bluuebunny/crossref_metadata_2025 huggingface dataset:
The impact of frontal lesions after mild to moderate traumatic brain injury on frontal network measures
Authors: Rakers Sandra E. , Liemburg Edith J. , van der Horn Harm J. , de Groot Jan Cees , Spikman Jacoba M. , van der Naalt Joukje
Published: November 2023

To investigate the impact of frontal macro-structural lesions on intrinsic network measures, we examined brain network function during resting-state fMRI in patients with frontal lesions in the subacute phase after mild to moderate traumatic brain injury. Additionally, network function was related to neuropsychological performances. 17 patients with frontal lesions, identified on admission CT after mild to moderate trauma, were compared to 30 traumatic brain injury patients without frontal lesions and 20 healthy controls. Three months post-injury, we acquired fMRI scans and neuropsychological assessments (measuring frontal executive functions and information processing speed). Using independent component analysis, the activity of and connectivity between network components (largely located in the prefrontal cortex) and relations with neuropsychological measures were examined and compared across groups. The analysis yielded five predominantly frontal components: anterior and posterior part of the default mode network, left and right frontoparietal network and salience network. No significant differences concerning fMRI measures were found across groups. However, the frontal lesions group performed significantly worse on neuropsychological tests than the other two groups. Additionally, the frontal lesions group showed a significant positive association of stronger default mode network–salience network connectivity with better executive performances. Our findings suggest that, on fMRI level, frontal network measures are not largely affected by frontal lesions following a mild to moderate traumatic brain injury. Yet, patients with damage to the frontal structures did show poorer executive abilities which might to some degree be related to altered frontal network connectivity between the default mode network and salience network.
National and subnational burden of leukemia and its risk factors, 1990–2019: Results from the Global Burden of Disease study 2019
Authors: Poopak Amirhossein , Saeedi Moghaddam Sahar , Esfahani Zahra , Keykhaei Mohammad , Rezaei Negar , Rezaei Nazila , Rashidi Mohammad-Mahdi , Ahmadi Naser , Abbasi-Kangevari Mohsen , Malekpour Mohammad-Reza , Ghamari Seyyed-Hadi , Djalalinia Shirin , Tavangar Seyed Mohammad , Larijani Bagher , Kompani Farzad
Published: November 2023

Background

Hematologic malignancies have a great essential role in cancer global burden. Leukemia which two major subtypes based on the onset, is one of the common subtypes of this malignancy.

Method

For the GBD 2019 study, cancer registry data and vital registration system were used to estimate leukemia mortality. The Meta-Regression-Bayesian Regularized Trimmed (MR-BRT), Cause of Death Ensemble model (CODEm) and Spatiotemporal Gaussian Process Regression (ST-GPR) were used to model our data and estimate each quantity of interest. Mortality to incidence ratios (MIR) were used to generate incidence and survival from mortality rate. Prevalence and survival were used to generate years lived with disability (YLDs). Age-specific mortality and life expectancy at the same age were used to estimate years of life lost (YLLs). The sum of YLLs and YLDs generates DALYs.

Results

The total national incidence of leukemia increased from 6092 (UI 95%: 3803–8507) in 1990 to 6767 (4646–7890) new cases in 2019. However, leukemia age-standardized incidence ratio(ASIR) decreased from 11.6 (8–14.8) to 8.9 (6.2–10.3) new cases per 100,000 in this exact period. At the national level, deaths from leukemia increased 1.5-fold between 1990 and 2019, from 3287 (2284–4201) to 4424 (3137–5030), whereas the age-standardized death rate(ASDR) decreased from 8.3 (6.1–9.8) in 1990 to 6 (4.3–6.8) per 100,000 in 2019. In the study period, total leukemia DALYs decreased 12.2% and reached 162850 (110681–188806), in 2019. The age-standardized DALYs decreased 36.7% from 324.3 (224.8–413.4) in 1990 to 205.3 (140.3–237.8) in 2019. ASDR, DALYs, YLLs, and YLDs rate to high BMI was increasing while smoking and occupational exposure to benzene and formaldehyde were decreasing in the study period.

Conclusion

This study provided a better understanding of leukemia burden and to reduce controversies of leukemia across Iran. The leukemia status alteration of the country, is trackable.
Combinatorial analysis of ACE and ACE2 polymorphisms reveals protection against COVID-19 worsening: A genetic association study in Brazilian patients
Authors: Sousa Romes Bittencourt Nogueira de , Nascimento Lis Raquel Silva do , Costa Luiz Henrique Alves , Leite Vanessa Rafaela Milhomem Cruz , Borges Clayton Luiz , Deus José Miguel de , Rebelo Ana Cristina Silva , Pinheiro Denise da Silva , Pedrino Gustavo Rodrigues
Published: November 2023

Since angiotensin-converting enzyme 2, ACE2, was identified as the receptor for SARS-CoV-2 and considering the intense physiological interplay between the two angitensinases isoforms, ACE and ACE2, as counter-regulatory axis of the renin-angiotensin system, we proposed the evaluation of polymorphisms in these two key regulators in relation to COVID-19 severity. A genetic association study involving 621 COVID-19 hospitalized patients from Brazil was performed. All subjects had a confirmed diagnosis of COVID-19 via RT-PCR. Patients were categorized into two groups: the "mild" group (N = 296), composed of individuals hospitalized in ward beds who progressed to cure, and the "severe" group (N = 325), composed of individuals who required hospitalization in an intensive care unit (ICU), or who died. Blood samples were genotyped for ACE I/D polymorphism and ACE2 G8790A polymorphism by real-time PCR via TaqMan assay. The analysis of combined polymorphisms revealed a protective role for genotypic profile II/A_ (ORA = 0,26; p = 0,037) against the worsening of COVID-19 in women. The results indicate a protection profile to COVID-19 progression, in which the II/A_ carriers have almost four times less chance of a severe outcome. It is proposed that a decreased activity of ACE (deleterious effects) in conjunction with an increased ACE2 activity (protective effects), should be the underlying mechanism. The findings are unprecedented once other studies have not explored the genotypic combination analysis for ACE and ACE2 polymorphisms and bring perspectives and expectations for dealing with the COVID-19 pandemic based on definitions of genetically-based risk groups within the context of personalized medicine.
Exploration of street space architectural color measurement based on street view big data and deep learning—A case study of Jiefang North Road Street in Tianjin
Authors: Han Xin , Yu Ying , Liu Lei , Li Ming , Wang Lei , Zhang Tianlin , Tang Fengliang , Shen Yingning , Li Mingshuai , Yu Shibao , Peng Hongxu , Zhang Jiazhen , Wang Fangzhou , Ji Xiaomeng , Zhang Xinpeng , Hou Min
Published: November 2023

Urban space architectural color is the first feature to be perceived in a complex vision beyond shape, texture and material, and plays an important role in the expression of urban territory, humanity and style. However, because of the difficulty of color measurement, the study of architectural color in street space has been difficult to achieve large-scale and fine development. The measurement of architectural color in urban space has received attention from many disciplines. With the development and promotion of information technology, the maturity of street view big data and deep learning technology has provided ideas for the research of street architectural color measurement. Based on this background, this study explores a highly efficient and large-scale method for determining architectural colors in urban space based on deep learning technology and street view big data, with street space architectural colors as the research object. We conducted empirical research in Jiefang North Road, Tianjin. We introduced the SegNet deep learning algorithm to semantically segment the street view images, extract the architectural elements and optimize the edges of the architecture. Based on K-Means clustering model, we identified the colors of the architectural elements in the street view. The accuracy of the building color measurement results was cross-sectionally verified by means of a questionnaire survey. The validation results show that the method is feasible for the study of architectural colors in street space. Finally, the overall coordination, sequence continuity, and primary and secondary hierarchy of architectural colors of Jiefang North Road in Tianjin were analyzed. The results show that the measurement model can realize the intuitive expression of architectural color information, and also can assist designers in the analysis of architectural color in street space with the guidance of color characteristics. The method helps managers, planners and even the general public to summarize the characteristics of color and dig out problems, and is of great significance in the assessment and transformation of the color quality of the street space environment.
Finding the best trade-off between performance and interpretability in predicting hospital length of stay using structured and unstructured data
Authors: Jaotombo Franck , Adorni Luca , Ghattas Badih , Boyer Laurent
Published: November 2023

Objective

This study aims to develop high-performing Machine Learning and Deep Learning models in predicting hospital length of stay (LOS) while enhancing interpretability. We compare performance and interpretability of models trained only on structured tabular data with models trained only on unstructured clinical text data, and on mixed data.

Methods

The structured data was used to train fourteen classical Machine Learning models including advanced ensemble trees, neural networks and k-nearest neighbors. The unstructured data was used to fine-tune a pre-trained Bio Clinical BERT Transformer Deep Learning model. The structured and unstructured data were then merged into a tabular dataset after vectorization of the clinical text and a dimensional reduction through Latent Dirichlet Allocation. The study used the free and publicly available Medical Information Mart for Intensive Care (MIMIC) III database, on the open AutoML Library AutoGluon. Performance is evaluated with respect to two types of random classifiers, used as baselines.

Results

The best model from structured data demonstrates high performance (ROC AUC = 0.944, PRC AUC = 0.655) with limited interpretability, where the most important predictors of prolonged LOS are the level of blood urea nitrogen and of platelets. The Transformer model displays a good but lower performance (ROC AUC = 0.842, PRC AUC = 0.375) with a richer array of interpretability by providing more specific in-hospital factors including procedures, conditions, and medical history. The best model trained on mixed data satisfies both a high level of performance (ROC AUC = 0.963, PRC AUC = 0.746) and a much larger scope in interpretability including pathologies of the intestine, the colon, and the blood; infectious diseases, respiratory problems, procedures involving sedation and intubation, and vascular surgery.

Conclusions

Our results outperform most of the state-of-the-art models in LOS prediction both in terms of performance and of interpretability. Data fusion between structured and unstructured text data may significantly improve performance and interpretability.
Link prediction and feature relevance in knowledge networks: A machine learning approach
Authors: Zinilli Antonio , Cerulli Giovanni
Published: November 2023

We propose a supervised machine learning approach to predict partnership formation between universities. We focus on successful joint R&D projects funded by the Horizon 2020 programme in three research domains: Social Sciences and Humanities, Physical and Engineering Sciences, and Life Sciences. We perform two related analyses: link formation prediction, and feature importance detection. In predicting link formation, we consider two settings: one including all features, both exogenous (pertaining to the node) and endogenous (pertaining to the network); and one including only exogenous features (thus removing the network attributes of the nodes). Using out-of-sample cross-validated accuracy, we obtain 91% prediction accuracy when both types of attributes are used, and around 67% when using only the exogenous ones. This proves that partnership predictive power is on average 24% larger for universities already incumbent in the programme than for newcomers (for which network attributes are clearly unknown). As for feature importance, by computing super-learner average partial effects and elasticities, we find that the endogenous attributes are the most relevant in affecting the probability to generate a link, and observe a largely negative elasticity of the link probability to feature changes, fairly uniform across attributes and domains.
Monocyte to Lymphocyte ratio is highly specific in diagnosing latent tuberculosis and declines significantly following tuberculosis preventive therapy: A cross-sectional and nested prospective observational study
Authors: Mayito Jonathan , Meya David B. , Miriam Akia , Dhikusooka Flavia , Rhein Joshua , Sekaggya-Wiltshire Christine
Published: November 2023

Background

Interferon-gamma release assay and tuberculin skin test use is limited by costly sundries and cross-reactivity with non-tuberculous mycobacteria and Bacille Calmette-Guérin (BCG) vaccination respectively. We investigated the Monocyte to Lymphocyte ratio (MLR) as a biomarker to overcome these limitations and for use in monitoring response to tuberculosis preventive therapy (TPT).

Methods

We conducted a cross-sectional and nested prospective observational study among asymptomatic adults living with Human Immuno-deficiency Virus (HIV) in Kampala, Uganda. Complete blood count (CBC) and QuantiFERON-TB® Gold-plus were measured at baseline and CBC repeated at three months. Multivariable logistic regression was performed to identify factors associated with a high MLR and decline in MLR.

Results

We recruited 110 adults living with HIV and on antiretroviral therapy, of which 82.5% (85/110) had suppressed viral loads, 71.8% (79/110) were female, and 73.6% (81/110) had a BCG scar. The derived MLR diagnostic cut-off was 0.35, based on which the MLR sensitivity, specificity, positive predictive value, and negative predictive value were 12.8%, 91.6%, 45.5%, and 65.7% respectively. The average MLR declined from 0.212 (95% CI: 0.190–0.235) at baseline to 0.182 (95% CI: 0.166–0.198) after three months of TPT. A viral load of >50 copies/ml (aOR, 5.67 [1.12–28.60]) was associated with a high MLR while that of <50 copies/ml (aOR, 0.07 [0.007–0.832]) was associated with a decline in MLR.

Conclusion

MLR was highly specific in diagnosing latent TB and declined significantly following three months of TPT. Implications of a high MLR and decline in MLR after TPT need further evaluation in a larger cohort.
The possible impact of escaped captive American mink (Neogale vison) on the population of feral mink in Denmark
Authors: Andersen Tobias Astell , Rørbæk René Worup , Pertoldi Cino , Pagh Sussie
Published: November 2023

The Danish feral mink (Neogale vison) population can be divided into wild-born and captive-born mink newly escaped from a farm. The impact of the captive-born mink on the population of feral population is unknown. Captive-born mink has lately been estimated to make up 25–30% of the feral mink population. In December 2020 Danish mink farms were decommissioned until January 2023. The aim of this study was to: 1) Examine whether a supplementation of farmed mink into the feral mink population influence the population growth and extinction rate of the feral mink, 2) Investigate which parameters affect the viability in feral mink populations the most. The age and mortality of 351 mink and the reproduction of 85 adult females culled by hunters from 2019–2022 were determined in three distinct geographic areas of Denmark (Jutland, Zealand, and Bornholm). VORTEX simulations were used to model the population viability and to simulate the impact of a supplementation of captive-born mink into the wild population. Simulations show that changes by 30% in the parameters: fecundity, percentages of breeding females and mortality influenced population size influenced the final population size significantly. The initial population size and inbreeding did not affect the population growth significantly. The simulations showed that the mink population in the regions of Jutland and Zealand could go extinct within 15 to 30 years without any supplementation of captive-born mink to the feral population. The population on Bornholm will however remain stable with current levels of mortality and reproduction even without supplementation of captive mink.
The feasibility of using ecological momentary assessment to understand urinary and fecal incontinence experiences in adults with spina bifida: A 30-day study
Authors: Hensel Devon J. , Young Audrey I. , Szymanski Konrad M.
Published: November 2023

In this paper, we evaluate the feasibility of using ecological momentary assessment (EMA) to understand urinary (UI) and fecal (FI) incontinence in adults with spina bifida (SB). As part of a larger 30-day prospective study to understand the incontinence in adults with SB (N = 89), participants completed end-of-day EMA diaries assessing the frequency and context of UI and FI. We used these data to assess the method feasibility across six dimensions: (a) compliance, or data entry which is consistent with study protocol and substantially complete; (b) reactivity, or behavior change attributed to study participation; (c) participant acceptability, or convenience and ease of method beneficial to compliance; (d) data capture, or the volume of incontinence behaviors collected; (e) the accuracy of incontinence reports; and f) participant-provided feedback for future studies. Participants were highly compliant with diary entry protocol and schedule: submitting 95.7% (2576/2700) of the expected total daily entries. The average completion time was two minutes. Neither the total number of submissions nor the completion time varied by demographic characteristics or health history. A sufficient volume of incontinence and affective outcomes were captured, with small downtrends in reporting of UI and affect over time. Exit survey recall was highly correlated with diary reports. Participants found the methodology to be acceptable, reported their experiences honestly, enjoyed and felt comfortable participating in the study and would engage in similar study in the future. Accurate information about the daily context of UI and FI is a key factor in the success of intervention or education programs relying on this information. Our findings demonstrate that EMA is a feasible way to describe UI and FI in adults with SB.
Feeling heard: Operationalizing a key concept for social relations
Authors: Roos Carla Anne , Postmes Tom , Koudenburg Namkje
Published: November 2023

Feeling heard is considered a cornerstone of close relationships and crucial to healthy self-development, but psychologically, this sentiment of feeling heard remains understudied. The current paper therefore aims to define and measure the experience of feeling heard. Based on an integrative literature review, feeling heard is conceptualized as consisting of five components at two conceptual levels. At the interpersonal level people feel heard when they have 1) voice, and receive 2) attention, 3) empathy, 4) respect. At the collective level people should experience 5) common ground. In two population surveys (N= 194,N= 1000), we find that feeling heard is a unitary concept, and we develop and validate the feeling heard scale (FHS); a concise eight-item scale with good psychometric properties. Results show that the FHS is a distinct predictor of conversation intentions in many different contexts and relationships. In fact, the FHS is the strongest predictor of intentions for conflict behavior among a set of 15 related variables (e.g., acquaintance, intimacy). We conclude by reflecting on the potential applications of this scale: in interpersonal relations and professional contacts, the FHS enables the assessment of one crucial dimension of social interaction.
The indole motif is essential for the antitrypanosomal activity of N5-substituted paullones
Authors: Ihnatenko Irina , Müller Marco J. , Orban Oliver C. F. , Lindhof Jens C. , Benítez Diego , Ortíz Cecilia , Dibello Estefanía , Seidl Leonardo L. , Comini Marcelo A. , Kunick Conrad
Published: November 2023

Severe infections with potentially fatal outcomes are caused by parasites from the genera Trypanosoma and Leishmania (class Kinetoplastea). The diseases affect people of remote areas in the tropics and subtropics with limited access to adequate health care. Besides insufficient diagnostics, treatment options are limited, with tenuous developments in recent years. Therefore, new antitrypanosomal antiinfectives are required to fight these maladies. In the presented approach, new compounds were developed and tested on the target trypanothione synthetase (TryS). This enzyme is crucial to the kinetoplastids’ unique trypanothione-based thiol redox metabolism and thus for pathogen survival. Preceding studies have shown that N5-substituted paullones display antitrypanosomal activity as well as TryS inhibition. Herein, this compound class was further examined regarding the structure-activity relationships (SAR). Diverse benzazepinone derivatives were designed and tested in cell-based assays on bloodstream Trypanosoma brucei brucei (T. b. brucei) and intracellular amastigotes of Leishmania infantum (L. infantum) as well as in enzyme-based assays on L. infantum TryS (LiTryS) and T. b. brucei TryS (TbTryS). While an exchange of just the substituent in the 9-position of paullones led to potent inhibitors on LiTryS and T. b. brucei parasites, new compounds lacking the indole moiety showed a total loss of activity in both assays. Conclusively, the indole as part of the paullone structure is pivotal for keeping the TryS inhibitory and antitrypanosomal activity of this substance class.
Bacillus subtilis engineered for topical delivery of an antifungal agent
Authors: Montgomery Veronica A. , Cain Ethan , Styczynski Mark P. , Prausnitz Mark R.
Published: November 2023

Fungal skin infections are a common condition affecting 20–25 percent of the world population. While these conditions are treatable with regular application of an antifungal medication, we sought to develop a more convenient, longer-lasting topical antifungal platform that could increase patient adherence to treatment regimens by using Bacillus subtilis, a naturally antifungal bacteria found on the skin, for drug production and delivery. In this study, we engineered B. subtilis for increased production of the antifungal lipopeptide iturin A by overexpression of the pleiotropic regulator DegQ. The engineered strain had an over 200% increase in iturin A production as detected by HPLC, accompanied by slower growth but the same terminal cell density as determined by absorbance measurements of liquid culture. In an in vitro antifungal assay, we found that despite its higher iturin A production, the engineered strain was less effective at reducing the growth of a plug of the pathogenic fungus Trichophyton mentagrophytes on an agar plate compared to the parent strain. The reduced efficacy of the engineered strain may be explained by its reduced growth rate, which highlights the need to address trade-offs between titers (e.g. measured drug production) and other figures of merit (e.g. growth rate) during metabolic engineering.
Availability and price of fruits and vegetables in the surroundings of food and nutrition public establishments
Authors: Paiva Gabriela Gomes de , Claro Rafael Moreira , Costa Bruna Vieira de Lima
Published: November 2023

Background

Inequalities of access to healthy food reinforce the need to strengthen public policies on Food and Nutritional Security. In this context, Food and Nutrition Public Establishments, which are public spaces for distribution and commercialization of healthy foods, stand out. However, in middle-income countries there is little monitoring of the impacts of public policies on food environments, which are fundamental for strengthening these actions. Thus, the purpose of the study was to evaluate the availability and price of fruits and vegetables in areas with and without Food and Nutrition Public Establishments.

Methodology

A cross-sectional study carried out in Belo Horizonte, Brazil. Audits were conducted in the retail food environment of a representative sample of Food and Nutrition Public Establishments (n = 10) and corresponding census sectors, without Food and Nutrition Public Establishments (n = 10). Information was collected on the availability and price of the most consumed fruits and vegetables in Belo Horizonte. The food retailers were grouped into fresh food retailers and mixed food retailers. The Chi-Square test was used to compare the availability of fruits and vegetables between areas. The Mann Whitney test was used to compare the prices of fruit and vegetables and the price differences between fresh food retailers and mixed food retailers between areas.

Results

148 food retailers were audited, including 17 Food and Nutrition Public Establishments. In fresh food retailers, the availability of vegetables was higher in areas with Food and Nutrition Public Establishments (p = 0.024). In mixed food retailers there was low availability of fruit and vegetables in both areas (34.0% vs. 26.2%; p>0.05). The price difference between fresh food retailers and mixed food retailers differed significantly between areas (p<0.001). In general, fresh food retailers had lower prices than mixed food retailers only in areas with Food and Nutrition Public Establishments.

Conclusions

The presence of Food and Nutrition Public Establishments was associated with the availability of vegetables, and with lower prices in fresh food retailers compared with mixed food retailers. Monitoring and understanding the impacts of public policies on the food environment are essential to register trends and provide relevant information to civil society and government authorities.
A novel objective for improving the sustainability of water supply system regarding hydrological response
Authors: Moudi Mahdi , Gai Qiuyan , Yuan He , Guiqing Li , Basirialmahjough Mahdi , Motamedi Artemis , Galoie Majid
Published: November 2023

In general, the sustainability of the water supply system is indicative of an adaptive operational approach, wherein the decision-maker adjusts the system’s performance based on the availability of water resources in a given time frame. In light of this, a novel framework is proposed in this study to evaluate sustainability, including three key indicators: resilience, reliability, and vulnerability. To address stressors that may lead to system failure, a multisectoral water allocation optimization is undertaken. In order to account for the future implications of climate change on the hydrological cycle, a simulation step, is incorporated, utilizing the Soil and Water Assessment Tool (SWAT) under various emission scenarios (RCP4.5 and RCP8.5), prior to integrating the streamflow data into our proposed optimal framework. To calibrate and validate historical data (2014–2019) and simulate future streamflow patterns (2025–2085), the Sistan Basin, located in an arid region of Iran, is analyzed as a case study. In light of the anticipated adverse impacts on the water supply system, certain adaptation measures, such as demand shrinkage scenarios, are considered to further appraise the proposed framework. Based on the final output, it is evident that the agricultural and industrial sectors, being the primary water consumers, are more susceptible to negative impacts resulting from the reduction in system sustainability. This susceptibility is primarily attributed to their highest vulnerability and comparatively lower reliability.
Regular exercise attenuates alcoholic myopathy in zebrafish by modulating mitochondrial homeostasis
Authors: Wen Wei , Guo Cheng , Chen Zhanglin , Yang Dong , Zhu Danting , Jing Quwen , Zheng Lan , Sun Chenchen , Tang Changfa
Published: November 2023

Alcoholic myopathy is caused by chronic consumption of alcohol (ethanol) and is characterized by weakness and atrophy of skeletal muscle. Regular exercise is one of the important ways to prevent or alleviate skeletal muscle myopathy. However, the beneficial effects and the exact mechanisms underlying regular exercise on alcohol myopathy remain unclear. In this study, a model of alcoholic myopathy was established using zebrafish soaked in 0.5% ethanol. Additionally, these zebrafish were intervened to swim for 8 weeks at an exercise intensity of 30% of the absolute critical swimming speed (Ucrit), aiming to explore the beneficial effects and underlying mechanisms of regular exercise on alcoholic myopathy. This study found that regular exercise inhibited protein degradation, improved locomotion ability, and increased muscle fiber cross-sectional area (CSA) in ethanol-treated zebrafish. In addition, regular exercise increases the functional activity of mitochondrial respiratory chain (MRC) complexes and upregulates the expression levels of MRC complexes. Regular exercise can also improve oxidative stress and mitochondrial dynamics in zebrafish skeletal muscle induced by ethanol. Additionally, regular exercise can activate mitochondrial biogenesis and inhibit mitochondrial unfolded protein response (UPRmt). Together, our results suggest regular exercise is an effective intervention strategy to improve mitochondrial homeostasis to attenuate alcoholic myopathy.
BioDiscViz: A visualization support and consensus signature selector for BioDiscML results
Authors: Bouirdene Sophiane , Leclercq Mickael , Quitté Léopold , Bilodeau Steve , Droit Arnaud
Published: November 2023

Machine learning (ML) algorithms are powerful tools to find complex patterns and biomarker signatures when conventional statistical methods fail to identify them. While the ML field made significant progress, state of the art methodologies to build efficient and non-overfitting models are not always applied in the literature. To this purpose, automatic programs, such as BioDiscML, were designed to identify biomarker signatures and correlated features while escaping overfitting using multiple evaluation strategies, such as cross validation, bootstrapping and repeated holdout. To further improve BioDiscML and reach a broader audience, better visualization support and flexibility in choosing the best models and signatures are needed. Thus, to provide researchers with an easily accessible and usable tool for in depth investigation of the results from BioDiscML outputs, we developed a visual interaction tool called BioDiscViz. This tool provides summaries, tables and graphics, in the form of Principal Component Analysis (PCA) plots, UMAP, t-SNE, heatmaps and boxplots for the best model and the correlated features. Furthermore, this tool also provides visual support to extract a consensus signature from BioDiscML models using a combination of filters. BioDiscViz will be a great visual support for research using ML, hence new opportunities in this field by opening it to a broader community.
Fractional-order numerical modeling to study chloride ion transport in concrete with fly ash or slag additions
Authors: Zhou Li , Huang Guangdong , Chen Ruige
Published: November 2023

To better study the chloride ion migration in concrete with fly ash or ground granulated blast furnace slag under low fatigue load, a Caputo time fractional-order chloride diffusion model is developed in this paper. The model, grounded in Fick’s second law with a fractional-order derivative, employs an implicit numerical method for discretization, resulting in a fractional-order numerical scheme. The stability and convergence of the scheme are rigorously proven within the paper. The model’s unknown parameters are estimated using genetic algorithm with a grid method. To validate the model’s effectiveness, its numerical solution is juxtaposed with experimental results from chloride erosion studies. Furthermore, the fitting efficacy of the Caputo time fractional-order numerical scheme is compared with that of the classical Fick’s second law numerical scheme and analytical solution. The research findings demonstrate that the fractional-order numerical scheme can more accurately simulate the chloride concentration in concrete containing fly ash or slag. Additionally, the model shows promise in predicting the service life of fly ash or slag concrete.
Sex-dimorphic expression of extracellular matrix genes in mouse bone marrow neutrophils
Authors: McGill Cassandra J. , Ewald Collin Y. , Benayoun Bérénice A.
Published: November 2023

The mammalian innate immune system is sex-dimorphic. Neutrophils are the most abundant leukocyte in humans and represent innate immunity’s first line of defense. We previously found that primary mouse bone marrow neutrophils show widespread sex-dimorphism throughout life, including at the transcriptional level. Extracellular matrix [ECM]-related terms were observed among the top sex-dimorphic genes. Since the ECM is emerging as an important regulator of innate immune responses, we sought to further investigate the transcriptomic profile of primary mouse bone marrow neutrophils at both the bulk and single-cell level to understand how biological sex may influence ECM component expression in neutrophils throughout life. Here, using curated gene lists of ECM components and unbiased weighted gene co-expression network analysis [WGCNA], we find that multiple ECM-related gene sets show widespread female-bias in expression in primary mouse neutrophils. Since many immune-related diseases (e.g., rheumatoid arthritis) are more prevalent in females, our work may provide insights into the pathogenesis of sex-dimorphic inflammatory diseases.
Comparative analysis of infertility healthcare utilization before and after insurance coverage of assisted reproductive technology: A cross-sectional study using National Patient Sample data
Authors: Lee Han-Sol , Lim Yu-Cheol , Kim Dong-Il , Park Kyoung-Sun , Lee Yoon Jae , Ha In-Hyuk , Lee Ye-Seul
Published: November 2023

This study aims to analyze the types and cost of infertility care provided in a clinical setting to examine the changes of healthcare utilization for infertility after the 2017 launch of assisted reproductive technology (ART) health insurance coverage in South Korea. Health Insurance Review Assessment—National Patient Sample data from 2016 and 2018 were analyzed comparatively. Data related to receiving medical service under the International Classification of Diseases 10th revision code N97 (female infertility) or N46 (male infertility) at least once were analyzed, including patients’ characteristics and healthcare utilization (type of healthcare facility and treatment approach). Between 2016 and 2018, the percentage of patients aged 30–34 receiving infertility care dropped; the percentages of patients in older age groups increased. The number of female patients remained comparable, whereas the number of male patients increased by 23%. Average visits per patient increased by about 1 day from 2016 to 2018. Total annual infertility care claim cost increased from $665,391.05 to $3,214,219.48; the per-patient annual cost increased from $114.76 to $522.38. The number of claims and cost of treatment and surgery increased markedly, as did the number of claims and cost of gonadotropins. With its focus on health insurance coverage of ART and results demonstrating increases in medical services, medications, cost, and patient utilization, this study reveals the significant effects of national health policies on the treatment, cost, and management of infertility.
MLpronto: A tool for democratizing machine learning
Authors: Tjaden Jacob , Tjaden Brian
Published: November 2023

The democratization of machine learning is a popular and growing movement. In a world with a wealth of publicly available data, it is important that algorithms for analysis of data are accessible and usable by everyone. We present MLpronto, a system for machine learning analysis that is designed to be easy to use so as to facilitate engagement with machine learning algorithms. With its web interface, MLpronto requires no computer programming or machine learning background, and it normally returns results in a matter of seconds. As input, MLpronto takes a file of data to be analyzed. MLpronto then executes some of the more commonly used supervised machine learning algorithms on the data and reports the results of the analyses. As part of its execution, MLpronto generates computer programming code corresponding to its machine learning analysis, which it also supplies as output. Thus, MLpronto can be used as a no-code solution for citizen data scientists with no machine learning or programming background, as an educational tool for those learning about machine learning, and as a first step for those who prefer to engage with programming code in order to facilitate rapid development of machine learning projects. MLpronto is freely available for use at https://mlpronto.org/.
Correlates of never testing for HIV among men who have sex with men in Malaysia: A cross-sectional study
Authors: JadKarim Luzan , Wickersham Jeffrey , Gautam Kamal , Azwa Iskandar , Saifi Rumana , Khati Antoine , Paudel Kiran , Ha Toan , Shrestha Roman
Published: November 2023

Introduction

HIV testing uptake remains very low among men who have sex with men (MSM) in Malaysia, a subgroup still bearing a disproportionate HIV burden. Therefore, we sought to identify and measure factors associated with never-testing for HIV among Malaysian MSM to further characterize this subgroup and inform future public health interventions addressing low testing rates in the country.

Methods

We conducted a cross-sectional online survey among Malaysian MSM (August to September 2021). Participants completed questionnaires, including socio-demographic characteristics, HIV/STI testing practices, drug- and sex-related behaviors, and knowledge and attitudes toward HIV prevention services. Out of 1,799 completed surveys, 870 were included in the analysis after eliminating duplicates and incomplete surveys. We used logistic regression to determine factors associated with never-testing for HIV.

Results

Overall, one-third of the study participants (33.8%) reported having never tested for HIV. Of those who reported to have tested for HIV (n = 576), half reported that they had tested for HIV in the past 6 months (50.3%). In multivariable logistic regression, MSM with HIV sero-concordant partner (aOR = 3.44, 95% CI = 1.56–7.60), without a prior diagnosis of a sexually transmitted infection (aOR = 2.83, 95% CI = 1.46–5.49), unaware of pre-exposure prophylaxis (PrEP; aOR = 2.71, 95% CI = 1.74–4.21), unaware of someone taking PrEP (aOR = 1.64, 95% CI = 1.15–2.35), and unwilling to use PrEP (aOR = 2.48, 95% CI = 1.43–4.30) had higher odds of never been tested for HIV. In contrast, MSM who were older (aOR = 0.95, 95% CI = 0.93–0.97) and of the Malaya ethnic group (aOR = 0.59, 95% CI = 0.37–0.95) had lower odds of never testing for HIV.

Conclusion

Our findings shed light on the characteristics of HIV never-testers among MSM in Malaysia. The results indicate the need for innovative strategies to increase the uptake of HIV testing services among members of the MSM community.
Open reproducible scientometric research with Alexandria3k
Authors: Spinellis Diomidis
Published: November 2023

Considerable scientific work involves locating, analyzing, systematizing, and synthesizing other publications, often with the help of online scientific publication databases and search engines. However, use of online sources suffers from a lack of repeatability and transparency, as well as from technical restrictions. Alexandria3k is a Python software package and an associated command-line tool that can populate embedded relational databases with slices from the complete set of several open publication metadata sets. These can then be employed for reproducible processing and analysis through versatile and performant queries. We demonstrate the software’s utility by visualizing the evolution of publications in diverse scientific fields and relationships among them, by outlining scientometric facts associated with COVID-19 research, and by replicating commonly-used bibliometric measures and findings regarding scientific productivity, impact, and disruption.
Effect of binocular vision during target shooting in archery
Authors: Hirota Masakazu , Hanai Tatsuhiro , Morimoto Takeshi
Published: November 2023

Purpose

This study aimed to evaluate the difference between binocular and monocular vision and eye movements during the competition using video-oculography (VOG).

Methods

Experiment 1 included 14 participants to evaluate differences in arrow convergence. Then, seven participants in Experiment 1 were randomly selected and included in Experiment 2, which evaluated eye movements during archery using VOG. The target used an 80-cm waterproof target face and was set at a distance of 30 m. All players shot the target 36 times using their bows and arrows. Experiments 1 and 2 evaluated the distribution of arrows in each score and the number of focus points, respectively, between binocular and monocular conditions.

Results

The arrows, which include the area of 9 points, were significantly greater in the binocular condition (11.85 ± 5.04 shots) than in the monocular condition (9.36 ± 5.41 shots) in Experiment 1 (P = 0.047). The players focused on the target under both binocular and monocular conditions, although the players were switching off fixation between the target and shooting sight under the binocular condition in Experiment 2.

Conclusion

These behaviors indicated that the players were trying to accurately shoot the target by exploring the distance between themselves and the target as a cue for depth perception.
In vitro antiproliferative and apoptotic effects of thiosemicarbazones based on (-)-camphene and R-(+)-limonene in human melanoma cells
Authors: Soares Paula Roberta Otaviano , Passos Débora Cristina Souza , da Silva Francielly Moreira , da Silva-Giardini Ana Paula B. , Coelho Narcimário Pereira , de Oliveira Cecília Maria Alves , Kato Lucília , da Silva Cleuza Conceição , Guillo Lidia
Published: November 2023

A series of 38 thiosemicarbazone derivatives based on camphene and limonene were evaluated for their antiproliferative activity. Among them, 19 were synthesized and characterized using proton and carbon-13 nuclear magnetic resonance (1H and 13C NMR). For initial compound selection, human melanoma cells (SK-MEL-37) were exposed to a single concentration of a compound (100 μM) for 24, 48, and 72 hours, and cell detachment was visually observed. Cell viability was determined using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) method. Nineteen compounds (4, 6, 8, 11, 13, 14, 15, 16, 17, 18, 20, 22, 25, 26, 31, 3’, 4’, 6’, and 9’) yielded cell viability below 20%. Subsequently, IC50 values for these compounds were determined, ranging from 11.56 to 55.38 μM, after 72 hours of treatment. Compound 17 (o-hydroxybenzaldehyde (-)-camphene-based thiosemicarbazone) demonstrated the lowest IC50 value, followed by compound 4 (benzaldehyde (-) camphene-based thiosemicarbazone) at 12.84 μM. Regarding compound 4, we observed the induction of a characteristic ladder pattern of DNA fragmentation through gel electrophoresis. Furthermore, fluorescence, flow cytometry and scanning microscopy assays revealed morphological changes consistent with apoptosis induction. Additionally, the measurement of caspase 6 and 8 activity in cellular extracts after treatment for 2, 4, 6, and 24 hours suggested the potential involvement of the extrinsic apoptosis pathway in the mechanism of action of compound 4. Further investigations, including molecular docking studies, are required to fully explore the potential of compound 4 and the other selected compounds, highlighting their promising role in future melanoma therapy research.
The role of primary care providers in testing for sexually transmitted infections in the MassHealth Medicaid program
Authors: Mick Eric O. , Sabatino Meagan J. , Alcusky Matthew J. , Eanet Frances E. , Pearson William S. , Ash Arlene S.
Published: November 2023

The objective of this study was to determine the prevalence and predictors of testing for sexually transmitted infections (STIs) under an accountable care model of health care delivery. Data sources were claims and encounter records from the Massachusetts Medicaid and Children’s Health Insurance Program (MassHealth) for enrollees aged 13 to 64 years in 2019. This cross-sectional study examines the one-year prevalence of STI testing and evaluates social determinants of health and other patient characteristics as predictors of such testing in both primary care and other settings. We identified visits with STI testing using procedure codes and primary care settings from provider code types. Among 740,417 members, 55% were female, 11% were homeless or unstably housed, and 15% had some level of disability. While the prevalence of testing in any setting was 20% (N = 151,428), only 57,215 members had testing performed in a primary care setting, resulting in an 8% prevalence of testing by primary care clinicians (PCCs). Members enrolled in a managed care organization (MCO) were significantly less likely to be tested by a primary care provider than those enrolled in accountable care organization (ACO) plans that have specific incentives for primary care practices to coordinate care. Enrollees in a Primary Care ACO had the highest rates of STI testing, both overall and by primary care providers. Massachusetts’ ACO delivery systems may be able to help practices increase STI screening with explicit incentives for STI testing in primary care settings.
Analyzing game statistics and career trajectories of female elite junior tennis players: A machine learning approach
Authors: Bozděch Michal , Zháněl Jiří
Published: November 2023

Tennis is a popular and complex sport influenced by various factors. Early training increases the risk of career dropout before peak performance. This study analyzed game statistics of World Junior Tennis Final participants (2012–2016), their career paths and it examined how game statistics impact rankings of top 300 female players, aiming to develop an accurate model using percentage-based variables. Descriptive and inferential statistics, including neural networks, were employed. Four machine learning models with categorical predictors and one response were created. Seven models with up to 18 variables and one ordinal (WTA rank) were also developed. Tournament rankings could be predicted using categorical data, but not subsequent professional rankings. Although effects on rankings among top 300 female players were identified, a reliable predictive model using only percentage-based data was not achieved. AI models provided insights into rankings and performance indicators, revealing a lower dropout rate than reported. Participation in elite junior tournaments is crucial for career development and designing training plans in tennis. Further research should explore game statistics, dropout rates, additional variables, and fine-tuning of AI models to improve predictions and understanding of the sport.