Green synthesized silver nanoparticles of Terminalia bellirica leaves extract: synthesis, characterization, in-silico studies, and antimalarial activity.

Malaria is a mosquito-borne infectious disease that is caused by the Plasmodium parasite. Most of the available medication are losing their efficacy. Therefore, it is crucial to create fresh leads to combat malaria. Green silver nanoparticles (AgNPs) have recently attracted a lot of attention in biomedical research. As a result, green mediated AgNPs from leaves of Terminalia bellirica, a medicinal plant with purported antimalarial effects, were used in this investigation. Initially, cysteine-rich proteins from Plasmodium species were studied in silico as potential therapeutic targets. With docking scores between -9.93 and -11.25 kcal/mol, four leaf constituents of Terminalia bellirica were identified. The green mediated silver nanoparticles were afterward produced using leaf extract and were further examined using UV-vis spectrophotometer, DLS, Zeta potential, FTIR, XRD, and FESEM. The size of synthesized TBL-AgNPs was validated by the FESEM results; the average size of TBL-AgNPs was around 44.05 nm. The zeta potential study also supported green mediated AgNPs stability. Additionally, Plasmodium falciparum (3D7) cultures were used to assess the antimalarial efficacy, and green mediated AgNPs could effectively inhibit the parasitized red blood cells (pRBCs). In conclusion, this novel class of AgNPs may be used as a potential therapeutic replacement for the treatment of malaria.

Exploring progress in iron supplement formulation approaches for treating iron deficiency anemia through bibliometric and thematic analysis.

Anemia is a severe health issue that affects around one-third of the global population. Therefore, the present study aims to conduct a bibliometric analysis to investigate the research trends regarding advancements on iron formulations in treating iron deficiency anemia via oral or parenteral route. This study adopts thematic and bibliometric methods on existing research on novel iron formulations. It also provides perspective into the existing understanding on treatment strategies for iron deficiency anemia. This study is conducted on 543 papers on various ferrous and ferric formulations used in the treatment of iron deficiency anemia. The study period is from 1977 to 2022, and the papers are identified from the Scopus database. The bibliometric analysis was carried out using the R tool's Bibliometrix package. The study discusses performance analysis, including annual publications, geographic analysis, relevant affiliations, journal analysis, and citation analysis. In addition, the conceptual structure, including the co-occurrence network, thematic map, thematic evolution, intellectual structure highlighting co-citation analysis, and social structure depicting the collaboration network and collaboration world map, are presented. The results showed increased research on formulation strategies for the treatment of iron deficiency anemia from 2010 onwards. The top 5 contributing countries are the USA, Italy, India, Germany, and the UK, and peer-reviewed journals from the area of nutrition. The most trending areas of study are iron deficiency anemia in pregnancy, chronic kidney diseases, inflammatory bowel diseases, and various intravenous formulations used in its treatment. The authors from Europe collaborate the most with authors from other countries. The study concludes that a safer and more effective iron formulation is needed to reduce the prevalence of anemia. The findings of the study are helpful in advancing research on innovative formulations for treating iron deficiency anemia. The insights from the study are helpful to policymakers in designing specific health policies and investing more in research and development of novel formulations for the treatment of iron deficiency anemia.

Formulation and application of poly lactic acid, gum, and cellulose-based ternary bioplastic for smart food packaging: A review.

In future, global demand for low-cost-sustainable materials possessing good strength is going to increase tremendously, to replace synthetic plastic materials, thus motivating scientists towards green composites. The PLA has been the most promising sustainable bio composites, due to its inherent antibacterial property, biodegradability, eco-friendliness, and good thermal and mechanical characteristics. However, PLA has certain demerits such as poor water and gas barrier properties, and low glass transition temperature, which restricts its use in food packaging applications. To overcome this, PLA is blended with polysaccharides such as gum and cellulose to enhance the water barrier, thermal, crystallization, degradability, and mechanical properties. Moreover, the addition of these polysaccharides not only reduces the production cost but also helps in manufacturing packaging material with superior quality. Hence this review focuses on various fabrication techniques, degradation of the ternary composite, and its application in the food sector. Moreover, this review discusses the enhanced barrier and mechanical properties of the ternary blend packaging material. Incorporation of gum enhanced flexibility, while the reinforcement of cellulose improved the structural integrity of the ternary composite. The unique properties of this ternary composite make it suitable for extending the shelf life of food packaging, specifically for fruits, vegetables, and fried products. Future studies must be conducted to investigate the optimization of formulations for specific food types, explore scalability for industrial applications, and integrate these composites with emerging technologies (3D/4D printing).

Mechanistic QSAR modeling derived virtual screening, drug repurposing, ADMET and in-vitro evaluation to identify anticancer lead as lysine-specific demethylase 5a inhibitor.

A lysine-specific demethylase is an enzyme that selectively eliminates methyl groups from lysine residues. KDM5A, also known as JARID1A or RBP2, belongs to the KDM5 Jumonji histone demethylase subfamily. To identify novel molecules that interact with the LSD5A receptor, we created a quantitative structure-activity relationship (QSAR) model. A group of 435 compounds was used in a study of the quantitative relationship between structure and activity to guess the IC50 values for blocking LASD5A. We used a genetic algorithm-multilinear regression-based quantitative structure-activity connection model to forecast the bioactivity (PIC50) of 1615 food and drug administration pharmaceuticals from the zinc database with the goal of repurposing clinically used medications. We used molecular docking, molecular dynamic simulation modelling, and molecular mechanics generalised surface area analysis to investigate the molecule's binding mechanism. A genetic algorithm and multi-linear regression method were used to make six variable-based quantitative structure-activity relationship models that worked well (R2 = 0.8521, Q2LOO = 0.8438, and Q2LMO = 0.8414). ZINC000000538621 was found to be a new hit against LSD5A after a quantitative structure-activity relationship-based virtual screening of 1615 zinc food and drug administration compounds. The docking analysis revealed that the hit molecule 11 in the KDM5A binding pocket adopted a conformation similar to the pdb-6bh1 ligand (docking score: -8.61 kcal/mol). The results from molecular docking and the quantitative structure-activity relationship were complementary and consistent. The most active lead molecule 11, which has shown encouraging results, has good absorption, distribution, metabolism, and excretion (ADME) properties, and its toxicity has been shown to be minimal. In addition, the MTT assay of ZINC000000538621 with MCF-7 cell lines backs up the in silico studies. We used molecular mechanics generalise borne surface area analysis and a 200-ns molecular dynamics simulation to find structural motifs for KDM5A enzyme interactions. Thus, our strategy will likely expand food and drug administration molecule repurposing research to find better anticancer drugs and therapies.Communicated by Ramaswamy H. Sarma.

Application of in-silico drug discovery techniques to discover a novel hit for target-specific inhibition of SARS-CoV-2 Mpro's revealed allosteric binding with MAO-B receptor: A theoretical study to find a cure for post-covid neurological disorder.

Several studies have revealed that SARS-CoV-2 damages brain function and produces significant neurological disability. The SARS-CoV-2 coronavirus, which causes COVID-19, may infect the heart, kidneys, and brain. Recent research suggests that monoamine oxidase B (MAO-B) may be involved in metabolomics variations in delirium-prone individuals and severe SARS-CoV-2 infection. In light of this situation, we have employed a variety of computational to develop suitable QSAR model using PyDescriptor and genetic algorithm-multilinear regression (GA-MLR) models (R2 = 0.800-793, Q2LOO = 0.734-0.727, and so on) on the data set of 106 molecules whose anti-SARS-CoV-2 activity was empirically determined. QSAR models generated follow OECD standards and are predictive. QSAR model descriptors were also observed in x-ray-resolved structures. After developing a QSAR model, we did a QSAR-based virtual screening on an in-house database of 200 compounds and found a potential hit molecule. The new hit's docking score (-8.208 kcal/mol) and PIC50 (7.85 M) demonstrated a significant affinity for SARS-CoV-2's main protease. Based on post-covid neurodegenerative episodes in Alzheimer's and Parkinson's-like disorders and MAO-B's role in neurodegeneration, the initially disclosed hit for the SARS-CoV-2 main protease was repurposed against the MAO-B receptor using receptor-based molecular docking, which yielded a docking score of -12.0 kcal/mol. This shows that the compound that inhibits SARS-CoV-2's primary protease may bind allosterically to the MAO-B receptor. We then did molecular dynamic simulations and MMGBSA tests to confirm molecular docking analyses and quantify binding free energy. The drug-receptor complex was stable during the 150-ns MD simulation. The first computational effort to show in-silico inhibition of SARS-CoV-2 Mpro and allosteric interaction of novel inhibitors with MAO-B in post-covid neurodegenerative symptoms and other disorders. The current study seeks a novel compound that inhibits SAR's COV-2 Mpro and perhaps binds MAO-B allosterically. Thus, this study will enable scientists design a new SARS-CoV-2 Mpro that inhibits the MAO-B receptor to treat post-covid neurological illness.

Neuroprotective potential of Afzelin: A novel approach for alleviating catalepsy and modulating Bcl-2 expression in Parkinson's disease therapy.

The lost dopaminergic neurons in the brain prevent mobility in Parkinson's disease (PD). It is impossible to stop the disease's progress by means of symptoms management. Research focuses on oxidative stress, mitochondrial dysfunction, and neuronal degeneration. Exploration of potential neuroprotective drugs against prosurvival B-cell lymphoma 2 (Bcl-2) protein is ongoing. An investigable cause behind PD, as well as preventive measures, could be discovered considering the association between such behavioural manifestations (cataleptic behaviours) and PD. The compound Afzelin, known to guard the nervous system, was chosen for this study. The study was done on rats divided into six different groups. First, there was a control group. The other group was treated with Reserpine (RES) (1 mg/kg). The third group received RES (1 mg/kg) and levodopa (30 mg/kg). The remaining three groups were given RES (1 mg/kg) in conjunction with Afzelin at the following doses: 5 mg/kg, 10 mg/kg, and 20 mg/kg. Cataleptic behavior and mobility in rats was assessed using the rotarod, open field, and modified forced-swim tests. thiobarbituric acid reactive substances (TBARS), nitric oxide (NO), biogenic amines, and Bcl-2 level in rat tissue homogenates were considered. According to the study's findings, the rats treated through co-administration of RES and Afzelin improved significantly in their cataleptic behaviours and locomotor activity. In addition, administering Afzelin itself caused Bcl-2 expression, which could have some neuroprotection properties. This study provides meaningful information on the effectiveness of Afzelin in handling catalepsy and other degenerative neurologic disorders. As a result, other studies need to be conducted to establish the reasons behind the reactions and determine the long-term effects of Afzelin on these conditions.

QSAR modeling approaches to identify a novel ACE2 inhibitor that selectively bind with the C and N terminals of the ectodomain.

Due to the high rates of drug development failure and the massive expenses associated with drug discovery, repurposing existing drugs has become more popular. As a result, we have used QSAR modelling on a large and varied dataset of 657 compounds in an effort to discover both explicit and subtle structural features requisite for ACE2 inhibitory activity, with the goal of identifying novel hit molecules. The QSAR modelling yielded a statistically robust QSAR model with high predictivity (R2tr=0.84, R2ex=0.79), previously undisclosed features, and novel mechanistic interpretations. The developed QSAR model predicted the ACE2 inhibitory activity (PIC50) of 1615 ZINC FDA compounds. This led to the detection of a PIC50 of 8.604 M for the hit molecule (ZINC000027990463). The hit molecule's docking score is -9.67 kcal/mol (RMSD 1.4). The hit molecule revealed 25 interactions with the residue ASP40, which defines the N and C termini of the ectodomain of ACE2. The HIT molecule conducted more than thirty contacts with water molecules and exhibited polar interaction with the ARG522 residue coupled with the second chloride ion, which is 10.4 nm away from the zinc ion. Both molecular docking and QSAR produced comparable findings. Moreover, MD simulation and MMGBSA studies verified docking analysis. The MD simulation showed that the hit molecule-ACE2 receptor complex is stable for 400 ns, suggesting that repurposed hit molecule 3 is a viable ACE2 inhibitor.

Multifunctional role of nanoparticles for the diagnosis and therapeutics of cardiovascular diseases.

The increasing burden of cardiovascular disease (CVD) remains responsible for morbidity and mortality worldwide; their effective diagnostic or treatment methods are of great interest to researchers. The use of NPs and nanocarriers in cardiology has drawn much interest. The present comprehensive review provides deep insights into the use of current and innovative approaches in CVD diagnostics to offer practical ways to utilize nanotechnological interventions and the critical elements in the CVD diagnosis, associated risk factors, and management strategies of patients with chronic CVDs. We proposed a decision tree-based solution by discussing the emerging applications of NPs for the higher number of rules to increase efficiency in treating CVDs. This review-based study explores the screening methods, tests, and toxicity to provide a unique way of creating a multi-parametric feature that includes cutting-edge techniques for identifying cardiovascular problems and their treatments. We discussed the benefits and drawbacks of various NPs in the context of cost, space, time and complexity that have been previously suggested in the literature for the diagnosis of CVDs risk factors. Also, we highlighted the advances in using NPs for targeted and improved drug delivery and discussed the evolution toward the nano-cardiovascular potential for medical science. Finally, we also examined the mixed-based diagnostic approaches crucial for treating cardiovascular disorders, broad applications and the potential future applications of nanotechnology in medical sciences.

Understanding the Therapeutic Approaches for Neuroprotection.

The term "neurodegenerative disorders" refers to a group of illnesses in which deterioration of nerve structure and function is a prominent feature. Cognitive capacities such as memory and decision-making deteriorate as a result of neuronal damage. The primary difficulty that remains is safeguarding neurons since they do not proliferate or regenerate spontaneously and are therefore not substituted by the body after they have been damaged. Millions of individuals throughout the world suffer from neurodegenerative diseases. Various pathways lead to neurodegeneration, including endoplasmic reticulum stress, calcium ion overload, mitochondrial dysfunction, reactive oxygen species generation, and apoptosis. Although different treatments and therapies are available for neuroprotection after a brain injury or damage, the obstacles are inextricably connected. Several studies have revealed the pathogenic effects of hypothermia, different breathed gases, stem cell treatments, mitochondrial transplantation, multi-pharmacological therapy, and other therapies that have improved neurological recovery and survival outcomes after brain damage. The present review highlights the use of therapeutic approaches that can be targeted to develop and understand significant therapies for treating neurodegenerative diseases.

A drug design strategy based on molecular docking and molecular dynamics simulations applied to development of inhibitor against triple-negative breast cancer by Scutellarein derivatives.

Triple-negative breast cancer (TNBC), accounting for 10-15% of all breast malignancies, is more prevalent in women under 40, particularly in those of African descent or carrying the BRCA1 mutation. TNBC is characterized by the absence of estrogen and progesterone receptors (ER, PR) and low or elevated HER2 expression. It represents a particularly aggressive form of breast cancer with limited therapeutic options and a poorer prognosis. In our study, we utilized the protein of TNBC collected from the Protein Data Bank (PDB) with the most stable configuration. We selected Scutellarein, a bioactive molecule renowned for its anti-cancer properties, and used its derivatives to design potential anti-cancer drugs employing computational tools. We applied and modified structural activity relationship methods to these derivatives and evaluated the probability of active (Pa) and inactive (Pi) outcomes using pass prediction scores. Furthermore, we employed in-silico approaches such as the assessment of absorption, distribution, metabolism, excretion, and toxicity (ADMET) parameters, and quantum calculations through density functional theory (DFT). Within the DFT calculations, we analyzed Frontier Molecular Orbitals, specifically the Highest Occupied Molecular Orbital (HOMO) and Lowest Unoccupied Molecular Orbital (LUMO). We then conducted molecular docking and dynamics against TNBC to ascertain binding affinity and stability. Our findings indicated that Scutellarein derivatives, specifically DM03 with a binding energy of -10.7 kcal/mol and DM04 with -11.0 kcal/mol, exhibited the maximum binding tendency against Human CK2 alpha kinase (PDB ID 7L1X). Molecular dynamic simulations were performed for 100 ns, and stability was assessed using root-mean-square deviation (RMSD) and root-mean-square fluctuation (RMSF) parameters, suggesting significant stability for our chosen compounds. Furthermore, these molecules met the pharmacokinetics requirements for potential therapeutic candidates, displaying non-carcinogenicity, minimal aquatic and non-aquatic toxicity, and greater aqueous solubility. Collectively, our computational data suggest that Scutellarein derivatives may serve as potential therapeutic agents for TNBC. However, further experimental investigations are needed to validate these findings.

Understanding the mechanistic pathways and clinical aspects associated with protein and gene based biomarkers in breast cancer.

Cancer is one of the most widespread and severe diseases with a huge mortality rate. In recent years, the second-leading mortality rate of any cancer globally has been breast cancer, which is one of the most common and deadly cancers found in women. Detecting breast cancer in its initial stages simplifies treatment, decreases death risk, and recovers survival rates for patients. The death rate for breast cancer has risen to 0.024 % in some regions. Sensitive and accurate technologies are required for the preclinical detection of BC at an initial stage. Biomarkers play a very crucial role in the early identification as well as diagnosis of women with breast cancer. Currently, a wide variety of cancer biomarkers have been discovered for the diagnosis of cancer. For the identification of these biomarkers from serum or other body fluids at physiological amounts, many detection methods have been developed. In the case of breast cancer, biomarkers are especially helpful in discovering those who are more likely to develop the disease, determining prognosis at the time of initial diagnosis and choosing the best systemic therapy. In this study we have compiled various clinical aspects and signaling pathways associated with protein-based biomarkers and gene-based biomarkers.

Curcuminoids as cell signaling pathway modulators: A potential strategy for cancer prevention.

Despite substantial advancements in curative modern medicine in the last few decades, cancer risk and casualty rates have continued to mount globally. The exact reason for cancer's onset and progression is still unknown. However, skeletal and functional abnormalities in the genetic code are assumed to be the primary cause of cancer. Many lines of evidences reported that some medicinal plants can be utilized to curb cancer cell proliferation with a safe, fruitful, and cost-efficient perspective. Curcuminoids, isolated from Curcuma longa, have gotten a lot of focus due to their anticancer potential as they reduce tumor progression, invasion, and dissemination. Further, they modulated signal transduction routes like MAPK, PI3K/Akt/mTOR, JAK/STAT, and Wnt/ß-catenin, etc., and triggered apoptosis as well as actuated autophagy in malignant cells without altering the normal cells, thus preventing cancer progression. Besides, Curcuminoids also regulate the function and expression of anti-tumor and carcinogenic miRNAs. Clinical studies also reported the therapeutic effect of Curcuminoids against various cancer through decreasing specific biomarkers like TNF-α, Bcl-2, COX-2, PGE2, VEGF, IκKß, and various cytokines like IL-12p70, IL-10, IL-2, IFN-γ levels and increasing in p53 and Bax levels. Thus, in the present review, we abridged the modulation of several signal transduction routes by Curcuminoids in various malignancies, and its modulatory role in the initiation of tumor-suppressive miRNAs and suppression of the oncogenic miRNAs are explored. Additionally, various pharmacokinetic approaches have been projected to address the Curcuminoids bioavailability like the use of piperine as an adjuvant; nanotechnology-based Curcuminoids preparations utilizing Curcuminoids analogues are also discussed.

Inhibition of Autophagy and the Cytoprotective Role of Smac Mimetic against ROS-Induced Cancer: A Potential Therapeutic Strategy in Relapse and Chemoresistance Cases in Breast Cancer.

With more than a million deaths each year, breast cancer is the top cause of death in women. Around 70% of breast cancers are hormonally responsive. Although several therapeutic options exist, cancer resistance and recurrence render them inefficient and insufficient. The major key reason behind this is the failure in the regulation of the cell death mechanism. In addition, ROS was also found to play a major role in this problem. The therapeutic benefits of Smac mimetic compound (SMC) BV6 on MCF7 were examined in the current study. Treatment with BV6 reduces viability and induces apoptosis in MCF7 breast cancer cells. BV6 suppresses autophagy and has demonstrated a defensive role in cancer cells against oxidative stress caused by H2O2. Overall, the present investigation shows that SMC has therapeutic and cytoprotective potential against oxidative stress in cancer cells. These Smac mimetic compounds may be used as anti-cancer drugs as well as antioxidants alone or in conjunction with other commonly used antioxidants.

Epigallocatechin-3-Gallate Therapeutic Potential in Cancer: Mechanism of Action and Clinical Implications.

Cellular signaling pathways involved in the maintenance of the equilibrium between cell proliferation and apoptosis have emerged as rational targets that can be exploited in the prevention and treatment of cancer. Epigallocatechin-3-gallate (EGCG) is the most abundant phenolic compound found in green tea. It has been shown to regulate multiple crucial cellular signaling pathways, including those mediated by EGFR, JAK-STAT, MAPKs, NF-κB, PI3K-AKT-mTOR, and others. Deregulation of the abovementioned pathways is involved in the pathophysiology of cancer. It has been demonstrated that EGCG may exert anti-proliferative, anti-inflammatory, and apoptosis-inducing effects or induce epigenetic changes. Furthermore, preclinical and clinical studies suggest that EGCG may be used in the treatment of numerous disorders, including cancer. This review aims to summarize the existing knowledge regarding the biological properties of EGCG, especially in the context of cancer treatment and prophylaxis.

Effects of gut microbiota on neurodegenerative diseases.

A progressive degradation of the brain's structure and function, which results in a reduction in cognitive and motor skills, characterizes neurodegenerative diseases (NDs) such as Alzheimer's disease (AD), Parkinson's disease (PD), Amyotrophic lateral sclerosis (ALS), and Huntington's disease (HD). The morbidity linked to NDs is growing, which poses a severe threat to human being's mental and physical ability to live well. The gut-brain axis (GBA) is now known to have a crucial role in the emergence of NDs. The gut microbiota is a conduit for the GBA, a two-way communication system between the gut and the brain. The myriad microorganisms that make up the gut microbiota can affect brain physiology by transmitting numerous microbial chemicals from the gut to the brain via the GBA or neurological system. The synthesis of neurotransmitters, the immunological response, and the metabolism of lipids and glucose have all been demonstrated to be impacted by alterations in the gut microbiota, such as an imbalance of helpful and harmful bacteria. In order to develop innovative interventions and clinical therapies for NDs, it is crucial to comprehend the participation of the gut microbiota in these conditions. In addition to using antibiotics and other drugs to target particular bacterial species that may be a factor in NDs, this also includes using probiotics and other fecal microbiota transplantation to maintain a healthy gut microbiota. In conclusion, the examination of the GBA can aid in understanding the etiology and development of NDs, which may benefit the improvement of clinical treatments for these disorders and ND interventions. This review indicates existing knowledge about the involvement of microbiota present in the gut in NDs and potential treatment options.

Recent Advances in Molecular Mechanisms of Cancer Immunotherapy.

Cancer is among the current leading causes of death worldwide, despite the novel advances that have been made toward its treatment, it is still considered a major public health concern. Considering both the serious impact of cancer on public health and the significant side effects and complications of conventional therapeutic options, the current strategies towards targeted cancer therapy must be enhanced to avoid undesired toxicity. Cancer immunotherapy has become preferable among researchers in recent years compared to conventional therapeutic options, such as chemotherapy, surgery, and radiotherapy. The understanding of how to control immune checkpoints, develop therapeutic cancer vaccines, genetically modify immune cells as well as enhance the activation of antitumor immune response led to the development of novel cancer treatments. In this review, we address recent advances in cancer immunotherapy molecular mechanisms. Different immunotherapeutic approaches are critically discussed, focusing on the challenges, potential risks, and prospects involving their use.

Investigating the role of Kinesin family in lung adenocarcinoma via integrated bioinformatics approach.

Lung cancer is the leading cause of mortality from cancer worldwide. Lung adenocarcinoma (LUAD) is a type of non-small cell lung cancer (NSCLC) with highest prevalence. Kinesins a class of motor proteins are shown to be involved in carcinogenesis. We conducted expression, stage plot and survival analyses on kinesin superfamily (KIF) and scrutinized the key prognostic kinesins. Genomic alterations of these kinesins were studied thereafter via cBioPortal. A protein-protein interaction network (PPIN) of selected kinesins and 50 closest altering genes was constructed followed by gene ontology (GO) term and pathway enrichment analyses. Multivariate survival analysis based on CpG methylation of selected kinesins was performed. Lastly, we conducted tumor immune infiltration analysis. Our results found KIF11/15/18B/20A/2C/4A/C1 to be significantly upregulated and correlated with poor survival in LUAD patients. These genes also showed to be highly associated with cell cycle. Out of our seven selected kinesins, KIFC1 showed the highest genomic alteration with highest number of CpG methylation. Also, CpG island (CGI) cg24827036 was discovered to be linked to LUAD prognosis. Therefore, we deduced that reducing the expression of KIFC1 could be a feasible treatment strategy and that it can be a wonderful individual prognostic biomarker. CGI cg24827036 can also be used as a therapy site in addition to being a great prognostic biomarker.

Formulation of pH-responsive highly swellable hydrogel scaffolds for controlled release of tramadol HCl: characterization and biocompatibility evaluation.

Introduction: The objective of current project was to formulate a system for controlled delivery of Tramadol HCl (TRD), an opioid analgesic used in the treatment of moderate to severe pain. Methods: For this purpose, a pH responsive AvT-co-poly hydrogel network was formulated through free radical polymerization by incorporating natural polymers i.e., aloe vera gel and tamarind gum, monomer and crosslinker. Formulated hydrogels were loaded with Tramadol HCl (TRD) and evaluated for percent drug loading, sol-gel fraction, dynamic and equilibrium swelling, morphological characteristics, structural features and in-vitro release of Tramadol HCl. Results and Discussions: Hydrogels were proved to be pH sensitive as remarkable dynamic swelling response ranging within 2.94g/g-10.81g/g was noticed at pH 7.4 as compared to pH 1.2. Percent drug loading was in the range of 70.28%-90.64% for all formulations. Thermal stability and compatibility of hydrogel components were validated by DSC analysis and FTIR spectroscopy. Controlled release pattern of Tramadol HCl from the polymeric network was confirmed as maximum release of 92.22% was observed for over a period of 24 hours at pH 7.4. Moreover, oral toxicity studies were also conducted in rabbits to investigate the safety of hydrogels. No evidence of any toxicity, lesions and degeneration was reported, confirming the biocompatibility and safety of grafted system.

Exploring the multifunctional roles of quantum dots for unlocking the future of biology and medicine.

With recent advancements in nanomedicines and their associated research with biological fields, their translation into clinically-applicable products is still below promises. Quantum dots (QDs) have received immense research attention and investment in the four decades since their discovery. We explored the extensive biomedical applications of QDs, viz. Bio-imaging, drug research, drug delivery, immune assays, biosensors, gene therapy, diagnostics, their toxic effects, and bio-compatibility. We unravelled the possibility of using emerging data-driven methodologies (bigdata, artificial intelligence, machine learning, high-throughput experimentation, computational automation) as excellent sources for time, space, and complexity optimization. We also discussed ongoing clinical trials, related challenges, and the technical aspects that should be considered to improve the clinical fate of QDs and promising future research directions.

Reviewing methods of deep learning for diagnosing COVID-19, its variants and synergistic medicine combinations.

The COVID-19 pandemic has necessitated the development of reliable diagnostic methods for accurately detecting the novel coronavirus and its variants. Deep learning (DL) techniques have shown promising potential as screening tools for COVID-19 detection. In this study, we explore the realistic development of DL-driven COVID-19 detection methods and focus on the fully automatic framework using available resources, which can effectively investigate various coronavirus variants through modalities. We conducted an exploration and comparison of several diagnostic techniques that are widely used and globally validated for the detection of COVID-19. Furthermore, we explore review-based studies that provide detailed information on synergistic medicine combinations for the treatment of COVID-19. We recommend DL methods that effectively reduce time, cost, and complexity, providing valuable guidance for utilizing available synergistic combinations in clinical and research settings. This study also highlights the implication of innovative diagnostic technical and instrumental strategies, exploring public datasets, and investigating synergistic medicines using optimised DL rules. By summarizing these findings, we aim to assist future researchers in their endeavours by providing a comprehensive overview of the implication of DL techniques in COVID-19 detection and treatment. Integrating DL methods with various diagnostic approaches holds great promise in improving the accuracy and efficiency of COVID-19 diagnostics, thus contributing to effective control and management of the ongoing pandemic.