bluuebunny/crossref_metadata_2025 huggingface dataset:
A Research Approach to Port Information Security Link Prediction Based on HWA Algorithm
Authors: Xia Zhixin , Zheng Zhangqi , Bai Lexin , Yang Xiaolei , Liu Yongshan
Published: November 2024

For the protection of information security, link prediction, as a basic problem of network science, has important application significance. However, most of the existing link prediction algorithms rely on the node information of the graph structure, which is not applicable in some graph structure data involving privacy. At the same time, most of the algorithms only consider the general graph structure and do not fully consider the high-order information in the graph. Because of this, this paper proposes an algorithm called hypergraph-based link prediction with self-attention (HWA) to solve the above problems. The algorithm can obtain hypergraphs without knowing the attribute information of hypergraph nodes and combines the graph convolutional network (GCN) framework to capture node feature information for link prediction. Experiments show that the HWA algorithm proposed in this paper, combined with the GCN framework, shows better link prediction performance than other graph-based neural network benchmark algorithms on eight real networks. This further verifies the validity and reliability of the model in this paper and provides new protection ideas and technical means for information security.
Towards a System Dynamics Framework for Human–Machine Learning Decisions: A Case Study of New York Citi Bike
Authors: Sankaran Ganesh , Palomino Marco A. , Knahl Martin , Siestrup Guido
Published: November 2024

The growing number of algorithmic decision-making environments, which blend machine and bounded human rationality, strengthen the need for a holistic performance assessment of such systems. Indeed, this combination amplifies the risk of local rationality, necessitating a robust evaluation framework. We propose a novel simulation-based model to quantify algorithmic interventions within organisational contexts, combining causal modelling and data science algorithms. To test our framework’s viability, we present a case study based on a bike-share system focusing on inventory balancing through crowdsourced user actions. Utilising New York’s Citi Bike service data, we highlight the frequent misalignment between incentives and their necessity. Our model examines the interaction dynamics between user and service provider rule-driven responses and algorithms predicting flow rates. This examination demonstrates why understanding these dynamics is essential for devising effective incentive policies. The study showcases how sophisticated machine learning models, with the ability to forecast underlying market demands unconstrained by historical supply issues, can cause imbalances that induce user behaviour, potentially spoiling plans without timely interventions. Our approach allows problems to surface during the design phase, potentially avoiding costly deployment errors in the joint performance of human and AI decision-makers.
The Lightweight Fracture Segmentation Algorithm for Logging Images Based on Fully 3D Attention Mechanism and Deformable Convolution
Authors: Yang Qishun , Zhang Liyan , Xi Zihan , Qian Yu , Li Ang
Published: November 2024

The challenge of fracture segmentation remains a significant obstacle in imaging logging interpretation within the current oil and gas exploration and development field. However, existing image segmentation algorithms still encounter issues related to accuracy, speed, and robustness, as well as a tendency to misdetect or overlook small fractures when applied to logging image fracture segmentation tasks. To address these challenges comprehensively, this paper proposes an end-to-end fracture segmentation algorithm named SWSDS-Net. This algorithm is built upon the UNet architecture and incorporates the SimAM with slicing (SWS) attention mechanism along with the deformable strip convolution (DSCN) module. The SWS introduces a fully 3D attention mechanism that effectively learns the weights of each neuron in the feature map, enabling better capture of fracture features while ensuring fair attention and enhancement for both large and small objects. Additionally, the deformable properties of DSCN allow for adaptive sampling based on fracture shapes, effectively tackling challenges posed by varying fracture shapes and enhancing segmentation robustness. Experimental results demonstrate that SWSDS-Net achieves optimal performance across all evaluation metrics in this task, delivering superior visual results in fracture segmentation while successfully overcoming limitations present in existing algorithms such as complex shapes, noise interference, and low-quality images. Moreover, serving as a lightweight network solution enables SWSDS-Net’s deployment on mobile devices at remote sites—an advancement that lays a solid foundation for interpreting logging data and promotes deep learning technology application within traditional industrial scenarios.
Multi-Objective Routing and Categorization of Urban Network Segments for Cyclists
Authors: Theodoreskos Konstantinos , Gkiotsalitis Konstantinos
Published: November 2024

This study develops a progressive navigation and guidance model for the route selection of cyclists executed in a designated area. The route selection of cyclists is modeled as a Pareto multi-objective optimization problem which is solved with the NSGA-II algorithm. The study aims to contribute to the ongoing efforts to create efficient and cyclist-friendly navigation tools to promote sustainable urban mobility. Data collection methods include GPS tracking, field measurements, and qualitative approaches to understand cyclists’ behavior and preferences. Nine objective functions are constructed based on criteria related to safety and comfort, incorporating decision variables related to cyclists riding on sidewalks, capturing the complexity of urban cycling infrastructure. Tests are performed in a defined area in the center of Athens, Greece. The NSGA-II algorithm is executed with modifications and the Pareto front is constructed, which consists of 28 alternative routes between two origin–destination points. The four routes that optimize the nine criteria of the objective functions are presented, with most routes passing through the Zappeion Gardens. The NSGA-II algorithm is proven to be a suitable approach for applications in networks with complex characteristics and for capturing cyclists’ choices when they face conflicting options. The study presents how a novel approach for the multi-objective optimization of cyclists’ route choice, which considers a wide range of cyclists’ needs and preferences, can be implemented in an urban environment with a lack of cycle infrastructure.
MS3D: A Multi-Scale Feature Fusion 3D Object Detection Method for Autonomous Driving Applications
Authors: Li Ying , Zhuang Wupeng , Yang Guangsong
Published: November 2024

With advancements in autonomous driving, LiDAR has become central to 3D object detection due to its precision and interference resistance. However, challenges such as point cloud sparsity and unstructured data persist. This study introduces MS3D (Multi-Scale Feature Fusion 3D Object Detection Method), a novel approach to 3D object detection that leverages the architecture of a 2D Convolutional Neural Network (CNN) as its core framework. It integrates a Second Feature Pyramid Network to enhance multi-scale feature representation and contextual integration. The Adam optimizer is employed for efficient adaptive parameter tuning, significantly improving detection performance. On the KITTI dataset, MS3D achieves average precisions of 93.58%, 90.91%, and 88.46% in easy, moderate, and hard scenarios, respectively, surpassing state-of-the-art models like VoxelNet, SECOND, and PointPillars.
Aflatoxin Exposure-Caused Male Reproductive Toxicity: Molecular Mechanisms, Detoxification, and Future Directions
Authors: Ye Dongyun , Hao Zhihui , Tang Shusheng , Velkov Tony , Dai Chongshan
Published: November 2024

Widespread endocrine disorders and infertility caused by environmental and food pollutants have drawn considerable global attention. Aflatoxins (AFTs), a prominent class of mycotoxins, are recognized as one of the key contributors to environmental and food contamination. Aflatoxin B1 (AFB1) is the most potent and toxic pollutant among them and is known to cause multiple toxic effects, including neuro-, nephro-, hepato-, immune-, and genotoxicity. Recently, concerns have been raised regarding AFB1-induced infertility in both animals and humans. Exposure to AFB1 can disrupt the structure and functionality of reproductive organs, leading to gametogenesis impairment in males, subsequently reducing fertility. The potential molecular mechanisms have been demonstrated to involve oxidative stress, cell cycle arrest, apoptosis, inflammatory responses, and autophagy. Furthermore, several signaling pathways, including nuclear factor erythroid 2-related factor 2; NOD-, LRR-, and pyrin domain-containing protein 3; nuclear factor kappa-B; p53; p21; phosphoinositide 3-kinase/protein kinase B; the mammalian target of rapamycin; adenosine 5′-monophosphate-activated protein kinase; and mitochondrial apoptotic pathways, are implicated in these processes. Various interventions, including the use of small molecules, Chinese herbal extracts, probiotic supplementation, and camel milk, have shown efficacy in ameliorating AFB1-induced male reproductive toxicity, by targeting these signaling pathways. This review provides a comprehensive summary of the harmful impacts of AFB1 exposure on male reproductive organs in mammals, highlighting the potential molecular mechanisms and protective agents.
Exploring the Genetic Relationship Between Type 2 Diabetes and Cardiovascular Disease: A Large-Scale Genetic Association and Polygenic Risk Score Study
Authors: Yao Ziwei , Zhang Xiaomai , Deng Liufei , Zhang Jiayu , Wen Yalu , Zheng Deqiang , Liu Long
Published: November 2024

Type 2 diabetes (T2D) is often comorbid with cardiovascular diseases (CVDs). The direction of causation between T2D and CVD is difficult to determine; however, there may be a common underlying pathway attributable to shared genetic factors. We aimed to determine whether there is a shared genetic susceptibility to T2D and CVD. This study utilizes large-scale datasets from the UK Biobank (UKB) and DIAGRAM consortium to investigate the genetic association between T2D and CVD through phenotypic association analyses, linkage disequilibrium score (LDSC) analysis, and polygenic risk score (PRS) analysis. LDSC analysis demonstrates significant genetic associations between T2D and various CVD subtypes, including angina, heart failure (HF), myocardial infarction (MI), peripheral vascular disease (PVD), and stroke. Although the genetic association between T2D and atrial fibrillation (AF) was not significant, individuals in the high-T2D PRS group had a significantly increased risk of CVD. These findings suggest a common genetic basis and suggest that genetic susceptibility to T2D may be a potential predictor of CVD risk.
Epigenetics of Hypertensive Nephropathy
Authors: Zhang Yize , Arzaghi Hamidreza , Ma Zhehan , Roye Yasmin , Musah Samira
Published: November 2024

Hypertensive nephropathy (HN) is a leading cause of chronic kidney disease (CKD) and end-stage renal disease (ESRD), contributing to significant morbidity, mortality, and rising healthcare costs. In this review article, we explore the role of epigenetic mechanisms in HN progression and their potential therapeutic implications. We begin by examining key epigenetic modifications—DNA methylation, histone modifications, and non-coding RNAs—observed in kidney disease. Next, we discuss the underlying pathophysiology of HN and highlight current in vitro and in vivo models used to study the condition. Finally, we compare various types of HN-induced renal injury and their associated epigenetic mechanisms with those observed in other kidney injury models, drawing inferences on potential epigenetic therapies for HN. The information gathered in this work indicate that epigenetic mechanisms can drive the progression of HN by regulating key molecular signaling pathways involved in renal damage and fibrosis. The limitations of Renin–Angiotensin–Aldosterone System (RAAS) inhibitors underscore the need for alternative treatments targeting epigenetic pathways. This review emphasizes the importance of further research into the epigenetic regulation of HN to develop more effective therapies and preventive strategies. Identifying novel epigenetic markers could provide new therapeutic opportunities for managing CKD and reducing the burden of ESRD.
Understanding Myelodysplasia and Inflammation Through the Lense of VEXAS Syndrome: A Review
Authors: Wolff Louis , Caratsch Leo , Zhao Lin-Pierre , Blum Sabine , Comte Denis
Published: November 2024

VEXAS syndrome, a monogenic X-linked disorder resulting from mutations in the UBA1 gene, has emerged as a key model for unraveling the links between systemic inflammatory or autoimmune diseases (SIAD) and myelodysplastic syndromes (MD). This syndrome is characterized by the presence of vacuoles, X-linked inheritance, autoinflammation, and somatic mutation patterns, highlighting a unique intersection between genetic and immunological dysregulation. Apart from VEXAS, 10% to 30% of individuals diagnosed with MDS exhibit SIAD phenotypes, a significant increase compared to the 5% incidence in the general population. In this comprehensive review, we aim to elucidate the molecular mechanisms driving the pro-inflammatory environment in MDS, focusing on the contribution of VEXAS syndrome to this complex interplay. We examine how UBA1 mutations disrupt cellular homeostasis, triggering inflammatory pathways. Furthermore, we explore the broader implications of these findings for the pathogenesis of MDS, proposing that the inflammatory dysregulation of VEXAS may shed light on mechanisms of disease progression and identify potential therapeutic targets in MDS. Through an integrated analysis of genetic, immunological, and clinical data, this review seeks to deepen our understanding of the complex relationship between systemic inflammation and hematological malignancies, paving the way for new diagnostic and therapeutic strategies.
Application of Machine Learning and Hydrological Models for Drought Evaluation in Ungauged Basins Using Satellite-Derived Precipitation Data
Authors: Parajuli Anjan , Parajuli Ranjan , Banjara Mandip , Bhusal Amrit , Dahal Dewasis , Kalra Ajay
Published: November 2024

Drought is a complex environmental hazard to ecosystems and society. Decision-making on drought management options requires evaluating and predicting the extremity of future drought events. In this regard, quantifiable indices such as the standardized precipitation index (SPI), the standardized precipitation evapotranspiration index (SPEI), and the standardized streamflow index (SSI) have been commonly used to characterize meteorological and hydrological drought. In general, the estimation and prediction of the indices require an extensive range of precipitation (SPI and SPEI) and discharge (SSI) datasets in space and time domains. However, there is a challenge for long-term and spatially extensive data availability, leading to the insufficiency of data in estimating drought indices. In this regard, this study uses satellite precipitation data to estimate and predict the drought indices. SPI values were calculated from the precipitation data obtained from the Centre for Hydrometeorology and Remote Sensing (CHRS) data portal for a study water basin. This study employs a hydrological model for calculating discharge and drought in the overall basin. It uses random forest (RF) and support vector regression (SVR) as machine learning models for SSI prediction for time scales of 1- and 3-month periods, which are widely used for establishing interactions between predictors and predictands that are both linear and non-linear. This study aims to evaluate drought severity variation in the overall basin using the hydrological model and compare this result with the machine learning model’s results. The results from the prediction model, hydrological model, and the station data show better correlation. The coefficients of determination obtained for 1-month SSI are 0.842 and 0.696, and those for the 3-month SSI are 0.919 and 0.862 in the RF and SVR models, respectively. These results also revealed more precise predictions of machine learning models in the longer duration as compared to the shorter one, with the better prediction result being from the SVR model. The hydrological model-evaluated SSI has 0.885 and 0.826 coefficients of determination for the 1- and 3-month time durations, respectively. The results and discussion in this research will aid planners and decision-makers in managing hydrological droughts in basins.
Biomechanics of Parkinson’s Disease with Systems Based on Expert Knowledge and Machine Learning: A Scoping Review
Authors: Sánchez-Fernández Luis Pastor
Published: November 2024

Patients with Parkinson’s disease (PD) can present several biomechanical alterations, such as tremors, rigidity, bradykinesia, postural instability, and gait alterations. The Movement Disorder Society–Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) has a good reputation for uniformly evaluating motor and non-motor aspects of PD. However, motor clinical assessment depends on visual observations, which are mostly qualitative, with subtle differences not recognized. Many works have examined evaluations and analyses of these biomechanical alterations. However, there are no reviews on this topic. This paper presents a scoping review of computer models based on expert knowledge and machine learning (ML). The eligibility criteria and sources of evidence are represented by papers in journals indexed in the Journal Citation Report (JCR), and this paper analyzes the data, methods, results, and application opportunities in clinical environments or as support for new research. Finally, we analyze the results’ explainability and the acceptance of such systems as tools to help physicians, both now and in future contributions. Many researchers have addressed PD biomechanics by using explainable artificial intelligence or combining several analysis models to provide explainable and transparent results, considering possible biases and precision and creating trust and security when using the models.
Minimally Invasive and Emerging Diagnostic Approaches in Endometrial Cancer: Epigenetic Insights and the Promise of DNA Methylation
Authors: Porcaro Floriana , Paolucci Antonella , Porcaro Piercarmine , Cardinale Gaetano , Romitelli Antonia , Cozzolino Domenico , Voccola Serena
Published: November 2024

Endometrial cancer (EC) is the most common gynecological malignancy, with rising incidence and mortality rates. Key risk factors, including obesity, prolonged estrogen exposure, and metabolic disorders, underscore the urgent need for non-invasive, early diagnostic tools. This review focuses on the role of DNA methylation as a potential biomarker for early EC detection. Aberrant DNA methylation in the promoter regions of tumor suppressor genes can lead to gene silencing and cancer progression. We examine recent studies utilizing minimally invasive samples, such as urine, cervicovaginal, and cervical scrapes, to detect early-stage EC through DNA methylation patterns. Markers such as RASSF1A, HIST1H4F, GHSR, SST, and ZIC1 have demonstrated high diagnostic accuracy, with AUC values up to 0.95, effectively distinguishing EC from non-cancerous conditions. This review highlights the potential of DNA methylation-based testing as a non-invasive alternative to traditional diagnostic methods, offering earlier detection, better risk stratification, and more personalized treatment plans. These innovations hold the promise of transforming clinical practice by enabling more timely and effective management of endometrial cancer.
Comparative Analysis of Classification Criteria in IgG4-Related Disease and Evaluating Diagnostic Accuracy from a Retrospective Cohort in Clinical Practice
Authors: Lopez-Gomez Marta , Moya-Alvarado Patricia , Park Hye Sang , Martín Mar Concepción , Calleja Sara , Codes-Mendez Helena , Magallares Berta , Castellví Iván , Barros-Membrilla Antonio J. , Laiz Ana , Diaz-Torné César , Sainz Luis , Bernárdez Julia , Martínez-Martinez Laura , Corominas Hèctor
Published: November 2024

Introduction: We conducted a comprehensive comparative analysis of the Okazaki, Umehara, and American College of Rheumatology/European League Against Rheumatism (ACR/EULAR) classification criteria for diagnosing immunoglobulin G4-related disease (IgG4-RD). Materials and Methods: A retrospective study was conducted in a single tertiary hospital, using expert clinical judgment as the gold standard. We compared the diagnostic accuracy of the Okazaki, Umehara, and ACR/EULAR criteria in a cohort of 41 patients with suspected IgG4-RD. We assessed sensitivity, specificity, and positive and negative predictive values for each criterion, and conducted a separate analysis based on four IgG4-RD subtypes. Results: A total of 30 patients were confirmed to have IgG4-RD and 11 were identified as mimickers. The Umehara criteria demonstrated the highest sensitivity (83.33%), followed by the ACR/EULAR 2019 (66.67%) and Okazaki (60.0%) criteria. All three criteria exhibited 100% specificity, with overall diagnostic accuracy ranging from 70% to 88%. The areas under the curve (AUC) were 0.917 (Umehara), 0.800 (Okazaki), and 0.833 (ACR/EULAR 2019), indicating significant diagnostic effectiveness (p < 0.000). Subtype analysis revealed that the Umehara and ACR/EULAR 2019 criteria were more effective in diagnosing pancreato-hepato-biliary involvement (subtype 1), while the Okazaki and ACR/EULAR 2019 criteria were more effective in diagnosing retroperitoneal fibrosis and/or aortitis (subtype 2). Conclusions: Our study provides valuable insights into the diagnostic performance of the Okazaki, Umehara, and ACR/EULAR criteria for a cohort of patients with suspected IgG4-RD. The Umehara criterion demonstrated the highest sensitivity, suggesting its potential utility for screening purposes, while all three criteria showed consistent specificity.
The Text-Belief Consistency Effect Among Recent Upper Secondary Graduates: An Eye Tracking Study
Authors: Giménez-Salvador Mariola , Máñez Ignacio , Cerdán Raquel
Published: November 2024

Readers tend to allocate more cognitive resources to processing belief-consistent than belief-inconsistent information when reading multiple texts displaying discrepant views. This phenomenon, known as the text-belief consistency effect, results in individuals being more prone to making biased decisions and falling victim to manipulation and misinformation. This issue is gaining relevance due to the undeniably vast amount of information surrounding us. Hence, schools must ensure that students complete their education prepared to face this challenge. However, international surveys and research indicate a generalized literacy deficiency among students. In the present study, recent upper secondary graduates read four texts discussing a controversial topic to explore whether they effectively overcome the text-belief consistency effect or not. Eye tracking was used to explore immediate (or passive) and delayed (or strategic) text processing, and an essay task was used to measure their resulting mental representation of the text content. Results revealed no significant differences in immediate and delayed processing depending on whether the arguments were belief-consistent or belief-inconsistent. Moreover, essays displayed a balanced and unbiased approach to the debate. Despite these results suggesting this population may be capable of overcoming the text-belief consistency effect, limitations in the study and alternative explanations must be explored before drawing definite conclusions.
A Systematic Review of Working Memory Applications for Children with Learning Difficulties: Transfer Outcomes and Design Principles
Authors: Shaban Adel , Chang Victor , Amodu Onikepo D. , Attia Mohamed Ramadan , Abdelhamid Gomaa Said Mohamed
Published: November 2024

Working memory (WM) is a crucial cognitive function, and a deficit in this function is a critical factor in learning difficulties (LDs). As a result, there is growing interest in exploring different approaches to training WM to support students with LDs. Following the PRISMA 2020 guidelines, this systematic review aims to identify current computer-based WM training applications and their theoretical foundations, explore their effects on improving WM capacity and other cognitive/academic abilities, and extract design principles for creating an effective WM application for children with LDs. The 22 studies selected for this review provide strong evidence that children with LDs have low WM capacity and that their WM functions can be trained. The findings revealed four commercial WM training applications—COGMED, Jungle, BrainWare Safari, and N-back—that were utilized in 16 studies. However, these studies focused on suggesting different types of WM tasks and examining their effects rather than making those tasks user-friendly or providing practical guidelines for the end-user. To address this gap, the principles of the Human–Computer Interaction, with a focus on usability and user experience as well as relevant cognitive theories, and the design recommendations from the selected studies have been reviewed to extract a set of proposed guidelines. A total of 15 guidelines have been extracted that can be utilized to design WM training programs specifically for children with LDs.
Sustainable Omega-3 Lipid Production from Agro-Industrial By-Products Using Thraustochytrids: Enabling Process Development, Optimization, and Scale-Up
Authors: dos Reis Guilherme Anacleto , Orozco Colonia Brigitte Sthepani , Martínez-Burgos Walter Jose , Ocán-Torres Diego , Rodrigues Cristine , de Melo Pereira Gilberto Vinícius , Soccol Carlos Ricardo
Published: November 2024

Thraustochytrids are emerging as a valuable biomass source for high-quality omega-3 polyunsaturated fatty acids (PUFAs), crucial for both human and animal nutrition. This research focuses on cultivating Schizochytrium limacinum SR21 using cost-effective agro-industrial by-products, namely sugarcane molasses (SCM), corn steep liquor (CSL), and residual yeast cream (RYC), to optimize biomass and lipid production through a comprehensive multistep bioprocess. The study involved optimization experiments in shake flasks and stirred-tank bioreactors, where we evaluated biomass, lipid content, and DHA yields. Shake flask optimization resulted in significant enhancements in biomass, lipid content, and lipid production by factors of 1.12, 1.72, and 1.92, respectively. In a 10 L stirred-tank bioreactor, biomass surged to 39.29 g/L, lipid concentration increased to 14.98 g/L, and DHA levels reached an impressive 32.83%. The optimal concentrations identified were 66 g/L of SCM, 24.5 g/L of CSL, and 6 g/L of RYC, achieving a desirability index of 0.87, aimed at maximizing biomass and lipid production. This study shows that agro-industrial by-products can be effective and low-cost substrates for producing lipids using thraustochytrids, offering a sustainable option for omega-3 PUFA production. The findings support future improvements in bioprocesses and potential uses of thraustochytrid biomass in food fortification, dietary supplements, nutraceuticals, and as vegan omega-3 sources.
Analysis of the Beneficial Effects of Probiotics on the Gut–Prostate Axis Using Prostatic Co-Culture Model
Authors: Ferrari Sara , Galla Rebecca , Mulè Simone , Uberti Francesca
Published: November 2024

The link between the gut environment and the prostate has recently been proposed as a potential therapeutic approach for treating benign prostatic hyperplasia (BPH). Therefore, this study examined the advantages of a novel oral probiotic supplement to improve intestinal health and treat BPH. A 3D intestinal barrier model that simulated oral intake was used to analyse the combined regulative abilities of Bifidobacterium longum and Bifidobacterium psychaerophilum. Then, a co-culture prostatic model was used to investigate the biological consequences of the combination under conditions mimicking BPH. The results show the connection between the gut microbiome and prostate disease since the probiotics successfully modulate the primary mechanism involved in the pathogenesis of BPH. Indeed, after the intestinal passage, the mediators released from B. longum and B. psychaerophilum induced a substantial decrease in reactive oxidative species of about 6 times and inflammation (about 5 times regarding interleukine-6 and 10) and a sharp increase in testosterone and serotonin levels (about 95%). Further, proliferation and BPH principal mediators (such as androgen and dihydrotestosterone) were highly affected and nearly restored to physiological levels. Thus, BPH can be directly affected by probiotic supplementation; specifically, B. longum and B. psychaerophilum, in combination, seem able to promote the mitigation of this disease.
Household Food Insecurity During the COVID-19 Pandemic Between Slum and Non-Slum Areas in Kinshasa, DR Congo: A Cross-Sectional Study
Authors: Akilimali Pierre Z. , Kazenza Benito M. , Kabasubabo Francis K. , Egbende Landry M. , Kayembe Dynah M. , Tran Nguyen Toan , Mashinda Désiré K.
Published: November 2024

Introduction: Food insecurity is a vital issue, especially in places such as Kinshasa. Additionally, food insecurity has been worsened by the COVID-19 pandemic, particularly in low- and middle-income countries. Thus, this study examined food insecurity in Kinshasa after the peak of the pandemic to understand the impact of post-pandemic recovery efforts as well as the heterogeneity of this problem according to the residence of respondent (slum vs. non-slum areas). Methods: Grounded in the four key dimensions of food security (availability, access, vulnerability, and utilization), this cross-sectional study was conducted in Kinshasa with a representative sample of 2170 households selected from 62 enumeration areas. We used a questionnaire to interview participants about their food situations. Interviews were conducted with the head of each household or their designated representative by 150 master’s students using tablets powered by the SurveyCTO application. Household food security status was evaluated using the Household Food Insecurity Access Scale. A logistic regression model was developed to assess household risk factors associated with food insecurity. Results: Most people we talked to were over 40 years old, and many lived in households with fewer than six people. About a third of the households were overcrowded. The prevalence of food insecurity was 76.5% (95%CI: 74.6–78.3). Factors associated with food insecurity included being a household head aged over 50 years, insufficient living space, lower socioeconomic status, and residing in slum areas (AOR: 1.38; 95% CI: 1.06–1.79). Conclusions: Vulnerable groups, such as slum residents, older adults, and informal workers are more likely to be affected by food insecurity. Addressing these challenges requires the government to develop targeted strategies that bolster resilience and mitigate household vulnerability during crises.
Linking Inca Terraces with Landslide Occurrence in the Ticsani Valley, Peru
Authors: Ronda Gonzalo , Santi Paul , Pope Isaac E. , Vargas Luque Arquímedes L. , Paria Christ Jesus Barriga
Published: November 2024

Since the times of the Incas, farmers in the remote Andes of Peru have constructed terraces to grow crops in a landscape characterized by steep slopes, semiarid climate, and landslide geohazards. Recent investigations have concluded that terracing and irrigation techniques could enhance landslide risk due to the increase in water percolation and interception of surface flow in unstable slopes, leading to failure. In this study, we generated an inventory of 170 landslides and terraced areas to assess the spatial coherence, causative relations, and geomechanical processes linking landslide presence and Inca terraces in a 250 km2 area located in the Ticsani valley, southern Peru. To assess spatial coherence, a tool was developed based on the confusion matrix approach. Performance parameters were quantified for areas close to the main rivers and communities yielding precision and recall values between 64% and 81%. On a larger scale, poor performance was obtained pointing to the existence of additional processes linked to landslide presence. To investigate the role of other natural variables in landslide prediction, a logistic regression analysis was performed. The results showed that terrace presence is a statistically relevant factor that bolsters landslide presence predictions, apart from first-order natural variables like distance to rivers, curvature, and geology. To explore potential geomechanical processes linking terraces and slope failures, FEM numerical modeling was conducted. Results suggested that both decreased permeability and increased surface irrigation, at 70% of the average annual rainfall, are capable of inducing slope failure. Overall, irrigated terraces appear to further promote slope instability due to infiltration of irrigation water in an area characterized by fluvial erosion, high relief, and poor geologic materials, exposing local communities to increased landslide risk.
Sources and Types of Sexual Information Used by Adolescents: A Systematic Literature Review
Authors: Silva Sofia , Romão Joana , Ferreira Catarina Braz , Figueiredo Patrícia , Ramião Eduarda , Barroso Ricardo
Published: November 2024

Background/Objectives: Sexuality is part of everyone’s life, especially during adolescence, when young people are discovering themselves and experiencing several changes. Adolescents need to be informed about their sexuality, so they seek and receive information about it from a variety of sources and on different topics. This systematic review aimed to synthesize studies that explored the sources adolescents use and topics they search for. Methods: Quantitative, qualitative, and mixed articles published in Portuguese, Spanish, or English and with respondents aged between 12 and 20 years were included in this study. To fulfill the proposed objectives, three online databases (EBSCOhost, PubMed, and Web of Science) were used, including a total of 48 studies. Results: The most common sources of information are family, friends, school, and the Internet, depending mainly on the reliability of the source and the anonymity when using it. The main topics adolescents search for are sexual intercourse, contraception, relationships, and LGBT issues, since these are less addressed topics. Conclusions: These results are useful in a practical way as a basis for the development of sex education programs that correspond to the needs of adolescents, since they allow us to know which information they are looking for and the sources from which they can receive it.
Effect of Genotype on the Response to Diet in Cardiovascular Disease—A Scoping Review
Authors: González-Quijano Génesis K. , León-Reyes Guadalupe , Rosado Eliane Lopes , Martínez J. Alfredo , de Luis Daniel A. , Ramos-Lopez Omar , Tejero María Elizabeth
Published: November 2024

Background/Objectives: Nutrigenetics investigates the role of genetic variants that contribute to the inter-individual variation in response to food intake. Risk factors for cardiovascular disease (CVD) are influenced by the complex interplay of genetic and environmental factors, including the diet. The aim of this scoping review is to analyze the literature on the effect of genotypes on the response to dietary interventions for the treatment of CVD risk factors. Methods: A literature search was conducted in MEDLINE to identify published articles fulfilling the inclusion criteria. Studies published in English between 2014 and 2024 were selected. Data were extracted according to the population, intervention, comparison, and outcome (PICO) format. Results: Forty-eight studies met the inclusion criteria. The studies differed in design, intervention characteristics, tested genotypes, and ancestry. The most frequently analyzed variants were single-nucleotide polymorphisms (SNPs) in genes associated with lipid metabolism, inflammation, and energy balance, among others. The interventions tested the effects of different dietary patterns, diets modified in macronutrient content and types of fat, natural and processed foods, nutraceuticals, and nutrient supplements. Common APOE variants were the most analyzed genotypes showing significant interactions with different dietary interventions affecting blood lipids. Other genotypes found in pathways involving folic acid, lipid metabolism and transport have shown interactions with diverse dietary components across studies. Conclusions: Gene–diet interactions are observed in multiple dietary interventions. Replication of findings of nutrigenetic studies is required across different populations. The response to dietary treatments modifies CVD-related risk factors and shows variation associated with genotypes.
Association Between the Food Environment Around Schools and Food Consumption of Adolescents in Large and Small Municipalities in Southern Brazil
Authors: da Silva Maria Beatriz Carolina , Pinheiro Katiany Claudete , Rockenbach Gabriele , Hinnig Patrícia de Fragas , de Pinho Maria Gabriela Matias , de Souza Lidiamara Dornelles , Lopes Adalberto A. S. , de Vasconcelos Francisco de Assis Guedes , Corrêa Elizabeth Nappi
Published: November 2024

This cross-sectional study aimed to evaluate the association between the consumption of healthy and unhealthy food markers among adolescents enrolled in the ninth grade of elementary school in municipal public schools and the food environment around the schools in two municipalities of different sizes, located in Southern Brazil. The data were collected between 2022 and 2023, with 449 adolescent participants. Of these, 347 were students from the municipality of Florianópolis, and 102 were students from the municipality of Governador Celso Ramos, all aged between 13 and 17 years. The establishments located around the schools were evaluated using AUDITNOVA, an instrument that investigates the environmental dimension and food dimension. The consumption of healthy eating markers (beans, vegetables, and fresh fruits) and unhealthy eating markers (ultra-processed foods, soft drinks, sweets, and fried snacks) among students was assessed using a food frequency questionnaire. Statistically significant associations were observed between the food environment around the school and the consumption of unhealthy food markers (OR = 0.63; 95% CI = 0.41–0.98 p = 0.041) but only in the large municipality. No significant associations were found in the students’ food consumption in the small municipality. A significant association between the school food environment and adolescents’ consumption of unhealthy foods was observed in Florianópolis. Healthy food consumption was low among students in the small municipality, Governador Celso Ramos.
Are the Common Genetic 3′UTR Variants in ADME Genes Playing a Role in Tolerance of Breast Cancer Chemotherapy?
Authors: Tęcza Karolina , Kalinowska-Herok Magdalena , Rusinek Dagmara , Zajkowicz Artur , Pfeifer Aleksandra , Oczko-Wojciechowska Małgorzata , Pamuła-Piłat Jolanta
Published: November 2024

We studied the associations between 3′UTR genetic variants in ADME genes, clinical factors, and the risk of breast cancer chemotherapy toxicity. Those variants and factors were tested in relation to seven symptoms belonging to myelotoxicity (anemia, leukopenia, neutropenia), gastrointestinal side effects (vomiting, nausea), nephrotoxicity, and hepatotoxicity, occurring in overall, early, or recurrent settings. The cumulative risk of overall symptoms of anemia was connected with AKR1C3 rs3209896 AG, ERCC1 rs3212986 GT, and >6 cycles of chemotherapy; leukopenia was determined by ABCC1 rs129081 allele G and DPYD rs291593 allele T; neutropenia risk was correlated with accumulation of genetic variants of DPYD rs291583 allele G, ABCB1 rs17064 AT, and positive HER2 status. Risk of nephrotoxicity was determined by homozygote DPYD rs291593, homozygote AKR1C3 rs3209896, postmenopausal age, and negative ER status. Increased risk of hepatotoxicity was connected with NR1/2 rs3732359 allele G, postmenopausal age, and with present metastases. The risk of nausea and vomiting was linked to several genetic factors and premenopausal age. We concluded that chemotherapy tolerance emerges from the simultaneous interaction of many genetic and clinical factors.
Transcriptome Analysis of Porcine Immune Cells Stimulated by Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) and Caesalpinia sappan Extract
Authors: Arjin Chaiwat , Hnokaew Patipan , Tasuksai Patchara , Thongkham Marninphan , Pringproa Kidsadagon , Arunorat Jirapat , Yano Terdsak , Seel-audom Mintra , Rachtanapun Pornchai , Sringarm Korawan , Chuammitri Phongsakorn
Published: November 2024

The current level of knowledge on transcriptome responses triggered by Caesalpinia sappan (CS) extract in porcine peripheral blood mononuclear cells (PBMCs) after porcine reproductive and respiratory syndrome virus (PRRSV) infection is limited. Therefore, in the present study, we aimed to detect significant genes and pathways involved in CS extract supplementation responsiveness of PBMCs after PRRSV infection. RNA sequencing was conducted on PBMCs, which were isolated from six weaned piglets. The resultant transcriptional responses were examined by mRNA sequencing. Differential expression analysis identified 263 and 274 differentially expressed genes (DEGs) between the PRRSV and CTRL groups, and the PRRSV+CS and CTRL groups, respectively. Among these, ZNF646 and KAT5 emerged as the most promising candidate genes, potentially influencing the interaction between PRRSV-infected PBMCs and CS extract supplementation through the regulation of gene networks and cellular homeostasis during stress. Two pathways were detected to be associated with CS extract supplementation responsiveness: the cellular response to stress pathway and the NF-kB signaling pathway. Consequently, our study reveals a novel mechanism underlying cellular stress response and the NF-κB signaling pathway in PRRSV-infected PBMCs, and identifies a potential application of CS extract for activating the NF-κB signaling pathway. In conclusion, by supplementing CS extract in PBMC cells infected with PRRSV, we found that CS extract modulates PRRSV infection by inducing cellular stress, which is regulated by the NF-κB signaling pathway. This induced stress creates an adverse environment for PRRSV survival. This study contributes to a deeper understanding of the therapeutic targets and pathogenesis of PRRSV infection. Importantly, our results demonstrate that CS extract has the potential to be a candidate for modulating PRRSV infection.
The Trajectory of Damaged-Base Eversion into the Active Site of Apurinic/Apyrimidinic Endonuclease APE1 Regulates This Enzyme’s Substrate Specificity
Authors: Bulygin Anatoly A. , Kuznetsov Nikita A.
Published: November 2024

Apurinic/apyrimidinic endonuclease 1 (APE1) is responsible for the hydrolysis of the phosphodiester bond on the 5′ side of an apurinic/apyrimidinic site during base excision repair. Moreover, in DNA, this enzyme can recognize nucleotides containing such damaged bases as 5,6-dihydro-2′-deoxyuridine (DHU), 2′-deoxyuridine (dU), alpha-2′-deoxyadenosine (αA), and 1,N6-ethenoadenosine (εA). Previously, by pulsed electron–electron double resonance spectroscopy and pre-steady-state kinetic analysis, we have revealed multistep DNA rearrangements during the formation of the catalytic complex. In the present study, the modeling of the eversion trajectory of nucleotides with various damaged bases was performed by directed molecular dynamics simulations. It was found that each damaged base at the beginning of the eversion interacts with protein loop Val196-Arg201, which should be moved to enable further nucleotide eversion. This movement involves a shift in loop Val196-Arg201 away from loop Asn253-Thr257 and requires the disruption of contacts between these loops. The Glu260Ala substitution facilitates the separation of the two loops. Moreover, conformational changes in the Asn253-Thr257 loop should occur in the second half of the lesion eversion trajectory. All these perturbations within the protein globule tend to reduce steric interactions of each damaged base with the protein during the eversion of the nucleotide from DNA and movement to the active site. These perturbations are important determinants of substrate specificity of endonuclease APE1.
Collateral Sensitivity to β-Lactam Antibiotics in Evolved Apramycin-Resistant MRSA
Authors: Wu Jingjing , Wu Shiqian , Liu Juan , Li Changmin , Zheng Mei , Li Fuhao , Zhang Yan , Wu Yashuang , Yu Yang
Published: November 2024

Collateral sensitivity is an evolutionary trade-off for bacteria where acquiring resistance to one antibiotic results in an increased sensitivity to another antibiotic. This study was designed to evaluate the collateral sensitivity of methicillin-resistant Staphylococcus aureus (MRSA) to β-lactam antibiotics induced by the evolution of resistance to apramycin. Collateral sensitivity to ampicillin, cephazolin, ceftriaxone, cefotaxime, cefepime and cefquinome occurred after MRSA were exposed to apramycin and induced to acquire resistance. This sensitivity was associated with reduced β-lactamase activity and decreased expression of the mecA gene. We also found a decrease in the proton motive force and decreased efflux activity. These results provide new insights into collateral sensitivity-based strategies for the treatment of MRSA.
Fed-Batch Strategy Achieves the Production of High Concentration Fermentable Sugar Solution and Cellulosic Ethanol from Pretreated Corn Stover and Corn Cob
Authors: Huang Jiamin , Li Xuezhi , Zhao Jian , Qu Yinbo
Published: November 2024

The bioconversion of lignocellulosic biomass, which are abundant and renewable resources, into liquid fuels and bulk chemicals is a promising solution to the current challenges of resource scarcity, energy crisis, and carbon emissions. Considering the separation of some end-products, it is necessary to firstly obtain a high concentration separated fermentable sugar solution, and then conduct fermentation. For this purpose, in this study, using acid catalyzed steam explosion pretreated corn stover (ACSE-CS) and corn cob residues (CCR) as cellulosic substrate, respectively, the batch feeding strategies and enzymatic hydrolysis conditions were investigated to achieve the efficient enzymatic hydrolysis at high solid loading. It was shown that the fermentable sugar solutions of 161.2 g/L and 205 g/L were obtained, respectively, by fed-batch enzymatic hydrolysis of ACSE-CS under 30% of final solid loading with 10 FPU/g DM of crude cellulase, and of CCR at 27% of final solid loading with 8 FPU/g DM of crude cellulase, which have the potential to be directly applied to the large-scale fermentation process without the need for concentration, and the conversion of glucan in ACSE-CS and CCR reached 80.9% and 87.6%, respectively, at 72 h of enzymatic hydrolysis. This study also applied the fed-batch simultaneous saccharification and co-fermentation process to effectively convert the two cellulosic substrates into ethanol, and the ethanol concentrations in fermentation broth reached 46.1 g/L and 72.8 g/L for ACSE-CS and CCR, respectively, at 144 h of fermentation. This study provides a valuable reference for the establishment of “sugar platform” based on lignocellulosic biomass and the production of cellulosic ethanol.