Strategies adopted by gastric pathogen Helicobacter pylori for a mature biofilm formation: Antimicrobial peptides as a visionary treatment.

Enormous efforts in recent past two decades to eradicate the pathogen that has been prevalent in half of the world's population have been problematic. The biofilm formed by Helicobacter pylori provides resistance towards innate immune cells, various combinatorial antibiotics, and human antimicrobial peptides, despite the fact that these all are potent enough to eradicate it in vitro. Biofilm provides the opportunity to secrete various virulence factors that strengthen the interaction between host and pathogen helping in evading the innate immune system and ultimately leading to persistence. To our knowledge, this review is the first of its kind to explain briefly the journey of H. pylori starting with the chemotaxis, the mechanism for selecting the site for colonization, the stress faced by the pathogen, and various adaptations to evade these stress conditions by forming biofilm and the morphological changes acquired by the pathogen in mature biofilm. Furthermore, we have explained the human GI tract antimicrobial peptides and the reason behind the failure of these AMPs, and how encapsulation of Pexiganan-A(MSI-78A) in a chitosan microsphere increases the efficiency of eradication.

Erratum to "Perceptions and practices of COVID-19 protective measures among the general public of North India" [Clin Epidemiol Glob Health 13 (2022) 100927].

[This corrects the article DOI: 10.1016/j.cegh.2021.100927.].

Machine Learning-Based 30-Day Hospital Readmission Predictions for COPD Patients Using Physical Activity Data of Daily Living with Accelerometer-Based Device.

Chronic obstructive pulmonary disease (COPD) is a significantly concerning disease, and is ranked highest in terms of 30-day hospital readmission. Generally, physical activity (PA) of daily living reflects the health status and is proposed as a strong indicator of 30-day hospital readmission for patients with COPD. This study attempted to predict 30-day hospital readmission by analyzing continuous PA data using machine learning (ML) methods. Data were collected from 16 patients with COPD over 3877 days, and clinical information extracted from the patients' hospital records. Activity-based parameters were conceptualized and evaluated, and ML models were trained and validated to retrospectively analyze the PA data, identify the nonlinear classification characteristics of different risk factors, and predict hospital readmissions. Overall, this study predicted 30-day hospital readmission and prediction performance is summarized as two distinct approaches: prediction-based performance and event-based performance. In a prediction-based performance analysis, readmissions predicted with 70.35% accuracy; and in an event-based performance analysis, the total 30-day readmissions were predicted with a precision of 72.73%. PA data reflect the health status; thus, PA data can be used to predict hospital readmissions. Predicting readmissions will improve patient care, reduce the burden of medical costs burden, and can assist in staging suitable interventions, such as promoting PA, alternate treatment plans, or changes in lifestyle to prevent readmissions.

A comprehensive approach to discover Toxin-Antitoxin systems from human pathogen Helicobacter pylori: A poison and its antidote encapsulated in the genome.

AIM: An enormous presence and their identified role as stress managers, antibiotic resistance, persistence, and biofilm formation is the reason why the research on Toxin-Antitoxin (TA) loci is getting more and more emphasis. These set of genes consist of poison (Toxin) and its antidote (Antitoxin) expressing in an operon where the toxin inhibits the cellular process and antitoxin which can be a protein or non-coding RNA, rescues the toxin. Most recent progress in genomics and in silico studies have revealed new TA families, and types of TA on bacterial chromosome. However, there is almost no or very little is known about the TA in H. pylori. Therefore, this study aims to identify the TA genes in human pathogen using a comprehensive in silico approach. METHODOLOGY: Here, we have collected the genome-wide data of TA in H. pylori 26695 using TASmania, a new TA database. Further, entire TA dataset was validated with several other databases available for TA, operon analysis and experimental data available. KEY FINDINGS: The study revealed the presence of 80 putative TA genes in H. pylori and highlighted their similarity as well as uniqueness in comparison to other three known TA carrying human pathogens. SIGNIFICANCE: The present study indicates the presence of a large number of TA genes in H. pylori which make biofilm and goes into persistence. Hence, our innovative approach unlocks the prospect for characterizing these putative TA genes and their role as stress managers.

Perceptions and practices of COVID-19 protective measures among the general public of North India.

BACKGROUND: India has a high COVID-19 burden. The Indian government responded to the pandemic by mandating its population to adhere to certain Protective Measures (PMs). Compliance to these PMs depends on their acceptability and adaptability among the general public. AIMS: To explore the perceptions and practices of COVID-19 related PMs among the general public of North India. METHODS: Qualitative study in four administrative districts (Lucknow, Etawah, Patna and Darbhanga) of North India. Two urban and two rural districts were purposefully selected. Audio in-depth interviews (IDIs) were conducted with healthy caregivers of children (2-59 months). Data was managed using Atlast Ti and analyzed using conventional content analysis. RESULTS: From July-Sep 2020, 60 IDIs were conducted; 36.6% (22/60) were females and 26.6% (16/60) had below primary education. Respondents concurred that most people in their society flouted the recommended PMs. The reasons for poor/non-compliance with PMs were: perceived poor susceptibility to illness, perceived less severity of COVID-19 and low perceived benefits of complying with the PMs. Respondents opined that COVID-19 is less prevalent in rural areas and among the educated population. Most respondents were aware of the recommended PMs and opined that these must be followed, however subjective norms, social norms and behavioral intentions negatively impacted compliance. CONCLUSIONS: Since there was poor community perception of susceptibility to COVID-19 as well as poor perceived severity, the community did not understand the benefits of adhering to the recommended PMs. Therefore, future health communication strategies must take these into account to increase the possibility of success.

Clinicoepidemiological Profile and Genetic Characterization of Circulating Rotavirus Strain among Children < 5 Years Hospitalized for Acute Gastroenteritis in Western Rajasthan, India.

OBJECTIVE: To determine the clinical and epidemiological profile and circulating strains of rotavirus among children less than 5 y of age hospitalized for diarrhea in a tertiary care center of western Rajasthan. METHOD: Children < 5 y of age admitted for acute gastroenteritis were recruited in this hospital-based surveillance study. Detailed clinical history and sociodemographic information was collected for all enrolled children. Severity of the gastroenteritis was assessed using the 20-point Vesikari Clinical Severity Scoring System. Rotavirus positivity was tested in the stool samples collected from children by commercially available techniques and further molecular characterization done as per defined protocol. RESULTS: Out of 1055 enrolled children, overall positivity rate of typable rotavirus was 18.95% (169/892). Among children who were less than 24 mo of age, positivity due to rotavirus diarrhea was maximum (24.4%). Distinct seasonality was observed as maximum cases of rotavirus diarrhea were detected in the months of December to February. Commonest G type was G3 (54%) followed by G1 (19%) while predominant P type was P[8] (77%) followed by P[4] (11%). G3P[8] (51.83%) was the commonest genotype observed in the study region. CONCLUSION: The current study found positivity of rotavirus to be 18.95% among children aged 0-59 mo admitted due to acute gastroenteritis is a tertiary care setting in northern part of India. Emergence of newer predominant strains emphasizes the need of continued surveillance to determine the changing trends.

High throughput and comprehensive approach to develop multiepitope vaccine against minacious COVID-19.

The ongoing enigmatic COVID-19 outbreak, first reported from Wuhan, China, on last day of the year 2019, which has spread to 213 countries, territories/areas till 28th April 2020, threatens hundreds of thousands human souls. This devastating viral infection has stimulated the urgent development of viable vaccine against COVID-19 across the research institutes around the globe. The World Health Organization (WHO) has also confirmed that the recent pandemic is causing Public Health Emergency of International apprehension. Moreover, the earlier two pathogenic SARS-CoV and MERS-CoV and many others yet to be identified pose a universal menace. Here, in this piece of work, we have utilized an in silico structural biology and advanced immunoinformatic strategies to devise a multi-epitope subunit vaccine against ongoing COVID-19 infection. The engineered vaccine sequence is adjuvanted with ß-3 defensin and comprised of B-cell epitopes, HTL epitopes and CTL epitopes. This is very likely that the vaccine will be able to elicit the strong immune response. Further, specific binding of the engineered vaccine and immune cell receptor TLR3 was estimated by molecular interaction studies. Strong interaction in the binding groove as well as good docking scores affirmed the stringency of engineered vaccine. The interaction is stable with minimal deviation in root-mean square deviation and root-mean-square fluctuation was confirmed by the molecular dynamics simulation experiment. The immune-simulation by C-ImmSim server, which mimics the natural immune environment, yielded more potent immune response data of B-cells, Th cells, Tc cells and IgG for vaccine. The encouraging data obtained from the various in-silico works indicated this vaccine as an effective therapeutic against COVID-19.

Receptor-ligand based molecular interaction to discover adjuvant for immune cell TLRs to develop next-generation vaccine.

Human immune cell toll-like receptors (TLRs) provide a novel chance for the development of the vaccine adjuvant engaging TLR signaling. A library of peptides was developed and peptides structure was generated through homology modeling and refinement. Further, these peptides were subjected to receptor-ligand interaction study against human immune cell TLRs using Schrödinger-suite software. Here, we identified the most potent ligands for each human immune cell receptor and identified it as a potent adjuvant. This work portrays the ability of binding of different known protein adjuvants with human TLRs 1--10. The significance of the study deals with the identification of adjuvant (ligand) for human TLRs individually which assist in the development of the optimal highly immunogenic vaccine.

Structural vaccinology approach to investigate the virulent and secretory proteins of Bacillus anthracis for devising anthrax next-generation vaccine.

Communicated by Ramaswamy H. Sarma.

Cloning, expression and characterization of a thermo-alkali-stable xylanase from Aspergillus oryzae LC1 in Escherichia coli BL21(DE3).

In the present investigation, cloning and overexpression of xylanase (XynF1), the main xylanase of A. oryzae LC1, was performed in prokaryotic system E. coli BL21(DE3) to produce recombinant xylanase with high titer of specific activity (1037.3 U/mg), which was 9.3-fold higher than the native strain. Further, the recombinant XynF1 of size 37 kDa was purified using Ni2+-NTA resins followed by cation exchange chromatography, which showed an 1.8-fold increase in purity with 71.4% yield. The r-XynF1 exhibited a wide range of activity at different pH (3.0-10.0) range and temperature (30-70 °C) with an optimum pH at 5.0 and temperature at 30 °C. The results from the current study, clearly demonstrate that this is an effective method to generate a recombinant enzyme with improved activity, making it useful for possible industrial applications.

Prediction of 30-Day Readmission for COPD Patients Using Accelerometer-Based Activity Monitoring.

Chronic obstructive pulmonary disease (COPD) claimed 3.0 million lives in 2016 and ranked 3rd among the top 10 global causes of death. Moreover, once diagnosed and discharged from the hospital, the 30-day readmission risk in COPD patients is found to be the highest among all chronic diseases. The existing diagnosis methods, such as Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2019, Body-mass index, airflow Obstruction, Dyspnea, and Exercise (BODE) index, modified Medical Research Council (mMRC), COPD assessment test (CAT), 6-minute walking distance, which are adopted currently by physicians cannot predict the potential readmission of COPD patients, especially within the 30 days after discharge from the hospital. In this paper, a statistical model was proposed to predict the readmission risk of COPD patients within 30-days by monitoring their physical activity (PA) in daily living with accelerometer-based wrist-worn wearable devices. This proposed model was based on our previously reported PA models for activity index (AI) and regularity index (RI) and it introduced a new parameter, quality of activity (QoA), which incorporates previously proposed parameters, such as AI and RI, with other activity-based indices to predict the readmission risk. Data were collected from continuous PA monitoring of 16 COPD patients after hospital discharge as test subjects and readmission prediction criteria were proposed, with a 63% sensitivity and a 37.78% positive prediction rate. Compared to other clinical assessment, diagnosis, and prevention methods, the proposed model showed significant improvement in predicting the 30-day readmission risk.

Activity Monitoring with a Wrist-Worn, Accelerometer-Based Device.

This study condenses huge amount of raw data measured from a MEMS accelerometer-based, wrist-worn device on different levels of physical activities (PAs) for subjects wearing the device 24 h a day continuously. In this study, we have employed the device to build up assessment models for quantifying activities, to develop an algorithm for sleep duration detection and to assess the regularity of activity of daily living (ADL) quantitatively. A new parameter, the activity index (AI), has been proposed to represent the quantity of activities and can be used to categorize different PAs into 5 levels, namely, rest/sleep, sedentary, light, moderate, and vigorous activity states. Another new parameter, the regularity index (RI), was calculated to represent the degree of regularity for ADL. The methods proposed in this study have been used to monitor a subject's daily PA status and to access sleep quality, along with the quantitative assessment of the regularity of activity of daily living (ADL) with the 24-h continuously recorded data over several months to develop activity-based evaluation models for different medical-care applications. This work provides simple models for activity monitoring based on the accelerometer-based, wrist-worn device without trying to identify the details of types of activity and that are suitable for further applications combined with cloud computing services.

Levels of activity identification & sleep duration detection with a wrist-worn accelerometer-based device.

In this study, a model for identifying the levels of physical activity (PA) with a wrist-worn accelerometer-based device has been proposed. The levels of identified PA have been categorized into rest/sleep, sedentary, light, moderate, and vigorous activity states by analyzing the data collected from 10 normal subjects. An activity-based sleep duration detection algorithm has been proposed and implemented thereafter to further distinguish activities between short period of rest and sleep. The model and method proposed in this study could be further used to monitor subject's daily PA status and sleep quality assessment in the future for various home-based healthcare applications.