MEK inhibition reprograms CD8+ T lymphocytes into memory stem cells with potent antitumor effects.

Regenerative stem cell-like memory (TSCM) CD8+ T cells persist longer and produce stronger effector functions. We found that MEK1/2 inhibition (MEKi) induces TSCM that have naive phenotype with self-renewability, enhanced multipotency and proliferative capacity. This is achieved by delaying cell division and enhancing mitochondrial biogenesis and fatty acid oxidation, without affecting T cell receptor-mediated activation. DNA methylation profiling revealed that MEKi-induced TSCM cells exhibited plasticity and loci-specific profiles similar to bona fide TSCM isolated from healthy donors, with intermediate characteristics compared to naive and central memory T cells. Ex vivo, antigenic rechallenge of MEKi-treated CD8+ T cells showed stronger recall responses. This strategy generated T cells with higher efficacy for adoptive cell therapy. Moreover, MEKi treatment of tumor-bearing mice also showed strong immune-mediated antitumor effects. In conclusion, we show that MEKi leads to CD8+ T cell reprogramming into TSCM that acts as a reservoir for effector T cells with potent therapeutic characteristics.

Author Correction: PD-1 blockade in subprimed CD8 cells induces dysfunctional PD-1+CD38hi cells and anti-PD-1 resistance.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

PD-1 blockade in subprimed CD8 cells induces dysfunctional PD-1+CD38hi cells and anti-PD-1 resistance.

Understanding resistance to antibody to programmed cell death protein 1 (PD-1; anti-PD-1) is crucial for the development of reversal strategies. In anti-PD-1-resistant models, simultaneous anti-PD-1 and vaccine therapy reversed resistance, while PD-1 blockade before antigen priming abolished therapeutic outcomes. This was due to induction of dysfunctional PD-1+CD38hi CD8+ cells by PD-1 blockade in suboptimally primed CD8 cell conditions induced by tumors. This results in erroneous T cell receptor signaling and unresponsiveness to antigenic restimulation. On the other hand, PD-1 blockade of optimally primed CD8 cells prevented the induction of dysfunctional CD8 cells, reversing resistance. Depleting PD-1+CD38hi CD8+ cells enhanced therapeutic outcomes. Furthermore, non-responding patients showed more PD-1+CD38+CD8+ cells in tumor and blood than responders. In conclusion, the status of CD8+ T cell priming is a major contributor to anti-PD-1 therapeutic resistance. PD-1 blockade in unprimed or suboptimally primed CD8 cells induces resistance through the induction of PD-1+CD38hi CD8+ cells that is reversed by optimal priming. PD-1+CD38hi CD8+ cells serve as a predictive and therapeutic biomarker for anti-PD-1 treatment. Sequencing of anti-PD-1 and vaccine is crucial for successful therapy.

iACP-MultiCNN: Multi-channel CNN based anticancer peptides identification.

Cancer is one of the most dangerous diseases in the world that often leads to misery and death. Current treatments include different kinds of anticancer therapy which exhibit different types of side effects. Because of certain physicochemical properties, anticancer peptides (ACPs) have opened a new path of treatments for this deadly disease. That is why a well-performed methodology for identifying novel anticancer peptides has great importance in the fight against cancer. In addition to the laboratory techniques, various machine learning and deep learning methodologies have developed in recent years for this task. Although these models have shown reasonable predictive ability, there's still room for improvement in terms of performance and exploring new types of algorithms. In this work, we have proposed a novel multi-channel convolutional neural network (CNN) for identifying anticancer peptides from protein sequences. We have collected data from the existing state-of-the-art methodologies and applied binary encoding for data preprocessing. We have also employed k-fold cross-validation to train our models on benchmark datasets and compared our models' performance on the independent datasets. The comparison has indicated our models' superiority on various evaluation metrics. We think our work can be a valuable asset in finding novel anticancer peptides. We have provided a user-friendly web server for academic purposes and it is publicly available at: http://103.99.176.239/iacp-cnn/.

Barriers to Infection of Human Cells by Feline Leukemia Virus: Insights into Resistance to Zoonosis.

The human genome displays a rich fossil record of past gammaretrovirus infections, yet no current epidemic is evident, despite environmental exposure to viruses that infect human cells in vitro Feline leukemia viruses (FeLVs) rank high on this list, but neither domestic nor workplace exposure has been associated with detectable serological responses. Nonspecific inactivation of gammaretroviruses by serum factors appears insufficient to explain these observations. To investigate further, we explored the susceptibilities of primary and established human cell lines to FeLV-B, the most likely zoonotic variant. Fully permissive infection was common in cancer-derived cell lines but was also a feature of nontransformed keratinocytes and lung fibroblasts. Cells of hematopoietic origin were generally less permissive and formed discrete groups on the basis of high or low intracellular protein expression and virion release. Potent repression was observed in primary human blood mononuclear cells and a subset of leukemia cell lines. However, the early steps of reverse transcription and integration appear to be unimpaired in nonpermissive cells. FeLV-B was subject to G→A hypermutation with a predominant APOBEC3G signature in partially permissive cells but was not mutated in permissive cells or in nonpermissive cells that block secondary viral spread. Distinct cellular barriers that protect primary human blood cells are likely to be important in protection against zoonotic infection with FeLV.IMPORTANCE Domestic exposure to gammaretroviruses such as feline leukemia viruses (FeLVs) occurs worldwide, but the basis of human resistance to infection remains incompletely understood. The potential threat is evident from the human genome sequence, which reveals many past epidemics of gammaretrovirus infection, and from recent cross-species jumps of gammaretroviruses from rodents to primates and marsupials. This study examined resistance to infection at the cellular level with the most prevalent human cell-tropic FeLV variant, FeLV-B. We found that blood cells are uniquely resistant to infection with FeLV-B due to the activity of cellular enzymes that mutate the viral genome. A second block, which appears to suppress viral gene expression after the viral genome has integrated into the host cell genome, was identified. Since cells derived from other normal human cell types are fully supportive of FeLV replication, innate resistance of blood cells could be critical in protecting against cross-species infection.

Homeostatic PPARα Signaling Limits Inflammatory Responses to Commensal Microbiota in the Intestine.

Dietary lipids and their metabolites activate members of the peroxisome proliferative-activated receptor (PPAR) family of transcription factors and are critical for colonic health. The PPARα isoform plays a vital role in regulating inflammation in various disease settings, but its role in intestinal inflammation, commensal homeostasis, and mucosal immunity in the gut are unclear. In this study, we demonstrate that the PPARα pathway in innate immune cells orchestrates gut mucosal immunity and commensal homeostasis by regulating the expression of IL-22 and the antimicrobial peptides RegIIIß, RegIIIγ, and calprotectin. Additionally, the PPARα pathway is critical for imparting regulatory phenotype in intestinal macrophages. PPARα deficiency in mice led to commensal dysbiosis in the gut, resulting in a microbiota-dependent increase in the expression of inflammatory cytokines and enhanced susceptibility to intestinal inflammation. Pharmacological activation of this pathway decreased the expression of inflammatory cytokines and ameliorated colonic inflammation. Taken together, these findings identify a new important innate immune function for the PPARα signaling pathway in regulating intestinal inflammation, mucosal immunity, and commensal homeostasis. Thus, the manipulation of the PPARα pathway could provide novel opportunities for enhancing mucosal immunity and treating intestinal inflammation.

predCar-site: Carbonylation sites prediction in proteins using support vector machine with resolving data imbalanced issue.

The carbonylation is found as an irreversible post-translational modification and considered a biomarker of oxidative stress. It plays major role not only in orchestrating various biological processes but also associated with some diseases such as Alzheimer's disease, diabetes, and Parkinson's disease. However, since the experimental technologies are costly and time-consuming to detect the carbonylation sites in proteins, an accurate computational method for predicting carbonylation sites is an urgent issue which can be useful for drug development. In this study, a novel computational tool termed predCar-Site has been developed to predict protein carbonylation sites by (1) incorporating the sequence-coupled information into the general pseudo amino acid composition, (2) balancing the effect of skewed training dataset by Different Error Costs method, and (3) constructing a predictor using support vector machine as classifier. This predCar-Site predictor achieves an average AUC (area under curve) score of 0.9959, 0.9999, 1, and 0.9997 in predicting the carbonylation sites of K, P, R, and T, respectively. All of the experimental results along with AUC are found from the average of 5 complete runs of the 10-fold cross-validation and those results indicate significantly better performance than existing predictors. A user-friendly web server of predCar-Site is available at http://research.ru.ac.bd/predCar-Site/.

History of UV Lamps, Types, and Their Applications.

The use of ultraviolet (UV) light, for the treatment of skin conditions, dates back to the early 1900s. It is well known that sunlight can be of therapeutic value, but it can also lead to deleterious effects such as burning and carcinogenesis. Extensive research has expanded our understanding of UV radiation and its effects in human systems and has led to the development of man-made UV sources that are more precise, safer, and more effective for the treatment of wide variety of dermatologic conditions.

Predictors for progression of metastatic prostate cancer to castration-resistant prostate cancer in Indians.

BACKGROUND & OBJECTIVES: There is lack of data on natural history and progression of prostate cancer (PC) which have implications in the management of the disease. We undertook this retrospective study to analyze factors predicting progression of metastatic PC to castration-resistant prostate cancer (CRPC) in Indian men. METHODS: Complete records of 223 of the 489 patients with metastatic PC were obtained from computerized data based system in a tertiary care hospital in north India between January 2000 to June 2012. Patients with follow up of < 6 months were excluded. Age (≤ and > 65 yr), baseline PSA (< and ≥ 50 ng/ml), bone scan and Gleason score (≤7 and >7) were recorded. Extent of bone disease (EOD) was stratified according to the number of bone lesions i.e., < 5, 5-10, > 10. CRPC was defined as two consecutive PSA rise of > 50 per cent from nadir or an absolute value of > 5 ng/ml. RESULTS: Mean age of patients was 61.5 ± 12.45 yr and their PSA level was 325.6 ± 631.35 ng/dl. Of the 223 patients, 193 (86%) progressed to CRPC at median time of 10.7 (4-124) months. Median follow up was 24 (6-137) months. On univariate and multivariate analyses EOD on bone scan was found to be a significant predictor ( P=0.006) for time to CRPC. Median time to CRPC was 10 months (CI 95%, 7.5-12.48) with >10 lesions or super scan versus 16 months (CI 95%, 10.3-21.6) with <10 bone lesion (P=0.01). Ninety (46.6 %) patients of CRPC died with median time to death from time of CRPC 21 (10-120) months. INTERPRETATION & CONCLUSIONS: Median time for progression of metastatic PC to CRPC ranged from 10-16 months depending on the extent of the bone involvement. In Indians, the aggressive course of advanced prostate cancer warrants further clinical trials to explore the need for additional treatment along with initial castration.

The surface glycoprotein of feline leukemia virus isolate FeLV-945 is a determinant of altered pathogenesis in the presence or absence of the unique viral long terminal repeat.

Feline leukemia virus (FeLV) is a naturally transmitted gammaretrovirus that infects domestic cats. FeLV-945, the predominant isolate associated with non-T-cell disease in a natural cohort, is a member of FeLV subgroup A but differs in sequence from the FeLV-A prototype, FeLV-A/61E, in the surface glycoprotein (SU) and long terminal repeat (LTR). Substitution of the FeLV-945 LTR into FeLV-A/61E resulted in pathogenesis indistinguishable from that of FeLV-A/61E, namely, thymic lymphoma of T-cell origin. In contrast, substitution of both FeLV-945 LTR and SU into FeLV-A/61E resulted in multicentric lymphoma of non-T-cell origin. These results implicated the FeLV-945 SU as a determinant of pathogenic spectrum. The present study was undertaken to test the hypothesis that FeLV-945 SU can act in the absence of other unique sequence elements of FeLV-945 to determine the disease spectrum. Substitution of FeLV-A/61E SU with that of FeLV-945 altered the clinical presentation and resulted in tumors that demonstrated expression of CD45R in the presence or absence of CD3. Despite the evident expression of CD45R, a typical B-cell marker, T-cell receptor beta (TCRß) gene rearrangement indicated a T-cell origin. Tumor cells were detectable in bone marrow and blood at earlier times during the disease process, and the predominant SU genes from proviruses integrated in tumor DNA carried markers of genetic recombination. The findings demonstrate that FeLV-945 SU alters pathogenesis, although incompletely, in the absence of FeLV-945 LTR. Evidence demonstrates that FeLV-945 SU and LTR are required together to fully recapitulate the distinctive non-T-cell disease outcome seen in the natural cohort.

Free to total serum prostate specific antigen ratio in symptomatic men does not help in differentiating benign from malignant disease of the prostate.

INTRODUCTION: Free to total prostate specific antigen ratio (f/t PSA) has been used to help improving specificity of PSA in the range of 4-10 ng/ml based on the data on population based screening. There is no data on test characteristics of f/t PSA in men presenting with clinical symptoms of benign prostatic hyperplasia (BPH). This study is aimed to determine the usefulness of f/t PSA in symptomatic men. METHODOLOGY: From January 2006 to June 2012, men of 50-75 years with lower urinary tract symptoms (LUTS), normal rectal examination and PSA between 4-20 ng/ml had free and total PSA assessment. Men with clinical evidence of prostatitis, retention, history of 5α blocker reductase inhibitors and those who had surgery or biopsy on the prostate in last 3 months were excluded. Receiver operating characteristic curves were derived for f/t PSA and total PSA. The effect of age, prostate volume and Gleason score on the f/t PSA was also analyzed. All statistical analyses were performed on SPSS 16 (Chicago, USA). RESULTS: Out of 170 men with the mean age of 67.4 ± 6.6 years, 43 (25.3%) had cancer on biopsy. Area under the curve for predicting the presence or absence of prostate cancer in all the men with f/t ratio was 0.63 (confidence interval [CI]: 0.54-0.71). The median value of f/t PSA for men with cancer was 5.5% (1-25%) and 9.2% (1-63%) for those with no cancer. Cut-offs derived at 95% specificity at PSA between 4-10 ng/ml and 4-20 ng/ml were 0.5% and 1% respectively. The specificity of f/t PSA ratio at cut-off levels 7%, 10% and 15% was 73%, 60%, 45% for PSA range of 4-10 ng/ml and 63%, 47% and 35% for PSA range of 4-20 ng/ml PSA. Age, prostate volume and Gleason grade did not show any effect on f/t PSA. CONCLUSION: In men with LUTS the specificity of various f/t PSA ratio cut-offs; described for population based screening, is too low to be used as an aid to defer the decision of biopsy in PSA ranges of 4-20 ng/ml.

Synthesis and biological evaluation of some novel sulfamoylphenyl-pyridazinone as anti-inflammatory agents (Part-II * ).

Seven novel 6-aryl-2-(p-sulfamoylphenyl)-4,5-dihydropyridazin-3(2H)-ones (2a-g) were synthesized by the condensation of appropriate aroylpropionic acid and 4-hydrazinobenzenesulfonamide hydrochloride in ethanol. Structure of all compounds have been elucidated by elemental analysis, IR, (1)H NMR, (13)C NMR, DEPT and MS spectrscopy. These compounds were tested for their anti-inflammatory activity in carrageenan-induced rat paw edema model. Compound 2b exhibited anti-inflammatory activity comparable to that of celecoxib (at 5 h). Two other compounds 2d and 2g showed promising anti-inflammatory activity (edema reduction more than 80% at 5 h). These compounds (2b, 2d and 2g) did not produce any ulceration in gastric region.

Introduction to diabetes mellitus.

The chronic metabolic disorder diabetes mellitus is a fast-growing global problem with huge social, health, and economic consequences. It is estimated that in 2010 there were globally 285 million people (approximately 6.4% of the adult population) suffering from this disease. This number is estimated to increase to 430 million in the absence of better control or cure. An ageing population and obesity are two main reasons for the increase. Furthermore it has been shown that almost 50% of the putative diabetics are not diagnosed until 10 years after onset of the disease, hence the real prevalence of global diabetes must be astronomically high. This chapter introduces the types of diabetes and diabetic complications such as impairment of immune system, periodontal disease, retinopathy, nephropathy, somatic and autonomic neuropathy, cardiovascular diseases and diabetic foot. Also included are the current management and treatments, and emerging therapies.

Accurately predicting nitrosylated tyrosine sites using probabilistic sequence information.

Post-translational modification (PTM) is defined as the enzymatic changes of proteins after the translation process in protein biosynthesis. Nitrotyrosine, which is one of the most important modifications of proteins, is interceded by the active nitrogen molecule. It is known to be associated with different diseases including autoimmune diseases characterized by chronic inflammation and cell damage. Currently, nitrotyrosine sites are identified using experimental approaches which are laborious and costly. In this study, we propose a new machine learning method called PredNitro to accurately predict nitrotyrosine sites. To build PredNitro, we use sequence coupling information from the neighboring amino acids of tyrosine residues along with a support vector machine as our classification technique.Our results demonstrates that PredNitro achieves 98.0% accuracy with more than 0.96 MCC and 0.99 AUC in both 5-fold cross-validation and jackknife cross-validation tests which are significantly better than those reported in previous studies. PredNitro is publicly available as an online predictor at: http://103.99.176.239/PredNitro.

predML-Site: Predicting Multiple Lysine PTM Sites With Optimal Feature Representation and Data Imbalance Minimization.

Identifying of post-translational modifications (PTM) is crucial in the study of computational proteomics, cell biology, pathogenesis, and drug development due to its role in many bio-molecular mechanisms. Computational methods for predicting multiple PTM at the same lysine residues, often referred to as K-PTM, is still evolving. This paper presents a novel computational tool, abbreviated as predML-Site, for predicting KPTM, such as acetylation, crotonylation, methylation, succinylation from an uncategorized peptide sample involving single, multiple, or no modification. For informative feature representation, multiple sequence encoding schemes, such as the sequence-coupling, binary encoding, k-spaced amino acid pairs, amino acid factor have been used with ANOVA and incremental feature selection. As a core predictor, a cost-sensitive SVM classifier has been adopted which effectively mitigates the effect of class-label imbalance in the dataset. predML-Site predicts multi-label PTM sites with 84.18% accuracy using the top 91 features. It has also achieved 85.34% aiming and 86.58% coverage rate which are much better than the existing state-of-the-art predictors on the same rigorous validation test. This performance indicates that predML-Site can be used as a supportive tool for further K-PTM study. For the convenience of the experimental scientists, predML-Site has been deployed as a user-friendly web-server at http://103.99.176.239/predML-Site.

Myoelectric Pattern Recognition Performance Enhancement Using Nonlinear Features.

The multichannel electrode array used for electromyogram (EMG) pattern recognition provides good performance, but it has a high cost, is computationally expensive, and is inconvenient to wear. Therefore, researchers try to use as few channels as possible while maintaining improved pattern recognition performance. However, minimizing the number of channels affects the performance due to the least separable margin among the movements possessing weak signal strengths. To meet these challenges, two time-domain features based on nonlinear scaling, the log of the mean absolute value (LMAV) and the nonlinear scaled value (NSV), are proposed. In this study, we validate the proposed features on two datasets, the existing four feature extraction methods, variable window size, and various signal-to-noise ratios (SNR). In addition, we also propose a feature extraction method where the LMAV and NSV are grouped with the existing 11 time-domain features. The proposed feature extraction method enhances accuracy, sensitivity, specificity, precision, and F1 score by 1.00%, 5.01%, 0.55%, 4.71%, and 5.06% for dataset 1, and 1.18%, 5.90%, 0.66%, 5.63%, and 6.04% for dataset 2, respectively. Therefore, the experimental results strongly suggest the proposed feature extraction method, for taking a step forward with regard to improved myoelectric pattern recognition performance.

Nomogram-Based Chronic Kidney Disease Prediction Model for Type 1 Diabetes Mellitus Patients Using Routine Pathological Data.

Type 1 diabetes mellitus (T1DM) patients are a significant threat to chronic kidney disease (CKD) development during their life. However, there is always a high chance of delay in CKD detection because CKD can be asymptomatic, and T1DM patients bypass traditional CKD tests during their routine checkups. This study aims to develop and validate a prediction model and nomogram of CKD in T1DM patients using readily available routine checkup data for early CKD detection. This research utilized 1375 T1DM patients' sixteen years of longitudinal data from multi-center Epidemiology of Diabetes Interventions and Complications (EDIC) clinical trials conducted at 28 sites in the USA and Canada and considered 17 routinely available features. Three feature ranking algorithms, extreme gradient boosting (XGB), random forest (RF), and extremely randomized trees classifier (ERT), were applied to create three feature ranking lists, and logistic regression analyses were performed to develop CKD prediction models using these ranked feature lists to identify the best performing top-ranked features combination. Finally, the most significant features were selected to develop a multivariate logistic regression-based CKD prediction model for T1DM patients. This model was evaluated using sensitivity, specificity, accuracy, precision, and F1 score on train and test data. A nomogram of the final model was further generated for easy application in clinical practices. Hypertension, duration of diabetes, drinking habit, triglycerides, ACE inhibitors, low-density lipoprotein (LDL) cholesterol, age, and smoking habit were the top-8 features ranked by the XGB model and identified as the most important features for predicting CKD in T1DM patients. These eight features were selected to develop the final prediction model using multivariate logistic regression, which showed 90.04% and 88.59% accuracy in internal and test data validation. The proposed model showed excellent performance and can be used for CKD identification in T1DM patients during routine checkups.

Prevalence of heavy metal resistance in bacteria isolated from tannery effluents and affected soil.

In the present study, a total of 198 bacteria were isolated, 88 from the tannery effluents and 110 from agricultural soil irrigated with the tannery effluents. Tannery effluents and soils were analyzed for metal concentrations by atomic absorption spectrophotometer. The tannery effluents and soil samples were found to be contaminated with chromium, nickel, zinc, copper, and cadmium. All isolates were tested for their resistance against Cr(6+ ), Cr(3+ ), Ni(2+ ), Zn(2+ ), Cu(2+ ), Cd(2+ ), and Hg(2+ ). From the total of 198 isolates, maximum bacterial isolates were found to be resistant to Cr(6+ ) 178 (89.9%) followed by Cr(3+ ) 146 (73.7%), Cd(2+ ) 86 (43.4%), Zn(2+ ) 83 (41.9%), Ni(2+ ) 61 (30.8%), and Cu(2+ ) 51 (25.6%). However, most of the isolates were sensitive to Hg(2+ ). Among the isolates from tannery effluents, 97.8% were resistant to Cr(6+ ) and 64.8% were resistant to Cr(3+ ). Most of the soil isolates were resistant against Cr(6+ ) (83.6%) and Cr(3+ ) (81.8%). All isolates were categorized into Gram-positive and Gram-negative bacteria. In a total of 114 Gram-positive isolates, 91.2% were resistant to Cr(6+ ) followed by 73.7% to Cr(3+ ), 42.1% to Zn(2+ ), 40.4% to Cd(2+ ), and 32.5% to Ni(2+ ). Among Gram-negative isolates, 88.1% were found showing resistance to Cr(6+ ), 75.0% to Cr(3+ ), and 47.6% were resistant to Cd(2+ ). Majority of these metal-resistant isolates were surprisingly found sensitive to the ten commonly used antibiotics. Out of 198 isolates, 114 were found sensitive to all antibiotics whereas only two isolates were resistant to maximum eight antibiotics at a time. Forty-one and 40 isolates which constitute 20.7% and 20.2% were resistant to methicilin and amoxicillin, respectively.

A new approach to expert reviewer detection and product rating derivation from online experiential product reviews.

Consumer reviews have emerged as one of the most influential factors in a person's purchase behavior. The existing open-source approaches for detecting expert reviewers and determining product ratings suffer from limitations and are susceptible to manipulation. In this work, we addressed these limitations by developing two algorithms and evaluated them on three datasets from amazon.com (the largest dataset contains nearly eight million reviews). In the first algorithm, we used a combination of the existing open-source approaches such as filtering by volume of contribution, helpfulness ratio, volume of helpfulness, and deviation from the estimated actual rating to detect the experts. The second algorithm is based on link analytic mutual iterative reinforcement of product ratings and reviewers' weights. In the second algorithm, both reviewers and products carry weights reflecting their relative importance. The reviewers influence the product rating according to their weight. Similarly, the reviewers' weights are impacted by their amount of deviation from the estimated actual product rating and the product's weight. Our evaluation using three datasets from amazon.com found the second algorithm superior to the other algorithms in detecting experts and deriving product ratings, significantly reducing the avg. error and avg. Mean Squared Error of the experts over the best of the other algorithms even after maintaining similar product coverage and quantity of reviews.

COVID-19 health safety practices: Influence on grocery shopping behavior.

During COVID-19 lockdown, individuals were asked to leave their home only to meet the most urgent needs, such as grocery purchases and medical emergencies. This study aimed to know the consumers' health safety practices and their concerns toward grocery shopping and to know their adoption of healthier food as a result of the outbreak. An online survey was conducted during the second month of the COVID-19 lockdown. This study includes 212 respondents. Appropriate statistical tools were used to analyze the data. The findings of the study revealed that females were ahead compared to males in pursuing health safety practices during grocery shopping, but the frequency of following physical distancing for both males and females was not up to the mark. The most important concern about grocery shopping was fear of unavailability of stocks and fear of getting infected from grocery storekeepers. It was also found that, compared to earlier, people had reduced their frequency of grocery shopping and tried to shop quickly and efficiently. People bought more packaged foods and also made purchases from brands that were new to them. As a result of the COVID-19 pandemic, the adoption of healthier food habits varied significantly with gender, age, and household income of the respondents. This study indicates that there is a need to raise awareness among people on how to shop safely in grocery stores and that good hygiene practice should be followed in grocery stores to mitigate the risk of infection to consumers.