In vitro cone beam computed tomography imaging of periodontal bone

OBJECTIVES

To assess the accuracy of NewTom 9000 cone beam CT (CBCT) images for the detection and quantification of periodontal bone defects in three dimensions.

METHODS

A sample of 146 sites in 5 dry skulls provided the ground truth (GT). Half of the sample had bone loss of at least 3 mm. Two metal spheres at each site ensured correspondence between GT and CBCT measurements. Skulls were submerged in water and scanned with the NewTom QR-DVT-9000. A full mouth series (FMX) was obtained of each skull using photostimulable phosphor plates. Six observers measured the bone height of each site and rated the presence or absence of bone loss. Measurements were compared to GT and A(z)-values were calculated from receiver operating characteristic curves.

RESULTS

The A(z)-value for CBCT was 0.74 (standard deviation (SD) = 0.14) and for FMX 0.48 (SD = 0.09). The difference was significant (ANOVA: P < 0.01). The diagnostic accuracy of CBCT was lower for anterior teeth (A(z) = 0.59) than for molars (A(z) = 0.82) and premolars (A(z) = 0.79) (Tukey's HSD (honestly significant difference): P < 0.01). The mean absolute difference between CBCT and GT was 1.27 mm (SD = 1.43) and between FMX and GT 1.49 mm (SE = 1.24) (ANOVA: P < 0.01). Measurements in the anterior mandible were less accurate than in other areas (Tukey's HSD: P < 0.01).

CONCLUSION

The NewTom 9000 cone beam CT scanner provides better diagnostic and quantitative information on periodontal bone levels in three dimensions than conventional radiography. The accuracy in the anterior aspect of the jaws is limited.

A computational model revealing the immune-related hub genes and key pathways involved in rheumatoid arthritis (RA)

Rheumatoid arthritis (RA) has one of the highest disability rates among inflammatory joint disorders. However, the reason and possible molecular events are still unclear. There are various treatment options available, but no complete cure. To obtain early diagnosis and successful medication in RA, it is necessary to explore gene susceptibility and pathogenic factors. The main intend of our work is to explore the immune-related hub genes with similar functions that are differentially expressed in RA patients. Three datasets such as GSE21959, GSE55457, and GSE77298, were taken to analyze the differently expressed genes (DEGs) among 55 RA and 33 control samples. We obtained 331 upregulated and 275 downregulated DEGs from three Gene Expression Omnibus (GEO) datasets using the R package. Furthermore, a protein-protein interaction network was built for upregulated and downregulated DEGs using Cytoscape. Subsequently, MCODE analysis was performed and obtained the top two modules in each DEG's upregulated and downregulated protein-protein interactions (PPIs) network. CytoNCA and cytoHubba were performed and identified overlapping DEGs. In addition, we narrowed down DEGs by filtering with immune-related genes and identified DE-IRGs. Gene ontology (GO) and KEGG pathway analysis in upregulated and downregulated DEGs were executed with the DAVID platform. Our study obtained the nine most significant DE-IRGs in RA such as CXCR4, CDK1, BUB1, BIRC5, AGTR1, EGFR, EDNRB, KALRN, and GHSR. Among them, CXCR4, CDK1, BUB1, and BIRC5 are overexpressed in RA and may contribute to the pathophysiology of the disease. Similarly, AGTR1, EGFR, EDNRB, KALRN, and GHSR are all low expressed in RA and may have a contribution to pathogenesis. GO, KEGG functional enrichment, and GeneMANIA showed that the dysregulated process of DE-IRGs causes RA development and progression. These findings may be helpful in future studies in RA diagnosis and therapy.

Whole-exome sequencing analysis of NSCLC reveals the pathogenic missense variants from cancer-associated genes

BACKGROUND

Non-small-cell lung cancer (NSCLC) is the most common type of lung cancer. NSCLC accounts for 84% of all lung cancer cases. In recent years, advances in pathway understanding, methods for discovering novel genetic biomarkers, and new drugs designed to inhibit the signaling cascades have enabled clinicians to personalize therapy for NSCLC.

OBJECTIVES

The primary aim of this study is to identify the genes associated with NSCLC that harbor pathogenic variants that could be causative for NSCLC. The second aim is to investigate their roles in different pathways that lead to NSCLC.

METHODS

We examined exome-sequencing datasets from 54 NSCLC patients to characterize the variants associated with NSCLC.

RESULTS

Our findings revealed that 17 variants in 14 genes were considered highly pathogenic, including CDKN2A, ERBB2, FOXP1, IDH1, JAK3, KMT2D, K-Ras, MSH3, MSH6, POLE, RNF43, TCF7L2, TP53, and TSC1. Gene set enrichment analysis revealed the involvement of transmembrane receptor protein tyrosine kinase activity, protein binding, ATP binding, phosphatidylinositol-4,5-bisphosphate 3-kinase, and Ras guanyl-nucleotide exchange factor activity. Pathway analysis of these genes yielded different cancer-related pathways, including colorectal, prostate, endometrial, pancreatic, PI3K-Akt signaling pathways, and signaling pathways regulating pluripotency of stem cells. Module 1 from protein-protein interactions (PPIs) identified genes that harbor pathogenic SNPs. Three of the most deleterious SNPs are ERBB2 (rs1196929947), K-Ras (rs121913529), and POLE (rs751425952). Interestingly, one patient has a pathogenic K-Ras variant (rs121913529) co-occurred with the missense variant (rs752054698) inTSC1 gene.

CONCLUSION

This study maps highly pathogenic variants associated with NSCLC and investigates their contributions to the pathogenesis of NSCLC. This study sheds light on the potential applications of precision medicine in patients with NSCLC.

Cytogenetic studies on spray painters in south India

Studies on the frequencies of chromosomal aberrations were carried out on 104 spray painters working in automobile body reconditioning, steel furniture making and refrigerator repainting workshops in the metro city, Chennai, of south India. Randomly selected 50 male subjects not connected with this occupation were included as controls in the study. Chromosomal analysis was carried out in 48h lymphocyte (short duration) cultures representing the first mitotic division, on a subset of samples consisting of 50 spray painters, 20 controls and 72h (longer duration) cultures representing the second cell division, on all subjects. Baseline frequency of chromosomal aberrations was significantly higher among painters as compared to matched controls. Smoking and alcoholism as modulating factors had no added effect on the frequency of aberrant metaphases. Stepwise multiple linear regression analysis indicated that duration of service and age were significant factors that influence the frequency of chromosomal aberrations observed.

Linguistic Adaptation and Psychometric Properties of Tamil Version of General Oral Health Assessment Index-Tml

Background:

Oral health has an impact on quality of life hence for research purpose validation of a Tamil version of General Oral Health Assessment Index would enable it to be used as a valuable tool among Tamil speaking population.

Aim:

In this study, we aimed to assess the psychometric properties of translated Tamil version of General Oral Health Assessment Index (GOHAI-Tml).

Subjects and Methods:

Linguistic adaptation involved forward and backward blind translation process. Reliability was analyzed using test-retest, Cronbach alpha, and split half reliability. Inter-item and item-total correlation were evaluated using Spearman rank correlation. Convenience sampling was done, and 265 consecutive patients aged 20–70 years attending the outpatient department were recruited. Subjects were requested to fill a self-reporting questionnaire along with Tamil GOHAI version. Clinical examination was done on the same visit. Concurrent validity was measured by assessing the relationship between GOHAI scores and self-perceived oral health and general health status, satisfaction with oral health, need for dental treatment and esthetic satisfaction. Discriminant validity was evaluated by comparing the GOHAI scores with the objectively assessed clinical parameters. Exploratory factor analysis was done to examine the factor structure.

Results:

Mean GOHAI-Tml was 52.7 (6.8, range 22–60, median 54). The mean number of negative impacts was 2 (2.4, range 0–11, median 1). The Spearman rank correlation for test-retest ranged from 0.8 to 0.9 (P < 0.001) for all the 12 items between visits. The Cronbach alpha for 265 samples was 0.8 suggesting good internal consistency and homogeneity between items. Item scale correlation ranged from 0.4 to 0.8 (P < 0.001). Concurrent and discriminant validity was established. Principal component analysis resulted in extraction of four factors which together accounted for 66.4% (7.9/12) variance.

Conclusion:

GOHAI-Tml has shown acceptable psychometric properties, so that it can be used as an efficient tool in identifying the impact of oral health on quality of life among the Tamil speaking population.

Integrative ontology and pathway-based approach identifies distinct molecular signatures in transcriptomes of esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) remains a serious concern globally due to many factors that including late diagnosis, lack of an ideal biomarker for diagnosis and prognosis, and high rate of mortality. In this study, we aimed to identify the essential dysregulated genes and molecular signatures associated with the progression and development of ESCC. The dataset with 15 ESCCs and the 15 adjacent normal tissue samples from the surrounding histopathologically tumor-free mucosa was selected. We applied bioinformatics pipelines including various topological parameters from MCODE, CytoNCA, and cytoHubba to prioritize the most significantly associated DEGs with ESCC. We performed functional enrichment annotation for the identified DEGs using DAVID and MetaCore™ GeneGo platforms. Furthermore, we validated the essential core genes in TCGA and GTEx datasets between the normal mucosa and ESCC for their expression levels. These DEGs were primarily enriched in positive regulation of transferase activity, negative regulation of organelle organization, cell cycle mitosis/S-phase transition, spindle organization/assembly, development, and regulation of angiogenesis. Subsequently, the DEGs were associated with the pathways such as oocyte meiosis, cell cycle, and DNA replication. Our study identified the eight-core genes (AURKA, AURKB, MCM2, CDC20, TPX2, PLK1, FOXM1, and MCM7) that are highly expressed among the ESCC, and TCGA dataset. The multigene comparison and principal component analysis resulted in elevated signals for the AURKA, MCM2, CDC20, TPX2, PLK1, and FOXM1. Overall, our study reported GO profiles and molecular signatures that might help researchers to grasp the pathological mechanisms underlying ESCC development and eventually provide novel therapeutic and diagnostic strategies.

Hippocampus Segmentation-Based Alzheimer's Disease Diagnosis and Classification of MRI Images

Alzheimer's disease represents a neurological condition characterized by steady cognitive decline and eventual memory loss due to the death of brain cells. It is one of the most prominent dementia types observed in patients and which hence underlines the imminent need for potential methods to diagnose the disease early on. This work considers a novel approach by utilizing a reduced version of one of the datasets used in this work to achieve a considerably accurate prediction while also enabling quicker training. It leverages image segmentation to isolate the hippocampus region from brain MRI images and then strikes a comparison between models trained on the segmented portions and models trained on complete images. This research uses two datasets-4 classes of images from Kaggle and a popular OASIS 2 MRI and demographic dataset. A deep learning-based approach was adopted to train the Kaggle dataset to perform severity classification, and the hippocampus region segmented from a reduced version of the OASIS dataset was trained on supervised and ensemble learning algorithms to detect Alzheimer's disease. The metric used for the assessment of model performance is classification accuracy. A comparative analysis between the proposed approach and existing work was also performed, and it was observed that the proposed approach is effective in the early diagnosis of Alzheimer's disease.

A study on genetic variability of pathogenic Aeromonas hydrophila strains and the varied responses of the strains towards phyto-extracts

The present study evaluated genetic variation in Aeromonas hydrophila strains using PCR-RAPD and their varied susceptibility to phyto-extract. Four strains of Aeromonas hydrophila isolated from skin infections of common freshwater fish, Cyprinus carpio were characterized by various biochemical methods, physiological tests and PCR- RAPD. Antimicrobial activity of the leaf extracts of three medicinal plants, Ocimum sanctum, Adathoda vasica and Calendula officinalis were tested against the four strains of A. hydrophila by disc diffusion (Kirby-Bauer) method. Antagonistic effects of leaf extracts against A. hydrophila strains were assessed by co-culture method. RAPD analysis showed that all the microbes isolated from skin infection belong to the same species but there was no 100% genetic similarity among them Dendrogram constructed by UPGMA clearly supported the PCR pattern of genetic variability among the strains. This study revealed that Aeromonas hydophila exhibits genetic variability and varied susceptibility towards phyto-extracts. Results indicated that phyto-extracts offers a promising alternative to the use of antibiotics in controlling Aeromonas hydrophila.

The targeted next-generation sequence revealed SMAD4, AKT1, and TP53 mutations from circulating cell-free DNA of breast cancer and its effect on protein structure - A computational approach

Breast cancer biomarkers that detect marginally advanced stages are still challenging. The detection of specific abnormalities, targeted therapy selection, prognosis, and monitoring of treatment effectiveness over time are all made possible by circulating free DNA (cfDNA) analysis. The proposed study will detect specific genetic abnormalities from the plasma cfDNA of a female breast cancer patient by sequencing a cancer-related gene panel (MGM455 - Oncotrack Ultima), including 56 theranostic genes (SNVs and small INDELs). Initially, we determined the pathogenicity of the observed mutations using PredictSNP, iStable, Align-GVGD, and ConSurf servers. As a next step, molecular dynamics (MD) was implemented to determine the functional significance of SMAD4 mutation (V465M). Lastly, the mutant gene relationships were examined using the Cytoscape plug-in GeneMANIA. Using ClueGO, we determined the gene's functional enrichment and integrative analysis. The structural characteristics of SMAD4 V465M protein by MD simulation analysis further demonstrated that the mutation was deleterious. The simulation showed that the native structure was more significantly altered by the SMAD4 (V465M) mutation. Our findings suggest that SMAD4 V465M mutation might be significantly associated with breast cancer, and other patient-found mutations (AKT1-E17K and TP53-R175H) are synergistically involved in the process of SMAD4 translocate to nuclease, which affects the target gene translation. Therefore, this combination of gene mutations could alter the TGF-β signaling pathway in BC. We further proposed that the SMAD4 protein loss may contribute to an aggressive phenotype by inhibiting the TGF-β signaling pathway. Thus, breast cancer's SMAD4 (V465M) mutation might increase their invasive and metastatic capabilities.Communicated by Ramaswamy H. Sarma.

Mechanistic Insights into the Binding of Boar Salivary Pheromones and Putative Molecule with Receptor Proteins: A Comparative Computational Approach

Precise estrus detection in sows is pivotal in increasing the productivity within the pork industry. Sows in estrus exhibit exclusive behaviors when exposed to either a live boar or the steroid pheromones androstenone and androstenol. Recently, a study employing solid-phase microextraction-gas chromatography-mass spectrometry has identified a novel salivary molecule in boars, known as quinoline. This finding has intriguing implications as a synthetic mixture of androstenone, androstenol, and quinoline induces estrus behaviors in sows. Nevertheless, the precise pheromonal characteristics of quinoline remain elusive. In this study, we validate and compare the binding efficiency of androstenone, androstenol, and quinoline with porcine olfactory receptor proteins (odorant-binding protein [OBP], pheromaxein, salivary lipocalin [SAL], and Von Ebner's gland protein [VEGP]) using molecular docking and molecular dynamics simulations. All protein-ligand complexes demonstrated stability, as evidenced by the root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), radius of gyration (Rg), solvent-accessible surface area (SASA), and hydrogen-bond (H-bond) plots. Furthermore, quinoline displayed higher binding efficiency with OBP, measured at -85.456 ± 8.268 kJ/mol, compared to androstenone and androstenol, as determined by molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA) calculations. Conversely, quinoline exhibited a lower binding efficacy when interacting with SAL, pheromaxein, and VEGP compared to androstenone and androstenol. These findings, in part, suggest the binding possibility of quinoline with carrier proteins and warrant further investigation to support the role of quinoline in porcine chemical communication.

R-CNN and YOLOV4 based Deep Learning Model for intelligent detection of weaponries in real time video

The security of civilians and high-profile officials is of the utmost importance and is often challenging during continuous surveillance carried out by security professionals. Humans have limitations like attention span, distraction, and memory of events which are vulnerabilities of any security system. An automated model that can perform intelligent real-time weapon detection is essential to ensure that such vulnerabilities are prevented from creeping into the system. This will continuously monitor the specified area and alert the security personnel in case of security breaches like the presence of unauthorized armed people. The objective of the proposed system is to detect the presence of a weapon, identify the type of weapon, and capture the image of the attackers which will be useful for further investigation. A custom weapons dataset has been constructed, consisting of five different weapons, such as an axe, knife, pistol, rifle, and sword. Using this dataset, the proposed system is employed and compared with the faster Region Based Convolution Neural Network (R-CNN) and YOLOv4. The YOLOv4 model provided a 96.04% mAP score and frames per second (FPS) of 19 on GPU (GEFORCE MX250) with an average accuracy of 73%. The R-CNN model provided an average accuracy of 71%. The result of the proposed system shows that the YOLOv4 model achieves a higher mAP score on GPU (GEFORCE MX250) for weapon detection in surveillance video cameras.

Identification and Validation of B-Cell Epitopes on the VP1 Protein of Parvovirus B19 through Molecular Docking and Dynamics Simulation

This study aimed to identify B-cell epitope candidates using multiple epitope identification software and in silico analysis of the modeled B19 V protein against specific antibodies using molecular docking and dynamics simulation. Materials and Methods : Full-length amino acid sequences of the VP1 protein of B19 V were retrieved from NCBI. A consensus sequence was generated using CLC sequence viewer. Linear B cell epitopes were identified using Bepipred 2.0, ABCpred, and LBTope. The linear epitope was synthesized and validated against B19 V-specific antibodies. A 3D model of the B19 V VP1 consensus protein was generated using the ITASSER server. Discontinuous B cell epitopes were identified using Discotope 2.0 and Ellipro. Molecular docking and molecular dynamics simulation was performed to investigate the interaction between the modeled B19 V protein and specific anti-B19 V antibody. Results : The identified epitope was 100% conserved and similarly identified through ABCpred and LBTope. The HADDOCK score and MDS analysis, such as hydrogen bond interactions and MMPBSA analysis, revealed that the VP1 and mAb H chains formed a significantly stable complex. The MDS demonstrated that the VP1-mAb H chain complexes had lower RMSF values around 130 to 200 residues, a region responsible for the catalytic network for enzyme activity; as a result, the flexibility of the antibody-bound VP1 decreased when compared to Apo-VP1. Conclusion: A viable epitope identified through this process was synthesized and validated using ELISA, which highlighted the role of the epitope identification process in diagnostics. This study also sheds light on the complex interplay between VP1 and the mAb H chain and highlights key binding specificity and stability determinants.

Comparative Atomistic Insights on Apo and ATP-I1171N/S/T in Nonsmall-Cell Lung Cancer

Anaplastic lymphoma kinase (ALK) rearrangements occur in about 5% of nonsmall cell lung cancer (NSCLC) patients. Despite being first recognized as EML4-ALK, fusions with several additional genes have been identified, all of which cause constitutive activation of the ALK kinase and subsequently lead to tumor development. ALK inhibitors first-line crizotinib, second-line ceritinib, and alectinib are effective against NSCLC patients with these rearrangements. Patients progressing on crizotinib had various mutations in the ALK kinase domain. ALK fusion proteins are activated by oligomerization through the fusion partner, which leads to the autophosphorylation of the kinase's domain and consequent downstream activation. The proposed computational study focuses on understanding the activation mechanism of ALK and ATP binding of wild-type (WT) and I1171N/S/T mutations. We analyzed the conformational change of ALK I1171N/S/T mutations and ATP binding using molecular docking and molecular dynamics simulation approaches. According to principal component analysis and free energy landscape, it is clear that I1171N/S/T mutations in Apo and ATP showed different energy minima/unstable structures compared to WT-Apo. The results revealed that I1171N/S/T mutations and ATP binding significantly supported a change toward an active-state conformation, whereas WT-Apo remained inactive. We demonstrated that I1171N/S/T mutations are persistent in an active state and independent of ATP. The I1171S/T mutations showed greater intermolecular H-bonds with ATP than WT-ATP. The molecular mechanics Poisson-Boltzmann surface area analysis revealed that the I1171N/S/T mutation binding energy was similar to that of WT-ATP. This study shows that I1171N/S/T can form stable bonds with ATP and may contribute to a constitutively active kinase. Based on the Y1278-C1097 H-bond and E1167-K1150 salt bridge interaction, I1171N strongly promotes the constitutively active kinase independent of ATP. This structural mechanism study will aid in understanding the oncogenic activity of ALK and the basis for improving the ALK inhibitors.

Deciphering the Impact of Rare Missense Variants in EGFR-TKI-Resistant Non-Small-Cell Lung Cancer through Whole Exome Sequencing: A Computational Approach

Targeted therapy revolutionizes the treatment of non-small-cell lung cancer (NSCLC), harboring molecular change. Epidermal growth factor receptor(EGFR) mutations play a crucial role in the development of NSCLC, serving as a pivotal factor in its pathogenesis. We elucidated the mechanisms of resistance and potential therapeutic strategies in NSCLC resistant to the EGFR-tyrosine kinase inhibitor (EGFR-TKI). This is achieved by identifying rare missense variants through whole exome sequencing (WES). The goal is to enhance our understanding, identify biomarkers, and lay the groundwork for targeted interventions, thereby offering hope for an improved NSCLC treatment landscape. We conducted WES analysis on 16 NSCLC samples with EGFR-TKI-resistant NSCLC obtained from SRA-NCBI (PRJEB50602) to reveal genomic profiles within the EGFR-TKI. Our findings showed that 48% of the variants were missense, and after filtering with the Ensembl variant effect predictor, 53 rare missense variants in 23 genes were identified as highly deleterious. Further examination using pathogenic tools like PredictSNP revealed 12 deleterious rare missense variants in 7 genes: ZNF717, PSPH, ESRRA, SEMA3G, PTPN7, CAVIN4, and MYBBP1A. Molecular dynamics simulation (MDS) suggested that the L385P variant alters the structural flexibility of ESRRA, potentially leading to unfolding of ERRα proteins. This could impact their function and alter ERRα expression. These insights from MDS enhance our understanding of the structural and dynamic consequences of the L385P ESRRA variant and provide valuable implications for subsequent therapeutic considerations and targeted interventions.

A new horizon in the phosphorylated sites of AGA: the structural impact of C163S mutation in aspartylglucosaminuria through molecular dynamics simulation

Aspartylglucosaminuria (AGU) is a lysosomal storage disorder caused by insufficient aspartylglucosaminidase (AGA) activity leading to chronic neurodegeneration. We utilized the PhosphoSitePlus tool to identify the AGA protein's phosphorylation sites. The phosphorylation was induced on the specific residue of the three-dimensional AGA protein, and the structural changes upon phosphorylation were studied via molecular dynamics simulation. Furthermore, the structural behaviour of C163S mutation and C163S mutation with adjacent phosphorylation was investigated. We have examined the structural impact of phosphorylated forms and C163S mutation in AGA. Molecular dynamics simulations (200 ns) exposed patterns of deviation, fluctuation, and change in compactness of Y178 phosphorylated AGA protein (Y178-p), T215 phosphorylated AGA protein (T215-p), T324 phosphorylated AGA protein (T324-p), C163S mutant AGA protein (C163S), and C163S mutation with Y178 phosphorylated AGA protein (C163S-Y178-p). Y178-p, T215-p, and C163S mutation demonstrated an increase in intramolecular hydrogen bonds, leading to greater compactness of the AGA forms. Principle component analysis (PCA) and Gibbs free energy of the phosphorylated/C163S mutation structures exhibit transition in motion/orientation than Wild type (WT). T215-p may be more dominant among these than the other studied phosphorylated forms. It might contribute to hydrolyzing L-asparagine functioning as an asparaginase, thereby regulating neurotransmitter activity. This study revealed structural insights into the phosphorylation of Y178, T215, and T324 in AGA protein. Additionally, it exposed the structural changes of the C163S mutation and C163S-Y178-p of AGA protein. This research will shed light on a better understanding of AGA's phosphorylated mechanism.Communicated by Ramaswamy H. Sarma.

Evaluation of Supervised Machine Learning Algorithms and Computational Structural Validation of Single Nucleotide Polymorphisms Related to Acute Liver Injury with Paracetamol

AIMS

To identify single nucleotide polymorphisms (SNPs) of paracetamol-metabolizing enzymes that can predict acute liver injury.

BACKGROUND

Paracetamol is a commonly administered analgesic/antipyretic in critically ill and chronic renal failure patients and several SNPs influence the therapeutic and toxic effects.

OBJECTIVE

To evaluate the role of machine learning algorithms (MLAs) and bioinformatics tools to delineate the predictor SNPs as well as to understand their molecular dynamics.

METHODS

A cross-sectional study was undertaken by recruiting critically ill patients with chronic renal failure and administering intravenous paracetamol as a standard of care. Serum concentrations of paracetamol and the principal metabolites were estimated. Following SNPs were evaluated: CYP2E1*2, CYP2E1_-1295G>C, CYP2D6*10, CYP3A4*1B, CYP3A4*2, CYP1A2*1K, CYP1A2*6, CYP3A4*3, and CYP3A5*7. MLAs were used to identify the predictor genetic variable for acute liver failure. Bioinformatics tools such as Predict SNP2 and molecular docking (MD) were undertaken to evaluate the impact of the above SNPs with binding affinity to paracetamol.

RESULTS

CYP2E1*2 and CYP1A2*1C genotypes were identified by MLAs to significantly predict hepatotoxicity. The predictSNP2 revealed that CYP1A2*3 was highly deleterious in all the tools. MD revealed binding energy of -5.5 Kcal/mol, -6.9 Kcal/mol, and -6.8 Kcal/mol for CYP1A2, CYP1A2*3, and CYP1A2*6 against paracetamol. MD simulations revealed that CYP1A2*3 and CYP1A2*6 missense variants in CYP1A2 affect the binding ability with paracetamol. In-silico techniques found that CYP1A2*2 and CYP1A2*6 are highly harmful. MD simulations revealed CYP3A4*2 (A>G) had decreased binding energy with paracetamol than CYP3A4, and CYP3A4*2(A>T) and CYP3A4*3 both have greater binding energy with paracetamol.

CONCLUSION

Polymorphisms in CYP2E1, CYP1A2, CYP3A4, and CYP3A5 significantly influence paracetamol's clinical outcomes or binding affinity. Robust clinical studies are needed to identify these polymorphisms' clinical impact on the pharmacokinetics or pharmacodynamics of paracetamol.

HPV and molecular mimicry in systemic lupus erythematosus and an impact of compiling B-cell epitopes and MHC-class II binding profiles with in silico evidence

Epidemiological link between HPV and SLE is evolving. The possibility of HPV infection-induced molecular mimicry and systemic lupus erythematosus (SLE) was elucidated through detailed in silico analyses. Conserved regions in the structural protein sequences of high-risk HPV types were inferred, and sequence homologies between viral and human peptides were identified to delineate proteins implicated in SLE. B-cell epitopes and MHC-class II binding were compiled using Immune Epitope Database and ProPred II analysis tool. Molecular modeling and molecular dynamics/simulation (MDS) were performed using AutoDock Vina and GROMACS, respectively. Sequence alignment revealed 32 conserved regions, and 27/32 viral peptides showed varying similarities to human peptides, rich in B-cell epitopes with superior accessibility, high hydrophilicity, antigenicity and disposition to bind many class-II HLA alleles. Molecular docking of 13 viral peptides homologous (100%) to human peptides implicated in SLE showed that VIR-PEP1 (QLFNKPYWL) and VIR-PEP2 (DTYRFVTS) exhibited higher binding affinities than corresponding human peptides to SLE predisposing HLA-DRB1 allele. MDS of these peptides showed that the viral peptides had superior folding, compactness, and a higher number of hydrogen bonds than human peptides throughout the simulation period. SASA analysis revealed that the VIR-PEP1&2 fluctuated less frequently than corresponding human peptides. MM-PBSA revealed that the VIR-PEP2 complex exhibited higher binding energy than the human peptide complex. This suggests that highly conserved structural peptides of high-risk HPV types homologous to human peptides could compete and bind avidly to the HLA allele associated with SLE and predispose HPV-infected individuals to SLE through molecular mimicry.Communicated by Ramaswamy H. Sarma.

Deciphering the miRNA-mRNA Interaction Landscape between Breast Cancer and Triple-Negative Breast Cancer: An Integrated Bioinformatics Approach

Breast cancer (BC) is globally recognized as the second most prevalent form of cancer. It predominantly affects women and can be categorized into distinct types based on the overexpression of specific cancer receptors.The key receptors implicated in this context are the human epidermal growth factor receptor-2 (HER2), estrogen receptor (ER), and progesterone receptor (PR), alongside a particularly intricate subclass known as triple-negative breast cancer (TNBC). This subclassification is critical for the stratification of breast cancer and informs therapeutic decision-making processes. Due to a lack of therapeutic targets, such as growth factor receptors, TNBC is the most aggressive type. Hence, identifying targetable regulators such as miRNAs could pave the way for potential therapeutic interventions. To identify common differentially expressed mRNAs (DE-mRNAs) in BC, including TNBC, we leveraged two data sets from the GEO collection and The Cancer Genome Atlas (TCGA). Significant DE-mRNAs were identified through PPI, MCODE, CytoNCA, and CytoHubba analyses. Following this, miRNAs were predicted using mirDIP. We utilized GSE42568, GSE185645, and TCGA and identified 159 common DE-mRNAs. Using Cytoscape plug-ins, we identified the 10 most significant DE-mRNAs in BC. Using mirDIP, target miRNAs for 10 DE-mRNAs were identified. We conducted an advanced analysis on the TNBC GEO data set (GSE45498) to corroborate the significance of shared DE-mRNAs and DE-miRNAs in TNBC. We identified four downregulated DE-miRNAs, including hsa-miR-802, hsa-miR-1258, hsa-miR-548a-3p, and hsa-miR-2053, significantly associated with TNBC. Our study revealed significant miRNA-mRNA interactions, specifically hsa-miR-802/MELK, hsa-miR-1258/NCAPG, miR-548a-3p/CCNA2, and hsa-miR-2053/NUSAP1, in both BC and TNBC. The observed downregulation of hsa-miR-548a-3p is associated with diminished survival rates in BC patients, emphasizing their potential utility as prognostic indicators. Furthermore, the differential expression of mRNAs, including CCNB2, UBE2C, MELK, and KIF2C, correlates with reduced survival outcomes, signifying their critical role as potential targets for therapeutic intervention in both BC and TNBC. These findings highlight specific regulatory mechanisms that are potentially crucial for understanding and treating these cancer types.

ZFTA-fusion in supratentorial ependymomas: low prevalence in South Asians and no correlation with survival

BACKGROUND

- Supratentorial ependymomas (STEs) are an aggressive group of ependymoma, topographically distinct from their posterior fossa and spinal counterparts. ZFTA fusion-positive cases have been reported to account for the majority of STEs, although data on its association with poorer outcomes is inconsistent.

MATERIALS AND METHODS

- We assessed the prevalence of the ZFTA-fusion by RT PCR and FISH in a cohort of 61 patients (68 samples) with STE. Our primary outcome was to determine the role of the ZFTA-fusion on progression-free and overall survival of patients with STE. Our secondary objectives were to assess the impact of ZFTA-fusion on NF-kB pathway signalling via surrogate markers of this pathway, namely COX-2, CCND1 and L1CAM.

RESULTS

- ZFTA-fusion was noted in 21.3% of STEs in our cohort. The presence of this rearrangement did not significantly impact the PFS or OS of patients with STEs and was not associated with upregulation of markers of the NF-kB pathway. Only gross total resection was significantly associated with better progression-free survival.

CONCLUSION

- In contradiction to prior reports from across the world, the ZFTA-fusion is far less prevalent among our population. It does not appear to drive NF-kB signaling or significantly affect outcomes. Gross total resection (GTR) must be attempted in all cases of STE and adjuvant radiation and/or chemotherapy employed when GTR is not achieved.

A computational examination of the therapeutic advantages of fourth-generation ALK inhibitors TPX-0131 and repotrectinib over third-generation lorlatinib for NSCLC with ALK F1174C/L/V mutations

Background: In non-small-cell lung cancer (NSCLC), a pivotal factor in promoting cancer development is the rearrangement in the anaplastic lymphoma kinase ALK gene, resulting in elevated ALK protein expression. F1174C/L/V is the acquired secondary resistant mutation in ALK. Significant survival improvements have been seen while tyrosine kinase inhibitors specifically target ALK. Nevertheless, the emergence of drug resistance hinders the clinical effectiveness of these drugs. Objective: This research sought to find the binding affinity/inhibitory effects of the existing drug lorlatinib (LOR) and upcoming TPX-0131 (zotizalkib/TPX) and repotrectinib (TPX-0005/REP) inhibitors against ALK F1174C/L/V mutations using computational approaches to identify potential strategies over resistance. Methods: We conducted molecular docking, molecular dynamics simulation, and MMPBSA calculations to investigate how compact macrocyclic inhibitors, such as TPX-0131 and repotrectinib, fit within the ATP-binding boundary and differ from LOR. Results: Our results demonstrated that TPX-0131 and repotrectinib contributed to higher binding energy in F1174C and F1174L mutations than LOR. Repotrectinib showed greater binding energy in the F1174V mutation, whereas LOR and TPX-0131 exhibited similar binding energy. However, all three inhibitors showed significant binding energy toward F1174C/L/V mutations found in NSCLC. Conclusion: This comparative study of the potential binding effects of fourth-generation inhibitors TPX-0131 and repotrectinib and third-generation inhibitor LOR for ALK F1174C/L/V mutations revealed the atomistic insights of the binding mechanism. These computational findings enable us to carry out further research for the clinical implementation of fourth-generation ALK inhibitors on ALK-positive NSCLC.

Controlling cell proliferation by targeting cyclin-dependent kinase 6 using drug repurposing approach

Cyclin-dependent kinase 6 (CDK6) is an essential kinase in cell cycle progression, which is a viable target for inhibitors in various malignancies, including breast cancer. This study aimed to virtually screen efficient compounds as new leads in treating breast cancer using a drug repurposing approach. Apoptosis regulatory compounds were taken from the seleckchem database. Molecular docking experiments were carried out in the presence of abemaciclib, a routinely used FDA drug. Compared to conventional drugs, the two compounds demonstrated a higher binding affinity for CDK6. Compounds (N-benzyl-6-[(4-hydroxyphenyl)methyl]-8-(naphthalen-1-ylmethyl)-4,7-dioxo-3,6,9,9a-tetrahydro-2H-pyrazino[1,2-a]pyrimidine-1-carboxamide) and (1'-[4-[1-(4-fluorophenyl)indol-3-yl]butyl]spiro[1H-2-benzofuran-3,4'-piperidine]) were discovered to have an inhibitory effect against CDK6 at -8.49 and -6.78kcal/mol, respectively, compared to -8.09kcal/mol of the control molecule, the interacting residues of these two new compounds were found to fall within the binding site of the CDK6 molecule. Both compounds exhibited equal ADME features compared with abemaciclib and would be well distributed and metabolized by the body with an appropriate druglikeness range. Lastly, molecular dynamics was initiated for 200ns for the selected potent inhibitors and abemaciclib as complexed with CDK6. The RMSD, RMSF, Rg, H-Bond interactions, SASA, PCA, FEL, and MM/PBSA analysis were performed for the complexes to assess the stability, fluctuations, radius of gyration, hydrogen bond interaction, solvent accessibility, essential dynamics, free energy landscape, and MM/PBSA. The selected two compounds are small molecules in the appropriate druglikeness range. The results observed in molecular docking and molecular dynamics simulations were most promising for two compounds, suggesting their potent inhibitory effect against CDK6. We propose that these candidate compounds can undergo in vitro validation and in vivo testing for their further use against cancer.