bluuebunny/crossref_metadata_2025 huggingface dataset:
Students’ perception of the educational environment at King Saud bin Abdulaziz University for health sciences using DREEM tool
Authors: Awawdeh Mohammed , Alosail Lama A. , Alqahtani Maram , Almotairi Afrah , Almikhem Rahaf N. , Alahmadi Rahaf A. , Aldughaither Aida A. , Alamoud Khalid A.
Published: January 2024

Background

Students’ learning results are influenced by the educational environment. The best learning environment is created when students are involved in the evaluation process of their education. The purpose of this study was to evaluate students’ perceptions of their learning environment at King Saud bin Abdulaziz University for Health Sciences (KSAU-HS) in Riyadh using the Dundee Ready Education Environment Measure (DREEM) instrument.

Methods

This observational cross-sectional study was conducted through an online questionnaire using the Arabic version of the DREEM tool. Students from six colleges at KSAU-HS Riyadh campus were asked to complete the questionnaire through emails. The study was carried out between November 2021 and April 2022. Descriptive statistics and inferential statistics were performed for DREEM as both a continuous (two-way ANOVA test) and categorical variable (Chi-squared and Monte-Carlo test).

Results

A total of 370 students completed the questionnaire. The overall DREEM score for the study was 125.88/200, with a standard deviation of 58.79. SSP items received the highest scores, while SAP items earned the lowest scores. The college and the academic level showed statistically significant differences in the DREEM overall score and the five subscales, whereas gender showed no significant difference. The college of pharmacy scored the highest total DREEM score (140.35 ± 27.75), and scored higher among the five subscales than both colleges of dentistry (114.13 ± 29.74) and medicine (113.87 ± 33.03). Students in their third year had the greatest overall DREEM score (132.23 ± 29.76), and scored higher in SPL, SPA and SSP compared to students in their sixth year, in which the total DREEM score was (111.65 ± 27.58).

Conclusions

Students of KSAU-HS generally perceived the educational environment as having more positive than negative. The educational level and college differed significantly in the overall DREEM score and the five subscales. Junior students had better perception of the educational environment and they differed significantly in the SPL and SPA subscales. The faculty of pharmacy had higher scores in the overall DREEM and the five subsequent scales than colleges of dentistry and medicine. Further research is needed in order to optimize the educational environment by investigating different solutions.
A command centre implementation before and during the COVID-19 pandemic in a community hospital
Authors: Grosman-Rimon Liza , Wegier Pete , Rodriguez Ruben , Casey Jane , Tory Susan , Solanki Jhanvi , Collins Barbara E.
Published: January 2024

Introduction

The objective of the study was to assess the effects of high-reliability system by implementing a command centre (CC) on clinical outcomes in a community hospital before and during COVID-19 pandemic from the year 2016 to 2021.

Methods

A descriptive, retrospective study was conducted at an acute care community hospital. The administrative data included monthly average admissions, intensive care unit (ICU) admissions, average length of stay, total ICU length of stay, and in-hospital mortality. In-hospital acquired events were recorded and defined as one of the following: cardiac arrest, cerebral infarction, respiratory arrest, or sepsis after hospital admissions. A subgroup statistical analysis of patients with in-hospital acquired events was performed. In addition, a subgroup statistical analysis was performed for the department of medicine.

Results

The rates of in-hospital acquired events and in-hospital mortality among all admitted patients did not change significantly throughout the years 2016 to 2021. In the subgroup of patients with in-hospital acquired events, the in-hospital mortality rate also did not change during the years of the study, despite the increase in the ICU admissions during the COVID-19 pandemic.Although the in-hospital mortality rate did not increase for all admitted patients, the in-hospital mortality rate increased in the department of medicine.

Conclusion

Implementation of CC and centralized management systems has the potential to improve quality of care by supporting early identification and real-time management of patients at risk of harm and clinical deterioration, including COVID-19 patients.
Artificial intelligence performance in detecting lymphoma from medical imaging: a systematic review and meta-analysis
Authors: Bai Anying , Si Mingyu , Xue Peng , Qu Yimin , Jiang Yu
Published: January 2024

Background

Accurate diagnosis and early treatment are essential in the fight against lymphatic cancer. The application of artificial intelligence (AI) in the field of medical imaging shows great potential, but the diagnostic accuracy of lymphoma is unclear. This study was done to systematically review and meta-analyse researches concerning the diagnostic performance of AI in detecting lymphoma using medical imaging for the first time.

Methods

Searches were conducted in Medline, Embase, IEEE and Cochrane up to December 2023. Data extraction and assessment of the included study quality were independently conducted by two investigators. Studies that reported the diagnostic performance of an AI model/s for the early detection of lymphoma using medical imaging were included in the systemic review. We extracted the binary diagnostic accuracy data to obtain the outcomes of interest: sensitivity (SE), specificity (SP), and Area Under the Curve (AUC). The study was registered with the PROSPERO, CRD42022383386.

Results

Thirty studies were included in the systematic review, sixteen of which were meta-analyzed with a pooled sensitivity of 87% (95%CI 83–91%), specificity of 94% (92–96%), and AUC of 97% (95–98%). Satisfactory diagnostic performance was observed in subgroup analyses based on algorithms types (machine learning versus deep learning, and whether transfer learning was applied), sample size (≤ 200 or >  200), clinicians versus AI models and geographical distribution of institutions (Asia versus non-Asia).

Conclusions

Even if possible overestimation and further studies with a better standards for application of AI algorithms in lymphoma detection are needed, we suggest the AI may be useful in lymphoma diagnosis.
Benefits and challenges experienced by participants on long-term methadone maintenance treatment in China: a qualitative study
Authors: Tang Xijia , Xiong Wenxue , Chen Wen , Wang Chijie , Wang Hexuan , Li Boyu , Zhang Zirong , Ling Li
Published: January 2024

Background

Methadone maintenance treatment (MMT) has been implemented in China for nearly two decades, with a significant decrease in the number of participants in recent years. However, there is a lack of comprehensive research focusing on the long-term effectiveness in the context of this decline, especially from the perspectives of MMT participants themselves. This study aims to address this gap by examining the benefits and challenges experienced by long-term MMT participants in China, to uncover potential causes of the decrease in participant numbers and to improve the effectiveness of the program.

Methods

We conducted semi-structured interviews with 21 long-term MMT participants (treatment duration ≥ 5 years) recruited through purposive sampling from 6 MMT clinics in the Guangdong Province, China, between December 2021 and August 2022. Thematic analysis was employed to analyze the transcribed interviews. Two analysts independently coded the data, and a third researcher double-coded 20% of transcripts to ensure intercoder reliability.

Results

Overall, participants corroborated the notable decline in MMT participants during their long-term MMT, citing death, arrest, and self-perceived abstinence from heroin, as their perceived driving factors. They reported positive changes in their health, family relationships, and social functioning. However, they identified economic hardship as their greatest challenge associated with MMT, further exacerbated by other barriers including the conflict of clinic opening hours and working schedules, discrimination from employers, and COVID-19-related restrictions. Additionally, participants identified issues with dose adjustment and emergency treatment continuation.

Conclusions

This study outlines the overall improvement in the quality of life of long-term MMT participants. However, it highlights the need for official guidelines for dose adjustment and emergency treatment continuation as well as the provision of health education, job referrals, and flexibility of clinic opening times to facilitate the return to society receiving participants. Establishing a follow-up mechanism for those receiving MMT is also recommended to prevent relapses to heroin and other illicit substances.
Human lifespan and sex-specific patterns of resilience to disease: a retrospective population-wide cohort study
Authors: Sol Joaquim , Ortega-Bravo Marta , Portero-Otín Manuel , Piñol-Ripoll Gerard , Ribas-Ripoll Vicent , Artigues-Barberà Eva , Butí Miquel , Pamplona Reinald , Jové Mariona
Published: January 2024

Background

Slower paces of aging are related to lower risk of developing diseases and premature death. Therefore, the greatest challenge of modern societies is to ensure that the increase in lifespan is accompanied by an increase in health span. To better understand the differences in human lifespan, new insight concerning the relationship between lifespan and the age of onset of diseases, and the ability to avoid them is needed. We aimed to comprehensively study, at a population-wide level, the sex-specific disease patterns associated with human lifespan.

Methods

Observational data from the SIDIAP database of a cohort of 482,058 individuals that died in Catalonia (Spain) at ages over 50 years old between the 1st of January 2006 and the 30th of June 2022 were included. The time to the onset of the first disease in multiple organ systems, the prevalence of escapers, the percentage of life free of disease, and their relationship with lifespan were evaluated considering sex-specific traits.

Results

In the study cohort, 50.4% of the participants were women and the mean lifespan was 83 years. The results show novel relationships between the age of onset of disease, health span, and lifespan. The key findings include: Firstly, the onset of both single and multisystem diseases is progressively delayed as lifespan increases. Secondly, the prevalence of escapers is lower in lifespans around life expectancy. Thirdly, the number of disease-free systems decreases until individuals reach lifespans around 87–88 years old, at which point it starts to increase. Furthermore, long-lived women are less susceptible to multisystem diseases. The associations between health span and lifespan are system-dependent, and disease onset and the percentage of life spent free of disease at the time of death contribute to explaining lifespan variability. Lastly, the study highlights significant system-specific disparities between women and men.

Conclusions

Health interventions focused on delaying aging and age-related diseases should be the most effective in increasing not only lifespan but also health span. The findings of this research highlight the relevance of Electronic Health Records in studying the aging process and open up new possibilities in age-related disease prevention that should assist primary care professionals in devising individualized care and treatment plans.
Single-cell RNA sequencing in donor and end-stage heart failure patients identifies NLRP3 as a therapeutic target for arrhythmogenic right ventricular cardiomyopathy
Authors: Fu Mengxia , Hua Xiumeng , Shu Songren , Xu Xinjie , Zhang Hang , Peng Zhiming , Mo Han , Liu Yanyun , Chen Xiao , Yang Yicheng , Zhang Ningning , Wang Xiaohu , Liu Zirui , Yue Guangxin , Hu Shengshou , Song Jiangping
Published: January 2024

Background

Dilation may be the first right ventricular change and accelerates the progression of threatening ventricular tachyarrhythmias and heart failure for patients with arrhythmogenic right ventricular cardiomyopathy (ARVC), but the treatment for right ventricular dilation remains limited.

Methods

Single-cell RNA sequencing (scRNA-seq) of blood and biventricular myocardium from 8 study participants was performed, including 6 end-stage heart failure patients with ARVC and 2 normal controls. ScRNA-seq data was then deeply analyzed, including cluster annotation, cellular proportion calculation, and characterization of cellular developmental trajectories and interactions. An integrative analysis of our single-cell data and published genome-wide association study-based data provided insights into the cell-specific contributions to the cardiac arrhythmia phenotype of ARVC. Desmoglein 2 (Dsg2)mut/mut mice were used as the ARVC model to verify the therapeutic effects of pharmacological intervention on identified cellular cluster.

Results

Right ventricle of ARVC was enriched of CCL3+ proinflammatory macrophages and TNMD+ fibroblasts. Fibroblasts were preferentially affected in ARVC and perturbations associated with ARVC overlap with those reside in genetic variants associated with cardiac arrhythmia. Proinflammatory macrophages strongly interact with fibroblast. Pharmacological inhibition of Nod-like receptor protein 3 (NLRP3), a transcriptional factor predominantly expressed by the CCL3+ proinflammatory macrophages and several other myeloid subclusters, could significantly alleviate right ventricular dilation and dysfunction in Dsg2mut/mut mice (an ARVC mouse model).

Conclusions

This study provided a comprehensive analysis of the lineage-specific changes in the blood and myocardium from ARVC patients at a single-cell resolution. Pharmacological inhibition of NLRP3 could prevent right ventricular dilation and dysfunction of mice with ARVC.
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

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

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

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

Ferroptosis 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

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

The 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 $$O(|\Sigma |^{3.726}(n+k) + |\Sigma |^{1.726}nk)$$

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(
|
Σ

|

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)

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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

Herbicide 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

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

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

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.
Co-creating holistic injury prevention training for youth handball: Development of an intervention targeting end-users at the individual, team, and organizational levels
Authors: Ageberg Eva , Bunke Sofia , Linnéll Jennie , Moesch Karin
Published: January 2024

Background

Interventions that are co-created with end-users, and that are informed by behavior change or implementation theories, support implementation in real world settings. However, injury prevention programs for youth athletes have typically been developed by experts with no, or insufficiently described, end-user involvement and without guidance by theories. The aim of the current study was to describe the development of a holistic injury prevention intervention for youth handball targeting end-users at different levels, through using knowledge from end-users and researchers/experts and applying relevant behavior change and implementation theories.

Methods

Knowledge from researchers/experts (sports medicine, sport psychology, handball, physical therapy, strength and conditioning (n = 14)) and end-users (coaches, players, club administrators, n = 16), and applying relevant implementation (Consolidated Framework for Implementation Research, CFIR), behavior change (Health Action Process Approach, HAPA) and motivational (Self-Determination Theory, SDT) theories, were used to co-design the intervention. Early end-users (coaches (n = 6), players (n = 3) and a club administrator (n = 1)) were interviewed for initial feedback.

Results

The intervention consisted of end-user-targeted information and training that was made available in a specifically developed interactive mobile application with modules for players, coaches, club administrators, and caregivers. Information for all end-users included benefits and principles of physical and psychological injury prevention training, load-management, motivation, and communication. Information about implementation was developed for club administrators specifically. For coaches, training to do with their teams included handball-specific injury prevention exercises (legs, shoulders, core) combined with psychological aspects (motivation, task focus, body awareness) to integrate within warm-up and handball skills training. Training for players included handball-specific multi-joint strength, power, and explosive exercises (legs, shoulders, core) and sport psychology exercises (self-awareness, relaxation, being in the present moment, prevent and handle stress). To support self-management, adoption, and motivation, programs were provided, and players and coaches could change, add, progress the difficulty of exercises, and build their own programs. Initial feedback from early end-users was generally positive.

Conclusions

Utilizing an approach where researchers/experts and end-users co-created injury prevention training specifically for youth handball, an intervention was generated that included information and holistic training targeting end-users at the individual (players, caregivers), team (coaches), and organizational (club administrators) levels.
Ultrasound shear wave speeds reduced following hamstring strain injury but not after returning to sport
Authors: Crawford Scott K. , Wille Christa M. , Joachim Mikel R. , Lee Kenneth S. , Heiderscheit Bryan C.
Published: January 2024

Objectives

The purpose of the study was to investigate differences in ultrasound shear wave speed (SWS) between uninjured and injured limbs following hamstring strain injury (HSI) at time of injury (TOI), return to sport (RTS), and 12 weeks after RTS (12wks).

Methods

This observational, prospective, cross-sectional design included male and female collegiate athletes who sustained an HSI. SWS imaging was performed at TOI, RTS, and 12wks with magnetic resonance imaging. SWS maps were acquired by a musculoskeletal-trained sonographer at the injury location of the injured limb and location-matched on the contralateral limb. The average SWS from three 5 mm diameter Q-boxes on each limb were used for analysis. A linear mixed effects model was performed to determine differences in SWS between limbs across the study time points.

Results

SWS was lower in the injured limb compared to the contralateral limb at TOI (uninjured – injured limb difference: 0.23 [0.05, 0.41] m/s, p = 0.006). No between-limb differences in SWS were observed at RTS (0.15 [-0.05, 0.36] m/s, p = 0.23) or 12wks (-0.11 [-0.41, 0.18] m/s, p = 0.84).

Conclusions

The SWS in the injured limb of collegiate athletes after HSI was lower compared to the uninjured limb at TOI but not at RTS or 12 weeks after RTS.

Critical relevance statement

Hamstring strain injury with structural disruption can be detected by lower injured limb shear wave speed compared to the uninjured limb. Lack of between-limb differences at return to sport may demonstrate changes consistent with healing. Shear wave speed may complement traditional ultrasound or MRI for monitoring muscle injury.

Key points

• Ultrasound shear wave speed can non-invasively measure tissue elasticity in muscle injury locations.

• Injured limb time of injury shear wave speeds were lower versus uninjured limb but not thereafter.

• Null return to sport shear wave speed differences may correspond to structural changes associated with healing.

• Shear wave speed may provide quantitative measures for monitoring muscle elasticity during recovery.

Graphical Abstract
Imaging phenotyping using 18F-FDG PET/CT radiomics to predict micropapillary and solid pattern in lung adenocarcinoma
Authors: Zhou Linyi , Sun Jinju , Long He , Zhou Weicheng , Xia Renxiang , Luo Yi , Fang Jingqin , Wang Yi , Chen Xiao
Published: January 2024

Objectives

To develop and validate a machine learning model using 18F-FDG PET/CT radiomics signature and clinical features to predict the presence of micropapillary and solid (MP/S) components in lung adenocarcinoma.

Methods

Eight hundred and forty-six patients who underwent preoperative PET/CT with pathologically confirmed adenocarcinoma were enrolled. After segmentation, 1688 radiomics features were extracted from PET/CT and selected to construct predictive models. Then, we developed a nomogram based on PET/CT radiomics integrated with clinical features. Receiver operating curves, calibration curves, and decision curve analysis (DCA) were performed for diagnostics assessment and test of the developed models for distinguishing patients with MP/S components from the patients without.

Results

PET/CT radiomics-clinical combined model could well distinguish patients with MP/S components from those without MP/S components (AUC = 0.87), which performed better than PET (AUC = 0.829, p < 0.05) or CT (AUC = 0.827, p < 0.05) radiomics models in the training cohort. In test cohorts, radiomics-clinical combined model outperformed the PET radiomics model in test cohort 1 (AUC = 0.859 vs 0.799, p < 0.05) and the CT radiomics model in test cohort 2 (AUC = 0.880 vs 0.829, p < 0.05). Calibration curve indicated good coherence between all model prediction and the actual observation in training and test cohorts. DCA revealed PET/CT radiomics-clinical model exerted the highest clinical benefit.

Conclusion

18F-FDG PET/CT radiomics signatures could achieve promising prediction efficiency to identify the presence of MP/S components in adenocarcinoma patients to help the clinician decide on personalized treatment and surveillance strategies. The PET/CT radiomics-clinical combined model performed best.

Critical relevance statement

18F-FDG PET/CT radiomics signatures could achieve promising prediction efficiency to identify the presence of micropapillary and solid components in adenocarcinoma patients to help the clinician decide on personalized treatment and surveillance strategies.

Graphical Abstract
The effect of feature normalization methods in radiomics
Authors: Demircioğlu Aydin
Published: January 2024

Objectives

In radiomics, different feature normalization methods, such as z-Score or Min–Max, are currently utilized, but their specific impact on the model is unclear. We aimed to measure their effect on the predictive performance and the feature selection.

Methods

We employed fifteen publicly available radiomics datasets to compare seven normalization methods. Using four feature selection and classifier methods, we used cross-validation to measure the area under the curve (AUC) of the resulting models, the agreement of selected features, and the model calibration. In addition, we assessed whether normalization before cross-validation introduces bias.

Results

On average, the difference between the normalization methods was relatively small, with a gain of at most + 0.012 in AUC when comparing the z-Score (mean AUC: 0.707 ± 0.102) to no normalization (mean AUC: 0.719 ± 0.107). However, on some datasets, the difference reached + 0.051. The z-Score performed best, while the tanh transformation showed the worst performance and even decreased the overall predictive performance. While quantile transformation performed, on average, slightly worse than the z-Score, it outperformed all other methods on one out of three datasets. The agreement between the features selected by different normalization methods was only mild, reaching at most 62%. Applying the normalization before cross-validation did not introduce significant bias.

Conclusion

The choice of the feature normalization method influenced the predictive performance but depended strongly on the dataset. It strongly impacted the set of selected features.

Critical relevance statement

Feature normalization plays a crucial role in the preprocessing and influences the predictive performance and the selected features, complicating feature interpretation.

Key points

• The impact of feature normalization methods on radiomic models was measured.

• Normalization methods performed similarly on average, but differed more strongly on some datasets.

• Different methods led to different sets of selected features, impeding feature interpretation.

• Model calibration was not largely affected by the normalization method.

Graphical Abstract