bluuebunny/crossref_metadata_2025 huggingface dataset:
Neural Network-Based Parameter Estimation in Dynamical Systems
Authors: Kastoris Dimitris , Giotopoulos Kostas , Papadopoulos Dimitris
Published: November 2024

Mathematical models are designed to assist decision-making processes across various scientific fields. These models typically contain numerous parameters, the values’ estimation of which often comes under analysis when evaluating the strength of these models as management tools. Advanced artificial intelligence software, has proven to be highly effective in estimating these parameters. In this research work, we use the Lotka-Volterra model to describe the dynamics of a telecommunication sector in Greece and then we propose a methodology that employs a feed-forward neural network (NN). The NN is used to estimate the parameter’s values of the Lotka-Volterra system, which are later applied to solve the system using a fourth algebraic order Runge-Kutta method. The application of the proposed architecture to the specific case study, reveals that the model fits well to the experiential data. Furthermore, the results of our method surpassed the other three methods used for comparison, demonstrating its higher accuracy and effectiveness. The implementation of the proposed feed-forward neural network as well as the fourth algebraic order Runge-Kutta method was accomplished using MATLAB.
Development of a Machine Learning Natural Ventilation Rate Model by Studying the Wind Field Inside and Around Multiple Rows Chinese Solar Greenhouses
Authors: Liu Ran , Shi Yunyan , Bournet Pierre-Emmanuel , Liu Kaige
Published: November 2024

This paper experimented with a methodology of machine learning modelling using virtual samples generated by a fast CFD (Computational Fluid Duy) simulations, in order to predict the greenhouse natural ventilation. However, the output natural ventilation rates using fast two-dimensional (2D) CFD models are not always consistent with the three-dimensional (3D) one for all the scenarios. The first contribution of this paper is a proposed comparative modelling methodology between two-dimensional and three-dimensional CFD (Computational Fluid Dynamics) studies, regarding its validity, especially when buildings are in rows. The results show that the error on the ventilation rate prediction could exceed 50%, if 2D models are not properly used. Subsequently, in those scenarios where the 2D and the 3D model had equal accuracy, nearly one thousand samples were generated using fast 2D CFD simulations to train natural ventilation rate regression tree-model. This model is efficient to deal with the combined effect of wind pressure and thermal gradients under various vent configurations, with only four necessary inputs. In addition, by analyzing the wind speed distribution contour of the outdoor wind field around the greenhouse rows, the optimal wind speed measuring locations were determined to eliminate interference for predicting the natural ventilation rate.
Secure Aggregation-Based Big Data Analysis and Power Prediction Model for Photovoltaic Systems: A Multi-Layered Approach
Authors: Huang Qiwei , Wahaballa Abubaker
Published: November 2024

This study introduces a fresh approach to boost the security and accuracy of predicting photovoltaic (PV) power generation using secure aggregation techniques. The author will focus on several key stages in the PV data lifecycle, such as collecting, transmitting, storing, and analyzing data. To protect against potential attacks and prevent information leaks during these four crucial processes, we use Paillier and BVG homomorphic encryption methods. By combining TLS protocol with edge computing during data transmission, we not only improve data security but also reduce latency while tackling threats from attackers. There are two different types of attackers: honest but curious adversaries and active adversaries. Additionally, we make strategies for key management, access control, and auditing to ensure that access to information is monitored to help enhance overall system security. In the final phase of analyzing and predicting PV power output, we utilize advanced models like LSTM networks and CEEMDAN to achieve precise time-series predictions. The results indicate that these methods can effectively manage large PV datasets while keeping high prediction accuracy alongside strong security measures. The research establishes a foundation for improving homomorphic encryption, enhancing key management, and creating a big data security framework specific to photovoltaic energy production.
Serotonin Inhibits Claustrum Projection Neurons
Authors: Augustine George , Wong Kelly Li Lin , Graf Martin
Published: November 2024

The claustrum, a small but densely interconnected brain structure, is innervated by axons containing neuromodulators such as serotonin (5-HT), a neuromodulator that has been implicated in control of sleep and in the actions of psychedelic drugs. However, little is known about how 5-HT influences the claustrum. We have combined whole-cell patch clamp measurements of ionic currents, flash photolysis and receptor pharmacology to characterize the 5-HT responses of individual claustral projection neurons (PNs) in mouse brain slices. Serotonin application elicited a long-lasting outward current in claustral PNs. This current was due to an increase in membrane permeability to K+ ions and was mediated mainly by the type 1A 5-HT receptor (5-HTR-1A). The 5-HT-induced K+ current hyperpolarized, and thereby inhibited, PNs by reducing action potential firing. Focal uncaging of 5-HT revealed that inhibitory 5-HTR-1As were located at both the soma and dendrites of PNs. We conclude that 5-HT creates a net inhibition in the claustrum, an action that should decrease claustrum sensitivity to excitatory input from other brain areas and thereby contribute to 5-HT action in the brain.
Sustainable Versus Conventional Bioactive Extractions from Tunisian Carob Pulp: Evaluation of Polyphenol Profile by HPLC-HRMS, Antioxidant Capacity and Chemometric Analysis
Authors: Saadi Chaima , Sakouhi Faouzi , Chami Mohamad Ali El , Cáceres-Jiménez Salud , Moreno-Ortega Alicia , Boukhchina Sadok , Moreno Rojas Jose Manuel , Rodríguez-Solana Raquel
Published: November 2024

Carob pulp is a Mediterranean by-product highlighted as an important source of bioactive compounds potentially used in different industrial applications. This paper deals with the comparison of methods elaborated with combinations of conventional (maceration-M, organic solvents and water) and non-conventional green (ultrasound-assisted extraction -UAE, and natural deep eutectic solvents -NADES) extraction approaches and using chemometric tools for screening the polyphenol profile by HPLC-HRMS and bioactive potential measured by Folin-Ciocalteu, DPPH and ABTS assays of carob pulp from two Tunisian ubications (North and South). Regarding the factors studied (extraction technique and solvent, and geographical location), the solvent marked the higher variability found for the different families of compounds studied. The highest yield of total phenolics was achieved by the conventional method ethanol 75%-M (5023.92 µg/g) and the green approaches water-UAE (5008.32 µg/g), followed by the NADES lactic acid: sodium acetate (3:1) (3117.23 µg/g). The latter standing out for its contents in flavonols and hydrolizable tannins and antioxidant potential. The two Tunisian locations studied showed differentiation in the phenolic content depending on the extraction method. However, in general, higher contents were observed in extracts from the southern region. The chemometric evaluation confirm the suitability of the proposed green methods as excellent powerful tools for bioactive extraction from carob pulp, with similar, improved or highly selective phenolic recoveries compared to the conventional methods assessed.
Exploring Foundational Experiments in GlycoRNA
Authors: Parsons James V.
Published: November 2024

In traditional models of molecular and cellular biology, RNA has been limited to primarily intracellular function in mammalian cells, and has only been subject to chemically simple post-transcriptional modifications. Recent advances have identified an isoform of RNA that challenges this model in two major ways: by expanding its domain to the mammalian cell surface, and identifying it as a target for glycosylation. This isoform, termed glycoRNA, has elevated the nucleic acid from an enzymatic biopolymer to a potential cell signaling molecule with implications for human disease phenotypes. In this review, we summarize the key features of glycoRNA and explore early studies as to its cellular role. We also collate information on glycoRNA-expressing cell lines and high-confidence glycosylated transcripts, providing several resources to assist future studies. Finally, we highlight the important challenges and next steps to characterize this novel glycoconjugate.
Exploring Immunotherapeutic Strategies For Bacterial And Viral Diseases: Recent Advances, Challenges And Future Perspectives
Authors: Adedokun Ayodele , Adigun Olaniyi , Muhammad Adamu , Idris Ibrahim , Ntasin Paul , Olowu Babatunde , Ikele-Awaogu Chinyere , Fadele Precious , Dibia Ernesto
Published: November 2024

Antimicrobial resistance (AMR) is a growing global threat, affecting the effectiveness of antimicrobials and posing significant challenges in the treatment of bacterial and viral infections. The emergence of the coronavirus in 2019 and the ongoing menace of infectious diseases such as HIV/AIDS, tuberculosis, and hepatitis remind us of the impact infections have on economic stability and global health, and therefore, the need for a more holistic and long-term solution as opposed to antibiotics - measures that were previously relied on. This review explores recent advances in immunotherapeutic strategies, particularly cytokine-based therapies, adoptive cell therapy, monoclonal antibodies, and immune checkpoint inhibitors, in the control of AMR. It focuses on pathogens with high clinical relevance, including Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, and Mycobacterium tuberculosis, and viral threats such as HIV and SARS-CoV-2. New inventive approaches such as CAR T cell therapy and MAIT cells were discussed in the context of bacterial and viral infections, highlighting promising results from clinical trials and addressing the challenges of toxicity, immune evasion, and therapy resistance inherent in these diseases. Future priorities include optimizing combination therapies and exploring new immunomodulatory targets to improve these interventions' effectiveness in treating AMR and other infectious diseases.
Natremia Significantly Influences the Clinical Outcomes in Patients with Severe Traumatic Brain Injury
Authors: Sharma Bharti , Jiang Winston , Hasan Munirah M. , Agriantonis George , Bhatia Navin D. , Shafaee Zahra , Twelker Kate , Whittington Jennifer
Published: November 2024

Fluctuations in sodium levels (SL) can indicate disease severity and independently affect prognosis in critically ill patients. Our primary objective is to study the impact of sodium on clinical outcomes in patients with traumatic brain injury (TBI). This is a single-center, retrospective study of patients with severe TBI from January 1, 2020, to December 31, 2023, inclusive. We found multiple significant relationships between SL and various prognostic factors and outcomes. Statistically significant negative correlations were identified between age and admission SL as well as ICU admission SL (p = 8.79 x10-8 p = 0.000205). There was a positive correlation with intensive care unit (ICU) discharge levels (p = 0.0301) and no significance for hospital discharge or death. Differences in SL upon admission were statistically significant across four age ranges (pediatric, young adult, older adults, and elderly) (p = 2.394e-06). ICU admission (p = 0.00633), hospital discharge (p = 0.0266), and death (p = 0.0413) also showed significance. We compared sodium ranges (extreme hyponatremia, hyponatremia, normonatremia, hypernatremia, and extreme hypernatremia) and found statistically significant differences in SL at admission, ICU admission, and ICU discharge when compared to admission injury severity scores and Glasgow Coma Scale (GCS) scores. A linear regression analysis revealed a statistically significant positive correlation between ICU admission SL and ISS. We discovered statistically significant differences when comparing ICU admission levels to hospital length of stay (LOS), ventilator days, and mortality. Additionally, we noted positive correlations between ICU admission SL and several factors, including hospital LOS, ICU LOS, ventilator days, and mortality. Finally, the variation in SL from hospital admission to ICU admission was positively correlated with hospital LOS (p = 0.0148), ventilator days (p = 0.0261), and mortality (p=6.9x10-8). Our findings show that hypernatremia is linked to poorer outcomes in patients with TBI, providing useful clinical insight into the management of critically ill patients with TBI. Further studies examining other metabolites would be beneficial for gaining a deeper understanding of the complex pathophysiology of TBI.
Evaluation of Chemical Composition and Anti‐Staphylococcal Activity of Essential Oils from Leaves of Two Indigenous Plant Species Litsea leytensis and Piper philippinum from Leyte, Philippines
Authors: Albarico Genesis , Urbanova Klara , Houdkova Marketa , Bande Marlito , Tulin Edgardo , Kokoskova Tersia , Kokoska Ladislav
Published: November 2024

Indigenous plants from Southeast Asia, specifically those from the Philippines, remain underex-plored in terms of their essential oils (EOs) potential. The chemical composition of hydrodistilled leaf EOs from two indigenous EOs-bearing species, namely Litsea leytensis (Lauraceae) and Piper philippinum (Piperaceae), was described, using dual-column/dual-detector GC-MS analysis. When analysed using two columns differing in their polarity (HP-5MS/DB-WAX), L. leytensis EO had high amounts of caryophyllene oxide (15.70/16.76%) as the primary component, followed by β-caryophyllene (11.04/11.12%) and α-copaene (8.85/8.87%). Ishwarane (26.98/24.9%), nerolidol (10.14/10.42%) and 3-ishwarone (6.84/2.46%) were the most abundant constituents of P. philippinum EO. Additionally, the in vitro growth-inhibitory activity of the EOs in the liquid and vapor phases against Staphylococcus aureus was evaluated using the broth microdilution volatilization assay; however, both EOs had no anti-staphylococcal effect. This is the first study evaluating antibacterial activity and chemical composition of EOs from L. leytensis and P. philippinum. However, the iden-tification of potentially bioactive compounds in both EOs suggests further investigation of these species.
Advances in Vaccine Adjuvants for Teleost Fish: Implications for Aquatic Welfare and the Potential of Nanoparticle-based Formulations
Authors: Tammas Iosif , Bitchava Konstantina , Gelasakis and Athanasios
Published: November 2024

Vaccine adjuvants are crucial for reinforcing the immunogenicity of vaccines. Therefore, they are widely used in the aquaculture sector as vaccine components facilitating the efficient prevention of infectious diseases and promoting sustainable teleost fish growth. Despite their benefits, there has been a growing concern about the potential adverse effects of vaccine adjuvants in teleost fish, connoting a valid impact on their overall health and welfare. Among adjuvants used in aquaculture vaccinology, nanoparticle-based formulations have given rise to a promising new alternative to traditional options, such as oil-based emulsions and aluminum compounds, offering the benefit of minimizing relevant side-effects. The aim of this paper was to review the current status of the adjuvants used in aquaculture, provide a description and an evaluation of their mode of action and side-effects, and explore the potential use of nanoparticle formulations as adjuvants to improve the efficacy of aquaculture vaccines. By demonstrating and assessing the equilibrium between teleost fish welfare and immunological efficacy, this review presents a collective perspective that will assist in establishing a framework for the utilization of effective, species-specific practices around adjuvant use in aquaculture, while also addressing the challenges of welfare-friendly immunization.
The Role of Dendritic Cells in Adaptive Immune Response Induced by Ova/Pdda Nanoparticles
Authors: Pereira Daniele R. , Pérez-Betancourt Yunys , Távora Bianca C. L. F. , Magalhaes Geraldo S. , Carmona-Ribeiro Ana Maria , Faquim-Mauro Eliana L.
Published: November 2024

Cationic polymers were previously shown to assemble with negatively charged proteins yielding nanoparticles (NPs). Poly-diallyl-dimethyl-ammonium chloride (PDDA) is a cationic polymer able to combine with ovalbumin (OVA) yielding a stable colloidal dispersion of OVA/PDDA NPs eliciting significant anti-OVA immune response. Dendritic Cells (DC), as sentinels of foreign antigens, exert a crucial role in the induction of antigen-specific T cell activation and consequent adaptive immune response. Objective: The present study aimed at evaluating the involvement of DCs in the adaptive immune response induced by OVA/PDDA. Methods/Results: Confirming the potent induction of adaptive immune response against OVA/PDDA, the data showed increased CD19+CD138+ plasma cells and CD19+CD38+CD27+ memory cells in spleens of mice immunized with OVA/PDDA-NPs 28 days before. OVA/PDDA-NPs also induced the migration and maturation of DCs to draining lymph nodes on days 3 and 4 of mice immunization. The in vitro results with bone-marrow differentiated DCs (iBM-DCs) showed an increase of the binding and uptake of OVA/PDDA NPs by these cells compared with soluble OVA. In addition, OVA/PDDA NPs were able to induce DC maturation and upregulation of costimulatory and MHC-II molecules, TNF- and IL-12 production. iBM-DCs incubated with OVA/PDDA NPs promoted high OVA-specific T cell proliferative response. Conclusion: Altogether, the data demonstrated the central role of DCs in the induction of antigen-specific immune response by OVA-PDDA-NPs, thus proving these NPs as potent adjuvants for subunit vaccine design.
Endocrine Hormones and Their Impact on Pubertal Gynecomastia
Authors: Shi Ziang , Xin Minqiang
Published: November 2024

Pubertal gynecomastia (PG) refers to the abnormal development and hyperplasia of unilateral or bilateral breast tissue in adolescent males, a common condition with a prevalence of up to 50% among appropriately aged adolescents, and an increasing incidence trend over the years. The etiology of PG is multifactorial, including physiological, pharmacological, and pathological causes. Endocrine hormones play a crucial role in the pathogenesis of PG across different etiologies. This review provides a detailed discussion on the effects of various endocrine hormones, including FSH, LH, T, E2, PRL, GH, and thyroid hormones, on pubertal gynecomastia in adolescent males, aiming to offer valuable insights for clinical diagnosis and treatment.
Multimorbidity in Patients with Chronic Liver Disease: A Population-Based Study in the EpiChron Cohort, Spain
Authors: Moreno-Juste Aida , Poblador-Plou Beatriz , Laguna-Berna Clara , Cruces-Mateo Belén , Lenotti Elisa , Santos-Mejías Alejandro , Gimeno-Feliu Luis Andrés , Gimeno-Miguel Antonio
Published: November 2024

Background/Objectives: Chronic liver disease (CLD) is highly relevant in clinical practice due to its increasing incidence and associated mortality. We aimed to exhaustively characterize the multimorbidity in patients with CLD. Methods: Retrospective observational study of patients aged 18 years and older with a diagnosis of CLD in 2015 in the EpiChron Cohort (Spain). We analysed the prevalence of comorbidities according to sex and age, conducted a logistic regression analysis with CLD as the independent variable and each of the comorbidities as dependent variables to obtain odds ratios (OR) adjusted for age and sex, and performed an exploratory factor analysis to identify the presence of multimorbidity patterns. Results: 6836 adults had a diagnosis of CLD (mean age 61.6 years; 62.5% women), with an average of 13 co-existing chronic conditions. Arterial hypertension, lipid metabolism disorders, diabetes, obesity, and musculoskeletal diseases were the most frequent diseases. From the list of 110 chronic conditions analysed, 75 were systematically associated with CLD, including (OR, 95% confidence interval) chronic pancreatitis (41.2, 33.5-50.6), and inherited metabolic disorders (14.9, 11.8-18.8). Three multimorbidity patterns were identified in both men and women, and called cardiovascular, metabolic-geriatric, and mental-substance use, with some differences by sex. Conclusions: Multimorbidity is the norm in patients with CLD. Our results reveal that a comprehensive and integral approach based on person-centred care, which should take into account their entire spectrum of multimorbidity, is necessary during the care of this type of patients in clinical practice.
Prime Generation via Polynomials: Analysis and Applications
Authors: Singh Samrat
Published: November 2024

This research offers an extensive analysis of a family of prime-generating polynomials \( P_k(n) = n^2 - (2k - 79)n + [41 + (k - 39)(k - 40)] \), designed to generate prime numbers for integer values of \( n \) up to \( k \) where \( k \in \{1, 2, \ldots, 80\} \). We elaborate on mathematical clarity, consistency in proofs, error bounds, prime repetition analysis, and cryptographic implications. This study provides in-depth inductive proofs, graphical error bounds analysis, prime repetition statistics, and cryptographic security assessments, offering novel insights and future directions for research in number theory and secure prime generation.
Evaluation of Fish Biosolids as a Growth Media Component for Organic Tomato Transplant Production
Authors: Schembri Cicely , Kaczmar Nicholas , Osborn John , Timmons Michael Ben , Mattson and Neil S.
Published: November 2024

Interest among consumers is increasing for the availability of organically produced fruits and vegetables. Seafood demand is increasingly being met by fish raised using aquaculture methods that provide fish excretory products that can meet organic standards for nutrient sources for organic vegetables. We conducted an experiment in a glass greenhouse to evaluate fish biosolids as a growth media component for organic tomato transplant production. We compared the fishbiosolids treatment to several different organic fertilizers along with a commonly used inorganic slow-release fertilizer (Osmocote). All treatments used a target N concentration of 400 mg/L incorporated into the substrate and we also included fish biosolids treatments of 200 and 800 mg/L. Plant performance was montiored for 5 weeks starting with commercially available 2-week old seedlings. Results showed that the 800 mg/L fish biosolids treatment compared very favorably with the inorganic Osmocote treatment at the conclusion of the trial. The 800 mg/L fish biosolids treatment exceeded the Osmocote treatment for chlorophyll content and for leaf number for the first 4 weeks of the 5 week trial. Grower management protocols could further improve seedling performance by providing additional top dressings of fish biolsolids or fish effluent waters as the plants age.
Are Δ9-Tetrahydrocannabinol and Its Major Metabolites Substrates or Inhibitors of Placental or Human Hepatic Drug Solute-Carrier Transporters?
Authors: Chen Xin , Gáborik Zsuzsanna , Mao Qingcheng , Unadkat Jashvant D
Published: November 2024

Δ9-Tetrahydrocannabinol (THC) is the primary psychoactive component of cannabis which is in-creasingly consumed by pregnant people. In humans, THC is sequentially metabolized in the liver to its circulating metabolites 11-hydroxy-THC (11-OH-THC, psychoactive) and 11-nor-9-carboxy-THC (THC-COOH, non-psychoactive). Human and macaque data show that fetal exposure to THC is considerably lower than its corresponding maternal exposure. Through perfused human placenta studies, we have shown that this is due to active efflux of THC (fe-tal-to-maternal) by a placental transporter(s) other than P-glycoprotein or breast cancer resistance protein. The identity of this placental transporter(s) as well as whether THC or its metabolites are substrates or inhibitors of hepatic solute carrier transporters is unknown. Therefore, we investigated whether 5 μM THC, 0.3 μM 11-OH-THC, and 2.5 μM THC-COOH are substrates and/or inhibitors of placental or hepatic solute carrier transporters at their pharmacological-relevant concentrations. Using HEK cells overexpressing human OATP1B1, OATP1B3, OATP2B1, OCT1, OCT3, OAT2, OAT4, or NTCP, and prototypic substrates/inhibitors of these transporters, we found that THC and THC-COOH were substrates but not inhibitors of OCT1. THC-COOH was a weak substrate of OCT3 and a weak inhibitor of OAT4. THC, 11-OH-THC, and THC-COOH were found not to be substrates/inhibitors of the remaining transporters investigated.
Association of BMI with Hepatic Steatosis, Fibrosis, and Inflammation: Insights from a Deceased Donor Liver Cohort Study Based on the UNOS Database
Authors: Bian Congwen , Huang Hanfei , Zeng Zhong
Published: November 2024

Background: While the prevalence of obesity and its negative effects on graft steatosis in liver transplantation are well recognized, the impact of obesity in the absence of hepatic steatosis, fibrosis, and inflammation in deceased donor livers remains unclear. This knowledge gap may affect the decision to adopt a transplant strategy and influence the following outcomes. Methods: A donor population-based cohort study was performed on 35,529 donors who received liver biopsy from 1987 to 2024. Donor BMI was categorized and assessed for its association with liver conditions, including macrovesicular steatosis, microvesicular steatosis, liver fibrosis, and portal infiltrates. Multivariable logistic regression and restricted cubic spline (RCS) regression models were employed to explore both linear and nonlinear relationships between BMI and the specified liver conditions. Results: In a cohort of 35,529 donors, donor livers from higher BMI groups exhibited higher percentages of macro-steatosis, micro-steatosis,advanced fibrosis and portal infiltrate.Logistic regression indicated obesity as an independent predictor of liver histology assessment: for higher risk with moderate-servere macro-steatosis (OR 2.29, 95% CI 2.11–2.49, p < 0.001),moderate-servere micro-steatosis (OR 1.71, 95% CI 1.57–1.87, p < 0.001), portal infiltrate (OR 1.37, 95% CI 1.3–1.45, p < 0.001) and advanced fibrosis (OR 1.04, 95% CI 0.94–1.14, p < 0.001). Restricted cubic spline regression depicted J-shaped with moderate-servere macro-steatosis and portal infiltrate,a U-shaped advanced fibrosis, and a upside down U-shaped with moderate-servere micro-steatosis,P for for nonlinearity <0.0001),respectively. Subgroup analyses identified interactions with factors such as gender, hypertension, and hepatitis C, highlighting BMI’s complex influence on liver histology and reinforcing its role in liver donor evaluation. Conclusion: This donor population-based cohort study found a different association pattern between donor BMI and liver biopsy outcomes,integrating BMI into donor liver assessments could enhance decision-making during transplantation, potentially reducing organ discard rates and improving transplant success by identifying high-risk organs earlier.
The Development of a Model Considering Hope, Uncertainty Emotion Regulation in People with Chronic Low Back Pain: A Worked Example of a Social Constructivist Meta-Ethnography Study
Authors: McMillan Justine , Soundy Andrew
Published: November 2024

Abstract: Objective: Chronic low back pain (CLBP) is a significant global concern. Its prevalence is increasing, and current management strategies demonstrate at best, moderate effectiveness. The purpose of this study was to explore the concepts of hope, uncertainty and how they both influence emotion regulation because these concepts are extremely prevalent for patients and clinicians during CLBP consultations. Methods: A soccial constructivist meta-ethnographic is a highly interpretative type of qualitative review that generates new theory, enabling a valuable insight to this unique area. A framework was followed; its iterative analytical process involves multiple search strategies, exploring how studies relate, generating ideas and developing a substantive theory. Results: This review represents the first worked example of a theory generating review process. One model was created (see figure 5) that focuses on how the individual with CLBP regulate their emotions and considers factors that feed into the process and result from the process. The outcome of the model produced either adaptative or maladaptive emotional regulation strategies (ERS). Conclusions: Hope and uncertainty are key concepts that are interlinked and play a vital role on health outcomes of people with CLBP. Research is required to explore how the model can be operationalised in clinical practice.
Sending Astronauts Created by Synthetic Biology and AI with Plant Characteristics
to Exoplanets：A Consideration for Humanity's Future Beyond the Solar System
Authors: Sun Tianxi
Published: November 2024

Based on the fact that the solar system will eventually be destroyed and that humans cannot travel to the nearest habitable exoplanet within a lifetime, this article suggests sending synthetic biology- and AI- created astronauts with some plant characteristics to the closest habitable exoplanet. The paper assesses the potential impact of this future technology on various aspects of human society, including scientific, ethical, and cultural dimensions. As long as these astronauts with some plant characteristics possess human consciousness, it is irrelevant whether they are hybrids of carbon- and silicon- based life forms. They will carry on the human heritage on exoplanets. Humanity has two survival options. The first option is the Martian migration program led by Elon Reeve Musk, which is both visible and realistic. It could provide an immediate option for human continuation and expansion, although it may not help us escape the future burning of the Sun during its red giant phase. The second option involves directly sending astronauts with some plant characteristics beyond the solar system. Escaping to Mars still does not free humans from the risk of extinction. We must strive with all our might; otherwise, humanity will be forever trapped within the solar system, awaiting the inevitable helium flash to come...
Facile Preparation of Composite Coatings with Incorporated 13X Zeolite and CeO2
Authors: Mojsilović Kristina , Tadić Nenad , Stojanović Srna , Damjanović-Vasilić Ljiljana , Vasilić Rastko
Published: November 2024

One-step methods for the formation of efficient thin film catalysts for wastewater treatment under sunlight spectrum is a topic of interest of many research groups. This article reports on the facile preparation of photocatalytic coatings by plasma electrolytic oxidation processing from 0.01 M sodium tungstate electrolyte solution containing both 13 X zeolite and CeO2. Obtained coatings are characterized with respect to their surface morphology, chemical and phase composition, and for their possible application as photocatalysts in photodegradation of organic pollutants. All prepared coatings contain elements originating from both substrate and electrolyte solution. Addition of 1 g/L of 13X zeolite and CeO2 in various concentrations to electrolyte solution results in increased photodecomposition of model organic pollutant. The highest photodegradation under simulated sunlight is observed for coatings formed in 0.01 M sodium tungstate with addition of 1 g/L of 13 X zeolite and 1 g/L of CeO2, reaching 50 % after 6 h of irradiation.
Adverse Childhood Experience and Vulnerability to Mood and Anxiety Disorders During the COVID-19 Pandemic
Authors: Patten Scott B.
Published: November 2024

The COVID-19 pandemic had a global impact on mental health. Identification of individuals at higher or lower risk of mental health issues may assist with targeting prevention, support and treatment efforts during future pandemics. Using a Canadian national mental health survey that collected data (March 2022 – December 2022) during the pandemic period, this study examined vulnerability of participants reporting exposure to child abuse or neglect by examining the risk of mood, anxiety and substance use disorders over a one year period. Psychiatric disorders were identified using the Composite International Diagnostic Interview (CIDI). Because childhood adversities are well-known risk factors for mental disorders, the analysis focused on interactions between childhood adversities and pandemic stressors by estimating the relative excess risk due to interaction (RERI). RERIs provide evidence of synergy based on the occurrence of greater than additive interactions. Evidence of synergy was consistently found between physical and sexual abuse and mood and anxiety disorders. There was no such evidence for substance use disorders. Childhood adversities increase vulnerability to stressors and may be useful for identification of individuals with greater mental health needs during public health emergencies.
How Does Professional Habitus Impact Nursing Autonomy? A Hermeneutic Qualitative Study Using Bourdieu’s Framework
Authors: Avilés González Cesar Iván , Morales Viana Liliana Cristina , Piedrahita Sandoval1 Laura Elvira , Sotelo-Daza ,  Jorge
Published: November 2024

Abstract:.. introduction In the professional practice of nursing, differences have been described between the habitus shared in the academic training process and the professional practice developed in the field of health systems; in this scenario, nurses tend to be affected by how their professional habitus has been established, which, in some way, alters the cultural capital established in their academic training process. The research objective was to identify aspects that facilitate and limit the development of the theoretical component in nursing practice.Method: The research was based on a qualitative hermeneutic study addressed from a critical approach that linked Bourdieu's field theory. The study included 17 students, 11 nurses active in health services, and six university professors. Data were collected from a sociodemographic questionnaire, episodic interviews, and focus groups. The information collected was analyzed using the hermeneutic understanding process from the grounded theory.Results: The research revealed a central thematic core called clarification of the role of the nurse (professional habitus) and three secondary thematic cores related to the need to strengthen the nursing essence (identity habitus), the adjustment of training processes (optimization habitus) and, finally, the strengthening of the nurse's credibility (validation habitus).Conclusion: The professional habitus of nursing professionals is shaped by different elements of the social field of the health system. This field is repressed by hierarchical structures that succeed in disconnecting theory from praxis. Aspects such as subordination to the hegemonic biological discourse and the medical profession, the limited appreciation of humanized care, restrictions on the recognition of the nursing process by health institutions, and limited solidarity and leadership end up conditioning the accumulation of symbolic capital and social capital of nursing, which leads to the loss of autonomy and the advancement of professional development.
Nuclear Accumulation of Bm65 aggreGATE IS BLOCKED by Mutations in the Nuclear Export Sequence of Bm65
Authors: Li Guohui , Liu Wenchao , Liu Yunyun , Xu Junting , Chen Huiqing , Zhu Feifei , Hu Zhaoyang , Guo Zhongjian , Chen Keping , Tang Qi
Published: November 2024

A nuclear export signal (NES) is a cluster of hydrophobic amino acids that can maintain the dynamic shuttling of target proteins between the nucleus and cytoplasm. Bioinformatics analysis showed that the hydrophobic region of 92PLLLHKFLLA in Bm65 is very likely to be an NES and may be involved in the production of infectious virions. In this study, we generated several mutations in 92PLLLHKFLLA of Bm65, which were further used to generate recombinant viruses to study their roles in viral propagation. Subcellular analysis revealed that the 92PLLLHKFLLA sequence is an NES involved in the dynamic transport of Bm65. Mutations in the hydrophobic region could block the formation and accumulation of Bm65 aggregates, resulting in a uniform distribution of Bm65 in BmN cells. The ribosomal protein L13 (RPL13) of silkworm was previously reported to interact with Bm65. Here, intracellular co-localization analysis showed that the interaction between Bm65 and RPL13 was regulated by the 92PLLLHKFLLA of Bm65. In summary, the interaction between Bm65 and RPL13 is essential for the production and accumulation of Bm65 aggregates and may play an important role in the regulation of viral propagation.
Development and Comparative Analysis of Machine Learning Models for Hypoxemia Severity Triage in CBRNE Emergency Scenarios Using Physiological and Demographic Data from Medical-Grade Devices
Authors: Nanini Santino , Abid Mariem , Mamouni Yassir , Wiedemann Arnaud , Jouvet Philippe , Bourassa Stephane
Published: November 2024

This paper presents the development of machine learning (ML) models to predict hypoxemia severity during emergency triage, especially in Chemical, Biological, Radiological, Nuclear, and Explosive (CBRNE) events, using physiological data from medical-grade sensors. Gradient Boosting Models (XGBoost, LightGBM, CatBoost) and sequential models (LSTM, GRU) were trained on physiological and demographic data from the MIMIC-III and IV datasets. A robust preprocessing pipeline addressed missing data, class imbalances, and incorporated synthetic data flagged with masks.
Gradient Boosting Models (GBMs) outperformed sequential models in terms of training speed, interpretability, and reliability, making them well-suited for real-time decision-making. While their performance was comparable to that of sequential models, the GBMs used score features from six physiological variables derived from the enhanced National Early Warning Score (NEWS) 2, which we termed NEWS2+. This approach significantly improved prediction accuracy.
While sequential models handled temporal data well, their performance gains didn’t justify the higher computational cost. A 5-minute prediction window was chosen for timely intervention, with minute-level interpolations standardizing the data.
Feature importance analysis highlighted the significant role of mask and score features in enhancing both transparency and performance. Temporal dependencies proved to be less critical, as Gradient Boosting Models were able to capture key patterns effectively without relying on them.
This study highlights ML's potential to improve triage and reduce alarm fatigue. Future work will integrate data from multiple hospitals to enhance model generalizability across clinical settings.
Essential Tremor: A Focused Literature Review on its Pathophysiology, Neurophysiology, Etiology, and Management
Authors: Bradley Carrie , Garrison Nyah , Washington Amber , Wood Brandon
Published: November 2024

Essential Tremor (ET) is among the most common neurological movement disorders, with incidence rates increasing with age. The disorder is characterized by a bilateral action tremor of the upper limbs, enduring for a minimum of three years in duration, and shows early signs of onset with progression over time. Recent terminology has categorized a subcategory of ET, known as Essential-Tremor Plus (ET-Plus), which consists of a combination of symptoms that include tremors at rest and additional neurological signs. This includes memory impairment, gait disturbances, or various other neurological symptoms that do not have full clinical significance for diagnosis and suggest a more complex underlying neurological condition. Abnormalities located primarily in the cerebellum, including the loss and damage to Purkinje Cells (PC), were core pathological features of cerebellar damage in postmortem ET. Given the complexity and uncertainty of the pathophysiological aspects of tremor generation, treatment options are still limited, and current therapeutic measures lack the capacity to fully alleviate symptoms. In consideration, there are current pharmaceutical, stimulation, and genetic studies being conducted to characterize the etiology and pathophysiology of ET and aid in the reduction of progression and symptoms. In this review, we will discuss various aspects of ET including neurophysiology, pathophysiology, genetic factors and etiology, treatment options and future directions of advancements for ET management.
Electrolessly Deposited Cobalt-Phosphorous Coatings for Efficient Hydrogen and Oxygen Evolution Reactions
Authors: Amber Huma , Balčiūnaitė Aldona , Sukackienė Zita , Tamašauskaitė-Tamašiūnaitė Loreta , Norkus Eugenijus
Published: November 2024

Hydrogen production by water splitting is one of the low-cost green hydrogen production technologies. The challenge is to develop inexpensive and highly active catalysts. Herein, we present the preparation of electrocatalysts based on cobalt-phosphorus (Co-P) coatings with different P contents for hydrogen and oxygen evolution reactions (HER and OER). The Co-P coatings were deposited on the copper (Cu) surface using the inexpensive and simple method of electroless metal deposition. The morphology, structure, and composition of the Co-P coatings deposited on the Cu surface were studied by scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX), while their activity for HER and OER in 1 M KOH was investigated by linear sweep voltammetry (LSVs) and chrono-techniques. It was found that the catalyst activity for both HER and OER depends on the P content of the catalyst and varies to the highest efficiency for each reaction. The Co-P coating with the 11 wt% of P exhibited the lowest overpotential value of –115.4 mV for the HER to obtain a current density of 10 mA cm-2 compared to the Co-P coatings with 8 wt% (–121.5 mV) and 5 wt% (–182.9 mV) of P. In contrast, the lowest OER overpotential (394 mV) was observed for the Co-P coating with the 8 wt% of P to obtain a current density of 10 mA cm-2 as compared to the Co-P coatings with 5 wt% (416 mV) and 11 wt% (432 mV) of P. These results suggest that the obtained catalysts are suitable for HER and OER in alkaline media.
Federated Learning for Indoor Air Quality Monitoring and Activity Recognition Approach
Authors: Aymene Berkani Mohamed Rafik , Chouchane Ammar , Belabbaci El Ouanas
Published: November 2024

This paper presents a novel privacy-preserving approach, Fed-CNN1D (Federated Convolutional Neural Network 1D), based on federated learning for monitoring air quality and classifying different activities of daily living in indoor spaces. The system employs six different types of sensors to collect measurement parameters, which are then used to train a 1D CNN model locally for activity recognition. The proposed model is lightweight and edge deployable, making it suitable for real-time applications. Experiments were conducted using an air quality dataset specifically curated for Activity of Daily Living (ADL) classification. The results demonstrate that our approach Fed-CNN1D achieves 96.50% accuracy, 96.27% F1-Score, 96.54% precision, 96.21% recall, 0.11% loss, with low communication cost of 0.099Mb, and a swift detection time of 15 ms.
From Tradition to Innovation: Diverse Molecular Techniques in the Fight Against Infectious Diseases
Authors: AlSharksi Ahmed Nouri , Sirekbasan Serhat , Gürkök-Tan Tuğba , Mustapha Adam
Published: November 2024

Infectious diseases impose a significant burden on global health systems due to high morbidity and mortality rates. According to the World Health Organization, millions die from infectious diseases annually, often due to delays in accurate diagnosis. Traditional diagnostic methods in clinical microbiology, primarily culture-based techniques, are time-consuming and may fail with hard-to-culture pathogens. Molecular biology advancements, notably the Polymerase Chain Reaction (PCR), have revolutionized infectious disease diagnostics by allowing rapid and sensitive detection of pathogens' genetic material. PCR has become the gold standard for many infections, particularly highlighted during the COVID-19 pandemic. Following PCR, Next-Generation Sequencing (NGS) has emerged, enabling comprehensive genomic analysis of pathogens, thus facilitating the detection of new strains and antibiotic resistance tracking. Innovative approaches like CRISPR technology are also enhancing diagnostic precision by identifying specific DNA/RNA sequences. However, the implementation of these methods faces challenges, particularly in low- and middle-income countries due to infrastructural and financial constraints. This review will explore the role of molecular diagnostic methods in infectious disease diagnosis, comparing their advantages and limitations, with a focus on PCR and NGS technologies and their future potential.
Neural Network for Enhancing Robot Assisted Rehabilitation: A Systematic Review
Authors: Hasan Sk , Alam Nafizul , Mashud Gazi Abdullah , Bhujel Subodh
Published: November 2024

Recently, the integration of neural networks into robotic exoskeletons for physical rehabilitation has become popular due to their ability to interpret complex physiological signals. Surface electromyography (sEMG), electromyography (EMG), electroencephalography (EEG), and other physiological signals enable communication between the human body and robotic systems. Utilizing physiological signals for communicating with robots plays a crucial role in robot assisted neurorehabilitation. This systematic review synthesizes 44 peer-reviewed studies, exploring how neural networks can improve exoskeleton robot assisted rehabilitation for individuals with impaired upper limbs. By categorizing the studies based on robot assisted joints, sensor systems, and control methodologies, we offer a comprehensive overview of neural network applications in this field. Our findings demonstrate that neural networks, such as Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM), and Radial Basis Function Neural Networks (RBFNN), and other forms of neural network significantly contribute to patient specific rehabilitation by enabling adaptive learning and personalized therapy. CNNs improve motion intention estimation and control accuracy, while LSTM networks capture temporal muscle activity patterns for real-time rehabilitation. RBFNNs improve human-robot interaction by adapting to individual movement patterns, leading to more personalized and efficient therapy. This review highlights the potential of neural networks to revolutionize upper limb rehabilitation, improving motor recovery and patient outcomes in both clinical and home-based settings. It also recommends the future direction to customize existing neural networks for robot assisted rehabilitation applications.