Exploring TLR signaling pathways as promising targets in cervical cancer: The road less traveled.

Cervical cancer is the leading cause of cancer-related deaths for women globally. Despite notable advancements in prevention and treatment, the identification of novel therapeutic targets remains crucial for cervical cancer. Toll-like receptors (TLRs) play an essential role in innate immunity as pattern-recognition receptors. There are several types of pathogen-associated molecular patterns (PAMPs), including those present in cervical cancer cells, which have the ability to activate toll-like receptors (TLRs). Recent studies have revealed dysregulated toll-like receptor (TLR) signaling pathways in cervical cancer, leading to the production of inflammatory cytokines and chemokines that can facilitate tumor growth and metastasis. Consequently, TLRs hold significant promise as potential targets for innovative therapeutic agents against cervical cancer. This book chapter explores the role of TLR signaling pathways in cervical cancer, highlighting their potential for targeted therapy while addressing challenges such as tumor heterogeneity and off-target effects. Despite these obstacles, targeting TLR signaling pathways presents a promising approach for the development of novel and effective treatments for cervical cancer.

Role of Network Pharmacology in Prediction of Mechanism of Neuroprotective Compounds.

Network pharmacology is an emerging pioneering approach in the drug discovery process, which is used to predict the therapeutic mechanism of compounds using various bioinformatic tools and databases. Emerging studies have indicated the use of network pharmacological approaches in various research fields, particularly in the identification of possible mechanisms of herbal compounds/ayurvedic formulations in the management of various diseases. These techniques could also play an important role in the prediction of the possible mechanisms of neuroprotective compounds. The first part of the chapter includes an introduction on neuroprotective compounds based on literature. Further, network pharmacological approaches are briefly discussed. The use of network pharmacology in the prediction of the neuroprotective mechanism of compounds is discussed in detail with suitable examples. Finally, the chapter concludes with the current challenges and future prospectives.

Computational and in vitro screening validates the repositioning potential of Coxibs as anti-fibrotic agents.

Idiopathic pulmonary fibrosis (IPF) is a life-threatening disease with a survival rate of <5 years. The TGF-ß plays a significant role in the progression and severity of IPF. The TGF-ß receptor type1 TGFBR1 antagonists inhibit the process of fibrosis and may have a role in the treatment of IPF. The main objective of the study was to identify promising drug candidates against IPF using In-silico and In-vitro evaluation methods. An in-silico screening was carried out of the marketed Coxibs to find their TGFBR1 inhibitory potential considering their structural resemblance with the JZO-a co-crystalized ligand of the crystal structure of the TGFBR1. The virtual screening yielded rofecoxib as a TGFBR1 ligand with a significant docking score. To further validate the outcome of molecular docking studies, MD simulation of 200 ns was carried out followed by the determination of conformational stability, binding free energy calculation using MMPBSA/MMGBSA, and Free Energy Landscape (FEL). The therapeutic efficacy of rofecoxib was compared with that of nintedanib (a therapeutic agent used in the treatment of IPF) at equimolar concentrations (5 µM). The model of TGF-ß1 (1 ng/ml)-induced EMT of A549 was used to determine the effect of rofecoxib on the EMT markers like cellular morphology, cytokine expressions, fibrosis associated protein, E-cadherin, and α-smooth muscle actin. In vitro results indicated that rofecoxib significantly suppresses the TGF-ß1-induced EMT of A549 cells and validates the possible preventive/protective role of rofecoxib in pulmonary fibrosis. In conclusion, rofecoxib may be considered for repositioning as an anti-fibrotic agent.Communicated by Ramaswamy H. Sarma.

Use of improved memory type control charts for monitoring cancer patients recovery time censored data.

Control charts are a statistical approach for monitoring cancer data that can assist discover patterns, trends, and unusual deviations in cancer-related data across time. To detect deviations from predicted patterns, control charts are extensively used in quality control and process management. Control charts may be used to track numerous parameters in cancer data, such as incidence rates, death rates, survival time, recovery time, and other related indicators. In this study, CDEC chart is proposed to monitor the cancer patients recovery time censored data. This paper presents a composite dual exponentially weighted moving average Cumulative sum (CDEC) control chart for monitoring cancer patients recovery time censored data. This approach seeks to detect changes in the mean recovery time of cancer patients which usually follows Weibull lifetimes. The results are calculated using type I censored data under known and estimated parameter conditions. We combine the conditional expected value (CEV) and conditional median (CM) approaches, which are extensively used in statistical analysis to determine the central tendency of a dataset, to create an efficient control chart. The suggested chart's performance is assessed using the average run length (ARL), which evaluates how efficiently the chart can detect a change in the process mean. The CDEC chart is compared to existing control charts. A simulation study and a real-world data set related to cancer patients recovery time censored data is used for results illustration. The proposed CDEC control chart is developed for the data monitoring when complete information about the patients are not available. So, instead of doping the patients information we can used the proposed chart to monitor the patients information even if it is censored. The authors conclude that the suggested CDEC chart is more efficient than competitor control charts for monitoring cancer patients recovery time censored data. Overall, this study introduces an efficient new approach for cancer patients recovery time censored data, which might have significant effect on quality control and process improvement across a wide range of healthcare and medical studies.

Cisplatin and Starvation Differently Sensitize Autophagy in Renal Carcinoma: A Potential Therapeutic Pathway to Target Variegated Drugs Resistant Cancerous Cells.

Cisplatin, a powerful chemotherapy medication, has long been a cornerstone in the fight against cancer due to chemotherapeutic failure. The mechanism of cisplatin resistance/failure is a multifaceted and complex issue that consists mainly of apoptosis inhibition through autophagy sensitization. Currently, researchers are exploring ways to regulate autophagy in order to tip the balance in favor of effective chemotherapy. Based on this notion, the current study primarily identifies the differentially expressed genes (DEGs) in cisplatin-treated autophagic ACHN cells through the Illumina Hi-seq platform. A protein-protein interaction network was constructed using the STRING database and KEGG. GO classifiers were implicated to identify genes and their participating biological pathways. ClueGO, David, and MCODE detected ontological enrichment and sub-networking. The network topology was further examined using 12 different algorithms to identify top-ranked hub genes through the Cytoscape plugin Cytohubba to identify potential targets, which established profound drug efficacy under an autophagic environment. Considerable upregulation of genes related to autophagy and apoptosis suggests that autophagy boosts cisplatin efficacy in malignant ACHN cells with minimal harm to normal HEK-293 growth. Furthermore, the determination of cellular viability and apoptosis by AnnexinV/FITC-PI assay corroborates with in silico data, indicating the reliability of the bioinformatics method followed by qRT-PCR. Altogether, our data provide a clear molecular insight into drug efficacy under starved conditions to improve chemotherapy and will likely prompt more clinical trials on this aspect.

Characterization of a hemolytic and antibiotic-resistant Pseudomonas aeruginosa strain S3 pathogenic to fish isolated from Mahananda River in India.

Virulent strain Pseudomonas aeruginosa isolated from Mahananda River exhibited the highest hemolytic activity and virulence factors and was pathogenic to fish as clinical signs of hemorrhagic spots, loss of scales, and fin erosions were found. S3 was cytotoxic to the human liver cell line (WRL-68) in the trypan blue dye exclusion assay. Genotype characterization using whole genome analysis showed that S3 was similar to P. aeruginosa PAO1. The draft genome sequence had an estimated length of 62,69,783 bp, a GC content of 66.3%, and contained 5916 coding sequences. Eight genes across the genome were predicted to be related to hemolysin action. Antibiotic resistance genes such as class C and class D beta-lactamases, fosA, APH, and catB were detected, along with the strong presence of multiple efflux system genes. This study shows that river water is contaminated by pathogenic P. aeruginosa harboring an array of virulence and antibiotic resistance genes which warrants periodic monitoring to prevent disease outbreaks.

Physical characterization and bioavailability assessment of 5-fluorouracil-based nanostructured lipid carrier (NLC): In vitro drug release, Hemolysis, and permeability modulation.

5-Fluorouracil (5-FU) is an anticancer agent belonging to BCS Class III that exhibits poor release characteristics and low retention in the biological system. The main objective of this investigation was to develop a drug delivery system, i.e., Nanostructure Lipid Carriers (NLCs) loaded with 5-FU to prolong its biological retention through 5-FU-loaded NLCs (5-FUNLC) were designed to manipulate physicochemical characteristics and assessment of in vitro and in vivo performance. The developed NLCs underwent comprehensive characterization, including assessments for particle size, zeta potential, morphological evaluation, and FT-IR spectroscopy. Additionally, specific evaluations were conducted for 5-FUNLCs, encompassing analyses for encapsulation efficiency of the drug, release characteristics in PBS at pH 6.8, and stability study. The lipophilic character of 5-FUNLC was confirmed through the measurement of the partition coefficient (log P). 5-FUNLCs were observed as spherical-shaped particles with a mean size of 300 ± 25 nm. The encapsulation efficiency was determined to be 89%, indicating effective drug loading within the NLCs. Furthermore, these NLCs exhibited a sustained release nature lasting up to 3-4 h, indicating their potential for controlled drug release over time. Lipid components were biocompatible with the 5-FU to determine thermal transition temperature and show good stability for 30 days. Additionally, an in vitro hemolysis study that confirmed the system did not cause any destruction to the RBCs during intravenous administration. The drug's gut permeability was assessed utilizing the optimized 5-FUNLC (F2) in comparison to 5-FU through the intestine or gut sac model (in the apical to basolateral direction, A → B). The permeability coefficient was measured as 4.91 × 10-5 cm/h with a significant difference. Additionally, the antioxidant potential of the NLCs was demonstrated through the DPPH method. The NLCs' performance was further assessed through in vivo pharmacokinetic studies on Wistar Rats, resulting in a 1.5-fold enhancement in their activity compared to free 5-FU. These NLCs offer improved drug solubility and sustained release, which collectively contribute to enhanced therapeutic outcomes and modulate bioavailability. The study concludes by highlighting the potential of 5-FUNLC as an innovative and efficient drug delivery system. The findings suggest that further preclinical investigations are warranted, indicating a promising avenue for the development of more effective and well-tolerated treatments for cancer.

A new unit distribution: properties, estimation, and regression analysis.

This research commences a unit statistical model named power new power function distribution, exhibiting a thorough analysis of its complementary properties. We investigate the advantages of the new model, and some fundamental distributional properties are derived. The study aims to improve insight and application by presenting quantitative and qualitative perceptions. To estimate the three unknown parameters of the model, we carefully examine various methods: the maximum likelihood, least squares, weighted least squares, Anderson-Darling, and Cramér-von Mises. Through a Monte Carlo simulation experiment, we quantitatively evaluate the effectiveness of these estimation methods, extending a robust evaluation framework. A unique part of this research lies in developing a novel regressive analysis based on the proposed distribution. The application of this analysis reveals new viewpoints and improves the benefit of the model in practical situations. As the emphasis of the study is primarily on practical applications, the viability of the proposed model is assessed through the analysis of real datasets sourced from diverse fields.

Efficient imputation methods in case of measurement errors.

This manuscript develops few efficient difference and ratio kinds of imputations to handle the situation of missing observations given that these observations are polluted by the measurement errors (ME). The mean square errors of the developed imputations are studied to the primary degree approximation by adopting Taylor series expansion. The proposed imputations are equated with the latest existing imputations presented in the literature. The execution of the proposed imputations is assessed by utilizing a broad empirical study utilizing some real and hypothetically created populations. Appropriate remarks are made for sampling respondents regarding practical applications.

Formulation of silver nanoparticles using Duabanga grandiflora leaf extract and evaluation of their versatile therapeutic applications.

The current research focused on the green synthesis of silver nanoparticles (AgNPs) using Duabanga grandiflora leaf extract. The green synthesis of AgNPs was confirmed by the surface plasmon resonance band at 453 nm in a UV-Visible analysis. The formulated AgNPs had a diameter of around 99.72 nm with a spherical shape. Fourier transform infrared (FTIR) spectrum revealed the bio-reducing potential of phytochemicals present in D. grandiflora, which fundamentally influenced the synthesis of AgNPs. Zeta potential, dynamic light scattering (DLS), scanning electron microscopic (SEM), energy-dispersive X-ray spectroscopic (EDX), X-ray diffraction (XRD), and transmission electron microscopic (TEM) analyses were executed to reveal the physicochemical attributes of the AgNPs. The AgNPs were further investigated for their antioxidant, antidiabetic, anticancer, and antibacterial potential. The DPPH free radical assay revealed the potential radical scavenging capacity (IC50 = 76.73 µg/ml) of green synthesized AgNPs. α-Amylase inhibitory assay displayed significant inhibitory potential (IC50 = 162.11 µg/ml) of this starch-breaking enzyme by AgNPs, revealing the antidiabetic potential of AgNPs. AgNPs exhibited potential cytotoxic activity (IC50 = 244.57 µg/ml) against malignant human kidney cells. In addition, AgNPs showed outstanding antibacterial activity against both Gram-negative (Escherichia coli) and Gram-positive (Staphylococcus aureus) bacterial strains. Interestingly, AgNPs showed cytotoxic and antimicrobial activities at much higher concentrations than radical scavenging and α-amylase inhibitory concentrations. Thus, our finding elaborated the scope of green synthesized AgNPs for diverse therapeutic applications (dose-dependent) for further clinical translation.

Structural-based Study to Identify the Repurposed Candidates Against Bacterial Infections.

BACKGROUND: Microbial infections are mostly caused by Gram-positive as well as Gram-negative bacteria affecting millions of people worldwide. There is an urgent need to explore existing molecules or discover new chemical entities (NCEs) against bacterial infection. OBJECTIVE: The main objective of the current investigation is to explore recently US-FDA- approved drugs (2019-2023) against various targets of Gram-positive and Gram-negative bacteria using high-performance computational studies. AIM: The current study aims to find out the potential drugs of recently US-FDA-approved drugs as repurposing candidates against bacterial infections. METHODS: The targets of Gram-positive and Gram-negative bacteria were identified using literature studies whereas ligands were selected from the FDA-approved drug lists of the last 5 years. Further, the drugs and targets were prepared through the LigPrep and Protein Preparation Wizard modules of Schrödinger (release 2023-1) respectively. The GlideDock and Desmond modules of Schrödinger were used for the molecular docking study and molecular dynamics simulation respectively. RESULTS: A total of 202 drugs were found in the FDA lists which were approved in the last five years. Out of them, 77 drugs were selected for docking study based on their properties. A total of 21 drugs have shown energetically favored binding conformation of drugs in the active site of bacterial targets. The interaction of these drugs was studied in detail using molecular dynamics (MD) simulation. The MD simulation results have shown stable dynamic conformation of triclabendazole (anti-helminthic) with topoisomerase II of gram-negative bacteria whereas solriamfetol (for obstructive sleep apnea) has shown stable dynamic conformation in the active site of restriction endonuclease of gram-positive bacteria. CONCLUSION: The identified drugs can be repurposed against Gram-positive and Gramnegative bacterial infections. However, further experimental studies are required to confirm their antibacterial potential.

Monkeypox virus: insights into pathogenesis and laboratory testing methods.

The monkeypox virus (MPXV) is a zoonotic pathogen that transmits between monkeys and humans, exhibiting clinical similarities with the smallpox virus. Studies on the immunopathogenesis of MPXV revealed that an initial strong innate immune response is elicited on viral infection that subsequently helps in circumventing the host defense. Once the World Health Organization (WHO) declared it a global public health emergency in July 2022, it became essential to clearly demarcate the MPXV-induced symptoms from other viral infections. We have exhaustively searched the various databases involving Google Scholar, PubMed, and Medline to extract the information comprehensively compiled in this review. The primary focus of this review is to describe the diagnostic methods for MPXV such as polymerase chain reaction (PCR), and serological assays, along with developments in viral isolation, imaging techniques, and next-generation sequencing. These innovative technologies have the potential to greatly enhance the accuracy of diagnostic procedures. Significant discoveries involving MPXV immunopathogenesis have also been highlighted. Overall, this will be a knowledge repertoire that will be crucial for the development of efficient monitoring and control strategies in response to the MPXV infection helping clinicians and researchers in formulating healthcare strategies.

"Synthesis and characterization of a novel pyridinium iodide-tagged Schiff base and its metal complexes as potential ACHN inhibitors".

In quest of developing an efficient and effective drug against the ACHN human renal adenocarcinoma cell line herein, we report the synthesis and characterization of a novel Pyridinium iodide-tagged Schiff base (5) and its Cu (II)/Zn (II)/Cd (II)-complexes (6). The synthesized compounds are well characterized by Elemental analysis, UV-Visible, FTIR, Magnetic Susceptibility, NMR, HRMS, MALDI, and PXRD techniques. They were then subsequently tested on the ACHN cell lines using MTT assays and their IC50 values were determined, followed by their ROS production capacity. Among the tested compounds Zn (II)-complex 6(b) was found to be the most potent one with a minimum IC50 value while the ligand (5) was the least.

Ion Transport Basis of Diarrhea, Paneth Cell Metaplasia, and Upregulation of Mechanosensory Pathway in Anti-CD40 Colitis Mice.

BACKGROUND: Anti-Cluster of differentiation (CD)-40-induced colitis, driven by innate inflammatory responses in the intestine, is a potent animal model exhibiting IBD pathophysiology including diarrhea. However, the ion transport basis of diarrhea and some key mucosal pathways (Paneth cells, stem cell niche, and mechanosensory) in this model have not been investigated. METHODS: Mucosal scrapings and intestinal tissue from control and CD40 antibody (150 µg) treated Rag2-/- mice were examined for gut inflammation, Paneth cell numbers, expression of key transporters, tight/adherens junction proteins, stem cell niche, and mechanosensory pathway via hematoxylin and eosin staining, quantitative polymerase chain reaction, and western blotting. RESULTS: Compared with control, anti-CD40 antibody treatment resulted in a significant loss of body weight (P < .05) and diarrhea at day 3 postinjection. Distal colonic tissues of anti-CD40 mice exhibited increased inflammatory infiltrates, higher claudin-2 expression, and appearance of Paneth cell-like structures indicative of Paneth cell metaplasia. Significantly reduced expression (P < .005) of downregulated in adenoma (key Cl- transporter), P-glycoprotein/multidrug resistantance-1 (MDR1, xenobiotic transporter), and adherens junction protein E-cadherin (~2-fold P < .05) was also observed in the colon of anti-CD40 colitis mice. Interestingly, there were also marked alterations in the stem cell markers and upregulation of the mechanosensory YAP-TAZ pathway, suggesting the activation of alternate regeneration pathway post-tissue injury in this model. CONCLUSION: Our data demonstrate that the anti-CD40 colitis model shows key features of IBD observed in the human disease, hence making it a suitable model to investigate the pathophysiology of ulcerative colitis (UC).

Our studies demonstrate the ion transport basis of diarrhea, downregulation of MDR1 and E-cadherin, Paneth cell metaplasia, and induction of claudin-2 and mechanosensory pathway in anti-CD40 colitis (innate immune-based model of IBD), similar to the human disease.

Design based synthetic imputation methods for domain mean.

In real life, situations may arise when the available data are insufficient to provide accurate estimates for the domain, the small area estimation (SAE) technique has been used to get accurate estimates for the variable under study. The problem of missing data is a serious problem that has an impact on sample surveys, but small area estimates are especially prone to it. This paper is a basic effort that suggests design based synthetic imputation methods for the domain mean estimation using simple random sampling in order to address the issue of missing data under SAE. The expression of the mean square error for the proposed imputation methods are obtained up to first order approximation. The efficiency conditions are determined and a thorough simulation study is carried out using artificially generated data sets. An application is included with real data that further supports this study.

FDA-approved heterocyclic molecules for cancer treatment: Synthesis, dosage, mechanism of action and their adverse effect.

As the incorporation of heterocycles increases the physical characteristics and biological activity of pharmacological molecules, heterocyclic scaffolds are commonly discovered as common cores in a wide spectrum of biologically active drugs. In the contemporary context, many heterocycles have arisen, playing vital roles in diverse pharmaceutical compounds that benefit humanity. Over 85 % of FDA-approved medication molecules contain heterocycles, and most importantly, numerous heterocyclic medicinal molecules indicate potential benefits against a range: of malignancies. The unique flexibility and dynamic core scaffold of these compounds have aided anticancer research. These medications are used to treat cancer patients by targeting particular genes, enzymes, and receptors. Aside from the drugs that are now on the market, numerous forms are being researched for their potential anti-cancer activity. Here in this review, we classified some molecules and biologically active heterocycles containing anticancer medicinal moieties approved by the FDA between 2019 and 2021 based on their use in various forms of cancer. We will focus on those that are suitable for cancer treatment, as well as the essential biochemical mechanisms of action, biological targets, synthetic methods, and inherent limiting considerations in their use.

Unveiling the potential of recently FDA-approved drugs as quorum sensing inhibitors against P. Aeruginosa using high-performance computational techniques.

Through cell-to-cell communication, activation of efflux pumps, formation of biofilms, and other mechanisms, pseudomonas aeruginosa's quorum sensing systems (QSS), notably the lasl/las-r system, contribute a vital role in the development of anti-microbial resistance (AMR). Identifying potential drugs against these targets could have significant implications for combating pseudomonal infections. The current study aims to identify promising recently FDA-approved drugs against lasl/las-r proteins. The ligands were selected from the FDA-approved drug lists of the last 5 years. Out of 202, 78 drugs were checked for interaction with lasl/las-r protein and 4 drugs revealed top binding conformations characterized by favorable energetic profiles within the active site of the las-r protein which were further assigned for 250-ns molecular dynamics (MD) simulation. The MD analysis confirmed the dynamical stability of brexanolone and oteseconazole with las-r protein. The root mean square deviation (RMSD), radius of gyration (Rg) and solvent-accessible surface area (SASA) analysis have indicated less deviation, more compactness of protein and less exposure of protein ligand complex to its surroundings as compared to the reference ligand-protein complex. The hydroxyl group in the oteseconazole whereas hydroxyl and ketone group in the brexanolone were responsible for hydrogen bonds with the active site residue of las r ptotein as indicated by ligand-protein contacts diagram. The binding energies per residue analysis revealed TYR-47 as the most contributing amino acid residue for interaction with oteseconazole and brexanolone. The identified drugs may be potential repurposing candidates against pseudomonal infections through inhibition of las-r protein.Communicated by Ramaswamy H. Sarma.

Identification of novel signal of Raynaud's phenomenon with Calcitonin Gene-Related Peptide(CGRP) antagonists using data mining algorithms and network pharmacological approaches.

BACKGROUND: Calcitonin gene-related peptide (CGRP) antagonists are recently approved for the treatment of migraine. AIM: The main aim of the current study was to find out the association of CGRP antagonists with RP using data mining algorithms integrated with network pharmacological approaches. RESEARCH DESIGN AND METHODS: The individual case safety reports were extracted using OpenVigil2.1-MedDRA-V17 (2004Q1-2022Q3), the United States Adverse Event Reporting System (US FAERS). The data mining algorithms i.e. reporting odds ratio (ROR) with 95% confidence and proportionality reporting ratio (PRR) with associated chi-square value were calculated along with a minimum of three ICSRs to identify the signal. Further, the network was constructed using Cytoscape 3.7.2. Finally, molecular docking was performed using Glide, Schrodinger Inc. RESULTS: The PRR ≥2 with a linked chi-square value ≥4, add up of co-occurrence ≥3, and a lower limit of 95% confidence interval of ROR exceeding 2 indicates a positive signal of RP. Further, the network pharmacological and molecular docking results have shown the involvement of insulin-like growth factor 1-receptor (IGF1R) pathways. CONCLUSION: The RP is recognized as a novel signal with all CGRP antagonists.