, BMI, physical and mental health, chronic conditions), and health behaviours (smoking, alcohol status). Group-based trajectory modelling was used to identify trajectories of physical activity. Multinomial logistic regression models were used to examine the determinants of physical activity trajectories.

Results
Five trajectories were identified: Low-stable (13.3% of participants), Moderate-stable (50.4%), Moderate-increasing (22.2%), High-declining (7.7%), and High-stable (6.6%). Sociodemographic characteristics (area of residence, education, income management, living with children, and providing care) were determinants of physical activity trajectories, but the strongest factors were BMI, physical and mental health. Women who were overweight/obese and had poor physical and mental health were less likely to be in the High-stable group than in any other group. Changes in these variables (increasing BMI, and declining physical and mental health) and in marital status (getting married) were positively associated with being in trajectories other than the High-stable group.

Conclusions
Although most women maintained physical activity at or above current guidelines, very low physical activity levels in the Low-stable group, and declining levels in the High-declining group are concerning. The data suggest that physical activity promotion strategies could be targeted to these groups, which are characterised by socioeconomic disadvantage, high (and increasing) BMI, and poor (and worsening) physical and mental health. Removing barriers to physical activity in these women, and increasing opportunities for activity, may reduce chronic disease risk in older age.
The microRNA-211-5p/P2RX7/ERK/GPX4 axis regulates epilepsy-associated neuronal ferroptosis and oxidative stress
Authors: Li Xueying , Quan Pusheng , Si Yao , Liu Fei , Fan Yuwei , Ding Feifan , Sun Lina , Liu Han , Huang Shuo , Sun Linlin , Yang Fan , Yao Lifen 
Published: January 2024

AbstractFerroptosis is an iron-dependent cell death mechanism involving the accumulation of lipid peroxides. As a critical regulator, glutathione peroxidase 4 (GPX4) has been demonstrated to be downregulated in epilepsy. However, the mechanism of ferroptosis in epilepsy remains unclear. In this study, bioinformatics analysis, analysis of epilepsy patient blood samples and cell and mouse experiments revealed strong associations among epilepsy, ferroptosis, microRNA-211-5p and purinergic receptor P2X 7 (P2RX7). P2RX7 is a nonselective ligand-gated homotrimeric cation channel, and its activation mainly increases neuronal activity during epileptic seizures. In our study, the upregulation of P2RX7 in epilepsy was attributed to the downregulation of microRNA (miR)-211-5p. Furthermore, P2RX7 has been found to regulate GPX4/HO-1 by alleviating lipid peroxidation induced by suppression of the MAPK/ERK signaling pathway in murine models. The dynamic decrease in miR-211-5p expression induces hypersynchronization and both nonconvulsive and convulsive seizures, and forebrain miR-211-5p suppression exacerbates long-lasting pentylenetetrazole-induced seizures. Additionally, in this study, induction of miR-211-5p expression or genetic-silencing of P2RX7 significantly reduced the seizure score and duration in murine models through the abovementioned pathways. These results suggest that the miR-211-5p/P2RX7 axis is a novel target for suppressing both ferroptosis and epilepsy.
Comparison of deep learning networks for fully automated head and neck tumor delineation on multi-centric PET/CT images
Authors: Wang Yiling , Lombardo Elia , Huang Lili , Avanzo Michele , Fanetti Giuseppe , Franchin Giovanni , Zschaeck Sebastian , Weingärtner Julian , Belka Claus , Riboldi Marco , Kurz Christopher , Landry Guillaume 
Published: January 2024

Abstract
Objectives
Deep learning-based auto-segmentation of head and neck cancer (HNC) tumors is expected to have better reproducibility than manual delineation. Positron emission tomography (PET) and computed tomography (CT) are commonly used in tumor segmentation. However, current methods still face challenges in handling whole-body scans where a manual selection of a bounding box may be required. Moreover, different institutions might still apply different guidelines for tumor delineation. This study aimed at exploring the auto-localization and segmentation of HNC tumors from entire PET/CT scans and investigating the transferability of trained baseline models to external real world cohorts.

Methods
We employed 2D Retina Unet to find HNC tumors from whole-body PET/CT and utilized a regular Unet to segment the union of the tumor and involved lymph nodes. In comparison, 2D/3D Retina Unets were also implemented to localize and segment the same target in an end-to-end manner. The segmentation performance was evaluated via Dice similarity coefficient (DSC) and Hausdorff distance 95th percentile (HD95). Delineated PET/CT scans from the HECKTOR challenge were used to train the baseline models by 5-fold cross-validation. Another 271 delineated PET/CTs from three different institutions (MAASTRO, CRO, BERLIN) were used for external testing. Finally, facility-specific transfer learning was applied to investigate the improvement of segmentation performance against baseline models.

Results
Encouraging localization results were observed, achieving a maximum omnidirectional tumor center difference lower than 6.8 cm for external testing. The three baseline models yielded similar averaged cross-validation (CV) results with a DSC in a range of 0.71–0.75, while the averaged CV HD95 was 8.6, 10.7 and 9.8 mm for the regular Unet, 2D and 3D Retina Unets, respectively. More than a 10% drop in DSC and a 40% increase in HD95 were observed if the baseline models were tested on the three external cohorts directly. After the facility-specific training, an improvement in external testing was observed for all models. The regular Unet had the best DSC (0.70) for the MAASTRO cohort, and the best HD95 (7.8 and 7.9 mm) in the MAASTRO and CRO cohorts. The 2D Retina Unet had the best DSC (0.76 and 0.67) for the CRO and BERLIN cohorts, and the best HD95 (12.4 mm) for the BERLIN cohort.

Conclusion
The regular Unet outperformed the other two baseline models in CV and most external testing cohorts. Facility-specific transfer learning can potentially improve HNC segmentation performance for individual institutions, where the 2D Retina Unets could achieve comparable or even better results than the regular Unet.
Dollo-CDP: a polynomial-time algorithm for the clade-constrained large Dollo parsimony problem
Authors: Dai Junyan , Rubel Tobias , Han Yunheng , Molloy Erin K. 
Published: January 2024

AbstractThe last decade of phylogenetics has seen the development of many methods that leverage constraints plus dynamic programming. The goal of this algorithmic technique is to produce a phylogeny that is optimal with respect to some objective function and that lies within a constrained version of tree space. The popular species tree estimation method ASTRAL, for example, returns a tree that (1) maximizes the quartet score computed with respect to the input gene trees and that (2) draws its branches (bipartitions) from the input constraint set. This technique has yet to be used for parsimony problems where the input are binary characters, sometimes with missing values. Here, we introduce the clade-constrained character parsimony problem and present an algorithm that solves this problem for the Dollo criterion score in $$O(|\Sigma |^{3.726}(n+k) + |\Sigma |^{1.726}nk)$$

O
(
|
Σ

|

3.726

(
n
+
k
)

+
|
Σ

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time, where n is the number of leaves, k is the number of characters, and $$\Sigma$$
Σ
is the set of clades used as constraints. Dollo parsimony, which requires traits/mutations to be gained at most once but allows them to be lost any number of times, is widely used for tumor phylogenetics as well as species phylogenetics, for example analyses of low-homoplasy retroelement insertions across the vertebrate tree of life. This motivated us to implement our algorithm in a software package, called Dollo-CDP, and evaluate its utility for analyzing retroelement insertion presence / absence patterns for bats, birds, toothed whales as well as simulated data. Our results show that Dollo-CDP can improve upon heuristic search from a single starting tree, often recovering a better scoring tree. Moreover, Dollo-CDP scales to data sets with much larger numbers of taxa than branch-and-bound while still having an optimality guarantee, albeit a more restricted one. Lastly, we show that our algorithm for Dollo parsimony can easily be adapted to Camin-Sokal parsimony but not Fitch parsimony.
The Association of Agent Orange Exposure with the progression of monoclonal gammopathy of undetermined significance to multiple myeloma: a population-based study of Vietnam War Era Veterans
Authors: Liu Lawrence W. , Wang Mei , Grandhi Nikhil , Schroeder Mark A. , Thomas Theodore , Vargo Kristin , Gao Feng , Sanfilippo Kristen M. , Chang Su-Hsin 
Published: January 2024

AbstractHerbicide and pesticide exposure [e.g., agent orange (AO)] is associated with an increased risk of multiple myeloma (MM) due to the contaminant, 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). However, it is unclear whether TCDD/AO exposure (AO exposure hereafter) increases the risk of progression of monoclonal gammopathy of undetermined significance (MGUS) to MM. We sought to evaluate the association in a nationwide study of US Veterans. A natural language processing algorithm was used to confirm MGUS and progression to MM. We included Veterans who were diagnosed with MGUS from 10/1/1999 to 12/31/2021 and served during the Vietnam War Era from 1/9/1962 to 5/7/1975. AO exposure was stratified according to three TCDD exposure levels: high (1/9/1962–11/30/1965), medium (12/1/1965–12/31/1970), or low (1/1/1971–5/7/1975). The association between AO exposure and progression was analyzed using multivariable Fine-Gray subdistribution hazard model with death as a competing event. The analytic cohort included 10,847 Veterans with MGUS, of whom 26.3% had AO exposure and 7.4% progressed to MM over a median follow-up of 5.2 years. In multivariable analysis, high exposure was associated with an increased progression rate (multivariable-adjusted hazard ratio 1.48; 95% confidence interval 1.02–2.16), compared to Veterans with no exposure. This information is critical to inform progression risk in patients diagnosed with MGUS and prior AO exposure. It is also applicable to MGUS patients with occupational TCDD exposure from herbicides and pesticides.
Nutritional treatment of children 6–59 months with severely low weight-for-age z-score: a study protocol for a 3-arm randomized controlled trial
Authors: Kangas Suvi T. , Ouédraogo Césaire T. , Tounkara Moctar , Ouoluoguem Bareye , Coulibaly Issa Niamanto , Haidara Alhousseyni , Diarra Niele Hawa , Diassana Koniba , Tausanovitch Zachary , Ritz Christian , Wells Jonathan C. , Briend André , Myatt Mark , Radin Elizabeth , Bailey Jeanette 
Published: January 2024

Abstract
Background
Admission criteria that treat children with low mid-upper-arm circumference (MUAC), and low weight-for-height z-score (WHZ) are not aligned with the evidence on which children are at risk of mortality. An analysis of community-based cohort data from Senegal found that a combination of weight-for-age (WAZ) and MUAC criteria identified all children at risk of near-term death associated with severe anthropometric deficits. This study will address whether children with WAZ <−3 but MUAC ≥125 mm benefit from therapeutic feeding with ready-to-use therapeutic foods (RUTF) and whether a simplified protocol is non-inferior to the weight-based standard protocol.

Methods
This is a prospective individually randomized controlled 3-arm trial conducted in the Nara health district in Mali. Children aged 6–59 months presenting with MUAC ≥125 mm and WAZ <−3 will be randomized to (1) control group receiving no treatment, (2) simplified treatment receiving 1 sachet of RUTF daily until WAZ ≥−3 for 2 visits, (3) standard treatment receiving RUTF according to WHZ category: (a) WHZ <−3 receive 200 kcal/kg/day until WHZ ≥−2 for 2 visits, (b) WHZ ≥−3 but <−2 receive 1 sachet daily until WHZ ≥−2 for 2 visits or (c) WHZ ≥−2 receive no treatment. All children will be followed up first fortnightly for 12 weeks and then monthly until 6 months post-enrolment. The primary endpoint will be measured at 2 months with the primary outcome being WAZ as a continuous measure. Other outcomes include other anthropometric measurements and a secondary endpoint will be observed at 6 months. A total of 1397 children will be recruited including 209 in the control and 594 in both the simplified and standard arms. The sample size should enable us to conclude on the superiority of the simplified treatment compared to no treatment and on the non-inferiority of the simplified treatment versus standard treatment with a margin of non-inferiority of 0.2 WAZ.

Discussion
This trial aims to generate new evidence on the benefit of treating children with WAZ <−3 but MUAC ≥125 mm in order to guide the choice of admission criteria to malnutrition treatment and build evidence on the most efficient treatment protocol.

Trial registration
This trial was registered at ClinicalTrials.gov: NCT05248516 on February 21, 2022.
Two protocols using fluralaner for Rhipicephalus microplus strategic control on taurine cattle in a tropical region
Authors: de Aquino Lidia Mendes , Zapa Dina Maria Beltran , de Castro Rodrigues Daniel , Strydom Tom , Torres Siddhartha , Ferreira Lorena Lopes , Barufi Francisco , de Amaral Heitor Oliveira Arriero , de Borges Fernando de Almeida , Gallina Tiago , de Mendonça Rafael Paranhos , Soares Vando Edésio , Monteiro Caio Marcio Oliveira , Lopes Welber Daniel Zanetti 
Published: January 2024

Abstract
Background
The present study aimed to evaluate the effects of different treatment strategies using a new commercial formulation containing pour-on fluralaner on Rhipicephalus microplus infestation in cattle and in pastures in a tropical climate region where up to five generations of this tick species can occur per year.

Methods
Forty-five naturally infested cattle were divided into three experimental groups: T01, treated with fluralaner (2.5 mg/kg) pour-on every 42 days; T02, the cattle received the first treatment with fluralaner on Day 0 but the next treatment involved a weekly visual evaluation; T03, control, received palliative treatment with a spray formulation when the group mean was ≥ 30 ticks. Counts of female R. microplus were performed weekly until day 343, and larval counts on pasture were performed on Days 0, 30, and 60 and every 30 days until Day 330.

Results
Using fluralaner, six applications were performed in Group T01, and four were performed in Group T02. In the control group (T03), it was necessary to perform eight palliative acaricide treatments with the spray formulation. The animals in T01 and T02 showed lower mean tick counts (p ≤ 0.05) than the control group (T03) on 28 and 27 of the 49 evaluated dates, respectively. In the paddock where the animals were kept as controls, the R. microplus larvae counts increased to 1458. In the paddocks where the animals were treated with fluralaner, the number was ≤ 19 per paddock during the study.

Conclusions
The different strategic treatment protocols performed with pour-on fluralaner (2.5 mg/kg) over a year in taurine cattle in a tropical region with a history of up to five annual generations of cattle ticks were effective, maintaining levels of R. microplus infestations in animals and in pastures close to zero in most of the study. Depending on the retreatment criterion adopted, the number of applications per year may be lower, resulting in a reduction in the mean cost of acaricide treatment per year and lower exposure of R. microplus populations to the active ingredient, resulting in lower resistance and selection pressure.

Graphical Abstract
Replacement of fluoroscopy by ultrasonography in the evaluation of hemidiaphragm function, an exploratory prospective study
Authors: Skaarup Søren Helbo , Juhl-Olsen Peter , Grundahl Anne Sofie , Løgstrup Brian Bridal 
Published: January 2024

Abstract
Introduction
Dysfunction of the diaphragm may ultimately lead to respiratory insufficiency and compromise patient outcome. Evaluation of diaphragm function is cumbersome. Fluoroscopy has been the gold standard to measure diaphragmatic excursion. Ultrasonography can visualize diaphragm excursion and holds many advantages such as no radiation exposure, increased portability and accessibility. However, correlation between fluoroscopy and ultrasonography has never been studied. We aimed to compare fluoroscopic and ultrasound measures of diaphragm excursion to determine if ultrasonography can replace fluoroscopy.

Methods
We performed ultrasound and fluoroscopy simultaneously during sniff inspiration and at total inspiratory capacity in patients with chronic obstructive pulmonary disease, heart failure and in healthy volunteers. Cranio-caudal excursion was measured by fluoroscopy and compared directly to M-mode excursion, B-mode excursion, area change, resting thickness, thickening fraction and contraction velocity measured by ultrasonography.

Results
Forty-two participants were included. The Pearson correlation between M-mode and fluoroscopy excursion was 0.61. The slope was 0.9 (90%CI 0.76–1.04) in a regression analysis. Using the Bland–Altman method, the bias was − 0.39 cm (95% CI − 1.04–0.26), p = 0.24. The Pearson correlation between fluoroscopy and B-mode and area change ultrasonography was high; low for thickness and fraction. All correlations were lower during sniff inspiration compared with inspiratory capacity breathing.

Conclusion
Ultrasonography has an acceptable correlation and bias compared to fluoroscopy and can thus be used as the primary tool to evaluate diaphragm excursion.