QUFIND: tool for comparative prediction and mining of G4 quadruplexes overlapping with CpG islands.

G-quadruplexes (G4s) are secondary structures in DNA that have been shown to be involved in gene regulation. They play a vital role in the cellular processes and several pathogens including bacteria, fungi, and viruses have also been shown to possess G4s that help them in their pathogenesis. Additionally, cross-talk among the CpG islands and G4s has been shown to influence biological processes. The virus-encoded G4s are affected by the mutational landscape leading to the formation/deletion of these G4s. Therefore, understanding and predicting these multivariate effects on traditional and non-traditional quadruplexes forms an important area of research, that is, yet to be investigated. We have designed a user-friendly webserver QUFIND (http://soodlab.com/qufinder/) that can predict traditional as well as non-traditional quadruplexes in a given sequence. QUFIND is connected with ENSEMBL and NCBI so that the sequences can be fetched in a real-time manner. The algorithm is designed in such a way that the user is provided with multiple options to customize the base (A, T, G, or C), size of the stem (2-5), loop length (1-30), number of bulges (1-5) as well as the number of mismatches (0-2) enabling the identification of any of the secondary structure as per their interest. QUFIND is designed to predict both CpG islands as well as G4s in a given sequence. Since G4s are very short as compared to the CpG islands, hence, QUFIND can also predict the overlapping G4s within CpG islands. Therefore, the user has the flexibility to identify either overlapping or non-overlapping G4s along with the CpG islands. Additionally, one section of QUFIND is dedicated to comparing the G4s in two viral sequences. The visualization is designed in such a manner that the user is able to see the unique quadruplexes in both the input sequences. The efficiency of QUFIND is calculated on G4s obtained from G4 high throughput sequencing data (n = 1000) or experimentally validated G4s (n = 329). Our results revealed that QUFIND is able to predict G4-quadruplexes obtained from G4-sequencing data with 90.06% prediction accuracy whereas experimentally validated quadruplexes were predicted with 97.26% prediction accuracy.

iIL13Pred: improved prediction of IL-13 inducing peptides using popular machine learning classifiers.

BACKGROUND: Inflammatory mediators play havoc in several diseases including the novel Coronavirus disease 2019 (COVID-19) and generally correlate with the severity of the disease. Interleukin-13 (IL-13), is a pleiotropic cytokine that is known to be associated with airway inflammation in asthma and reactive airway diseases, in neoplastic and autoimmune diseases. Interestingly, the recent association of IL-13 with COVID-19 severity has sparked interest in this cytokine. Therefore characterization of new molecules which can regulate IL-13 induction might lead to novel therapeutics. RESULTS: Here, we present an improved prediction of IL-13-inducing peptides. The positive and negative datasets were obtained from a recent study (IL13Pred) and the Pfeature algorithm was used to compute features for the peptides. As compared to the state-of-the-art which used the regularization based feature selection technique (linear support vector classifier with the L1 penalty), we used a multivariate feature selection technique (minimum redundancy maximum relevance) to obtain non-redundant and highly relevant features. In the proposed study (improved IL-13 prediction (iIL13Pred)), the use of the mRMR feature selection method is instrumental in choosing the most discriminatory features of IL-13-inducing peptides with improved performance. We investigated seven common machine learning classifiers including Decision Tree, Gaussian Naïve Bayes, k-Nearest Neighbour, Logistic Regression, Support Vector Machine, Random Forest, and extreme gradient boosting to efficiently classify IL-13-inducing peptides. We report improved AUC, and MCC scores of 0.83 and 0.33 on validation data as compared to the current method. CONCLUSIONS: Extensive benchmarking experiments suggest that the proposed method (iIL13Pred) could provide improved performance metrics in terms of sensitivity, specificity, accuracy, the area under the curve - receiver operating characteristics (AUCROC) and Matthews correlation coefficient (MCC) than the existing state-of-the-art approach (IL13Pred) on the validation dataset and an external dataset comprising of experimentally validated IL-13-inducing peptides. Additionally, the experiments were performed with an increased number of experimentally validated training datasets to obtain a more robust model. A user-friendly web server ( www.soodlab.com/iil13pred ) is also designed to facilitate rapid screening of IL-13-inducing peptides.

A Delphi consensus on the nomenclature and diagnosis of lichen planus pigmentosus and related entities.

BACKGROUND: Although well known in clinical practice, research in lichen planus pigmentosus and related dermal pigmentary diseases is restricted due to lack of consensus on nomenclature and disease definition. AIMS AND OBJECTIVES: Delphi exercise to define and categorise acquired dermal pigmentary diseases. METHODS: Core areas were identified including disease definition, etiopathogenesis, risk factors, clinical features, diagnostic methods, treatment modalities and outcome measures. The Delphi exercise was conducted in three rounds. RESULTS: Sixteen researchers representing 12 different universities across India and Australia agreed to be part of this Delphi exercise. At the end of three rounds, a consensus of >80% was reached on usage of the umbrella term 'acquired dermal macular hyperpigmentation'. It was agreed that there were minimal differences, if any, among the disorders previously defined as ashy dermatosis, erythema dyschromicum perstans, Riehl's melanosis and pigmented contact dermatitis. It was also agreed that lichen planus pigmentosus, erythema dyschromicum perstans and ashy dermatosis did not differ significantly apart from the sites of involvement, as historically described in the literature. Exposure to hair colours, sunlight and cosmetics was associated with these disorders in a significant proportion of patients. Participants agreed that both histopathology and dermatoscopy could diagnose dermal pigmentation characteristic of acquired dermal macular hyperpigmentation but could not differentiate the individual entities of ashy dermatosis, erythema dyschromicum perstans, Riehl's melanosis, lichen planus pigmentosus and pigmented contact dermatitis. LIMITATIONS: A wider consensus involving representatives from East Asian, European and Latin American countries is required. CONCLUSION: Acquired dermal macular hyperpigmentation could be an appropriate conglomerate terminology for acquired dermatoses characterised by idiopathic or multifactorial non-inflammatory macular dermal hyperpigmentation.

Comparative Evaluation of Microbial Contamination on the Mobile Phones Used by Dental Health-care Professionals versus Faculty of School System.

Introduction: Mobile phones are frequently used in environments of high bacteria presence. These can harbor various potential pathogens and become an exogenous source of nosocomial infections. Even in recent outbreak of COVID-19, it has become a point which needs to be sanitized to prevent and control further disease transmission as it is equally important for health-care professionals to use mobile phones in the hospital and other health and care settings, especially for communication. The present study was conducted to determine the potential role of mobile phones in the dissemination of disease. Objective: To compare the evaluation of microbial contamination on the mobile phones used by dental health-care professionals and faculty of senior secondary school and to access the microbial contamination of mobile phones by measuring the percentages of pathogens and to determine the type of bacteria commonly present on mobile phones. It also assesses the efficacy of 70% ethyl alcohol to be used as decontamination solution. Materials and Methods: A total of 126 mobile phones were screened in the study; 63 mobile phones belonging to dental health-care personnel from nine different specialties of dental college (Group 1 - test group) and 63 mobile phones belonging to nonhealth-care personnel like school teachers of senior schools (Group 2 - control group). All the samples were taken before and after cleaning with 70% ethyl alcohol. A total of 252 swab samples were taken. Results: Microbial contamination was approximately 68% in swab samples taken from mobile phones before cleaning with 70% of ethyl alcohol but even with one time disinfection with alcohol, decontamination was found to be only 95% effective. Coagulase-negative Staphylococcus was the most common isolated organism in swabs collected from dental college. Pathogenic bacteria were more prevalent in samples of dental college than to school samples. Conclusion: Ninetythree percentage of cell phones of health-care workers were contaminated and they act as potential source of nosocomial infections. Alcohol should be used to disinfect the mobile phones.

In silico analysis of SARS-CoV-2 genomes: Insights from SARS encoded non-coding RNAs.

The recent pandemic caused by Severe Acute Respiratory Syndrome Coronavirus-2 has resulted in enormous deaths around the world. Clues from genomic sequences of parent and their mutants can be obtained to understand the evolving pathogenesis of this virus. Apart from the viral proteins, virus-encoded microRNAs (miRNAs) have been shown to play a vital role in regulating viral pathogenesis. Thus we sought to investigate the miRNAs encoded by SARS-CoV-2, its mutants, and the host. Here, we present the results obtained using a dual approach i.e (i) identifying host-encoded miRNAs that might regulate viral pathogenesis and (ii) identifying viral-encoded miRNAs that might regulate host cell signaling pathways and aid in viral pathogenesis. Analysis utilizing the first approach resulted in the identification of ten host-encoded miRNAs that could target the SARS, SARS-CoV-2, and its mutants. Interestingly our analysis revealed that there is a significantly higher number of host miRNAs that could target the SARS-CoV-2 genome as compared to the SARS reference genome. Results from the second approach resulted in the identification of a set of virus-encoded miRNAs which might regulate host signaling pathways. Our analysis further identified a similar "GA" rich motif in the SARS-CoV-2 and its mutant genomes that was shown to play a vital role in lung pathogenesis during severe SARS infections. In summary, we have identified human and virus-encoded miRNAs that might regulate the pathogenesis of SARS coronaviruses and describe similar non-coding RNA sequences in SARS-CoV-2 that were shown to regulate SARS-induced lung pathology in mice.

Proteochemometric Method for pIC50 Prediction of Flaviviridae.

Viruses remain an area of concern despite constant development of antiviral drugs and therapies. One of the contributors is the Flaviviridae family of viruses causing diseases that need attention. Among other anitviral methods, antiviral peptides are being studied as viable candidates. Although antiviral peptides (AVPs) are emerging as potential therapeutics, it is important to assess the efficacy of a given peptide in terms of its bioactivity. Experimental identification of the bioactivity of each potential peptide is an expensive and time consuming task. Computational methods like proteochemometric modeling (PCM) is a promising method for prediction of bioactivity (pIC50) based on peptide and target sequence pair. In this study, we propose a prediction of pIC50 of AVP against the Flaviviridae family that may help make the decision to choose a peptide with desired efficacy. The peptides data was collected from a public database and target sequences were manually curated from literature. Features are calculated using peptide and target sequence PCM descriptors which consist of individual and cross-term features of peptide and respective target. The resultant R 2 and MAPE values are 0.85 and 8.44%, respectively, for prediction of pIC50 value of AVPs.

Time Series Analysis of SARS-CoV-2 Genomes and Correlations among Highly Prevalent Mutations.

The efforts of the scientific community to tame the recent pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seem to have been diluted by the emergence of new viral strains. Therefore, it is imperative to understand the effect of mutations on viral evolution. We performed a time series analysis on 59,541 SARS-CoV-2 genomic sequences from around the world to gain insights into the kinetics of the mutations arising in the viral genomes. These 59,541 genomes were grouped according to month (January 2020 to March 2021) based on the collection date. Meta-analysis of these data led us to identify significant mutations in viral genomes. Pearson correlation of these mutations led us to the identification of 16 comutations. Among these comutations, some of the individual mutations have been shown to contribute to viral replication and fitness, suggesting a possible role of other unexplored mutations in viral evolution. We observed that the mutations 241C>T in the 5' untranslated region (UTR), 3037C>T in nsp3, 14408C>T in the RNA-dependent RNA polymerase (RdRp), and 23403A>G in spike are correlated with each other and were grouped in a single cluster by hierarchical clustering. These mutations have replaced the wild-type nucleotides in SARS-CoV-2 sequences. Additionally, we employed a suite of computational tools to investigate the effects of T85I (1059C>T), P323L (14408C>T), and Q57H (25563G>T) mutations in nsp2, RdRp, and the ORF3a protein of SARS-CoV-2, respectively. We observed that the mutations T85I and Q57H tend to be deleterious and destabilize the respective wild-type protein, whereas P323L in RdRp tends to be neutral and has a stabilizing effect. IMPORTANCE We performed a meta-analysis on SARS-CoV-2 genomes categorized by collection month and identified several significant mutations. Pearson correlation analysis of these significant mutations identified 16 comutations having absolute correlation coefficients of >0.4 and a frequency of >30% in the genomes used in this study. The correlation results were further validated by another statistical tool called hierarchical clustering, where mutations were grouped in clusters on the basis of their similarity. We identified several positive and negative correlations among comutations in SARS-CoV-2 isolates from around the world which might contribute to viral pathogenesis. The negative correlations among some of the mutations in SARS-CoV-2 identified in this study warrant further investigations. Further analysis of mutations such as T85I in nsp2 and Q57H in ORF3a protein revealed that these mutations tend to destabilize the protein relative to the wild type, whereas P323L in RdRp is neutral and has a stabilizing effect. Thus, we have identified several comutations which can be further characterized to gain insights into SARS-CoV-2 evolution.

Novel insights into host responses to Japanese Encephalitis Virus infection: Reanalysis of public transcriptome and microRNAome datasets.

PURPOSE: Japanese encephalitis (JE), caused by the Japanese encephalitis virus (JEV), is the principal cause of viral encephalitis in South-East Asian and Western Pacific countries; accounting for 68,000 cases, and up to 20,400 fatalities, annually across the world. Despite being a high-risk condition, there is no specific treatment for JE. Given rapid additions in genomics databases and the power of data reanalysis in addressing critical medical questions, the present study was designed to identify novel host factors that might have potential roles in JEV infection. METHODS: We extracted microarray and RNA-Seq data sets from NCBI-GEO and compared mock and JEV-infected samples. Raw data from all the studies were re-analyzed to identify host factors associated with JEV replication. RESULTS: We identified several coding and non-coding host factors that had no prior known role in viral infections. Of these, the coding transcripts: Myosin Heavy Chain 10 (MYH10), Progestin and AdipoQ Receptor Family Member 8 (PAQR8), and the microRNAs: hsa-miR-193b-5p, hsa-miR-3714 and hsa-miR-513a-5p were found to be novel host factors deregulated during JEV infection. MYH10 encodes a conventional non-muscle myosin, and mutations in MYH10 have been shown to cause neurological defects. PAQR8 has been associated with epilepsy, which exhibits symptoms similar to JEV infection. JE is a neuro-degenerative disease, and the known involvement of MYH10 and PAQR8 in neurological disorders strongly indicates potential roles of these host factors in JEV infection. Additionally, we observed that MYH10 and PAQR8 had a significant negative correlation with Activating transcription factor 3 (ATF3), which is a previously validated modulator of JEV infection. ATF3 is a transcription factor that binds to the promotors of genes encoding other transcription factors or interferon-stimulated genes and negatively regulates host antiviral responses during JE. CONCLUSION: Our findings demonstrate the significance of data reanalysis in the identification of novel host factors that may become targets for diagnosis/ therapy against viral diseases of major concern, such as, JE. The deregulated coding and non-coding transcripts identified in this study need further experimental analysis for validation.

A prospective real-world study evaluating serum levels of arginine and cysteine in women with chronic telogen effluvium: do we really need blanket prescription of amino acid supplementation?

Amino acids form a major component of hair fibres and are prescribed routinely in the form of nutritional supplements in patients with chronic telogen effluvium (CTE). Such a practice is based on assumption of a nutritional deficiency state in such patients. In this prospective study, we evaluated the serum levels of cysteine and arginine in 30 women with CTE and in healthy controls. We found no significant difference between the two groups in terms of serum arginine levels. Cysteine levels were higher in patients with CTE (P < 0.001). No correlation was found between levels of serum amino acids (cysteine and arginine) and either diet type (vegetarian or not) or body mass index, and no significant correlation between levels of the two amino acids and severity of disease. Our work suggests that arginine and cysteine deficiency is not present in women with CTE. Supplementation is unlikely to be of any benefit in nutrient-replete populations and only adds to the cost of therapy.

A novel binary k-mer approach for classification of coding and non-coding RNAs across diverse species.

Classification among coding sequences (CDS) and non-coding RNA (ncRNA) sequences is a challenge and several machine learning models have been developed for the same. Since the frequency of curated CDS is many-folds as compared to that of the ncRNAs, we devised a novel approach to work with the complete datasets from fifteen diverse species. In our proposed binary approach, we replaced all the 'A's and 'T's with '0's and 'G's and 'C's with '1's to obtain a binary form of CDS and ncRNAs. The k-mer analysis of these binary sequences revealed that the frequency of binary patterns among the CDS and ncRNAs can be used as features to distinguish among them. Using insights from these distinguishing frequencies, we used k-nearest neighbor classifier to classify among them. Our strategy is not only time-efficient but leads to significantly increased performance metrics in terms of Matthews Correlation Coefficient (MCC), Accuracy, F1 score, Precision, Recall and AUC-ROC, for species like P. paniscus, M. mulatta, M. lucifugus, G. gallus, C. japonica, C. abingdonii, A. carolinensis, D. melanogaster and C. elegans when compared with the conventional ATGC approach. Additionally, we also show that the performance obtained for diverse species tested on the model based on H. sapiens, correlated with the geological evolutionary timeline, thereby further strengthening our approach. Therefore, we propose that CDS and ncRNAs can be efficiently classified using "2-character" binary frequency as compared to "4-character" frequency of ATGC approach. Thus, our highly efficient binary approach can replace the more complex ATGC approach successfully.

Adjunctive use of saturated solution of potassium iodide (SSKI) with liposomal amphotericin B (L-AMB) in mucormycosis achieves favorable response, shortened dose and duration of amphotericin: A retrospective study from a COVID-19 tertiary care center.

PURPOSE: Second wave of COVID-19 pandemic was associated with an unprecedented rise in cases of mucormycosis, treatment of which has been challenging owing to the availability and side effects associated with amphotericin. METHODS: All patients presenting with rhino-orbital cerebral mucormycosis (ROCM) following COVID-19 infection between April 2021 to June 2021 were included in this retrospective interventional study. Primary objective was to assess the clinical response with combination of intravenous liposomal amphotericin B (4-5 mg/kg/day) and saturated solution of potassium iodide (SSKI) given orally along with surgical debridement. RESULTS: Twenty-five patients of ROCM were treated with the regimen. Mean age and fasting blood sugar levels were 53.48 years and 239.64 mg/dL respectively. All patients had history of intake of steroids with a mean daily dose of 86.39 mg of prednisolone equivalent. 88% of patients had a "proven" diagnosis of mucormycosis. Cultures were positive in 52% of patients with Rhizopus arrhizus as the predominant species. The mean daily dose of amphotericin received was 268 mg/day with a mean duration of 9.52 days. Mean daily dose of SSKI was 2.57 g. 21 patients (84%) had stabilization of disease at week 8 and achieved cure at the end of treatment whereas the mortality rate was 16%. Factors that significantly affected outcome were eye and central nervous system (CNS) involvement on presentation. CONCLUSION: SSKI, with its remarkably low cost and safety profile, makes it a potential adjuvant drug that may help achieve the twin benefits of shortened duration and dose of LAMB.