Visual and cognitive processes contribute to age-related improvements in visual selective attention.

Children (N = 103, 4-9 years, 59 females, 84% White, c. 2019) completed visual processing, visual feature integration (color, luminance, motion), and visual search tasks. Contrast sensitivity and feature search improved with age similarly for luminance and color-defined targets. Incidental feature integration improved more with age for color-motion than luminance-motion. Individual differences in feature search ( ß = .11) and incidental feature integration ( ß = .06) mediated age-related changes in conjunction visual search, an index of visual selective attention. These findings suggest that visual selective attention is best conceptualized as a series of developmental trajectories, within an individual, that vary by an object's defining features. These data have implications for design of educational and interventional strategies intended to maximize attention for learning and memory.

RNA-binding domain of SARS-CoV2 nucleocapsid: MD simulation study of the effect of the proline substitutions P67S and P80R on the structure of the protein.

The nucleocapsid component of SARS-CoV2 is involved in the viral genome packaging. GammaP.1(Brazil) and the 20 C-US(USA) variants had a high frequency of the P80R and P67S mutations respectively in the RNA-binding domain of the nucleocapsid. Since RNA-binding domain participates in the electrostatic interactions with the viral genome, the study of the effects of proline substitutions on the flexibility of the protein will be meaningful. It evinced that the trajectory of the wildtype and mutants was stable during the simulation and exhibited distinct changes in the flexibility of the protein. Moreover, the beta-hairpin loop region of the protein structures exhibited high amplitude fluctuations and dominant motions. Additionally, modulations were detected in the drug binding site. Besides, the extent of correlation and anti-correlation motions involving the protruding region, helix, and the other RNA binding sites differed between the wildtype and mutants. The secondary structure analysis disclosed the variation in the occurrence pattern of the secondary structure elements between the proteins. Protein-ssRNA interaction analysis was also done to detect the amino acid contacts with ssRNA. R44, R59, and Y61 residues of the wildtype and P80R mutant exhibited different duration contacts with the ssRNA. It was also noticed that R44, R59, and Y61 of the wildtype and P80R formed hydrogen bonds with the ssRNA. However in P67S, residues T43, R44, R45, R40, R59, and R41 displayed contacts and formed hydrogen bonds with ssRNA. Binding free energy was also calculated and was lowest for P67S than wildtype andP80R. Thus, proline substitutions influence the structure of the RNA-binding domain and may modulate viral genome packaging besides the host-immune response.Communicated by Ramaswamy H. Sarma.

Predicting phenotypes of beef eating quality traits.

Introduction: Phenotype predictions of beef eating quality for individual animals could be used to allocate animals to longer and more expensive feeding regimes as they enter the feedlot if they are predicted to have higher eating quality, and to sort carcasses into consumer or market value categories. Phenotype predictions can include genetic effects (breed effects, heterosis and breeding value), predicted from genetic markers, as well as fixed effects such as days aged and carcass weight, hump height, ossification, and hormone growth promotant (HGP) status. Methods: Here we assessed accuracy of phenotype predictions for five eating quality traits (tenderness, juiciness, flavour, overall liking and MQ4) in striploins from 1701 animals from a wide variety of backgrounds, including Bos indicus and Bos taurus breeds, using genotypes and simple fixed effects including days aged and carcass weight. The genetic components were predicted based on 709k single nucleotide polymorphism (SNP) using BayesR model, which assumes some markers may have a moderate to large effect. Fixed effects in the prediction included principal components of the genomic relationship matrix, to account for breed effects, heterosis, days aged and carcass weight. Results and Discussion: A model which allowed breed effects to be captured in the SNP effects (e.g., not explicitly fitting these effects) tended to have slightly higher accuracies (0.43-0.50) compared to when these effects were explicitly fitted as fixed effects (0.42-0.49), perhaps because breed effects when explicitly fitted were estimated with more error than when incorporated into the (random) SNP effects. Adding estimates of effects of days aged and carcass weight did not increase the accuracy of phenotype predictions in this particular analysis. The accuracy of phenotype prediction for beef eating quality traits was sufficiently high that such predictions could be useful in predicting eating quality from DNA samples taken from an animal/carcass as it enters the processing plant, to enable optimal supply chain value extraction by sorting product into markets with different quality. The BayesR predictions identified several novel genes potentially associated with beef eating quality.

Attention along the cortical hierarchy: Development matters.

We build on the existing biased competition view to argue that attention is an emergent property of neural computations within and across hierarchically embedded and structurally connected cortical pathways. Critically then, one must ask, what is attention emergent from? Within this framework, developmental changes in the quality of sensory input and feedforward-feedback information flow shape the emergence and efficiency of attention. Several gradients of developing structural and functional cortical architecture across the caudal-to-rostral axis provide the substrate for attention to emerge. Neural activity within visual areas depends on neuronal density, receptive field size, tuning properties of neurons, and the location of and competition between features and objects in the visual field. These visual cortical properties highlight the information processing bottleneck attention needs to resolve. Recurrent feedforward and feedback connections convey sensory information through a series of steps at each level of the cortical hierarchy, integrating sensory information across the entire extent of the cortical hierarchy and linking sensory processing to higher-order brain regions. Higher-order regions concurrently provide input conveying behavioral context and goals. Thus, attention reflects the output of a series of complex biased competition neural computations that occur within and across hierarchically embedded cortical regions. Cortical development proceeds along the caudal-to-rostral axis, mirroring the flow in sensory information from caudal to rostral regions, and visual processing continues to develop into childhood. Examining both typical and atypical development will offer critical mechanistic insight not otherwise available in the adult stable state. This article is categorized under: Psychology > Attention.

The long arm of adversity: Children's kindergarten math skills are associated with maternal childhood adversity.

BACKGROUND: Childhood adversity is associated with poorer health and lower academic achievement later in life. Poor math skills in particular place individuals at higher risk for physical and mental illness, unemployment, and incarceration, suggesting math achievement may be one explanatory mechanism linking adversity to later functioning. While it is well documented that children's adversity is associated with lower academic achievement, it is also plausible that adversity mothers experience across their lifetime may affect the child's academic achievement. OBJECTIVE: Determine whether adversity children directly experience and adversity mothers experience in their own childhood and/or adulthood is related to children's kindergarten math skills. PARTICIPANTS AND METHODS: 91 Mothers completed the Assessment of Parent and Child Adversity questionnaire, and their kindergartners completed the KeyMath-3 Diagnostic Assessment. RESULTS: Maternal childhood adversity, but not adulthood adversity, was negatively related to children's numeration (ß = -0.27, 95% CI [-0.48, -0.05], p = .015) and addition/subtraction abilities in kindergarten (ß = -0.25, 95% CI [-0.46, -0.04], p = .023). Maternal childhood maltreatment and other adversity were together related to their child's numeration only (R2 = 0.08, 95% CI [0.02, 0.23], p = .026). Prevalence of children's direct adversity was low and not related to their kindergarten math skills. CONCLUSIONS: Our findings suggest that adversity impacts children's math skills as early as kindergarten via the intergenerational transmission of maternal adversity. Mothers that experienced early-life adversity and their children may benefit from early intervention to level the playing field at school entry.

Mannose 2, 3, 4, 5, 6-O-pentasulfate (MPS): a partial activator of human heparin cofactor II with anticoagulation potential.

Thromboembolic diseases are a major cause of mortality in human and the currently available anticoagulants are associated with various drawbacks, therefore the search for anticoagulants that have better safety profile is highly desirable. Compounds that are part of the dietary routine can be modified to possibly increase their anticoagulant potential. We show mannose 2,3,4,5,6-O-pentasulfate (MPS) as a synthetically modified form of mannose that has appreciable anticoagulation properties. An in silico study identified that mannose in sulfated form can bind effectively to the heparin-binding site of antithrombin (ATIII) and heparin cofactor II (HCII). Mannose was sulfated using a simple sulfation strategy-involving triethylamine-sulfur trioxide adduct. HCII and ATIII were purified from human plasma and the binding analysis using fluorometer and isothermal calorimetry showed that MPS binds at a unique site. A thrombin inhibition analysis using the chromogenic substrate showed that MPS partially enhances the activity of HCII. Further an assessment of in vitro blood coagulation assays using human plasma showed that the activated partial thromboplastin time (APTT) and prothrombin time (PT) were prolonged in the presence of MPS. A molecular dynamics simulation analysis of the HCII-MPS complex showed fluctuations in a N-terminal loop and the cofactor binding site of HCII. The results indicate that MPS is a promising lead due to its effect on the in vitro coagulation rate.Communicated by Ramaswamy H. Sarma.

Serological fingerprints link antiviral activity of therapeutic antibodies to affinity and concentration.

The effectiveness of therapeutic monoclonal antibodies (mAbs) against variants of the SARS-CoV-2 virus is highly variable. As target recognition of mAbs relies on tight binding affinity, we assessed the affinities of five therapeutic mAbs to the receptor binding domain (RBD) of wild type (A), Delta (B.1.617.2), and Omicron BA.1 SARS-CoV-2 (B.1.1.529.1) spike using microfluidic diffusional sizing (MDS). Four therapeutic mAbs showed strongly reduced affinity to Omicron BA.1 RBD, whereas one (sotrovimab) was less impacted. These affinity reductions correlate with reduced antiviral activities suggesting that affinity could serve as a rapid indicator for activity before time-consuming virus neutralization assays are performed. We also compared the same mAbs to serological fingerprints (affinity and concentration) obtained by MDS of antibodies in sera of 65 convalescent individuals. The affinities of the therapeutic mAbs to wild type and Delta RBD were similar to the serum antibody response, indicating high antiviral activities. For Omicron BA.1 RBD, only sotrovimab retained affinities within the range of the serum antibody response, in agreement with high antiviral activity. These results suggest that serological fingerprints provide a route to evaluating affinity and antiviral activity of mAb drugs and could guide the development of new therapeutics.

Intersection of network medicine and machine learning towards investigating the key biomarkers and pathways underlying amyotrophic lateral sclerosis: a systematic review.

BACKGROUND: Network medicine is an emerging area of research that focuses on delving into the molecular complexity of the disease, leading to the discovery of network biomarkers and therapeutic target discovery. Amyotrophic lateral sclerosis (ALS) is a complicated rare disease with unknown pathogenesis and no available treatment. In ALS, network properties appear to be potential biomarkers that can be beneficial in disease-related applications when explored independently or in tandem with machine learning (ML) techniques. OBJECTIVE: This systematic literature review explores recent trends in network medicine and implementations of network-based ML algorithms in ALS. We aim to provide an overview of the identified primary studies and gather details on identifying the potential biomarkers and delineated pathways. METHODS: The current study consists of searching for and investigating primary studies from PubMed and Dimensions.ai, published between 2018 and 2022 that reported network medicine perspectives and the coupling of ML techniques. Each abstract and full-text study was individually evaluated, and the relevant studies were finally included in the review for discussion once they met the inclusion and exclusion criteria. RESULTS: We identified 109 eligible publications from primary studies representing this systematic review. The data coalesced into two themes: application of network science to identify disease modules and promising biomarkers in ALS, along with network-based ML approaches. Conclusion This systematic review gives an overview of the network medicine approaches and implementations of network-based ML algorithms in ALS to determine new disease genes, and identify critical pathways and therapeutic target discovery for personalized treatment.

Genomic landscape of the DHA1 family in Candida auris and mapping substrate repertoire of CauMdr1.

The last decade has witnessed the rise of an extremely threatening healthcare-associated multidrug-resistant non-albicans Candida (NAC) species, Candida auris. Since besides target alterations, efflux mechanisms contribute maximally to antifungal resistance, it is imperative to investigate their contributions in this pathogen. Of note, within the major facilitator superfamily (MFS) of efflux pumps, drug/H+ antiporter family 1 (DHA1) has been established as a predominant contributor towards xenobiotic efflux. Our study provides a complete landscape of DHA1 transporters encoded in the genome of C. auris. This study identifies 14 DHA1 transporters encoded in the genome of the pathogen. We also construct deletion and heterologous overexpression strains for the most important DHA1 drug transporter, viz., CauMdr1 to map the spectrum of its substrates. While the knockout strain did not show any significant changes in the resistance patterns against most of the tested substrates, the ortholog when overexpressed in a minimal background Saccharomyces cerevisiae strain, AD1-8u-, showed significant enhancement in the minimum inhibitory concentrations (MICs) against a large panel of antifungal molecules. Altogether, the present study provides a comprehensive template for investigating the role of DHA1 members of C. auris in antifungal resistance mechanisms. KEY POINTS: • Fourteen putative DHA1 transporters are encoded in the Candida auris genome. • Deletion of the CauMDR1 gene does not lead to major changes in drug resistance. • CauMdr1 recognizes and effluxes numerous xenobiotics, including prominent azoles.

Both COVID-19 infection and vaccination induce high-affinity cross-clade responses to SARS-CoV-2 variants.

The B.1.1.529 (omicron) variant has rapidly supplanted most other SARS-CoV-2 variants. Using microfluidics-based antibody affinity profiling (MAAP), we have characterized affinity and IgG concentration in the plasma of 39 individuals with multiple trajectories of SARS-CoV-2 infection and/or vaccination. Antibody affinity was similar against the wild-type, delta, and omicron variants (K A ranges: 122 ± 155, 159 ± 148, 211 ± 307 µM-1, respectively), indicating a surprisingly broad and mature cross-clade immune response. Postinfectious and vaccinated subjects showed different IgG profiles, with IgG3 (p-value = 0.002) against spike being more prominent in the former group. Lastly, we found that the ELISA titers correlated linearly with measured concentrations (R = 0.72) but not with affinity (R = 0.29). These findings suggest that the wild-type and delta spike induce a polyclonal immune response capable of binding the omicron spike with similar affinity. Changes in titers were primarily driven by antibody concentration, suggesting that B-cell expansion, rather than affinity maturation, dominated the response after infection or vaccination.

Bioinformatic Identification of ABC Transporters in Candida auris.

Antifungal resistance mediated by overexpression of ABC transporters is one of the primary roadblocks to effective therapy against Candida infections. Thus, identification and characterization of the ABC transporter repertoire in Candida species are of high relevance. The method described in the chapter is based on our previously developed bioinformatic pipeline for identification of ABC proteins in Candida species. The methodology essentially involves the utilization of a hidden Markov model (HMM) profile of the nucleotide-binding domain (NBD) of ABC proteins to mine these proteins from the proteome of Candida species. Further, a widely used tool to predict membrane protein topology is exploited to identify the true transporter candidates out of the ABC proteins. Even though the chapter specifically focuses on a method to identify ABC transporters in Candida auris , the same can also be applied to any other Candida species.

Genome-wide analysis of PTR transporters in Candida species and their functional characterization in Candida auris.

The peptide transport (PTR) or proton-dependent oligopeptide transporter (POT) family exploits the inwardly directed proton motive force to facilitate the cellular uptake of di/tripeptides. Interestingly, some representatives are also shown to import peptide-based antifungals in certain Candida species. Thus, the identification and characterization of PTR transporters serve as an essential first step for their potential usage as antifungal peptide uptake systems. Herein, we present a genome-wide inventory of the PTR transporters in five prominent Candida species. Our study identifies 2 PTR transporters each in C. albicans and C. dubliniensis, 1 in C. glabrata, 4 in C. parapsilosis, and 3 in C. auris. Notably, despite all representatives retaining the conserved features seen in the PTR family, there exist two distinct classes of PTR transporters that differ in terms of their sequence identities and lengths of certain extracellular and intracellular segments. Further, we also evaluated the contribution of each PTR protein of the newly emerged multi-drug-resistant C. auris in di/tripeptide uptake. Notably, deletion of two PTR genes BNJ08_003830 and BNJ08_005124 led to a marked reduction in the transport capabilities of several tested di/tripeptides. However, all three genes could complement the role of native PTR2 gene of Saccharomyces cerevisiae, albeit to varied levels. Besides, BNJ08_005124 deletion also resulted in increased resistance toward the peptide-nucleoside drug Nikkomycin Z as well as the glucosamine-6-phosphate synthase inhibitor, L-norvalyl-N3-(4-methoxyfumaroyl)-L-2,3-diaminopropionoic acid (Nva-FMDP), pointing toward its predominant role in their uptake mechanism. Altogether, the study provides an important template for future structure-function investigations of PTR transporters in Candida species. KEY POINTS: • Candida genome encodes for two distinct classes of PTR transporters. • Candida auris encodes for 3 PTR transporters with different specificities. • BNJ08_005124 in C. auris is involved in the uptake of Nikkomycin Z and Nva-FMDP.

Identifying the Novel Inhibitors Against the Mycolic Acid Biosynthesis Pathway Target "mtFabH" of Mycobacterium tuberculosis.

Mycolic acids are the key constituents of mycobacterial cell wall, which protect the bacteria from antibiotic susceptibility, helping to subvert and escape from the host immune system. Thus, the enzymes involved in regulating and biosynthesis of mycolic acids can be explored as potential drug targets to kill Mycobacterium tuberculosis (Mtb). Herein, Kyoto Encyclopedia of Genes and Genomes is used to understand the fatty acid metabolism signaling pathway and integrative computational approach to identify the novel lead molecules against the mtFabH (ß-ketoacyl-acyl carrier protein synthase III), the key regulatory enzyme of the mycolic acid pathway. The structure-based virtual screening of antimycobacterial compounds from ChEMBL library against mtFabH results in the selection of 10 lead molecules. Molecular binding and drug-likeness properties of lead molecules compared with mtFabH inhibitor suggest that only two compounds, ChEMBL414848 (C1) and ChEMBL363794 (C2), may be explored as potential lead molecules. However, the spatial stability and binding free energy estimation of thiolactomycin (TLM) and compounds C1 and C2 with mtFabH using molecular dynamics simulation, followed by molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) indicate the better activity of C2 (ΔG = -14.18 kcal/mol) as compared with TLM (ΔG = -9.21 kcal/mol) and C1 (ΔG = -13.50 kcal/mol). Thus, compound C1 may be explored as promising drug candidate for the structure-based drug designing of mtFabH inhibitors in the therapy of Mtb.

Computational Insights of Unfolding of N-Terminal Domain of TDP-43 Reveal the Conformational Heterogeneity in the Unfolding Pathway.

TDP-43 proteinopathies is a disease hallmark that characterizes amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD). The N-terminal domain of TDP-43 (NTD) is important to both TDP-43 physiology and TDP-43 proteinopathy. However, its folding and dimerization process is still poorly characterized. In the present study, we have investigated the folding/unfolding of NTD employing all-atom molecular dynamics (MD) simulations in 8 M dimethylsulfoxide (DMSO) at high temperatures. The MD results showed that the unfolding of the NTD at high temperature evolves through the formation of a number of conformational states differing in their stability and free energy. The presence of structurally heterogeneous population of intermediate ensembles was further characterized by the different extents of solvent exposure of Trp80 during unfolding. We suggest that these non-natives unfolded intermediate ensembles may facilitate NTD oligomerization and subsequently TDP-43 oligomerization, which might lead to the formation of irreversible pathological aggregates, characteristics of disease pathogenesis.

Visual working memory performance is intact across development in autism spectrum disorder.

Autism spectrum disorder (ASD) is associated with atypical visual processing and deficits in working memory (WM). Visual WM performance typically improves between childhood and adulthood, but such improvement may be atypical in ASD. To better understand how visual WM develops, we used a well-established change detection task across multiple visual features. We examined visual WM for color, shape, and pattern in children, adolescents, and adults with and without ASD. VWM capacity and performance for all visual features improved across age similarly for both the TD and ASD groups. While performance was better on set size 4 trials than set size 8 trials for color, shape, and no change trials, such an effect was not evident for pattern change trials. Overall, the present findings suggest that VWM for different visual features may be intact across development in ASD. The ability to hold multiple objects in mind (WM) improves across typical development, but it remains unclear whether such improvement occurs in ASD. We found that developmental improvements in WM for different types of object details (e.g., color, shape, and pattern) is generally similar for both ASD and typical development. LAY SUMMARY: The ability to hold multiple objects in mind (working memory [WM]) improves across typical development, but it remains unclear whether such improvement occurs in autism spectrum disorder (ASD). We found that developmental improvements in WM for different types of object details (e.g., color, shape, pattern) is generally similar for both ASD and typical development.

Predicting children's math skills from task-based and resting-state functional brain connectivity.

A critical goal of cognitive neuroscience is to predict behavior from neural structure and function, thereby providing crucial insights into who might benefit from clinical and/or educational interventions. Across development, the strength of functional connectivity among a distributed set of brain regions is associated with children's math skills. Therefore, in the present study we use connectome-based predictive modeling to investigate whether functional connectivity during numerical processing and at rest "predicts" children's math skills (N = 31, Mage = 9.21 years, 14 Female). Overall, we found that functional connectivity during symbolic number comparison and rest, but not during nonsymbolic number comparison, predicts children's math skills. Each task revealed a largely distinct set of predictive connections distributed across canonical brain networks and major brain lobes. Most of these predictive connections were negatively correlated with children's math skills so that weaker connectivity predicted better math skills. Notably, these predictive connections were largely nonoverlapping across task states, suggesting children's math abilities may depend on state-dependent patterns of network segregation and/or regional specialization. Furthermore, the current predictive modeling approach moves beyond brain-behavior correlations and toward building models of brain connectivity that may eventually aid in predicting future math skills.

Age differences and brain maturation provide insight into heterogeneous results in autism spectrum disorder.

Studies comparing individuals with autism spectrum disorder (ASD) to typically developing (TD) individuals have yielded inconsistent results. These inconsistencies reflect, in part, atypical trajectories of development in children and young adults with ASD compared to TD peers. These different trajectories alter group differences between children with and without ASD as they age. This paper first summarizes the disparate trajectories evident in our studies and, upon further investigation, laboratories using the same recruiting source. These studies indicated that cognition improves into adulthood typically, and is associated with the maturation of striatal, frontal, and temporal lobes, but these age-related improvements did not emerge in the young adults with ASD. This pattern - of improvement into adulthood in the TD group but not in the group with ASD - occurred in both social and non-social tasks. However, the difference between TD and ASD trajectories was most robust on a social task, face recognition. While tempting to ascribe this uneven deficit to the social differences in ASD, it may also reflect the prolonged typical development of social cognitive tasks such as face recognition into adulthood. This paper then reviews the evidence on age-related and developmental changes from other studies on ASD. The broader literature also suggests that individuals with ASD do not exhibit the typical improvements during adolescence on skills important for navigating the transition to adulthood. These skills include execution function, social cognition and communication, and emotional recognition and self-awareness. Relatedly, neuroimaging studies indicate arrested or atypical brain maturation in striatal, frontal, and temporal regions during adolescence in ASD. This review not only highlights the importance of a developmental framework and explicit consideration of age and/or stage when studying ASD, but also the potential importance of adolescence on outcomes in ASD.

Mapping the FtsQBL divisome components in bacterial NTD pathogens as potential drug targets.

Cytokinesis is an essential process in bacterial cell division, and it involves more than 25 essential/non-essential cell division proteins that form a protein complex known as a divisome. Central to the divisome are the proteins FtsB and FtsL binding to FtsQ to form a complex FtsQBL, which helps link the early proteins with late proteins. The FtsQBL complex is highly conserved as a component across bacteria. Pathogens like Vibrio cholerae, Mycobacterium ulcerans, Mycobacterium leprae, and Chlamydia trachomatis are the causative agents of the bacterial Neglected Tropical Diseases Cholera, Buruli ulcer, Leprosy, and Trachoma, respectively, some of which seemingly lack known homologs for some of the FtsQBL complex proteins. In the absence of experimental characterization, either due to insufficient resources or the massive increase in novel sequences generated from genomics, functional annotation is traditionally inferred by sequence similarity to a known homolog. With the advent of accurate protein structure prediction methods, features both at the fold level and at the protein interaction level can be used to identify orthologs that cannot be unambiguously identified using sequence similarity methods. Using the FtsQBL complex proteins as a case study, we report potential remote homologs using Profile Hidden Markov models and structures predicted using AlphaFold. Predicted ortholog structures show conformational similarity with corresponding E. coli proteins irrespective of their level of sequence similarity. Alphafold multimer was used to characterize remote homologs as FtsB or FtsL, when they were not sufficiently distinguishable at both the sequence or structure level, as their interactions with FtsQ and FtsW play a crucial role in their function. The structures were then analyzed to identify functionally critical regions of the proteins consistent with their homologs and delineate regions potentially useful for inhibitor discovery.

ICMR's Antimicrobial Resistance Surveillance system (i-AMRSS): a promising tool for global antimicrobial resistance surveillance.

BACKGROUND: Growing resistance to antimicrobials has become an important health issue of the 21st century. Many international, national and local approaches are being employed for the control and prevention of antimicrobial resistance (AMR). Among them, surveillance is reported to be the best method to reduce the spread of infection and thereby AMR. An integral component of AMR surveillance is the informatics suite for collection, storage and analysis of surveillance data. METHODS: Considering the traits of an optimal surveillance tool and constraints with existing tools, Indian Council of Medical Research (ICMR) initiated the design and development of ICMR's Antimicrobial Resistance Surveillance system (i-AMRSS). i-AMRSS is a web-based tool built using modular architecture. It is capable of collecting standardized data from small laboratories to generate local and nationwide reports. RESULTS: i-AMRSS is a robust, comprehensive, modular, extensible and intelligent open-source tool piloted in ICMR's AMR Network (31 hospitals and laboratories across India) since 2016. The developed tool has collected more than 280 000 patient records to date. CONCLUSIONS: The standardized data collected through i-AMRSS would be valuable for various collaborators to monitor outbreaks and infection control practices, evaluate transmission dynamics and formulate antibiotic use and selling policies. The tool is presently being used to capture human testing and consumption data, however, it can be extended for AMR surveillance using a 'One Health' approach.

ABC-finder: A containerized web server for the identification and topology prediction of ABC proteins.

In view of the multiple clinical and physiological implications of ABC transporter proteins, there is a considerable interest among researchers to characterize them functionally. However, such characterizations are based on the premise that ABC proteins are accurately identified in the proteome of an organism, and their topology is correctly predicted. With this objective, we have developed ABC-finder, i.e., a Docker-based package for the identification of ABC proteins in all organisms, and visualization of the topology of ABC proteins using a web browser. ABC-finder is built and deployed in a Linux container, making it scalable for many concurrent users on our servers and enabling users to download and run it locally. Overall, ABC-finder is a convenient, portable, and platform-independent tool for the identification and topology prediction of ABC proteins. ABC-finder is accessible at http://abc-finder.osdd.jnu.ac.in.