bluuebunny/crossref_metadata_2025 huggingface dataset:
Combinations of Terminalia bellirica (Gaertn.) Roxb. and Terminalia chebula Retz. Extracts with Selected Antibiotics Against Antibiotic-Resistant Bacteria: Bioactivity and Phytochemistry
Authors: Tiwana Gagan , Cock Ian Edwin , Cheesman Matthew James
Published: October 2024

Antimicrobial resistance (AMR) has arisen due to antibiotic overuse and misuse. Antibiotic resistance renders standard treatments less effective, making it difficult to control some infections, thereby increasing morbidity and mortality. Medicinal plants are attracting increased interest as antibiotics lose efficacy. This study evaluates the antibacterial activity of solvent extracts prepared using Terminalia bellirica and Terminalia chebula fruit against six bacterial pathogens using disc diffusion and broth microdilution assays. The aqueous and methanol extracts of T. bellirica and T. chebula showed substantial zones of inhibition (ZOIs) against Staphylococcus aureus and methicillin-resistant S. aureus (MRSA). The activity against those bacteria was strong, with minimum inhibitory concentrations (MIC) ranging from 94 µg/mL to 392 µg/mL. Additionally, the T. bellirica methanolic extract showed noteworthy antibacterial activity against Escherichia coli and an extended spectrum β-lactamase (ESBL) E. coli strain (MIC values of 755 µg/mL for both). The aqueous T. bellirica and T. chebula extracts also inhibited Klebsiella pneumoniae growth (MIC values of 784 µg/mL and 556 µg/mL, respectively). The corresponding methanolic extracts also inhibited ESBL K. pneumoniae growth (MIC values of 755 µg/mL and 1509 µg/mL, respectively). Eighteen additive interactions were observed when extracts were combined with reference antibiotics. Strong antagonism occurred when any of the extracts were mixed with polymyxin B. Liquid chromatography-mass spectroscopy (LC-MS) analysis of the extracts revealed several interesting flavonoids and tannins, including 6-galloylglucose, 1,2,6-trigalloyl-β-D-glucopyranose, 6-O-[(2E)-3-phenyl-2-propenoyl]-1-O-(3,4,5-trihydroxybenzoyl)-β-D-glucopyranose, propyl gallate, methyl gallate, sanguiin H4, hamamelitannin, pyrogallol, gallic acid, ellagic acid, chebulic acid, and chebuloside II. All extracts were nontoxic in brine shrimp assays. This lack of toxicity, combined with their antibacterial activities, suggests that these plant species may be promising sources of antibacterial compound(s) that warrant further study.
Queen Bee Larva, an Edible By-Product of Royal Jelly, Alleviate D-Galactose-Induced Aging in Mouse by Regulating Gut Microbiota Structure and Amino Acid Metabolism
Authors: Zhao Tong , Xue Xiaofeng , Liu Pingxiang , Hu Han , Wang Kai , Wang Yutao , Wu Liming
Published: October 2024

Queen bee larva (QBL), as a by-product of royal jelly, is a kind of protein-rich edible insect. However, the development and utilization of QBL have been very limited for an extended period, resulting in considerable economic waste. Notably, QBL has substantial potential for anti-aging treatments; however, systematic studies have been scarce. The present study aimed to analyze the effects of freeze-dried QBL powder (QBLP) treatment in a D-galactose (D-gal)-induced-aging mouse and to explore the mechanisms. A behavioral test indicated that QBLP-treated mice had improved cognitive function and memory decline caused by aging compared to untreated aged mice. Furthermore, QBLP treatment improved organ index in aged mice and prevented pathological damage to the brain tissue. Concomitantly, treatment of D-gal-induced-aging mice with QBLP significantly reduced the oxidative damage of serum and increased the skin moisture content of aging mice. Finally, integrated analyses of the gut microbiota and the serum metabolome showed that QBLP supplementation altered the composition of the gut microbiota, enriched biochemical pathways associated with amino acid metabolism, and adjusted serum concentrations of beneficial free amino acids. Overall, QBLP can improve symptoms related to D-gal-induced aging in mice by regulating gut microbiota structure and amino acid metabolism.
High-Power, High-Beam-Quality, Long-Pulse-Width 532 nm Laser Based on a 4f Optical System
Authors: Hu Jiapeng , Li Wenbo , Li Dong , Liu Hongcai , Xia Nanhui , Zhang Tianyu , Liu Xuesheng , Liu Youqiang , Wang Zhiyong
Published: October 2024

In response to the demand for high-power, long-pulse-width 532 nm lasers in the medical and industrial processing fields, this paper explains how the laser cavity of a high-power Nd:YAG 532 nm laser can be extended while maintaining the laser’s q-parameter by using a 4f optical system. The results show that at a repetition rate of 10 kHz, the extended cavity achieved a maximum average power of 112 W. Compared with the short cavity, the power was not significantly reduced. The pulse width was extended from 56 ns to 85 ns, and its broadening ratio reached 46.5%. The laser maintained good beam quality during high-power operation.
Analysis of the Construction Sequence of a Reaction Wall in a Structural Laboratory Supported by the VDC Methodology
Authors: Rengifo Fuentes Rafael , Valdez Eguiluz Noe , Almeida Del Savio Alexandre
Published: October 2024

The structures laboratory is a crucial facility for supporting research development related to the construction industry. This kind of laboratory has several components, and one of its key components is the reaction wall. The reaction wall supports the execution of experimental tests on structural elements under specific configurations and loads. Constructing a reaction wall presents challenges due to the highest standards to be met. This research analyzes the construction process of a reaction wall at a private university in Peru. Initially, a schedule was proposed by a contractor. However, the client, knowing the complexity of such construction, asked to review the initial schedule to ensure that it would meet the constructability requirements under the integrated product-organization-process approach given by the virtual design and construction (VDC) methodology. The result of this study pointed out the need to revise the original proposed schedule, extending the construction time to 66% due to the lack of construction processes compatible with the requirements for the reaction wall’s execution. Finally, a survey was conducted to observe the learning curve associated with implementing the VDC methodology.
Influence of Solution Treatment Temperatures on LPBF-Produced Inconel 939 Alloy on Mechanical Performance
Authors: Piwowarski Piotr , Moszczyńska Dorota , Paradowski Krystian , Wieczorek-Czarnocka Monika , Mizera Jarosław
Published: October 2024

This study investigates the influence of solution treatment temperatures on the microstructure and mechanical properties of LPBF (Laser Powder Bed Fusion)-manufactured Inconel 939 alloy. The primary objectives are to assess the impact of sub-recrystallization (below recrystallization temperature) and recrystallization temperatures during solution treatment on mechanical performance under different conditions. This study validates the hypothesis concerning carbide redistribution and mechanical performance in LPBF-produced Inconel 939 parts through comprehensive analysis, including microstructure studies and tensile tests. The results indicate that higher heat treatment temperatures lead to significant changes in carbide redistribution and mechanical performance. For instance, at room temperature, the specimen with sub-recrystallization solution treatment temperature exhibited superior mechanical properties compared to both the as-built and recrystallization-temperature solution treatment specimens. However, at elevated temperatures (700 °C), a reversal in mechanical anisotropy was observed, with the vertical axis demonstrating higher tensile strength compared to the horizontal axis for all material states. Furthermore, a microstructural analysis revealed distinct changes in grain structure and precipitate distribution, particularly the migration of carbides from grain boundaries to intragranular regions. These findings underscore the importance of precise control over heat treatment parameters to achieve optimal mechanical behavior. This research provides valuable insights into optimizing LPBF processes for the Inconel 939 alloy, highlighting the need for a meticulous control of the solution treatment parameters to ensure mechanical integrity. The findings contribute to a broader understanding of material-specific responses in additive manufacturing, with significant implications for aerospace applications.
AI-Driven Particulate Matter Estimation Using Urban CCTV: A Comparative Analysis Under Various Experimental Conditions
Authors: Choi Woochul , Sung Hongki , Chong Kyusoo
Published: October 2024

Despite the high public interest in particulate matter (PM), a key determinant for indoor and outdoor activities, the current PM information provided by monitoring stations (e.g., data per administrative district) is insufficient. This study employed the closed-circuit television (CCTV) cameras densely installed within a city to explore the spatial expansion of PM information. It conducted a comparative analysis of PM estimation effects under diverse experimental conditions based on AI image recognition. It also fills a gap by providing an optimal analysis framework that comprehensively considers the combination of variables, including the sun’s position, day and night settings, and the PM distribution per class. In the deep learning model structure and process comparison experiment, the hybrid DL-ML model using ResNet152 and XGBoost showed the highest predictive power. The classification model was better than the ResNet regression model, and the hybrid DL-ML model with the post-processed XGBoost was better than the single ResNet152 model regarding AI prediction of PM. All four experiments that excluded the nighttime, added the solar incidence angle variable, applied the distribution of PM per class, and removed the outlier removal algorithm showed high predictive power. In particular, the final experiment that satisfied all conditions, including the exclusion of nighttime, addition of solar incidence angle variable, and application of outlier removal algorithm, derived predictive values that are expected to be commercialized.
KAN-Transformer Model for UltraShort-Term Wind Power Prediction Based on EWMA Data Processing
Authors: Xing Feng , Gao Yanlong , Kang Lipeng , Zhang Mingming , Qin Caiyan
Published: October 2024

When using the Transformer model for wind power prediction, the presence of noise in wind power data and the model’s final layer relying solely on a simple linear output reduces the model’s ability to capture nonlinear relationships, leading to a decrease in prediction accuracy. To address these issues, this paper proposes an ultrashort-term wind power prediction model based on exponential weighted moving average (EWMA) data processing and Kolmogorov–Arnold Network (KAN)-Transformer. First, multiple variable features are smoothed using EWMA, which suppresses noise while preserving the original data trends. Then, the EWMA-processed data is input into the Encoder and Decoder modules of the Transformer model to extract features. The output from the Decoder layer is then passed through the KAN layer, built using a cubic B-spline function, to enhance the model’s ability to capture nonlinear relationships, thereby improving the prediction accuracy of the Transformer model for wind power. Finally, experimental analysis is conducted, and it shows that the proposed model achieves the highest prediction accuracy, with a mean absolute error of 4.38 MW, a root mean squared error of 7.37 MW, and a coefficient of determination of 98.73%.
Rock Slope Instability Mechanism Induced by Repeated Mining in Mountain Mining Areas
Authors: Luo Rong , Li Guangyue , Chen Lu , Zeng Ling , Pei Ke , Yu Xiangxi
Published: October 2024

When mineral resources are extracted using underground mining methods in hilly regions, landslides or slope failures can be induced frequently. In this study, slope collapse disasters in mountain mining areas were analyzed. The model test and numerical simulation of the slope impacted by repeated mining were carried out. The crack evolution and failure process were analyzed to reveal the instability mechanism. The results show that the rock mass would topple to the inside of the slope first, when the subsidence of overlying rock was induced by the mining of the upper coal seam. When repeated mining was performed in the lower coal seam, the mining induced macro-cracks that could connect with natural fissures, inducing the outward displacement of the slope. Then, the rock mass at the foot of the slope has to bear the upper load, which is also squeezed out by the collapsed rock mass, forming the potential slip zone. Finally, the instability is caused by the shear slip of the slope toe rock mass. Therefore, the instability evolution of the slope under underground repeated mining disturbance can be divided into four stages as follows: roof caving and overlaying rock subsidence, joint rock toppling, fracture penetration, and slope toe shearing and slope slipping.
Objective Measures of Work and Non-Work Physical Behaviors Associated with Neck and Back Pain in Viticulture Workers
Authors: de Lavor Joaquim Martins , Pina Ana Karolina Almeida , de Brito Camila Alves , de Almeida Wéverton Berto , Brusaca Luiz Augusto , Schmit Emanuelle Francine Detogni , de Oliveira Ana Beatriz , da Silva Amanda Alves Marcelino , Magalhães Paulo André Freire , Locks Francisco
Published: October 2024

Musculoskeletal disorders are prevalent among agricultural workers, increasing the risk of work-related diseases due to manual labor, repetitive tasks, and prolonged postures. This study evaluates the association between physical behaviors during work and non-work, measured objectively, and musculoskeletal pain in the neck, upper back, and lower back in viticulture workers. A cross-sectional quantitative study was conducted with 75 viticulturists of both sexes aged 18 years or older. An accelerometer measured physical behaviors (lying down, sitting, standing, moving, walking, and sleeping) during work and non-work periods. Pain intensity was quantified using a 0–10 scale and categorized as “Low” and “High” pain intensity. Binary logistic regression tested the association between pain and time spent on physical behaviors. Results indicated a high prevalence of pain: 46.7% cervical, 52% upper back, and 60% lower back. Standing was the most common behavior during work, while lying and sitting were predominant during non-work. An increased sleeping time was associated with a decreased probability of experiencing high-intensity neck pain. Increased time spent lying down during non-work hours was associated with an increased probability of experiencing high-intensity upper back pain. No physical behavior was associated with high-intensity lower back pain. In conclusion, sedentary behaviors worsen upper back pain, and sleep reduces neck pain in viticulture workers.
Balance of Antioxidants vs. Oxidants in Perinatal Asphyxia
Authors: Rallis Dimitrios , Dermitzaki Niki , Baltogianni Maria , Kapetaniou Konstantina , Giapros Vasileios
Published: October 2024

Perinatal asphyxia refers to an acute event of cerebral ischemia and hypoxia during the perinatal period, leading to various degrees of brain injury. The mechanisms involved in perinatal asphyxia include the production of reactive oxygen species (ROS), accumulation of intracellular calcium, lipid peroxidation, excitatory amino acid receptor overactivation, energy failure, and caspase-mediated cell death. Both primary and secondary neuronal damage are caused by the overproduction of ROS following a hypoxic/ischemic event. ROS can react with nearly any type of molecule, including lipids, proteins, polysaccharides, and DNA. Neonates who suffer from perinatal asphyxia are prone to oxidative stress, which is characterized by a disruption in the oxidant/antioxidant balance, favoring oxidants over the intracellular and extracellular antioxidant scavenging mechanisms. Current research has focused on developing treatment strategies that potentially improve the endogenous antioxidant neuroprotective mechanisms or minimize injury resulting from hypoxia/ischemia. In this narrative review, we aim to present evidence regarding the contribution of oxidant/antioxidant balance to the pathogenesis and progression of perinatal asphyxia. Also, we aim to explore the role of potential antioxidant therapies as promising treatment strategies for perinatal asphyxia, especially as an adjunct to therapeutic hypothermia in infants with perinatal asphyxia. The current literature on antioxidant treatments in newborns is limited; however, allopurinol, melatonin, and erythropoietin have shown some positive effects in clinical trials. Inhibitors of nitric oxide synthase, N-acetylcysteine, and docosahexaenoic acid have shown promising neuroprotective effects in preclinical studies. Finally, nanotherapeutics could potentially modulate oxidative stress in hypoxemic/ischemic brain injury by targeted medication delivery. Future research on neuroprotectants and their processes is warranted to develop innovative treatments for hypoxia/ischemia in clinical practice.
Model-Centric Integration of Uncertain Expert Knowledge into Importance Sampling-Based Parameter Estimation
Authors: Kenyeres Éva , Abonyi János
Published: October 2024

This study presents a model-based parameter estimation method for integrating and validating uncertainty in expert knowledge and simulation models. The parameters of the models of complex systems are often unknown due to a lack of measurement data. The experience-based knowledge of experts can substitute missing information, which is usually imprecise. The novelty of the present paper is a method based on Monte Carlo (MC) simulation and importance sampling (IS) techniques for integrating uncertain expert knowledge into the system model. Uncertain knowledge about the model parameters is propagated through the system model by MC simulation in the form of a discrete sample, while IS helps to weight the sample elements regarding imprecise knowledge about the outputs in an iterative circle. Thereby, the consistency of expert judgments can be investigated as well. The contributions of this paper include an expert knowledge-based parameter estimation technique and a method for the evaluation of expert judgments according to the estimation results to eliminate incorrect ones. The applicability of the proposed method is introduced through a case study of a Hungarian operating waste separation system. The results verify that the assessments of experts can be efficiently integrated into system models, and their consistency can be evaluated.
Element Migration of Mineralization-Alteration Zones and Its Geological Implication in the Beiya Porphyry–Skarn Deposit, Northwestern Yunnan, China
Authors: Liu Fei , Han Runsheng , Guo Yuxinyue , Wang Mingzhi , Tan Wei
Published: October 2024

Porphyry and the associated skarn-type deposit is one of the most important types of ore deposits worldwide, which usually exhibit significant zoning of mineralization-alteration, but the research on element migration in these mineralization-alteration zones is relatively weak. The Beiya porphyry–skarn gold-polymetallic deposit is a super-large Cenozoic deposit located in the Sanjiang metallogenic belt, northwestern Yunnan, China. In this paper, through a detailed analysis of mineralization and alteration zoning and its element migration regularity, the findings are as follows: (1) Three types of hydrothermal alteration—porphyry alteration, contact alteration, and wall-rock alteration—are developed, and porphyry alteration includes potassic, phyllic, propylitic, and argillic alteration; (2) five types of mineralization—porphyry-type Cu–Au–(Mo), skarn-type Au–Fe–(Cu), hydrothermal vein-type Au–Fe, distal hydrothermal-type Pb-polymetallic, and oxidizing-leaching enriched-type Au—occur in a diversity of forms, which are dominantly controlled by structures and lithologies; (3) concentric-banded mineralization-alteration zones are exhibited centrally from the alkaline porphyry outward or upward, namely [porphyry alteration] potassic → phyllic → propylitic → argillic → [contact alteration] skarnitization–marbleization → [wall-rock alteration] marbleization–silicification–calcitization; (4) porphyry-type mineralization predominantly forms within potassic and phyllic zones, while skarn-type mineralization occurs in contact alteration zones, and proximal and distal hydrothermal (vein)-type mineralization are commonly distributed in marbleization–silicification–calcitization alteration zones; and (5) element migration analysis demonstrates a significantly lateral and vertical zoning in the metallogenic element association of Cu–Mo → Cu–Au → Au–Fe–Cu → Au–Fe → Pb–Zn–Au–Ag–Fe from alkaline porphyry outward to the wall-rock. The mineralization-alteration zoning model indicates the Beiya deposit has similar mineralization and alteration zone characteristics to the typical porphyry copper system; and element migration within mineralization-alteration zones provides new scientific information for understanding the metallogenic regularity and prospecting at Beiya, as well as the similar types of deposits in the Sanjiang metallogenic belt and elsewhere in the world.
Experimental and Numerical Evaluation of Calcium-Silicate-Based Mineral Foam for Blast Mitigation
Authors: Aminou Aldjabar , Ben Rhouma Mohamed , Belkassem Bachir , Ousji Hamza , Pyl Lincy , Lecompte David
Published: October 2024

Cellular materials such as aluminum and polyurethane foams are recognized for their effectiveness in energy absorption. They commonly serve as crushable cores in sacrificial cladding for blast mitigation purposes. This study delves into the effectiveness of autoclaved aerated concrete (AAC), a lightweight, porous material known for its energy-absorbing properties as a crushable core in sacrificial cladding. The experimental set-up features a rigid frame made of steel measuring 1000 × 1000 × 15 mm3 with a central square opening (300 × 300 mm2) holding a 2 mm thick aluminum plate representing the structure. The dynamic response of the aluminum plate is captured using two high-speed cameras arranged in a stereoscopic configuration. Three-dimensional digital image correlation is used to compute the transient deformation fields. Blast loading is achieved by detonating 20 g of C4 explosive set at 250 mm from the plate’s center. The study assesses the mineral foam’s absorption capacity by comparing out-of-plane displacement and mean permanent deformation of the aluminum plate with and without the protective solution. Six foam configurations (A to F) are tested experimentally and numerically, varying in the foam’s free space for expansion relative to its total volume. Results show positive protective effects, with configuration F reducing maximum deflection by at least 30% and configuration C by up to 70%. Foam configuration influences energy dissipation, with an optimal lateral surface-to-volume ratio (ζ) enhancing protective effects, although excessive ζ leads to non-uniform foam crushing. To address the influence of front skin deformability, a non-deformable front skin has been adopted. The latter demonstrates an increased effectiveness of the sacrificial cladding, particularly for ζ values above the optimal value obtained when using a deformable front skin. Notably, using a non-deformable front skin increases maximum deflection reduction and foam energy absorption by up to approximately 30%.
Novel Drug Combinations in Lung Cancer: New Potential Synergies Between 5-FU and Repurposed Drugs
Authors: Ribeiro Eduarda , Vale Nuno
Published: October 2024

The therapeutic potential of combining 5-FU with repurposed drugs such as Sildenafil, Tezosentan, Levosimendan, and Resveratrol was investigated in lung cancer treatment using the A549 cell line. This study aimed to enhance 5-FU efficacy while mitigating side effects and overcoming drug resistance. The cytotoxic effects of 5-FU were assessed via MTT assay, with an IC50 value of 5.03 µM for A549 cells. Subsequent experiments evaluated the impact of combining 5-FU with the aforementioned drugs on cell viability, clonogenic potential, and morphology. The results demonstrated that while Sildenafil and Tezosentan modestly improved 5-FU efficacy, Levosimendan reduced cell viability by 40% (p < 0.01) and Resveratrol by over 50% (p < 0.001), with clonogenicity reduced by up to 60% (p < 0.001). These findings suggest that combining 5-FU with Levosimendan or Resveratrol offers promising approaches for lung cancer therapy, potentially reducing the need for higher doses of 5-FU and minimizing associated toxicity. Future studies are warranted to elucidate the mechanisms underlying these interactions and assess their clinical relevance.
An Engineering Model to Represent Positive Return Strokes—An Extension of the Modified Transmission Line (MTL) Model
Authors: Cooray Vernon , Rachidi Farhad , Rubinstein Marcos
Published: October 2024

An engineering model to represent positive return strokes is introduced as an extension of the Modified Transmission Line model with Linear Current Decay (MTLL). This extension is grounded in experimental data on the electric fields and currents associated with positive return strokes. The core premise of the model is that once the return stroke front reaches the cloud, recoil leader-type activities within the cloud feed the lightning channel with a positive charge. This positive charge then travels to the ground in the form of an M-component, enhancing both the amplitude and duration of the impulse current in the channel and at ground level. The propagation of the return stroke current along the channel follows the MTLL model, while the M-component is treated as a current pulse traveling from the cloud to the ground. At ground level, the M-component current is fully reflected. The model successfully generates electromagnetic fields that resemble those observed from positive return strokes, and it is easily applicable to studies involving the interaction of positive return stroke fields with power lines and the Earth’s upper atmosphere.
Stability of Certain Non-Autonomous Cooperative Systems of Difference Equations with the Application to Evolutionary Dynamics
Authors: Kulenović Mustafa R. S. , Nurkanović Mehmed , Nurkanović Zehra , Trolle Susan
Published: October 2024

This paper investigates the dynamics of non-autonomous cooperative systems of difference equations with asymptotically constant coefficients. We are mainly interested in global attractivity results for such systems and the application of such results to evolutionary population cooperation models. We use two methods to extend the global attractivity results for autonomous cooperative systems to related non-autonomous cooperative systems which appear in recent problems in evolutionary dynamics.
Mobile Application and Machine Learning-Driven Scheme for Intelligent Diabetes Progression Analysis and Management Using Multiple Risk Factors
Authors: Jiang Huaiyan , Wang Han , Pan Ting , Liu Yuhang , Jing Peiguang , Liu Yu
Published: October 2024

Diabetes mellitus is a chronic disease that affects over 500 million people worldwide, necessitating personalized health management programs for effective long-term control. Among the various biomarkers, glycated hemoglobin (HbA1c) is a crucial indicator for monitoring long-term blood glucose levels and assessing diabetes progression. This study introduces an innovative approach to diabetes management by integrating a mobile application and machine learning. We designed and implemented an intelligent application capable of collecting comprehensive data from diabetic patients, creating a novel diabetes dataset named DiabMini with 127 features of 88 instances, including medical information, personal information, and detailed nutrient intake and lifestyle. Leveraging the DiabMini, we focused the analysis on HbA1c dynamics due to their clinical significance in tracking diabetes progression. We developed a stacking model combining eXtreme Gradient Boosting (XGBoost), Support Vector Classifier (SVC), Extra Trees (ET), and K-Nearest Neighbors (KNN) to explore the impact of various influencing factors on HbA1c dynamics, which achieved a classification accuracy of 94.23%. Additionally, we applied SHapley Additive exPlanations (SHAP) to visualize the contributions of risk factors to HbA1c dynamics, thus clarifying the differential impacts of these factors on diabetes progression. In conclusion, this study demonstrates the potential of integrating mobile health applications with machine learning to enhance personalized diabetes management.
Integrating Molecular Perspectives: Strategies for Comprehensive Multi-Omics Integrative Data Analysis and Machine Learning Applications in Transcriptomics, Proteomics, and Metabolomics
Authors: Sanches Pedro H. Godoy , de Melo Nicolly Clemente , Porcari Andreia M. , de Carvalho Lucas Miguel
Published: October 2024

With the advent of high-throughput technologies, the field of omics has made significant strides in characterizing biological systems at various levels of complexity. Transcriptomics, proteomics, and metabolomics are the three most widely used omics technologies, each providing unique insights into different layers of a biological system. However, analyzing each omics data set separately may not provide a comprehensive understanding of the subject under study. Therefore, integrating multi-omics data has become increasingly important in bioinformatics research. In this article, we review strategies for integrating transcriptomics, proteomics, and metabolomics data, including co-expression analysis, metabolite–gene networks, constraint-based models, pathway enrichment analysis, and interactome analysis. We discuss combined omics integration approaches, correlation-based strategies, and machine learning techniques that utilize one or more types of omics data. By presenting these methods, we aim to provide researchers with a better understanding of how to integrate omics data to gain a more comprehensive view of a biological system, facilitating the identification of complex patterns and interactions that might be missed by single-omics analyses.
“Seeing Is Believing”: How Neutron Crystallography Informs Enzyme Mechanisms by Visualizing Unique Water Species
Authors: Wan Qun , Bennett Brad C.
Published: October 2024

Hydrogen is the lightest atom and composes approximately half of the atomic content in macromolecules, yet their location can only be inferred or predicted in most macromolecular structures. This is because hydrogen can rarely be directly observed by the most common structure determination techniques (such as X-ray crystallography and electron cryomicroscopy). However, knowledge of hydrogen atom positions, especially for enzymes, can reveal protonation states of titratable active site residues, hydrogen bonding patterns, and the orientation of water molecules. Though we know they are present, this vital layer of information, which can inform a myriad of biological processes, is frustratingly invisible to us. The good news is that, even at modest resolution, neutron crystallography (NC) can reveal this layer and has emerged this century as a powerful tool to elucidate enzyme catalytic mechanisms. Due to its strong and coherent scattering of neutrons, incorporation of deuterium into the protein crystal amplifies the power of NC. This is especially true when solvation and the specific participation of key water molecules are crucial for catalysis. Neutron data allow the modeling of all three atoms in water molecules and have even revealed previously unobserved and unique species such as hydronium (D3O+) and deuteroxide (OD−) ions as well as lone deuterons (D+). Herein, we briefly review why neutrons are ideal probes for identifying catalytically important water molecules and these unique water-like species, limitations in interpretation, and four vignettes of enzyme success stories from disparate research groups. One of these groups was that of Dr. Chris G. Dealwis, who died unexpectedly in 2022. As a memorial appreciation of his scientific career, we will also highlight his interest and contributions to the neutron crystallography field. As both the authors were mentored by Chris, we feel we have a unique perspective on his love of molecular structure and admiration for neutrons as a tool to query those structures.
Putative Nociceptive Responses in a Decapod Crustacean: The Shore Crab (Carcinus maenas)
Authors: Kasiouras Eleftherios , Hubbard Peter C. , Gräns Albin , Sneddon Lynne U.
Published: October 2024

Nociceptors are receptors that detect injurious stimuli and are necessary to convey such information from the periphery to the central nervous system. While nociception has been extensively studied in various taxa, there is relatively little electrophysiological evidence for the existence of nociceptors in decapod crustaceans. This study investigated putative nociceptive responses in the shore crabs, specifically their response to mechanical and noxious chemical stimuli. Extracellular multi-unit electrophysiological recordings were conducted from the anterior ganglion and the circumesophageal connective ganglia to assess nociceptive responses. Soft tissues at the joints of the chelae, antennae, and walking legs were stimulated using acetic acid (noxious stimulus) and von Frey hairs (mechanical stimulus), while nearby ganglion activity was recorded. The results indicate the existence of nociceptors in the tested areas, with mechanical stimuli eliciting shorter, more intense neural activity compared with acetic acid. Although acetic acid triggered responses in all areas, the antennae and antennules did not respond to mechanical stimuli. Though we acknowledge the challenges of conducting in vivo electrophysiological recordings, future research should focus on further characterizing nociceptor activity because the results suggest the presence of nociceptors.
Targeting Sepsis: Disease Tolerance, Immune Resilience, and Compartmentalized Immunity
Authors: Garduno Alexis , Martín-Loeches Ignacio
Published: October 2024

Introduction: Sepsis remains a major contributor to critical care mortality and morbidity worldwide. Despite advances in understanding its complex immunopathology, the compartmentalized nature of immune responses across different organs has yet to be fully translated into targeted therapies. This review explores the burden of sepsis on organ-specific immune dysregulation, immune resilience, and epigenetic reprogramming, emphasizing translational challenges and opportunities. Methods: We implemented a systematic literature search strategy, incorporating data from studies published between 2010 and 2024, to evaluate the role of molecular profiling techniques, including transcriptomics and epigenetic markers, in assessing the feasibility of targeted therapies. Results: Sepsis-induced immune dysregulation manifests differently in various organs, with lung, heart, liver, and kidney responses driven by unique local immune environments. Organ-specific biomarkers, such as the Spns2/S1P axis in lung macrophages, mitochondrial dysfunction in the heart, proenkephalin for early acute kidney injury (AKI), and adrenomedullin for predicting multi-organ failure, offer promising avenues for timely intervention. Furthermore, immune resilience, particularly through regulatory T-cell modulation and cytokine targeting (e.g., IL-18), is crucial for long-term recovery. Epigenetic mechanisms, including histone modification and trained immunity, present opportunities for reprogramming immune responses but require more precision to avoid unintended inflammatory sequelae. Conclusions: A deeper understanding of compartmentalized immune responses and the dynamic immune landscape in sepsis is critical for developing precision therapies. Real-time immune monitoring and organ-targeted interventions could revolutionize sepsis management, although significant barriers remain in clinical translation. Further research is required to establish biomarkers and treatment timing that optimize therapeutic efficacy while minimizing systemic risks.
Comparative Analysis of Blood Transfusion Accuracy and Hemolysis Rate of Transfusion Cartridge Set Between Conventional Infusion Pumps and Cylinder-Type Infusion Pumps
Authors: Lee Hee-Young , Kim Sun-Ju , Lee Kang-Hyun , Park Il-Hwan , Jeon Hyeok-Jin , Youk Hyun
Published: October 2024

Background: Infusion pumps are critical in delivering fluids, including medications and blood products, in controlled amounts. However, conventional pumps can cause hemolysis and other issues such as flow variations and infection risks, especially during blood transfusions. To address these limitations, a novel cylinder-type infusion pump, the Anyfusion H-100, was developed, which includes a specialized blood transfusion cartridge set that combines syringe and peristaltic infusion methods. This study evaluates the accuracy and hemolysis rates of the Anyfusion H-100 compared to conventional pumps, aiming to confirm its viability as a safe and effective medical device for blood transfusions. Methods: This study evaluated six different infusion rates (10–180 cc/hr) and conducted 57 transfusion trials, 20 of which used a 1:1 blood–saline dilution. Blood transfusion accuracy was measured using research-grade packed red blood cells, and hemolysis rates were assessed before and after transfusion by chi-square tests and independent sample t-tests. Results: Anyfusion demonstrated an average transfusion error rate of 3.77%, compared to 4.00% for the Terufusion, with no statistically significant difference in hemolysis rates (p = 0.697). Bland–Altman plots confirmed their equivalent performance, with hemolysis rates of 0.566 ± 0.095% for Anyfusion and 0.518 ± 0.126% for Terufusion. Conclusions: Anyfusion provides an accurate and reliable blood transfusion performance comparable to that of Terufusion, with no significant difference in hemolysis rates; its integration of syringe and infusion methods shows a potential for safer and more efficient transfusion practices, especially in pediatric and emergency settings.
Hippocampal Leptin Resistance and Cognitive Decline: Mechanisms, Therapeutic Strategies and Clinical Implications
Authors: Valladolid-Acebes Ismael
Published: October 2024

Background: Leptin, an adipokine essential for regulating energy balance, exerts important effects on brain function, notably within the hippocampus, a region integral to learning and memory. Leptin resistance, characterized by diminished responsiveness to elevated leptin levels, disrupts hippocampal function and exacerbates both obesity and cognitive impairments. Scope: This review critically examines how leptin resistance impairs hippocampal synaptic plasticity processes, specifically affecting long-term potentiation (LTP) and long-term depression (LTD), which are crucial for cognitive performance. Findings: Recent research highlights that leptin resistance disrupts N-methyl-D-aspartate (NMDA) receptor dynamics and hippocampal structure, leading to deficits in spatial learning and memory. Additionally, high-fat diets (HFDs), which contribute to leptin resistance, further deteriorate hippocampal function. Potential therapeutic strategies, including leptin sensitizers, show promise in mitigating brain disorders associated with leptin resistance. Complementary interventions such as caloric restriction and physical exercise also enhance leptin sensitivity and offer potential benefits to alleviating cognitive impairments. Aims of the review: This review synthesizes recent findings on the molecular pathways underlying leptin resistance and its impact on synaptic transmission and plasticity in the hippocampus. By identifying potential therapeutic targets, this work aims to provide an integrated approach for addressing cognitive deficits in obesity, ultimately improving the quality of life for affected individuals.
The Influence of Maternal Lifestyle Factors on Human Breast Milk Microbial Composition: A Narrative Review
Authors: Bianco Irene , Ferrara Chiara , Romano Francesca , Loperfido Federica , Sottotetti Francesca , El Masri Dana , Vincenti Alessandra , Cena Hellas , De Giuseppe Rachele
Published: October 2024

Human breast milk (HBM) is considered the gold standard for infant nutrition due to its optimal nutrient profile and complex composition of cellular and non-cellular components. Breastfeeding positively influences the newborn’s gut microbiota and health, reducing the risk of conditions like gastrointestinal infections and chronic diseases (e.g., allergies, asthma, diabetes, and obesity). Research has revealed that HBM contains beneficial microbes that aid gut microbiota maturation through mechanisms like antimicrobial production and pathogen exclusion. The HBM microbiota composition can be affected by several factors, including gestational age, delivery mode, medical treatments, lactation stage, as well as maternal lifestyle habits (e.g., diet, physical activity, sleep quality, smoking, alcohol consumption, stress level). Particularly, lifestyle factors can play a significant role in shaping the HBM microbiota by directly modulating the microbial composition or influencing the maternal gut microbiota and influencing the HBM microbes through the enteromammary pathway. This narrative review of current findings summarized how maternal lifestyle influences HBM microbiota. While the influence of maternal diet on HBM microbiota is well-documented, indicating that dietary patterns, especially those rich in plant-based proteins and complex carbohydrates, can positively influence HBM microbiota, the impact of other lifestyle factors is poorly investigated. Maintaining a healthy lifestyle during pregnancy and breastfeeding is crucial for the health of both mother and baby. Understanding how maternal lifestyle factors influence microbial colonization of HBM, along with their interactions and impact, is key to developing new strategies that support the beneficial maturation of the infant’s gut microbiota.
Electrochemical Immunosensors on Laser-Induced Graphene Platforms for Monitoring of Anti-RBD Antibodies After SARS-CoV-2 Infection
Authors: Martins Beatriz R. , Andrade Cristhianne Molinero R. , Simão Guilherme F. , de Paula Martins Rhéltheer , de Faria Lucas V. , Matias Tiago A. , Júnior Virmondes Rodrigues , Munoz Rodrigo Alejandro Abarza , Alves Renata Pereira
Published: October 2024

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has posed a major challenge to global health. The development of fast, accurate, and accessible diagnostic methods is essential in controlling the disease and mitigating its impacts. In this context, electrochemical biosensors present themselves as promising tools for the efficient monitoring of SARS-CoV-2 infection. We have developed a highly specific biosensor for the detection of anti-SARS-CoV-2 antibodies in patient sera. The use of the RBD-S region as an antigen, although purified to minimize cross-linking, poses a specific challenge. The structural similarity between SARS-CoV-2 and other respiratory viruses, as well as the complexity of the serum matrix, hinders robust analytical strategies to ensure diagnostic accuracy. This work presents a novel immunosensor for COVID-19 diagnosis using laser-induced graphene (LIG) electrodes subjected to electrochemical reduction with graphene (named rGraphene-LIG). In the present study, we chose an initial approach focused on demonstrating the concept and evaluating the feasibility of the rGraphene-LIG sensor for SARS-CoV-2 detection. The rGraphene-LIG electrodes presented a notable current increase for the redox probe in the aqueous solution of a mixture of 5 mmol L−1 potassium ferricyanide/ferrocyanide ([Fe(CN)6]3−/[Fe(CN)6]4−) in 0.1 mol L−1 KCl (pH set at 7.4). As a proof of concept, the rGraphene-LIG electrode was applied for antibody determination in real samples using cyclic voltammetry, and a limit of detection (LOD) of 0.032 μg L−1 was achieved. When determining antigens in commercial samples, we obtained an LOD of 560 ηg mL−1 and a limit of quantification of 1677 ηg mL−1. The results of the electrochemical experiments were in accordance with the surface roughness obtained from atomic force microscopy images. Based on these results, the rGraphene-LIG electrode is shown to be an excellent platform for immunoglobulin detection when present in individuals after antigenic exposure caused by SARS-CoV-2.
The First N,O-Chelated Diphenylboron-Based Fluorescent Probe for Peroxynitrite and Its Bioimaging Applications
Authors: Ye Xiaoping , Li Longxuan , Liu Hong , Fang Yuyu , Liu Xiaoya
Published: October 2024

Peroxynitrite (ONOO−) is a reactive oxygen species (ROS) that takes part in the oxidation-reduction homeostasis while at the same time being responsible for activating numerous pathological pathways. Accordingly, monitoring the dynamic changes in ONOO− concentration has attracted a great deal of attention, undoubtedly prompting the development of appropriate fluorescent chemosensors. Herein, we developed a novel N,O-chelated diphenylboron-based fluorescent probe (DPB) for ONOO− featuring high selectivity, a quick response time (2.0 min), and a low detection limit (55 nM). DPB incorporates tetra-coordinated boron in the center of the fluorogenic core and a three-coordinated boron from the pinacolphenylboronate fragment, which acts as the recognition site for ONOO−. As confirmed by HR-MS and 1H NMR, the interaction of DPB with ONOO− led to an oxidative cleavage of pinacolphenylboronate moiety to produce strongly emissive derivative DPB-OH. The fluorescence enhancement is likely a result of a substantial deactivation of non-radiative decay due to the replacement of the bulky pinacolphenylboronate moiety with a compact hydroxyl group. Importantly, DPB probe exhibits negligible cytotoxicity and favorable biocompatibility allowing for an efficient tracking of ONOO− in living cells and zebrafish. Overall, the current study does not only represents the first N,O-chelated diphenylboron-based fluorescent probe for a specific analyte, but also serves as a guideline for designing more potent fluorescent probes based on the chemistry of boron chelates.
A Metal-Organic Framework-Based Colorimetric Sensor Array for Transcutaneous CO2 Monitoring via Lensless Imaging
Authors: Ahmed Syed Saad , Yu Jingjing , Ding Wei , Ghosh Sabyasachi , Brumels David , Tan Songxin , Jaishi Laxmi Raj , Amjad Amirhossein , Xian Xiaojun
Published: October 2024

Transcutaneous carbon dioxide (TcPCO2) monitoring provides a non-invasive alternative to measuring arterial carbon dioxide (PaCO2), making it valuable for various applications, such as sleep diagnostics and neonatal care. However, traditional transcutaneous monitors are bulky, expensive, and pose risks such as skin burns. To address these limitations, we have introduced a compact, cost-effective CMOS imager-based sensor for TcPCO2 detection by utilizing colorimetric reactions with metal–organic framework (MOF)-based nano-hybrid materials. The sensor, with a colorimetric sensing array fabricated on an ultrathin PDMS membrane and then adhered to the CMOS imager surface, can record real-time sensing data through image processing without the need for additional optical components, which significantly reduces the sensor’s size. Our system shows impressive sensitivity and selectivity, with a low detection limit of 26 ppm, a broad detection range of 0–2% CO2, and strong resistance to interference from common skin gases. Feasibility tests on human subjects demonstrate the potential of this MOF-CMOS imager-based colorimetric sensor for clinical applications. Additionally, its compact design and responsiveness make it suitable for sports and exercise settings, offering valuable insights into respiratory function and performance. The sensing system’s compact size, low cost, and reversible and highly sensitive TcPCO2 monitoring capability make it ideal for integration into wearable devices for remote health tracking.