Matrix Metalloproteinase-7 Promoter Site Single Nucleotide Polymorphism (-181A>G) in Epithelial Ovarian Cancer in the Eastern Indian Population.

BACKGROUND: Matrix metalloproteinase-7 (MMP7) plays multiple roles in different stages of tumor development. Elevated MMP7 activity has been reported in ovarian cancer. Single nucleotide polymorphism (SNP) of promoter sites of the MMP7 gene has been shown to cause alteration in gene expression, hence resulting in changes in susceptibility to various diseases and tumor development. METHODS: The current study evaluated the association of epithelial ovarian cancer risk with MMP7 promoter site -181A>G polymorphism in the population of eastern India. The present case-control study included 64 histopathologically confirmed cases of epithelial ovarian cancer and 100 control subjects. The MMP7 -181A/G polymorphism was identified using polymerase chain reaction-restriction fragment length polymorphism. The association between genotypes and epithelial ovarian cancer risk was analyzed by odds ratio (OR) with a 95% confidence interval. RESULTS: The frequencies of AA, AG, and GG genotypes in ovarian cancer cases were 37.5%, 46.9%, and 15.6%, respectively, while that of control subjects were 56%, 36%, and 8%, respectively, in the study population. By taking the wild-type AA genotype as a reference, it was found that genotype GG was associated with a significant risk for epithelial ovarian cancer (OR: 2.92). Frequency distribution of genotypes did not show any significant association with tumor characteristics like the International Federation of Gynecology and Obstetrics (FIGO) stage, histology, lymph node status, and distant metastasis. CONCLUSION: The present study demonstrated the association of MMP7 promoter site -181 GG genotype and the G allele with increased risk for epithelial ovarian cancer in the eastern Indian population.

Serum versican as a potential biomarker in patients with uterine fibroids: A study from Eastern India.

Objective: Versican is a chondroitin sulphate proteoglycan with raised expression at site of inflammation, and uterine fibroids are associated with local inflammation. Hence, this study aimed to estimate serum Versican levels in pre-menopausal women with uterine fibroids to evaluate its diagnostic efficiency. Materials and Methods: This case-control study included forty uterine fibroid cases and 40 healthy controls. Cases clinically evaluated with USG findings, that is number, location of fibroid and volume calculated by prolate ellipse formula a × b × c × 0.523 (a - height, b - width, c - depth). Biochemical investigations, that is serum Versican levels, were estimated by ELISA with total cholesterol, HDLc and LDLc. Triglycerides by fully automated chemistry analysers. Serum biochemical parameters were compared and correlated with volume of fibroid. Area under receiver operating characteristic curve was calculated along with cut-off value to determine diagnostic potential of Versican, differentiating women with fibroids. Results: In the present study, patients with fibroids had decreased levels of serum Versican (79.43 ± 18.60) as compared to healthy controls (101.81 ± 28.24, P < 0.001). There was a statistically significant negative correlation (r = - 0. 307, P = 0.04) between serum Versican level and volume of fibroid. Area under ROC was 0.726 (95% CI: 0.616-0.836; P = 0.001). The best cut-off value for serum Versican level was 96.90 ng/ml with 90% sensitivity and 48% specificity. Conclusion: Serum Versican levels were found significantly lower in women with fibroid with a negative correlation with volume of fibroid uterus. Furthermore, extensive study would help in substantiating diagnostic potential of serum Versican in fibroid uterus patients.

Morphological assessment of the surface profile, mesiodistal diameter, and contact tightness of Class II composite restorations using three matrix systems: An in vitro study.

Context: Sectional matrices and contact rings are valuable aids to establish proximal contact tightness in Class II composite restorations. Aims: This study aims to evaluate the proximal contact area in Class II composite restorations using three matrix systems based on morphological analysis, mesiodistal (M-D) diameter and contact tightness. Subjects and Methods: A standardized DO cavity was prepared in 30 plastic molar teeth. They were randomly divided into three groups (n = 10) and restored using Tetric N-Ceram composite material and three matrix systems - Saddle matrix, Palodent system, and Palodent Plus system. The quality of proximal contacts was assessed by measuring the maximum M-D diameter of the restored teeth using a digital caliper; the tightness of the proximal contact area using Unifloss and a standardized metal blade (30 µm). Qualitative assessment of contact morphology was done by visual means while quantitative assessment of contour was done using Medit scanner superimposing method and ExoCAD software. Statistical Analysis Used: One-way ANOVA test was used to compare the mean M-D diameter (in mm) in the occlusal third, middle third, and the proximal contact area between the three groups. Chi-square test was used to compare the proximal contact area tightness using the passage of Unifloss. The buccolingual and occluso-gingival morphology was also compared among the three groups. The level of significance (P value) was set at P < 0.05. Results: For the occlusal and middle third, significantly larger diameters were achieved with the Palodent Plus system than with the Saddle matrix. More flat contours were seen in the case of the Saddle matrix than in the case of the Palodent system while the Palodent Plus system exhibited a minimal depth of concavity as determined by three-dimensional imaging of the contact morphology. Conclusions: Palodent Plus and Palodent matrix systems established superior contacts and contours than the Saddle matrix.

Analysis of Biochemical and Inflammatory Markers for Predicting COVID-19 Severity: Insights From a Tertiary Healthcare Institution of Eastern India.

Background Coronavirus disease-19 (COVID-19) patients often deteriorate rapidly based on viral infection-related inflammation and the subsequent cytokine storm. The clinical symptoms were found to be inconsistent with laboratory findings. There is a need to develop biochemical severity score to closely monitor COVID-19 patients. Methods This study was conducted in the department of biochemistry at All India Institute of Medical Sciences (AIIMS) Bhubaneswar in collaboration with the intensive care unit. Laboratory data of 7,395 patients diagnosed with COVID-19 during the first three waves of the pandemic were analyzed. The serum high sensitivity high-sensitivity C-reactive protein (hs-CRP, immuno-turbidity method), lactate dehydrogenase (LDH, modified Wacker et al. method), and liver enzymes (kinetic-UV method) were estimated by fully automated chemistry analyzer. Serum ferritin and interleukin-6 (IL-6) were measured by one-step immunoassay using chemiluminescence technology. Three models were used in logistic regression to check for the predictive potential of biochemical parameters, and a COVID-19 biochemical severity score was calculated using a non-linear regression algorithm. Results The receiver operating characteristic curve found age, urea, uric acid, CRP, ferritin, IL6, and LDH with the highest odds of predicting ICU admission for COVID-19 patients. COVID-19 biochemical severity scores higher than 0.775 were highly predictive (odds ratio of 5.925) of ICU admission (AUC=0.740, p<0.001) as compared to any other individual parameter. For the validation, 30% of the total dataset was used as testing data (n=2095) with a sensitivity of 68.3%, specificity of 74.5%, and odds ratio of 6.304. Conclusion Age, urea, uric acid, ferritin, IL6, LDH, and CRP-based predictive probability algorithm calculating COVID-19 severity was found to be highly predictive of ICU admission for COVID-19 patients.

The Evaluation of the Quality Performance of Biochemical Analytes in Clinical Biochemistry Laboratory Using Six Sigma Matrices.

Introduction This study was conducted to assess the analytical performance of biochemical tests using Six Sigma methodology and to assess the underlying causes of unsatisfied performance of analytes with a sigma value of less than 4 using quality goal index (QGI) and root cause analysis (RCA). Methodology Daily data for internal quality control (IQC) for both level 1 (L1) and level 2 (L2) and monthly data for external quality assessment for a period of six months were recorded. The coefficient of variation (CV), bias, and total allowable error (TEa) were calculated to analyze the sigma (σ) values for 19 biochemical analytes. Quality goal index (QGI) analysis was done to analyze impressions and inaccuracies in analyte performance having a sigma value of less than 4. Root cause analysis (RCA) was done to evaluate the possible causes that can improve quality performance. Results Creatinine and high-density lipoprotein (HDL) had sigma metrics of ≤2.0, and chloride, aspartate aminotransferase (AST), and alkaline phosphatase (ALP) had sigma values between 2 and 3. Glucose, total protein (TP), phosphate (Phos), and potassium had sigma values between 4 and 5 in level 1 QC. Sigma grading for level 2 quality control (QC) also gave similar results. For analytes with σ < 4, QGI analysis exposed inaccuracy or imprecision issues and identified errors such as the reconstitution of IQC, storage temperature, and air bubbles while processing the QC, being common causes of poor performance. Conclusion Six Sigma approach is helpful for quality assurance and identifying areas for improvement. Assessing Six Sigma metrics should be a routine practice to decide the frequency of QC run and to detect errors in analysis.

Machine learning predictive models of LDL-C in the population of eastern India and its comparison with directly measured and calculated LDL-C.

BACKGROUND: LDL-C is a strong risk factor for cardiovascular disorders. The formulas used to calculate LDL-C showed varying performance in different populations. Machine learning models can study complex interactions between the variables and can be used to predict outcomes more accurately. The current study evaluated the predictive performance of three machine learning models-random forests, XGBoost, and support vector Rregression (SVR) to predict LDL-C from total cholesterol, triglyceride, and HDL-C in comparison to linear regression model and some existing formulas for LDL-C calculation, in eastern Indian population. METHODS: The lipid profiles performed in the clinical biochemistry laboratory of AIIMS Bhubaneswar during 2019-2021, a total of 13,391 samples were included in the study. Laboratory results were collected from the laboratory database. 70% of data were classified as train set and used to develop the three machine learning models and linear regression formula. These models were tested in the rest 30% of the data (test set) for validation. Performance of models was evaluated in comparison to best six existing LDL-C calculating formulas. RESULTS: LDL-C predicted by XGBoost and random forests models showed a strong correlation with directly estimated LDL-C (r = 0.98). Two machine learning models performed superior to the six existing and commonly used LDL-C calculating formulas like Friedewald in the study population. When compared in different triglycerides strata also, these two models outperformed the other methods used. CONCLUSION: Machine learning models like XGBoost and random forests can be used to predict LDL-C with more accuracy comparing to conventional linear regression LDL-C formulas.

The Association Between Ferritin and Vitamin D Levels in Premenopausal Fibroid Uterus Cases With Anemia.

Objective The present study aimed to evaluate the association between serum ferritin and vitamin D levels in fibroid uterus cases presenting with anemia. Methods Sixty premenopausal women with uterine fibroids (30 associated with anemia and 30 without anemia) were enrolled as cases and control. All participants were evaluated on the basis of a questionnaire, which included queries related to obstetric, medical, and sociodemographic history. Peripheral blood smear, complete blood count (CBC), hemoglobin (Hb), and serum ferritin concentration were measured by a fully automated analyzer, and 25(OH) vitamin D level was measured by enzyme-linked immunosorbent assay (ELISA). Results There was a significant difference in ferritin levels between cases and control (p<0.001). The exposure to sunlight was moderate (one-hour exposure) in all subjects, eliminating the confounding effect of sunlight exposure influencing vitamin D levels. The median vitamin D level in cases was 5.0 ng/ml [interquartile range (IQR): 4.8], and that in control was 18.4 ng/ml (IQR: 7.9; p<0.001). A strong positive correlation of (r)=0.616 (p<0.001) was found between serum ferritin and vitamin D levels. Conclusion Fibroid uterus cases with anemia are more prone to vitamin D deficiency as compared to cases without anemia. Vitamin D estimation in fibroid uterus cases presenting with anemia would be useful for better patient management.

Serum Lysyl Oxidase Levels and Lysyl Oxidase Gene Polymorphism in Ovarian Cancer Patients of Eastern Indian Population.

(1) Background: Lysyl oxidase (LOX) plays a dual role in carcinogenesis and studies show a higher risk of cancer in LOX G473A variants. The present study evaluated the pattern of LOX G473A polymorphism (rs1800449) and serum LOX levels in ovarian cancer patients. (2) Methods: Serum LOX levels were estimated by enzyme linked immunosorbent assay (ELISA). A polymorphism of rs1800449 of LOX gene was detected by the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. Selected samples were sequenced for external validation. (3) Results: A majority of study participants were from low socio-economic status. Serum LOX level was significantly higher in ovarian cancer patients as compared to control. Serum LOX level in early-stage ovarian cancer was significantly lower as compared to advanced stage (FIGO stage III & IV). Wild type GG genotype was used as reference. Genotypes AA were associated with a significant risk of epithelial ovarian cancer (OR 3.208; p value- 0.033). A allele of rs1800449 polymorphism of LOX gene, the odds ratio was 1.866 (95% Confidence Interval 1.112-3.16) p value = 0.017 (4) Conclusions: A allele of rs1800449 polymorphism of LOX gene presents an increased risk of ovarian cancer in East Indian population. Serum LOX levels could be a potential biomarker for the diagnosis and prognosis of ovarian cancer.

Comparison of test performance of biochemical parameters in semiautomatic method and fully automatic analyzer method.

BACKGROUND: The primary health-care center (PHC) and community health center (CHC) are not well equipped with laboratory services. Semiauto analyzer-based reporting could be an effective modality, provided that the performance standard is comparable to that of the fully automatic analyzer. So, the objective of this study was to analyze the test results of biochemical parameters in semiauto and fully automatic analyzer and to compare the quality performance. MATERIALS AND METHODS: One hundred forty-nine patients undergoing routine biochemical investigations in the department laboratory were enrolled in this study. Two millimeter of venous blood was collected from all the participants and processed for urea, cholesterol, triglyceride (TG), serum glutamate-oxaloacetate transaminase (SGOT) (aspartate aminotransferase), and serum glutamate-pyruvate transaminase (SGPT) (alanine aminotransferase) by using standard kits (ERBA) in semiauto analyzer (Transasia Erba Chem5X by Calbiotech Inc. USA, semiautomated clinical chemistry analyzer) and the fully automatic analyzer (Cobas Integra 400 Roche, Germany) method. RESULTS: There was high variability in the distribution of urea, TG, SGOT, and SGPT values in both measurement methods, whereas cholesterol data followed a normal distribution (skewness: 1.522, 1.037; kurtosis: 2.373, 0.693 in semiauto and automated methods, respectively). A significant positive correlation between both the methods of assessment was observed in urea, cholesterol, TGs, SGOT, and SGPT. The mean difference for urea was -9.85 ± 23.997 (LOA: 37.189, -56.88), whereas it was highest for TG -24.34 ± 38.513 (LOA: 51.144, -99.829), suggesting that both methods can measure urea with less difference in absolute values, whereas for TG the measurement values are highly variable. CONCLUSION: The test performance of biochemical parameters such as urea, total cholesterol, TGs, SGOT, and SGPT taken by semiauto analyzer and fully automatic analyzer method of assessment were highly related and comparable.

Clinical and Metabolic Complications in patients with thalassemia undergoing transfusion therapy.

BACKGROUND: The transfusions in patients with thalassemia are a double-edged sword as the patients develop complications due to inadequate transfusions and due to multiple transfusions. These complications vary from metabolic complications such as diabetes mellitus and clinical complications such as growth retardation, transfusion-transmitted infections (TTI), and iron overload. We selected Balasore district in Odisha which is a satellite center of AIIMS Bhubaneshwar and has a huge population of hemoglobinopathy patients especially thalassemia and this district in Odisha lags in terms of healthcare and health awareness. MATERIALS AND METHOD: In all, 123 patients with thalassemia major were included in this study for the evaluation of metabolic and clinical complications. Anthropometric measurements such as height and weight with age and gender were used for evaluation of growth parameters as per World Health Organization (WHO) reference data. Children were termed wasted and stunted if the values were below 2 standard deviation of the reference WHO median. Blood samples were collected for TTI status and fasting blood sugar levels. RESULT: A total of 118 (95.9%) were detected to have under nutrition, 73 (59.3%) of the patients were HCV-positive, and 54 (48.6%) had high fasting blood sugar levels. Based on the HCV status, they were classified as HCV-positive and HCV-negative to compare the anthropometric and growth status in these patients. About 98.6% of the HCV-positive cases were undernutrition and 83.6% were stunted. CONCLUSION: There is an increasing trend of associated metabolic derangements in patients with thalassemia. The district-level health services have an urgent need for improvement in chelation regimes and screening technologies.

SLTChemDB: A database of chemical compounds present in Smokeless tobacco products.

Smokeless tobacco (SLT), a cause of potentially preventable diseases, has a diverse chemical composition encompassing toxicants as well as potent carcinogens. Though the chemical profile of SLT products has been analyzed earlier, this information is not available in a comprehensive and easily accessible format. Hence, there is an imperative felt need to develop a one-stop information source providing inclusive information on SLT products. SLTChemDB is the first such database that makes available detailed information on various properties of chemical compounds identified across different brands of SLT products. The primary information for the database was extracted through extensive literature search, which was further curated from popular chemical web servers and databases. At present, SLTChemDB contains comprehensive information on 233 unique chemical compounds and 82 SLT products. The database has been made user-friendly with facility for systematic search and filters. SLTChemDB would provide the initial data on chemical compounds in SLT products to various tobacco testing laboratories. The database also highlights research gaps and thus, would be a guide for researchers interested in chemistry and toxicology of SLT products. With regular update of information in the database, it shall be a valuable evidence base for policymakers to formulate stringent policies for SLT control.

Serum Biomarker Based Algorithms in Diagnosis of Ovarian Cancer: A Review.

Epithelial ovarian cancer accounts for more than 90% of ovarian tumours and continues as a leading cause of death from gynaecological malignancies. It is often difficult to differentiate a benign ovarian mass from malignant ones. Invasive histopathological biopsy is used as the gold standard diagnostic tool to diagnose cancer in patients with ovarian mass. A wide spectrum of Biomarkers were tried in various studies to develop a non invasive diagnostic tool, out of which HE4 and CA 125 remain the only clinically useful biomarker. Consequently various Biomarker based algorithms i.e. Risk of Malignancy Index, risk of ovarian cancer algorithm, OVA1, risk of malignancy algorithm were generated that have been developed to assess the risk of a mass being malignant. These algorithms help in timely triage of patients. Recently in 2016 FDA cleared Ova1 test (OVERA) with CA 125-II, HE4, apolipoprotein A-1, FSH, and transferring (Sensitivity 91% and Specificity 69%) as a referral or Triage test in patients presenting with ovarian mass. Combination of protein and circulating Micro RNA analysis in blood, could provide a comprehensive screening and diagnostic panel, in management of patients presenting with ovarian mass in one clinical setting.

Association between Cyclin D1 G870A (rs9344) polymorphism and cancer risk in Indian population: meta-analysis and trial sequential analysis.

Introduction: Association between Cyclin D1 (CCND1) single nucleotide polymorphism (SNP) rs9344 and cancer risk is paradoxical. Thus, we performed a meta-analysis to explore the association between CCND1 variant and overall cancer risk in Indian population. Methods: Data from 12 published studies including 3739 subjects were collected using Pubmed and Embase. RevMan (Review Manager) 5.3 was used to perform the meta-analysis. OR with 95%CI were calculated to establish the association. Results: Overall, the cumulative findings demonstrated that CCND1 polymorphism (rs9344) was not significantly associated with cancer risk in all the genetic models studied (dominant model: GG vs GA+AA: OR (95%CI) = 0.81 (0.60-1.09), P=0.17; recessive model: GG+GA vs AA: OR (95%CI) = 1.23 (0.96-1.59), P=0.11; co-dominant model: GG vs AA: OR (95%CI) = 1.35 (0.93-1.97), P=0.12; co-dominant model: (GG vs GA: OR (95%CI) = 1.16 (0.85-1.59), P=0.34; allelic model: A vs G: OR (95%CI) = 1.20 (1.14-2.85), P=0.23; allelic model: G vs A: OR (95%CI) = 0.83 (0.62-1.12), P=0.23). Subgroup analysis according to cancer types presented significant association of CCND1 polymorphism and increased breast cancer risk in dominant model (GG vs GA+AA: OR = 2.75, 95%CI = 1.54-4.90, P=0.0006) and allelic model (G vs A: OR = 1.63, 95%CI = 1.22-2.19, P=0.001). An increased esophageal cancer risk in recessive model (GG+GA vs AA: OR = 1.51, 95%CI = 1.05-2.16, P=0.03) and co-dominant model (GG vs AA: OR = 2.51, 95%CI = 1.10-5.71, P=0.03) was detected. A higher risk for colorectal cancer was detected under both the co-dominant models (GG vs AA: OR = 2.46, 95%CI = 1.34-4.51, P=0.004 and GG vs GA: OR = 1.74, 95%CI = 1.14-2.67, P=0.01). However, in case of cervical cancer risk a non-significant association was reported under the recessive model (GG+GA vs AA: OR = 1.52, 95%CI = 0.60-3.90, P=0.38) with reference to CCND1 polymorphism (rs9344). The trial sequential analysis (TSA) showed that the cumulative Z-curve neither crossed the trial sequential monitoring boundary nor reached the required information size (RIS). Thus, present meta-analysis remained inconclusive due to insufficient evidence. Conclusion:CCND1 polymorphism rs9344 may not have a role in overall cancer susceptibility in Indian population. However, this polymorphism acts as a crucial risk factor for breast, esophageal, and colorectal cancer but not for cervical cancer. Future studies with larger sample size are required to draw a reliable conclusion.

Regulation of toxic contents of smokeless tobacco products.

Effective regulation of contents of tobacco products is one of the primary milestones to reduce negative health effects associated with the use of smokeless tobacco (SLT) products. As per the available sources, testing of some SLT products has been done on ad hoc basis, but there is a lack of comprehensive and periodic analysis of these products. In addition, the available results indicate huge variations among the levels of pH, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone, N-nitrosonornicotine, benzo[a]pyrene, heavy metals and nicotine within different products as well as within different brands of the same product. This review was aimed to throw light on the variations and gaps in testing of SLT products and emphasize the need for strong policy regulation for monitoring the chemical constituents of these products.

In-silico study of toxicokinetics and disease association of chemicals present in smokeless tobacco products.

Smokeless tobacco (SLT) products are consumed by millions of people in over 130 countries around the world. Consumption of SLT has been estimated to cause a number of diseases accounting to more than 0.65 million deaths per year. There is sufficient epidemiological evidence on the association of SLT products with nicotine addiction, cancers of oral cavity and digestive systems but there is a lack of understanding of the role of toxic chemicals in these diseases. We provide the first comprehensive in-silico analysis of chemical compounds present in different SLT products used worldwide. Many of these compounds are found to have good absorption, solubility and permeability along with mutagenic and toxic properties. They are also found to target more than 350 human proteins involved in a plethora of human biological processes and pathways. Along with all the previously known diseases, the present study has identified the association of compounds of SLT products with a number of unknown diseases like neurodegenerative, immune and cardiac diseases (Left ventricular non compaction, dilated cardiomyopathy etc). These findings indicate far-reaching impact of SLT products on human health than already known which needs further validations using epidemiological, in-vitro and in-vivo methodologies. Thus, this study will provide one stop information for the policy makers in development of regulatory policies on toxic contents of SLT products.

Lysyl Oxidase: Its Diversity in Health and Diseases.

The mechanical properties of extracellular matrix (ECM) and connective tissues is largely dependent on the collagen and elastin structure. Lysyl oxidase (LOX) plays a critical role in the formation and repair of the ECM by oxidizing lysine residues in elastin and collagen, thereby initiating the formation of covalent cross linkages which stabilize these fibrous proteins. Due to its multiple functions both extracellularly and intracellularly, lysyl oxidase is involved in several processes in the tumorigenic pathway, in many different cancer types and stages. Alteration in LOX activity is implicated in many diseases and disorders including inflammation and inflammatory diseases, fibrosis of distinct organs and fibrotic disorders, cancer promotion and progression. There are only sparse reports of mutations or epigenetic alterations in the LOX gene. This review provides the recent clinical developments in the molecular mechanisms and pathologic process, pointing out LOX as a potential therapeutic target in translational medicine.

Effect of Guava in Blood Glucose and Lipid Profile in Healthy Human Subjects: A Randomized Controlled Study.

INTRODUCTION: The fruit of Psidium guajava (P.guajava) is known to contain free sugars yet the fruit juice showed hypoglycaemic effect. Hypoglycaemic activity of guava leaves has been well documented but not for guava fruit. AIM: So we aimed to evaluate the effect of ripe guava (with peel and without peel) fruit supplementation on blood glucose and lipid profile in healthy human subjects. MATERIALS AND METHODS: Randomized Controlled study undertaken in: 1) Baseline; 2) 6 weeks supplementation phase. Forty five healthy MBBS students were included and randomly enrolled into Group A, Group B and Group C. In Baseline phase: Fasting Plasma Glucose (FPG) and serum lipid profile was done in all 3 groups. Group A were supplemented with 400g of ripe guava with peel and group B without peel, for 6 weeks. Rest 15 treated as control i.e., Group C. RESULT: Supplementation of ripe guava fruit with peel reduced BMI as well as blood pressure (p<0.05) in group A, whereas the FPG, Total cholesterol, Triglycerides were found significantly increased (p<0.05). Group B registered a significant fall (p<0.05) in BMI as well as blood pressure. Fall in FPG level after guava pulp supplementation was not significant. Serum Total cholesterol, Triglycerides and Low Density Lipoprotein Cholesterol (LDLc) levels decreased significantly (p<0.05) indicating that guava pulp without peel may have a favourable effect on lipid levels and blood sugar as well. CONCLUSION: Guava fruit without peel is more effective in lowering blood sugar as well as serum total cholesterol, triglycerides and LDLc. It increases HDLc levels also.

OrCanome: a Comprehensive Resource for Oral Cancer.

Oral cancer is one of the most prevalent cancers in India but the underlying mechanisms are minimally unraveled. Cancer research has immensely benefited from genome scale high throughput studies which have contributed to expanding the volume of data. Such datasets also exist for oral cancer genes but there has been no consolidated approach to integrate the data to reveal meaningful biological information. OrCanome is one of the largest and comprehensive, user-friendly databases of oral cancer. It features a compilation of over 900 genes dysregulated in oral cancer and provides detailed annotations of the genes, transcripts and proteins along with additional information encompassing expression, inhibitors, epitopes and pathways. The resource has been envisioned as a one-stop solution for genomic, transcriptomic and proteomic annotation of these genes and the integrated approach will facilitate the identification of potential biomarkers and therapeutic targets.