bluuebunny/crossref_metadata_2025 huggingface dataset:
Ambivalence model of suicidality [ABS-model]: an orientation model for the treatment of suicidal individuals
Authors: Teismann Tobias , Britton Peter C. , Forkmann Thomas
Published: November 2024

The existing models for understanding suicidal ideation and behavior do not provide satisfactory orientation for clinical-therapeutic work with suicidal clients. Based on the observation that ambivalence accompanies the entire suicidal process and building on the empirical knowledge about suicidal ambivalence, this article presents the ambivalence model of suicidality (ABS model), a new clinical working model that aims to provide a framework for risk assessment, case conceptualization and treatment planning in the treatment of suicidal individuals. The model divides the suicidal process into three phases (uncertainty phase, transition phase and action phase), describes the psychological state within the different phases, and identifies phase-specific therapeutic interventions. The ABS model is a descriptive model that can be used to structure and organize crisis intervention and psychotherapy with suicidal patients.
The construction and validation of the novel nomograms for the risk prediction of prenatal depression: a cross-sectional study
Authors: Huo Lanting , Yu Xingfeng , Nisar Anum , Yang Lei , Li Xiaomei
Published: November 2024

Background

Nomograms are superior to traditional multivariate regression models in the competence of quantifying an individual’s personalized risk of having a given condition. To date, no literature has been found to report a quantified risk prediction model for prenatal depression. Therefore, this study was conducted to investigate the prevalence and associated factors of prenatal depression. Moreover, two novel nomograms were constructed for the quantitative risk prediction.

Methods

In this cross-sectional study, the participants were recruited using convenience sampling and administered with the research questionnaires. The prevalence of prenatal depression was calculated with a cutoff point of ≥ 10 in the 8-item Patient Health Questionnaire. Univariate and multivariate binomial logistic regression models were subsequently employed to identify the associated factors of prenatal depression. Two nomograms for the risk prediction were constructed and multiple diagnostic parameters were used to examine their performances.

Results

The prevalence of prenatal depression was 9.5%. Multivariate binomial logistic regression model based on sociodemographic, health-related, and pregnancy-related variables (model I) suggested that unemployment, poor relationship with partners, antecedent history of gynecologic diseases, unplanned pregnancy, an earlier stage of pregnancy, and more severe vomiting symptoms were associated with increased risk of prenatal depression. In the regression model that further included psychosocial indicators (model II), unemployment, antecedent history of gynecologic diseases, unplanned pregnancy, an earlier stage of pregnancy, and a higher total score in the Pregnancy Stress Rating Scale were found to be associated with prenatal depression. The diagnostic parameters suggested that both nomograms for the risk prediction of prenatal depression have satisfactory discriminative and predictive efficiency and clinical utility. The nomogram based on model II tended to have superior performances and a broader estimating range and that based on model I could be advantageous in its ease of use.

Conclusions

The prevalence of prenatal depression was considerably high. Risk factors associated with prenatal depression included unemployment, poor relationship with partners, antecedent history of gynecologic diseases, unplanned pregnancy, an earlier stage of pregnancy, more severe vomiting symptoms, and prenatal stress. The risk prediction model I could be used for fasting screening, while model II could generate more precise risk estimations.
A rapid review of digital approaches for the participatory development of health-related interventions
Authors: Doerwald Friederike , Stalling Imke , Recke Carina , Busse Heide , Shrestha Rehana , Rach Stefan , Bammann Karin
Published: November 2024

Objectives

Using participatory approaches to design health interventions is promising, and the ongoing digitalization has enabled the development of diverse digital formats for this purpose. These digital formats bring forth distinct advantages and challenges that should be carefully considered. This rapid review aims to present an overview of digital formats employed in participatory health intervention development and their reported benefits and barriers.

Design

A qualitative rapid review was conducted, following recommendations by the Cochrane Rapid Reviews Methods Group. The literature search was carried out in October 2022 and encompassed the PubMed, Embase, PsycINFO, and Cochrane CENTRAL databases. Studies were included if they were published in 2010 or later and reported the development of a health-related intervention employing digital formats in the participatory process.

Results

A total of 22 studies were included. We identified three types of digital formats used for participatory health intervention development: web-based participatory formats (n = 14), digital participatory visual formats (n = 5), and digital participatory mapping (n = 3). The reported benefits of applying digital formats included enhanced participant anonymity, increased time and cost efficiency, and more flexibility regarding scheduling and extent of participation. Among the reported barriers were sufficient internet connectivity, required technical skills, and online fatigue.

Conclusion

The review shows a variety of digital formats employed to develop participatory health interventions. Yet, these methods are primarily digital adaptations of pre-existing analog formats. Innovative digital approaches involving, for example, virtual reality devices remain largely unused. The review also revealed a need for establishing shared terminology and reporting standards to facilitate communication, comparison, and synthesis of findings in this evolving area of research.
The association between the COVID-19 pandemic and interpersonal relationships among youth with a child maltreatment history
Authors: McCarthy Julie-Anne , Osorio Ana M. , Taillieu Tamara L. , Stewart-Tufescu Ashley , Afifi Tracie O.
Published: November 2024

Introduction

The COVID-19 pandemic had significant impacts on youth health and well-being. Youth with prior inequities, such as those exposed to child maltreatment, may have experienced greater psychosocial challenges and long-term difficulties than their peers, including sustained interpersonal relationships problems. Given the importance of healthy relationships during adolescence and early adulthood, the significant impact the pandemic had on youth, and the potential disproportionate challenges for youth with a child maltreatment history, the purpose of the present study was to better understand changes in relational conflict among youth with and without a child maltreatment history from the perspectives of youth themselves. Specifically, the aims were to examine if youth child maltreatment history was associated with an increased likelihood of reporting increased conflict with (a) parents, (b) siblings, or (c) intimate partners during the first three years of the COVID-19 pandemic.

Methods

Data were drawn from the Well-Being and Experiences (WE) Study; a longitudinal and intergenerational cohort study of 1,000 youth/parent dyads in Manitoba, Canada that began in 2017. WE study data were collected annually via self-reported youth surveys between 2017 and 2022 for a total of 5 waves of data collection, and COVID-19 questions were included in Waves 3 (2020), 4 (2021) and 5 (2022) (n = 586, 56.43% female, ages 18 to 21 at Wave 5). Multinomial regressions models were computed to examine whether a youth's child maltreatment history was associated with increased, decreased, or consistent levels of conflict with parents, siblings, and intimate partners in 2020, 2021, and 2022 compared to pre-pandemic levels.

Results

Results indicated that compared to youth with no child maltreatment history, youth with a child maltreatment history were more likely to report increased conflict across all three types of relationships during first three years of the pandemic.

Discussion

Findings contribute to our understanding of the association between the COVID-19 pandemic and interpersonal relationships among youth who have a child maltreatment history compared to their peers without child maltreatment histories, signal potential long-term challenges or inequities for youth and families with a history of maltreatment, and may inform policy, programming, intervention, and recovery efforts in the post-COVID-19 period, and for future global emergencies.
Simulating the psychological and neural effects of affective touch with soft robotics: an experimental study
Authors: Zheng Caroline Y. , Wang Ker-Jiun , Wairagkar Maitreyee , von Mohr Mariana , Lintunen Erik , Fotopoulou Aikaterini
Published: November 2024

Human affective touch is known to be beneficial for social-emotional interactions and has a therapeutic effect. For touch initiated by robotic entities, richer affective affordance is a critical enabler to unlock its potential in social-emotional interactions and especially in care and therapeutic applications. Simulating the attributes of particular types of human affective touch to inform robotic touch design can be a beneficial step. Inspired by the scientific finding on CT-optimal affective touch - a gentle skin stroking at velocities of 1–10 cm/s evidenced to be pleasant and calming, we developed a proof-of-concept haptic rendering system - S-CAT, using pneumatic silicone soft robotic material to simulate the attributes (velocity, temperature and applied normal force) of CT-optimal affective touch. To investigate whether the affective touch performed by the S-CAT system elicits psychological effects comparable to CT-optimal, manual affective touch, we conducted an experimental study comparing the effects of CT-optimal versus non-CT-optimal stimulation velocities in each of three types of stimulation modes (S-CAT device, skin-to-skin manual stroking, hairbrush manual stroking), and across them. Our measures included subjective ratings of touch pleasantness and intensity, neurophysiological responses (EEG), and qualitative comments. Our results showed that velocity modulated subjective and neurophysiological responses in each and across these three stimulation modes, and that CT-optimal stimulations from S-CAT system and manual method received similar ratings and verbal comments on pleasantness, suggesting that the S-CAT touch can have comparable effects to manual stroking. We discuss the design insights learned and the design space that this study opens up to support well-being and healthcare.
Unlocking the potential of neuromuscular electrical stimulation: achieving physical activity benefits for all abilities
Authors: Ackermann Paul W. , Juthberg Robin , Flodin Johanna
Published: November 2024

Neuromuscular Electrical Stimulation (NMES) uses electrical impulses to induce muscle contractions, providing benefits in rehabilitation, muscle activation, and as an adjunct to exercise, particularly for individuals experiencing immobilization or physical disability. NMES technology has significantly progressed, with advancements in device development and a deeper understanding of treatment parameters, such as frequency, intensity, and pulse duration. These improvements have expanded NMES applications beyond rehabilitation to include enhanced post-exercise recovery, improved blood glucose uptake, and increased lower limb venous return, potentially reducing thrombotic risks. Despite its benefits, NMES faces challenges in user compliance, often due to improper electrode placement and discomfort during treatment. Research highlights the importance of optimizing stimulation parameters, including electrode positioning, to improve both comfort and treatment efficacy. Recent innovations, such as automated processes for locating optimal stimulation points and adaptable electrode sizes, aim to address these issues. When combined with wearable technologies, these innovations could improve NMES treatment adherence and deliver more consistent, long-term therapeutic outcomes for patients with various physical limitations. Together, these developments indicate a promising future for NMES, presenting a valuable tool to enhance the benefits of physical activity across diverse populations, from rehabilitative care to broader health and wellness applications.
Serum-derived host miR-423-5p and miR-378a-3p as molecular markers for severe tuberculosis: a promising prognostic tool for survival
Authors: Hurtado Joaquin , Buroni María , Giordano Alvaro , Nin Nicolas , Hurtado F. Javier , Tosar Juan Pablo , Robello Carlos , Greif Gonzalo
Published: November 2024

Tuberculosis (TB) remains a leading cause of infectious disease-related mortality. Annually, 10 million people contract TB, resulting in 1.5 million deaths, despite being a preventable and curable disease. Severe TB cases necessitate Intensive Care Unit (ICU) admission, with mortality rates ranging from 15.5 to 65.9%. Recent research highlights the role of microRNAs (miRNAs) in infectious disease diagnosis, with studies reporting distinct miRNA profiles in active pulmonary TB and sputum samples. This study aims to identify miRNAs as potential prognostic biomarkers for severe TB in ICU patients. Total RNA was extracted from the serum of ICU TB patients and controls. miRNA libraries were prepared and high throughput sequenced using a MiSeq Illumina platform. Differential miRNA abundance between patients and controls was analyzed with sRNAtoolbox, and DESeq2 was used for comparisons. Results demonstrated three differentially abundant miRNAs in severe TB patients' serum, validated by RT-qPCR. Stratifying patients by outcome revealed a significant difference in the ratio between two miRNAs: hsa-miR-378a-3p and hsa-miR-423-5p. The analysis showed that a miRNA-423-5p/miRNA-378a-3p ratio < 27 is associated with a poor prognosis, highlighting its potential as a prognostic indicator of disease severity. These findings are promising and warrant validation, while assessing these biomarkers in non-severe TB settings could further help identify more aggressive forms of the disease. In conclusion, this study explores the potential of circulating miRNAs as prognostic tools for severe TB cases in the ICU, offering a promising avenue for improving clinical decision-making and patient outcomes. Further validation and exploration in diverse TB contexts are essential for comprehensive understanding and application.
The first meta-analysis of the G96S single nucleotide polymorphism (SNP) of the prion protein gene (PRNP) with chronic wasting disease in white-tailed deer
Authors: Won Sae-Young , Kim Yong-Chan
Published: November 2024

Background

Prion diseases are irreversible infectious neurodegenerative diseases caused by a contagious form of prion protein (PrPSc). Since chronic wasting disease (CWD)-infected white-tailed deer are strong carriers of the prion seed through corpses via scavenger animals, preemptive control based on genetic information for a culling system is necessary. However, the risk of CWD-related genetic variants has not been fully evaluated. In the present study, we carried out a quantitative estimation of the risk of a G96S single nucleotide polymorphism (SNP) of the PRNP gene to CWD infection in white-tailed deer.

Methods

We carried out a literature search for genetic data of the G96S (c.286G>A) SNP of the PRNP gene from CWD-infected white-tailed deer and matched controls. We performed a meta-analysis using incorporated eligible studies to evaluate the association of the G96S SNP of the PRNP gene with susceptibility to CWD in white-tailed deer.

Results

We identified a strong association between the G96S (c.286G>A) SNP of the PRNP gene and susceptibility to CWD infection in white-tailed deer using meta-analysis. We observed the most significant association in the recessive model (odds ratio = 3.0050, 95% confidence interval: 2.0593; 4.3851, p < 0.0001), followed by the additive model (odds ratio = 2.7222, 95% confidence interval: 1.9028; 3.8945, p < 0.0001) and the heterozygote (AA vs. AG) comparison (odds ratio = 2.7405, 95% confidence interval: 1.9215; 3.9085, p < 0.0001).

Conclusion

To the best of our knowledge, this was the first meta-analysis of the association between the G96S (c.286G>A) SNP of the PRNP gene and susceptibility to CWD infection.
Efficient Discretization of the Laplacian: Application to Moving Boundary Problems
Authors: Castillo Sebastian-Josue , Izsák Ferenc
Published: November 2024

An efficient approximation is developed for the Laplacian operator by merging the advances of finite difference and finite element approximations. This approach is applicable to a general quadrilateral grid. The optimal coefficients for the approximation are computed using a pointwise optimization process. In this process, an overdetermined system is solved in the least-square sense using weighted polynomial approximation. The proposed algorithm is a vectorized procedure, keeping the computational time at a low level. The performance of this method is demonstrated on a model problem involving the numerical solution of a Poisson problem. Its true potential is evident when applied to moving boundary problems, which typically require a dynamic grid for efficient simulation. Within the framework of the proposed algorithm, we can compute the spatial discretization on the new grid quickly. This procedure is tested in the Stefan problem. For this, we give the simulation algorithm in detail utilizing the quadrilateral grid geometry. The performance is again demonstrated in a series of numerical experiments.
Intermittent Short Circuit Fault Location for CAN Based on Two-Port Network Modeling
Authors: Wang Longkai , Yang Yi , Lei Yong
Published: November 2024

The Controller Area Network (CAN) has been adopted in various reliability-critical industrial systems. However, intermittent connection (IC) problems of network cables may worsen system performance and even threaten operational safety. Recently, there have been several studies on diagnosing intermittent open circuit faults, but the intermittent short circuit (ISC) fault diagnosis has not been addressed. In this paper, a novel ISC fault location method for CANs is proposed based on two-port network modeling. First, the CAN network is modeled as a switched system that depends on the states of the sending nodes using a two-port network approach. An equivalent circuit model and a voltage transfer difference function (VTDF) group are derived for each state where one particular node is sending. Second, upon each fault, corresponding direction events are defined by comparing the two VTDF values that are calculated from the voltages collected at network ends. Then, the fault and health domains can be determined by integrating these direction events with the network topology information according to their statistical significance. Third, a bidirectional eviction localization algorithm is developed to identify ISC fault locations based on the fault and health domains. A testbed is constructed, and case studies are conducted to demonstrate that the proposed method can correctly locate the ISC faults in various network topological layouts.
Human Preferences for Dogs and Cats in China: The Current Situation and Influencing Factors of Watching Online Videos and Pet Ownership
Authors: Zhang Xu , He Yuansi , Yang Shuai , Wang Daiping
Published: November 2024

Dogs and cats have become the most important and successful pets through long-term domestication. People keep them for various reasons, such as their functional roles or for physical or psychological support. However, why humans are so attached to dogs and cats remains unclear. A comprehensive understanding of the current state of human preferences for dogs and cats and the potential influential factors behind it is required. Here, we investigate this question using two independent online datasets and anonymous questionnaires in China. We find that current human preferences for dog and cat videos are relatively higher than for most other interests, video plays ranking among the top three out of fifteen interests. We also find genetic variations, gender, age, and economic development levels notably influence human preferences for dogs and cats. Specifically, dog and cat ownership are significantly associated with parents’ pet ownership of dogs and cats (Spearman’s rank correlation coefficient is 0.43, 95% CI: 0.38–0.47), and the primary reason is to gain emotional support. Further analysis finds that women, young people, and those with higher incomes are more likely to prefer dog and cat videos. Our study provides insights into why humans become so attached to dogs and cats and establishes a foundation for developing co-evolutionary models.
Dendrite-Free Zn Anode Modified by Organic Coating for Stable Aqueous Zinc Ion Batteries
Authors: Li Fujie , Zhang Hongfei , Liu Xuehua , Xu Binghui , Wang Chao
Published: November 2024

Aqueous zinc-ion batteries (AZIBs) have emerged as highly promising options for large-scale energy storage systems due to their cost-effectiveness, substantial energy capacity, and improved safety features. However, the Zn anode faces challenges such as self-corrosion and dendrite formation, which limit its practical use in AZIB applications. In this work, a simple blade-coating method was used to successfully coat poly (vinylidene fluoride–hexafluoro propylene) (PVDF-HFP) on the Zn anode. The coated Zn anode (P-Zn) displayed a stable cycling performance (700 h) at 1 mA cm−2 current density in the symmetric cell. In addition, the full cell using MnO2 as the cathode and P-Zn as the anode retained almost full capacity even after 1400 cycles at 2C, far outperforming the full cell using the unmodified Zn anode with only 50% capacity retention after 600 cycles. In situ optical observations of Zn deposition demonstrate that the special organic coating significantly enhances the uniform deposition of Zn2+, thus effectively mitigating corrosion and hydrogen evolution. Density Functional Theory (DFT) calculations show that the PVDF-HFP coating effectively narrows the adsorption energy gap between the P-Zn (002) and (101) planes, leading to the homogeneous deposition of Zn2+ with fewer Zn dendrites. A simple and feasible strategy for designing ultra-stable AZIBs by coating an organic protective layer on the Zn surface is provided by this work.
Pleiotropic Effects of PCSK9 Inhibitors on Cardio-Cerebrovascular Diseases
Authors: Li Zhenzhen , Zhu Lin , Xu Yeqiong , Zhang Yiting , Liu Yukai , Sun Huiling , Li Shuo , Wang Meng , Jiang Teng , Zhou Junshan , Deng Qiwen
Published: November 2024

Cardiovascular disease (CVD) and ischemic stroke (IS) are the primary causes of mortality worldwide. Hypercholesterolemia has been recognized as an independent risk factor for CVD and IS. Numerous clinical trials have unequivocally demonstrated that reducing levels of low-density lipoprotein cholesterol (LDL-C) significantly mitigates the risk of both cardiac and cerebral vascular events, thereby enhancing patient prognosis. Consequently, LDL-C reduction remains a pivotal therapeutic strategy for CVD and IS. However, despite intensive statin therapy, a significant proportion of high-risk hypercholesterolemic patients fail to achieve sufficient reductions in LDL-C levels. In response to this challenge, an inhibitor targeting proprotein convertase subtilisin-kexin type 9 (PCSK9) has been developed as a therapeutic intervention for hyperlipidemia. Numerous randomized controlled trials (RCTs) have conclusively demonstrated that the combination of PCSK9 inhibitors and statins significantly enhances prognosis not only in patients with CVD, but also in those afflicted with symptomatic intracranial artery stenosis (sICAS). PCSK9 inhibitors significantly reduce LDL-C levels by binding to the PCSK9 molecule and preventing its interaction with LDLRs. This prevents degradation of the receptor and increases uptake of LDL-C, thereby decreasing its concentration in blood. Besides significantly reducing LDL-C levels, PCSK9 inhibitors also demonstrate anti-inflammatory and anti-atherosclerotic properties while promoting plaque stabilization and inhibiting platelet aggregation and thrombosis. This article aims to provide a comprehensive review based on the relevant literature regarding the evolving understanding of pleiotropic effects associated with PCSK9 inhibitors, particularly focusing on their impact on the cardiovascular system and central nervous system.
Expanding the Molecular Genetic Landscape of Dystrophinopathies and Associated Phenotypes
Authors: Neuhoff Katja , Kilicarslan Ozge Aksel , Preuße Corinna , Zaum Ann-Kathrin , Kölbel Heike , Lochmüller Hanns , Schara-Schmidt Ulrike , Polavarapu Kiran , Roos Andreas , Gangfuß Andrea
Published: November 2024

Background/Objectives: X-linked dystrophinopathies are a group of neuromuscular diseases caused by pathogenic variants in the DMD gene (MIM *300377). Duchenne muscular dystrophy (DMD; MIM #310200) is the most common inherited muscular dystrophy. Methods: We screened datasets of 403 male, genetically confirmed X-linked dystrophinopathy patients and identified 13 pathogenic variants of the DMD gene that have not been described in the literature thus far. For all patients we provide additional data on the clinical course, genotype–phenotype correlations as well as histological datasets of nine patients. In two cases, we used RNA-Seq analyses, showing that this method can be particularly helpful in cases of deep intrinsic variants. Results: We were able to show, that a combination of the different datasets is helpful to counsel families and provides a better understanding of the underlying pathophysiology. Conclusions: Overall, we elaborated upon the persistent challenge of determining the course of disease from genetic analysis alone, rather supporting the concept of a clinical continuum of dystrophinopathies with our combined clinical, histological and molecular genetic findings.
Emotion Classification from Electroencephalographic Signals Using Machine Learning
Authors: Mendivil Sauceda Jesus Arturo , Marquez Bogart Yail , Esqueda Elizondo José Jaime
Published: November 2024

Background: Emotions significantly influence decision-making, social interactions, and medical outcomes. Leveraging emotion recognition through Electroencephalography (EEG) signals offers potential advancements in personalized medicine, adaptive technologies, and mental health diagnostics. This study aimed to evaluate the performance of three neural network architectures—ShallowFBCSPNet, Deep4Net, and EEGNetv4—for emotion classification using the SEED-V dataset. Methods: The SEED-V dataset comprises EEG recordings from 16 individuals exposed to 15 emotion-eliciting video clips per session, targeting happiness, sadness, disgust, neutrality, and fear. EEG data were preprocessed with a bandpass filter, segmented by emotional episodes, and split into training (80%) and testing (20%) sets. Three neural networks were trained and evaluated to classify emotions from the EEG signals. Results: ShallowFBCSPNet achieved the highest accuracy at 39.13%, followed by Deep4Net (38.26%) and EEGNetv4 (25.22%). However, significant misclassification issues were observed, such as EEGNetv4 predicting all instances as “Disgust” or “Neutral” depending on the configuration. Compared to state-of-the-art methods, such as ResNet18 combined with differential entropy, which achieved 95.61% accuracy on the same dataset, the tested models demonstrated substantial limitations. Conclusions: Our results highlight the challenges of generalizing across emotional states using raw EEG signals, emphasizing the need for advanced preprocessing and feature-extraction techniques. Despite these limitations, this study provides valuable insights into the potential and constraints of neural networks for EEG-based emotion recognition, paving the way for future advancements in the field.
Correction: Rossi et al. Colorectal Cancer and Alcohol Consumption—Populations to Molecules. Cancers 2018, 10, 38
Authors: Rossi Marco , Jahanzaib Anwar Muhammad , Usman Ahmad , Keshavarzian Ali , Bishehsari Faraz
Published: November 2024

There was a mistake in the introduction section as published [...]
DNA Methylation Panels for the Differentiation of Lung and Gastric Adenocarcinomas from Other Common Primary Adenocarcinomas
Authors: Draškovič Tina , Omahen Lara , Jerše Maja , Zidar Nina , Hauptman Nina
Published: November 2024

Background/Objectives: Gastric and lung adenocarcinomas are among the most common adenocarcinomas worldwide. Our research aimed to validate methylation biomarkers that differentiate gastric and lung adenocarcinomas from hepatocellular carcinoma, cholangiocarcinoma, colorectal carcinoma, pancreatic adenocarcinoma and paired healthy tissues. Methods: The study analyzed 178 formalin-fixed, paraffin-embedded tissue samples, including 14 gastric adenocarcinomas, 15 lung adenocarcinomas, 15 hepatocellular carcinomas, 15 cholangiocarcinomas, 15 colorectal carcinomas, 15 pancreatic adenocarcinomas and their paired healthy tissues. Methylation status was determined experimentally by methylation-sensitive high resolution melting. The diagnostic panels were validated on bioinformatics datasets from The Cancer Genome Atlas and Gene Expression Omnibus, comprising 1981 and 773 samples, respectively. Sensitivity, specificity, diagnostic accuracy and predictive values for each cancer type were calculated for the experimental, Gene Expression Omnibus and The Cancer Genome Atlas datasets. Results: The gastric cancer-specific panel showed a sensitivity of 78.6–83.9%, a specificity of 86.6–94.6% and a diagnostic accuracy of 89.9–96.1% to differentiate between all tumors, and a sensitivity of 78.6–83.9%, a specificity of 89.2–96.4% and a diagnostic accuracy of 88–96.1% to differentiate between all tumors and healthy tissues. The lung adenocarcinoma-specific panel showed a sensitivity of 61.1–93.3%, a specificity of 70.3–90.8% and a diagnostic accuracy of 74.2–90.6% to differentiate between all tumors, and a sensitivity of 61.1–93.3%, a specificity of 77.9–93.4% and a diagnostic accuracy of 79.2% to 93.1% to differentiate between all tumors and healthy tissues. Conclusions: This study demonstrates the potential of using diagnostic methylation panels to differentiate gastric and lung adenocarcinomas from other common adenocarcinomas and paired healthy tissues.
Into the Future: Fighting Melanoma with Immunity
Authors: Corica Derek A. , Bell Scott D. , Miller Peyton J. , Kasperbauer Daniel T. , Lawler Nicholas J. , Wakefield Mark R. , Fang Yujiang
Published: November 2024

Immunotherapy offers a novel and promising option in the treatment of late-stage melanoma. By utilizing the immune system to assist in tumor destruction, patients have additional options after tumor progression. Immune checkpoint inhibitors reduce the ability for tumors to evade the immune system by inhibiting key surface proteins used to inactivate T-cells. Without these surface proteins, T-cells can induce cytotoxic responses against tumors. Tumor infiltrating lymphocyte therapy is a form of adoptive cell therapy that takes advantage of a small subset of T-cells that recognize and infiltrate tumors. Isolation and rapid expansion of these colonies assist the immune system in mounting a charged response that can induce remission. Tumor vaccines deliver a high dose of unique antigens expressed by tumor cells to the entire body. The introduction of large quantities of tumor antigens upregulates antigen presenting cells and leads to effective activation of the immune system against tumors. Cytokine therapy introduces high amounts of chemical messengers that are endogenous to the immune system and support T-cell expansion. While other methods of immunotherapy exist, immune checkpoint inhibitors, tumor infiltrating lymphocytes, tumor vaccines, and cytokine therapy are commonly used to treat melanoma. Like many other cancer treatments, immunotherapy is not without adverse effects, as toxicities represent a major obstacle. However, immunotherapy has been efficacious in the treatment of melanoma.
New Insights into Mucosa-Associated Microbiota in Paired Tumor and Non-Tumor Adjacent Mucosal Tissues in Colorectal Cancer Patients
Authors: González Adriana , Fullaondo Asier , Navarro David , Rodríguez Javier , Tirnauca Cristina , Odriozola Adrian
Published: November 2024

Background/Objective: Colorectal cancer (CRC) is one of the most common cancers worldwide. Increasing scientific evidence supports the idea that gut microbiota dysbiosis accompanies colorectal tumorigenesis, and these changes could be causative. Implementing gut microbiota analysis in clinical practice is limited by sample type, sequencing platform and taxonomic classification. This article aims to address these limitations, providing new insights into the microbiota associated with CRC pathogenesis and implementing its analyses in personalized medicine. Methods: To that aim, we evaluate differences in the bacterial composition of 130 paired tumor and non-tumor adjacent tissues from a cohort of CRC patients from the Biobank of the University of Navarra, Spain. The V3–V4 region of the 16S rRNA gene was amplified, sequenced using the MinION platform, and taxonomically classified using the NCBI database. Results: To our knowledge, this is the first study to report an increased relative abundance of Streptococcus periodonticum and a decreased relative abundance of Corynebacterium associated with CRC. Genera such as Fusobacterium, Leptotrichia and Streptococcus showed higher relative abundances in tumor than in non-tumor tissues, as previously described in the literature. Specifically, we identified higher levels of Fusobacterium animalis, Fusobacterium nucleatum, Fusobacterium polymorphum and S. periodonticum in tumor tissues. In contrast, genera such as Bacteroides and Corynebacterium showed lower relative abundances in tumor tissues. There were also differences at the taxonomic level between tumor locations. Conclusions: These results, consistent with previous studies, further support the hypothesis that Leptotrichia and Fusobacterium contribute to CRC progression, with F. nucleatum and F. animalis proposed as key CRC pathogenic taxa. Overall, these results contribute to a better understanding of the CRC-associated microbiota, addressing critical barriers to its implementation in personalized medicine.
Reliability of Automated RECIST 1.1 and Volumetric RECIST Target Lesion Response Evaluation in Follow-Up CT—A Multi-Center, Multi-Observer Reading Study
Authors: Dahm Isabel C. , Kolb Manuel , Altmann Sebastian , Nikolaou Konstantin , Gatidis Sergios , Othman Ahmed E. , Hering Alessa , Moltz Jan H. , Peisen Felix
Published: November 2024

Objectives: To evaluate the performance of a custom-made convolutional neural network (CNN) algorithm for fully automated lesion tracking and segmentation, as well as RECIST 1.1 evaluation, in longitudinal computed tomography (CT) studies compared to a manual Response Evaluation Criteria in Solid Tumors (RECIST 1.1) evaluation performed by three radiologists. Methods: Baseline and follow-up CTs of patients with stage IV melanoma (n = 58) was investigated in a retrospective reading study. Three radiologists performed manual measurements of metastatic lesions. Fully automated segmentations were generated, and diameters and volumes were computed from the segmentation results, with subsequent RECIST 1.1 evaluation. We measured (1) the intra- and inter-reader variability in the manual diameter measurements, (2) the agreement between manual and automated diameter measurements, as well as the resulting RECIST 1.1 categories, and (3) the agreement between the RECIST 1.1 categories derived from automated diameter measurement compared to automated volume measurements. Results: In total, 114 target lesions were measured at baseline and follow-up. The intraclass correlation coefficients (ICCs) for the intra- and inter-reader reliability of the diameter measurements were excellent, being >0.90 for all readers. There was moderate to almost perfect agreement when comparing the timepoint response category derived from the mean manual diameter measurements from all three readers with those derived from automated diameter measurements (Cohen’s k 0.67–0.76). The agreement between the manual and automated volumetric timepoint responses was substantial (Fleiss’ k 0.66–0.68) and that between the automated diameter and volume timepoint responses was substantial to almost perfect (Cohen’s k 0.81). Conclusions: The automated diameter measurement of preselected target lesions in follow-up CT is reliable and can potentially help to accelerate RECIST evaluation.
Assessment of Linguistic Profile of Oral-Language-Proficient Hearing-Impaired Children Using Clinical Evaluation of Language Fundamentals: Fifth Edition (CELF5)
Authors: Durán-Bouza Montserrat , Pernas Lorena , Brenlla-Blanco Juan-Carlos
Published: November 2024

Background/Objectives: Specific tests for the assessment of language development and language skills in deaf children are scarce. For this reason, parent inventories and/or standardized tests that are reliable and valid in the hearing population are used. The main aim of this study was to assess the usefulness of the Clinical Evaluation of Language Fundamentals 5 (CELF5) in determining the language skills of hearing-impaired children in a comprehensive way in comparison to their hearing peers. Methods: The sample consisted of 70 deaf and 73 hearing children aged 5–11 years. Although the results show statistically significant differences in language skills between deaf and hearing children, deaf children scored around average on 8 of the 12 subtests of the CELF5. Results: Children using total communication modality had the highest scores, followed by those using oral language and sign language. The CELF5 subtests showed high internal consistency in the deaf group. A percentile scale was also developed for this population group. Conclusions: The CELF5 showed to be a reliable test for the assessment of receptive and expressive language in children with deafness who are competent in oral language. However, further research is needed to develop language assessment tests adapted to the deaf population that are sensitive to different communication modalities.
Prevalence of Overweight and Obesity and Association with Risk Factors in Secondary School Children in Croatia
Authors: Matana Antonela , Krajinović Helena
Published: November 2024

Background: Childhood and adolescent overweight and obesity represent significant global health concerns. The primary objective of this study was to assess the prevalence and associations of some potential risk factors with overweight and obesity among Croatian adolescents aged 15 to 18. Methods: This cross-sectional study included 344 secondary school students from Croatia’s Mediterranean region, with data collected through an anonymous questionnaire. The questionnaire gathered sociodemographic information, adherence to the Mediterranean diet of both children and their parents, and the children’s dietary habits and physical activity levels. Results: Weight status data revealed that 2.6% of participants were underweight, 82% had normal weight, 11% were overweight, and 4.4% were classified as obese. The results indicated that boys (p < 0.001), children who skip breakfast (p = 0.031), those with less active lifestyles compared to their peers (p = 0.001), children whose mothers have a higher BMI (p < 0.001), and children from smaller families (p = 0.034) are at greater risk of being overweight or obese. Conclusions: This study provides valuable insights into the risk factors associated with overweight and obesity in this age group, which can support the development of targeted strategies for this population.
Study on Infrared Spectrum Analysis of Asphalt Aging Based on Full Spectrum Segmentation
Authors: Zhou Hao , Zhao Pinhui , Xu Qiang , Han Kechao , Zhang Guixia , Cui Jipeng , Meng Weikun , Wu Wenxin
Published: November 2024

Infrared spectroscopy is an effective method for studying asphalt aging. To improve the effectiveness of infrared spectroscopy in asphalt aging, this paper first performs preprocessing of the infrared spectral signals and divides the full spectrum into six segments. By quantitative analysis of the relation of noise and signals of different segments, a correlation model between noise and errors was established and a reasonable signal analysis range was determined. A stable method for describing the aging degree, which is based on the area change values of the infrared spectral curve over a wide wavelength range, was determined, and the aging model was established. Based on the relationship between PAV aging and natural aging, a model has been established to describe the relationship between the spectral area increase and aging in the asphalt pavement aging process. This model can be used to determine the actual service time of the asphalt pavement through infrared spectral analysis.
Multi-UAV Obstacle Avoidance and Formation Control in Unknown Environments
Authors: Li Yawen , Zhang Pengfei , Wang Zhongliu , Rong Dian , Niu Muyang , Liu Cong
Published: November 2024

To address the issues of local minima, target unreachability, and significant formation disruption during obstacle avoidance in the conventional artificial potential field (APF), a control approach that integrates APF with optimal consensus control which can achieve cooperative obstacle avoidance is proposed. Based on the double integrator multi-UAV formation model with a fixed undirected communication topology, the optimal consensus control protocol incorporating an obstacle avoidance cost function is introduced. This addresses the limitations of APF-based obstacle avoidance while simultaneously managing multi-UAV formation control. Training interactions in randomly generated unknown obstacle environments are conducted using Random Search for Hyperparameter Optimization (RSHO). Combined with the evaluation model, select the optimal solution of the consensus performance index, control consumption performance index, and obstacle avoidance performance index parameters of the multi-UAV formation control system. Furthermore, a virtual repulsive potential field is designed for each UAV to prevent inter-UAV collisions during obstacle avoidance. Simulation results show that the improved APF (IAPF) with optimal consensus control effectively overcomes the limitations of conventional APF. It achieves multi-UAV formation obstacle avoidance control in unknown environments and avoids the phenomenon of inter-UAV collisions during the obstacle avoidance process while maintaining formation integrity, accelerating formation reconfiguration and convergence, reducing consensus consumption and control loss due to obstacle avoidance, shortening mission time, and enhancing obstacle avoidance efficiency, highlighting the superiority of multi-UAV formation obstacle avoidance.
Guaranteed Performance Resilient Security Consensus Control for Nonlinear Networked Control Systems Under Asynchronous DoS Cyber Attacks and Applications on Multi-UAVs Networks
Authors: Zhou Chuhan , Wang Ying , Sun Yun , Fu Chaoqi
Published: November 2024

This paper investigates the guaranteed performance resilient security consensus control of nonlinear networked control systems (NCSs) subject to asynchronous denial-of-service (DoS) cyber attacks, where the communication channel disruptions and recoveries occur randomly. The main works of this paper are outlined as follows: (1) a rigorous quantitative modeling of asynchronous DoS cyber attacks is formulated, leveraging connectivity analysis and the graph theory; (2) an innovative guaranteed performance function is introduced, which imposes constraints on the system’s convergence behavior while alleviating restrictions on initial tracking errors; (3) to address the challenge of estimating unmeasurable system states arising from the output-feedback scheme, a novel fuzzy state observer is devised; and (4) based on the aforementioned designs, a switching guaranteed performance resilient security consensus controller is proposed. This controller is tailored to the network connectivity characteristics of NCSs, ensuring resilient convergence of the system despite asynchronous DoS attacks. Notably, consensus tracking errors are maintained within predefined performance bounds. The experiment results of numerical simulation and hardware-in-the-loop simulation of multiple unmanned aerial vehicles (multi-UAVs) networks illustrate the effectiveness and practicality of proposed control scheme.
A Novel Fault Diagnosis Method Using FCEEMD-Based Multi-Complexity Low-Dimensional Features and Directed Acyclic Graph LSTSVM
Authors: Lu Rongrong , Xu Miao , Zhou Chengjiang , Zhang Zhaodong , Tan Kairong , Sun Yuhuan , Wang Yuran , Mao Min
Published: November 2024

Rolling bearings, as critical components of rotating machinery, significantly influence equipment reliability and operational efficiency. Accurate fault diagnosis is therefore crucial for maintaining industrial production safety and continuity. This paper presents a new fault diagnosis method based on FCEEMD multi-complexity low-dimensional features and directed acyclic graph LSTSVM. The Fast Complementary Ensemble Empirical Mode Decomposition (FCEEMD) method is applied to decompose vibration signals, effectively reducing background noise. Nonlinear complexity features are then extracted, including sample entropy (SE), permutation entropy (PE), dispersion entropy (DE), Gini coefficient, the square envelope Gini coefficient (SEGI), and the square envelope spectral Gini coefficient (SESGI), enhancing the capture of the signal complexity. In addition, 16 time-domain and 13 frequency-domain features are used to characterize the signal, forming a high-dimensional feature matrix. Robust unsupervised feature selection with local preservation (RULSP) is employed to identify low-dimensional sensitive features. Finally, a multi-classifier based on DAG LSTSVM is constructed using the directed acyclic graph (DAG) strategy, improving fault diagnosis precision. Experiments on both laboratory bearing faults and industrial check valve faults demonstrate nearly 100% diagnostic accuracy, highlighting the method’s effectiveness and potential.