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BackgroundType 2 diabetes mellitus is a metabolic disease categorized by hyperglycemia, resistance to insulin, and ß-cell dysfunction. Around the globe, approximately 422 million people have diabetes, out of which 1.5 million die annually. In spite of innovative advancements in the treatment of diabetes, no biological drug has been known to successfully cure and avert its progression. Thereupon, natural drugs derived from plants are emerging as a novel therapeutic strategy to combat diseases like diabetes.ObjectiveThe current study aims to investigate the antidiabetic potential of natural compounds of Oryza sativa L. indica (black rice) in disease treatment.MethodsAntioxidant activity and alpha amylase assays were performed to evaluate the therapeutic potential of the extract of Oryza sativa L. indica. Gas chromatography–mass spectrometry (GC–MS) was used for identification of constituents from the ethanol extract. ADMET profiling (absorption, distribution, metabolism, excretion, and toxicity), network pharmacology, and molecular dynamics simulation were employed in order to uncover the active ingredients and their therapeutic targets in O. sativa L. indica against type 2 diabetes mellitus.ResultsGC–MS of the plant extract provided a list of 184 compounds. Lipinski filter and toxicity parameters screened out 18 compounds. The topological parameters of the protein–protein interaction (PPI) were used to shortlist the nine key proteins (STAT3, HSP90AA1, AKT1, SRC, ESR1, MAPK1, NFKB1, EP300, and CREBBP) in the type 2 diabetes mellitus pathways. Later, molecular docking analysis and simulations showed that C14 (1H-purine-8-propanoic acid, .alpha.-amino-2, 3, 6, 7-tetrahydro-1,3,7-trimethyl-2,6-dioxo-) and C18 (cyclohexane-carboxamide, N-furfuryl) bind with AKT1 and ESR1 with a binding energy of 8.1, 6.9, 7.3, and 7.2 kcal/mol, respectively. RMSD (root-mean-square deviation) and RMSF (root-mean-square fluctuation) values for AKT1 and ESR1 have shown very little fluctuation, indicating that proteins were stabilized after ligand docking.ConclusionThis study suggests therapeutic drug candidates against AKT1 and ESR1 to treat type 2 diabetes mellitus. However, further wet-lab analysis is required to discover the best remedy for type 2 diabetes mellitus.

The increasing prevalence of multi-morbidities, particularly the incidence of breast cancer in diabetic/osteoarthritic patients emphasize on the need for exploring the underlying molecular mechanisms resulting in carcinogenesis. To address this, present study employed a systems biology approach to identify switch genes pivotal to the crosstalk between diseased states resulting in multi-morbid conditions. Hub genes previously reported for type 2 diabetes mellitus (T2DM), osteoarthritis (OA), and triple negative breast cancer (TNBC), were extracted from published literature and fed into an integrated bioinformatics analyses pipeline. Thirty-one hub genes common to all three diseases were identified. Functional enrichment analyses showed these were mainly enriched for immune and metabolism associated terms including advanced glycation end products (AGE) pathways, cancer pathways, particularly breast neoplasm, immune system signalling and adipose tissue. The T2DM-OA-TNBC interactome was subjected to protein-protein interaction network analyses to identify meta hub/clustered genes. These were prioritized and wired into a three disease signalling map presenting the enriched molecular crosstalk on T2DM-OA-TNBC axes to gain insight into the molecular mechanisms underlying disease-disease interactions. Deciphering the molecular bases for the intertwined metabolic and immune states may potentiate the discovery of biomarkers critical for identifying and targeting the immuno-metabolic origin of disease.

Nanotechnology has transformed drug delivery, offering opportunities to enhance treatment outcomes while minimizing adverse effects. This study focuses on gelatin-coated cobalt and manganese ferrite nanoparticles for potential drug delivery applications. The synthesis involved a co-precipitation method, and the nanoparticles were characterized using various techniques, including X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), Raman spectroscopy, and vibrating sample magnetometer (VSM). Results revealed stable structures, distinct chemical features introduced by gelatin coating, and unique magnetic properties. The hemolysis assay demonstrated reduced hemolytic activity with gelatin coating, enhancing biocompatibility. Drug release studies indicated differential release profiles, with gelatin-coated cobalt ferrite exhibiting higher drug release compared to gelatin-coated manganese ferrite. The Higuchi model supported diffusion-controlled drug release for gelatin-coated cobalt ferrite. These findings suggest the potential of gelatin-coated ferrite nanoparticles for controlled and targeted drug delivery, highlighting their significance in advancing nanomedicine.

Abstract Rheumatoid arthritis (RA), is marked by joint inflammation leading to pannus formation which results in cartilage destruction promoting bone erosion. The pathological hallmark of RA includes synovial hyperplasia and synovial angiogenesis. Active tissue neovascularization is observed in RA. Vascular endothelial Growth factor A (VEGFA), an endothelial cell-specific proangiogenic molecule is triggered by hypoxic cells and its levels are upregulated in RA. The aim of this study was to investigate functional and pathogenic VEGFA variants and to identify the impact of point mutation in VEGFA’s interaction with VEGFR2 and how these polymorphisms affect the susceptibility and severity of RA. We investigated impact of these point mutations on the stability of VEGFA using various computational tools. These mutations were further identified by conservational profile as they are highly involved as structural and functional mutations. Furthermore, these selected variants were modelled and docked against targeted domain regions IGD2 and IGD3 of VEGFR2. Further molecular dynamic simulations were performed using Gromacs. Out of 168 nsSNPS, 19 were highlighted as highly pathogenic using insilico prediction tools. InterPro and ConSurf revealed domains and conserved variants respectively. After stability analysis, we concluded that almost all the mutations were responsible for decreasing the protein stability. HOPE predicted that all the selected damaging nsSNPs were present in the domain which is essential for the functioning of VEGFA protein. Constructed Ramachandran plot and ERRAT validated the quality of all the models. Based on the interactions predicted by STRING database, we performed Protein–Protein docking between VEGFA and VEGFR2. We found few conserved interactions and new polar contacts among wild-type and mutants with VEGFR2. From the simulations, we concluded that mutant R108Q was the most stabilizing mutant among all others whereas R82Q, C86Y, and R108W complexed with VEGFR2 were comparatively less stabilizing as compared to the wild type. This study provides insight into pathogenic nsSNPs that can affect VEGFA protein structure and function. These high-risk variants must be taken into consideration for genetic screening of patients suffering from RA.

Abstract Background Synovial fibroblasts in rheumatoid arthritis (RAFLS) exhibit a pathological aberration of glycolysis and glutaminolysis. Henceforth, we aimed to investigate if dual inhibition of these pathways by phytobiological compound c28MS has the potential of synergistic therapy for arthritis by targeting both glucose and glutamine metabolism. Methods The presence of HK2 and GLS across various cell types and associated gene expression in human synovial cells and a murine model of arthritis was evaluated by scRNA-seq. The metabolic profiling of RAFLS cells was done using H1-nuclear magnetic resonance spectroscopy under glycolytic and glutaminolytic inhibitory conditions by incubating with 3-bromopyruvate, CB839, or dual inhibitor c28MS. FLS functional analysis was conducted under similar conditions. ELISA was employed for the quantification of IL-6, CCL2, and MMP3. K/BxN sera was administered to mice to induce arthritis for in vivo arthritis experiments. Results scRNA-seq analysis revealed that many fibroblasts expressed Hk2 along with Gls with several genes including Ptgs2, Hif1a, Timp1, Cxcl5, and Plod2 only associated with double-positive fibroblasts, suggesting that dual inhibition can be an attractive target for fibroblasts. Metabolomic and functional analysis revealed that c28MS decreased the aggressive behavior of RAFLS by targeting both upregulated glycolysis and glutaminolysis. c28MS administered in vivo significantly decreased the severity of arthritis in the K/BxN model. Conclusion Our findings imply that dual inhibition of glycolysis and glutaminolysis could be an effective approach for the treatment of RA. It also suggests that targeting more than one metabolic pathway can be a novel treatment approach in non-cancer diseases.

Abstract The CTLA4 receptor is an immune checkpoint involved in the downregulation of T cells. Polymorphisms in this gene have been found to be associated with different diseases like rheumatoid arthritis, autosomal dominant immune dysregulation syndrome, juvenile idiopathic arthritis and autoimmune Addison's disease. Therefore, the identification of polymorphisms that have an effect on the structure and function of CTLA4 gene is important. Here we identified the most damaging missense or non-synonymous SNPs (nsSNPs) that might be crucial for the structure and function of CTLA4 using different bioinformatics tools. These in silico tools included SIFT, PROVEAN, PhD-SNP, PolyPhen-2 followed by MutPred2, I-Mutant 2.0 and ConSurf. The protein structures were predicted using Phyre2 and I-TASSER, while the gene–gene interactions were predicted by GeneMANIA and STRING. Our study identified three damaging missense SNPs rs1553657429, rs1559591863 and rs778534474 in coding region of CTLA4 gene. Among these SNPs the rs1553657429 showed a loss of potential phosphorylation site and was found to be highly conserved. The prediction of gene–gene interaction showed the interaction of CTlA4 with other genes and its importance in different pathways. This investigation of damaging nsSNPs can be considered in future while studying CTLA4 related diseases and can be of great importance in precision medicine.

Objective: This study aimed to assess the anti-rheumatic potential of Dodonaea viscosa and to evaluate its bioactive small molecules for their beneficial effects in the management of rheumatoid arthritis.Methods:In vitro bioactivity assays were performed to assess the healing potential of D. viscosa and statistical analysis was performed by using the linear regression technique. In silico analysis was performed to identify the key inhibitors of the disease to target TNF-α. The plant extract was prepared using ethanol solvent via the Soxhlet method. Phytochemical and bioactivity testing was performed. Gas chromatography–mass spectrometry (GC-MS) analysis was conducted for bioactive plant compounds. Disease-specific target was shortlisted by HUB gene analysis. Molecular docking and molecular dynamic simulations were run for validation of the results.Results: Phytochemical studies verified the presence of phenols, flavonoids, steroids, sterols, saponins, coumarins, tannins, and terpenoids. The significant antioxidant potential of plant extract was evaluated by the DPPH and Ferric Reducing Antioxidant Power (FRAP) assays, while the anti-inflammatory potential was evaluated by the protein denaturation and Human Red Blood Cell (HRBC) membrane stabilization assays. In silico studies revealed that nine of the 480 compounds found in D. viscosa (ethanol extract) had drug-like properties. Tumor necrosis factor alpha (TNF-α) was selected as a key disease gene through HUB gene analysis. Results of molecular docking and MD simulation analysis demonstrated that 4-(1-hydroxy-3-oxo-1H-isoindol-2-yl) benzoic acid (PubChemID 18873897), had the best binding affinity with TNF-α amongst all nine compounds.Conclusion: 4-(1-hydroxy-3-oxo-1H-isoindol-2-yl) benzoic acid (PubChemID 18873897), have the potential to be a good small molecule inhibitor of TNF-α against rheumatoid arthritis.

The bidirectional causal relationship between type 2 diabetes mellitus (T2DM) and breast cancer (BC) has been established by numerous epidemiological studies. However, the underlying molecular mechanisms are not yet fully understood. Identification of hub genes implicated in T2DM-BC molecular crosstalk may help elucidate on the causative mechanisms. For this, expression series GSE29231 (T2DM-adipose tissue), GSE70905 (BC- breast adenocarcinoma biopsies) and GSE150586 (diabetes and BC breast biopsies) were extracted from Gene Expression Omnibus (GEO) database, and analyzed to obtain differentially expressed genes (DEGs). The overlapping DEGs were determined using FunRich. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Transcription Factor (TF) analyses were performed on EnrichR software and a protein-protein interaction (PPI) network was constructed using STRING software. The network was analyzed on Cytoscape to determine hub genes and Kaplan-Meier plots were obtained. A total of 94 overlapping DEGs were identified between T2DM and BC samples. These DEGs were mainly enriched for GO terms RNA polymerase II core promoter proximal region sequence and its DNA binding, and cAMP response element binding protein, and KEGG pathways including bladder cancer, thyroid cancer and PI3K-AKT signaling. Eight hub genes were identified: interleukin 6 (IL6), tumor protein 53 (TP53), interleukin 8 (CXCL8), MYC, matrix metalloproteinase 9 (MMP9), beta-catenin 1 (CTNNB1), nitric oxide synthase 3 (NOS3) and interleukin 1 beta (IL1β). MMP9 and MYC associated unfavorably with overall survival (OS) in breast cancer patients, IL6, TP53, IL1β and CTNNB1 associated favorably, whereas NOS3 did not show any correlation with OS. Salt inducible kinase 1 (SIK1) was identified as a significant key DEG for comorbid samples when compared with BC, also dysregulated in T2DM and BC samples (adjusted p

Chronic hyperglycemia and oxidative stress in Type 2 Diabetes Mellitus trigger cellular dysfunction via the formation of Advanced Glycation End Products (AGEs), resulting in dicarbonyl stress. Glyoxalase-1 (Glo-1) is the main defense against dicarbonyl stress. The aim of this study was to explore any cross-talk between Glo-1 and markers of hyperglycemia and oxidative stress. The siRNA-mediated downregulation of Glo-1 was performed in human microvascular endothelial cell line (HMEC-1). A Glo-1 transgenic rat model was developed. Glo-1 activity, as determined spectrophotometrically, and methylglyoxal were quantified using UPLC-MS/MS and the expression of representative markers of hyperglycemia and oxidative stress was performed using quantitative real-time PCR. A significant increase in the expression of Vascular Cell Adhesion Molecule-1 (VCAM-1) was observed in the case of the siRNA-mediated downregulation of Glo-1 in the microvasculature model under hyperglycemic conditions (p-value < 0.001), as well the as overexpression of Glo-1 in the macrovasculature (p-value = 0.0125). The expression of thioredoxin interacting protein (TXNIP) was found to be significantly upregulated in wildtype diabetic conditions vs. Glo-1 transgenic control conditions (p-value = 0.008), whereas the downregulation of Glo-1 had no impact on TXNIP expression. These findings substantiate the role of VCAM as an important marker of dicarbonyl stress (represented by Glo-1 downregulation), as well as of hyperglycemia, in diabetic vascular complications. Our findings also suggest a potential feedback loop that may exist between Glo-1 and TXNIP, as the highest expression of TXNIP is observed in cases of wildtype diabetic conditions, and the lowest expression of TXNIP is observed when Glo-1 transgene is being expressed in absence of dicarbonyl stress.

Type 2 Diabetes Mellitus is one of the most common metabolic disorders, and is characterized by abnormal blood sugar level due to impaired insulin secretion or impaired insulin action—or both. Metformin is the most commonly used drug for the treatment of Type 2 Diabetes Mellitus, but due to its slow mode of action and various side effects it shows poor and slow therapeutic response in patients. Currently, scientists are trying to tackle these limitations by developing nanomedicine. This research reports novel synthesis of silver nanoparticles using aqueous extract of Thymus serpyllum and aims to elucidate its therapeutic potential as an antidiabetic agent on streptozotocin induced diabetic BALB/c mice. Thymus serpyllum mediated silver nanoparticles were characterized through UV, SEM, XRD, and FTIR. The alpha amylase inhibition and antioxidant activity were checked through α amylase and DPPH radical scavenging assay, respectively. To check the effect of silver nanoparticles on blood glucose levels FBG, IPGTT, ITT tests were employed on STZ induced BALB/c mice. To assess the morphological changes in the anatomy of liver, pancreas, and kidney of BALB/c mice due to silver nanoparticles, histological analysis was done through H&E staining system. Finally, AMPK and IRS1 genes expression analysis was carried out via real time PCR. Silver nanoparticles were found to be spherical in shape with an average size of 42 nm. They showed an IC50 of 8 μg/mL and 10 μg/mL for α amylase and DPPH assay, respectively. Our study suggests that silver nanoparticles—specifically 10 mg/kg—cause a significant increase in the expression of AMPK and IRS1, which ultimately increase the glucose uptake in cells. Thymus serpyllum mediated silver nanoparticles possess strong antioxidant and antidiabetic potential and can further be explored as an effective and cheaper alternative option for treatment of Type 2 Diabetes Mellitus.

Type 2 diabetes mellitus (T2DM) is a complex metabolic disorder that is characterized by hyperglycemia, insulin resistance, and lack of insulin production. It has been previously reported that Thymus serpyllum has therapeutic potential against many diseases. To investigate the antidiabetic action of Thymus serpyllum, this study aimed to analyze its restorative impact in diabetic mice, in which it was administered in diet. Diabetes was induced in BALB/c mice fed with a high-fat diet and two intraperitoneal injections of streptozotocin. With the onset of diabetes, the mice were administered daily with aqueous extract of Thymus serpyllum (500 mg/kg/d and 800 mg/kg/d) for 4 weeks. Body weight and fasting blood glucose levels were measured after every 1 week of the treatment. Subsequently, intraperitoneal glucose tolerance and insulin tolerance tests were conducted. In addition, liver tissue was isolated for assessment in terms of levels of gene expression of the AMPK, IRS1, and GLUT2 gene. Treatment with the aqueous extract of Thymus serpyllum was found to be significantly effective in controlling hyperglycemia and improving glucose and insulin tolerance. Predictable with these impacts, the extract of Thymus serpyllum upregulated the AMPK expression at the mRNA level, as well as upregulating the expression of IRS1 and GLUT2 gene. Histopathological examination of the liver, kidney, and pancreas also revealed the restorative impact in terms of cellular morphology. The results hence demonstrated that oral administration of aqueous extract of Thymus serpyllum can potentially attenuate hyperglycemia in the liver muscle of streptozotocin (STZ)-induced diabetic mice via AMPK and IRS1 upregulation.

Enhancement of glycolysis and glutaminolysis are the two most common modalities associated with metabolic reprogramming in rheumatoid arthritis (RA). This enhancement is concomitant to the upregulation of hexokinase 2 (HK2) and glutaminase 1 (GLS1). Hence, the current study was undertaken to identify potential phytobiological inhibitors against HK2 and GLS1, from Dracaena (Sansevieria) trifasciata, an indigenous ethnomedicinal plant found in Pakistan, using computational analysis. Phytobiologics from Dracaena trifasciata were assessed for their ability to co-inhibit HK2 and GLS1 via molecular docking and molecular dynamics simulations. The results underscored seven phytobiologics with promising binding affinities for both HK2 and GLS1. Molecular dynamics simulations further elucidated that all seven identified phytobiologics inhibited HK2 by forming stable complexes but only five amongst the seven had the potential to form stable complexes with GLS1 in real time, thereby implying the potential of co-inhibition for these five compounds. Compound 28MS exhibited an equally strong binding profile for both HK2 (−8.19 kcal/mol) and GLS1 (−8.99 kcal/mol). Furthermore, it exhibited a similar trend in stability during simulation for both targets. Our results serve as a primer for a more lucid understanding towards co-inhibition of HK2 and GLS1 using multiple computational approaches. The identified phytobiologics should undergo in-vitro and in-vivo validation to corroborate their therapeutic potential in RA.

Rheumatoid arthritis is an autoimmune disorder of complex disease etiology. Currently available serological diagnostic markers lack in terms of sensitivity and specificity and thus additional biomarkers are warranted for early disease diagnosis and management. We aimed to screen and compare serum proteome profiles of rheumatoid arthritis serotypes with healthy controls in the Pakistani population for identification of potential disease biomarkers. Serum samples from rheumatoid arthritis patients and healthy controls were enriched for low abundance proteins using ProteoMinerTM columns. Rheumatoid arthritis patients were assigned to one of the four serotypes based on anti-citrullinated peptide antibodies and rheumatoid factor. Serum protein profiles were analyzed via liquid chromatography-tandem mass spectrometry. The changes in the protein abundances were determined using label-free quantification software ProgenesisQITM followed by pathway analysis. Findings were validated in an independent cohort of patients and healthy controls using an enzyme-linked immunosorbent assay. A total of 213 proteins were identified. Comparative analysis of all groups (false discovery rate < 0.05, >2-fold change, and identified with ≥2 unique peptides) identified ten proteins that were differentially expressed between rheumatoid arthritis serotypes and healthy controls including pregnancy zone protein, selenoprotein P, C4b-binding protein beta chain, apolipoprotein M, N-acetylmuramoyl-L-alanine amidase, catalytic chain, oncoprotein-induced transcript 3 protein, Carboxypeptidase N subunit 2, Apolipoprotein C-I and Apolipoprotein C-III. Pathway analysis predicted inhibition of liver X receptor/retinoid X receptor activation pathway and production of nitric oxide and reactive oxygen species pathway in macrophages in all serotypes. A catalogue of potential serum biomarkers for rheumatoid arthritis were identified. These biomarkers can be further evaluated in larger cohorts from different populations for their diagnostic and prognostic potential.