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The emergence of antifungal drug resistance in Candida species has led to increased morbidity and mortality in immunocompromised patients. Understanding species distribution and antifungal drug resistance patterns is an essential step for novel drug development. A systematic review was performed addressing this challenge in India with keywords inclusive of ‘Candida’, ‘Antifungal Drug Resistance’, ‘Candidemia’, ‘Candidiasis’ and ‘India’. A total of 106 studies (January 1978–March 2020) from 20 Indian states were included. Of over 11,429 isolates, Candida albicans was the major species accounting for 37.95% of total isolates followed by C. tropicalis (29.40%), C. glabrata (11.68%) and C. parapsilosis (8.36%). Rates of antifungal resistance were highest in non-albicans Candida (NAC) species - C. haemuloni (47.16%), C. krusei (28.99%), C. lipolytica (28.89%) and C. glabrata (20.69%). Approximately 10.34% isolates of C. albicans were observed to be drug resistant. Candida species were frequently resistant to certain azoles (ketoconazole-22.2%, miconazole–22.1% and fluconazole–21.8%). In conclusion, the present systematic review illustrates the overall distribution and antifungal resistance pattern of Candida species among the Indian population that could be helpful in the future for the formation of treatment recommendations for the region but also elsewhere. Lay Summary A total of 106 studies were reviewed to define the prevalence, distribution and antifungal resistance pattern of Candida species in India. The presented data could become the point of reference for all reported findings on Candida species in India.

Background: Calcium-based and non-calcium-based phosphate binders are frequently used to treat hyperphosphatemia in patients with chronic kidney disease (CKD). Objectives: This study aimed to compare the effects of calcium acetate and sevelamer carbonate on the progression of aortic vascular calcification in patients with CKD stages 4 and 5. Methods: This was an open-label randomized prospective comparative study, in which the participants encompassed both male and female patients with ambulatory hyperphosphatemic CKD stages 4 and 5 aged above 18 years. One hundred fifty patients with CKD stages 4 and 5 were screened for Aortic vascular calcification using digital X-ray lumbar spine and multi-slice CT scan, of whom fifty patients with vascular calcification were selected and randomly assigned into two groups. The participants were then serially studied for the effects of phosphate binders on the progression of vascular calcification over one year. One group was prescribed calcium acetate, and the other group was prescribed sevelamer carbonate. Results: Fifty hyperphosphatemic CKD patients with a mean age of 57 years were randomly assigned into two groups. There was no statistically significant difference between the two groups; however, the patients assigned to the sevelamer group were older and higher aortic calcification index (ACI) (P = 0.035) and Kauppila scores (P = 0.04), and elevated serum calcium (P = 0.04), Ca X PO4 (P = 0.006), and vitamin D. In calcium acetate-treated patients, the mean ACI increased significantly during six months and one year; however, the increase was not significant in the sevelamer group. Serum cholesterol, serum triglycerides, serum iPTH level, and the inflammatory markers of atherosclerosis-high sensitivity of C-reactive protein (hs-CRP), interleukin-6 (IL-6), decreased significantly in the sevelamer group. Conclusions: The prevalence of vascular (abdominal aortic) calcification in pre-ESRD (CKD stage 4 and 5) patients was 75%. Abdominal aortic calcification increased significantly in calcium acetate-treated patients during six months and one year; however, the progression was not significant regarding sevelamer. Because of its pleiotropic properties, sevelamer is more effective and consistent in retarding the progression of vascular calcification than calcium acetate in patients with CKD stages 4 and 5.

Vascular calcification is one of the independent risk factors associated with cardiovascular disease (CVD) in chronic kidney disease (CKD) patients. This study evaluated the prevalence of vascular calcification in Indian patients with CKD stages 4 and 5. This was a prospective study conducted between January 2011 and June 2012. CKD stage 4 and 5 patients of either sex aged >18 years were screened for aortic vascular calcification using digital X-ray lumbar spine and multislice computed tomography (CT) scan. In addition, details of inflammatory markers [high-sensitivity C-reactive protein (hs-CRP) and interleukin (IL-6)] were also collected. A total of 150 patients (stage 4, n = 98; stage 5, n = 56) were screened for vascular calcification, and the mean age was 56.56 years. Patients with CKD stage 5 had significantly higher (P ≤0.05) serum creatinine and lower estimated glomerular filtration rate, total cholesterol, and low-density lipoprotein than CKD stage 4. Significantly, more patients with CKD stage 5 had a history of CVD. A total of 113 (75.3%) patients had vascular calcification [aortic calcification index (ACI) >0] with significantly higher prevalence in CKD stage 5 (85.72%) as compared to CKD stage 4 (69.15%). Patients having high aortic calcification (ACI >20%) were older (P = 0.0013); had a higher frequency of diabetes, and CVD; and had significantly (P

Soft Biometrics is a growing field that has been known to improve the recognition system as witnessed in the past decade. When combined with hard biometrics like iris, gait, fingerprint recognition etc. it has been seen that the efficiency of the system increases many folds. With the Pandemic came the need to recognise faces covered with mask in an efficient way- soft biometrics proved to be an aid in this. While recent advances in computer vision have helped in the estimation of age and gender - the system could be improved by extending the scope and detecting quite a few other soft biometric attributes that helps us in identifying a person, including but not limited to - eyeglasses, hair type and color, mustache, eyebrows etc. In this paper we propose a system of identification that uses the ocular and forehead part of the face as modalities to train our models that uses transfer learning techniques to help in the detection of 12 soft biometric attributes (FFHQ dataset) and 25 soft biometric attributes (CelebA dataset) for masked faces. We compare the results with the unmasked faces in order to see the variation of efficiency using these data-sets Throughout the paper we have implemented 4 enhanced models namely - enhanced Alexnet ,enhanced Resnet50, enhanced MobilenetV2 and enhanced SqueezeNet. The enhanced models apply transfer learning to the normal models and aids in improving accuracy. In the end we compare the results and see how the accuracy varies according to the model used and whether the images are masked or unmasked. We conclude that for images containing facial masks - using enhanced MobileNet would give a splendid accuracy of 92.5% (for FFHQ dataset) and 87% (for CelebA dataset).

The emergence of multidrug-resistant strains of Candida albicans has become a global threat mostly due to co-infection with immune-compromised patients leading to invasive candidiasis. The life-threatening form of the disease can be managed quickly and effectively by drug repurposing. Thus, the study used in silico approaches to evaluate Food and Drug Administration (FDA) approved drugs against three drug targets-TRR1, TOM40, and YHB1. The tertiary structures of three drug targets were modeled, refined, and evaluated for their structural integrity based on PROCHECK, ERRAT, and PROSA. High-throughput virtual screening of FDA-approved drugs (8815), interaction analysis, and energy profiles had revealed that DB01102 (Arbutamine), DB01611 (Hydroxychloroquine), and DB09319 (Carindacillin) exhibited better binding affinity with TRR1, TOM40, and YHB1, respectively. Notably, the molecular dynamic simulation explored that Gln45, Thr119, and Asp288 of TRR1; Thr107 and Ser121 of TOM40; Arg193, Glu213, and Ser228 of YHB1 are crucial residues for stable drug-target interaction. Additionally, it also prioritized Arbutamine-TRR1 as the best drug-target complex based on MM-PBSA (-52.72 kcal/mol), RMSD (2.43 A), and radius of gyration (-21.49 A) analysis. In-depth, PCA results supported the findings of molecular dynamic simulations. Interestingly, the conserved region (>70%) among the TRR1 sequences from pathogenic Candida species indicated the effectiveness of Arbutamine against multiple species of Candida as well. Thus, the study dispenses new insight and enriches the understanding of developing an advanced technique to consider potential antifungals against C. albicans. Nonetheless, a detailed experimental validation is needed to investigate the efficacy of Arbutamin against life-threatening candidiasis.

Background: Myopia, commonly referred to as short sightedness is a form of refractive error and is a very common cause of visual disability throughout the world. Methods: Hospital based prospective study conducted on 100 patients of Myopia attending to Department of Opthalmolgy. Results: There was no significant difference in the age, gender distribution, baseline myopia progression or follow-up duration between patients who used night application compared with daytime atropine. Effectiveness was better with daytime application. Conclusion: 1% atropine eye drops were well tolerated and efficacious for the retardation of progressive myopia in Indian eyes. Effectiveness was better with daytime application. Further studies are necessary to assess the role of 1% atropine in the rapid progressors and patients poorly responding to low-dose atropine. Keywords: Myopia, Atropine, low dose.

Introduction: Tobacco-smoking is one of the most important risk factor for preterm delivery, pregnancy loss, low birth weight, and fetal growth restriction. It is estimated that approximate...

Wealth of structural data on theurapeutic targets in complex with monoclonal antibodies (mAbs) and advances in molecular modeling algorithms present exciting opportunities in the field of novel biologic design. Interleukin 23 (IL23), a well-known drug target for autoimmune diseases, in complex with mAb 7G10 offers prospect to design potent lead antibodies by traversing the complete epitope-paratope interface. Herein, key interactions aiding antibody-based neutralization in IL23-7G10 complex are resolute through PyMOL, LigPlot

Psoriasis is a systemic hyperproliferative inflammatory skin disorder, although rarely fatal but significantly reduces quality of life. Understanding the full genetic component of the disease association may provide insight into biological pathways as well as targets and biomarkers for diagnosis, prognosis and therapy. Studies related to psoriasis associated genes and genetic markers are scattered and not easily amendable to data-mining. To alleviate difficulties, we have developed dbGAPs an integrated knowledgebase representing a gateway to psoriasis associated genomic data. The database contains annotation for 202 manually curated genes associated with psoriasis and its subtypes with cross-references. Functional enrichment of these genes, in context of Gene Ontology and pathways, provide insight into their important role in psoriasis etiology and pathogenesis. The dbGAPs interface is enriched with an interactive search engine for data retrieval along with unique customized tools for Single Nucleotide Polymorphism (SNP)/indel detection and SNP/indel annotations. dbGAPs is accessible at http://www.bmicnip.in/dbgaps/ .

The recent outbreaks of Zika virus and the absence of a specific therapy have necessitated to identify T-cell-stimulating antigenic peptides as potential subunit vaccine candidates. The translated ssRNA (+) genome of Zika virus was explored in EMBOSS antigenic and VaxiJen to predict 63 peptides as potential antigens. Three MHC-II binding peptide prediction tools, viz. NetMHCIIpan, PREDIVAC and immune epitope database (IEDB) were employed in consensus on 63 antigenic peptides to propose 14 T-helper cell epitopes. Similarly, analysis on 63 antigenic peptides through NetMHC, NetCTL and IEDB MHC-I binding peptide prediction tool led to identification of 14 CTL epitopes. Seven T-cell epitopes, C:44-66, M:135-149, NS2A:124-144, NS3:421-453, NS3:540-554, NS4B:90-134 and NS4B:171-188, are observed to share overlapping MHC-I and MHC-II binding motifs and hence, are being proposed to constitute minimum T-cell antigens to elicit protective T-cell immune response against Zika. Three of them, C:44-66, NS3:421-453 and NS3:540-554 are identified to be conserved across all the selected strains of Zika virus. Moreover, the 21 T-cell epitopes are non-self to humans and exhibited good coverage in variable populations of 14 geographical locations. Therefore, 21 T-cell epitopes are proposed as potential subunit vaccines against Zika virus. Electronic supplementary material The online version of this article (10.1007/s12539-017-0238-3) contains supplementary material, which is available to authorized users.

Computer-aided antibody engineering has been successful in the design of new biologics for disease diagnosis and therapeutic interventions. Interleukin-6 (IL-6), a well-recognized drug target for various autoimmune and inflammatory diseases such as rheumatoid arthritis, multiple sclerosis, and psoriasis, was investigated in silico to design potential lead antibodies. Here, crystal structure of IL-6 along with monoclonal antibody olokizumab was explored to predict antigen-antibody (Ag - Ab)-interacting residues using DiscoTope, Paratome, and PyMOL. Tyr56, Tyr103 in heavy chain and Gly30, Ile31 in light chain of olokizumab were mutated with residues Ser, Thr, Tyr, Trp, and Phe. A set of 899 mutant macromolecules were designed, and binding affinity of these macromolecules to IL-6 was evaluated through Ag - Ab docking (ZDOCK, ClusPro, and Rosetta server), binding free-energy calculations using Molecular Mechanics/Poisson Boltzman Surface Area (MM/PBSA) method, and interaction energy estimation. In comparison to olokizumab, eight newly designed theoretical antibodies demonstrated better result in all assessments. Therefore, these newly designed macromolecules were proposed as potential lead antibodies to serve as a therapeutics option for IL-6-mediated diseases.

C. albicans infections are increasingly becoming a threat to public health with emergence of drug resistant strains. It emphasizes the need to look for alternate drug targets through genome-wide screening. In the present study, whole proteome of C. albicans SC5314 was analyzed in single click target mining workflow of TiDv2. A protein-protein interaction network (PPI) for the resulting putative targets was generated based on String database. Ninety four proteins with higher connectivity (degree ≥ 10) in the network are noted as hub genes. Among them, 24 are observed to be known targets while 70 are novel ones. Further, chokepoint analysis revealed FAS2, FOL1 and ERG5 as chokepoint enzymes in their respective pathways. Subsequently, the chokepoints were selected as prior interest for in silico gene knockout via MATLAB and COBRA Toolbox. In silico gene knockout pointed that FAS2 inhibition reduced the growth rate of pathogen from 0.2879 mmol.gDW−1.h−1 to zero. Furthermore, enzyme inhibition assay of FAS2 with cerulenin strengthen the computational outcome with MIC 1.25 μg/mL. Hence, the study establishes FAS2 as a promising target to design therapeutics against C. albicans.

Leptospirosis is one of the leading zoonotic infections worldwide. As with other infectious diseases, report of antimicrobial resistance to existing therapeutic arsenal poses challenges in the management of disease. Hence, identification of novel drug targets for the pathogen deems essential. Present study used combined approach of comparative and subtractive genomics to identify putative drug targets. Crucial genes of 16 pathogenic Leptospira strains were filtered and subjected to homology search via target identification tool "TiD". Thereafter, comparative analysis was performed for non-homologous, essential genes to accomplish the broad-spectrum drug target. Consequently, 37 essential genes were found to be conserved in at least 10 strains of Leptospira. Further, prioritization of resultant set of genes revealed 18 were hubs in protein-protein interaction network. Sixteen putative targets among the hub genes were conserved in all strains of Leptospira. Out of sixteen, fourteen were enzymes while 8 were novel and 4 were involved in virulence mechanism. In addition, genome scale metabolic network reconstruction and choke point analysis revealed cobA (porphyrin and chlorophyll metabolism) and thiL (thiamine metabolism) as chokepoints in their respective metabolic pathways. The proposed hub genes could act as putative broad-spectrum drug targets for Leptospira species, however, these putative targets should be validated to ensure them as real one prior to utilizing them for target based lead discovery.