Green synthesis, antibacterial and antifungal evaluation of new thiazolidine-2,4-dione derivatives: molecular dynamic simulation, POM study and identification of antitumor pharmacophore sites.

In this study, a series of thiazolidine-2,4-dione derivatives 3a-i were synthesized and evaluated for antibacterial activity against Gram-positive and Gram-negative strains of Bacillus licheniformis, Escherichia coli, Pseudomonas aeruginosa and Staphylococcus aureus. Newly prepared thiazolidine (TZD) derivatives were further screened separately for in vitro antifungal activity against cultures of fungal species, namely, Aspergillus niger, Alternaria brassicicola, Chaetomium murorum, Fusarium oxysporum, Lycopodium sp. and Penicillium notatum. The electron-donating substituents (-OH and -OCH3) and electron-withdrawing substituents (-Cl and -NO2) on the attached arylidene moieties of five-membered heterocyclic ring enhanced the broad spectrum of antimicrobial and antifungal activities. The molecular docking study has revealed that compound 3h strongly interacts with the catalytic residues of the active site of the ß-carbonic anhydrase (P. aeruginosa) and has the best docking score. In silico pharmacokinetics studies showed the drug-likeness and non-toxic nature of the synthesized compounds, which indicates the combined antibacterial, antiviral and antitumor pharmacophore sites of the targeted drug. This work demonstrates that potential TZD derivatives bind to different types of bacterial and fungal pathogens for circumventing their activities and opens avenues for the development of newer drug candidates that can target bacterial and fungal pathogens.Communicated by Ramaswamy H. Sarma.

Theoretical, antioxidant, antidiabetic and in silico molecular docking and pharmacokinetics studies of heteroleptic oxovanadium(IV) complexes of thiosemicarbazone-based ligands and diclofenac.

A series of new heteroleptic oxovanadium(IV) complexes with the general formula [VOL1-6(Dcf)] (1-6), where L1-6 = thiosemicarbazone (TSC)-based ligands and Dcf = diclofenac have been synthesized and characterized. The spectral studies along with the density functional theory calculations evidenced the distorted square-pyramidal geometry around oxovanadium(IV) ion through imine nitrogen and thione sulfur atoms of TSC moiety, and two asymmetric carboxylate oxygen atoms of diclofenac drug. The complexes were evaluated for in vitro antioxidant activity using 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS), 2,2'-diphenyl-1-picrylhydrazyl (DPPH), hydrogen peroxide (H2O2) and superoxide radical scavenging assays with respect to the standard antioxidant drugs butylated hydroxyanisole (BHA) and rutin. The in vitro antidiabetic activity of the complexes was tested with enzymes such as α-amylase, α-glucosidase and glucose-6-phosphatase. The complexes containing methyl substituent showed higher activity than that containing the nitro substituent due to the electron-donating effect of methyl group. The in silico molecular docking studies of the oxovanadium(IV) complexes with α-amylase and α-glucosidase enzymes showed strong interaction via hydrogen bonding and hydrophobic interactions. The dynamic behavior of the proposed complexes was analyzed by molecular dynamics (MDs) simulations, which revealed the stability of docked structures with α-amylase and α-glucosidase enzymes. The in silico physicochemical and pharmacokinetics parameters, such as Lipinski's 'rule of five', Veber's rule and absorption, distribution, metabolism and excretion (ADME) properties predicted non-toxic, non-carcinogenic and safe oral administration of the synthesized complexes.Communicated by Ramaswamy H. Sarma.

Novel Biomarker Prediction for Lung Cancer Using Random Forest Classifiers.

Lung cancer is considered the most common and the deadliest cancer type. Lung cancer could be mainly of 2 types: small cell lung cancer and non-small cell lung cancer. Non-small cell lung cancer is affected by about 85% while small cell lung cancer is only about 14%. Over the last decade, functional genomics has arisen as a revolutionary tool for studying genetics and uncovering changes in gene expression. RNA-Seq has been applied to investigate the rare and novel transcripts that aid in discovering genetic changes that occur in tumours due to different lung cancers. Although RNA-Seq helps to understand and characterise the gene expression involved in lung cancer diagnostics, discovering the biomarkers remains a challenge. Usage of classification models helps uncover and classify the biomarkers based on gene expression levels over the different lung cancers. The current research concentrates on computing transcript statistics from gene transcript files with a normalised fold change of genes and identifying quantifiable differences in gene expression levels between the reference genome and lung cancer samples. The collected data is analysed, and machine learning models were developed to classify genes as causing NSCLC, causing SCLC, causing both or neither. An exploratory data analysis was performed to identify the probability distribution and principal features. Due to the limited number of features available, all of them were used in predicting the class. To address the imbalance in the dataset, an under-sampling algorithm Near Miss was carried out on the dataset. For classification, the research primarily focused on 4 supervised machine learning algorithms: Logistic Regression, KNN classifier, SVM classifier and Random Forest classifier and additionally, 2 ensemble algorithms were considered: XGboost and AdaBoost. Out of these, based on the weighted metrics considered, the Random Forest classifier showing 87% accuracy was considered to be the best performing algorithm and thus was used to predict the biomarkers causing NSCLC and SCLC. The imbalance and limited features in the dataset restrict any further improvement in the model's accuracy or precision. In our present study using the gene expression values (LogFC, P Value) as the feature sets in the Random Forest Classifier BRAF, KRAS, NRAS, EGFR is predicted to be the possible biomarkers causing NSCLC and ATF6, ATF3, PGDFA, PGDFD, PGDFC and PIP5K1C is predicted to be the possible biomarkers causing SCLC from the transcriptome analysis. It gave a precision of 91.3% and 91% recall after fine tuning. Some of the common biomarkers predicted for NSCLC and SCLC were CDK4, CDK6, BAK1, CDKN1A, DDB2.

Identification of novel regulatory pathways across normal human bronchial epithelial cell lines (NHBEs) and peripheral blood mononuclear cell lines (PBMCs) in COVID-19 patients using transcriptome analysis.

The SARS-CoV-2 is one of the most infectious and deadly coronaviruses, which has gripped the world, causing the COVID-19 pandemic. Despite the numerous studies being conducted on this virus, many uncertainties are with the disease. This is exacerbated by the speedy mutations acquired by the viral strain, which enables the disease to present itself differently in different people, introducing new factors of uncertainty. This study aims at the identification of regulatory pathways across two cell lines, namely, the peripheral blood mononuclear cell line (PBMC) and the normal human bronchial epithelial (NHBE) cell line. Both the above-mentioned cell lines were considered because they support viral replication. Furthermore, the NHBE cell line captures vital changes in the lungs, which are the main organs affected by the COVID-19 patients, and the PBMC cell line is closely linked to the body's immune system. RNA-Seq analysis, differential gene expression and gene set enrichment analysis for pathway identification were followed. Pathway analysis throws light upon the various systems affected in the body due to the COVID-19. Gene regulatory networks associated with the significant pathways were also designed. These networks aid in identifying various gene targets, along with their interactions. Studying the functionality of the pathways and the gene interactions associated with them, aided by long COVID studies, will provide immense clarity about the current COVID-19 scenario. In the long term, this will help in the design of therapeutic approaches against the SARS-CoV-2 and can also contribute to drug repurposing studies. Ultimately, this study identifies and analyses the relationship of various undiscovered or lesser explored pathways in the human body to the SARS-CoV-2 and establish a clearer picture of the association to help streamline further studies and approaches.

Clinico-demographic profile and outcomes of 25-gauge vitrectomy in advanced stage 5 retinopathy of prematurity.

BACKGROUND: Stage 5 retinopathy of prematurity is a difficult condition to treat despite technological advances in vitreous surgery. METHODS: A retrospective chart review of all consecutive cases of stage 5 ROP was performed between December 2016 and December 2018, and 21 babies were included for assessment of surgical outcomes using a modified vitrectomy technique. Data extracted from documents included demography, ROP screening status, preoperative prophylactic therapy, clinical presentation, surgery performed, and postsurgical outcomes. RESULTS: Out of the 21 babies, ophthalmologist screening was done in 42.9%. Mean birth weight was 1185 ± 222.4 g with a mean gestational age of 29.86 ± 2.0 weeks and mean post-menstrual age of 44.55 ± 9.82 weeks. Lesser than stage 5 disease was seen in 16.7% of eyes and they were managed accordingly. Seventy percent of babies had bilateral disease. 21 eyes underwent 25-gauge pars plicata vitrectomy using a modified technique. After an average follow-up duration of 6.33 ± 2.18 months, the final macular attachment rate was 19%. Anteriorly closed-posteriorly closed type configuration of retinal detachments had a poorer outcome. Fix and follow visual acuity was achieved in 23.8% of eyes, while 57.1% of eyes had a perception of light. CONCLUSIONS: Management of stage 5 ROP is mostly surgical; however, the risk of ending up with a poor vision or vision loss is high, irrespective of whether surgery is performed. The modified surgical technique with a spacer described in this study may help in better manipulation of instruments inside the vitreous cavity.

Mandibular metastasis of thyroid carcinoma: a case report.

Metastatic carcinomas to the jaw bones are uncommon and comprise to about 1% of all malignant oral neoplasms. It may be the first indication of an unknown malignancy from a distant primary site which is usually associated with poor prognosis. We report a rare case of thyroid carcinoma metastatic to the mandible in a 76-year-old elderly male patient in which the lesion was asymptomatic. Microscopic examination revealed a tumour structure consisting of cords and islands of infiltrating epithelium. The immunohistochemical marker, thyroid transcription factor -1 was done which showed a positive staining by the follicular cells. The tumour was diagnosed as metastatic follicular thyroid carcinoma. It should be emphasized that histopathological diagnosis along with panel of markers play an important role in diagnosing the site of origin of bone metastasis and these lesions should be included in the differential diagnosis of asymptomatic jaw lesions.

Enhanced diradical nature in oxyallyl derivatives leads to near infra red absorption: a comparative study of the squaraine and croconate dyes using computational techniques.

We apply many criteria to estimate the diradical character of the ground state singlets of several oxyallyl derivatives. This is carried out as the oxyallyl derivatives like squaraine and croconate dyes can be represented by both mesoionic and diradical formulas, the domination of which would characterize its lowest energy transition. One criterion applied is the singlet-triplet gap, which is known to be inversely proportional to the diradical character. Another criterion is the occupation number; this is determined for the symmetry broken state of the molecules in the unrestricted formalism, and the difference of occupation in the HOMO and LUMO is related to the diradical character. The diradical character of all of the croconates and few squaraines is estimated to be large. All of these have absorption above 750 nm and can be classified as near infrared (NIR) dyes, leading to the inference that NIR absorptions in these molecules are largely due to the dominance of the diradical character. To understand the reliability of the DFT methods for the absorption property predictions of these molecules, TD-DFT studies to calculate the vertical excitation energies have been carried out, using the B3LYP/ BLYP exchange correlation functionals and the LB94 asymptotic functional with and without the inclusion of solvent. The deviations, in both the squaraine series (average lower diradical character), are found to be systematic, and with the inclusion of the solvent in the calculation, the deviations decrease. The best least-squares fit with the experimentally observed values using B3LYP /6-311G(d, p) for the symmetric squaraines yields an R value of 0.92 and, for the unsymmetric squaraines, an R value of 0.936. With inclusion of the solvent, the R value is 0.96 for the symmetric squaraines and 0.961 for the unsymmetric squaraines, indicating that these DFT functionals with linear scaling may be used to study these systems. The croconate dyes, however, have larger deviation from the experimentally observed values in all of the functionals studied even after inclusion of the solvent effects. The deviations are also not systematic. The deviation with respect to the experiment in this case is attributed to the average larger diradical character in this series.