bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of Satellite Time-Synchronized Digital Image Correlation for High-Precision Dynamic Measurement of Aircraft Exteriors
Authors: Zhang Keming , shi peng , Yusheng Cai , Jia Huang , Wencheng Liu , Zheng pei , Ke Zhu , Liu Yayan , Chunxia Yang
Published: April 2024

A study was conducted to assess the precision and reliability of digital image correlation (DIC) techniques in remote synchronous operations for external aircraft measurements with a wide field of view, validating their effectiveness and accuracy. The study established a measurement system using three-dimensional DIC, which transmitted real-time satellite time data obtained from a GPS clock source to a trigger unit, with a synchronization accuracy better than 1 microsecond. Unlike low-precision synchronization that relies on the local relative time of the computer, the method proposed in this paper solves the problem of high-precision absolute time synchronization of the left and right cameras in remote acquisition. To mitigate the influence of environmental temperature on measurement precision, we employed an active temperature compensation device. This device effectively reduced the DIC measurement error for rotational angles to less than 0.025 degrees. The reliability and precision of the method proposed in this paper were thoroughly examined, revealing an average angular accuracy of less than 0.02 degrees and a relative error of under 1%. Using the Stereo-DIC system, the accuracy of the measurements is clarified for specific conditions. Additionally, we use this system to measure simulated aircraft landing gear, which moves at an angular velocity of 52.4°/s over a distance of 5 m with a wide field of view of 16.8°. Through the above two experimental tests, the camera successfully acquired stable satellite time information and accurately captured the time targets, demonstrating the system's reliability for practical engineering applications. This research significantly contributes to the engineering utilization of Stereo-DIC for external aircraft measurements, showcasing its potential in real-world scenarios.
Cu2+ doped CsPb(Cl/Br)3 quantum dots glasses for high performance long wavelength pass filters in the blue-purple region
Authors: Song Linke , Yu Hui , Zhang Xizhen , Li Gang , Zhang Sujuan , Pan xiuyu , Cheng Yi , Chen Baojiu
Published: April 2024

The CsPb(Cl/Br)3 quantum dots (QDs) with high Cl content are difficult to precipitate in the glass matrix, which hiders the development of the long wavelength pass filter operating in blue-purple region. In this work, the Cu2+ doped CsPb(Cl/Br)3 QDs glasses have been fabricated in the borate glass matrix by melt quenching process. To increase the Cl content, high Cl/Br ratio is used, and a crucible cover is used during the melting process to reduce Cl volatilization. The transmittance (T%), optical density (OD), photoluminescence (PL), PL excitation (PLE) and PL decay have been evaluated. The working wavelength of filters has been extended from ~500 nm to 412 nm. Small amount Cu2+ of 0.005–0.3 mol % is used for PL quenching and meanwhile maintaining excellent properties in transmittance and OD. As Cu2+ concentration increases, the PL intensity is quenched and the PL lifetime is decreased for the CsPb(Cl/Br)3 QDs. Quenching mechanism is considered as energy dependent electron transfer (ET). The fabricated CsPb(Cl/Br)3 QD glasses can meet requirements for the long wavelength pass filters in the blue-purple region.
SubGE-DDI: A new prediction model for drug-drug interaction established through biomedical texts and drug-pairs knowledge subgraph enhancement
Authors: Shi Yiyang , He Mingxiu , Chen Junheng , Han Fangfang , Cai Yongming
Published: April 2024

Biomedical texts provide important data for investigating drug-drug interactions (DDIs) in the field of pharmacovigilance. Although researchers have attempted to investigate DDIs from biomedical texts and predict unknown DDIs, the lack of accurate manual annotations significantly hinders the performance of machine learning algorithms. In this study, a new DDI prediction framework, Subgraph Enhance model, was developed for DDI (SubGE-DDI) to improve the performance of machine learning algorithms. This model uses drug pairs knowledge subgraph information to achieve large-scale plain text prediction without many annotations. This model treats DDI prediction as a multi-class classification problem and predicts the specific DDI type for each drug pair (e.g. Mechanism, Effect, Advise, Interact and Negative). The drug pairs knowledge subgraph was derived from a huge drug knowledge graph containing various public datasets, such as DrugBank, TwoSIDES, OffSIDES, DrugCentral, EntrezeGene, SMPDB (The Small Molecule Pathway Database), CTD (The Comparative Toxicogenomics Database) and SIDER. The SubGE-DDI was evaluated from the public dataset (SemEval-2013 Task 9 dataset) and then compared with other state-of-the-art baselines. SubGE-DDI achieves 83.91% micro F1 score and 84.75% macro F1 score in the test dataset, outperforming the other state-of-the-art baselines. These findings show that the proposed drug pairs knowledge subgraph-assisted model can effectively improve the prediction performance of DDIs from biomedical texts.
Biomedical text readability after hypernym substitution with fine-tuned large language models
Authors: Swanson Karl , He Shuhan , Calvano Josh , Chen David , Telvizian Talar , Jiang Lawrence , Chong Paul , Schwell Jacob , Mak Gin , Lee Jarone
Published: April 2024

The advent of patient access to complex medical information online has highlighted the need for simplification of biomedical text to improve patient understanding and engagement in taking ownership of their health. However, comprehension of biomedical text remains a difficult task due to the need for domain-specific expertise. We aimed to study the simplification of biomedical text via large language models (LLMs) commonly used for general natural language processing tasks involve text comprehension, summarization, generation, and prediction of new text from prompts. Specifically, we finetuned three variants of large language models to perform substitutions of complex words and word phrases in biomedical text with a related hypernym. The output of the text substitution process using LLMs was evaluated by comparing the pre- and post-substitution texts using four readability metrics and two measures of sentence complexity. A sample of 1,000 biomedical definitions in the National Library of Medicine’s Unified Medical Language System (UMLS) was processed with three LLM approaches, and each showed an improvement in readability and sentence complexity after hypernym substitution. Readability scores were translated from a pre-processed collegiate reading level to a post-processed US high-school level. Comparison between the three LLMs showed that the GPT-J-6b approach had the best improvement in measures of sentence complexity. This study demonstrates the merit of hypernym substitution to improve readability of complex biomedical text for the public and highlights the use case for fine-tuning open-access large language models for biomedical natural language processing.
Exploring the burden on family caregivers in providing care for their mentally ill relatives in the Upper East Region of Ghana
Authors: Daliri Dennis Bomansang , Afaya Agani , Laari Timothy Tienbia , Abagye Nancy , Aninanya Gifty Apiung
Published: April 2024

Caring for the mentally ill involves numerous challenges, including financial difficulties, stigma, and psychosocial issues, among others. Unpaid family caregivers must endure these challenges as they continue their care for their relatives with mental illness. Despite these burdens and their concomitant effects on both the patients and their caregivers, there is no evidence of this burden in the Bolgatanga municipality. This study explored the burden on family caregivers providing care for mentally ill relatives in the Bolgatanga Municipality of the Upper East Region of Ghana. The study employed a phenomenological research design. Fifteen family caregivers were purposively sampled from two secondary-level health facilities. In-depth interviews were conducted, audio-recorded, and transcribed verbatim. NVivo 12 pro software was used for data analysis. Thematic analysis was conducted following Braun and Clarke’s approach. The study identified three themes including social, physical, and psychological burdens. Under social burden, financial challenges and stigma were identified, weight loss was identified as a physical burden, and poor concentration as a psychological burden. These themes represent the challenges encountered by the family caregivers as they provided care for their mentally ill relatives. There is a need to provide support for family caregivers including respite, formation of support groups, and financial support to alleviate family caregivers of the burdens they endure. Additionally, it is imperative to integrate mental health services into the national health insurance scheme to alleviate the financial burden on family caregivers.
Machine learning for predicting Chagas disease infection in rural areas of Brazil
Authors: De Rose Ghilardi Fabio , Silva Gabriel , Vieira Thallyta Maria , Mota Ariela , Bierrenbach Ana Luiza , Damasceno Renata Fiuza , Oliveira Lea Campos de , Dias Porto Chiavegatto Filho Alexandre , Sabino Ester
Published: April 2024

Introduction

Chagas disease is a severe parasitic illness that is prevalent in Latin America and often goes unaddressed. Early detection and treatment are critical in preventing the progression of the illness and its associated life-threatening complications. In recent years, machine learning algorithms have emerged as powerful tools for disease prediction and diagnosis.

Methods

In this study, we developed machine learning algorithms to predict the risk of Chagas disease based on five general factors: age, gender, history of living in a mud or wooden house, history of being bitten by a triatomine bug, and family history of Chagas disease. We analyzed data from the Retrovirus Epidemiology Donor Study (REDS) to train five popular machine learning algorithms. The sample comprised 2,006 patients, divided into 75% for training and 25% for testing algorithm performance. We evaluated the model performance using precision, recall, and AUC-ROC metrics.

Results

The Adaboost algorithm yielded an AUC-ROC of 0.772, a precision of 0.199, and a recall of 0.612. We simulated the decision boundary using various thresholds and observed that in this dataset a threshold of 0.45 resulted in a 100% recall. This finding suggests that employing such a threshold could potentially save 22.5% of the cost associated with mass testing of Chagas disease.

Conclusion

Our findings highlight the potential of applying machine learning to improve the sensitivity and effectiveness of Chagas disease diagnosis and prevention. Furthermore, we emphasize the importance of integrating socio-demographic and environmental factors into neglected disease prediction models to enhance their performance.
High uptake of COVID-19 vaccines among healthcare workers in urban Uganda
Authors: Kyakuwa Nasimu , Kimbugwe Geofrey , Nakanjako Flavia , Kalute Hamza , Mpooya Simon , Atuhairwe Christine , Perez Laurent , Kikaire Bernard
Published: April 2024

Objectives

The aim of the study was to describe the facilitators, barriers to and level of uptake of COVID-19 vaccines among healthcare workers in primary healthcare facilities in an urban setting in Uganda.

Materials and methods

We conducted a cross-sectional study among HCWs in private and public health facilities in Entebbe municipality between July 2021 and August 2021. Data was collected using a structured questionnaire that was shared, via an online link, to consented participants. Uptake of the vaccines among healthcare workers was analysed as proportions, and logistic regression was used to analyse barriers and facilitators to uptake of COVID-19 vaccines.

Results

The study enrolled 360 participants, with 61.7% (n = 222) females. A total of 236 (65.6%) healthcare workers had received at least one dose of COVID-19 vaccine, with higher uptake among females 64% (n = 151). Age above 40 years (OR 2.16), working in a government healthcare facility (OR 3.12), participating in COVID-19 vaccine related activities (OR 4.62), and having tested for SARS-COV-2 (OR 3.05) increased the odds of having been vaccinated. Working in small roadside clinics reduced the odds of being vaccinated by almost 70%, while HCWs in government health services were 3.1 times more likely to have been vaccinated. History of having cared for a COVID-19 patient and having a positive SARS-COV-2 test result did not influence the uptake of the vaccines in the study population.

Conclusion

Vaccine uptake among HCWs was close to the World Health Organisation (WHO) recommended uptake of 70% by mid-2022.
The limitations of automatically generated curricula for continual learning
Authors: Kravchenko Anna , Cusack Rhodri
Published: April 2024

In many applications, artificial neural networks are best trained for a task by following a curriculum, in which simpler concepts are learned before more complex ones. This curriculum can be hand-crafted by the engineer or optimised like other hyperparameters, by evaluating many curricula. However, this is computationally intensive and the hyperparameters are unlikely to generalise to new datasets. An attractive alternative, demonstrated in influential prior works, is that the network could choose its own curriculum by monitoring its learning. This would be particularly beneficial for continual learning, in which the network must learn from an environment that is changing over time, relevant both to practical applications and in the modelling of human development. In this paper we test the generality of this approach using a proof-of-principle model, training a network on two sequential tasks under static and continual conditions, and investigating both the benefits of a curriculum and the handicap induced by continuous learning. Additionally, we test a variety of prior task-switching metrics, and find that in some cases even in this simple scenario the a network is often unable to choose the optimal curriculum, as the benefits are sometimes only apparent with hindsight, at the end of training. We discuss the implications of the results for network engineering and models of human development.
Does BRRD mitigate the bank-to-sovereign risk channel?
Authors: Lamers Martien , Present Thomas , Soenen Nicolas , Vennet Rudi Vander
Published: April 2024

We investigate the effectiveness of the Bank Recovery and Resolution Directive (BRRD) in mitigating the transmission of credit risk from banks to their sovereign, using CDS spreads to capture bank and sovereign credit risk for a sample of 43 banks in 8 Euro Area countries over the period 2009–2020. If the BRRD bail-in framework is credible, changes in bank default risk should not be transmitted to sovereign risk. In a novel approach we use banks earnings announcements to identify exogenous shocks to bank credit risk and investigate to what extent bank risk is transmitted to sovereign risk before and during the BRRD era. We find that bank-to-sovereign risk transmission has diminished after the introduction of the BRRD, suggesting that financial markets judge the BRRD framework as credible. The decline in bank-sovereign risk transmission is particularly significant in the periphery Euro Area countries, especially Italy and Spain, where the bank-sovereign nexus was most pronounced during the sovereign debt crisis. We report that the lower bank-to-sovereign credit risk transmission is associated with the parliamentary approval of the BRRD and not with the OMT program launched by the ECB to affect sovereign yield spreads, nor with specific bail-in or bailout cases which occurred during the BRRD era. Finally, we document that the reduction in risk transmission is most pronounced for banks classified as a Global Systemically Important Bank (G-SIB), stressing the importance of additional capital buffers imposed by Basel III.
Chest pain in pediatric patients in the emergency department- Presentation, risk factors and outcomes-A systematic review and meta-analysis
Authors: Alsabri Mohammed , Elshanbary Alaa Ahmed , Nourelden Anas Zakarya , Fathallah Ahmed Hashem , Zaazouee Mohamed Sayed , Pincay Jorge , Nakadar Zaid , Wasem Muhammad , Aeder Lita
Published: April 2024

Objective

This study aimed to assess and determine the presentation, risk factors, and outcomes of pediatric patients who were admitted for cardiac-related chest pain.

Background

Although chest pain is common in children, most cases are due to non-cardiac etiology. The risk of misdiagnosis and the pressure of potentially adverse outcomes can lead to unnecessary diagnostic testing and overall poorer patient experiences. Additionally, this can lead to a depletion of resources that could be better allocated towards patients who are truly suffering from cardiac-related pathology.

Methods

This review was conducted per PRISMA guidelines. This systematic review used several databases including MEDLINE, Embase, Scopus, and Web of Science to obtain its articles for review.

Results

A total of 6,520 articles were identified, and 11 articles were included in the study. 2.5% of our study population was found to have cardiac-related chest pain (prevalence = 0.025, 95% CI [0.013, 0.038]). The most commonly reported location of pain was retrosternal chest pain. 97.5% of the study population had a non-cardiac cause of chest pain, with musculoskeletal pain being identified as the most common cause (prevalence = 0.357, 95% CI [0.202, 0.512]), followed by idiopathic (prevalence = 0.352, 95% CI [0.258, 0.446]) and then gastrointestinal causes (prevalence = 0.053, 95% CI [0.039, 0.067]).

Conclusions

The overwhelming majority of pediatric chest pain cases stem from benign origins. This comprehensive analysis found musculoskeletal pain as the predominant culprit behind chest discomfort in children. Scrutinizing our study cohort revealed that retrosternal chest pain stands as the unequivocal epicenter of this affliction. Thorough evaluation of pediatric patients manifesting with chest pain is paramount for the delivery of unparalleled care, especially in the context of potential cardiac risks in the emergency department.
Crop cover and nutrient levels mediate the effects of land management type on aquatic invertebrate richness in prairie potholes
Authors: Kirk David Anthony , Collins Sara J. , Martínez-Lanfranco Juan Andrés , Martin Amanda E.
Published: April 2024

Aquatic invertebrates provide important ecosystem services, including decomposition and nutrient cycling, and provide nutrition for birds, fish, amphibians, and bats. Thus, the effects of agricultural land management practices on aquatic invertebrates are relevant to farmers, wildlife biologists, and policymakers. Here, we used data on aquatic invertebrates (159 taxa, 73 to species, 75 to genus/family) collected in 40 wetlands in the Canadian prairies to test for direct and indirect relationships among land management types (perennial cover, organic, minimum tillage, conventional), landscape structure (cropland and wetland cover within the surrounding landscape), and water quality (total nutrient levels, turbidity) on species richness of invertebrates using structural equation modelling. Additionally, we assessed variation in community composition within and among wetlands in different land use management types using a direct gradient analysis and variance partitioning. The direct effects of land management type were not supported but we found strong supportive evidence that effects of land management on richness were significantly mediated through cropland cover, nutrient levels, and turbidity. After controlling for these indirect effects, aquatic invertebrate richness decreased along a gradient from the lowest to the highest farming intensity, i.e., richness decreased from perennial cover sites to organic to minimum tillage to conventional sites. Support was also found for negative effects of nutrient levels and turbidity on richness. We did not find significant support for differences in gamma diversity or a simple test (homogeneity of multivariate dispersions) of differences in turnover among land management types; however, land management had a significant effect in distance-based redundancy analysis. Taken together, these results suggest that focusing conservation efforts on reducing cropland erosion and nutrient inputs to wetlands and creating more permanent cover may be effective strategies for conserving richness of aquatic invertebrates in agricultural landscapes in this region.
Mental health and burnout during medical school: Longitudinal evolution and covariates
Authors: Carrard Valerie , Berney Sylvie , Bourquin Céline , Ranjbar Setareh , Castelao Enrique , Schlegel Katja , Gaume Jacques , Bart Pierre-Alexandre , Schmid Mast Marianne , Preisig Martin , Berney Alexandre
Published: April 2024

Background

Medical students’ rate of depression, suicidal ideation, anxiety, and burnout have been shown to be higher than those of the same-age general population. However, longitudinal studies spanning the whole course of medical school are scarce and present contradictory findings. This study aims to analyze the longitudinal evolution of mental health and burnout from the first to the last year of medical school using a wide range of indicators. Moreover, biopsychosocial covariates that can influence this evolution are explored.

Method

In an open cohort study design, 3066 annual questionnaires were filled in by 1595 different students from the first to the sixth year of the Lausanne Medical School (Switzerland). Depression symptoms, suicidal ideation, anxiety symptoms, stress, and burnout were measured along with biopsychosocial covariates. The longitudinal evolution of mental health and burnout and the impact of covariates were modelled with linear mixed models.

Results

Comparison to a same-aged general population sample shows that medical students reported significantly more depression symptoms and anxiety symptoms. Medical students’ mental health improved during the course of the studies in terms of depression symptoms, suicidal ideation, and stress, although suicidal ideation increased again in the last year and anxiety symptoms remained stable. Conversely, the results regarding burnout globally showed a significant worsening from beginning to end of medical school. The covariates most strongly related to better mental health and less burnout were less emotion-focused coping, more social support, and more satisfaction with health.

Conclusion

Both improvement of mental health and worsening of burnout were observed during the course of medical school. This underlines that the beginning and the end of medical school bring specific challenges with the first years’ stressors negatively impacting mental health and the last year’s difficulties negatively impacting burnout.
Exploring the preservation of a parasitic trace in decapod crustaceans using finite elements analysis
Authors: Wright Nathan L. , Klompmaker Adiël A. , Petsios Elizabeth
Published: April 2024

The fossil record of parasitism is poorly understood, due largely to the scarcity of strong fossil evidence of parasites. Understanding the preservation potential for fossil parasitic evidence is critical to contextualizing the fossil record of parasitism. Here, we present the first use of X-ray computed tomography (CT) scanning and finite elements analysis (FEA) to analyze the impact of a parasite-induced fossil trace on host preservation. Four fossil and three modern decapod crustacean specimens with branchial swellings attributed to an epicaridean isopod parasite were CT scanned and examined with FEA to assess differences in the magnitude and distribution of stress between normal and swollen branchial chambers. The results of the FEA show highly localized stress peaks in reaction to point forces, with higher peak stress on the swollen branchial chamber for nearly all specimens and different forces applied, suggesting a possible shape-related decrease in the preservation potential of these parasitic swellings. Broader application of these methods as well as advances in the application of 3D data analysis in paleontology are critical to understanding the fossil record of parasitism and other poorly represented fossil groups.
Experiences of help-seeking from professional services for a child or young person’s mental health concerns during the pandemic: A qualitative study
Authors: Mathews Frances , Benham-Clarke Simon , Ford Tamsin J. , Hill Suzanne , Sadler Katharine , Newlove-Delgado Tamsin
Published: April 2024

Introduction

The immediate response to the Covid-19 pandemic saw school closures and a shift in provision to online health services for children and young people experiencing mental health concerns. This study provides mental health and referral services with an insight into difficulties experienced as well as recommendations on potential improvements.

Methods

Semi-structured interviews with 11 parents and six young people. Reflexive thematic analysis was used to analyse the data.

Results

Parents and young people reported mixed experiences on accessing mental health support. Priorities and pressures on health services impacted the likelihood of choosing to seek and being able to obtain help. Parents and young people had varying expectations and experiences in help-seeking during the pandemic which were also impacted by others’ experiences and views. For many, the relationship with the professional they were in contact with impacted their mental health treatment. Provision was sometimes accessed via private services due to long waiting lists or problems that did not “meet threshold”.

Conclusion

Understanding the experiences of seeking mental healthcare during the pandemic can inform improvements to access to services at a time when people are most vulnerable. Accessible provision other than private services needs to be made for those on waiting lists. For those who do not meet service threshold, intermediary support needs to be secured to prevent unnecessary exacerbation of symptoms and prolonged problems. If schools are to remain the hub for children and young people’s mental health services, they should be considered essential services at all times.
A study of market segmentation, government competition, and public service efficiency in China: Based on a semi-parametric spatial lag model
Authors: Yao Lan , Luo Ruoyu , Yi Xiaoqin
Published: April 2024

Despite significant growth in fiscal expenditure, the overall level of public services in China remains inadequate. One approach to improving government public service efficiency from the perspective of management psychology is to strengthen government competition. However, only a few studies have explored the improvement of public service efficiency through government competition, with even fewer addressing the phenomena of market segmentation and spatial effects that accompany the process of government competition. This paper aims to fill this research gap by examining the effects of government competition and market segmentation on public service efficiency, as well as their spatial disparities. We initially employs the DEA method to assess the efficiency of public services based on inputs and outputs, and examines its spatial variations. Subsequently, a semi-parametric spatial lag panel model is utilized to validate the effects of market segmentation and government competition on public service efficiency. Our findings indicate that inter-provincial market segmentation leads to a decline in public service efficiency. Moreover, the influence of horizontal competition between local governments on public service efficiency varies depending on the degree of positive and negative effects in their competition dynamics. The impact of vertical competition between central and local governments on public service efficiency is influenced by the degree of fiscal decentralization. When the level of fiscal decentralization is below 0.808, vertical competition between central and local governments has a promoting effect on public service efficiency. However, when the degree of fiscal decentralization exceeds 0.08, this promoting effect weakens and gradually transforms into a negative influence. The insights and evidence provided by this study offer valuable guidance for for effectively reshaping the fiscal relations between the central and local governments in China and improving public service efficiency in the context of a new round of fiscal and tax system reforms.
Assessing the role of actors in river restoration: A network perspective
Authors: Ioana-Toroimac Gabriela , Stoica Cătălina , Moroșanu Gabriela Adina , Șandor Ionuț Andrei , Constantin Dana Maria
Published: April 2024

The aim of this study was to identify and characterize the actors involved in river restoration in Romania by untangling the complex networks that they are part of. Actors were considered nodes in a social network, tied by a common action or project. The nodes were characterized through the centrality metrics of a network. The network of actors in river restoration in Romania has a low density and high average path length and diameter for such a spare network, which suggests that knowledge transfer and collaboration are difficult. In the context of a highly centralized water governance system in Romania, the National Authority for Water exerts power and influence in river restoration as well. It has numerous partners, both disconnected and well connected in the network, therefore, it tends to be connected to everybody, as well as gets and diffuses knowledge. Yet, other actors are willing to get involved in river restoration in Romania. NGOs and research organizations have a central position in the network and play various roles (e.g., unconcerned influencers, gate-keepers, pulse-takers). As a recommendation for governing river restoration in Romania, we urge the creation of a national programme focused on river restoration, where the call for projects would be coordinated by the National Authority for Water and open to its territorial subordinates in agreement with stakeholders from various sectors and domains.
Generative adversarial networks for anonymous acneic face dataset generation
Authors: Zein Hazem , Chantaf Samer , Fournier Régis , Nait-Ali Amine
Published: April 2024

It is well known that the performance of any classification model is effective if the dataset used for the training process and the test process satisfy some specific requirements. In other words, the more the dataset size is large, balanced, and representative, the more one can trust the proposed model’s effectiveness and, consequently, the obtained results. Unfortunately, large-size anonymous datasets are generally not publicly available in biomedical applications, especially those dealing with pathological human face images. This concern makes using deep-learning-based approaches challenging to deploy and difficult to reproduce or verify some published results. In this paper, we propose an efficient method to generate a realistic anonymous synthetic dataset of human faces, focusing on attributes related to acne disorders at three distinct levels of severity (Mild, Moderate, and Severe). Notably, our approach initiates from a small dataset of facial acne images, leveraging generative techniques to augment and diversify the dataset, ensuring comprehensive coverage of acne severity levels while maintaining anonymity and realism in the synthetic data. Therefore, a specific hierarchy StyleGAN-based algorithm trained at distinct levels is considered. Moreover, the utilization of generative adversarial networks for augmentation offers a means to circumvent potential privacy or legal concerns associated with acquiring medical datasets. This is attributed to the synthetic nature of the generated data, where no actual subjects are present, thereby ensuring compliance with privacy regulations and legal considerations. To evaluate the performance of the proposed scheme, we consider a CNN-based classification system, trained using the generated synthetic acneic face images and tested using authentic face images. Consequently, we show that an accuracy of 97.6% is achieved using InceptionResNetv2. As a result, this work allows the scientific community to employ the generated synthetic dataset for any data processing application without restrictions on legal or ethical concerns. Moreover, this approach can also be extended to other applications requiring the generation of synthetic medical images.
Fracture healing on non-union fracture model promoted by non-thermal atmospheric-pressure plasma
Authors: Saito Kosuke , Toyoda Hiromitsu , Okada Mitsuhiro , Oh Jun-Seok , Nakazawa Katsumasa , Ban Yoshitaka , Orita Kumi , Shimatani Akiyoshi , Yao Hana , Shirafuji Tatsuru , Nakamura Hiroaki
Published: April 2024

Non-thermal atmospheric-pressure plasma (NTAPP) is attracting widespread interest for use in medical applications. The tissue repair capacity of NTAPP has been reported in various fields; however, little is known about its effect on fracture healing. Non-union or delayed union after a fracture is a clinical challenge. In this study, we aimed to investigate how NTAPP irradiation promotes fracture healing in a non-union fracture model and its underlying mechanism, in vitro and in vivo. For the in vivo study, we created normal and non-union fracture models in LEW/SsNSlc rats to investigate the effects of NTAPP. To create a fracture, a transverse osteotomy was performed in the middle of the femoral shaft. To induce the non-union fracture model, the periosteum surrounding the fracture site was cauterized after a normal fracture model was created. The normal fracture model showed no significant difference in bone healing between the control and NTAPP-treated groups. The non-union fracture model demonstrated that the NTAPP-treated group showed consistent improvement in fracture healing. Histological and biomechanical assessments confirmed the fracture healing. The in vitro study using pre-osteoblastic MC3T3-E1 cells demonstrated that NTAPP irradiation under specific conditions did not reduce cell proliferation but did enhance osteoblastic differentiation. Overall, these results suggest that NTAPP is a novel approach to the treatment of bone fractures.
Interpreter usage and associations with latent tuberculosis infection treatment acceptance and completion in the USA among non-U.S.–born persons, 2012–2017
Authors: Gonzalez-Reyes Rebeca , Katz Dolly , Lambert Lauren , Sorri Yoseph , Narita Masahiro , Horne David J. ,   for the Tuberculosis Epidemiologic Studies Consortium
Published: April 2024

Background

Latent tuberculosis infection (LTBI) screening and treatment interventions that are tailored to optimize acceptance among the non-U.S.–born population are essential for U.S. tuberculosis elimination. We investigated the impact of medical interpreter use on LTBI treatment acceptance and completion among non-U.S.–born persons in a multisite study.

Methods

The Tuberculosis Epidemiologic Studies Consortium was a prospective cohort study that enrolled participants at high risk for LTBI at ten U.S. sites with 18 affiliated clinics from 2012 to 2017. Non-U.S.–born participants with at least one positive tuberculosis infection test result were included in analyses. Characteristics associated with LTBI treatment offer, acceptance, and completion were evaluated using multivariable logistic regression with random intercepts to account for clustering by enrollment site. Our primary outcomes were whether use of an interpreter was associated with LTBI treatment acceptance and completion. We also evaluated whether interpreter usage was associated treatment offer and whether interpreter type was associated with treatment offer, acceptance, or completion.

Results

Among 8,761 non-U.S.–born participants, those who used an interpreter during the initial interview had a significantly greater odds of accepting LTBI treatment than those who did not use an interpreter. There was no association between use of an interpreter and a clinician’s decision to offer treatment or treatment completion once accepted. Characteristics associated with lower odds of treatment being offered included experiencing homelessness and identifying as Pacific Islander persons. Lower treatment acceptance was observed in Black and Latino persons and lower treatment completion by participants experiencing homelessness. Successful treatment completion was associated with use of shorter rifamycin-based regimens. Interpreter type was not associated with LTBI treatment offer, acceptance, or completion.

Conclusions

We found greater LTBI treatment acceptance was associated with interpreter use among non-U.S.–born individuals.
Professional quality of life in animal research personnel is linked to retention & job satisfaction: A mixed-methods cross-sectional survey on compassion fatigue in the USA
Authors: Young Lauren , Ferrara Fabienne , Kelly Lisa , Martin Tara , Thompson-Iritani Sally , LaFollette Megan R.
Published: April 2024

Background

Working with research animals can be both rewarding and challenging. The rewarding part of the work is associated with understanding the necessity for animal research to improve the health of humans and animals and the knowledge that one can provide care and compassion for the animals. Challenges with animal research include witnessing stress/pain in animals necessitated by scientific requirements, end of study euthanasia, and societal stigmatization about animal research. These challenges could be compounded with more general workplace stresses, in turn, impacting job retention and satisfaction. However, these factors have yet to be formally evaluated. Therefore, the purpose of this survey was to comprehensively evaluate professional quality of life’s correlation with key workplace metrics.

Methods

Six institutions were recruited to participate in a longitudinal intervention trial on compassion fatigue resiliency. This manuscript reports key baseline metrics from this survey. A cross-sectional mixed methods survey was developed to evaluate professional quality of life, job satisfaction, retention, and factors influencing compassion fatigue resiliency. Quantitative data were analyzed via general linear models and qualitative data were analyzed by theme.

Results

Baseline data was collected from 198 participants. Personnel who reported higher compassion satisfaction also reported higher retention and job satisfaction. Conversely, personnel who reported higher burnout also reported lower job satisfaction. In response to open-ended questions, participants said their compassion fatigue was impacted by institutional culture (70% of participants), animal research (58%), general mental health (41%), and specific compassion fatigue support (24%).

Conclusions

In conclusion, these results show that professional quality of life is related to important operational metrics of job satisfaction and retention. Furthermore, compassion fatigue is impacted by factors beyond working with research animals, including institutional culture and general mental health support. Overall, this project provides rationale and insight for institutional support of compassion fatigue resiliency.
Land as a binding constraint to cluster-based development in Ethiopia: To cluster or not to cluster?
Authors: Dureti Guyo Godana , Tabe-Ojong Martin Paul JR.
Published: April 2024

Introduction

As one of the agglomeration models targeting cluster-based rural development, cluster farming has been promoted in Ethiopia and it is already reported to have significant welfare implications, but participation rates are not as high as expected. This study examines the role of land as a constraint to the development of cluster-based development in Ethiopia both using extensive and intensive measures of cluster farming. The study further disaggregates farm households based on their farm size to better understand potential heterogeneities in the relationship between farm size and cluster farming. The paper also documents other household socio-economic and network characteristics that may matter in cluster farming.

Methods

We use a large-scale farm household data from 3,969 households coupled with some expert insights on cluster farming in Ethiopia. Households in the study areas grow major staples such as maize, wheat, teff, malt barley, and sesame in four main regions of Ethiopia. We employ a double hurdle model to examine both the decision to participate and the extent to which households participate in cluster farming. By extent of participation, we refer to the amount of land and share of land farm households contribute to cluster farming. For robustness purposes, we also estimate the Tobit and Linear Probability Models.

Results

We show a positive association between farm size and cluster farming both at the extensive and intensive margins. This relationship turns negative for large amounts of land. This shows that cluster farming increases with farm size up to a threshold beyond which it declines. We also find suggestive evidence that participation rates are lower for small-scale farms, but also declines for large-scale farms. In addition, we show that access to information and network characteristics also matter in enabling cluster farming.

Conclusion

The findings of this study are relevant in the framework of plans to upscale the cluster-based development initiative in Ethiopia. Attention to landholding issues is key and may be an important area where policy action can be geared to boost cluster farming. Moreover, our results inform potential targeting plans that aim to increase the participation of small-scale farmers who are usually the intended targets of such programs.
Low-volume enrichment method supports high throughput bacteriophage screening and isolation from wastewater
Authors: Kenney Patrick O. , Gómez-Duarte Oscar G.
Published: April 2024

Bacteriophage therapy is a rapidly growing field of study. Narrow host ranges, bacterial resistance, and limited antibiotic availability make lytic phages a feasible therapeutic potential. Phage discovery, a critical step in developing phage therapy, is a pathway to accessible treatment. This has always been a laborious, time-consuming and resource-intensive process. In this paper, we describe a 96-well plate low-volume bacteriophage enrichment method with concentrated environmental sources to rapidly discover and isolate phages targeting multiple organisms simultaneously. Samples from natural water sources, wastewater influent, and activated sludge were tested in large volume enrichment cultures and low-volume 96-well plate format. Each plate has the capacity to run as many as 48 different combinations with multiple bacterial hosts. The time to identify the presence of phage in a sample was 5 to 10 hours in the low-volume format versus a minimum of 2 days in the traditional enrichment method. The labor and expense involved also favor the 96-well plate format. There was some loss of discovered phages using this technique, primarily targeting bacterial species less prevalent in the environment. This is an easily modifiable method that is amenable to automation and a variety of potential phage sources.
A design for life: Predicting cognitive performance from lifestyle choices
Authors: Nichols Emily S. , Nelson Georgia , Wild Conor J. , Owen Adrian M.
Published: April 2024

Maintaining cognitive capacity through adulthood has been the target of many recent studies that have examined the influence of lifestyle choices such as exercise, diet, and sleeping habits. Many of these studies have focused on a single factor (e.g., diet) and its effect on cognitive abilities; however, humans make numerous lifestyle choices every single day, many of which interact and influence each other. Here, we investigated whether combinations of lifestyle choices can predict better or worse cognitive performance in the general population, and whether optimal combinations of choices existed depending on the cognitive domain. Specifically, we examined 20 self-reported lifestyle choices, such as playing video games, drinking alcohol, and amount of exercise taken, in a sample of almost 10,000 participants. All participants also completed 12 cognitive tests that have been shown to generate three composite cognitive domain scores pertaining to short-term memory, verbal abilities, and reasoning. Using recursive feature elimination and random forest regression, we were able to explain 9% of the variance in short-term memory scores, 8% of the variance in reasoning scores, and 7% of the variance in verbal ability scores. While the regression model provided predictive power in all three domains, these levels indicate that even when considering a large number of lifestyle choices, there remains a considerable degree of variability in predicting short-term memory, reasoning and verbal abilities. Thus, while some modifiable lifestyle factors may have an impact on cognitive capacity, there likely exists no single optimal design for life.
A Theileria annulata parasite with a single mutation, methionine 128 to isoleucine (M128I), in cytochrome B is resistant to buparvaquone
Authors: Tajeri Shahin , Chattopadhyay Debasish , Langsley Gordon , Nijhof Ard M.
Published: April 2024

Tropical theileriosis is a fatal leukemic-like disease of cattle caused by the tick-transmitted protozoan parasite Theileria annulata. The economics of cattle meat and milk production is severely affected by theileriosis in endemic areas. The hydroxynaphtoquinone buparvaquone (BPQ) is the only available drug currently used to treat clinical theileriosis, whilst BPQ resistance is emerging and spreading in endemic areas. Here, we chronically exposed T. annulata-transformed macrophages in vitro to BPQ and monitored the emergence of drug-resistant parasites. Surviving parasites revealed a significant increase in BPQ IC50 compared to the wild type parasites. Drug resistant parasites from two independent cloned lines had an identical single mutation, M128I, in the gene coding for T. annulata cytochrome B (Tacytb). This in vitro generated mutation has not been reported in resistant field isolates previously, but is reminiscent of the methionine to isoleucine mutation in atovaquone-resistant Plasmodium and Babesia. The M128I mutation did not appear to exert any deleterious effect on parasite fitness (proliferation and differentiation to merozoites). To gain insight into whether drug-resistance could have resulted from altered drug binding to TaCytB we generated in silico a 3D-model of wild type TaCytB and docked BPQ to the predicted 3D-structure. Potential binding sites cluster in four areas of the protein structure including the Q01 site. The bound drug in the Q01 site is expected to pack against an alpha helix, which included M128, suggesting that the change in amino acid in this position may alter drug-binding. The in vitro generated BPQ resistant T. annulata is a useful tool to determine the contribution of the various predicted docking sites to BPQ resistance and will also allow testing novel drugs against theileriosis for their potential to overcome BPQ resistance.