bluuebunny/crossref_metadata_2025 huggingface dataset:
Performance evaluation and comparative analysis of different machine learning algorithms in predicting postnatal care utilization: Evidence from the ethiopian demographic and health survey 2016
Authors: Mamo Daniel Niguse , Walle Agmasie Damtew , Woldekidan Eden Ketema , Adem Jibril Bashir , Gebremariam Yosef Haile , Alemayehu Meron Asmamaw , Enyew Ermias Bekele , Kebede Shimels Derso
Published: January 2025

Postnatal care refers to the support provided to mothers and their newborns immediately after childbirth and during the first six weeks of life, a period when most maternal and neonatal deaths occur. In the 30 countries studied, nearly 40 percent of women did not receive a postpartum care check-up. This research aims to evaluate and compare the effectiveness of machine learning algorithms in predicting postnatal care utilization in Ethiopia and to identify the key factors involved. The study employs machine learning techniques to analyse secondary data from the 2016 Ethiopian Demographic and Health Survey. It aims to predict postnatal care utilization and identify key predictors via Python software, applying fifteen machine-learning algorithms to a sample of 7,193 women. Feature importance techniques were used to select the top predictors. The models’ effectiveness was evaluated using sensitivity, specificity, F1 score, precision, accuracy, and area under the curve. Among the four experiments, tenfold cross-validation with balancing using Synthetic Minority Over-sampling Technique was outperformed. From fifteen models, the MLP Classifier (f1 score = 0.9548, AUC = 0.99), Random Forest Classifier (f1 score = 0.9543, AUC = 0.98), and Bagging Classifier (f1 score = 0.9498, AUC = 0.98) performed excellently, with a strong ability to differentiate between classes. The Region, residence, maternal education, religion, wealth index, health insurance status, and place of delivery are identified as contributing factors that predict postnatal care utilization. This study assessed machine learning models for forecasting postnatal care usage. Ten-fold cross-validation with Synthetic Minority Oversampling Technique produced the best results, emphasizing the significance of addressing class imbalance in healthcare datasets. This approach enhances the accuracy and dependability of predictive models. Key findings reveal regional and socioeconomic factors influencing PNC utilization, which can guide targeted initiatives to improve postnatal care utilization and ultimately enhance maternal and child health.
Enhancing engagement in HIV care among adolescents and young adults: A focus on phone-based navigation and relationship building to address barriers in HIV care
Authors: Adhiambo Harriet Fridah , Mwamba Chanda , Lewis-Kulzer Jayne , Iguna Sarah , Ontuga Gladys Moraa , Mangale Dorothy Imbuka , Nyandieka Everlyne , Nyanga James , Opondo Isaya , Osoro Joseph , Montoya Lina , Nyagesoa Edwin , Sang Norton , Akama Eliud , Bukusi Elizabeth , Abuogi Lisa , Geng Elvin , Kwena Zachary Arochi
Published: January 2025

Structural, psychological, and clinical barriers to HIV care engagement among adolescents and young adults living with HIV (AYAH) persist globally despite gains in HIV epidemic control. Phone-based peer navigation may provide critical peer support, increase delivery flexibility, and require fewer resources. Prior studies show that phone-based navigation and automated text messaging interventions improve HIV care engagement, adherence, and retention among AYAH. However, little is known about AYAH experiences utilizing electronic phone-based peer navigation and automated text messaging (E-NAV). We assessed the experiences of AYAH receiving phone-based peer navigation to address barriers to HIV care engagement and viral suppression. We purposefully selected participants randomized to E-NAV within the Adapt for Adolescents in Kisumu, Kenya, and conducted 20 in-depth interviews. Interviews were conducted by a trained qualitative researcher between October and December 2021 and explored topics such as health-seeking and care experiences, E-NAV acceptability and benefits, and the client-navigator relationship. The interviews were audio-recorded and transcribed. We then applied inductive and deductive coding, followed by thematic analysis. Overall, participants found E-NAV acceptable in regard to content and frequency–particularly the opportunity to select a preferred time for calls/text messages, including evenings and weekends. They found the tone of navigator calls and messages friendly, supporting relationship building. Further, AYAH-navigator relationships were described as fraternal, client-focused, and confidential, which supported a personal connection and trust. Reported E-NAV benefits included adherence and appointment reminders, increased knowledge about HIV care, and strategies to address HIV stigma. Electronic navigation is a promising method for youth peer navigation because it optimizes reach (both in time and space) for youth that have severe constraints on both while preserving the ability to create a rapport and a relationship with patients.
Prevalence of mental health conditions in post-conflict Kasai Province, Democratic Republic of the Congo: A repeated, cross-sectional study
Authors: Seekles Maaike L. , Kadima Jacob K. , Omumbu Pierre O. L. , Kukola Junior K. , Kim Joy J. , Bulambo Christian B. , Mulamba Raphael M. , Nganda Motto , Dean Laura
Published: January 2025

Globally, one in five people in post-conflict areas are estimated to be living with a mental health condition. As a key public health issue, these conditions negatively affect individuals, communities, and societies to function after a conflict. Documenting the prevalence of mental health conditions amongst these populations is crucial to prioritise and guide future mental health interventions. This study was the first to use a repeated cross-sectional design and sex-disaggregated analysis, with the aim of estimating the prevalence of depression (PHQ-9) and anxiety (GAD-7) in a post-conflict population of the Kasai Province, Democratic Republic of the Congo. Several domains of Quality of life (WHO-QoL-BREF) were also assessed to gain insight into the relationship between bio-psychosocial stressors and mental health status. Using random cluster sampling, data were collected in two waves from 385 participants, with a one-year interval. The pooled prevalence across both waves was 34.3% for major depression disorder and 26.5% for generalised anxiety disorder. Multivariable linear regression analysis showed that depression and anxiety were both predicted by being female, being of older age, and by experiencing lower physical quality of life, but not by the passing of time. For both mental health outcomes, environmental quality of life served as a significant predictor for women, but not for men. In conclusion, these results suggest that a lack of mental health services and continued exposure to daily stressors are linked to a sustained high prevalence of mental health conditions in our study population. There is a significant need for the development of mental health services in the region. These services should go beyond biomedical interventions and include multi-sectoral approaches that consider the social determinants of (mental) health.
Individual and organizational factors associated with public health workforce competencies to advance health equity
Authors: Kett Paula M. , Shahrir Shahida , Bekemeier Betty , Schaffer Kay , Zemmel Danielle J. , Patterson Davis G.
Published: January 2025

Little is known about how to develop public health workforce capacity for health equity work. We explored associations of individual and organizational characteristics of local public health departments (LHDs) with competencies essential for advancing health equity. Data included responses of 29,751 staff from 742 LHDs in 48 states to the 2021 Public Health Workforce Interests and Needs Survey, plus LHD characteristics and county demographics. Logistic regression assessed associations between key factors and staff-reported “knowledge of” and “confidence in addressing” structural racism, health equity, social determinants of equity (SDoE), social determinants of health (SDOH), and environmental justice, as well as belief and involvement in addressing racism through one’s work. Staff with a master’s degree or higher compared to others had greater odds of reporting confidence in addressing structural racism (adjusted odds ratio [AOR] = 1.23) and health equity (AOR = 1.56), agreeing that addressing racism should be a part of their work (AOR = 2.45) and being involved in such efforts (AOR = 1.57). Staff identifying as Black, compared to white, had greater odds of reporting confidence in addressing all concepts: structural racism (AOR = 1.98), health equity (AOR = 1.34), SDoE (AOR = 1.53), SDOH (AOR = 1.21), and environmental justice (AOR = 1.72) and agreeing that addressing racism should be a part of their work (AOR = 2.11). Patterns were similar among staff identifying as Hispanic/Latino and other persons of color. Black (AOR = 0.68) and Hispanic/Latino (AOR = 0.83) staff had lower odds, however, of reporting engagement in activities to address racism. Finally, competencies positively associated with nearly all outcomes included cross-sector collaboration, ability to incorporate health equity into programming, and policy advocacy. LHD workforce development should include training that involves explicitly naming structural racism’s effects and complementary skills, such as policy development and cross-sector partnership building. Further exploration is needed into how best to grow commitment among white staff and to support staff of color in health equity work.
Chronic disease risk factors among hospital employees: A cross-sectional study in Türkiye
Authors: Medeni Volkan , Topcu Vildan , Bozdağ Fatma , Medeni İrem
Published: January 2025

Introduction

Chronic diseases have become a significant public health problem with the prolongation of human life. There are four main behavioral risk factors for mortality. This study evaluated the significant risk factors for chronic diseases in university hospital employees.

Materials and methods

The cross-sectional study population consisted of hospital employees working at Gazi University Hospital for at least one year. The sample size was calculated to be 285, with a 100% response rate. The study’s independent variables were age, gender, educational status, working department, and presence of chronic diseases. Dependent variables were smoking, alcohol use, physical inactivity, and body mass index (BMI) categories. Data on participants’ characteristics, habits, and behaviors were obtained from the hospital system or with open-ended questions. Their body weight and height were measured. The International Physical Activity Questionnaire (IPAQ) was used to assess physical inactivity.

Results

The smoking prevalence of hospital employees was 41.8%. Regular alcohol use was 19.3%. Based on the BMI values obtained, 37.9% of the participants were pre-obese, and 18.2% were obese. According to the results of the IPAQ, 13.7% were inactive. The prevalence of smoking was 50.4%, alcohol consume 11.6%, physical inactivity 50.4%, and overweight 65.3% among those who graduated from high school or lower. In contrast, the prevalences were 35.4%, 25.0%, 69.5%, and 49.4%, respectively, among those who graduated from university or higher. A one-unit increase in age of participants without chronic disease increased BMI by 1.06 times (p<0.05). When individuals with a high school education or lower are taken as the reference group, it was found that physical inactivity is 1.78 times higher among those with a university degree or higher (p<0.05).

Conclusion

The effect of education level on health habits and behaviors should be considered in terms of the target group and content of preventive health programs and awareness-raising studies.
Familiarity of an environment prevents song suppression in isolated zebra finches
Authors: Zai Anja T. , Rodrigues Diana I. , Stepien Anna E. , Lorenz Corinna , Giret Nicolas , Adam Iris , Hahnloser Richard H. R.
Published: January 2025

Despite the wide use of zebra finches as an animal model to study vocal learning and production, little is known about impacts on their welfare caused by routine experimental manipulations such as changing their social context. Here we conduct a post-hoc analysis of singing rate, an indicator of positive welfare, to gain insights into stress caused by social isolation, a common experimental manipulation. We find that isolation in an unfamiliar environment reduces singing rate for several days, indicating the presence of an acute stressor. However, we find no such decrease when social isolation is caused by either removal of a social companion or by transfer to a familiar environment. Furthermore, during repeated brief periods of isolation, singing rate remains high when isolation is induced by removal of social companions, but it fails to recover from a suppressed state when isolation is induced by recurrent transfer to an unknown environment. These findings suggest that stress from social isolation is negligible compared to stress caused by environmental changes and that frequent short visits of an unfamiliar environment are detrimental rather than beneficial. Together, these insights can serve to refine experimental studies and design paradigms maximizing the birds’ wellbeing and vocal output.
Let-7b-5p sensitizes breast cancer cells to doxorubicin through Aurora Kinase B
Authors: Kaya Murat , Abuaisha Asmaa , Suer Ilknur , Emiroglu Selman , Önder Semen , Onay Ucar Evren , Yenerel Mustafa Nuri , Palanduz Sukru , Cefle Kivanc , Ozturk Sukru , Kurt Zeyneb
Published: January 2025

MicroRNAs (miRNAs) are small, non-coding RNAs that regulate the expression level of the target genes in the cell. Breast cancer is responsible for the majority of cancer-related deaths among women globally. It has been proven that deregulated miRNAs may play an essential role in the progression of breast cancer. It has been shown in many cancers, including breast cancer, that aberrant expression of miRNAs may be associated with drug resistance. This study investigated the effect of let-7b-5p, detected by bioinformatics methods, on Dox resistance through the Aurora Kinase B (AURKB) gene. In silico analysis using publicly available miRNA expression, GEO datasets revealed that let-7b-5p significantly downregulated in BC. Further in silico studies revealed that of the genes among the potential targets of let-7b-5p, AURKB was the most negatively correlated and may be closely associated with Dox resistance. Expression analysis via quantitative PCR confirmed that let-7b-5p was downregulated and AURKB was upregulated in breast cancer tissue samples. Later, functional studies conducted with MCF-10A, MCF-7, and MDA-MB-231 cell lines demonstrated that let-7b-5p inhibits cancer cells through AURKB and sensitizes them to Dox resistance. In conclusion, it has been shown that the let-7b-5p/AURKB axis may be significant in breast cancer progression and the disruption in this axis may contribute to the trigger of Dox resistance.
Impact of partial occlusion of the face on multisensory emotion perception: Comparison of pre- and post-COVID-19 pandemic
Authors: Kawahara Misako , Tanaka Akihiro
Published: January 2025

We perceive and understand others’ emotional states from multisensory information such as facial expressions and vocal cues. However, such cues are not always available or clear. Can partial loss of visual cues affect multisensory emotion perception? In addition, the COVID-19 pandemic has led to the widespread use of face masks, which can reduce some facial cues used in emotion perception. Thus, can frequent exposure to masked faces affect emotion perception? We conducted an emotion perception task using audio-visual stimuli that partially occluded the speaker’s face. Participants were simultaneously shown a face and voice that expressed either congruent or incongruent emotions and judged whether the person was happy or angry. The stimuli included videos in which the eyes or mouth were partially covered and where the whole face was visible. Our findings showed that, when facial cues were partially occluded, participants relied more on vocal cues for emotion recognition. Moreover, when the mouth was covered, participants relied less on vocal cues after the pandemic compared to before. These findings indicate that partial face masking and prolonged exposure to masked faces can affect multisensory emotion perception. In unimodal emotion perception from only facial cues, accuracy also improved after the pandemic compared to before for faces with the mouth occluded. Therefore, changes in the reliance on vocal cues in multisensory emotion perception during the pandemic period could be explained by improved facial emotion perception from the eye region.
CAMSAP2 is required for bridging fiber assembly to ensure mitotic spindle assembly and chromosome segregation in human epithelial Caco-2 cells
Authors: Nishizawa Naoko , Arai Riku , Hiranuma Koki , Toya Mika , Sato Masamitsu
Published: January 2025

In mammalian epithelial cells, cytoplasmic microtubules are mainly non-centrosomal, through the functions of the minus-end binding proteins CAMSAP2 and CAMSAP3. When cells enter mitosis, cytoplasmic microtubules are reorganized into the spindle composed of both centrosomal and non-centrosomal microtubules. The function of the CAMSAP proteins upon spindle assembly remains unknown, as these do not exhibit evident localization to spindle microtubules. Here, we demonstrate that CAMSAP2, but not CAMSAP3, is required for spindle assembly upon mitotic entry. CAMSAP2 knockout (KO) Caco-2 cells showed a delay in mitotic progression, whereas CAMSAP3 KO cells did not. The spindle in CAMSAP2 KO cells was short and displayed a reduced microtubule density, particularly around chromosomes. This indicated a loss of bridging fibers, which are known to assist alignment of sister kinetochores through interaction with kinetochore fibers. Consistent with this, live-cell imaging of CAMSAP2 KO cells captured slow elongation of the anaphase spindle and errors in chromosome segregation. Therefore, we propose that CAMSAP2 ensures efficient reorganization of cytoplasmic microtubules into the mitotic spindle through constructing bridging fibers that assist faithful segregation of sister chromatids.
Frequencies and functions of vocalizations and gestures in the second year of life
Authors: Burkhardt-Reed Megan M. , Bene Edina R. , Oller D. Kimbrough
Published: January 2025

Speculations on the evolution of language have invoked comparisons across human and non-human primate communication. While there is widespread support for the claim that gesture plays a central, perhaps a predominant role in early language development and that gesture played the foundational role in language evolution, much empirical information does not accord with the gestural claims. The present study follows up on our prior work that challenged the gestural theory of language development with longitudinal data showing early speech-like vocalizations occurred more than 5 times as often as gestures in the first year of life. Now we bring longitudinal data on the second year (13, 16 and 20 mo), showing again that vocalizations predominated, and especially in conventional (learned) communication; > 9 times more spoken words were observed than gestures that could be viewed as functionally equivalent to words (i.e., signs). Our observations also showed that about ¾ of gestures across these second-year data were deictics (primarily pointing and reaching), acts that while significant in supporting the establishment of referential vocabulary in both spoken and signed languages, are not signs, but have single universal deictic functions in the here and now. In contrast, words and signs, the primary semantic components of spoken and signed languages, are functionally flexible, making possible reference to abstractions that are not bound to any particular illocutionary force nor to the here and now.
Characterization and evaluation of the cytotoxic, antioxidant, and anti-human lung cancer properties of copper nanoparticles green-synthesized by fennel extract following the PI3K/AKT/Mtor signaling pathway
Authors: Huang Tao , Ma KaiLi , Wang Yihua
Published: January 2025

This work established the cytotoxic, antioxidant and anticancer effects of copper nanoparticles (CuNPs) manufactured with fennel extract, especially on non-small cell lung cancer (NSCLC) as well. CuNPs caused cytotoxicity in a dose-dependent manner for two NSCLC cell lines, A549 and H1650. At 100 μg/ml, CuNPs reduced cell viability to 70% in A549 cells and 65% in H1650 cells. which showed a cytotoxic effect (p<0. 05). Lactate dehydrogenase (LDH) was correspondingly present in a high proportion in the cells, demonstrated upon testing. Together with their cytotoxic properties, CuNPs demonstrated high antioxidative activity. When the concentration of the nano particles was high (100 μg/ml), the ratio of reactive oxygen species (ROS) was reduced as much as 50%, which in turn suggested antioxidant activity. There was plenty of evidence that CuNPs had anti-cancer potential; this has been shown by the effect of the molecules on the PI3K/AKT/mTOR pathway, which was one of the pathways crucial for cancer survival. Western blot analysis and qRT-PCR results indicated a widespread degradation of the proteins in this pathway upon CuNP exposure. Interestingly, there was a declined phosphorylation up to 75% of PI3K, AKT, and mTOR at 100 μg/ml (p<0. 001). In summary, these findings illustrated the mechanisms behind the therapeutic effect of CuNPs, thus making them good targets for the NSCLC treatment. CuNPs have cytotoxic and antioxidant capacity, as well as significant alterations in lung cancers pathway, and therefore they can be considered as anti-cancer candidates.
Biophysical and biochemical evidence for the role of acetate kinases (AckAs) in an acetogenic pathway in pathogenic spirochetes
Authors: Deka Ranjit K. , Tso Shih-Chia , Liu Wei Z. , Brautigam Chad A.
Published: January 2025

Unraveling the metabolism of Treponema pallidum is a key component to understanding the pathogenesis of the human disease that it causes, syphilis. For decades, it was assumed that glucose was the sole carbon/energy source for this parasitic spirochete. But the lack of citric-acid-cycle enzymes suggested that alternative sources could be utilized, especially in microaerophilic host environments where glycolysis should not be robust. Recent bioinformatic, biophysical, and biochemical evidence supports the existence of an acetogenic energy-conservation pathway in T. pallidum and related treponemal species. In this hypothetical pathway, exogenous D-lactate can be utilized by the bacterium as an alternative energy source. Herein, we examined the final enzyme in this pathway, acetate kinase (named TP0476), which ostensibly catalyzes the generation of ATP from ADP and acetyl-phosphate. We found that TP0476 was able to carry out this reaction, but the protein was not suitable for biophysical and structural characterization. We thus performed additional studies on the homologous enzyme (75% amino-acid sequence identity) from the oral pathogen Treponema vincentii, TV0924. This protein also exhibited acetate kinase activity, and it was amenable to structural and biophysical studies. We established that the enzyme exists as a dimer in solution, and then determined its crystal structure at a resolution of 1.36 Å, showing that the protein has a similar fold to other known acetate kinases. Mutation of residues in the putative active site drastically altered its enzymatic activity. A second crystal structure of TV0924 in the presence of AMP (at 1.3 Å resolution) provided insight into the binding of one of the enzyme’s substrates. On balance, this evidence strongly supported the roles of TP0476 and TV0924 as acetate kinases, reinforcing the hypothesis of an acetogenic pathway in pathogenic treponemes.
Enhancing stroke disease classification through machine learning models via a novel voting system by feature selection techniques
Authors: Hasan Mahade , Yasmin Farhana , Hassan Md. Mehedi , Yu Xue , Yeasmin Soniya , Joshi Herat , Islam Sheikh Mohammed Shariful
Published: January 2025

Heart disease remains a leading cause of mortality and morbidity worldwide, necessitating the development of accurate and reliable predictive models to facilitate early detection and intervention. While state of the art work has focused on various machine learning approaches for predicting heart disease, but they could not able to achieve remarkable accuracy. In response to this need, we applied nine machine learning algorithms XGBoost, logistic regression, decision tree, random forest, k-nearest neighbors (KNN), support vector machine (SVM), gaussian naïve bayes (NB gaussian), adaptive boosting, and linear regression to predict heart disease based on a range of physiological indicators. Our approach involved feature selection techniques to identify the most relevant predictors, aimed at refining the models to enhance both performance and interpretability. The models were trained, incorporating processes such as grid search hyperparameter tuning, and cross-validation to minimize overfitting. Additionally, we have developed a novel voting system with feature selection techniques to advance heart disease classification. Furthermore, we have evaluated the models using key performance metrics including accuracy, precision, recall, F1-score, and the area under the receiver operating characteristic curve (ROC AUC). Among the models, XGBoost demonstrated exceptional performance, achieving 99% accuracy, precision, F1-Score, 98% recall, and 100% ROC AUC. This study offers a promising approach to early heart disease diagnosis and preventive healthcare.
The impact of recognition, fairness, and leadership on employee outcomes: A large-scale multi-group analysis
Authors: Jo Hyeon , Shin Donghyuk
Published: January 2025

In the dynamic field of organizational behavior, comprehending the determinants of employee engagement, burnout, and job satisfaction is pivotal. This research investigates the influence of various workplace factors, such as recognition, fairness, leadership, and workload, on these key employee outcomes. Utilizing Partial Least Squares Structural Equation Modeling (PLS-SEM) for analysis, the study examines data from 25,285 employees. The results indicate that recognition significantly boosts employee engagement, while fairness and involvement also positively contribute, albeit to a lesser extent. Transformational leadership plays a dual role, enhancing engagement and reducing burnout. Notably, workload overload presents a nuanced impact, affecting both engagement and burnout. The study additionally reveals the detrimental effect of technological disruption anxiety on job satisfaction. A significant finding from the Multi-Group Analysis (MGA) is the varying impact of these factors between the private and public sectors, particularly in the context of transformational leadership’s effect on burnout and the differential influence of workload on burnout. These insights are critical for formulating effective organizational strategies and policies, highlighting the need for customized recognition initiatives, equitable management approaches, and well-balanced workload allocation.
Analysis of the structure and robustness of the global semiconductor trade network
Authors: Li Long , Wang Hua , Li Zhiyi , Hu Shaodong
Published: January 2025

Amidst the global restructuring of the semiconductor supply chain, this paper constructs a global semiconductor trade network (2007, 2012, 2017, 2021) encompassing three segments (raw materials, equipment, and finished components), based on the CEPII database. After initially exploring trade flows among different regions, the paper conducts an in-depth analysis of the network’s overall structure and the significance of its nodes. Furthermore, the evolution of the trade network’s community structure is discussed and its robustness and dynamics over recent years are assessed through computer program simulation. The findings are as follows: First, semiconductor trade flows are concentrated primarily among a few regions in Asia, US, and EU. Second, the network has grown in size and exhibits significant “small-world” characteristics in all segments, deviating from the typical "sparsity" seen in large-scale networks. Third, Japan, the US, and a few European regions wield significant influence in semiconductor materials and equipment trade, while Asian economies such as Chinese mainland, Chinese Taiwan, and Korea dominate semiconductor components trade. Fourth, the raw materials trade network has diversified in recent years, while the trade networks for equipment and finished components remain in a state of continuous “polarization.” Fifth, the semiconductor trade network demonstrates robustness against random attacks but collapses quickly under targeted attacks. Among the three segments, the trade network of finished components, being larger in scale, exhibits greater resilience against both random and targeted attacks. This paper not only enhances the construction of the global semiconductor trade network but also introduces a dynamic perspective, offering deeper insights into its structure and robustness. The insights gained from this analysis provide valuable guidance for policymakers and companies, especially amidst rapid technological change and geopolitical tensions.
Examining the risk of delirium in patients hospitalized with COVID-19: Insights from the homeless population
Authors: O’Neill Liam , Chumbler Neale R.
Published: January 2025

For patients hospitalized with COVID-19, delirium is a serious and under-recognized complication, and people experiencing homelessness (PEH) may be at greater risk. This retrospective cohort study compared delirium-associated risk factors and clinical outcomes between PEH and non-PEH. This study used patient records from 154 hospitals discharged from 2020–2021 from the Texas Inpatient Public Use Data file. Study subjects (n = 878) were patients, aged 18–69 years, who were hospitalized with COVID-19 and were identified as homeless. The baseline group included (n = 176,518) patients with COVID-19 aged 18–69 years who were not homeless. Logistic regression models were used to identify risk factors for delirium. Relevant risk factors included chronic comorbidities, substance use disorders, and traumatic brain injury (TBI). Seven of the delirium-associated risk factors were more prevalent among PEH compared to baseline. PEH had higher rates of TBI, alcohol, cannabis, and opioid use disorders. PEH had significantly higher rates of delirium (10.6% vs. 8.1%; P<0.01). However, PEH had fewer respiratory complications, including pneumonia (48.5% vs. 81.9%; P<0.001) and respiratory failure (28.7% vs. 61.9%; P<0.001), and lower in-hospital mortality (3.3% vs. 9.5%; P<0.001). The anti-viral Remdesivir had a protective effect against delirium (AOR = 0.63; CI: 0.60, 0.66). Mean hospital length of stay (LOS) was more than twice as long for delirious patients compared with non-delirious patients (18.4 days vs. 7.7 days; P<0.001). Delirium greatly increased the risk of in-hospital mortality (AOR = 3.8; CI: 3.6, 4.0). For PEH (n = 29) who died from COVID-19, delirium was present in more than half (52%) of cases. Hospitals should screen PEH for delirium and adopt nursing protocols to prevent delirium and reduce its severity.
Linguistically informed ChatGPT prompts to enhance Japanese-Chinese machine translation: A case study on attributive clauses
Authors: Gu Wenshi
Published: January 2025

In the field of Japanese-Chinese translation linguistics, the issue of correctly translating attributive clauses has persistently proven to be challenging. Present-day machine translation tools often fail to accurately translate attributive clauses from Japanese to Chinese. In light of this, this paper investigates the linguistic problem underlying such difficulties, namely how does the semantic role of the modified noun affect the selection of translation patterns for attributive clauses, from a linguistic perspective. Through the analysis of numerous examples, the study develops a novel three-step prompt chaining strategy, which was tested using ChatGPT. The experimental results demonstrate that this approach significantly improves translation quality, with an average score increase of over 43%. These findings highlight the effectiveness and potential of linguistically informed prompt design in enhancing the translation accuracy of complex sentence structures. This study not only offers a new perspective on the integration of linguistics theory and machine translation technologies, but also provides valuable insights for optimizing large language models prompt and improving language education tools.
Futility in TAVI: A scoping review of definitions, predictive criteria, and medical predictive models
Authors: Ferry Charlie , Fiery-Fraillon Jade , Togni Mario , Cook Stephane
Published: January 2025

Background

Transcatheter Aortic Valve Implantation (TAVI) procedures are rapidly expanding, necessitating a more extensive stratification of patients with aortic stenosis. Especially in the high-risk group, some patients fail to derive optimal or any benefits from TAVI, leading to the risk of futile interventions. Despite consensus among several experts regarding the importance of recognizing and anticipating such interventions, the definition, and predictive criteria for futility in TAVI remain ambiguous.

Aim

The purpose of this study is to explore the literature addressing the definition, predictive criteria, and medical predictive models for futility in cases of TAVI.

Design

A scoping review was conducted by two researchers and reported in accordance with the PRISMA-ScR guidelines.

Eligibility criteria

Studies addressing futility in TAVI, including definitions, predictive variables, and models, were included without restrictions on study design but were excluded study only on surgical valve replacement, valve in valve or aortic stenosis causes by other pathology than calcification.

Information sources

We identified 129 studies from five key sources: CINAHL, PUBMED, the Cochrane Library, ClinicalTrials.gov, and EMBASE. The literature search was conducted in two rounds—first in February 2024 and again in October 2024—using no restrictions on the year of publication or the language of the studies. Additional references were included through cross-referencing.

Results

The definition of futility is not unanimous, although most researchers agreed on 1-year survival as a cutoff. The majority of studies focused on single variables that can predict 1-year survival, employing either prospective or retrospective designs. Frailty was the major concept studied. Numerous predictive models have been identified, but no consensus was found.

Conclusion

Futility concepts generate interest in the TAVI procedure. In this review, numerous articles state that 1-year mortality serves as a cutoff to define futile procedures. Some variables, cardiac or otherwise, are independent predictors of 1-year mortality. Medical predictive models showed moderate sensitivity and specificity, except for machine learning, which shows promise for the future. However, few articles delve deeply into non-quantifiable parameters such as patient goals and objectives or ethical questions. More studies should focus on these parameters.
Retrospective study of incidence/prevalence of pigmentary maculopathy and retinopathy in patients receiving pentosan polysulfate sodium
Authors: Yuan Zhong , Vaughan Subusola , Jeffcoat Carolyn , Hu Peter , Yuson Ritchie , Fife Daniel , Borkar Durga
Published: January 2025

Purpose

To evaluate prevalence and incidence rates of pigmentary maculopathy and retinopathy (PM/PR), and visual acuity (VA) changes in patients exposed to pentosan polysulfate sodium (PPS) and in patients with interstitial cystitis (IC) not exposed to PPS.

Methods

This is a retrospective cohort study (January 2015–March 2021) which included adult de-identified patients from the American Academy of Ophthalmology IRIS® Registry (Intelligent Research in Sight) and Komodo Health database. Three patient cohorts were identified: two PPS-exposed patient cohorts, and Non-PPS-exposed IC patient cohort. Key study outcomes included PM/PR/Any (defined based on prior literature regardless of PPS exposure) and PM/PR/PPS (further defined by an algorithm that was based on clinical notes and other protocol-prespecified criteria in PPS-exposed patients), and VA changes in each respective cohort.

Results

Prevalence of PM/PR/Any was relatively common in patients prior to PPS exposure (4.16%–8.43%). Incidence rate of PM/PR/PPS was uncommon in both PPS-exposed cohorts (0.13–0.15 per 100 person-years). Crude incidence rates of PM/PR/Any (based on ITT analysis) varied slightly across 3 study cohorts (2.13–2.81 and 2.38 per 100-person-years for PPS-exposed cohorts and Non-PPS-exposed IC cohort, respectively). Across all 3 study cohorts, patients with PM/PR/Any appeared to have approximately 2-fold higher proportion of 3 lines of VA worsening than those without PM/PR/Any.

Conclusion

Prevalence of PM/PR was common in patients prior to PPS exposure. Incidence of PM/PR/PPS that may be associated with PPS exposure was relatively uncommon. Crude incidence rates of PM/PR appeared similar across all patient cohorts regardless of PPS exposure.
Enhancing public sector employees ’ professional identity: A study using China’s Labor Force Survey data
Authors: Ren Xiaotong , Zhu Aimin , Yu Jiao , Guo Chunna
Published: January 2025

Public sector employees, as the crucial link between the party, government, and the general public, represent the frontline in safeguarding the interests of the people and providing services to them. They profoundly influence the implementation and execution of national policy directives. Using data from China’s Labor Force Survey and employing a combination of exploratory factor analysis and confirmatory factor analysis, this research constructs an evaluation index system for public sector employees’ Professional Identity. By dividing the evaluation index system into secondary indicators, and utilizing a structural equation standardization model, the study accurately determines the extent to which each level of indicators within the evaluation index system influences Professional Identity. This research provides pathway recommendations to enhance the Professional Identity of public sector employees, with the aim of mitigating occupational burnout and improving the quality of public services.
Cross-layer latency analysis for 5G NR in V2X communications
Authors: Horta Jorge , Siller Mario , Villarreal-Reyes Salvador
Published: January 2025

The 5G network was developed to push the capabilities of wireless networks to previously unseen performance limits, e.g., transmission rates of several gigabits per second, latency of less than a millisecond, and millions of devices connected at the same time. To meet these requirements, it is necessary to access new spectrum (the so-called millimeter waves) and use techniques such as Massive MIMO (Multiple-Input Multiple-Output) and beamforming. This required the design of a new radio interface, known as 5G NR, that includes improvements to its physical components and new protocols. The performance of the 5G network will depend heavily on the behavior of these new protocols under certain configuration parameters, traffic conditions, device density, and network architecture. This paper introduces an analytical model for the performance evaluation of 5G NR. The developed model describes the behavior of the different layer 1 and 2 protocols involved in 5G radio communication. Using the model, it is possible to evaluate the performance of 5G NR in terms of throughput and latency, two key performance metrics used to describe QoS (Quality of Service) thresholds of different applications. The protocol layer approach gives the model sufficient granularity to identify critical behaviors that significantly impact performance. This can help focus efforts on improving these key points or propose improvements/modifications to the operation of network protocols or devices. The use of this model for performance evaluation is exemplified by studying a Remote Driving scenario operated over 5G. This scenario has very stringent delay requirements, which, according to the model’s results, can be satisfied if the network conditions are adequate. This model and its results can be used as a starting point for performance evaluations of application involving end-to-end (E2E) communications.
A novel framework for increasing research transparency: Exploring the connection between diversity and innovation
Authors: Wojan Timothy R. , Lambert Dayton M.
Published: January 2025

A split sample/dual method research protocol is demonstrated to increase transparency while reducing the probability of false discovery. We apply the protocol to examine whether diversity in ownership teams increases or decreases the likelihood of a firm reporting a novel innovation using data from the 2018 United States Census Bureau’s Annual Business Survey. Transparency is increased in three ways: 1) all specification testing and identifying potentially productive models is done in an exploratory subsample that 2) preserves the validity of hypothesis test statistics from de novo estimation in the holdout confirmatory sample with 3) all findings publicly documented in an earlier registered report and in this journal publication. Bayesian estimation procedures that leverage information from the exploratory stage included in the confirmatory stage estimation replace traditional frequentist null hypothesis significance testing. In addition to increasing statistical power by using information from the full sample, Bayesian methods directly estimate a probability distribution for the magnitude of an effect, allowing much richer inference. Estimated magnitudes of diversity along academic discipline, race, ethnicity, and foreign-born status dimensions are positively associated with innovation. A maximally diverse ownership team on these dimensions would be roughly six times more likely to report new-to-market innovation than a homophilic team.
Adoption of AI writing tools among academic researchers: A Theory of Reasoned Action approach
Authors: Al-Bukhrani Mohammed A. , Alrefaee Yasser Mohammed Hamid , Tawfik Mohammed
Published: January 2025

This research explores the determinants affecting academic researchers’ acceptance of AI writing tools using the Theory of Reasoned Action (TRA). The impact of attitudes, subjective norms, and perceived barriers on researchers’ intentions to adopt these technologies is examined through a cross-sectional survey of 150 researchers. Structural Equation Modeling (SEM) is employed to evaluate the measurement and structural models. Findings confirm the positive influence of favorable attitudes and subjective norms on intentions to use AI writing tools. Interestingly, perceived barriers did not significantly impact attitudes or intentions, suggesting that in the academic context, potential benefits may outweigh perceived obstacles to AI writing tool adoption. Contrarily, perceived barriers do not significantly affect attitudes and intentions directly. The TRA model demonstrates considerable explanatory and predictive capabilities, indicating its effectiveness in understanding AI writing tool adoption among researchers. The study’s diverse sample across various disciplines and career stages provides insights that may be generalizable to similar academic contexts, though further research with larger samples is needed to confirm broader applicability. Results offer practical guidance for tool developers, academic institutions, and publishers aiming to foster responsible and efficient AI writing tool use in academia. Findings suggest strategies such as demonstrating clear productivity gains, establishing AI Writing Tool programs, and developing comprehensive training initiatives could promote responsible adoption. Strategies focusing on cultivating positive attitudes, leveraging social influence, and addressing perceived barriers could be particularly effective in promoting adoption. This pioneering study investigates researchers’ acceptance of AI writing tools using a technology acceptance model, contributing to the understanding of technology adoption in professional contexts and highlighting the importance of field-specific factors in examining adoption intentions and behaviors.
Ultra-compact quintuple-band terahertz metamaterial biosensor for enhanced blood cancer diagnostics
Authors: Hamza Musa N. , Tariqul Islam Mohammad , Lavadiya Sunil , ud Din Iftikhar , Sanches Bruno , Koziel Slawomir , Iffat Naqvi Syeda , Farmani Ali , Islam Md. Shabiul
Published: January 2025

Cancer and its diverse variations pose one of the most significant threats to human health and well-being. One of the most aggressive forms is blood cancer, originating from bone marrow cells and disrupting the production of normal blood cells. The incidence of blood cancer is steadily increasing, driven by both genetic and environmental factors. Therefore, early detection is crucial as it enhances treatment outcomes and improves success rates. However, accurate diagnosis is challenging due to the inherent similarities between normal and cancerous cells. Although various techniques are available for blood cancer identification, high-frequency imaging techniques have recently shown promise, particularly for real-time monitoring. Notably, terahertz (THz) frequencies offer unique advantages for biomedical applications. This research proposes an innovative terahertz metamaterial-based biosensor for high-efficacy blood cancer detection. The proposed structure is ultra-compact and operates across five bands within the range of 0.6 to 1.2 THz. It is constructed using a polyethylene terephthalate (PET) dielectric layer and two aluminum (Al) layers, with the top layer serving as a base for the THz-range resonator. Careful design, architectural arrangement, and optimization of the geometry parameters allow for achieving nearly perfect absorption rates (>95%) across all operating bands. The properties of the proposed sensor are extensively evaluated through full-wave electromagnetic (EM) analysis, which includes assessing the refractive index and the distribution of the electric field at individual working frequencies. The suitability for blood cancer diagnosis has been validated by integrating the sensor into a microwave imaging (MWI) system and conducting comprehensive simulation studies. These studies underscore the device’s capability to detect abnormalities, particularly in distinguishing between healthy and cancerous cells. Benchmarking against state-of-the-art biosensors in recent literature indicates that the proposed sensor is highly competitive in terms of major performance indicators while maintaining a compact size.