Fostering human learning in sequential decision-making: Understanding the role of evaluative feedback.

Cognitive rehabilitation, STEM (science, technology, engineering, and math) skill acquisition, and coaching games such as chess often require tutoring decision-making strategies. The advancement of AI-driven tutoring systems for facilitating human learning requires an understanding of the impact of evaluative feedback on human decision-making and skill development. To this end, we conduct human experiments using Amazon Mechanical Turk to study the influence of evaluative feedback on human decision-making in sequential tasks. In these experiments, participants solve the Tower of Hanoi puzzle and receive AI-generated feedback while solving it. We examine how this feedback affects their learning and skill transfer to related tasks. Additionally, treating humans as noisy optimal agents, we employ maximum entropy inverse reinforcement learning to analyze the effect of feedback on the implicit human reward structure that guides their decision making. Lastly, we explore various computational models to understand how people incorporate evaluative feedback into their decision-making processes. Our findings underscore that humans perceive evaluative feedback as indicative of their long-term strategic success, thus aiding in skill acquisition and transfer in sequential decision-making tasks. Moreover, we demonstrate that evaluative feedback fosters a more structured and organized learning experience compared to learning without feedback. Furthermore, our results indicate that providing intermediate goals alone does not significantly enhance human learning outcomes.

Advances in Vibrio-related infection management: an integrated technology approach for aquaculture and human health.

Vibrio species pose significant threats worldwide, causing mortalities in aquaculture and infections in humans. Global warming and the emergence of worldwide strains of Vibrio diseases are increasing day by day. Control of Vibrio species requires effective monitoring, diagnosis, and treatment strategies at the global scale. Despite current efforts based on chemical, biological, and mechanical means, Vibrio control management faces limitations due to complicated implementation processes. This review explores the intricacies and challenges of Vibrio-related diseases, including accurate and cost-effective diagnosis and effective control. The global burden due to emerging Vibrio species further complicates management strategies. We propose an innovative integrated technology model that harnesses cutting-edge technologies to address these obstacles. The proposed model incorporates advanced tools, such as biosensing technologies, the Internet of Things (IoT), remote sensing devices, cloud computing, and machine learning. This model offers invaluable insights and supports better decision-making by integrating real-time ecological data and biological phenotype signatures. A major advantage of our approach lies in leveraging cloud-based analytics programs, efficiently extracting meaningful information from vast and complex datasets. Collaborating with data and clinical professionals ensures logical and customized solutions tailored to each unique situation. Aquaculture biotechnology that prioritizes sustainability may have a large impact on human health and the seafood industry. Our review underscores the importance of adopting this model, revolutionizing the prognosis and management of Vibrio-related infections, even under complex circumstances. Furthermore, this model has promising implications for aquaculture and public health, addressing the United Nations Sustainable Development Goals and their development agenda.

Substrate Specificities of Variants of Barley (1,3)- and (1,3;1,4)-ß-d-Glucanases Resulting from Mutagenesis and Segment Hybridization.

Barley (1,3;1,4)-ß-d-glucanase is believed to have evolved from an ancestral monocotyledon (1,3)-ß-d-glucanase, enabling the hydrolysis of (1,3;1,4)-ß-d-glucans in the cell walls of leaves and germinating grains. In the present study, we investigated the substrate specificities of variants of the barley enzymes (1,3;1,4)-ß-d-glucan endohydrolase [(1,3;1,4)-ß-d-glucanase] isoenzyme EII (HvEII) and (1,3)-ß-d-glucan endohydrolase [(1,3)-ß-d-glucanase] isoenzyme GII (HvGII) obtained by protein segment hybridization and site-directed mutagenesis. Using protein segment hybridization, we obtained three variants of HvEII in which the substrate specificity was that of a (1,3)-ß-d-glucanase and one variant that hydrolyzed both (1,3)-ß-d-glucans and (1,3;1,4)-ß-d-glucans; the wild-type enzyme hydrolyzed only (1,3;1,4)-ß-d-glucans. Using substitutions of specific amino acid residues, we obtained one variant of HvEII that hydrolyzed both substrates. However, neither protein segment hybridization nor substitutions of specific amino acid residues gave variants of HvGII that could hydrolyze (1,3;1,4)-ß-d-glucans; the wild-type enzyme hydrolyzed only (1,3)-ß-d-glucans. Other HvEII and HvGII variants showed changes in specific activity and their ability to degrade the (1,3;1,4)-ß-d-glucans or (1,3)-ß-d-glucans to larger oligosaccharides. We also used molecular dynamics simulations to identify amino-acid residues or structural regions of wild-type HvEII and HvGII that interact with (1,3;1,4)-ß-d-glucans and (1,3)-ß-d-glucans, respectively, and may be responsible for the substrate specificities of the two enzymes.

Unlocking The Mysteries of DNA Adducts with Artificial Intelligence.

Cellular genome is considered a dynamic blueprint of a cell since it encodes genetic information that gets temporally altered due to various endogenous and exogenous insults. Largely, the extent of genomic dynamicity is controlled by the trade-off between DNA repair processes and the genotoxic potential of the causative agent (genotoxins or potential carcinogens). A subset of genotoxins form DNA adducts by covalently binding to the cellular DNA, triggering structural or functional changes that lead to significant alterations in cellular processes via genetic (e. g., mutations) or non-genetic (e. g., epigenome) routes. Identification, quantification, and characterization of DNA adducts are indispensable for their comprehensive understanding and could expedite the ongoing efforts in predicting carcinogenicity and their mode of action. In this review, we elaborate on using Artificial Intelligence (AI)-based modeling in adducts biology and present multiple computational strategies to gain advancements in decoding DNA adducts. The proposed AI-based strategies encompass predictive modeling for adduct formation via metabolic activation, novel adducts' identification, prediction of biochemical routes for adduct formation, adducts' half-life predictions within biological ecosystems, and, establishing methods to predict the link between adducts chemistry and its location within the genomic DNA. In summary, we discuss some futuristic AI-based approaches in DNA adduct biology.

Plants and endophytes interaction: a "secret wedlock" for sustainable biosynthesis of pharmaceutically important secondary metabolites.

Many plants possess immense pharmacological properties because of the presence of various therapeutic bioactive secondary metabolites that are of great importance in many pharmaceutical industries. Therefore, to strike a balance between meeting industry demands and conserving natural habitats, medicinal plants are being cultivated on a large scale. However, to enhance the yield and simultaneously manage the various pest infestations, agrochemicals are being routinely used that have a detrimental impact on the whole ecosystem, ranging from biodiversity loss to water pollution, soil degradation, nutrient imbalance and enormous health hazards to both consumers and agricultural workers. To address the challenges, biological eco-friendly alternatives are being looked upon with high hopes where endophytes pitch in as key players due to their tight association with the host plants. The intricate interplay between plants and endophytic microorganisms has emerged as a captivating subject of scientific investigation, with profound implications for the sustainable biosynthesis of pharmaceutically important secondary metabolites. This review delves into the hidden world of the "secret wedlock" between plants and endophytes, elucidating their multifaceted interactions that underpin the synthesis of bioactive compounds with medicinal significance in their plant hosts. Here, we briefly review endophytic diversity association with medicinal plants and highlight the potential role of core endomicrobiome. We also propose that successful implementation of in situ microbiome manipulation through high-end techniques can pave the way towards a more sustainable and pharmaceutically enriched future.

Antifungal activity of sustainable histone deacetylase inhibitors against planktonic cells and biofilms of Candida spp. and Cryptococcusneoformans.

The limited therapeutic options for fungal infections and the increased incidence of fungal strains resistant to antifungal drugs, especially Candida spp., require the development of new antifungal drugs and strategies. Histone deacetylase inhibitors (HDACi), like vorinostat, have been studied in cancer treatment and have antifungal effects, acting alone or synergistically with classical antifungals. Here we investigated the antifungal activity of two novel sustainable HDACi (LDT compounds) based on vorinostat structure. Molecular docking simulation studies reveal that LDT compounds can bind to Class-I HDACs of Candida albicans, C. tropicalis, and Cryptococcus neoformans, which showed similar binding mode to vorinostat. LDT compounds showed moderate activity when tested alone against fungi but act synergistically with antifungal azoles against Candida spp. They reduced biofilm formation by more than 50% in C. albicans (4 µg/mL), with the main action in fungal filamentation. Cytotoxicity of the LDT compounds against RAW264.7 cells was evaluated and LDT536 demonstrated cytotoxicity only at the concentration of 200 µmol/L, while LDT537 showed IC50 values of 29.12 µmol/L. Our data indicated that these sustainable and inexpensive HDACi have potential antifungal and antibiofilm activities, with better results than vorinostat, although further studies are necessary to better understand the mechanism against fungal cells.

Fungal infections are neglected diseases that affect more than a billion people worldwide. Some histone deacetylase inhibitors can act against fungal cells. Our data reveal that HDACi LDT536 and LDT537 have potential antibiofilm and antifungal activities.

Response of wastewater-based epidemiology predictor for the second wave of COVID-19 in Ahmedabad, India: A long-term data Perspective.

In this work, we present an eight-month longitudinal study of wastewater-based epidemiology (WBE) in Ahmedabad, India, where wastewater surveillance was introduced in September 2020 after the successful containment of the first wave of COVID-19 to predict the resurge of the infection during the second wave of the pandemic. The study aims to elucidate the weekly resolution of the SARS-CoV-2 RNA data for eight months in wastewater samples to predict the COVID-19 situation and identify hotspots in Ahmedabad. A total of 287 samples were analyzed for SARS-CoV-2 RNA using RT-PCR, and Spearman's rank correlation was applied to depict the early warning potential of WBE. During September 2020 to April 2021, the increasing number of positive wastewater influent samples correlated with the growing number of confirmed clinical cases. It also showed clear evidence of early detection of the second wave of COVID-19 in Ahmedabad (March 2021). 258 out of a total 287 samples were detected positive with at least two out of three SARS-CoV-2 genes (N, ORF- 1 ab, and S). Monthly variation represented a significant decline in all three gene copies in October compared to September 2020, followed by an abrupt increase in November 2020. A similar increment in the gene copies was observed in March and April 2021, which would be an indicator of the second wave of COVID-19. A lead time of 1-2 weeks was observed in the change of gene concentrations compared with clinically confirmed cases. Measured wastewater ORF- 1 ab gene copies ranged from 6.1 x 102 (October 2020) to 1.4 x 104 (November 2020) copies/mL, and wastewater gene levels typically lead to confirmed cases by one to two weeks. The study highlights the value of WBE as a monitoring tool to predict waves within a pandemic, identify local disease hotspots within a city, and guide rapid management interventions.

Sequence, structure and functionality of pectin methylesterases and their use in sustainable carbohydrate bioproducts: A review.

Pectin methylesterases (PMEs) are enzymes that play a critical role in modifying pectins, a class of complex polysaccharides in plant cell walls. These enzymes catalyze the removal of methyl ester groups from pectins, resulting in a change in the degree of esterification and consequently, the physicochemical properties of the polymers. PMEs are found in various plant tissues and organs, and their activity is tightly regulated in response to developmental and environmental factors. In addition to the biochemical modification of pectins, PMEs have been implicated in various biological processes, including fruit ripening, defense against pathogens, and cell wall remodelling. This review presents updated information on PMEs, including their sources, sequences and structural diversity, biochemical properties and function in plant development. The article also explores the mechanism of PME action and the factors influencing enzyme activity. In addition, the review highlights the potential applications of PMEs in various industrial sectors related to biomass exploitation, food, and textile industries, with a focus on development of bioproducts based on eco-friendly and efficient industrial processes.

Cell Wall Carbohydrate Dynamics during the Differentiation of Infection Structures by the Apple Scab Fungus, Venturia inaequalis.

Scab, caused by the biotrophic fungal pathogen Venturia inaequalis, is the most economically important disease of apples. During infection, V. inaequalis colonizes the subcuticular host environment, where it develops specialized infection structures called runner hyphae and stromata. These structures are thought to be involved in nutrient acquisition and effector (virulence factor) delivery, but also give rise to conidia that further the infection cycle. Despite their importance, very little is known about how these structures are differentiated. Likewise, nothing is known about how these structures are protected from host defenses or recognition by the host immune system. To better understand these processes, we first performed a glycosidic linkage analysis of sporulating tubular hyphae from V. inaequalis developed in culture. This analysis revealed that the V. inaequalis cell wall is mostly composed of glucans (44%) and mannans (37%), whereas chitin represents a much smaller proportion (4%). Next, we used transcriptomics and confocal laser scanning microscopy to provide insights into the cell wall carbohydrate composition of runner hyphae and stromata. These analyses revealed that, during subcuticular host colonization, genes of V. inaequalis putatively associated with the biosynthesis of immunogenic carbohydrates, such as chitin and ß-1,6-glucan, are downregulated relative to growth in culture, while on the surface of runner hyphae and stromata, chitin is deacetylated to the less-immunogenic carbohydrate chitosan. These changes are anticipated to enable the subcuticular differentiation of runner hyphae and stromata by V. inaequalis, as well as to protect these structures from host defenses and recognition by the host immune system. IMPORTANCE Plant-pathogenic fungi are a major threat to food security. Among these are subcuticular pathogens, which often cause latent asymptomatic infections, making them difficult to control. A key feature of these pathogens is their ability to differentiate specialized subcuticular infection structures that, to date, remain largely understudied. This is typified by Venturia inaequalis, which causes scab, the most economically important disease of apples. In this study, we show that, during subcuticular host colonization, V. inaequalis downregulates genes associated with the biosynthesis of two immunogenic cell wall carbohydrates, chitin and ß-1,6-glucan, and coats its subcuticular infection structures with a less-immunogenic carbohydrate, chitosan. These changes are anticipated to enable host colonization by V. inaequalis and provide a foundation for understanding subcuticular host colonization by other plant-pathogenic fungi. Such an understanding is important, as it may inform the development of novel control strategies against subcuticular plant-pathogenic fungi.

Family 92 carbohydrate-binding modules specific for ß-1,6-glucans increase the thermostability of a bacterial chitinase.

In biomass-processing industries there is a need for enzymes that can withstand high temperatures. Extensive research efforts have been dedicated to finding new thermostable enzymes as well as developing new means of stabilising existing enzymes. The attachment of a stable non-catalytic domain to an enzyme can, in some instances, protect a biocatalyst from thermal denaturation. Carbohydrate-binding modules (CBMs) are non-catalytic domains typically found appended to biomass-degrading or modifying enzymes, such as glycoside hydrolases (GHs). Most often, CBMs interact with the same polysaccharide as their enzyme partners, leading to an enhanced reaction rate via the promotion of enzyme-substrate interactions. Contradictory to this general concept, we show an example of a chitin-degrading enzyme from GH family 18 that is appended to two CBM domains from family 92, both of which bind preferentially to the non-substrate polysaccharide ß-1,6-glucan. During chitin hydrolysis, the CBMs do not contribute to enzyme-substrate interactions but instead confer a 10-15 °C increase in enzyme thermal stability. We propose that CBM92 domains may have a natural enzyme stabilisation role in some cases, which may be relevant to enzyme design for high-temperature applications in biorefinery.

Asynchrony rescues statistically optimal group decisions from information cascades through emergent leaders.

It is usually assumed that information cascades are most likely to occur when an early but incorrect opinion spreads through the group. Here, we analyse models of confidence-sharing in groups and reveal the opposite result: simple but plausible models of naive-Bayesian decision-making exhibit information cascades when group decisions are synchronous; however, when group decisions are asynchronous, the early decisions reached by Bayesian decision-makers tend to be correct and dominate the group consensus dynamics. Thus early decisions actually rescue the group from making errors, rather than contribute to it. We explore the likely realism of our assumed decision-making rule with reference to the evolution of mechanisms for aggregating social information, and known psychological and neuroscientific mechanisms.

Cd-induced cytosolic proteome changes in the cyanobacterium Anabaena sp. PCC7120 are mediated by LexA as one of the regulatory proteins.

LexA, a well-characterized transcriptional repressor of SOS genes in heterotrophic bacteria, has been shown to regulate diverse genes in cyanobacteria. An earlier study showed that LexA overexpression in a cyanobacterium, Anabaena sp. PCC7120 reduces its tolerance to Cd stress. This was later shown to be due to modulation of photosynthetic redox poising by LexA under Cd stress. However, due to the global regulatory nature of LexA and the prior prediction of AnLexA-box in a few heavy metal-responsive genes, we speculated that LexA has a broad role in Cd tolerance, with regulation over a variety of Cd stress-responsive genes in addition to photosynthetic genes. Thus, to further expand the knowledge on the regulatory role of LexA in Cd stress tolerance, a cytosolic proteome profiling of Anabaena constitutively overexpressing LexA upon Cd stress was performed. The proteomic study revealed 25 differentially accumulated proteins (DAPs) in response to the combined effect of LexA overexpression and Cd stress, and the other 11 DAPs exclusively in response to either LexA overexpression or Cd stress. The 36 identified proteins were related with a variety of functions, including photosynthesis, C-metabolism, antioxidants, protein turnover, post-transcriptional modifications, and a few unknown and hypothetical proteins. The regulation of LexA on corresponding genes, and six previously reported Cd efflux transporters, was further validated by the presence of AnLexA-boxes, transcript, and/or promoter analyses. In a nutshell, this study identifies the regulation of Anabaena LexA on several Cd stress-responsive genes of various functions, hence expanding the regulatory role of LexA under Cd stress.

Gamma (γ)-radiation stress response of the cyanobacterium Anabaena sp. PCC7120: Regulatory role of LexA and photophysiological changes.

High radioresistance of the cyanobacterium, Anabaena sp. PCC7120 has been attributed to efficient DNA repair, protein recycling, and oxidative stress management. However, the regulatory network involved in these batteries of responses remains unexplored. In the present study, the role of a global regulator, LexA in modulating gamma (γ)-radiation stress response of Anabaena was investigated. Comparison of the cytosolic proteome profiles upon γ-radiation in recombinant Anabaena strains, AnpAM (vector-control) and AnlexA+ (LexA-overexpressing), revealed 41 differentially accumulated proteins, corresponding to 29 distinct proteins. LexA was found to be involved in the regulation of 27 of the corresponding genes based on the presence of AnLexA-Box, EMSA, and/or qRT-PCR studies. The majority of the regulated genes were found to be involved in C-assimilation either through photosynthesis or C-catabolism and oxidative stress alleviation. Photosynthesis, measured in terms of PSII photophysiological parameters and thylakoid membrane proteome was found to be affected by γ-radiation in both AnpAM and AnlexA+ cells, with LexA affecting them even under control growth conditions. Thus, LexA functioned as one of the transcriptional regulators involved in modulating γ-radiation stress response in Anabaena. This study could pave the way for a deeper understanding of the regulation of γ-radiation-responsive genes in cyanobacteria at large.

Biochemical characterization and molecular insights into substrate recognition of pectin methylesterase from Phytophthora infestans.

Pectin methylesterases (PMEs) are a class of carbohydrate-active enzymes that act on the O6-methyl ester groups of the homogalacturonan component of pectins, resulting in de-esterification of the substrate polymers and formation of pectate and methanol. PMEs occur in higher plants and microorganisms, including fungi, oomycetes, bacteria, and archaea. Microbial PMEs play a crucial role in pathogens' invasion of plant tissues. Here, we have determined the structural and functional properties of Pi-PME, a PME from the oomycete plant pathogen Phytophthora infestans. This enzyme exhibits maximum activity at alkaline pH (8.5) and is active over a wide temperature range (25-50 °C). In silico determination of the structure of Pi-PME reveals that the protein consists essentially of three parallel ß-sheets interconnected by loops that adopt an overall ß-helix organization. The loop regions in the vicinity of the active site are extended compared to plant and fungal PMEs, but they are shorter than the corresponding bacterial and insect regions. Molecular dynamic simulations revealed that Pi-PME interacts most strongly with partially de-methylated homogalacturonans, suggesting that it preferentially uses this type of substrates. The results are compared and discussed with other known PMEs from different organisms, highlighting the specific features of Pi-PME.

Archaeal lipolytic enzymes: Current developments and further prospects.

Lipolytic enzymes include triacylglycerol lipases (EC 3.1.1.3) and esterases (EC 3.1.1.1) that catalyze the cleavage and formation of ester bonds. They are potential industrial biocatalysts because of their broad range of activities on natural and synthetic substrates, high stability in organic solvents, thermal stability, stability in highly acidic and alkaline pH conditions and enantio-, regio- and chemo-selectivity. They also have varied applications in different sectors, among which industrial biotechnology, the production of cleaning agents, and pharmaceuticals are the most important ones. Identifying extremophilic lipolytic enzymes is of paramount interest and is a growing field in academic and industrial research. This review is focused on the current knowledge and future avenues of investigation on lipolytic enzymes sourced from the underexploited archaeal domain. Archaea is a potential source for novel extremophilic enzymes, which have high demand in the industries. The archaeal lipases and esterases are clustered into different families based on their similarity/dissimilarity at the genetic level and protein structures. The updated information on characterized and putative lipase sequences has also been presented in this paper. Common structural scaffolds of archaeal lipases have been deduced and discussed in this review. However, huge diversity at the level of their genetic sequences has yet to be correlated with the structure-function relationship. Based on their biochemical properties, possible applications and future prospective of archaeal lipolytic enzymes have also been proposed.

Correction: Computational investigation of the increased virulence and pathogenesis of SARS-CoV-2 lineage B.1.1.7.

Correction for 'Computational investigation of the increased virulence and pathogenesis of SARS-CoV-2 lineage B.1.1.7' by N. Arul Murugan et al., Phys. Chem. Chem. Phys., 2022, 24, 20371-20380, https://doi.org/10.1039/D2CP00469K.

Computational investigation of the increased virulence and pathogenesis of SARS-CoV-2 lineage B.1.1.7.

New variants of SARS-CoV-2 are being reported worldwide. The World Health Organization has reported Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2) and Omicron (B.1.1.529) as the variants of concern. There are speculations that the variants might evade the host immune responses induced by currently available vaccines and develop resistance to drugs under consideration. The first step of viral infection in COVID-19 occurs through the interaction of the spike protein's receptor-binding domain (RBD) with the peptidase domain of the human ACE-2 (hACE-2) receptor. This study aims to get a molecular-level understanding of the mechanism behind the increased infection rate in the alpha variant. We have computationally studied the spike protein interaction in both the wild-type and B.1.1.7 variant with the hACE-2 receptor using molecular dynamics and MM-GBSA based binding free energy calculations. The binding free energy difference shows that the mutant variant of the spike protein has increased binding affinity for the hACE-2 receptor (i.e. ΔG(N501Y,A570D) is in the range -7.2 to -7.6 kcal mol-1) and the results were validated using Density functional theory. We demonstrate that with the use of state-of-the-art computational approaches, we can, in advance, predict the virulent nature of variants of SARS-CoV-2 and alert the world healthcare system.