bluuebunny/crossref_metadata_2025 huggingface dataset:
The impact of health promotion training on university students’ health perceptions, healthy lifestyle behaviors, and risky behaviors
Authors: Çol Bahar Kefel¡ , Başaran Ayşe Gümüşler , Köse Burcu Genç
Published: December 2024

Introduction

University period is a critical developmental stage in which health-related behaviors that will be effective throughout life are acquired. This study aims to to evaluate the effect of health promotion education given touniversity students on health perception, health behaviors and risky behaviors, to investigate the impact of the demographic characteristics of the participants on these three variables, and to investigate the potential relationship between the three variables.

Methods

It is a quasi-experimental study using a pre-post test design This study was conducted with 179 students. The Health Perception Scale, the Healthy Lifestyle Behaviors Scale, and the Risky Behaviors Scale were used to collect the data. A 7-week training program was implemented, and the post-training evaluation was made after 3 months. Percentage, mean, standard deviation, Mann–Whitney U, Kruskal-Wallis, Wilcoxon analysis, and Spearmen Correlation analysis were used to analyze the data.

Results

After health promotion training, it was determined that health perception and healthy lifestyle behaviors increased and risky behaviors decreased. A significant negative relationship was found between health perception after training and antisocial behavior, suicidal tendencies and dropping out of school. A significant negative relationship was found between healthy lifestyle habits and antisocial behavior, suicidal tendencies and school dropout. A positive significant relationship was determined between health perception and healthy lifestyle behaviors. The results of this study provide evidence of the effectiveness of training interventions in improving healthy lifestyle behaviors and health perception and reducing risky behaviors.

Discussion

The results support the planning of training programs to promote health on campuses. It also shows the effectiveness of training programs in preventing antisocial behavior, suicidal tendencies and school dropout.
Facing the fear: a narrative review on the potential of pressure training in music
Authors: de Bie Nicky , Hill Yannick , Pijpers J. R. (Rob) , Oudejans Raôul R. D.
Published: December 2024

Music performance anxiety (MPA) is one of the most reported psychological problems among musicians, posing a significant threat to the optimal performance, health, and psychological wellbeing of musicians. Most research on MPA treatment has focused on reducing symptoms of performance anxiety, but complete “cures” are uncommon. A promising addition or alternative that may help musicians enhance their performance under pressure, despite their anxiety, is pressure training (PT). In other high-pressure domains, such as sports and police work, pressure training has been proven effective in reducing choking and enhancing performance quality under pressure. Therefore, the aim of this narrative review is to explore the potential of pressure training in music settings. Specifically, we first provide a theoretical overview of current models explaining performance declines due to anxiety. Second, we discuss the current state of research on the effectiveness and application of pressure training in sports and police work as well as recent developments in pressure training interventions for music settings. While there is a limited number of studies investigating the effectiveness of pressure training on musicians' performance quality, research focusing on musicians' experiences has shown that pressure training can be particularly beneficial for enhancing performance skills, preparing for performances, and managing performance anxiety. Based on the reviewed literature, the final section points out suggestions for future research as well as recommendations for musicians, teachers, and music institutions for practical applications.
The substance use profiles of adults who sought mental health and addiction services through a centralized intake process in Nova Scotia (2020–2021)
Authors: Soboka Matiwos , Tibbo Philip G. , Stewart Sherry H. , Simon Patryk , Wang JianLi
Published: December 2024

Background

Despite the increasing substance use in Canada, our understanding of how substance use varies based on the intersections of gender, ethnicity/race, and income sources among preclinical populations remains limited. Thus, this study aimed to investigate, among clients of mental health and addiction (MHA) intake in Nova Scotia: 1) the prevalence of substance use by gender, ethnicity, and income source; 2) the routes of substance administration; 3) factors associated with substance use. Understanding how gender, ethnicity, and income sources intersect to influence substance use patterns is essential for designing prevention and treatment strategies tailored to an individual’s unique needs. Additionally, exploring the various routes of substance administration can provide insight into potential health risks, helping to inform harm reduction strategies.

Methods

This cross-sectional study included 22,500 adults who contacted MHA central intake in Nova Scotia in 2020 and 2021. Clients were assessed for substance use, substance use frequency, route of substance administration, and mental and physical health problems. The prevalence of substance use was examined as a function of gender, ethnicity, and income source. Multinomial logistic regression was used to investigate factors associated with substance use.

Results

Among the included MHA Intake clients, 36.1% reported daily substance use. The highest prevalence of daily substance use was identified among homeless (69.7%) and non-White men on social assistance/disability (60.9%). Also, non-White individuals on social assistance/disability were more likely to engage in frequent (aOR = 2.66, 95% =1.64, 4.30) and daily (aOR = 2.82, 95% CI: 2.08, 3.82) substance use compared to White individuals. Being young (aged 19-29), lack of access to private insurance, current/past mental illness, moderate/high suicide risk, and presence of two or more psychosocial stressors, were associated with occasional, frequent, and daily substance use alike.

Conclusions

The high prevalence of daily substance use among MHA Intake service users in Nova Scotia highlights the need for prevention and treatment strategies to address individual and structural level factors contributing to daily substance use.
Unemployment and mental health: a global study of unemployment’s influence on diverse mental disorders
Authors: Yang Yang , Niu Lisi , Amin Saqib , Yasin Iftikhar
Published: December 2024

Introduction

Globally, one in five individuals faces unemployment, which substantially increases their risk of developing mental disorders. Understanding the relationship between unemployment and specific mental health outcomes is crucial for formulating effective policy interventions.

Methods

This study examines the relationship between unemployment and mental disorders across 201 countries from 1970 to 2020. Using a fixed-effects model, we analyze the impact of unemployment on various mental health outcomes, including anxiety, depression, bipolar disorder, drug use, and eating disorders, with a focus on demographic variations.

Results

The analysis reveals a significant positive association between unemployment and mental disorders, particularly anxiety, depression, and bipolar disorder. Moreover, distinct patterns emerge, linking unemployment to higher rates of drug use and eating disorders in specific demographics.

Discussion

These findings underscore the critical interplay between socio-economic factors and mental health, highlighting the need for proactive strategies to address the dual burden of unemployment and mental health disorders. Targeted interventions, such as employment support programs and accessible mental health services, are essential to improve global mental health outcomes. These initiatives can also alleviate the economic burden of unemployment by boosting workforce participation and productivity. Long-term economic gains may offset the increased healthcare expenditures associated with mental health support.
The effect of activities of daily living on anxiety in older adult people: the mediating role of social participation
Authors: Zheng Juan , Xu Jianqiang , Liu Daqi
Published: December 2024

Objective

Anxiety is a serious psychiatric illness in older adult people. Activities of daily living and social participation are important factors influencing anxiety in older adult people. Using social participation as a mediating variable, this study explored the influence of activities of daily living on anxiety in older adult people to provide scientific evidence for improving the psychological health of older adult people.

Methods

A multistage stratified random sampling method was used in this study to recruit older adult people. T tests and variance analysis were used for single factor analysis, and a multiple linear regression model was used for multifactor analysis. Pearson correlation analysis was used to study the correlation between activities of daily living and social participation and anxiety. The Process program was used to perform the bootstrap test.

Results

The mean anxiety score of the interviewed older adult individuals was 3.028 ± 4.606 points, and 28.66% of the older adult individuals had anxiety. There was a statistically significant difference in the anxiety scores of older adult people across sex, age, marital status, education level, and health insurance status (p < 0.05). After controlling for other variables, each one-point increase in the activities of daily living score significantly increased the anxiety score by 0.122 points (𝛽=0.122, p < 0.001), and each one-point increase in the social participation score significantly decreased the anxiety score by 0.058 points (𝛽= − 0.058, p < 0.001). According to the results of the mediating effect analysis, there was a significant positive relationship between activities of daily living and anxiety, and the total effect was established (𝛽=0.1719, p < 0.001). After controlling for social participation, there was a significant direct effect of activities of daily living on anxiety in older adult people (𝛽=0.1255, p < 0.001). A partial mediating effect of social participation on the relationship between activities of daily living and anxiety in older adult people was found. The indirect effect of social participation was 26.99%.

Conclusion

Activities of daily living and social participation are important factors affecting anxiety in older adult people. Health education should be increased to enhance the physical activity of older adult people to improve their activities of daily living, create a good atmosphere for their social participation, improve their motivation for and continuity of social participation.
A synthetic segmentation dataset generator using a 3D modeling framework and raycaster: a mining industry application
Authors: Kilian Wilhelm Johannes , Prinsloo Jaco , Vosloo Jan , Taljaard Stéphan
Published: December 2024

Many industries utilize deep learning methods to increase efficiency and reduce costs. One of these methods, image segmentation, is used for object detection and recognition in localization and mapping. Segmentation models are trained using labeled datasets; however, manually creating datasets for every application, including deep-level mining, is time-consuming and typically expensive. Recently, many papers have shown that using synthetic datasets (digital recreations of real-world scenes) for training produces highly-accurate segmentation models. This paper proposes a synthetic segmentation dataset generator using a 3D modeling framework and raycaster. The generator was applied to a deep-level mining case study and produced a dataset containing labeled images of scenes typically found in this environment, therefore removing the requirement to create the dataset manually. Validation showed high accuracy segmentation after model training using the generated dataset (compared to other applications that use real-world datasets). Furthermore, the generator can be customized to produce datasets for many other applications.
Disparities in PrEP use and unmet need across PEPFAR-supported programs: doubling down on prevention to put people first and end AIDS as a public health threat by 2030
Authors: Mukherjee Trena I. , Yep Mitchell , Koluch Megan , Abayneh Sisay Alemayehu , Eyassu Gizachew , Manfredini Elizabeth , Herbst Sara
Published: December 2024

Background

In 2023, an estimated 1.3 million people newly acquired HIV. In the same year, 3.5 million individuals received pre-exposure prophylaxis (PrEP), falling short of the UNAIDS target of 21.2 million by 2025. With over 90% of global PrEP programming supported by PEPFAR, a better understanding of disparities in PrEP provision is needed to inform PEPFAR's approach to reach and deliver prevention services and achieve UNAIDS 95-95-95 goals in all populations by 2025. The objective of this paper is to assess unmet PrEP need in PEPFAR-supported countries.

Methods

We analyzed FY2023 Monitoring, Evaluation, and Reporting (MER) results from 48 PEPFAR-supported countries to calculate PrEP-to-need ratios (PnR) by geography and population. PnR offers an ecological measure to identify disparities and missed opportunities for PrEP programming. PnR was calculated as the ratio of PrEP users to the number of positive HIV tests. PrEP users are defined through new initiations (PrEP_NEW) and re-initiations or continuation (PrEP_CT). HTS_TST_POS measures the number of positive HIV tests and was used as a proxy for new diagnoses. PnR was also calculated using Naomi-estimated 2023 HIV incidence, where available. A higher PnR indicates more PrEP users relative to PrEP need in a population.

Results

In FY23, 1,760,888 people initiated PrEP, and 1,736,144 people tested positive for HIV. PnR ranged from 0.12 (India) to 6.46 (Brazil), and 19 (40%) countries had fewer PrEP users than positive HIV tests (PnR <1.0). By population, people 15–24 years old, people who inject drugs, and transgender populations had the highest median PnR. When examining estimated HIV incidence, Mozambique and South Africa reported lower than average PnR and higher than average HIV incidence.

Conclusion

PrEP use relative to population need varied greatly by country and subpopulation across PEPFAR programs, suggesting a need for greater advocacy, inclusivity, accessibility, and integrated prevention programming. PnR may be a useful indicator of population PrEP coverage and unmet need, and can inform effective, data-driven, and person-centered PEPFAR prevention programming and policies. Tailoring PrEP scale-up strategies by age, sex, key population, and geography is crucial to achieving UNAIDS targets and ending the AIDS epidemic as a public health threat for all by 2030.
Transdisciplinary knowledge co-production as a catalyst for community-led innovation: a case study of farmers’ milk cooperative in Laikipia, Kenya
Authors: Mukhovi Stellah Mikalitsa , Kiteme Boniface , Mwangi John , Wambugu Grace
Published: December 2024

Food systems must be reconfigured for them to alleviate poverty, hunger, food losses, and waste, promote healthy diets, inclusivity, resilience, and livelihood opportunities, and be environmentally sustainable. This requires a shift in production, and consumption, as well as transformative research, responsive policy, people-centered innovations, and safety nets for the most vulnerable people. Transformation of food systems also depends on a shift in science, policy, and practice to promote sustainable futures. For science to be transformative, discipline-oriented research is important, however, societal challenges are becoming more complex hence requiring more interdisciplinary research with collaboration and integration of knowledge from actors in policy and practice. Scientists must learn to first work together, and then work with non-academic actors to solve complex problems facing food systems and the society at large. This kind of research is transdisciplinary, meaning right from the framing of complex problems, data collection, analysis, and validation, non-academic actors must be actively involved in the process of knowledge co-creation to create sustainable outcomes. This study demonstrates how co-production of knowledge between academic and non-academic actors through a participatory negotiated process, can contribute to transformative development intervention. The study applies a case study of an agro-pastoral community involved in a milk value chain in Laikipia County. The transformative areas in the study were; (a) capacity development in commercial dairy farming, (b) formation of Umande farmers’ Cooperative, and (c) construction of a cooler house, and installation of a milk cooling system for milk bulking, and value addition. The case study offers several lessons; (a) the role of transdisciplinarity in science, policy, and practice, (b) proper identification of stakeholders in collaborative community development initiatives, (c) the community must always be at the forefront of any development initiative for ownership and sustainability, and (d) skills development and economic empowerment are paramount for any innovation in the community. The objectives of the study were (a) participatory assessment of the local food system to identify the strengths and weaknesses, (b) assessment of perceived benefits of farmer capacity development and lessons learned, and (c) assessment of farmer perception of the benefits of milk cooling and bulking system on livelihoods. More farmer -led development initiatives are needed to improve livelihoods of actors in food systems.
Onset and long-term duration of immunity provided by a single vaccination with recombinant a Marek’s disease virus with REV-LTR insertion
Authors: Dai Jun , Song Cuiping , Tan Lei , Sun Yingjie , Tang Ning , Qu Yang , Liao Ying , Qiu Xusheng , Ding Chan
Published: December 2024

Marek’s Disease (MD), caused by Marek’s disease virus (MDV), is a highly contagious lymphoproliferative disease in poultry. Despite the fact that MD has been effectively controlled by vaccines, the virulence of field isolates of MDV has continued to evolve, becoming more virulent under the immune pressure of vaccines. Our previous research has confirmed that the recombinant rMDV strain with REV-LTR insertion can be used as a live attenuated vaccine candidate. The aim of this research was to evaluate the onset and duration of immunity of the rMDV strain through two experiments. In both experiments, 1-day-old SPF chickens were vaccinated subcutaneously with the rMDV strain at a dose of 3,000 Plaque Formation Unit (PFU) per chick in 0.2 mL of the MD diluent. Then, in Experimental design 1, the chicks in the groups Vac-3d/CC-3d, Vac-5d/CC-5d, and Vac-7d/CC-7d were challenged separately with 500 PFU vvMDV strain MD5 at 3 days, 5 days, and 7 days after vaccination; in Experimental design 2, the chicks in group Vac-60d/CC-60d, Vac-120d/CC-120d, and Vac-180d/CC-180d were challenged at 60 days, 120 days, and 180 days after vaccination. The clinical symptoms and weight gain of chickens in each group were observed and recorded. The results showed that the rMDV strain with REV-LTR insertion provides protection starting from 3 days of age and achieves good immune effects at 5 days of age after 1-day-old immunization, and the immunization duration can reach for at least 180 days. Given age-related resistance, it can be confirmed that our vaccine can actually provide lifelong immunity. This study provides valuable insights into the onset and duration of immunity of the rMDV strain, which will provide a basis for the development and improvement of MD vaccines.
Stroke Dataset Modeling: Comparative Study of Machine Learning Classification Methods
Authors: Kitova Kalina , Ivanov Ivan , Hooper Vincent
Published: December 2024

Stroke prediction is a vital research area due to its significant implications for public health. This comparative study offers a detailed evaluation of algorithmic methodologies and outcomes from three recent prominent studies on stroke prediction. Ivanov et al. tackled issues of imbalanced datasets and algorithmic bias using deep learning techniques, achieving notable results with a 98% accuracy and a 97% recall rate. They utilized resampling methods to balance the classes and advanced imputation techniques to handle missing data, underscoring the critical role of data preprocessing in enhancing the performance of Support Vector Machines (SVMs). Hassan et al. addressed missing data and class imbalance using multiple imputations and the Synthetic Minority Oversampling Technique (SMOTE). They developed a Dense Stacking Ensemble (DSE) model with over 96% accuracy. Their results underscore the efficiency of ensemble learning techniques and imputation for handling imbalanced datasets in stroke prediction. Bathla et al. employed various classifiers and feature selection techniques, including SMOTE, for class balancing. Their Random Forest (RF) classifier, combined with Feature Importance (FI) selection, achieved an accuracy of 97.17%, illustrating the positive impact of RF and relevant feature selection on model performance. A comparative analysis indicated that Ivanov et al.’s method achieved the highest accuracy rate. However, the studies collectively highlight that the choice of models and techniques for stroke prediction should be tailored to the specific characteristics of the dataset used. This study emphasizes the importance of effective data management and model selection in enhancing predictive performance.
Proteomic Analysis of the Fish Pathogen Vibrio ordalii Strain Vo-LM-18 and Its Outer Membrane Vesicles
Authors: Echeverría-Bugueño Macarena , Hernández Mauricio , Avendaño-Herrera Ruben
Published: December 2024

Vibrio ordalii is the causative agent of atypical vibriosis in salmonids cultured in Chile. While extensive research provides insights into V. ordalii through phenotypic, antigenic, and genetic typing, as well as various virulence mechanisms, proteomic characterization remains largely unexplored. This study aimed to advance the proteomic knowledge of Chilean V. ordalii Vo-LM-18 and its OMVs, which have known virulence. Using Nano-UHPLC-LC-MS/MS, we identified 2242 proteins and 1755 proteins in its OMVs. Of these, 644 unique proteins were detected in V. ordalii Vo-LM-18, namely 156 unique proteins in its OMVs and 1596 shared proteins. The major categories for the OMVs were like those in the bacteria (i.e., cytoplasmic and cytoplasmic membrane proteins). Functional annotation identified 37 biological pathways in V. ordalii Vo-LM-18 and 28 in its OMVs. Proteins associated with transport, transcription, and virulence were predominant in both. Evident differences in protein expression were found. OMVs expressed a higher number of virulence-associated proteins, including those related to iron- and heme-uptake mechanisms. Notable pathways in the bacteria included flagellum assembly, heme group-associated proteins, and protein biosynthesis. This proteomic analysis is the first to detect the RTX toxin in a V. ordalii strain (Vo-LM-18) and its vesicles. Our results highlight the crucial role of OMVs in the pathogenesis and adaptation of V. ordalii, suggesting use as potential diagnostic biomarkers and therapeutic targets for bacterial infections.
Determination of Calcium and Phosphorus Digestibility of Individual Feed Ingredients as Affected by Limestone, in the Presence and Absence of Phytase in Broilers
Authors: Venter Kyle Marcus , Angel Roselina , Fourie Jamie , Plumstead Peter William , Li Wenting , Enting Henk , Dersjant-Li Yueming , Jansen van Rensburg Christine
Published: December 2024

To begin formulating broiler diets on a digestible calcium (Ca) basis, robust Ca digestibility values for ingredients and factors affecting this digestibility are needed. This study had three main objectives: (1) determine the standardized ileal digestibility (SID) of Ca and phosphorus (P) for seven plant-based feed ingredients in broilers, (2) assess the impact of phytate source on SID Ca from limestone (LS), and (3) evaluate the effect of phytase on SID Ca and P for the different ingredients. Two experiments were conducted to satisfy these objectives. In Experiment 1, a 4 × 2 × 2 factorial design was used, with four plant-based feed ingredients (corn, wheat, sorghum, and full-fat soybean meal (FFS)), two LS inclusions in the diet (absence of LS and the inclusion of LS required to achieve 0.65% Ca in the final diet), and two phytase doses (0 and 1000 FTU/kg diet). Experiment 2 utilized a 3 × 2 × 2 factorial design with three plant-based ingredients (soybean meal (SBM), rapeseed meal (RSM), and sunflower meal (SFM)), two LS inclusions in the diet (absence of LS and the inclusion of LS required to achieve 0.65% Ca in the final diet), and two phytase doses (0 and 1000 FTU/kg diet). The trial had eight replicate pens (6 broilers/replicate) per treatment. Data were analyzed using a factorial analysis in JMP Pro 16.0 with means separation performed when p < 0.05, using Tukey HSD. The SID Ca in the absence of phytase for wheat (72.9%) and FFS (69.9%) was higher (p < 0.05) than for sorghum (54.5%) and corn (46.3%). In Experiment 2, the SID Ca in the absence of phytase from SFM (61.0%) was higher (p < 0.01) than RSM (42.7%) and SBM (46.8%). The SID Ca from added LS was affected by the ingredient, with diets containing wheat and FFS resulting in the lowest (p < 0.05) SID Ca versus those containing corn and sorghum irrespective of phytase dose in Experiment 1, and the lowest (p < 0.05) for SBM and RSM vs. SFM in the absence of phytase in Experiment 2. Phytase supplementation increased (p < 0.01) SID Ca and SID P across all feed ingredients compared to non-supplemented diets. There was a two-way interaction (p < 0.01) of LS addition and ingredient on SID P in both experiments. The results of this study provide SID Ca and SID P values from the selected ingredients and show that phytate from different ingredients reacts differently with Ca from LS and should be considered when developing SID coefficients of Ca and P for use in commercial broiler feed formulation. The SID coefficients of Ca and P for the individual feed ingredients evaluated in this study will allow for the further development and transition towards dCa and dP in commercial feed formulation.
Perturbation Methods in Solving the Problem of Two Bodies of Variable Masses with Application of Computer Algebra
Authors: Prokopenya Alexander , Minglibayev Mukhtar , Ibraimova Aigerim
Published: December 2024

The classical many-body problem is not integrable, so perturbation theory based on an exact solution to the two-body problem is usually applied to investigate the dynamics of planetary systems. However, in the case of variable masses, the two-body problem is not integrable, in general, and application of perturbation theory is required to investigate it, as well. In the present paper, we use the perturbation theory to derive the differential equations determining the orbital elements of the relative motion of one body around the other. Two models of the perturbed aperiodic motion on conic and quasi-conic sections are considered and compared. Special attention is paid to the practically important case of small eccentricities, when the perturbing forces may be replaced by the corresponding power series expansions. The differential equations of the perturbed motion are averaged over the mean anomaly, and the evolutionary equations describing the behavior of the orbital elements over long periods of time are obtained for two models. Comparing the corresponding solutions to the evolutionary equations, we have shown that both models demonstrate similar behavior with regard to the secular perturbations of the orbital elements. However, the second model, based on the aperiodic motion on a quasi-conic section, is more appropriate for generalization to the many-body problem with variable masses. All the relevant symbolic and numerical calculations are performed with the computer algebra system Wolfram Mathematica.
Effects of Long-Term Fertilization on Phosphorus Form and Availability in Black Soil
Authors: Lu Enjia , Li Cuilan , Geng Yidan , Liang Tianfeng , Zhang Jinjing
Published: December 2024

This study explored the effect of the combined application of chemical and organic fertilizers on phosphorus morphology and its conversion to an active state. A long-term field positioning experiment comprising five treatments was conducted in black soil. The results concluded that the soil total phosphorus (TP), available phosphorus (AP), inorganic phosphorus, and organic phosphorus contents of all treatments ranked as follows: 1.5M1NPK > M2NPK > M1NPK > NPK > CK. The long-term application of chemical and organic fertilizers increased the proportion of soil reactive phosphorus and moderately reactive phosphorus but decreased the proportion of mildly active phosphorus and residual phosphorus. A phosphorus-31 nuclear magnetic resonance (31P NMR) spectral analysis showed that the contents of orthophosphate, pyrophosphate, phosphoric acid diesters, and orthophosphate acid monoesters increased with the application of chemical and organic fertilizers, of which 1.5M1NPK usually resulted in the highest increases. In conclusion, the long-term application of chemical fertilizers could promote the conversion of soil phosphorus into active phosphorus and improve the effectiveness of soil phosphorus, and the long-term use of organic and chemical fertilizers was more effective than the use of chemical fertilizers only, with 1.5M1NPK providing the best effects.
An Observational Study on the Prediction of Range of Motion in Soldiers Diagnosed with Patellar Tendinopathy Using Ultrasound Shear Wave Elastography
Authors: Kim Min-Woo , Lee Dong-Ha , Seo Young-Chae
Published: December 2024

Introduction: This study hypothesized that changes in the elasticity of the quadriceps and patellar tendons before and after the diagnosis of patellar tendinopathy would correlate with the range of motion (ROM) following conservative treatment. We aimed to prospectively assess post-treatment ROM using multinomial logistic regression, incorporating elasticity measurements obtained via shear wave elastography (SWE). Materials and Methods: From March 2023 to April 2024, 95 patients (86 men; aged 20–45 years, mean 25.62 ± 5.49 years) underwent SWE preoperatively and two days post-diagnosis of patellar tendinopathy. Elasticity measurements of the rectus femoris, vastus medialis, vastus lateralis, patellar tendon, and biceps tendon were obtained during full flexion and extension. Based on ROM 56 days post-treatment, patients were categorized into two groups: Group A (ROM > 120 degrees) and Group B (ROM < 120 degrees). A multinomial logistic regression algorithm was employed to classify the groups using patient information and tendon elasticity measurements both at diagnosis and 1-week post-diagnosis. Results: The predictive accuracy using only patient information was 62%, while using only elasticity measurements yielded 68% accuracy. When combining patient information with elasticity measurements taken at diagnosis and two days post-diagnosis, the algorithm achieved an accuracy of 79%, sensitivity of 92%, and specificity of 56%. Conclusions: The combination of patient information and tendon elasticity measurements obtained via SWE at pre-conservative treatment and early post-conservative treatment periods effectively predicts post-treatment ROM. This algorithm can guide rehabilitation strategies for soldiers with patellar tendinopathy.
Enhancing Sensitivity of Point-of-Care Thyroid Diagnosis via Computational Analysis of Lateral Flow Assay Images Using Novel Textural Features and Hybrid-AI Models
Authors: Fairooz Towfeeq , McNamee Sara E. , Finlay Dewar , Ng Kok Yew , McLaughlin James
Published: December 2024

Lateral flow assays are widely used in point-of-care diagnostics but face challenges in sensitivity and accuracy when detecting low analyte concentrations, such as thyroid-stimulating hormone biomarkers. This study aims to enhance assay performance by leveraging textural features and hybrid artificial intelligence models. A modified Gray-Level Co-occurrence Matrix, termed the Averaged Horizontal Multiple Offsets Gray-Level Co-occurrence Matrix, was utilised to compute the textural features of the biosensor assay images. Significant textural features were selected for further analysis. A deep learning Convolutional Neural Network model was employed to extract features from these textural features. Both traditional machine learning models and hybrid artificial intelligence models, which combine Convolutional Neural Network features with traditional algorithms, were used to categorise these textural features based on the thyroid-stimulating hormone concentration levels. The proposed method achieved accuracy levels exceeding 95%. This pioneering study highlights the utility of textural aspects of assay images for accurate predictive disease modelling, offering promising advancements in diagnostics and management within biomedical research.
Advances in Machine Learning-Aided Thermal Imaging for Early Detection of Diabetic Foot Ulcers: A Review
Authors: Wu Longyan , Huang Ran , He Xiaoyan , Tang Lisheng , Ma Xin
Published: December 2024

The prevention and early warning of foot ulcers are crucial in diabetic care; however, early microvascular lesions are difficult to detect and often diagnosed at later stages, posing serious health risks. Infrared thermal imaging, as a rapid and non-contact clinical examination technology, can sensitively detect hidden neuropathy and vascular lesions for early intervention. This review provides an informative summary of the background, mechanisms, thermal image datasets, and processing techniques used in thermal imaging for warning of diabetic foot ulcers. It specifically focuses on two-dimensional signal processing methods and the evaluation of computer-aided diagnostic methods commonly used for diabetic foot ulcers.
Within- and Between-Person Correlates of Affect and Sleep Health Among Health Science Students
Authors: Wang Yueying , Yang Jiechao , Yuan Jinjin , Izci-Balserak Bilgay , Mu Yunping , Chen Pei , Zhu Bingqian
Published: December 2024

Background/Objectives: To examine the relationships between state affect and sleep health at within- and between-person levels among health science students. Methods: A correlational design was used and 54 health science students were included. The participants completed baseline and 7-day ambulatory assessments in a free-living setting. Daily sleep and affect were measured using the Consensus Sleep Diary and Positive and Negative Affect Schedule. Mixed-effect models were used to examine the effects of affect on sleep health. Results: The participants were 19.8 (SD, 0.6) years and 92.6% were females. Approximately 40% had poor sleep quality. Controlling for the potential confounders (e.g., age, sex, and bedtime procrastination), higher within-person negative affect predicted shorter sleep duration, lower sleep efficiency, longer sleep onset latency, and less feeling rested. Higher between-person negative affect predicted shorter sleep duration. Higher within-person positive affect predicted longer sleep onset latency. Higher within- and between-person positive affect predicted more feeling rested. Conclusions: Negative affect was most consistently associated with sleep health at the individual level. Affect regulation should be considered when delivering personalized interventions targeting sleep health among health science students.
Low-Rank Tensor Fusion for Enhanced Deep Learning-Based Multimodal Brain Age Estimation
Authors: Liu Xia , Zheng Guowei , Beheshti Iman , Ji Shanling , Gou Zhinan , Cui Wenkuo
Published: December 2024

Background/Objectives: A multimodal brain age estimation model could provide enhanced insights into brain aging. However, effectively integrating multimodal neuroimaging data to enhance the accuracy of brain age estimation remains a challenging task. Methods: In this study, we developed an innovative data fusion technique employing a low-rank tensor fusion algorithm, tailored specifically for deep learning-based frameworks aimed at brain age estimation. Specifically, we utilized structural magnetic resonance imaging (sMRI), diffusion tensor imaging (DTI), and magnetoencephalography (MEG) to extract spatial–temporal brain features with different properties. These features were fused using the low-rank tensor algorithm and employed as predictors for estimating brain age. Results: Our prediction model achieved a desirable prediction accuracy on the independent test samples, demonstrating its robust performance. Conclusions: The results of our study suggest that the low-rank tensor fusion algorithm has the potential to effectively integrate multimodal data into deep learning frameworks for estimating brain age.
“Beyond the Knife”—Applying Theranostic Technologies to Enhance Outcomes in Neurosurgical Oncology
Authors: Guru Santosh , Lam Fred C. , Akhavan-Sigari Amirhossein , Hori Yusuke S. , AbuReesh Deyaaldeen , Tayag Armine , Emrich Sara C. , Ustrzynski Louisa , Park David J. , Chang Steven D.
Published: December 2024

The current standard of care for brain tumor management includes maximal safe surgical resection followed by concurrent chemotherapy and radiation therapy. Recent advances in image-guided surgical techniques have enhanced the precision of tumor resections, yet there remains a critical need for innovative technologies to further improve patient outcomes. Techniques such as fluorescence image-guided neurosurgery in combination with stereotactic radiosurgery have improved outcomes for patients with brain tumors. In this article for Brain Science’s Special Issue Recent Advances in Translational Neuro-Oncology, we review the use of image-guided neurosurgery and stereotactic radiosurgery for the treatment of brain tumors. In addition, we summarize the emerging use of theranostic nanoparticles for the delivery of diagnostic and therapeutic technologies to enable the neurosurgeon to perform more precise surgical resections in the operating room, to specifically target the delivery of existing and novel treatments to tumor cells, and to augment the efficacy of stereotactic radiosurgery. These innovative translational tools will allow neurosurgeons, neuro-oncologists, and radiation oncologists to go “beyond the knife” to improve the survival of brain tumor patients.
Microdissection of Distinct Morphological Regions Within Uveal Melanomas Identifies Novel Drug Targets
Authors: Toumi Elsa , Hesson Luke B. , Lin Vivian , Wright Dale , Hajdu Elektra , Lim Li-Anne S. , Giblin Michael , Zhou Fanfan , Hoffmeister Alexandra , Zabih Farida , Fung Adrian T. , Conway R. Max , Cherepanoff Svetlana
Published: December 2024

Background/Objectives: Uveal melanomas (UMs) are rare but often deadly malignancies that urgently require viable treatment options. UMs often exhibit tumour heterogeneity, with macroscopic and microscopic differences in morphology between different regions of the same tumour. However, to date, the clinical significance of this and how it may help guide personalised therapy have not been realised. Methods: Using targeted DNA and RNA sequencing of a small case series of large, high-risk primary UMs, we explored whether morphologically distinct regions of the same tumour were associated with distinct molecular profiles. Results: In four of the seven tumours analysed, we detected different sets of genetic variants following the separate analysis of microdissected melanotic and amelanotic regions of the same tumour. These included a MET exon 14 skipping RNA transcript that predicts sensitivity to crizotinib and variants in other genes that are important in active clinical trials for patients with UM and advanced solid tumours. The integration of TCGA data also identified recurrent mutational events in genes that were not previously implicated in UM development (FANCA, SLX4, BRCA2, and ATRX). Conclusions: Our findings show that the molecular analysis of spatially separated and morphologically distinct regions of the same tumour may yield additional, therapeutically relevant genetic variants in uveal melanomas and have implications for the future molecular testing of UMs to identify targeted therapies.
Association Between Hospital Efficiency and Quality of Care Among Fee-for-Service Medicare Beneficiaries with Prostate Cancer: A Retrospective Cohort Study
Authors: Chhatre Sumedha , Malkowicz S. Bruce , Vapiwala Neha , Guzzo Thomas J. , Jayadevappa Ravishankar
Published: December 2024

Background: Technical efficiency evaluates a hospital’s economic performance and plays an important role in variations in quality of care and outcomes. The study objective was to examine the association between hospital efficiency and quality of care among fee-for-service Medicare beneficiaries with prostate cancer and to assess if race moderates this association. Design: Retrospective study using Surveillance, Epidemiological, and End Results—Medicare (SEER-Medicare) data from 1998 to 2016 for prostate cancer patients aged ≥ 66. We computed hospital technical efficiency using a data envelopment analysis. Outcomes were emergency room visits, hospitalizations, cost, and mortality (all-cause and prostate cancer-specific). We used competing risk regression for survival, log-link GLM models for cost, and Poisson models for count data. The propensity score approach was used to minimize selection bias. Results: The cohort consisted of 323,325 patients. Compared to higher efficiency hospitals (upper quartile), low hospital efficiency (i.e., lower quartile) was associated with a higher hazard of long-term mortality (Hazard ratio (HR) = 1.06, 95% CI = 1.05, 1.08) and long-term prostate cancer-specific mortality (HR = 1.14, 95% CI = 1.11, 1.17). Compared to higher efficiency levels, lower levels were associated with impaired emergency room visits, hospitalizations, and costs. A one unit increase in the efficiency score was associated with greater benefits for cost and mortality for African American and white patients. The benefit was larger for African American patients compared to white patients. Conclusions: Increasing hospital efficiency may help improve outcomes among Medicare prostate cancer patients. Policies to redirect patients to hospitals with higher efficiency can enhance the quality of care and outcomes.
Real-World Efficacy and Adherence to Palbociclib in HR-Positive, HER2-Negative Advanced Breast Cancer: Insights from a Romanian Cohort
Authors: Lungulescu Cristian Virgil , Camen Georgiana-Cristiana , Naidin Mihaela-Simona , Berisha Tradian-Ciprian , Bita Andrei , Dinescu Venera-Cristina , Buteica Sandra Alice , Dimulescu Marina-Daniela , Volovat Simona Ruxandra , Turcu-Stiolica Adina
Published: December 2024

Background/Objectives: The first reimbursed prescription for palbociclib (Palbo) in breast cancer patients in Romania was issued in July 2018. The objective of this study is to assess the efficacy, safety, and adherence to Palbo in combination with aromatase inhibitor (AI) or fulvestrant in a real-world cohort of HR+/HER2− breast cancer patients from Romania. Methods: A retrospective analysis of reimbursed Palbo prescriptions was conducted using data extracted from the electronic database of the Romanian Health Insurance House, Dolj County, for disease code 124 (breast cancer), covering the period from 2018 to 2023. The primary outcome assessed was time to treatment discontinuation (TTD), with secondary outcomes including overall survival (OS) and Palbo adherence (which was measured by medication possession ratio). Results: A total of 125 patients were identified, with a median age of 62 years (IQR, 53–70), and 98% were female. Two treatment combinations were observed: Palbo + Aromatase Inhibitor (AI) in 104 patients (83.2%) and Palbo + fulvestrant in 21 patients (16.8%). The median TTD for the entire cohort was 19 months (95%CI, 19.3–24.9 months). In patients treated with Palbo + AI, the median TTD was not available/reached [NA] (95%CI, 36.0-NA months). For those receiving Palbo+fulvestrant, the median TTD was 25.0 months (95%CI, 13.0-NR months). No significant differences in TTD were observed among the two treatment combinations (χ2 = 1.33, df = 1, log-rank p = 0.249). The 12- and 36-month TTD rates were higher for Palbl combined with AI than combined with fulvestrant: 77.8% [95%CI, 69.7–86.7%] vs. 71.8% [95%CI, 53.6–96.2%], and 56.3% [95%CI, 45.9–69%] vs. 49.7% [95%CI, 29.7–83.2%], respectively. The median OS was 38 months (95%CI, 25.5–50.9). When treatment involved Palbo + AI, the median OS was NA (95%CI, 54.8-NA) months. When treatment involved Palbo + fulvestrant, the median was 50.8 (95%CI, 34.1-NA) months. Related to OS, no significant differences were found between the two types of treatments (log-rank p = 0.638). The 24- and 36-month OS rates were higher for Palbo combined with AI than combined with fulvestrant: 76.9% [95%CI, 69.2–85.5%] vs. 81% [95%CI, 65.8–99.6%], and 67.9% [95%CI, 59.2–77.8%] vs. 65.3% [95%CI, 47.4–90.0%], respectively. The mean adherence in our study was 0.91 ± 0.1. We found no correlation between adherence to Palbo and OS (Spearman’s rho = 0.04, p = 0.593). Conclusions: While both AI and fulvestrant remain viable options, the lack of significant differences in survival between these combinations suggests that treatment choice can be tailored to individual patient needs.
The Role of Lymphadenectomy in the Surgical Treatment of Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis
Authors: Spoletini Gabriele , Mauro Alberto , Caimano Miriam , Marrone Giuseppe , Frongillo Francesco , Agnes Salvatore , Lai Quirino , Bianco Giuseppe
Published: December 2024

Background: Lymphadenectomy in the operative management of hepatocellular carcinoma (HCC) remains controversial, with no recommendation for routine practice. Our study aimed to assess the effects of lymphadenectomy in addition to hepatic resection (HR) compared to HR alone for adults with HCC. Methods: This systematic review was conducted according to PRISMA guidelines until March 2023, searching and selecting the relevant literature comparing lymph node dissection or sampling, combined with HR, and with no lymph node removal. Critical appraisal of the included studies was performed using the ROBINS-I tool. Fixed- or random-effect meta-analysis models were carried out, and inter-studies were assessed for heterogeneity. Results: Fourteen studies were selected during the screening process. Data from eight studies containing 32,041 HCC patients were included in the quantitative synthesis. In total, 12,694 patients underwent lymph node dissection (LND), either selectively for preoperatively diagnosed or intraoperatively suspected lymph node metastasis (LNM) or unselectively (i.e., regardless of suspected LNM). According to LN status, 1-, 3- and 5-year mortality rates were higher in the LNM group with respect to both clinically negative LN (OR 3.25, 95% CI 2.52–4.21; p < 0.001; OR 3.79, 95% CI 2.74–5.24; p < 0.001; OR 3.92, 95% CI 2.61–5.88; p < 0.001) and proven LN0 (OR 1.75, 95% CI 1.0–3.04; p = 0.05; OR 2.88, 95% CI 1.79–4.63; p < 0.001; OR 2.54, 95% CI 1.33–4.84; p < 0.001). Moreover, the summary estimates of two controlled trials showed no significant difference in overall survival between LND groups and those without LND for negative LN patients. Conclusions: Lymph node dissection does not appear to improve overall survival, according to the available literature; thus, this does not support its routine adoption as part of standard liver resection for HCC. A case-by-case decision remains advisable.