Development of Predictive Models Based on Biochemical Parameters to Triage COVID-19 Patients: A Study Conducted in a Tertiary Care Hospital

Background The COVID-19 disease continues to cause severe mortality and morbidity. Biochemical parameters are being used to predict the severity of the infection. This study aims to predict disease severity and mortality to help reduce mortality through timely intervention in a cost-effective way. Methods A total of 324 COVID-19 cases admitted at our hospital (All India Institute of Medical Sciences, Patna, BR, India) between June 2020 to December 2020 (phase 1: 190 patients) and April 2021 to May 2021 (phase 2: 134 patients) were recruited for this study. Statistical analysis was done using SPSS Statistics version 23 (IBM Corp., Armonk, NY, USA) and model prediction using Python (The Python Software Foundation, Wilmington, DE, USA). Results There were significant differences in biochemical parameters at the time of admission among COVID-19 patients between phases 1 and 2, ICU and non-ICU admissions, and expired and discharged patients. The receiver operating characteristic (ROC) curves predicted mortality solely based on biochemical parameters. Using multiple logistic regression in Python, a total of four models (two each) were developed to predict ICU admission and mortality. A total of 92 out of 96 patients were placed into the correct management category by our model. This model would have allowed us to preserve 17 of the 21 patients we lost. Conclusions We developed predictive models for admission (ICU or non-ICU) and mortality based on biochemical parameters at the time of admission. A predictive model with a significant predictive capability for IL-6 and procalcitonin values using normal biochemical parameters was proposed. Both can be used as machine learning tools to prognosticate the severity of COVID-19 infections. This study is probably the first of its kind to propose triage for admission in the ICU or non-ICU at the medical emergency department during the first presentation for the necessary optimal treatment of COVID-19 based on a predictive model.

The Prognostic Value of De Ritis Ratio on the Survival Rate of ICU-Admitted COVID-19 Patients During the Second Wave: A Retrospective Study in a Tertiary Care Hospital in India

Background Prognostic markers are essential for optimizing COVID-19 patient care. This retrospective study examines the prognostic value of the De Ritis ratio (DRR) in intensive care unit (ICU)-admitted patients during the second wave of the pandemic. Methods A retrospective study of four-month duration (March to June 2021) was conducted on 161 ICU-admitted COVID-19 patients in a tertiary care hospital in India. The data included demographics, comorbidities, laboratory results, ICU admission dates, and survival outcomes. The De Ritis ratio was calculated on day 0, day 2, and day 5. The analyses included descriptive statistics, diagnostic accuracy, and logistic regression. Results Survival rates decreased with ICU stay: day 0 (survival, 58.4%; mortality, 41.6%), day 2 (survival, 54.5%; mortality, 45.5%), and day 5 (survival, 49.5%; mortality, 50.5%). De Ritis ratio's diagnostic accuracy varied, with increasing specificity and negative predictive value (NPV). Logistic regression showed higher day 5 De Ritis ratios, and male gender was associated with reduced survival odds. Conclusion The De Ritis ratio demonstrates promise as an early prognostic marker for COVID-19 patients, with an increase in predictive accuracy over time. The results emphasize the De Ritis ratio's potential as an early indicator of disease severity, offering clinicians a tool to recognize patients at higher risk and enhance the effectiveness of critical care interventions.

Newborn screening for congenital hypothyroidism, congenital adrenal hyperplasia and glucose-6-phosphate dehydrogenase deficiency in Bihar: A pressing priority in today's time

Background and Objective

Newborn screening (NBS) aims towards early detection of congenital disorders or prevention of intellectual and physical defects and life-threatening illness. Three disorders namely congenital hypothyroidism (CH), congenital adrenal hyperplasia (CAH) and glucose-6-phosphate dehydrogenase deficiency (G-6-PDD) were selected for a preliminary study for NBS. The study aimed to establish NBS in the Indian scenario that could lay a framework for future such initiatives.

Methods

A screening programme was conducted at a tertiary care hospital for 1 year. All the neonates born at All India Institute of Medical Sciences (AIIMS), Patna, were screened for their blood levels of glucose-6-phosphate dehydrogenase (G-6-PD), 17-hydroxyprogesterone (17-OHP) and thyroid-stimulating hormone (TSH). Heel-prick blood samples were collected within 48-72 h of birth, and the level of these parameters was accessed by enzyme immunoassay (EIA).

Results

A total of 492 neonates were born from January 2020 to December 2020, of which 369 newborns were screened for CAH, CH and G-6-PDD. Of 369 neonates, one case (male) had an increased level of TSH, six cases (all males) had an increased level of 17-OHP and no case was found with G-6-PDD.

Interpretation and Conclusions

Preliminary data on the prevalence of various genetic disorders revealed that CAH is the most prevalent disorder followed by CH in the population of Bihar. More efforts need to be undertaken to create awareness and to make screening a successful programme in India. A cost-effective nationwide screening programme is highly recommended for the detection of such cases at the earliest to avoid their future complication.

A Knowledge, Attitude, and Practice (KAP) Study on Phlebotomy Among Nurses in a Tertiary Hospital in Patna, India

INTRODUCTION

For most clinicians and nursing officers, laboratory testing is an unfamiliar part of medical caregiving, and ignorance may lead to serious avoidable errors. Phlebotomy, the first basic step towards laboratory testing, is to be taken seriously otherwise unnecessary repeat testing becomes mandatory. We hypothesized that there are some gaps in knowledge, attitude, and practice (KAP) among these nursing officers regarding practices of phlebotomy, which may influence the quality of blood samples. This study aims to assess the overall nurses' knowledge, attitude, and practice of phlebotomy to provide a remarkable improvement in blood sampling practice in our hospital.

MATERIAL AND METHODS

A prospective study was conducted involving nurses posted in different wards in All India Institute of Medical Sciences (AIIMS) Patna, India. A phlebotomy questionnaire was designed based on KAP on the clinical and laboratory standards of the WHO guidelines. A total of 30 questions were distributed among the nursing staff, 10 each from knowledge, attitude, and practice. Descriptive and logistic regression analyses were used to analyze the KAP levels and their influencing factors. All continuous variables were tested for normality conditions using the Shapiro-Wilk test and P>0.05 were considered for normality.

RESULTS AND CONCLUSION

The total average score of knowledge among the nurses was 7.62 (95%CI: 15.77-16.56). It was found that the nurses, on average, had a very strong positive attitude (93.36%). Regarding the distribution of practices of nurses, it was found that 87% had good practice as most of the positive practice items had high responses. The knowledge of phlebotomy among nurses was found to be satisfactory, except in a few areas. An education program on phlebotomy should be developed for nurses to improve and enhance their knowledge of phlebotomy.

The Role of Indirect Immunofluorescence (IIF) and Line Immunoassay (LIA) in the Diagnosis of Autoimmune Diseases and Their Clinical Correlation: An Observational Study From a Tertiary Care Center in Bihar

Background and aim The presence of distinct sets of autoantigens and autoantibodies bestow these autoimmune diseases (ADs) with specific immune profiles or fingerprints, which has cleared the diagnostic dilemma associated with these ADs. This study was planned to collate and compare the reporting of indirect immunofluorescence (IIF) with line immunoassay (LIA) and their clinical correlations. This study was conducted to investigate the association between the reporting of anti-nuclear antibody (ANA) screening by IIF and ANA profile reporting by LIA. Additionally, it aimed to explore the association of ANA pattern detection by IIF with the detection of autoantibodies against nuclear antigens by LIA and the association of autoantibody detection by LIA with clinical diagnosis. Methodology A total of 98 samples from patients suspected of having ADs were subjected to both IIF and LIA, and results were correlated with clinical diagnosis. Results In the homogenous pattern noted by IIF, the clustered antigens identified by LIA included dsDNA, Nucleosome, Histone, and Mi-2. In the speckled pattern, the identified antigens were SS-A/Ro52, P0, SS-A/Ro60, SS-B/La, and U1-snRNP. On the other hand, the nucleolar pattern revealed antigens AMA M2, PCNA, and CENP-B. The centromere pattern was mostly associated with CENP-B. The speckled pattern was found to be most commonly associated with systemic lupus erythematosus (SLE). The most common autoantibody found in total ANA profile-positive samples was anti-U1-snRNP followed by anti-SS-A/Ro60 and anti-SS-B/La, and all three were found to be associated with SLE. Conclusions SLE was the most common AD identified in our study samples, with the speckled pattern being the most common pattern on IIF and anti-U1-snRNP being the most common ANA identified by LIA. The fluorescence pattern of IIF predicts the presence of specific antibodies. LIA should be reserved for IIF-positive but dubious cases and whose signs and symptoms are nebulous and do not match the disease dictated by IIF.

Mannose-binding lectin gene 2 variant DD (rs 5030737) is associated with susceptibility to COVID-19 infection in the urban population of Patna City (India)

The study aimed to measure plasma levels of Mannose-Binding Lectin (MBL) and MBL-associated serine protease-2 (MASP-2) and their polymorphisms in COVID-19 patients and controls to detect association. As MBL is a protein of immunological importance, it may contribute to the first-line host defence against SARS-CoV-2. MBL initiates the lectin pathway of complement activation with help of MASP-1 and MASP-2. Hence, appropriate serum levels of MBL and MASPs are crucial in getting protection from the disease. The polymorphisms of MBL and MASP genes affect their plasma levels, impacting their protective function and thus may manifest susceptibility, extreme variability in the clinical symptoms and progression of COVID-19 disease. The present study was conducted to find plasma levels and genetic variations in MBL and MASP-2 in COVID-19 patients and controls using PCR-RFLP and ELISA, respectively.The present study was conducted to find plasma levels and genetic variations in MBL and MASP-2 in COVID-19 patients and controls using PCR-RFLP and ELISA, respectively. Our results indicate that median serum levels of MBL and MASP-2 were significantly low in diseased cases but attained normal levels on recovery. Only genotype DD was found to be associated with COVID-19 cases in the urban population of Patna city.

The second wave of COVID-19 wreaked havoc: A look at clinical and laboratory parameters of survivors and non-survivors admitted to Intensive Care Unit, a single-centered retrospective study

Background

The second wave of COVID-19 was disastrous and claimed many lives in India and abroad. The most challenging task was to provide the required treatment as per the patient's condition, within a limited span of time. The lack of prognostic predictors at the time of admission led to failure in prioritizing the patient's need for intensive care.

Aim

This study was conducted to find out the clinical and laboratory parameters at the time of admission to ICU as predictors of outcomes in COVID-19 patients, which can help in judicious utilization of the available resources for better patient care.

Subjects and Methods

Study comprises of 161 ICU admitted patients. Study of clinical traits, comorbidities, test results, and demographic variables were carried out among survivors and non-survivor.

Result

Maximum death were patients of age group 21-30 years and male gender. Mortality in hypertensives, diabetics, and patients with sepsis were found to be statistically significant. Patients who developed ARDS and pneumonia or needed ventilation died invariably. High levels of laboratory parameters like IL-6, LDH, PT, INR, aPTT, ferritin, WBC count, and D-dimer were significantly associated with poor outcomes and at a particular cutoff had optimum sensitivity and specificity to predict mortality in ICU admitted COVID-19 patients. At the same time, low lymphocyte count and PaO2/FiO2 ratio was significantly associated with bad prognosis (P < 0.05).

Conclusion

This paper will help in prioritizing patients in ICU who need special attention especially at the time of meager supply of resources.

Evaluation of C4b as an adjunct marker in symptomatic RT-PCR negative Covid-19 cases

Introduction

Detecting low viral load has been a challenge in this pandemic, which has led to its escalated transmission. Complement activation has been implicated in pathogenesis of Covid-19 infection. Thus, evaluation of complement activation in suspected Covid-19 infection may help to detect infection and limit false negative cases thus limiting transmission of infection. We speculate that measuring C4b, produced from an activated complement system due to the presence of Covid-19 may help in its detection, even when the viral titers are low.

Methods

Plasma C4b levels of symptomatic RT-PCR positive patients (cases, n = 40); symptomatic RT-PCR negative patients (n = 35) and asymptomatic RT-PCR negative controls (n = 40) were evaluated. Plasma C5b-9, IL-6, D-dimer and C1-Inhibitor (C1-INH) were also measured in cases and controls. ELISA kits were used for all measurements. Statistical analyses were carried out using Stata, version 12 (Stata Corp., Texas, USA).

Results

C4b levels were found to be significantly increased in RT-PCR positive patients as compared to asymptomatic RT-PCR negative controls. RT-PCR negative but symptomatic patients still showed increased C4b levels. The significantly higher levels of C4b in cases with a cut-off value of ≥ 116 ng/ml with optimum sensitivity and specificity of 80% and 52% respectively is indicative of its possible use as an adjunct marker. Increased levels of D-dimer, IL6, along with decreased levels of C1-INH were found in cases compared to controls. Whereas, C5b-9 levels were not significantly raised in cases.

Conclusions

The results of our study suggests that plasma C4b may help to detect infection in false negative cases of RT-PCR that escape detection owing to low viral load. However, to confirm it a large-scale study is needed.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12291-022-01033-z.

Relation Between HbA1c and Lipid Profile Among Prediabetics, Diabetics, and Non-diabetics: A Hospital-Based Cross-Sectional Analysis

INTRODUCTION

An unusually high blood glucose level is a hallmark of diabetes mellitus, with an imbalance between insulin levels and insulin sensitivity leading to an insulin functional deficit. Since it serves as both a risk indicator and a gauge of long-term glycemic control, the HbA1c concentration is a crucial component of standard diabetes treatment. The use of the HbA1c concentration in the diagnosis of diabetes is expanding as the test's accuracy increases. Dyslipidemic profiles can appear before type 2 diabetes manifests itself and are independent risk factors for the disease. Additionally, dyslipidemia, especially in diabetics, might affect pancreatic beta-cell survival and activity. This study was undertaken with the aim to find out any correlation between HbA1c and lipid profile among diabetics, prediabetics, and non-diabetics.

METHODS

A total of 1,000 individuals with age 18-60 years were included in the study (non-diabetics = 186, prediabetics = 238, diabetics = 576). HbA1c was estimated by capillary electrophoresis and a lipid profile was done using a fully automatic chemistry analyzer.

RESULT

Diabetes was found to be significantly associated with dyslipidemia. In diabetics, a statistically significant increase in the level of triglyceride and very low-density lipoprotein (VLDL) was seen as compared to prediabetics. Diabetic women were found to be significantly more dyslipidemic as compared to diabetic males. The mean HbA1c among diabetics was found to be 8.3.

CONCLUSION

In hyperglycemia-induced dyslipidemia, raised triglyceride and VLDL were the most common findings, and combined lipid abnormalities were more commonly seen as compared to a single abnormality in the lipid profile. Patients with poor glycemic control more commonly develop dyslipidemia, which may be a reason for an increased incidence of cardiovascular catastrophes in such patients.

BacARscan: an in-silico resource to discern diversity in antibiotic resistance genes

Antibiotic resistance has escalated as a significant problem of broad public health significance. Regular surveillance of antibiotic resistance genes (ARGs) in microbes and metagenomes from human, animal, and environmental sources is vital to understanding ARGs' epidemiology and foreseeing the emergence of new antibiotic resistance determinants. Whole-genome sequencing (WGS)-based identification of the microbial ARGs using antibiotic resistance databases and in-silico prediction tools can significantly expedite the monitoring and characterization of ARGs in various niches. The major hindrance to the annotation of ARGs from WGS data is that most genome databases contain fragmented genes/genomes (due to incomplete assembly). Herein, we describe an in-silico Bacterial Antibiotic Resistance scan (BacARscan) (http://proteininformatics.org/mkumar/bacarscan/) that can detect, predict and characterize ARGs in -omics datasets, including short sequencing, reads, and fragmented contigs. Benchmarking on an independent non-redundant data set revealed that the performance of BacARscan was better than other existing methods, with nearly 92% precision and 95% F-measure on a combined dataset of ARG and non-ARG proteins. One of the most notable improvements of BacARscan over other ARG annotation methods is its ability to work on genomes and short reads sequence libraries with equal efficiency and without any requirement for assembly of short reads. Thus, BacARscan can help monitor the prevalence and diversity of ARGs in microbial populations and metagenomic samples from animal, human and environmental settings. The authors intend to constantly update the current version of BacARscan as and when new ARGs are discovered. Executable versions, source codes, sequences used for development, and usage instructions are available at (http://www.proteininformatics.org/mkumar/bacarscan/downloads.html) and GitHub repository (https://github.com/mkubiophysics/BacARscan).

Lived Experience of Nurses in COVID-19 Units - A Phenomenological Study from Eastern India

Introduction: Nurses are the frontline workers who had to play multiple functions like in acute care, community, etc. but, it was stated that COVID-19 has caused immense trauma to nurses globally. Methods: A descriptive phenomenological study to explore the lived experience of nurses working in COVID-19 units was conducted among nine senior nursing officers recruited by purposive homogenous sampling and interviewed with an open-ended interview guide by ensuring data saturation. COREQ guideline were adopted for this qualitative study. Results: Qualitative data were analysed using Giorgi's framework, and themes and sub-themes were derived. The major themes that emerged in the present study were "Reactions and preparation", "Feelings and satisfaction in active duty", "Role of a helping hand", "Working experience in PPE", and "Pandemic and socialization". Each theme had further sub-themes to classify the verbatims. Conclusion: Most of the nurses had anxiety and prepared themselves to play with fire, had unrealistic hope, and mixed emotions, kept their family away and intentionally concealed information to reduce family's fear, were satisfied with training and preparation, and had unpleasant experiences with PPE, had to restrict their social activities and felt social stigma. It also concludes with the recommendation that warrants the need to improve their professional quality of life and working conditions by safeguarding nurses' physical and mental health.

Efficacy of Lipid Ratios and Platelet Distribution Width for Assessment of Liver Fibrosis in Patients With Non-alcoholic Fatty Liver Disease

Introduction

The clinical course of non-alcoholic fatty liver disease (NAFLD) in its long term may follow a benign course or have an adverse outcome leading to hepatocellular carcinoma (HCC) or end-stage liver disease requiring liver transplantation. Such patients represent only a small proportion of all NAFLD cases, making case finding a real challenge.

Aims

This study was planned to test the efficacy of simple laboratory parameters for their ability to screen advanced cases of NAFLD who need early attention to extricate them from the cumbersome outcome.

Material and method

The study protocol enrolled 129 diagnosed cases of NAFLD. Patients were categorized as group I with mild/moderate fibrosis (MF) comprising of F0 to F2 and group II with advanced fibrosis (AF) comprising of F3 and F4 based on Fibroscan kPa (kilopascal) score.

Results

Group I consisted of 96 MF patients, while group II included 33 AF patients. Mean values of alanine transaminase (ALT), aspartate transaminase (AST), alkaline phosphatase (ALP), triglyceride (TG), triglyceride/high-density lipoprotein (TG/HDL) ratio, total cholesterol/high-density lipoprotein (TC/HDL) ratio, and platelet distribution width (PDW) were significantly higher in patients with AF (group II), while platelet count (PC) was significantly lower in group II. The area under the receiver operative characteristic (AUROC) curve was highest for PDW [0.730 (0.644-0.815)] and TG/HDL ratio [0.719 (0.612-0.827)]. TG/HDL ratio at a cut-off of >2.4 had a sensitivity and specificity of 84.85% and 34.38%, respectively, and PDW at a cut-off of >16.40 had a sensitivity and specificity of 84.85% and 54.17%, respectively.

Conclusion

Decent sensitivity at particular cut-offs for TG/HDL ratio and PDW makes them suitable to be applied for screening advanced cases of NAFLD that require early ministration and medication to block its further progression to its intricate form.

Mobile technology: A tool for healthcare and a boon in pandemic

Healthcare systems deal with disease prevention, early detection, diagnosis, investigation, and timely, affordable, and safe treatment. For the delivery of services in the health sector, communication is the key to linking the service provider and the patients. Mobile technology in the recent past has rendered various platforms of communications for the healthcare system. Thus, in health, mobile technology has greatly contributed to time management and cost reduction for healthcare at every level including hospital visits to individual appointments with doctors, hence the convenience. With advancements in mobile technologies and the growing number of mobile users, newer opportunities have opened up for the use of mobiles for patient care. Emerging information and communication technologies with the help of the Internet of Things (IoT) have been instrumental in integrating different domains of the health sector with mobile technology. Thus, the technology may have the potential to become powerful medical tools to support the health sector at all levels of care. In this review, the concept, applications, and advantages of mobile technology for health and the present pandemic have been discussed. It also discusses mobile health technology, as a support system for convenient and safer healthcare for public health, and the opportunities to improve its applications for unseen future health crises.

Diagnostic Accuracy of FIB-4 and FIB-5 Scores as Compared to Fibroscan for Assessment of Liver Fibrosis in Patients With Non-Alcoholic Fatty Liver Disease

Introduction Limited access/exorbitant cost of fibroscan and the associated risks with biopsy to assess fibrosis in non-alcoholic fatty liver disease (NAFLD) patients has made exigent demand of serum-based fibrosis scores to be validated for their accuracy and efficacy. The objective of the study was to compare the accuracy of FIB-4 (fibrosis-4) and FIB-5 (fibrofast) scores to rule out advanced fibrosis in NAFLD patients. Methods A total of 145 patients were categorized as group I with mild/moderate fibrosis (MF) comprising of F0 to F2 and group II with advanced fibrosis (AF) comprising of F3 and F4 based on fibroscan kPa (kilopascal) score. Results Group II had significantly higher alanine transaminase (ALT), aspartate transaminase (AST), haemoglobin % (Hb %), bilirubin and alkaline phosphatase (ALP) values and significantly lower platelet count and albumin as compared to group I. The FIB-4 score was significantly higher in group II [1.8 (1.1 - 4.7)], as compared with group I [0.98 (0.63 - 1.67)], p-value = 0.0001. FIB-5 score of group II [-6.4 (-8.8 - 3.4)] was significantly lower as compared with group I [-4.8 (-6.8 - 2.0)], p-value = 0.003. FIB-4 and FIB-5 had area under receiver operator characteristic (AUROC) curve of 0.712 and 0.655, respectively. FIB-4 at cut-off of <2.02 had a negative predictive value (NPV) of 90.7%. FIB-5 at a cut-off of <-7.11 has an NPV of 94.1% and at a cut-off of <-3.24 had an NPV of 88.9%. Conclusion We concluded that both FIB-4 and FIB-5 can be used to rule out advanced fibrosis in NAFLD patients in a resource-limited and indigent setting as both the scores have NPV greater than 90%.

Effectiveness of Kanna photoscreener in detecting amblyopia risk factors

Purpose:

Amblyopia is a significant public health problem. Photoscreeners have been shown to have significant potential for screening; however, most are limited by cost and display low accuracy. The purpose of this study was validate a novel artificial intelligence (AI) and machine learning–based facial photoscreener “Kanna,” and to determine its effectiveness in detecting amblyopia risk factors.

Methods:

A prospective study that included 654 patients aged below 18 years was conducted in our outpatient clinic. Using an android smartphone, three images of each the participants’ face were captured by trained optometrists in dark and ambient light conditions and uploaded onto Kanna. Deep learning was used to create an amblyopia risk score based on our previous study. The algorithm generates a risk dashboard consisting of six values: five normalized risk scores for ptosis, strabismus, hyperopia, myopia and media opacities; and one binary value denoting if a child is “at-risk” or “not at-risk.” The presence of amblyopia risk factors (ARF) as determined on the ophthalmic examination was compared with the Kanna photoscreener.

Results:

Correlated patient data for 654 participants were analyzed. The mean age of the study population was 7.87 years. The algorithm had an F-score, 85.9%; accuracy, 90.8%; sensitivity, 83.6%; specificity, 94.5%; positive predictive value, 88.4%; and negative predictive value, 91.9% in identifying amblyopia risk factors. The P value for the amblyopia risk calculation was 8.5 × 10⁻¹⁴² implying strong statistical significance.

Conclusion:

The Kanna photo-based screener that uses deep learning to analyze photographs is an effective alternative for screening children for amblyopia risk factors.

Non-invasive saliva-based screening of high-risk Human Papilloma Virus 16 and 18 in healthy young adults and creating awareness about its vaccination

Context:

Human Papilloma Virus (HPV) has not only been linked with cervical cancer but also a key player in other types including oral cancer. Vaccine against HPV has shown promising outcomes in protection against cervical cancer. It is suggested that the same vaccine may be a safeguard against oral cancer as well. Since prevalence of oral cancer is on rise because of various reasons besides high-risk sexual behavior, its prevention becomes equally important.

Aim:

Study aimed at screening saliva samples of healthy young adults to detect the presence of HPV with an intention to increase awareness regarding HPV and its vaccination.

Settings and Design:

The study was executed in the department of Biochemistry, AIIMS, Patna. This cross-sectional study included 100 consented healthy undergraduate medical and nursing students.

Methods and Material:

We isolated DNA from all saliva samples, amplified using multiplex PCR and gel electrophoresed to screen HPV 16 and 18. Feedback about the study in creating awareness regarding HPV and its vaccine was conducted using three-point Likert scale.

Statistical analysis:

The collected responses were entered in Microsoft excel. The results were expressed in frequency and percentages.

Results:

All saliva samples screened were found negative for HPV 16 and 18 DNA. Responses from feedback showed improved knowledge and awareness about the HPV and its vaccine among the participants.

Conclusion:

Even all the saliva samples tested were found negative for HPV DNA, the screening of high-risk HPV in saliva of young medical and nursing students generated curiosity among them to know more about HPV and its vaccine. This exercise may have helped in increasing the acceptance of HPV vaccine and the awareness of getting it at their ideal age to be benefited with dual protection, from oral and cervical (in case of females) cancers lifelong.

Correlation of over-expression of rv1900c with enhanced survival of M. smegmatis under stress conditions: Modulation of cell surface properties

Mycobacterium tuberculosis has distinct cell wall composition that helps in intracellular survival of bacteria. Rv1900c, a two domain protein, has been grouped in lip gene family. The expression of rv1900c was upregulated under acidic, nutritive and iron stress conditions in M. tuberculosis H37Ra. To investigate the biological effect of Rv1900c in mycobacterium physiology, rv1900c gene was cloned in M. smegmatis, a surrogate host. Its counterpart MSMEG_4477 in M. smegmatis demonstrated 38% protein similarity with Rv1900c. MSMEG_4477 gene was knocked out in M. smegmatis by homologous recombination. rv1900c and MSMEG_4477 genes, cloned in pVV16, were expressed in the M. smegmatis knockout strain (M. smegmatis ΔMSMEG_4477). Gene knockout significantly altered colony morphology and growth kinetics of M. smegmatis. M. smegmatis ΔMSMEG_1900 (pVV16::rv1900c) colonies were less wrinkled and had smooth surface as compared to M. smegmatis ΔMSMEG_4477. The changes were reverted back to normal upon expression of MSMEG_4477 in knockout strain M. smegmatis ΔMSMEG_4477 (pVV16::MSMEG_4477). The expression of rv1900c enhanced the biofilm formation and survival of bacteria under various in vitro stresses like acidic, nutritive stress, including lysozyme, SDS and multiple antibiotics treatment in comparison to control. On the other hand the expression of rv1900c decreased the cell wall permeability. The resistance provided by M. smegmatis ΔMSMEG_4477 (pVV16::MSMEG_4477) was comparable to M. smegmatis having vector alone (MS_vec). The lipid content of M. smegmatis ΔMSMEG_1900 (pVV16::rv1900c) was observed to be different from M. smegmatis ΔMSMEG_4477 (pVV16::MSMEG_4477). M. smegmatis ΔMSMEG_1900 (pVV16::rv1900c) was more tolerant to stress conditions in comparison to M. smegmatis ΔMSMEG_4477 (pVV16::MSMEG_4477). Expression of rv1900c enhanced the intracellular survival of mycobacteria. Therefore, the present study suggested an association of Rv1900c to the stress tolerance by cell wall modification that might have resulted in enhanced intracellular survival of the mycobacteria.

Application of deep learning and image processing analysis of photographs for amblyopia screening

Purpose

Photo screeners and autorefractors have been used to screen children for amblyopia risk factors (ARF) but are limited by cost and efficacy. We looked for a deep learning and image processing analysis-based system to screen for ARF.

Methods

An android smartphone was used to capture images using a specially coded application that modified the camera setting. An algorithm was developed to process images taken in different light conditions in an automated manner to predict the presence of ARF. Deep learning and image processing models were used to segment images of the face. Light settings and distances were tested to obtain the necessary features. Deep learning was thereafter used to formulate normalized risks using sigmoidal models for each ARF creating a risk dashboard. The model was tested on 54 young adults and results statistically analyzed.

Results

A combination of low-light and ambient-light images was needed for screening for exclusive ARF. The algorithm had an F-Score of 73.2% with an accuracy of 79.6%, a sensitivity of 88.2%, and a specificity of 75.6% in detecting the ARF.

Conclusion

Deep-learning and image-processing analysis of photographs acquired from a smartphone are useful in screening for ARF in children and young adults for a referral to doctors for further diagnosis and treatment.

The lipolytic activity of LipJ, a stress-induced enzyme, is regulated by its C-terminal adenylate cyclase domain

Aim: The confirmation of lipolytic activity and role of Rv1900c in the Mycobacterium physiology Methods: rv1900c/N-terminus domain (rv1900NT) were cloned in pET28a/Escherichia coli, purified by affinity chromatography and characterized. Results: A zone of clearance on tributyrin-agar and activity with pNP-decanoate confirmed the lipolytic activity of Rv1900c. The Rv1900NT demonstrated higher enzyme specific activity, V_max and k_cat, but Rv1900c was more thermostable. The lipolytic activity of Rv1900c decreased in presence of ATP. Mycobacterium smegmatis expressed rv1900c/rv1900NT-altered colony morphology, growth, cell surface properties and survival under stress conditions. The effect was more prominent with Rv1900NT as compared with Rv1900c. Conclusion: The study confirmed the lipolytic activity of Rv1900c and suggested its regulation by the adenylate cyclase domain and role in the intracellular survival of bacteria.

FMD and CIMT: Surrogate Markers of Atherosclerosis in Subclinical and Overt Hypothyroidism in Sub Himalyan Region

INTRODUCTION

Hypothyroidism increases the risk of atherosclerosis. Carotid intima-media thickness (CIMT) and flow-mediated dilation (FMD) have been used as a noninvasive method to detect atherosclerosis. But the literature is scarce on patients with subclinical hypothyroidism. Such a study was not done in our region, so we conducted this study at a tertiary care center to compare CIMT and FMD among subclinical and overt hypothyroid patients and to analyze the risk of atherosclerosis.

METHODS

We evaluated 68 patients aged 18-50 years, with newly diagnosed hypothyroidism. We divided them into overt and subclinical hypothyroidism groups and compared the findings. All analyses were performed by the computerized SPSS 17.0. The results were noted as means ± SD and percentage. Student's t-test was used to compare continuous variables, and the Chi-square test was used to compare differences.

RESULTS

The total number of patients with dyslipidemia in the subclinical hypothyroidism (SCH) group was 22 (45.83%) and in the overt hypothyroidism (OH) group was 26 (54.16%) with a P- value of 0.009. The mean FMD% in subclinical hypothyroidism patients was 6.9816 ± 3.4224 and in overt hypothyroidism patients was 5.3670 ± 2.7278 (P = 0.03). The mean CIMT was 0.5009 ± 0.0732, CIMT in the SCH group was 0.5082 ± 0.0672 and in the OH group was 0.5305 ± 0.0799 (P = 0.2).

CONCLUSION

The outcome of this study specifies that hypothyroidism is associated with endothelial dysfunction as established by impaired FMD, and it may be the first marker of atherosclerosis appearing before any structural evidence like CIMT. We can speculate that there is a link between subclinical hypothyroidism and atherosclerosis, and thyroxine replacement in SCH may help to prevent the progression of atherosclerosis.

Sociodemographic profile and pattern of substance abusers: A retrospective study to unveil the public health problem of Punjab

INTRODUCTION

Substance abuse refers to the harmful or hazardous use of any psychoactive substance including licit and illicit drugs, other than when medically indicated. According to a UN report, 1 million heroin addicts are registered in India, and unofficially, there are as many as 5 million. Among all the states Punjab stood third in substance abuse and also injectable drug use. The present study was thus conducted to assess the sociodemographic profile and pattern of substance abuse among patients attending a Drug de-addiction centre.

MATERIAL AND METHODS

A record-based analysis from March 2015 to March 2019 was done. Substance dependence was diagnosed post detailed clinical interview by a consultant psychiatrist at the center using DSM -10. For the 966 registered patients admitted in the last four years, the record was checked for completeness of data and relevant information on socio-demographic profile, substance abused, duration of hospital stays, drop out and relapse rates was extracted.

RESULTS

Of the total admitted patients (n= 966) 100% addicts were of male gender and natives of Punjab. 514 (53.21%) were married followed by 434(44.93%) never married. Maximum patients 456(47.20%) were self-employed. Heroin was the most abused drug. The injecting route of drug abuse was used by most of the abusers i.e. 51.66%. Only 173 (17.90%) patients dropped out of the treatment followed by relapse in 192 (19.88%).

CONCLUSION

In this paper we demonstrated the vulnerability of young population towards drug addiction. Easy accessibility of drugs, peer pressure and difficult family circumstances raises the fragility to restore for substance use. However, community-based studies are imperative in order to estimate how big is the problem at the bottom.

Intron retention and its impact on gene expression and protein diversity: A review and a practical guide

Intron retention (IR) occurs when a complete and unspliced intron remains in mature mRNA. An increasing body of literature has demonstrated a major role for IR in numerous biological functions, including several that impact human health and disease. Although experimental technologies used to study other forms of mRNA splicing can also be used to investigate IR, a specialized downstream computational analysis is optimal for IR discovery and analysis. Here we provide a review of IR and its biological implications, as well as a practical guide for how to detect and analyze it. Several methods, including long read third generation direct RNA sequencing, are described. We have developed an R package, FakIR, to facilitate the execution of the bioinformatic tasks recommended in this review and a tutorial on how to fit them to users aims. Additionally, we provide guidelines and experimental protocols to validate IR discovery and to evaluate the potential impact of IR on gene expression and protein output. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA Processing > Splicing Regulation/Alternative Splicing RNA Methods > RNA Analyses in vitro and In Silico.

Identifying residues that determine palmitoylation using association rule mining

MOTIVATION

In eukaryotes, palmitoylation drives several essential cellular mechanisms like protein sorting, protein stability and protein-protein interaction. Several amino acids namely Cys, Gly, Ser, Thr and Lys undergo palmitoylation. But very little is known about the amino acid patterns that promote palmitoylation.

RESULTS

We deduced presence of statistically significant amino acids around palmitoylation sites and their association with different palmitoylated residues i.e. Cys, Gly and Ser. The results suggest that palmitoylation, irrespective of its target residue, generally occurs at sites where Cys, Leu, Lys, Arg, Ser and Met are abundant. Furthermore, functional properties of the three types of palmitoylated proteins were compared. We observed similar functional behavior of Cys and Gly palmitoylated proteins but proteins with Ser palmitoylation showed distinctiveness from remaining two. Motif-wise functional conservation was also observed in Cys palmitoylated proteins. We also did functional annotation of predicted human palmitoylome.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Adipokine Visfatin's Role in Pathogenesis of Diabesity and Related Metabolic Derangements

Visfatin is one of the prominent adipokines secreted by adipose tissue. The level of visfatin increases significantly in persons with obesity owing to increased body mass index (BMI). During obesity, the adipocytes, which populate adipose tissue, undergo hypertrophy and hyperplasia and secrete a number of adipocytokines including visfatin. Visfatin, which also acts as an enzyme nicotinamide phosphoribosyl transferase, is one of the prominent adipokines that influence metabolic homeostasis in the body. Visfatin exists in two forms, extracellular and intracellular, and enacts a multitude of actions. The direct and indirect evidence gathered from in-vitro, in-vivo and clinical studies indicate that visfatin modulates obesity and metabolic syndrome-related pathophysiological activities including enhanced inflammation, angiogenesis, synthesis of NAD mononucleotide, and upregulation of antiapoptotic proteins in a number of cell types. It has been implicated in a number of obesity-related alterations and metabolic derangement such as diabetes, cardiovascular complications and some forms of cancers. In this review, the novel hypothesis about the role of visfatin in diabesity has been proposed which implies recent advances in studies about the pathophysiological roles of visfatin during obesity and chronic high glucose in the circulation. Visfatin at high concentration attracts immune cells and produces chronic inflammation in adipocytes. Additionally, it induces insulin resistance in many tissues and causes pancreatic beta cells dysfunction at later stages. Further, its potential as an important target to develop molecular medicine in diabesity and related metabolic syndrome has been highlighted.

Comparative functional analysis of proteins containing low-complexity predicted amyloid regions

Background

In both prokaryotic and eukaryotic proteins, repeated occurrence of a single or a group of few amino acids are found. These regions are termed as low complexity regions (LCRs). It has been observed that amino acid bias in LCR is directly linked to their uncontrolled expansion and amyloid formation. But a comparative analysis of the behavior of LCR based on their constituent amino acids and their association with amyloidogenic propensity is not available.

Methods

Firstly we grouped all LCRs on the basis of their composition: homo-polymers, positively charged amino acids, negatively charged amino acids, polar amino acids and hydrophobic amino acids. We analyzed the compositional pattern of LCRs in each group and their propensity to form amyloids. The functional characteristics of proteins containing different groups of LCRs were explored using DAVID. In addition, we also analyzed the classes, pathways and functions of human proteins that form amyloids in LCRs.

Results

Among homopolymeric LCRs, the most common was Gln repeats. LCRs composed of repeats of Met and aromatic amino acids were amongst the least occurring. The results revealed that LCRs composed of negatively charged and polar amino acids were more common in comparison to LCRs formed by positively charged and hydrophobic amino acids. We also noted that generally proteins with LCRs were involved in transcription but those with Gly repeats were associated to translational activities. Our analysis suggests that proteins in which LCR is composed of hydrophobic residues are more prone toward amyloid formation. We also found that the human proteins with amyloid forming LCRs were generally involved in binding and catalytic activity.

Discussion

The presented analysis summarizes the most common and least occurring LCRs in proteins. Our results show that though repeats of Gln are the most abundant but Asn repeats make longest stretch of low complexity. The results showed that potential of LCRs to form amyloids varies with their amino acid composition.

Prediction of Rare Palmitoylation Events in Proteins

Palmitoylation directs many cellular processes such as protein trafficking, sorting, signaling, interactions with other biomolecules, to name a few. Palmitoylation commonly occurs on cysteine; however, occasional palmitoylation of few other amino acids has also been reported. To date, comprehensive analysis on occasional palmitoylation is unavailable. In the present study, we reported a computational method to predict palmitoylation of glycine and serine residues in a protein. The method is based on support vector machine (SVM). It was trained on position-specific scoring matrix of amino acids that surrounds palmitoylated glycine and serine. During training, SVM models were evaluated on leave-one-out cross validation, and the maximum prediction accuracies achieved during training were 100% glycine palmitoylation and 99.94% for serine palmitoylation. Similar prediction for performance was also shown on independent data sets. The two SVM models were used to develop a prediction method called RAREPalm. We provide web-server and standalone of RAREPalm, using the user that can predict the potential glycine and serine palmitoylation site(s) in a protein. Comparative analysis of glycine, serine, and cysteine palmitoylation was also done to analyze pathways and classes to which different forms of palmitoylation belong. We hope that our attempt will be useful in finding more glycine and serine that may undergo palmitoylation and expanding the information on these lesser known sites of palmitoylation.

miPepBase: A Database of Experimentally Verified Peptides Involved in Molecular Mimicry

Autoimmune diseases emerge due to several reasons, of which molecular mimicry i.e., similarity between the host's and pathogen's interacting peptides is an important reason. In the present study we have reported a database of only experimentally verified peptide sequences, which exhibit molecular mimicry. The database is named as miPepBase (Mimicry Peptide Database) and contains comprehensive information about mimicry proteins and peptides of both host (and model organism) and pathogen. It also provides information about physicochemical properties of protein and mimicry peptides, which might be helpful in predicting the nature of protein and optimization of protein expression. The miPepBase can be searched using a keyword or, by autoimmune disease(s) or by a combination of host and pathogen taxonomic group or their name. To facilitate the search of proteins and/or epitope in miPepBase, which is similar to the user's interest, BLAST search tool is also incorporated. miPepBase is an open access database and available at http://proteininformatics.org/mkumar/mipepbase.

Prediction of endoplasmic reticulum resident proteins using fragmented amino acid composition and support vector machine

Background

The endoplasmic reticulum plays an important role in many cellular processes, which includes protein synthesis, folding and post-translational processing of newly synthesized proteins. It is also the site for quality control of misfolded proteins and entry point of extracellular proteins to the secretory pathway. Hence at any given point of time, endoplasmic reticulum contains two different cohorts of proteins, (i) proteins involved in endoplasmic reticulum-specific function, which reside in the lumen of the endoplasmic reticulum, called as endoplasmic reticulum resident proteins and (ii) proteins which are in process of moving to the extracellular space. Thus, endoplasmic reticulum resident proteins must somehow be distinguished from newly synthesized secretory proteins, which pass through the endoplasmic reticulum on their way out of the cell. Approximately only 50% of the proteins used in this study as training data had endoplasmic reticulum retention signal, which shows that these signals are not essentially present in all endoplasmic reticulum resident proteins. This also strongly indicates the role of additional factors in retention of endoplasmic reticulum-specific proteins inside the endoplasmic reticulum.

Methods

This is a support vector machine based method, where we had used different forms of protein features as inputs for support vector machine to develop the prediction models. During training leave-one-out approach of cross-validation was used. Maximum performance was obtained with a combination of amino acid compositions of different part of proteins.

Results

In this study, we have reported a novel support vector machine based method for predicting endoplasmic reticulum resident proteins, named as ERPred. During training we achieved a maximum accuracy of 81.42% with leave-one-out approach of cross-validation. When evaluated on independent dataset, ERPred did prediction with sensitivity of 72.31% and specificity of 83.69%. We have also annotated six different proteomes to predict the candidate endoplasmic reticulum resident proteins in them. A webserver, ERPred, was developed to make the method available to the scientific community, which can be accessed at http://proteininformatics.org/mkumar/erpred/index.html.

Discussion

We found that out of 124 proteins of the training dataset, only 66 proteins had endoplasmic reticulum retention signals, which shows that these signals are not an absolute necessity for endoplasmic reticulum resident proteins to remain inside the endoplasmic reticulum. This observation also strongly indicates the role of additional factors in retention of proteins inside the endoplasmic reticulum. Our proposed predictor, ERPred, is a signal independent tool. It is tuned for the prediction of endoplasmic reticulum resident proteins, even if the query protein does not contain specific ER-retention signal.

Evaluation of Anti-Cyclic Citrullinated Peptide Autoantibodies and C-Reactive Protein in Common Autoimmune Skin Diseases with and without Arthritis

INTRODUCTION

Anti-Cyclic Citrullinated Peptides (CCPs) are a well known diagnostic and prognostic noble marker for rheumatoid arthritis. C-Reactive Protein (CRP) is an acute phase protein whose level rises in response to inflammation.

AIM

This study was undertaken to show the role of the two markers (anti-CCPs and CRP) in autoimmune skin disorder and their association with associated arthritis in these disorder.

MATERIALS AND METHODS

Serum anti-CCP antibodies and CRP was measured in 50 patients of autoimmune skin disease of which 28 were of psoriasis, 12 of Systemic Lupus Erythematosus (SLE) and 10 of Pemphigus Vulgaris (PV). These patients were categorised in two groups, with associated arthritis and without arthritis. The serum level of anti-CCP and CRP was correlated with the presence or absence of arthritis in these patients. Control group consists of 20 healthy subjects in which these two parameters were measured.

RESULTS

Out of total of 50 patients, anti-CCP was raised in 36.37% of patients with associated arthritis and 12.82% of patients without arthritis whereas CRP was raised in 63.63% of patients with arthritis and 35.89% of patients without arthritis. Mean serum anti-CCP in patient with arthritis was 15.78±13.94 U/ml and without arthritis was 7.56±7.68 U/ml with p=0.01 which was statistically significant. Mean serum CRP in arthritis was 21.11±15.51 mg/l and CRP without arthritis was 13.14±12.27 mg/l with p=0.07 which was statistically not significant.

CONCLUSION

Although both anti-CCP and CRP are valuable markers for autoimmune skin disorder, anti-CCP seems to show significant association with arthritis.

Estimation of serum Alpha feto-protein (AFP), interlukin-6 and Des-?-carboxyprothrombin (DCP) in case of hepatocellular carcinoma

Background: Hepatocellular carcinoma (HCC) is one the most common primary malignancy of the liver and represents the third leading cause of cancer-related deaths worldwide. Incidence rates are highest in East Asia and Sub-Saharan Africa. A number of evidence suggests a possible role of interleukin-6 (IL-6), ?-Fetoprotein (AFP) and Des-?-carboxyprothrombin (DCP) in the pathogenesis of hepatocellular carcinoma (HCC). The high DCP may be related to increase tumour behaviour, such as the presence of vascular invasion and intrahepatic metastasis of HCC cells. Patients and methods: We studied IL-6, AFP and DCP in patients with HCC or in healthy controls. AFP was measured by chemiluminescent immunoassay; Serum IL-6 and DCP were measured by enzyme linked immunosorbent assay in 30 patients with primary hepatocellular carcinoma and 30 normal subjects.Results: IL-6, AFP and DCP were found high in the serum of patients initially diagnosed with HCC (18±9.8), (315.99±594.62) and (26.15±5.01) respectively compared with healthy subjects (4.29±2.10), (3.13±1.27) and (4.25±1.22). A significant positive correlation was found between mean levels of IL- 6 & AFP in HCC (P < 0.05), Combination of IL-6, AFP and DCP improved the sensitivity in diagnosing HCC or predicting future HCC development. Conclusions: IL-6, DCP along with AFP could be considered a promising tumor marker for HCC. DCP is a well recognized tumor marker for the screening and diagnosis of HCC. In particular, the diagnostic value of the test is significantly increased when combined with AFP.Bangladesh Journal of Medical Science Vol.15(2) 2016 p.230-233

PredHSP: Sequence Based Proteome-Wide Heat Shock Protein Prediction and Classification Tool to Unlock the Stress Biology

Heat shock proteins are chaperonic proteins, which are present in every domain of life. They play a crucial role in folding/unfolding of proteins, their sorting and assembly into multi-protein complex, cell cycle control and also protect the cell during stress. Considering the fact that no web-based predictor is available for simultaneous prediction and classification of HSPs, it is imperative to develop a method, which can predict and classify them efficiently. In this study, we have developed coupled amino acid composition and support vector machine based two-tier method, PredHSP that identifies heat shock proteins (1^st tier) and classifies it to different families (at 2^nd tier). At 1^st tier, we achieved maximum accuracy 76.66% with MCC 0.43, while at 2^nd tier we achieved maximum accuracy 96.36% with MCC 0.87 for HSP20, 91.91% with MCC 0.83 for HSP40, 95.96% with MCC 0.72 for HSP60, 91.87% with MCC 0.71 for HSP70, 98.43% with MCC 0.70 for HSP90 and 97.48% with MCC 0.71 for HSP100. We have also developed a webserver, as well as standalone package for the use of scientific community, which can be accessed at http://14.139.227.92/mkumar/predhsp/index.html.

Biodegradation of pyrene and phenanthrene by bacterial consortium and evaluation of role of surfactant

High molecular weight poly aromatic hydrocarbons (HMW PAHs) are well known for their hydrophobicity and they get strongly adsorbed onto the soil particles. Generally, surfactants facilitate the biodegradation of PAH by enhancing their solubility and desorption of hydrophobic compounds from soil particles. To investigate the role of synthetic surfactant in biodegradation of PAHs, two bacterial strains BP10 and P2 were incubated in soil spiked with pyrene and phenantherene (100 μg g-1of soil each) in isolation and in combination with/without Tween 80. After 14 days of incubation, pyrene and phenantherene were degraded by a combination of BP10 and P2 to the extent of 98% and 99%, respectively. Addition of tween 80 reduced the degradation of pyrene and phenantherene by 35 and 10%, respectively. Biosurfactant produced by selected strains i.e. BP10 and P2 could enhance desorption of pyrene (100 μg g-1of soil) by about 27% and 12%, respectively. However, desorption activity was relatively higher (32 and 29%, respectively) in case of phenanthrene (100 μg g-1of soil) from the spiked soil. Present study showed that in spite of additional chemical surfactant, bioaugmentation of highly petroleum hydrocarbon degrading bacterial combination was very effective in boosting the bioremediation of PAHs- contaminated sites.

Low complexity and disordered regions of proteins have different structural and amino acid preferences

Low complexity regions (LCRs) or non-random regions of a few amino acids are abundantly present in proteins. LCRs are traditionally considered as floppy structures with high solvent accessibility. Thus little attention was paid to them for structural studies. However LCRs have been found to contain information relevant to protein structure and various important functions. The present study is an attempt to understand the structural trend of LCRs. Here we report a study conducted to understand the structural trend, solvent accessibility and amino acid preferences of LCRs. The results show that LCRs might attain any type of secondary structure; however, the helix is frequently seen, whereas sheets occur rarely. We also found that LCRs are not always exposed on the surface. We found insignificant contribution of trans-membrane helices to the overall helix content. The LCRs having a secondary structure have different enrichment and depletion of amino acids from LCRs without a secondary structure and disordered protein sequences. However, LCRs of NMR structures showed compositional and functional similarity to the disordered regions of proteins. We also noted that in ∼3/4 LCRs, the entire amino acid did not have a single structural class, but rather an ensemble of more than one secondary structure, which indicates that they are found at places where structure transition occurs. Overall analysis suggests that the overall protein sequence has a greater influence on the structural and sequence enrichment rather than only the local amino acid composition of LCRs.

NRfamPred: a proteome-scale two level method for prediction of nuclear receptor proteins and their sub-families

Nuclear receptor proteins (NRP) are transcription factor that regulate many vital cellular processes in animal cells. NRPs form a super-family of phylogenetically related proteins and divided into different sub-families on the basis of ligand characteristics and their functions. In the post-genomic era, when new proteins are being added to the database in a high-throughput mode, it becomes imperative to identify new NRPs using information from amino acid sequence alone. In this study we report a SVM based two level prediction systems, NRfamPred, using dipeptide composition of proteins as input. At the 1st level, NRfamPred screens whether the query protein is NRP or non-NRP; if the query protein belongs to NRP class, prediction moves to 2nd level and predicts the sub-family. Using leave-one-out cross-validation, we were able to achieve an overall accuracy of 97.88% at the 1st level and an overall accuracy of 98.11% at the 2nd level with dipeptide composition. Benchmarking on independent datasets showed that NRfamPred had comparable accuracy to other existing methods, developed on the same dataset. Our method predicted the existence of 76 NRPs in the human proteome, out of which 14 are novel NRPs. NRfamPred also predicted the sub-families of these 14 NRPs.

Protein sub-nuclear localization prediction using SVM and Pfam domain information

The nucleus is the largest and the highly organized organelle of eukaryotic cells. Within nucleus exist a number of pseudo-compartments, which are not separated by any membrane, yet each of them contains only a specific set of proteins. Understanding protein sub-nuclear localization can hence be an important step towards understanding biological functions of the nucleus. Here we have described a method, SubNucPred developed by us for predicting the sub-nuclear localization of proteins. This method predicts protein localization for 10 different sub-nuclear locations sequentially by combining presence or absence of unique Pfam domain and amino acid composition based SVM model. The prediction accuracy during leave-one-out cross-validation for centromeric proteins was 85.05%, for chromosomal proteins 76.85%, for nuclear speckle proteins 81.27%, for nucleolar proteins 81.79%, for nuclear envelope proteins 79.37%, for nuclear matrix proteins 77.78%, for nucleoplasm proteins 76.98%, for nuclear pore complex proteins 88.89%, for PML body proteins 75.40% and for telomeric proteins it was 83.33%. Comparison with other reported methods showed that SubNucPred performs better than existing methods. A web-server for predicting protein sub-nuclear localization named SubNucPred has been established at http://14.139.227.92/mkumar/subnucpred/. Standalone version of SubNucPred can also be downloaded from the web-server.

PalmPred: an SVM based palmitoylation prediction method using sequence profile information

Protein palmitoylation is the covalent attachment of the 16-carbon fatty acid palmitate to a cysteine residue. It is the most common acylation of protein and occurs only in eukaryotes. Palmitoylation plays an important role in the regulation of protein subcellular localization, stability, translocation to lipid rafts and many other protein functions. Hence, the accurate prediction of palmitoylation site(s) can help in understanding the molecular mechanism of palmitoylation and also in designing various related experiments. Here we present a novel in silico predictor called ‘PalmPred’ to identify palmitoylation sites from protein sequence information using a support vector machine model. The best performance of PalmPred was obtained by incorporating sequence conservation features of peptide of window size 11 using a leave-one-out approach. It helped in achieving an accuracy of 91.98%, sensitivity of 79.23%, specificity of 94.30%, and Matthews Correlation Coefficient of 0.71. PalmPred outperformed existing palmitoylation site prediction methods – IFS-Palm and WAP-Palm on an independent dataset. Based on these measures it can be anticipated that PalmPred will be helpful in identifying candidate palmitoylation sites. All the source datasets, standalone and web-server are available at http://14.139.227.92/mkumar/palmpred/.