Serum Metal Ion-Induced Cross-Linking of Photoelectrochemical Peptides and Circulating Proteins for Evaluating Cardiac Ischemia/Reperfusion

Sleep fragmentation exacerbates myocardial ischemia‒reperfusion injury by promoting copper overload in cardiomyocytes

Sleep disorders increase the risk and mortality of heart disease, but the brain-heart interaction has not yet been fully elucidated. Cuproptosis is a copper-dependent type of cell death activated by the excessive accumulation of intracellular copper. Here, we showed that 16 weeks of sleep fragmentation (SF) resulted in elevated copper levels in the male mouse heart and exacerbated myocardial ischemia-reperfusion injury with increased myocardial cuproptosis and apoptosis. Mechanistically, we found that SF promotes sympathetic overactivity, increases the germination of myocardial sympathetic nerve terminals, and increases the level of norepinephrine in cardiac tissue, thereby inhibits VPS35 expression and leads to impaired ATP7A related copper transport and copper overload in cardiomyocytes. Copper overload further leads to exacerbated cuproptosis and apoptosis, and these effects can be rescued by excision of the sympathetic nerve or administration of copper chelating agent. Our study elucidates one of the molecular mechanisms by which sleep disorders aggravate myocardial injury and suggests possible targets for intervention.

Cardiovascular diseases crossroads: cGAS-STING signaling and disease progression

It is now widely accepted that inflammation is critical in cardiovascular diseases (CVD). Here, studies are being conducted on how cyclic GMP-AMP synthase (cGAS), a component of innate immunity's DNA-sensing machinery, communicates with the STING receptor, which is involved in activating the immune system's antiviral response. Significantly, a growing body of research in recent years highlights the strong activation of the cGAS-STING signalling pathways in several cardiovascular diseases, such as myocardial infarction, heart failure, and myocarditis. This developing collection of research emphasises these pathways' crucial role in initiating and advancing cardiovascular disease. In this extensive narrative, we explore the role of the cGAS-STING pathway in the development of CVD. We elaborate on the basic mechanisms involved in the onset and progression of CVD. This review explores the most recent developments in the recognition and characterization of cGAS-STING pathway. Additionally, it considers the field's future prospects while examining how cGAS-STING pathway might be altered and its clinical applications for cardiovascular diseases.

Unlocking the future of brain research: MOFs, TMOs, and MOFs/TMOs for electrochemical NTMs detection and analysis

The central nervous system relies heavily on neurotransmitters (NTMs), and NTM imbalances have been linked to a wide range of neurological conditions. Thus, the development of reliable detection techniques is essential for advancing brain studies. This review offers a comprehensive analysis of metal-organic frameworks (MOFs), transition metal oxides (TMOs), and MOFs-derived TMOs (MOFs/TMOs) as materials for electrochemical (EC) sensors targeting the detection of key NTMs, specifically dopamine (DA), epinephrine (EP), and serotonin (SR). The unique properties and diverse families of MOFs and TMOs, along with their nanostructured hybrids, are discussed in the context of EC sensing. The review also addresses the challenges in detecting NTMs and proposes a systematic approach to tackle these obstacles. Despite the vast amount of research on MOFs and TMOs-based EC sensors for DA detection, the review highlights the gaps in the literature for MOFs/TMOs-based EC sensors specifically for EP and SR detection, as well as the limited research on microneedles (MNs)-based EC sensors modified with MOFs, TMOs, and MOFs/TMOs for NTMs detection. This review serves as a foundation to encourage researchers to further explore the potential applications of MOFs, TMOs, and MOFs/TMOs-based EC sensors in the context of neurological disorders and other health conditions related to NTMs imbalances.

Inflammatory Studies of Dehydroandrographolide: Isolation, Spectroscopy, Biological Activity, and Theoretical Modeling

Dehydroandrographolide (DA) was isolated and experimentally characterized utilizing FT-IR, UV-Vis, and NMR spectroscopy techniques along with detailed theoretical modelled at the DFT/B3LYP-D3BJ/6-311 + + G(d,p) level of theory. Substantially, molecular electronic property investigations in the gaseous phase alongside five different solvents (ethanol, methanol, water, acetonitrile and DMSO) were comprehensively reported and compared with the experimental results. The globally harmonized scale (GHS), which is used to identify and label chemicals, was also utilized to demonstrate that the lead compound predicted an LD50 of 1190 mg/kg. This finding implies that consumers can safely consume the lead molecule. Notable impacts on hepatotoxicity, cytotoxicity, mutagenicity, and carcinogenicity were likewise found to be minimal to nonexistent for the compound. Additionally, in order to account for the biological performance of the studied compound, in-silico molecular docking simulation analysis was examined against different anti-inflammatory target of enzymes (3PGH, 4COX, and 6COX). From the examination, it can be inferred that DA@3PGH, DA@4COX, and DA@6COX, respectively, showed significant negative binding affinities of -7.2 kcal/mol, -8.0 kcal/mol, and - 6.9 kcal/mol. Thus, the high mean binding affinity in contrast to conventional drugs further reinforces these results as an anti-inflammatory agent.

The Multifunctional TRPC6 Protein: Significance in the Field of Cardiovascular Studies

Cardiovascular disease is the leading cause of death, medical complications, and healthcare costs. Although recent advances have been in treating cardiovascular disorders linked with a reduced ejection fraction, acutely decompensate cardiac failure remains a significant medical problem. The transient receptor potential cation channel (TRPC6) family responds to neurohormonal and mechanical stress, playing critical roles in cardiovascular diseases. Therefore, TRP C6 channels have great promise as therapeutic targets. Numerous studies have investigated the roles of TRP C6 channels in pain neurons, highlighting their significance in cardiovascular research. The TRPC6 protein exhibits a broad distribution in various organs and tissues, including the brain, nerves, heart, blood vessels, lungs, kidneys, gastrointestinal tract, and other bodily structures. Its activation can be triggered by alterations in osmotic pressure, mechanical stimulation, and diacylglycerol. Consequently, TRPC6 plays a significant role in the pathophysiological mechanisms underlying diverse diseases within living organisms. A recent study has indicated a strong correlation between the disorder known as TRPC6 and the development of cardiovascular diseases. Consequently, investigations into the association between TRPC6 and cardiovascular diseases have gained significant attention in the scientific community. This review explores the most recent developments in the recognition and characterization of TRPC6. Additionally, it considers the field's prospects while examining how TRPC6 might be altered and its clinical applications.

MLP-RL-CRD: diagnosis of cardiovascular risk in athletes using a reinforcement learning-based multilayer perceptron

Objective.Pre-participation medical screening of athletes is necessary to pinpoint individuals susceptible to cardiovascular events.Approach.The article presents a reinforcement learning (RL)-based multilayer perceptron, termed MLP-RL-CRD, designed to detect cardiovascular risk among athletes. The model underwent training using a publicized dataset that included the anthropological measurements (such as height and weight) and biomedical metrics (covering blood pressure and pulse rate) of 26 002 athletes. To address the data imbalance, a novel RL-based technique was adopted. The problem was framed as a series of sequential decisions in which an agent classified a received instance and received a reward at each level. To resolve the insensitivity to the initialization of conventional gradient-based learning methods, a mutual learning-based artificial bee colony (ML-ABC) was proposed.Main Results.The model outcomes were validated against positive (P) and negative (N) ECG findings that had been labeled by experts to signify individuals 'at risk' and 'not at risk,' respectively. The MLP-RL-CRD approach achieves superior outcomes (F-measure 87.4%; geometric mean 89.6%) compared with other deep models and traditional machine learning techniques. Optimal values for crucial parameters, including the reward function, were identified for the model based on experiments on the study dataset. Ablation studies, which omitted elements of the suggested model, affirmed the autonomous, positive, stepwise influence of these components on performing the model.Significance.This study introduces a novel, effective method for early cardiovascular risk detection in athletes, merging reinforcement learning and multilayer perceptrons, advancing medical screening and predictive healthcare. The results could have far-reaching implications for athlete health management and the broader field of predictive healthcare analytics.

Development of a high-performance label-free electrochemical immunosensor for early cancer diagnosis using anti-CEA/Ag-MOF/GO/GCE nanocomposite

In order to detect carcinoembryonic antigen (CEA) as a tumor marker in lung cancer for early cancer diagnosis, this study aimed to develop a label-free electrochemical immunosensor based on the immobilization of an Anti-CEA antibody on a metal-organic framework (MOF)-graphene oxide nanocomposite modified glassy carbon electrode (Anti-CEA/Ag-MOF/GO/GCE). Ag-MOF/GO nanocomposite was prepared on the GCE surface using the ultrasonic irradiation method, and Anti-CEA antibody was subsequently immobilized on the surface. Analysis of the crystal structure and morphology of the modified electrode using FE-SEM and XRD revealed that the correct combination of GO nanosheets and Ag-MOF nanoparticles produced a high surface area to trap the antibodies. Electrochemical tests utilizing the CV and DPV methods revealed that the immunosensor's sensitivity, stability, and selectivity were improved by Anti-CEA/Ag-MOF/GO/GCE. Results showed that, with a detection limit of 0.005 ng/mL, the change in the reduction peak current was inversely correlated with the logarithm concentration of CEA in the range of 10-3 to 5000 ng/mL. The suggested CEA immunosensor's applicability in a human serum sample was investigated, and findings of analytical studies via standard addition technique for both ELISA and DPV assays revealed that significant agreement existed between the outcomes of the two assays. Additionally, the recoveries ranged from 99.00% to 99.25%, and all relative standard deviations (RSDs) for the sample detections were below 5.01%, indicating satisfactory accuracy in results measured with the proposed CEA immunosensor, indicating that the prepared CEA immunosensor in this study can be used in clinical applications and human fluids.

Green synthesis, characterisation and antibacterial activities of Strobilanthes crispus-mediated silver nanoparticles (SC-AGNPS) against selected bacteria

This study aims to characterize and determine the antibacterial activities of synthesized Strobilanthes crispus-mediated AgNPs (SC-AgNPs) against Streptococcus mutans, Escherichia coli and Pseudomonas aeruginosa. S. crispus water extract acts as a reducing and capping agent in the synthesis of AgNPs. The synthesized AgNPs were characterized by using UV-Vis spectrophotometer, dynamic light scattering (DLS), field emission scanning electron microscope (FESEM), X-ray diffractometer (XRD) and Fourier transform infra-red (FTIR). FESEM images showed a rough surface with a spherical shape. The average size distribution of 75.25 nm with a polydispersity index (PDI) of 0.373. XRD analysis matched the face-centred cubic structure of silver. FTIR analysis revealed a shifted peak from 1404.99 to 1345.00 cm-1. MIC and MBC values of SC-AgNPs were 1.25 mg/mL and 2.5 mg/mL against E. coli, P. aeruginosa and S. mutans, respectively. Time-kill assay showed that SC-AgNPs significantly reduced bacterial growth as compared to non-treated bacteria. Morphologies of bacteria treated with SC-AgNPs were shrunk, lysed, irregular and smaller as compared to control. SC-AgNPs significantly disrupted the gene expression of eae A, gtf B and Pel A (p < 0.05). This study indicated that the synthesized SC-AgNPs were stable with enhanced antibacterial activities.

Achieving enhanced sensitivity and accuracy in carcinoembryonic antigen (CEA) detection as an indicator of cancer monitoring using thionine/chitosan/graphene oxide nanocomposite-modified electrochemical immunosensor

The current study has focused on electrochemical immunosensing of carcinoembryonic antigen (CEA) employing an immobilized antibody on a thionine, chitosan, or graphene oxide nanocomposite modified glassy carbon electrode (anti-CEA/THi-CS-GO/GCE) as an indicator of cancer monitoring. THi-CS-GO nanocomposites were made using ultrasonication, and analyses of their morphology and crystal structure using SEM, FTIR, and XRD showed that thionine and chitosan molecules were intercalated with stacking interactions with both the top and bottom of GO nanosheets. Electrochemical experiments revealed anti-CEA, THi-CS-GO/GCE to have exceptional sensitivity and selectivity towards CEA compounds. The detection limit value was established to be 0.8 pg/mL when it was discovered that variations in the decrease peak current were directly proportional to the logarithm concentration of CEA over a wide range from 10-3 to 104 ng/mL. Results of testing the immunosensor's application capability for detecting CEA in a sample of human serum show that ELISA and DPV results are very congruent. The produced immunosensor demonstrated adequate immunosensor precision in determining CEA in prepared genuine samples of human serum and clinical applications.

Deeper insight into ferroptosis: association with Alzheimer's, Parkinson's disease, and brain tumors and their possible treatment by nanomaterials induced ferroptosis

Ferroptosis is an emerging and novel type of iron-dependent programmed cell death which is mainly caused by the excessive deposition of free intracellular iron in the brain cells. This deposited free iron exerts a ferroptosis pathway, resulting in lipid peroxidation (LiPr). There are mainly three ferroptosis pathways viz. iron metabolism-mediated cysteine/glutamate, and LiPr-mediated. Iron is required by the brain as a redox metal for several physiological activities. Due to the iron homeostasis balance disruption, the brain gets adversely affected which further causes neurodegenerative diseases (NDDs) like Parkinson's and Alzheimer's disease, strokes, and brain tumors like glioblastoma (GBS), and glioma. Nanotechnology has played an important role in the prevention and treatment of these NDDs. A synergistic effect of nanomaterials and ferroptosis could prove to be an effective and efficient approach in the field of nanomedicine. In the current review, the authors have highlighted all the latest research in the field of ferroptosis, specifically emphasizing on the role of major molecular key players and various mechanisms involved in the ferroptosis pathway. Moreover, here the authors have also addressed the correlation of ferroptosis with the pathophysiology of NDDs and theragnostic effect of ferroptosis and nanomaterials for the prevention and treatment of NDDs.

A DFT study on the probability of using the heteroatom decorated graphitic carbonitride (g-C3N4) species for delivering of three novel Multiple sclerosis drugs

In this project, the possibility of drug delivery application of three anti-Multiple sclerosis (MS) agents (containing diroximel fumarate (DXF), dimethyl fumarate (DMF), and mono methyl fumarate (MMF)) by using some heteroatom decorated graphitic carbonitride (g-C3N4) (as nano-sized carriers) have been systematically investigated. The results of the study have indicated that As-g-C3N4 QD is not a suitable candidate for drug delivery (at least in the cases of DMF, and DXF drugs); while, it would be an accurate semiconductor sensor for selective detection of each mentioned agents. Also, the use of the P-doped as well as pristine g-C3N4 QD could lead to weak electronic signals with relatively same values (in electronvolts). It means that P-g-C3N4, and g-C3N4 QDs are not good sensors for detection of each of the three considered drugs. However, those two sorbents would be suitable carriers for delivering of all three mentioned pharmaceuticals.

A novel ensemble approach for estimating the competency of bank telemarketing

Having a reliable understanding of bank telemarketing performance is of great importance in the modern world of economy. Recently, machine learning models have obtained high attention for this purpose. In order to introduce and evaluate cutting-edge models, this study develops sophisticated hybrid models for estimating the success rate of bank telemarketing. A large free dataset is used which lists the clients' information of a Portuguese bank. The data are analyzed by four artificial neural networks (ANNs) trained by metaheuristic algorithms, namely electromagnetic field optimization (EFO), future search algorithm (FSA), harmony search algorithm (HSA), and social ski-driver (SSD). The models predict the subscription of clients for a long-term deposit by evaluating nineteen conditioning parameters. The results first indicated the high potential of all four models in analyzing and predicting the subscription pattern, thereby, revealing the competency of neuro-metaheuristic hybrids. However, comparatively speaking, the EFO yielded the most reliable approximation with an area under the curve (AUC) around 0.80. FSA-ANN emerged as the second-accurate model followed by the SSD and HSA with respective AUCs of 0.7714, 0.7663, and 0.7160. Moreover, the superiority of the EFO-ANN is confirmed against several conventional models from the previous literature, and finally, it is introduced as an effective model to be practically used by banking institutions for predicting the likelihood of deposit subscriptions.

The role of toll-like receptors (TLRs) and their therapeutic applications in glomerulonephritis

One of the most important features of innate immunity is the presence of a special group of pattern recognition receptors (PRRs) called toll-like receptors (TLRs), which recognize pathogen-associated molecular patterns (PAMPs) and damage-associated molecular patterns (DAMPs), resulting in a quick and effective immune response to them. Glomerulonephritis (GN) is one of the most important categories of renal disorders characterized by destructive responses of the immune system to the glomerulus. To date, the association of TLRs as important innate immune system members with GN has been one of the topics that attracted the attention of researchers in this field. However, the exact role of these receptors in the immunopathogenesis of GN has not yet been fully discussed. Therefore, this study aims to overview the role of TLRs in GN and the possibility of using them as a potential therapeutic target.

A review on immunoglobulin Y (IgY) conjugated with metal nanoparticles and biomedical uses

Today, the use of nanoparticles has attracted considerable attention in biomedical investigations and applications. Antibody-nanoparticle conjugates have proven to be useful tools for raising accuracy and sensitivity in in vitro diagnostics. IgY antibodies have benefits over different antibodies in terms of minimizing animal harm, reducing reactivity with mammalian factors, and cost-effective extraction. Metal nanoparticles are widely used for various medical and biological applications and are potential candidates for identifying pathogens and treating them, which can be mostly related to their special properties, including their shape and size. Avian IgY antibodies conjugated with nanoparticles have been widely used for the detection of parasitic, viral, and bacterial infections as well as allergens and toxicological and pharmaceutical molecules. This review aimed to investigate avian antibodies conjugated with metal nanoparticles and their biological applications.

Cell-free therapy based on extracellular vesicles: a promising therapeutic strategy for peripheral nerve injury

Peripheral nerve injury (PNI) is one of the public health concerns that can result in a loss of sensory or motor function in the areas in which injured and non-injured nerves come together. Up until now, there has been no optimized therapy for complete nerve regeneration after PNI. Exosome-based therapies are an emerging and effective therapeutic strategy for promoting nerve regeneration and functional recovery. Exosomes, as natural extracellular vesicles, contain bioactive molecules for intracellular communications and nervous tissue function, which could overcome the challenges of cell-based therapies. Furthermore, the bioactivity and ability of exosomes to deliver various types of agents, such as proteins and microRNA, have made exosomes a potential approach for neurotherapeutics. However, the type of cell origin, dosage, and targeted delivery of exosomes still pose challenges for the clinical translation of exosome therapeutics. In this review, we have focused on Schwann cell and mesenchymal stem cell (MSC)-derived exosomes in nerve tissue regeneration. Also, we expressed the current understanding of MSC-derived exosomes related to nerve regeneration and provided insights for developing a cell-free MSC therapeutic strategy for nerve injury.

Molecularly imprinted polymer-based sensors for identification volatile compounds in pharmaceutical products: in silico rational design

The present study aimed to strategically design a Molecularly Imprinted Polymer (MIP) with selective extraction capabilities for volatile compounds found in pork. These specific volatile compounds, such as 3-methyl-1-butanol, 1-nonanal, octanal, hexanal, 2-pentyl-furan, 1-penten-3-one, N-morpholinomethyl-isopropyl-sulfide, methyl butyrate, and (E,E)-2,4-decadienal, are primarily responsible for the distinctive aroma and flavor characteristics associated with pork. Molecular dynamics simulations were employed to investigate the stability of the pre-polymerization system, simulating the interactions between the volatile compounds as templates, 4-hydroxyethyl methacrylate (HEMA) as monomers, and ethylene glycol dimethacrylate (EGDMA) as crosslinkers. Computational simulations revealed that the optimal mole ratio of 1:4:20 for templates, monomers, and crosslinkers resulted in the most favorable functional radial distribution and exhibited the strongest interactions. To validate the computational findings, additional analyses were performed utilizing Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA), radial distribution function (RDF), and hydrogen bond (HBond) occupancy. The calculated binding free energy demonstrated that all template molecules were capable to bind with both the monomers and crosslinkers, including 1-penten-3-one and N-morpholinomethyl-isopropyl-sulfide displaying the strongest interactions, with values of -12,674 kJ/mol and -11,646 kJ/mol, respectively. The congruence between the results obtained from the molecular simulation analyses highlights the crucial role of molecular dynamics simulations in the study and development of MIP for the analysis of marker compounds present in pork.Communicated by Ramaswamy H. Sarma.

Spectroscopic and molecular modeling studies of binding interaction between the new complex of yttrium and 1,10-phenanthroline derivatives with DNA and BSA

In this study, the 4,9 diazafluoren-9-one ligand and [Y(Daf)2Cl3.OH2] complex were synthesized. The interaction of this complex with DNA and bovine serum albumin (BSA) was investigated by UV-vis and fluorescence spectroscopy. The molecular docking method was used to confirm the experimental results, investigate the type of interaction, and determine the binding site. The binding constant and Stern-Volmer constant were calculated using spectroscopy techniques. The binding constant of the Y-complex with DNA and BSA obtained using the UV-vis technique was 1.61 × 105 M-1 and 0.49 × 105 M-1, while that obtained using the fluorescence method was 3.39 × 105 M-1 and 3.63 × 105 M-1, respectively. The results of experimental and theoretical data showed that the interaction between the yttrium complex and DNA and BSA is driven by the hydrogen bond and van der Waals interaction, respectively. The yttrium complex communicates with DNA via the groove interaction. This complex has high binding energy with bovine serum albumin. In addition, the molecular docking results showed that the complex binds to the IIA subdomain of BSA (site I). Finally, anticancer activity of the yttrium complex was studied on MCF-7 and A549 cell lines by using the MTT method. The IC50 values obtained showed that the yttrium complex possesses anticancer activity.

A Hybrid Model for Cardiac Perfusion: Coupling a Discrete Coronary Arterial Tree Model with a Continuous Porous-Media Flow Model of the Myocardium

This paper presents a novel hybrid approach for the computational modeling of cardiac perfusion, combining a discrete model of the coronary arterial tree with a continuous porous-media flow model of the myocardium. The constructive constrained optimization (CCO) algorithm captures the detailed topology and geometry of the coronary arterial tree network, while Poiseuille's law governs blood flow within this network. Contrast agent dynamics, crucial for cardiac MRI perfusion assessment, are modeled using reaction-advection-diffusion equations within the porous-media framework. The model incorporates fibrosis-contrast agent interactions and considers contrast agent recirculation to simulate myocardial infarction and Gadolinium-based late-enhancement MRI findings. Numerical experiments simulate various scenarios, including normal perfusion, endocardial ischemia resulting from stenosis, and myocardial infarction. The results demonstrate the model's efficacy in establishing the relationship between blood flow and stenosis in the coronary arterial tree and contrast agent dynamics and perfusion in the myocardial tissue. The hybrid model enables the integration of information from two different exams: computational fractional flow reserve (cFFR) measurements of the heart coronaries obtained from CT scans and heart perfusion and anatomy derived from MRI scans. The cFFR data can be integrated with the discrete arterial tree, while cardiac perfusion MRI data can be incorporated into the continuum part of the model. This integration enhances clinical understanding and treatment strategies for managing cardiovascular disease.

Synthesis of poly (L-cysteine)/g-C3N4 modified glassy carbon electrodes for electrochemical detection of methotrexate as a medicine for treatment of breast cancer in pharmaceutical fluid samples

Analyzing the levels of anticancer medications in biological samples and body fluids reveals important details on the course and effects of chemotherapy. p (L-Cys)/graphitic-carbon nitride (g-C₃N₄)/GCE, a modified glassy carbon electrode, was created for the current study's electrochemical detection of methotrexate (MTX), a drug used to treat breast cancer, in pharmaceutical fluid samples. l-Cysteine was electro-polymerized on the surface of the g-C₃N₄/GCE after the g-C₃N₄ was first modified to prepare the p (L-Cys)/g-C₃N₄/GCE. Analyses of morphology and structure showed that well-crystalline p (L-Cys) on g-C₃N₄/GCE was successfully electropolymerized. Studying the electrochemical characteristics of p (L-Cys)/g-C₃N₄/GCE using CV and DPV techniques revealed a synergistic impact between g-C₃N₄ and l-cysteine that improved the stability and selectivity of the electrochemical oxidation of MTX while enhancing the electrochemical signal. Results showed that 7.5-780 μM was the linear range, and that 0.11841 μA/μM and 6 nM, respectively, were the sensitivity and limit of detection. The applicability of the suggested sensors was assessed using real pharmaceutical preparations, and the results showed that p (L-Cys)/g-C₃N₄/GCE had a high degree of precision. Five breast cancer patients who volunteered and provided prepared blood serum samples between the ages of 35 and 50 were used to examine the validity and accuracy of the proposed sensor in the current work for the determination of MTX. The results showed good recovery values (greater than 97.20%), appropriate accuracy (RSD less than 5.11%), and good agreement between the ELISA and DPV analysis results. These findings showed that p (L-Cys)/g-C₃N₄/GCE can be applied as a trustworthy MTX sensor for MTX level monitoring in blood samples and pharmaceutical samples.

A normalized differential sequence feature encoding method based on amino acid sequences

Protein interactions are the foundation of all metabolic activities of cells, such as apoptosis, the immune response, and metabolic pathways. In order to optimize the performance of protein interaction prediction, a coding method based on normalized difference sequence characteristics (NDSF) of amino acid sequences is proposed. By using the positional relationships between amino acids in the sequences and the correlation characteristics between sequence pairs, NDSF is jointly encoded. Using principal component analysis (PCA) and local linear embedding (LLE) dimensionality reduction methods, the coded 174-dimensional human protein sequence vector is extracted using sequence features. This study compares the classification performance of four ensemble learning methods (AdaBoost, Extra trees, LightGBM, XGBoost) applied to PCA and LLE features. Cross-validation and grid search methods are used to find the best combination of parameters. The results show that the accuracy of NDSF is generally higher than that of the sequence matrix-based coding method (MOS) coding method, and the loss and coding time can be greatly reduced. The bar chart of feature extraction shows that the classification accuracy is significantly higher when using the linear dimensionality reduction method, PCA, compared to the nonlinear dimensionality reduction method, LLE. After classification with XGBoost, the model accuracy reaches 99.2%, which provides the best performance among all models. This study suggests that NDSF combined with PCA and XGBoost may be an effective strategy for classifying different human protein interactions.

Investigation of structural, electronic, mechanical, & optical characteristics of Ra based-cubic hydrides RbRaX3 (X= F and cl) perovskite materials for solar cell applications: First principle study

Perovskite materials are considered the gateway of various physical applications to meet the production and consumption of energy and medical fields. Density Functional Theory (DFT) becomes the most important field in the modern era to investigate perovskite materials for various physical properties. DFT nowadays is used to explore the perovskite materials for a lot of applications like photocatalytic, optoelectronic, and photovoltaics. We discussed radium based cubic hydrides RbRaX3 (while X = F & Cl) perovskite material's electrical, optical, elastic, & physical characteristics with the help of DFT-based CASTEP code with PBE exchange-correlation efficient of GGA. The RbRaF3 & RbRaCl3 have three-dimensional nature by means of space group 221 (Pm3 m). According to electronic characteristics, the direct bandgap of RbRaF3 RbRaCl3 are 3.18eV and 2.209eV, respectively. Both compounds are brittle in nature via Poisson's ratio & Pugh's criteria. Thus, our novel RbRaX3 (X = F and Cl) compounds have excellent applications for solar cell and medical areas.

Co-administration of exercise training and melatonin on the function of diabetic heart tissue: a systematic review and meta-analysis of rodent models

PURPOSE

Diabetes mellitus (DM), a hyperglycemic condition, occurs due to the failure of insulin secretion and resistance. This study investigated the combined effects of exercise training and melatonin (Mel) on the function of heart tissue in diabetic rodent models.

METHODS

A systematic search was conducted in Embase, ProQuest, Cochrane library, Clinicaltrial.gov, WHO, Google Scholar, PubMed, Ovid, Scopus, Web of Science, Ongoing Trials Registers, and Conference Proceedings in July 2022 with no limit of date or language. All trials associated with the effect of Mel and exercise in diabetic rodent models were included. Of the 962 relevant publications, 58 studies met our inclusion criteria as follows; Mel and type 1 DM (16 studies), Mel and type 2 DM (6 studies), exercise and type 1 DM (24 studies), and exercise and type 2 DM (12 studies). Meta-analysis of the data was done using the Mantel Haenszel method.

RESULTS

In most of these studies, antioxidant status and oxidative stress, inflammatory response, apoptosis rate, lipid profiles, and glucose levels were monitored in diabetic heart tissue. According to our findings, both Mel and exercise can improve antioxidant capacity by activating antioxidant enzymes compared to the control diabetic groups (p < 0.05). The levels of pro-inflammatory cytokines, especially TNF-α were reduced in diabetic rodents after being treated with Mel and exercise. Apoptotic changes were diminished in diabetic rodents subjected to the Mel regime and exercise in which p53 levels and the activity of Caspases reached near normal levels (p < 0.05). Based on the data, both Mel and exercise can change the lipid profile in diabetic rodents, especially rats, and close it to near-to-control levels.

CONCLUSION

These data showed that exercise and Mel can reduce the harmful effects of diabetic conditions on the heart through the regulation of lipid profile, antioxidant capacity, apoptosis, and inflammation.

Platelet-derived microvesicles (PMVs) in cancer progression and clinical applications

Platelet-derived microvesicles (PMVs), the microvesicles with the highest concentration in the bloodstream, play a key role in the regulation of hemostasis, inflammation, and angiogenesis. PMVs have recently been identified as key factors in the link between platelets and cancer. PMVs bind to both cancer cells and nontransformed cells in the microenvironment of the tumor, and then transfer platelet-derived contents to the target cell. These contents have the potential to either stimulate or modulate the target cell's response. PMVs are encased in a lipid bilayer that contains surface proteins and lipids as well as components found inside the PMV. Each of these components participates in known and potential PMV roles in cancer. The complicated roles played by PMVs in the onset, development, and progression of cancer and cancer-related comorbidities are summarized in this study.

Influence of stent-induced vessel deformation on hemodynamic feature of bloodstream inside ICA aneurysms

One of the effective treatment options for intracranial aneurysms is stent-assisted coiling. Though, previous works have demonstrated that stent usage would result in the deformation of the local vasculature. The effect of simple stent on the blood hemodynamics is still uncertain. In this work, hemodynamic features of the blood stream on four different ICA aneurysm with/without interventional are investigated. To estimate the relative impacts of vessel deformation, four distinctive ICA aneurysm is simulated by the one-way FSI technique. Four hemodynamic factors of aneurysm blood velocity, wall pressure and WSS are compared in the peak systolic stage to disclose the impact of defamation by the stent in two conditions. The stent usage would decrease almost all of the mentioned parameters, except for OSI. Stenting reduces neck inflow rate, while the effect of interventional was not consistent among the aneurysms. The deformation of an aneurysm has a strong influence on the hemodynamics of an aneurysm. This outcome is ignored by most of the preceding investigations, which focused on the pre-interventional state for studying the relationship between hemodynamics and stents. Present results show that the application of stent without coiling would improve most hemodynamic factors, especially when the deformation of the aneurysm is high enough.

Effects of coiling embolism on blood hemodynamic of the MCA aneurysm: a numerical study

One of common endovascular technique for treatment of MCA aneurysm is using coiling gel for limiting of blood stream. In this work, computational fluid dynamic is used for the simulation of the blood hemodynamic inside MCA in existence of coiling gel. This work has tried to visualize the impacts of blood characteristics i.e. hematocrit as a protein related factor on efficiency of coiling fiber inside the aneurysm. Tufts of polyester fibers may be attached to the coil to support thrombosis and platelet aggregation. Blood rheology analysis is done by solving RANS equations and it is assumed that blood stream is non-Newtonian with fluid-solid interaction. OSI and WSS are compared on sac surface area for different stages of blood cycle. Achieved results confirm that the coiling gel substantially decreases the blood circulation inside the aneurysm sac. It is also found that the influence of blood hematocrit decreases when the MCA aneurysm is filled by the coiling gel.

Influence of the coiling porosity on the risk reduction of the cerebral aneurysm rupture: computational study

The formation and progress of cerebral aneurysm is highly associated with hemodynamic factors and blood flow feature. In this study, comprehensive efforts are done to investigate the blood hemodynamic effects on the creation and growth of the Internal Carotid Artery. The computational fluid dynamic method is used for the visualization of the bloodstream inside the aneurysm. Transitional, non-Newtonian and incompressible conditions are considered for solving the Navier-Stokes equation to achieve the high-risk region on the aneurysm wall. OSI and WSS of the aneurysm wall are compared within different blood flow stages. The effects of blood viscosity and coiling treatment on these factors are presented in this work. Our study shows that in male patients (HCT = 0.45), changing the porosity of coiling from 0.89 with 0.79 would decreases maximum OSI up to 75% (in maximum acceleration). However, this effect is limited to about 45% for female patients (HCT = 0.35).

The neuroprotective effects of fisetin, a natural flavonoid in neurodegenerative diseases: Focus on the role of oxidative stress

Oxidative stress (OS) disrupts the chemical integrity of macromolecules and increases the risk of neurodegenerative diseases. Fisetin is a flavonoid that exhibits potent antioxidant properties and protects the cells against OS. We have viewed the NCBI database, PubMed, Science Direct (Elsevier), Springer-Nature, ResearchGate, and Google Scholar databases to search and collect relevant articles during the preparation of this review. The search keywords are OS, neurodegenerative diseases, fisetin, etc. High level of ROS in the brain tissue decreases ATP levels, and mitochondrial membrane potential and induces lipid peroxidation, chronic inflammation, DNA damage, and apoptosis. The subsequent results are various neuronal diseases. Fisetin is a polyphenolic compound, commonly present in dietary ingredients. The antioxidant properties of this flavonoid diminish oxidative stress, ROS production, neurotoxicity, neuro-inflammation, and neurological disorders. Moreover, it maintains the redox profiles, and mitochondrial functions and inhibits NO production. At the molecular level, fisetin regulates the activity of PI3K/Akt, Nrf2, NF-κB, protein kinase C, and MAPK pathways to prevent OS, inflammatory response, and cytotoxicity. The antioxidant properties of fisetin protect the neural cells from inflammation and apoptotic degeneration. Thus, it can be used in the prevention of neurodegenerative disorders.