bluuebunny/crossref_metadata_2025 huggingface dataset:
Nerve Growth Factor Shows Biphasic Expression during Adjuvant-Induced Neurogenic Inflammation
Authors: Gujar Vikramsingh , Pande Radhika Dilip , Das Subhas
Published: March 2024

Chronic inflammatory diseases are considered the most significant cause of death worldwide. Current treatments for inflammatory diseases are limited due to the lack of understanding of the biological factors involved in early-stage disease progression. Nerve growth factor (NGF) is a neurotrophic factor directly associated with inflammatory and autoimmune diseases like osteoarthritis, multiple sclerosis, and rheumatoid arthritis. It has been shown that NGF levels are significantly upregulated at the site of inflammation and play a crucial role in developing a robust inflammatory response. However, little is known about NGF's temporal expression profile during the initial progressive phase of inflammation. This study aimed to determine the temporal expression pattern of NGF in rat skin during Adjuvant-Induced Arthritis (AIA). Sprague Dawley rats were randomly divided into control and Complete Freund's Adjuvant (CFA) treated groups. Levels of NGF were evaluated following unilateral AIA at different time points and it was found that peripheral inflammation due to AIA significantly upregulated the expression of NGF mRNA and Protein in a biphasic pattern. These results suggest that NGF signaling is crucial for initiating and maintaining peripheral neurogenic inflammation in rats during AIA.
Environmental Factors Affecting Requirements for Wind Power Stations
Authors: Orynycz Olga , Ruchała Paweł , Tucki Karol , Wasiak Andrzej
Published: March 2024

The paper presents modelling of relationships between wind velocity distributions observed in Poland and technical requirements for wind power stations design. The wind velocities distributions for various locations in Poland are determined, and expressed in Weibull distribution parameters. Theoretical computations concerning the dependence of wind power station as function of wind speed and aire physical properties are presented. Conclusions important for design of power stations fitted to atmospheric conditions in Poland are given. Wind power plants have been an important source of electricity generation for many years.Wind power modelling with the use of wind speed is used to improve the accuracy of forecasts and analyses of the power production of wind farms.
Association Between Planetary Health Diet with Regular Consumption of Breakfast and a Well-Balanced Diet: A Cross-sectional Analysis in Japanese Male Undergraduates
Authors: Kibayashi Etsuko , Nakade Makiko
Published: March 2024

Few young Japanese adults regularly consume a well-balanced diet composed of staples, course dishes, and sides. We hypothesised that adopting the recommended planetary health diet with regular breakfast consumption would promote well-balanced diets among young Japanese male undergraduates. This study aimed to examine the structural association between a planetary health diet with regular breakfast consumption and well-balanced diet intake. Participants were 142 male undergraduates who completed a 2022 online questionnaire via Google Forms in a cross-sectional study at a public university in Hyogo Prefecture. A planetary health diet comprises the consumption of the recommended eight items. A covariance structure analysis was performed in a hypothetical model with factors (regular breakfast consumption and eight items) potentially associated with the intake of a well-balanced diet at least twice daily. Acceptable goodness-of-fit was obtained by excluding chicken dishes and nuts from the eight recommended items of the planetary health diet. Frequent consumption of the remaining six recommended items (fish, eggs, soybeans/soybean products, dairy foods, vegetables, and fruits) was significantly positively correlated with regular breakfast consumption and a significant positive path to a well-balanced diet. Among male university students, regular breakfast consumption and a planetary health diet may lead to a well-balanced diet.
Symptom Severity Changes in Obsessive-Compulsive Patients during COVID-19 Pandemic Are Associated with Shorter Illness Duration and Benzodiazepine Use: Possible Evolutionary Advantage of a Psychiatric Disorder
Authors: D’Urso Giordano , Magliacano Alfonso , Manzo Marco , Pomes Mattia Vittorio , Iuliano Carla , Iasevoli Felice , Dell'Osso Bernardo , De Bartolomeis Andrea
Published: March 2024

Obsessive–compulsive disorder (OCD) is believed to follow a waxing and waning course, often according to environmental stressors. During the COVID-19 pandemic, pre-existing OCD symptoms were reported to increase and to change from checking to washing behaviors, while new-onset symptoms were predominantly of the hoarding type. In the present study, we followed the evolution of OCD symptoms, anxiety, depression, and insight of illness in forty-six OCD patients throughout the pandemic. Clinical measures were collected at four different time points before and during the COVID-19 pandemic in Italy. Within-subject comparisons were used to compare clinical scale scores across time, and correlations were examined between patients' baseline characteristics and changes in clinical scores. We found that all clinical measures increased during the first Italian lockdown, with respect to the pre-pandemic values. Anxiety decreased during the temporary elimination of restriction provisions, whereas severity of OCD symptoms and insight returned to pre-pandemic values during the second mandatory lockdown. These results were observed only in two sub-groups of patients: those taking benzodiazepines and those with shorter illness duration. Our findings suggest the need of additional clinical attention to these specific sub-groups of OCD patients in case of particularly distressing circumstances, while pointing to a possible adaptive role of their OCD symptoms when the environment requires a higher care of hygiene and extraordinary supply of essential resources.
Synergizing Transfer Learning and Multi-Agent Systems for Thermal Parametrization in Induction Traction Motors
Authors: Mehboob Fozia , Fattouh Anas , Sahoo Smruti
Published: March 2024

This paper presents an innovative multi-agent, data-driven reinforcement learning (RL) approach to develop and utilize the thermal equivalent network model that represents the motor's thermal dynamics. A multi-agent reinforcement learning is designed and trained to adjust the model parameters using data from several motor driving cycles. To ensure the incoming driving cycle matches the historical data before employing the pre-trained RL agents, offline statistical analysis and clustering techniques are developed and used. Numerical simulations highlighted the RL agent's ability to develop strategies that effectively address the variability of driving cycles. The proposed RL framework showed its capability to accurately reflect the motor's thermal behavior under various driving conditions.
Chemical Characterization and Evaluation of the Antimicrobial Activity of Extracts from Two Cultivars of Cannabis sativa L. (Tisza and Kompolti) Grown in Sardinia
Authors: Juliano Claudia C.A. , Mattu Ivana , Marchetti Mauro , Usai Marianna
Published: March 2024

The present work was aimed at the chemical characterization and antimicrobial activity of some extracts of aerial parts (essential oils from leaves and inflorescences, and resins from inflorescences) of two legal hemp (Cannabis sativa) varieties, Tisza and Kompolti, grown in Sardinia. Chemical characterization was carried out by gas chromatography (GC) and gas chromatography-mass spectrometry (GC-MS) techniques. The antimicrobial activity of these extracts against a panel of microorganisms was also determined via minimum inhibitory concentration (M.I.C.) determination. While the results showed a minor or negligible antimicrobial activity of the extracts against Gram+ and Candida strains, a good antibacterial activity (especially of resins) was recorded against S. aureus; no substantial differences were detected between of the chemical compositions of the two Cannabis varieties.
Effects of Planting Position, Seedling Size and Organic N-fertilization on Establishment of Planted Scots Pine and Norway Spruce
Authors: Häggström Bodil , Hajek Jörgen , Nordin Annika , Öhlund Jonas
Published: March 2024

The forest regeneration phase in Sweden commonly involves mechanical soil preparation followed by planting of Scots pine or Norway spruce seedlings. The prepared soil offers planting positions with different properties, including decreased damage by pine weevil (Hylobius abietis L.). Nitrogen fertilization can be applied at the time of planting to aid establishment of the seedlings. In this study we compared the effect of organic nitrogen-fertilization for different planting positions, and seedling sizes on early survival and growth of Scots pine and Norway spruce seedlings. The main planting positions were capped mound, hinge, and mineral soil. Seedlings planted close to organic material were categorized as “low quality positions”, since proximity to organic material increase pine weevil attraction. Higher mortality rates related to pine weevil damage were recorded for seedlings planted in the low-quality positions, regardless of seedling size or N-fertilization. Pine weevil attack rates increased with increasing seedling size. Growth was in general lowest in mineral soil positions. The effect of organic N-fertilization on growth was positive for spruce regardless of planting positions and seedling size, while depending on planting position and seedling size for pine, indicating that effects of organic N-fertilization depend on seedling species, -size and planting position.
A Survey of Deep Learning Methods for Estimating the Accuracy of Protein Quaternary Structure Models
Authors: Chen Xiao , Liu Jian , Park Nolan , Cheng Jianlin
Published: March 2024

The quality prediction of quaternary structure models of a protein complex, in the absence
of its true structure, is known as the Estimation of Model Accuracy (EMA). EMA is useful for
ranking predicted protein complex structures and using them appropriately in biomedical research,
such as protein-protein interaction studies, protein design, and drug discovery. With the advent
of more accurate protein complex (multimer) prediction tools, such as AlphaFold2-Multimer and
ESMFold, the estimation of the accuracy of protein complex structures has attracted increasing
attention. Many deep learning methods have been developed to tackle this problem; however,
there is a noticeable absence of a comprehensive overview of these methods to facilitate future
development. Addressing this gap, we present a review of deep learning EMA methods for protein
complex structures developed in the past several years, analyzing their methodologies and impacts.
We also provide a prospective summary of some potential new developments for further improving
the accuracy of the EMA methods.
Structural Behaviour and Strength Evaluation of a Venetian Church through Finite Element Analysis
Authors: Stavroulaki Maria E. , Liofagos Ioannis (Yannos) , Darmarakis Panagiotis
Published: March 2024

Evaluation of structural behaviour of a masonry Venetian Church with pointed vault, is presented in this paper through an analysis following the neccessary steps of a monument study. Having a detailed geometric model and the material estimation, the finite element method was used in order the influence of specific structural parts of the structure like masonry butresses and walls connections to the structural behaviour are examined. The comparison of the eigenfrequencies which are estimated by in situ measurements and finite element modal analysis is used to model identification. The response spectrum analysis, the static analysis for subsidence of some parts and the transient analysis of a specific seismic excitation are used to evaluation of the church strength. Comparison of modal analysis results with the structural pathology is helpful to this research about the structural behaviour of the church.
Identification, Expression and Evolutional Analysis of Two cyp19-Like Genes in Amphioxus
Authors: Wang Yajun , Lin Jingyuan , Li Wenjin , Ji Guangdong , Liu Zhenhui
Published: March 2024

The mechanism of sex determination and differentiation in animals remains a central focus of reproductive and developmental biology research, and the regulation of sex differentiation in amphioxus remains poorly understood. Cytochrome P450 Family 19 Subfamily A member 1 (CYP19A1) is a crucial sex differentiation gene that catalyzes the conversion of androgens into estrogens. In this study, we identified two aromatase-like genes in amphioxus: cyp19-like1 and cyp19-like2. Cyp19-like1 is more primitive and may represent the ancestral form of cyp19 in zebrafish and other vertebrates. Cyp19-like2, on the other hand, is likely the result of gene duplication within am-phioxus suggesting its potential role as a key gene in sex differentiation. To gain further insights into the expression patterns of these two aromatase-like, we examined their expression in different gonad tissues and during different stages of gonad development. While the expression patterns of the two genes differ in gonad tissues, both are highly expressed in the gonad primordium and are primarily localized to microsomal membrane systems. However, as development proceeds, their expression levels decrease significantly. This study enhances our understanding of sex dif-ferentiation mechanisms in amphioxus and provides valuable insights into the formation and evolution of sex determination mechanisms in vertebrates.
Evaluation of the Ability of Using Shear-horizontal Surface Acoustic Wave Biosensors to Perform Sterility Testing of Nutrient Media
Authors: Sigmus Aimofumhe Eshiobomhe , Badewole Favour , Smith Dy’Mond , Thomas Marlon Sheldon
Published: March 2024

In this article, we describe a simple procedure for evaluating the sterility of nutrient media using a shear-horizontal surface acoustic wave (SH-SAW) biosensor. We used the SH-SAW biosensor platform to monitor the time-dependent phase responses of the material for the media that binds to a monolayer of 3-mercaptopropanyl-N-hydroxy succinimide on the biosensor surface. Increases in the phase shift less than 50% of the starting phase shift recorded 180 minutes after the sterilization indicate a successful sterility test of the media. Our devices were then applied to sterility testing using a viable Escherichia coli (E. coli) K-12 solution to confirm our hypothesis. Filtered LB Broth was the negative control, and a 24-hour culture of E. coli was the positive control. Before testing, the cell solution was pelleted, the media decanted and then replaced with a 1x phosphate-buffered saline solution (1x PBS). Since we know that the N-hydroxysuccinimide residues will bind to amine groups, only in cases where microbial species are present will the surface binding increase greater than 50%. We confirmed our hypothesis using SH-SAW biosensors and overnight E. coli cultures. The sensitivity for our 250 MHz quartz SH-SAW sensors was calculated based on the response from the E. coli K-12 solution over the linear dynamic range, which appears to be 2x104 – 2x107 CFU per ml and has a sensitivity of S = 1.655x105 o m2 Kg-1. The limit of detection (LOD) for these sensors was calculated to be approximately 2x10-9 grams (g) which is estimated to be approximately 2,000 Escherichia coli (E. coli) K-12 cells. However, the sensitivity and insertion loss remained approximately unchanged before and after coating the sensor with 3,3'-Dithiobis(succinimidyl) Propionate (DSP).
An Autonomous Tow Truck Algorithm for Engineless Aircraft Taxiing
Authors: Zaninotto Stefano , Gauci Jason , Zammit Brian
Published: March 2024

The aviation industry has proposed multiple solutions to reduce fuel consumption, air pollution and noise at airports, one of which involves deploying electric trucks for aircraft towing between the stand and the runway. However, the introduction of tow trucks results in increased surface traffic, posing challenges from the perspective of Air Traffic Controller's (ATCO). Various solutions involving automated planning and execution have been proposed, but many are constrained by their inability to manage multiple active runways simultaneously, and their failure to account for tow truck battery state-of-charge during assignments.
This paper presents a novel system for taxi operations that employs autonomous tow trucks to enhance ground operations and address deficiencies in existing approaches. The system focuses on identifying conflict-free solutions that minimize taxi-related delays and route length while maximising the efficient use of the tow trucks. The algorithm operates at a strategic level and uses a centralised approach. It has the capacity to cater for multiple active runways and considers factors such as tow truck battery state-of-charge and availability of charging stations. Furthermore, the proposed algorithm is capable of scheduling and routing tow trucks for aircraft taxiing without generating traffic conflicts.
Quantitative Peripheral Live Single T-Cell Dynamic Polyfunctionality as a Predictive Biomarker in Cancer Immunotherapy
Authors: Lim Zuan-Fu , Wu Xiaoliang , Zhu Lin , Albandar Heidar , Hafez Maria , Zhao Chenchen , Almubarak Mohammed , Smolkin Matthew B , Zheng Hong , Wen Sijin , Ma Patrick C
Published: March 2024

Predictive biomarkers for immune checkpoint inhibitors (ICI), such as PD-L1 expression (TPS), remain limited in clinical applications. Improved novel ICI predictive biomarkers are urgently needed. We evaluated a live single-cell functional liquid biopsy cytokine profiling platform to track immunotherapy treatment response and outcomes. Peripheral blood mononuclear cell samples of healthy donors and NSCLC patients undergoing ICI-based therapies were collected longitudinally pre-/post-treatment under IRB-approved protocols. Samples were enriched for CD4+ and CD8+ T-lymphocytes and analyzed on the IsoLight platform. The single T-cells were captured in microchambers on IsoCode chips for cytokines profiling. Functional polyfunctionality data from 55,775 single cells were analyzed using the IsoSpeak software, kappa coefficient, and Kaplan-Meier survival plots. We found a significant difference between responders and non-responders in CD8+ T-cells’ changes in overall polyfunctionality and polyfunctional strength index (ΔPSI). ΔPSI score in CD8+ T-cells performed better than PD-L1 TPS and, when combined with PD-L1 TPS, strongly correlated with early ICI treatment response with a kappa coefficient of 1.0 (p=0.003). High CD4+ T-cells ΔPSI predicted a strong trend of improved PFS (3.9-fold) and OS (3-fold). In conclusion, single peripheral T-cell polyfunctionality dynamics analysis is a promising liquid biopsy profiling platform as NSCLC ICI predictive biomarker regardless of oncogene-addiction status.
Operational Analysis of an Axial and Solid Double-Pole-Tweeted-Rotor Configuration in a PM Flux Switching Generators
Authors: Neto Manuel Pedro Garcia , Silva Francisco Ferreira , Branco P. J. da Costa
Published: March 2024

Two beneficial characteristics of aircraft generators are having armature windings and PM excitation sources placed on the stator side (maintenance and thermal management) and having a clear-cut rotor without permanent magnets or excitation windings (vulnerable at high speeds due to associated centripetal mechanical stresses). Within this framework, a doubly-salient permanent magnet (DSPM) generator was conceived by optimizing the stator size and rotor structure to minimize the torque ripple and maximize the RMS voltage value per turn of each generator phase. A Multi-Objective Design Strategy based on a 2D finite element analysis was used, being set to have characteristics closest to optimal for a Boeing 767 turbine, that is, the necessary electromotive force for a required power of 90 kW at 3000 rpm, feeding a simplified Boeing 767 electrical power distribution system. The results show that the machine could not deliver the required power at 3000 rpm since the 2D finite elements analysis demonstrates that the 2D model gives optimistic results when compared with the 3D FEM model. However, with a 3D finite element analysis of the machine feeding the aircraft load, it was seen that the machine’s efficiency is 92%, suggesting this machine can be a plausible solution.
Biocidal activity of the Bacillus thuringiensis 3D Cry toxins: Molecular crosstalk at the insect midgut with implication in insect resistance development
Authors: Guerrero Manriquez Gloria Guillermina Guillermina
Published: March 2024

Bacillus thuringiensis (Bt) is a Gram-positive bacteria characterized by the production of parasporal crystalline proteins toxic to a wide range of insect orders. Cry toxins targeted pests of crops of economic importance. Nowadays, it has been described around 600 genes encode crystalline proteins of molecular weight from a molecular weight of 50 to 130 kDa. These proteins are formed by three domains which X-rays have elucidated tridimensional structures. Their mode of action remains to be defined and understood. However, most of these proteins follow a basic program for their biocidal activity. A critical step in the mode of action of the 3D Cry toxins is the specific binding to the receptors present in the midgut epithelial. These receptors are determinants of the specificity and susceptibility of targeted insects. Among them is the classical set of glycosyl phosphate inositol (GPI)-anchored membrane receptors, such as N-aminopeptidase, Alkaline Phosphatase, and classical epithelial cadherins DE-Cadherins. The second group of binding proteins includes ABC transporters, V-ATPase, and other lipid rafts-associated proteins. The hallmark of this molecular crosstalk at the insect midgut epithelium is the conservation in the mode of action of the 3D-Cy toxins, but on the other side, a lock of the receptor expression, and the activation of the insect response which ultimately leads to insect resistance development and for instance a fight for ecological survival.
Research Progress on Spike-Dependent SARS CoV-2 Fusion Inhibitors and Small Molecules Targeting the S2 Subunit of Spike
Authors: Freidel Matthew R. , Armen Roger S.
Published: March 2024

Since the beginning of the COVID-19 pandemic, extensive drug repurposing efforts sought to identify small molecule antivirals with various mechanisms of action. Here we aim to review research progress on small molecule viral entry and fusion inhibitors that directly bind to the SARS CoV-2 Spike protein. Early in the pandemic, numerous small molecules were identified in drug repurposing screens and reported to be effective in vitro SARS CoV-2 viral entry or fusion inhibitors. However, given minimal experimental information regarding the exact location of small molecule binding sites on Spike, it was unclear what the specific mechanism of action was, or where the exact binding sites were on Spike for some inhibitor candidates. The work of countless researchers has yielded great progress, with the identification of many viral entry inhibitors that target elements on the S1 receptor binding domain (RBD) or N-terminal domain (NTD) and disrupt S1 receptor binding function. In this review, we will also focus on highlighting fusion inhibitors that target inhibition of the S2 fusion function, either by disrupting the formation of the postfusion S2 conformation or alternatively by stabilizing structural elements of the prefusion S2 conformation to prevent conformational changes associated with S2 function. We highlight experimentally validated binding sites on the S1/S2 interface and on the S2 subunit. While most mutations to the Spike protein to date in variants of concern (VOCs) have been localized to the S1 subunit, the S2 subunit sequence is more conserved with only a few observed mutations in proximity to S2 binding sites. Several recent small molecules targeting S2 have been shown to have robust activity over numerous recent VOC mutant strains and/or greater broad spectrum antiviral activity for other more distantly related coronaviruses.
Communicating about Sex Is Important in Generating Positive Perceptions about One’s Sexual and Romantic Life. The Last Decade Has Provided Insight into the Theoretical Applications on Sex Communication Research. While the Focus on Extant Research Focuses
Authors: Fedd Andre , Samp Jennifer Anne , Ray Colter
Published: March 2024

Communicating about sex is important in generating positive perceptions about one’s sexual and romantic life. The last decade has provided insight into the theoretical applications on sex communication research. While the focus on extant research focuses on the psychological processes’ individuals employ to talk about sex, no theoretical framework exists that identifies key constructs that provides a parsimonious understanding about the communicative processes of sex and sexuality. This review sought to identified key constructs that are suitable to develop a sex talk theory. In the current project, we reviewed 24 studies including 8,698 participants (Mage = 24.98) that applied a theoretical framework to sex research. This review identified three salient constructs (e.g., disclosure, cognitive, and relational and behavioral) that are important for a sex talk theory. Last, this review indicated that scholarship should explain the relationships between the key constructs. We provided several recommendations that scholars should take when developing a theory in sex communication research.
SERVIR West Africa Land Use and Land Cover Task Force: Building a Collaborative Network to Support Capacity Development in the Harmonization of Land Cover and Land Use Mapping and Monitoring in West Africa
Authors: Mensah Foster , Bartel Paul , Abramowitz Jacob , Cherrington Emil A. , Mahamane Mansour , Mamane Bako , Henry Matieu , Mushtaq Fatima , Di Gregorio Antonio , Dieye Amadou Moctar , Sanou Patrice , Enaruvbe Glory , Mar Ndeye Fatou
Published: March 2024

The availability of current land cover and land use (LCLU) information for monitoring the status of land resources has considerable value in ensuring sustainable land use planning. Similarly, the need to provide updated information on the extent of LCLU change in West Africa has become apparent, given the increasing demand for land resources driven by the rapid population growth in the sub-region. SERVIR West Africa, a regional consortium jointly supported by USAID and NASA to foster the use of geospatial and earth observation data and science for decision-making on critical environmental and food security challenges, in collaboration with the Food and Agriculture Organization of the United Nations (FAO), is building technical capacity in the sub-region to develop and implement harmonized regional land cover classification system for LULC change monitoring in West Africa, based on the Land Cover Meta Language (LCML-ISO 19144-2). This article focuses on the process, potential opportunities, outputs of this collaboration, exemplary use cases, and recommendations for the next steps.
A Deep Learning Model for Detecting the Diabetic Retinopathy Stages with Discrete Wavelet Transform
Authors: Mutawa A.M. , Al-Sabti Khalid , Raizada Seemant , Sruthi Sai
Published: March 2024

Diabetic retinopathy (DR) is the primary factor leading to vision impairment and blindness in diabetic people. Uncontrolled diabetes can damage the retinal blood vessels. Initial detection and prompt medical intervention are vital in preventing progressive vision impairment. Today's growing medical field poses more significant workload and diagnostic demands on medical professionals. In the proposed study, a convolutional neural network (CNN) is employed to detect the stages of DR. This research is crucial for studying DR because of its innovative methodology incorporating two different public datasets. This strategy enhances the model's capacity to generalize unseen DR images, as each dataset encompasses unique demographics and clinical circumstances. The network can learn and capture complicated hierarchical image features with asymmetric weights. Each image undergoes preprocessing using contrast-limited adaptive histogram equalization (CLAHE) and the discrete wavelet transform (DWT). The model is trained and validated using the combined datasets of Dataset for Diabetic Retinopathy (DDR) and the Asia Pacific Tele-Ophthalmology Society (APTOS). The CNN model is tuned with different learning rates and optimizers. The CNN model with Adam optimizer achieved 70% accuracy and an area under curve (AUC) score of 0.82. The recommended study results may reduce diabetes-related vision impairment by early DR severity identification.
Effectiveness of Maximum, Explosive and Combined Strength Training on Endurance Runners Performance Indicators: A Systematic Review and Meta-Analysis
Authors: Prieto-González Pablo , Yagin Fatma Hilal , Sánchez-Infante Jorge , Ardigò Luca Paolo
Published: March 2024

The effectiveness of combining strength-specific training with endurance training to enhance the performance of endurance runners remains uncertain. This study aimed to analyze effect of practising maximum-strength (MAX), explosive strength (EXP) or both combined (COMB) on seven runners’ performance-indicators: vertical jump (VJ), one-repetition-maximum-squat (1RM), peak-velocity/peak-running-speed (PV), lactate-threshold (over incremental-test-protocols, LT), middle-distance-time-trial (TT), maximum-oxygen-consumption (VO2max), running-economy (RE). Systematic-review (Scopus, Wed of Science, Sports Discuss, PubMed) with meta-analysis was conducted following PRISMA standards. Inclusion-criteria (PICOS) were: recreational or well-trained athletes aged 18-45 performing concurrent-training ≥five-week. Used search-terms were related to different types of strength/endurance, participants’ age, sport-modality. 20 manuscripts were selected, quality-assessed with PEDro. MAX training is more effective than EXP, COMB in improving VJ, 1RM, PV, while COMB is more effective than MAX, EXP to enhance TT. MAX is more effective than EXP in improving LT. Concurrent-workouts do not provide additional benefits to VO2max. It is unknown which strength-modality (MAX, EXP or COMB) is more effective in improving RE. Concurrent-training is more effective than single-mode-endurance-training for enhancing specific performance-variables in adult-endurance-runners. Middle-, long-distance-runners may consider incorporating MAX-training to target specific goals, e.g., improving VJ, 1RM, LT, PV while utilizing COMB-training to enhance TT. Certain variables may benefit from EXP. New randomized-controlled-trials are required to confirm these findings.
Plant-Based Diet and Supplements Reduced COVID-19 Severity and Mortality in Elderly Patients with Multiple Comorbidities (Part 2: Exploring the Underlying Mechanisms of Successful Intervention)
Authors: Mulijono Dasaad , Hutapea Albert Manggading , Lister I Nyoman Ehrich , Sudaryo Mondastri Khorib , Umniyati Helwiah
Published: March 2024

Abstract: The potential advantages of plant-based interventions in decreasing the incidence and lessening the severity and mortality of COVID-19 are yet to be widely acknowledged. Nevertheless, recent investigations propose that these interventions could be effective. Our recent publication (part one) features an interventional study in which we incorporated plant-based foods and provided supplementation to 3470 elderly COVID-19 patients with multiple comorbidities. We pay close attention to the precise selection of food items, the application of appropriate processing methods, and the provision of nourishing meals to our patients. Our outcome was highly successful as we achieved a zero mortality rate, and none of our patients experienced worsening conditions or required hospitalization. This second paper presents our theoretical framework on the mechanisms through which plant-based and supplement interventions can mitigate disease severity and mortality. However, only very recently have experts validated our hypotheses. The measures and methods used to address the ongoing SARS-CoV-2 pandemic through plant-based interventions and supplements are effective and may help prevent or manage future pandemics.
Is This the End of Anthropology as We Know It? Some Implication of FAIR Principles on Tales in Ethnological and Anthropological Qualitative Research
Authors: Orlić Olga
Published: March 2024

Open science, accessibility and knowledge sharing, especially of articles and monographs stemming from a publicly funded research, seem to be quite a positive direction in the development of science and have received almost unanimous approval from a scientific community. However, when it comes to data sharing, the data obtained by qualitative methodology deserve special attention and treatment. Although FAIR principles provide ways to anonymise the data and interlocoutors (as explained in Celjak et al 2020) individuals coming from smaller communities or even communities of practice can sometimes be easily regcognized by members of the same communitiy, especially if the data refers to audio files! The researcher is obliged to thoroughly describe the ways in which the data will be managed and used, and if it will state that the data will be managed in line with FAIR principles, this will inevitably impact the narratives collected. The prerogative to make all the data open will inevitably lead to autocesorship i.e. in creating a kind of FAIRy Tales for the future, interlocutors will share with researchers. Having all that in mind I argue for a more vigilant approach when embracing the idea that all the data should be made FAIR. Not all the data should be made FAIR because this could, in the end, compromise the research process itself. Some data must remain in the space of trust created between main actors in the research process. These data should be treated with CARE principles.
A role of trace amine-associated receptors in the immune system function
Authors: Moiseenko Vyacheslav I. , Apryatina Vera A. , Gainetdinov Raul R. , Apryatin Sergey A.
Published: March 2024

Trace amines are a separate, independent group of biogenic amines, close in structure to classical monoamine neurotransmitters such as dopamine, serotonin and norepinephrine.
G protein-coupled Trace Amine-Associated Receptors (TAAR) are mostly investigated for their involvement in the pathogenesis of neuropsychiatric disorders, but expression of TAAR family receptors is observed also in various populations of cells of the immune system. The review is focused on the basic information on the interaction of trace amines and their receptors with cells of the general immune system of humans and other mammals, as well as on data on TAARs role in the function of individual populations of myeloid and lymphoid cells.
With further research on the regulatory role of the trace amine system in the pathogenesis of the immune response and determination of the biological mechanisms for their action it would be possible to develop new methods for treating diseases related to immune system dysfunctions.
Composition and Bioactivity from the Essential Oil of Tetradenia riparia in Pathogenic Bacteria, Aedes aegypti L. (Diptera: Culicidae), and Toxicological Evaluation of Mus musculus (Rodentia: Muridae)
Authors: Rabelo Erica de Menezes , Martins Rosany Lopes , Rodrigues Alex Bruno Lobato , De Sousa Ridelley de Sousa , Farias Ana Luzia Ferreira , Galardo Allan Kardec Ribeiro , Cantuária Patrick de Castro , Tomazi Rosana , Almeida Sheylla Susan M. da S. de
Published: March 2024

Objective: In this work, we evaluated the chemical composition by chromatography coupled to mass spectrometry, antimicrobial and insecticidal activity of essential oils (TrEO) and nanoeffu-sion (NTrEO) of oil from Tetradenia riparia leaves. We also evaluated the acute toxicity in Mus musculus. The results showed that S. aureus showed greater susceptibility to TrEO, with a minimum inhibitory concentration (MIC) of 125 µg.mL-1, when compared to P. aeruginosa, E. coli, which presented a MIC of 250 µg.mL-1. There was a greater toxic effect on TrEO (LC50 = 630.29 µg.mL-1) and NTrEO (LC50 = 713.68 µg.mL-1) larvae, effect on pupae (LC50 = 630.29 µg.mL-1) and NTrEO (LC50 = 713.68 µg.mL-1) and ovicide (LC50 = 631.184 µg.mL-1) and NTrEO (LC50 = 146.701 µg.mL-1) of Ae. aegypti after 24 h of exposure, when compared to other exposure periods. Chemical analysis re-vealed 20 components, aromadendrene oxide (23.47%) being the main component. Female and male mice were used to assess toxicity and oral administration of NTrEO to mice did not result in acute toxicity. Thus, the essential oil of T. riparia and its nanoemulsion have insecticidal and an-timicrobial potential for Ae. aegypti, S. aureus, E. coli, P. aeruginosa, and has a high toxicological safety threshold at the concentrations evaluated in this study.
Evolutionary Reinforcement Learning of Neural Network Controller for Acrobot Task — Part4: Particle Swarm Optimization
Authors: Okada Hidehiko
Published: March 2024

Evolutionary algorithms and swarm intelligence algorithms find applicability in reinforcement learning of neural networks due to their independence from gradient-based methods. To achieve successful training of neural networks using these algorithms, careful considerations must be made to select appropriate algorithms due to the availability of various algorithmic variations. In Part1, 2 and 3, the author previously reported experimental evaluations on Evolution Strategy, Genetic Algorithm, and Differential Evolution for reinforcement learning of neural networks, utilizing the Acrobot control task. This article constitutes Part4 of the series of comparative research. In this study, Particle Swarm Optimization is adopted as an instance of major swarm intelligence algorithms. The experimental result shows that PSO performed worse than all of DE, GA and ES. The difference between PSO and DE was statistically significant (p<.01). In addition, PSO exhibited lower capability in exploring solutions in high-dimensional search spaces than DE, GA, and ES did. A larger swarm size compensated for the weakness of PSO in global exploration, thus making itself more beneficial than a larger number of swarm search iterations.
Role of Epigenetics in Drug-Induced Autism Spectrum Disorder
Authors: Csoka Antonei B , El Kouhen Nacer , Bennani Samia , Getachew Bruk , Aschner Michael , Tizabi Yousef
Published: March 2024

Autism spectrum disorder (ASD) is a neurodevelopmental disease characterized by persistent deficits in social interaction and communication, repetitive movements, abnormal focusing on objects, or activity that can significantly affect the quality of life of the afflicted. Brain neuronal and glial cells have been implicated. It has a genetic component but can also be triggered by environmental factors or drugs. For example, prenatal exposure to valproic acid (VPA) or acetaminophen (APAP) or ingestion of propionic acid (PPA) can increase the risk of ASD. Recently, epigenetic influences on ASD have been brought to the forefront of investigations on the etiology, prevention, and treatment of this disorder. Epigenetics refers to DNA modifications that alter gene expression without making any changes to the DNA sequence. Although an increasing number of pharmaceuticals and environmental chemicals are being implicated in the etiology of ASD, here we specifically focus on the molecular influence of the above-mentioned drugs on epigenetic alterations in neuronal and glial cells and their potential connection to ASD. It is concluded that a better understanding of these phenomena can lead to more effective interventions in ASD.
Exploring the Nexus between Dental Stem Cells and Maternal Oral Health during Pregnancy: What We Know and What We Don't
Authors: Meto Aida , Sula Ana , Peppoloni Samuele , Meto Agron , Blasi Elisabetta
Published: March 2024

During pregnancy, profound physiological changes occur in the maternal body, including those affecting oral health. Dental stem cells (DSCs) have emerged as promising candidates for regenerative therapies in dentistry. This manuscript delves into the intricate interplay between DSC behavior and maternal oral health during pregnancy. We provide an overview of current knowledge concerning the impact of pregnancy on DSCs, highlighting their potential roles in maintaining oral homeostasis and responding to pathological conditions. Additionally, we identify key research gaps and propose future directions for investigating novel therapeutic strategies leveraging DSCs to improve maternal and fetal oral health outcomes. By elucidating this relationship, we aim to pave the way for innovative approaches in preventive and regenerative dentistry tailored to the unique needs of pregnant women.
A Full-Newton Step Interior-Point Method for Weighted Quadratic Programming Based on the Algebraic Equivalent Transformation
Authors: Rao Yongsheng , Su Jianwei , Kheirfam Behrouz
Published: March 2024

In this paper, a new full-Newton step feasible interior point method for convex quadratic programming is presented and analyzed. The idea behind this method is to replace the complementarity condition with a non-negative variable weight vector and use the algebraic equivalent transformation for the obtained equation. Under the selection of appropriate parameters, the quadratic rate of convergence of the new algorithm is established. In addition, the iteration complexity of the algorithm is obtained. Finally, some numerical results are presented to demonstrate the practical performance of the proposed algorithm.
Using Plant Growth Promoting Bacillus pumilus Strains in Mitigation of Heavy Metals in Lettuce (Lactuca sativa)
Authors: Sakib S M Nazmuz
Published: March 2024

Heavy metal accumulation in soils used for agricultural purposes is a major issue as it can affect the growth of plants and contain health risks as plants containing heavy metals are taken as food. This study provided the potential of three Bacillus pumilus strains (C-2PMW-8, C-1 SSK-8, and C-1PWK-7) for mitigation of the health factors related to heavy metals on lettuce (Lactuca sativa) grown in chromium contaminated soil from activities related to mining. Lettuce seeds inoculated with B. pumilus strains were grown in pots with garden soil amended with varying amount of chromite mine soil (2.27%, 4.65%, 7.14%). Growth indicators like days to germination, percentage of germination, leaf weight, leaf area and rate of survival decreased with incremental soil chromium levels but improved highly with inoculation of B. pumilus compared to uninoculated controls. When B. pumilus strains were provided, there was also a decreased level in the buildup of chromium in soil as well as lettuce shoots. The results explains that plant growth-promoting B. pumilus strains may be able to lower down the detrimental effects of chromium on lettuce development, hence increment in the effectiveness of phytoremediation.
SkinLiTE: Lightweight Supervised Contrastive Learning Model for Enhanced Skin Lesion Detection and Disease Typification in Dermoscopic Images
Authors: Alzahrani Salha M.
Published: March 2024

This study introduces SkinLiTE, a lightweight supervised contrastive learning model, tailored to enhance the detection and typification of skin lesions in dermoscopic images. The core of SkinLiTE lies in its unique integration of supervised and contrastive learning approaches, which leverages labeled data to learn generalizable representations. This approach is particularly adept at handling the complexities and imbalances inherent in skin lesions datasets. The methodology encompasses a two-phase learning process. In the first phase, SkinLiTE utilizes an encoder network and a projection head to transform and project dermoscopic images into a feature space where contrastive loss is applied, focusing on minimizing intra-class variations while maximizing inter-class differences. The second phase freezes the encoder's weights, leveraging the learned representations for classification through a series of dense and dropout layers. The model was evaluated using three datasets from Skin Cancer ISIC 2019-2020, covering a wide range of skin conditions. SkinLiTE demonstrated superior performance across various metrics—accuracy, AUC , and F1 score—particularly when compared with traditional supervised learning models. Notably, SkinLiTE achieved an accuracy of 0.9087 using AugMix augmentation for binary classification of skin lesions. It also showed comparable results with the state-of-the-art approaches of ISIC challenge without relying on external data, underscoring its efficacy and efficiency. The results highlight the potential of SkinLiTE as a significant step forward in the field of dermatological AI, offering a robust, efficient, and accurate tool for skin lesion detection and classification. Its lightweight architecture and ability to handle imbalanced datasets make it particularly suited for integration into Internet of Medical Things environments, paving the way for enhanced remote patient monitoring and diagnostic capabilities. This research contributes to the evolving landscape of AI in healthcare, demonstrating the impact of innovative learning methodologies in medical image analysis.
Integrating Genome-Scale Metabolic Models with Patient Plasma Metabolome to Study Endothelial Metabolism In Situ
Authors: Silva-Lance Fernando , Montejano-Montelongo Isabel , Bautista Eric , Nielsen Lars K. , Johansson Pär I. , Marin de Mas Igor
Published: March 2024

Abstract: Patient blood samples are invaluable in clinical omics databases, yet current methodologies often fail to fully uncover the molecular mechanisms driving patient pathology. While Genome-scale Metabolic Models (GEMs) show promise in systems medicine by integrating various omics data, having only exometabolomic data remains a limiting factor. To address this gap, we introduce a comprehensive pipeline integrating GEMs with patient plasma metabolome. This pipeline constructs case-specific GEMs using literature-based and patient-specific metabolomic data. Novel computational methods, including adaptive sampling and an in-house developed algorithm for the rational exploration of the sampled space of solutions, enhance integration accuracy while improving computational performance. Model characterization involves task analysis in combination with clustering methods to identify critical cellular functions. The new pipeline was applied to a cohort of trauma patients to investigates shock-induced endotheliopathy using patient plasma metabolome data. By analyzing endothelial cell metabolism comprehensively, the pipeline identified critical substrates and contributed to the development of targeted therapeutic strategies. Our study demonstrates the efficacy of integrating patient plasma metabolome data into computational models to analyze endothelial cell metabolism in disease contexts. This approach offers a deeper understanding of metabolic dysregulations and provides insights into diseases with metabolic components and potential treatments.
Data Envelopment Analysis (DEA) to Estimate Technical and Scale Efficiencies of Smallholder Pineapple Farmers in Ghana
Authors: Boakye Kwaku , Lee Yu-Feng , Annor-Frempong Festus , Dadzie Samuel , Salifu Iddrisu
Published: March 2024

The study focused on the technical and scale efficiency of smallholder pineapple farmers in the Central Region of Ghana. The input-oriented Data Envelopment Analysis (DEA) was used to estimate technical, pure and scale efficiencies of the smallholder pineapple farmers, of which a random sampling procedure was used to select 320 respondents. The study revealed that the farmers were technically inefficient with mean technical efficiency under Constant Returns to Scale (CRS), pure efficiency under Variable Returns to Scale (VRS) and the Scale Efficiency levels of 0.505, 0.641 and 0.772, respectively, due to farmers’ inability to exploit fully the available technology while experiencing evident post-harvest losses resulting from low adoption of post-harvest technologies. Such findings are meaningful and could help the farming communities and relevant policymakers to understand the issues in farming production and hence undertake necessary actions to potentially improve farmers’ technical and scale efficiencies in the study area.