Exploring complexity of class-A Beta-lactamase family using physiochemical-based multiplex networks.

The Beta-lactamase protein family is vital in countering Beta-lactam antibiotics, a widely used antimicrobial. To enhance our understanding of this family, we adopted a novel approach employing a multiplex network representation of its multiple sequence alignment. Each network layer, derived from the physiochemical properties of amino acids, unveils distinct insights into the intricate interactions among nodes, thereby enabling the identification of key motifs. Nodes with identical property signs tend to aggregate, providing evidence of the presence of consequential functional and evolutionary constraints shaping the Beta-lactamase family. We further investigate the distribution of evolutionary links across various layers. We observe that polarity manifests the highest number of unique links at lower thresholds, followed by hydrophobicity and polarizability, wherein hydrophobicity exerts dominance at higher thresholds. Further, the combinations of polarizability and volume, exhibit multiple simultaneous connections at all thresholds. The combination of hydrophobicity, polarizability, and volume uncovers shared links exclusive to these layers, implying substantial evolutionary impacts that may have functional or structural implications. By assessing the multi-degree of nodes, we unveil the hierarchical influence of properties at each position, identifying crucial properties responsible for the protein's functionality and providing valuable insights into potential targets for modulating enzymatic activity.

Analysing role of airborne particulate matter in abetting SARS-CoV-2 outbreak for scheming regional pandemic regulatory modalities.

The mutating SARS-CoV-2 necessitates gauging the role of airborne particulate matter in the COVID-19 outbreak for designing area-specific regulation modalities based on the environmental state-of-affair. To scheme the protocols, the hotspots of air pollutants such as PM2.5, PM10, NH3, NO, NO2, SO2, and and environmental factors including relative humidity (RH), and temperature, along with COVID-19 cases and mortality from January 2020 till December 2020 from 29 different ground monitoring stations spanning Delhi, are mapped. Spearman correlation coefficients show a positive relationship between SARS-COV-2 with particulate matter (PM2.5 with r > 0.36 and PM10 with r > 0.31 and p-value <0·001). Besides, SARS-COV-2 transmission showed a substantial correlation with NH3 (r = 0.41), NO2 (r = 0.36), and NO (r = 0.35) with a p-value <0.001, which is highly indicative of their role in SARS-CoV-2 transmission. These outcomes are associated with the source of PM and its constituent trace elements to understand their overtone with COVID-19. This strongly validates temporal and spatial variation in COVID-19 dependence on air pollutants as well as on environmental factors. Besides, the bottlenecks of missing latent data, monotonous dependence of variables, and the role air pollutants with secondary environmental variables are discussed. The analysis set the foundation for strategizing regional-based modalities considering environmental variables (i.e., pollutant concentration, relative humidity, temperature) as well as urban and transportation planning for efficient control and handling of future public health emergencies.

Reply to Kapur, V. Is Pre-Exposure Prophylaxis a Cost-Effective Intervention to Avert Rabies Deaths among School-Aged Children in India? Comment on "Royal et al. A Cost-Effectiveness Analysis of Pre-Exposure Prophylaxis to Avert Rabies Deaths in School-Aged Children in India. Vaccines 2023, 11, 88".

Thank you so much for forwarding the critical analysis the author (VK) conducted on our recently published modelling study 'A Cost-Effectiveness Analysis of Pre-Exposure Prophylaxis to Avert Rabies Deaths in School-Aged Children in India' in your reputed journal [...].

Assessing temporal correlation in environmental risk factors to design efficient area-specific COVID-19 regulations: Delhi based case study.

Amid ongoing devastation due to Serve-Acute-Respiratory-Coronavirus2 (SARS-CoV-2), the global spatial and temporal variation in the pandemic spread has strongly anticipated the requirement of designing area-specific preventive strategies based on geographic and meteorological state-of-affairs. Epidemiological and regression models have strongly projected particulate matter (PM) as leading environmental-risk factor for the COVID-19 outbreak. Understanding the role of secondary environmental-factors like ammonia (NH3) and relative humidity (RH), latency of missing data structuring, monotonous correlation remains obstacles to scheme conclusive outcomes. We mapped hotspots of airborne PM2.5, PM10, NH3, and RH concentrations, and COVID-19 cases and mortalities for January, 2021-July,2021 from combined data of 17 ground-monitoring stations across Delhi. Spearmen and Pearson coefficient correlation show strong association (p-value < 0.001) of COVID-19 cases and mortalities with PM2.5 (r > 0.60) and PM10 (r > 0.40), respectively. Interestingly, the COVID-19 spread shows significant dependence on RH (r > 0.5) and NH3 (r = 0.4), anticipating their potential role in SARS-CoV-2 outbreak. We found systematic lockdown as a successful measure in combatting SARS-CoV-2 outbreak. These outcomes strongly demonstrate regional and temporal differences in COVID-19 severity with environmental-risk factors. The study lays the groundwork for designing and implementing regulatory strategies, and proper urban and transportation planning based on area-specific environmental conditions to control future infectious public health emergencies.

A Cost-Effectiveness Analysis of Pre-Exposure Prophylaxis to Avert Rabies Deaths in School-Aged Children in India.

Children contribute to one-half of the total painful rabies mortalities in India. The state-of-the-art rabies mortality averting strategies need exploration for the effective implementation of pre-exposure prophylaxis (PrEP) in India. This study reports on the economic evaluation of various PrEP and post-exposure prophylaxis (PEP) strategies to avert rabies mortalities in school-aged children in India. A decision tree model has been developed for children in the age group of 5-15 years to evaluate various PrEP + PEP and PEP only regimens. The 2-site intradermal regimen administered on day zero and seven was chosen as the intervention [PrEP (I)]. ICER was calculated from the quasi-societal and quasi-health systems' perspectives for the base case analysis, along with one-way sensitivity, and scenario analyses for each regimen. The incremental DALYs averted per million population with the implementation of PrEP (I) ranged between 451 and 85,069 in 2020. The ICER was reported in the range of USD 384-352/DALY averted (non-dominant) in comparison to PEP regimens from a quasi-societal perspective. PrEP (I) is reported to be 'very cost effective' in comparison with PEP regimens from the quasi-societal and quasi-health systems' perspectives and reduce deaths by up to 89.9%. This study concludes that the PrEP (I) regimen is a cost-effective and life-saving strategy to avert painful mortalities due to rabies in school-aged children in India.

Targeting functional motifs of a protein family.

The structural organization of a protein family is investigated by devising a method based on the random matrix theory (RMT), which uses the physiochemical properties of the amino acid with multiple sequence alignment. A graphical method to represent protein sequences using physiochemical properties is devised that gives a fast, easy, and informative way of comparing the evolutionary distances between protein sequences. A correlation matrix associated with each property is calculated, where the noise reduction and information filtering is done using RMT involving an ensemble of Wishart matrices. The analysis of the eigenvalue statistics of the correlation matrix for the ß-lactamase family shows the universal features as observed in the Gaussian orthogonal ensemble (GOE). The property-based approach captures the short- as well as the long-range correlation (approximately following GOE) between the eigenvalues, whereas the previous approach (treating amino acids as characters) gives the usual short-range correlations, while the long-range correlations are the same as that of an uncorrelated series. The distribution of the eigenvector components for the eigenvalues outside the bulk (RMT bound) deviates significantly from RMT observations and contains important information about the system. The information content of each eigenvector of the correlation matrix is quantified by introducing an entropic estimate, which shows that for the ß-lactamase family the smallest eigenvectors (low eigenmodes) are highly localized as well as informative. These small eigenvectors when processed gives clusters involving positions that have well-defined biological and structural importance matching with experiments. The approach is crucial for the recognition of structural motifs as shown in ß-lactamase (and other families) and selectively identifies the important positions for targets to deactivate (activate) the enzymatic actions.

Genus distribution and thermodynamics of a random matrix model of RNA with Penner interaction.

The nonlinear Penner external interaction is introduced and studied in the random matrix model of homo RNA. A numerical technique is developed to study the partition function, and a general formula is obtained for all lengths. The genus distribution function for the system is obtained, plotted, and compared with the genus distribution for the real RNA structures found from the protein databank. The genus distribution shows that the nonlinear interaction favors the formation of low genus structures and matches the result for real RNA structures. The distribution of structure with temperature suggests that nonlinear interaction is biased toward the planar structures. The variation of chemical potential with temperature and interaction strength indicates the presence of additional molecules in the system other than the magnesium ions and possibly represents a phase transition. The specific heat has a bump and its derivatives shows a double-peak behavior at a particular temperature. On analyzing the specific heat and derivatives for each genus separately, the planar structure (genus zero) is shown to contribute the most to the bump and double peak. This observation in the nonlinear model is similar to that observed in the unfolding experiments on RNA.