Evaluation of Surface Microstructure and Compressive Strength of Mineral Trioxide Aggregate and Biodentine in the Existence and Absence of Oral Tissue Fluids.

Background: Calcium silicate cement like mineral trioxide aggregate (MTA) and Biodentine are known for their biocompatibility and are effectively used as retrograde filling materials. During their placement, the materials interact with oral tissue fluids like saliva and blood, so the aim of the present study was to assess the effect of distilled water, saline, and blood on the surface microstructure and compressive strength of MTA and Biodentine. Materials and methods: In this experimental study, a total of 84 custom-made cylindrical molds were randomly allocated into two main cement groups (n = 42) MTA and Biodentine. Each group was further subdivided into three subgroups (n = 14) as per the testing conditions, that is, samples exposed to distilled water, saline, and fresh blood. Around 10 samples from each subgroup were tested for compressive strength using a universal testing machine (UTM), and the remaining four samples were used to examine the surface characteristics of MTA and Biodentine using a scanning electron microscope (SEM). One-way analysis of variance (ANOVA) and Tukey's post hoc tests were employed to calculate the mean compressive strength and standard deviation values. Results: There was a significant difference in the compressive strength between MTA and Biodentine, especially in the presence of blood. During the SEM analysis, it was found that samples contaminated with blood or saline were devoid of acicular crystals in both groups. MTA group showed a more porous matrix with few hexagonal crystals than Biodentine. Conclusion: Biodentine may be advantageous as a root-end filling or root repair material in the presence of blood. How to cite this article: Bhullar KK, Gupta V, Sapra M, et al. Evaluation of Surface Microstructure and Compressive Strength of Mineral Trioxide Aggregate and Biodentine in the Existence and Absence of Oral Tissue Fluids. Int J Clin Pediatr Dent 2024;17(S-1):S1-S5.

Prediction of neurologic outcome after out-of-hospital cardiac arrest: An interpretable approach with machine learning.

Out-of-hospital cardiac arrest (OHCA) is a critical condition with low survival rates. In patients with a return of spontaneous circulation, brain injury is a leading cause of death. In this study, we propose an interpretable machine learning approach for predicting neurologic outcome after OHCA, using information available at the time of hospital admission. METHODS: The study population were 55 615 OHCA cases registered in the Swedish Cardiopulmonary Resuscitation Registry between 2010 and 2020. The dataset was split to training and validation sets (for model development) and test set (for evaluation of the final model). We used an XGBoost algorithm with stratified, repeated 10-fold cross-validation along with Optuna framework for hyperparameters tuning. The final model was trained on 10 features selected based on the importance scores and evaluated on the test set in terms of discrimination, calibration and bias-variance tradeoff. We used SHapley Additive exPlanations to address the 'black-box' model and align with eXplainable artificial intelligence. RESULTS: The final model achieved: area under the receiver operating characteristic value 0.964 (95% confidence interval (CI) [0.960-0.968]), sensitivity 0.606 (95% CI [0.573-0.634]), specificity 0.975 (95% CI [0.972-0.978]), positive predictive value (PPV) 0.664 (95% CI [0.625-0.696]), negative predictive value (NPV) 0.969 (95% CI [0.966-0.972]), macro F1 0.803 (95% CI [0.788-0.816]), and showed a very good calibration. SHAP features with the highest impact on the model's output were:'ROSC on arrival to hospital', 'Initial rhythm asystole' and 'Conscious on arrival to hospital'. CONCLUSIONS: The XGBoost machine learning model with 10 features available at the time of hospital admission showed good performance for predicting neurologic outcome after OHCA, with no apparent signs of overfitting.

SignEEG v1.0: Multimodal Dataset with Electroencephalography and Hand-written Signature for Biometric Systems.

Handwritten signatures in biometric authentication leverage unique individual characteristics for identification, offering high specificity through dynamic and static properties. However, this modality faces significant challenges from sophisticated forgery attempts, underscoring the need for enhanced security measures in common applications. To address forgery in signature-based biometric systems, integrating a forgery-resistant modality, namely, noninvasive electroencephalography (EEG), which captures unique brain activity patterns, can significantly enhance system robustness by leveraging multimodality's strengths. By combining EEG, a physiological modality, with handwritten signatures, a behavioral modality, our approach capitalizes on the strengths of both, significantly fortifying the robustness of biometric systems through this multimodal integration. In addition, EEG's resistance to replication offers a high-security level, making it a robust addition to user identification and verification. This study presents a new multimodal SignEEG v1.0 dataset based on EEG and hand-drawn signatures from 70 subjects. EEG signals and hand-drawn signatures have been collected with Emotiv Insight and Wacom One sensors, respectively. The multimodal data consists of three paradigms based on mental, & motor imagery, and physical execution: i) thinking of the signature's image, (ii) drawing the signature mentally, and (iii) drawing a signature physically. Extensive experiments have been conducted to establish a baseline with machine learning classifiers. The results demonstrate that multimodality in biometric systems significantly enhances robustness, achieving high reliability even with limited sample sizes. We release the raw, pre-processed data and easy-to-follow implementation details.

Prediction of survival in out-of-hospital cardiac arrest: the updated Swedish cardiac arrest risk score (SCARS) model.

Aims: Out-of-hospital cardiac arrest (OHCA) is a major health concern worldwide. Although one-third of all patients achieve a return of spontaneous circulation and may undergo a difficult period in the intensive care unit, only 1 in 10 survive. This study aims to improve our previously developed machine learning model for early prognostication of survival in OHCA. Methods and results: We studied all cases registered in the Swedish Cardiopulmonary Resuscitation Registry during 2010 and 2020 (n = 55 615). We compared the predictive performance of extreme gradient boosting (XGB), light gradient boosting machine (LightGBM), logistic regression, CatBoost, random forest, and TabNet. For each framework, we developed models that optimized (i) a weighted F1 score to penalize models that yielded more false negatives and (ii) a precision-recall area under the curve (PR AUC). LightGBM assigned higher importance values to a larger set of variables, while XGB made predictions using fewer predictors. The area under the curve receiver operating characteristic (AUC ROC) scores for LightGBM were 0.958 (optimized for weighted F1) and 0.961 (optimized for a PR AUC), while for XGB, the scores were 0.958 and 0.960, respectively. The calibration plots showed a subtle underestimation of survival for LightGBM, contrasting with a mild overestimation for XGB models. In the crucial range of 0-10% likelihood of survival, the XGB model, optimized with the PR AUC, emerged as a clinically safe model. Conclusion: We improved our previous prediction model by creating a parsimonious model with an AUC ROC at 0.96, with excellent calibration and no apparent risk of underestimating survival in the critical probability range (0-10%). The model is available at www.gocares.se.

A chromosome-scale assembly of Brassica carinata (BBCC) accession HC20 containing resistance to multiple pathogens and an early generation assessment of introgressions into B. juncea (AABB).

Brassica carinata (BBCC) commonly referred to as Ethiopian mustard is a natural allotetraploid containing the genomes of Brassica nigra (BB) and Brassica oleracea (CC). It is an oilseed crop endemic to the northeastern regions of Africa. Although it is under limited cultivation, B. carinata is valuable as it is resistant/highly tolerant to most of the pathogens affecting widely cultivated Brassica species of the U's triangle. We report a chromosome-scale genome assembly of B. carinata accession HC20 using long-read Oxford Nanopore sequencing and Bionano optical maps. The assembly has a scaffold N50 of ~39.8 Mb and covers ~1.11 Gb of the genome. We compared the long-read genome assemblies of the U's triangle species and found extensive gene collinearity between the diploids and allopolyploids with no evidence of major gene losses. Therefore, B. juncea (AABB), B. napus (AACC), and B. carinata can be regarded as strict allopolyploids. We cataloged the nucleotide-binding and leucine-rich repeat immune receptor (NLR) repertoire of B. carinata and, identified 465 NLRs, and compared these with the NLRs in the other Brassica species. We investigated the extent and nature of early-generation genomic interactions between the constituent genomes of B. carinata and B. juncea in interspecific crosses between the two species. Besides the expected recombination between the constituent B genomes, extensive homoeologous exchanges were observed between the A and C genomes. Interspecific crosses, therefore, can be used for transferring disease resistance from B. carinata to B. juncea and broadening the genetic base of the two allotetraploid species.

Making Germs Visible - Assessing the Impact of a School-Based, Low-Cost Intervention on Hand Hygiene Knowledge, Attitude and Practice of Children in Rural India.

Handwashing with soap at critical moments is one of the most important factors in controlling the spread of germs and preventing the spread of infection. The objective of this study was to determine the effectiveness of a low-cost, school-based intervention that simulated germs and their spread on hand hygiene knowledge, attitude and practice of primary school children. Five hundred and sixty-two students from 28 rural schools were enrolled in this pre-posttest study. Endline data was collected 4 weeks after conducting the intervention at baseline. The mean scores for knowledge, attitude and practice improved significantly after the intervention (p < .05). Significant positive gains were also observed in children's understanding of germs, the associated illness threat and washing hands with soap as a prevention mechanism. The present study suggests that entertainment-education-based interventions have the potential to improve hygiene behavior among children while being low-cost.

Bimodal electroencephalography-functional magnetic resonance imaging dataset for inner-speech recognition.

The recognition of inner speech, which could give a 'voice' to patients that have no ability to speak or move, is a challenge for brain-computer interfaces (BCIs). A shortcoming of the available datasets is that they do not combine modalities to increase the performance of inner speech recognition. Multimodal datasets of brain data enable the fusion of neuroimaging modalities with complimentary properties, such as the high spatial resolution of functional magnetic resonance imaging (fMRI) and the temporal resolution of electroencephalography (EEG), and therefore are promising for decoding inner speech. This paper presents the first publicly available bimodal dataset containing EEG and fMRI data acquired nonsimultaneously during inner-speech production. Data were obtained from four healthy, right-handed participants during an inner-speech task with words in either a social or numerical category. Each of the 8-word stimuli were assessed with 40 trials, resulting in 320 trials in each modality for each participant. The aim of this work is to provide a publicly available bimodal dataset on inner speech, contributing towards speech prostheses.

Genetic mapping of some key plant architecture traits in Brassica juncea using a doubled haploid population derived from a cross between two distinct lines: vegetable type Tumida and oleiferous Varuna.

KEY MESSAGE: Genetic mapping of some key plant architectural traits in a vegetable type and an oleiferous B. juncea cross revealed QTL and candidate genes for breeding more productive ideotypes. Brassica juncea (AABB, 2n = 36), commonly called mustard, is an allopolyploid crop of recent origin but contains considerable morphological and genetic variation. An F1-derived doubled haploid population developed from a cross between an Indian oleiferous line, Varuna, and a Chinese stem type vegetable mustard, Tumida showed significant variability for some key plant architectural traits-four stem strength-related traits, stem diameter (Dia), plant height (Plht), branch initiation height (Bih), number of primary branches (Pbr), and days to flowering (Df). Multi-environment QTL analysis identified twenty Stable QTL for the above-mentioned nine plant architectural traits. Though Tumida is ill-adapted to the Indian growing conditions, it was found to contribute favorable alleles in Stable QTL for five architectural traits-press force, Dia, Plht, Bih, and Pbr; these QTL could be used to breed superior ideotypes in the oleiferous mustard lines. A QTL cluster on LG A10 contained Stable QTL for seven architectural traits that included major QTL (phenotypic variance ≥ 10%) for Df and Pbr, with Tumida contributing the trait-enhancing alleles for both. Since early flowering is critical for the cultivation of mustard in the Indian subcontinent, this QTL cannot be used for the improvement of Pbr in the Indian gene pool lines. Conditional QTL analysis for Pbr, however, identified other QTL which could be used for the improvement of Pbr without affecting Df. The Stable QTL intervals were mapped on the genome assemblies of Tumida and Varuna for the identification of candidate genes.

Lessons Learnt and the Way Forward for Drug Development Against Isocitrate Lyase from Mycobacterium tuberculosis.

Isocitrate lyase (ICL), an enzyme of the glyoxylate shunt pathway, is essential for the virulence and persistence of dreaded Mycobacterium tuberculosis (Mtb) in its host. This pathway, along with the methylcitrate cycle, facilitates the utilization of fatty acids as a carbon source inside hostile host environments such as in granulomas, and hence enzymes of this pathway are novel antitubercular targets. The genome sequence of pathogenic Mtb H37Rv presents three ICLs annotated as Rv0467 (prokaryotic homologue), Rv1915 and Rv1916. The latter two, Rv1915 and Rv1916, together constitute the longer version of ICL2, a eukaryotic counterpart. Despite being a well-known drug target, no Mtb ICL inhibitor has reached clinical trials due to challenges associated with targeting all the 3 orthologs. This gap is the result of uncharacterized Rv1915 and Rv1916. This review aims to appreciate chronologically the key studies that have built our comprehension of Mtb ICLs. Recently characterized Mtb Rv1915 and Rv1916, which further open venues for developing effective inhibitors against the persistent and drug-resistant Mtb, are discussed separately.

Downstream Acute Care Utilization Following Initial Prescription of an Opioid Pain Reliever Among Emergency Department Patients With Low-Severity Conditions.

INTRODUCTION: We sought to investigate the association between receipt of an opioid pain reliever (OPR) in the emergency department (ED) and downstream acute health care utilization. METHODS: Within Kaiser Permanente Northern California, we identified opioid-naïve patients, ages 18-64, who were treated and discharged from the ED for a painful, low-severity condition between January 1, 2017, and December 31, 2017. We also identified patients who received an OPR, either administered in the ED or obtained at a Kaiser Permanente Northern California pharmacy within 7 days of ED arrival, and investigated subsequent acute care utilization in cases with at least 1 ED, urgent care, or inpatient visit within 1 month or 3 months of the index encounter or 2 visits within 12 months. RESULTS: Of the 39,468 adults included in our study, 50.7% were female, 55.0% were non-White, and 25.2% received an OPR in association with their index ED encounter. After adjustment, we found that patients who received an OPR had greater odds of downstream acute care utilization than those who did not, with odds ratios of 1.68, 1.53, and 1.50 at 1, 3, and 12 months, respectively (all p < 0.05). CONCLUSION: Patients who received an OPR at their index encounter had substantially increased odds of a subsequent ED, urgent care, or inpatient visit. This effect was most pronounced early in follow-up and persisted for the duration of the study period. Receipt of an OPR among opioid-naïve adults for a painful, low-severity condition is associated with increased downstream acute care utilization.

Rv1915 and Rv1916 from Mycobacterium tuberculosis H37Rv form in vitro protein-protein complex.

BACKGROUND: Mycobacterium tuberculosis (Mtb) isocitrate lyase (ICL) is an established drug target that facilitates Mtb persistence. Unlike other mycobacterial strains, where ICL2 is a single gene product, H37Rv has a split event, resulting in two tandemly coded icls - rv1915 and rv1916. Our recent report on functionality of individual Rv1915 and Rv1916, led to postulate the cooperative role of these proteins in pathogen's survival under nutrient-limiting conditions. This study investigates the possibility of Rv1915 and Rv1916 interacting and forming a complex. METHODS: Pull down assay, activity assay, mass spectrometry and site directed mutagenesis was employed to investigate and validate Rv1915-Rv1916 complex formation. RESULTS: Rv1915 and Rv1916 form a stable complex in vitro, with enhanced ICL/MICL activities as opposed to individual proteins. Further, activities monitored in the presence of acetyl-CoA show significant increase for Rv1916 and the complex but not of Rv0467 and Rv1915Δ90CT. Both full length and truncated Rv1915Δ90CT can form complex, implying the absence of its C-terminal disordered region in complex formation. Further, in silico analysis and site-directed mutagenesis studies reveal Y64 and Y65 to be crucial residues for Rv1915-Rv1916 complex formation. CONCLUSIONS: This study uncovers the association between Rv1915 and Rv1916 and supports the role of acetyl-CoA in escalating the ICL/MICL activities of Rv1916 and Rv1915Δ90CT-Rv1916 complex. GENERAL SIGNIFICANCE: Partitioning of ICL2 into Rv1915 and Rv1916 that associates to form a complex in Mtb H37Rv, suggests its importance in signaling and regulation of metabolic pathway particularly in carbon assimilation.

Electronic Patient Symptom Management Program to Support Patients Receiving Cancer Treatment at Home During the COVID-19 Pandemic.

OBJECTIVES: Remote patient monitoring became critical for patients receiving cancer treatment during the COVID-19 pandemic. We sought to test feasibility of an electronic patient symptom management program implemented during a pandemic. We collected and analyzed the real-world data to inform practice quality improvement and understand the patient experience. METHODS: Eligible patients had breast, lung, or ovarian cancers, multiple myeloma, or acute myeloid leukemia and 12 weeks of planned chemotherapy. Patients were notified that a symptom survey with common symptoms derived from the National Cancer Institute's Patient-Reported Outcomes Version of the Common Terminology Criteria for Adverse Events was available to complete using a smart phone, tablet, or computer. Patients recorded their symptoms and results were sent to the provider. Patients received care guidelines for mild/moderate severity symptoms and a phone call from the provider for severe reports. RESULTS: A total of 282 patients generated > 119 088 data points. Patients completed 2860 of 3248 assigned surveys (88%), and 152 of 282 patients (54%) had symptom reports that generated an immediate notification to the provider. Longitudinal data were analyzed to determine whether previous reports predicted a notification alert and whether symptoms resolved after the alert was addressed. CONCLUSIONS: An electronic patient symptom management program was implemented in the midst of the COVID-19 pandemic. Enrollment of 282 patients and a high survey completion (88%) demonstrated feasibility/acceptance. Patients reported symptoms at severe levels of 54% of the time and received self-management instructions and provider phone calls that resolved or decreased the severity of the symptom. A standard approach and validated instrument provide opportunities for improving and benchmarking outcomes.

Genetic Analysis of Heterosis for Yield Influencing Traits in Brassica juncea Using a Doubled Haploid Population and Its Backcross Progenies.

The exploitation of heterosis through hybrid breeding is one of the major breeding objectives for productivity increase in crop plants. This research analyzes the genetic basis of heterosis in Brassica juncea by using a doubled haploid (DH) mapping population derived from F1 between two heterotic inbred parents, one belonging to the Indian and the other belonging to the east European gene pool, and their two corresponding sets of backcross hybrids. An Illumina Infinium Brassica 90K SNP array-based genetic map was used to identify yield influencing quantitative trait loci (QTL) related to plant architecture, flowering, and silique- and seed-related traits using five different data sets from multiple trials, allowing the estimation of additive and dominance effects, as well as digenic epistatic interactions. In total, 695 additive QTL were detected for the 14 traits in the three trials using five data sets, with overdominance observed to be the predominant type of effect in determining the expression of heterotic QTL. The results indicated that the design in the present study was efficient for identifying common QTL across multiple trials and populations, which constitute a valuable resource for marker-assisted selection and further research. In addition, a total of 637 epistatic loci were identified, and it was concluded that epistasis among loci without detectable main effects plays an important role in controlling heterosis in yield of B. juncea.

Rational Design and Development of HDAC Inhibitors for Breast Cancer Treatment.

BACKGROUND: Breast cancer is the most prevalent cancer amongst females across the globe, and with over 2 million new cases reported in 2018, it poses a huge economic burden to the already dwindling public health. A dearth of therapies in the pipeline to treat triple-negative breast cancers and acquisition of resistance against the existing line of treatments urge the need to strategize novel therapeutics in order to add new drugs to the pipeline. HDAC inhibitors (HDACi) is one such class of small molecule inhibitors that target histone deacetylases to bring about chromosomal remodelling and normalize dysregulated gene expression that marks breast cancer progression. OBJECTIVE: While four HDACi have been approved by the FDA for the treatment of different cancer types, no HDACi is specifically earmarked for clinical management of breast cancer. Owing to the differential HDAC expression pertaining to different types of breast cancers, isoform-selective HDAC inhibitors need to be discovered. CONCLUSION: This review attempts to set the stage for the rational structure-based discovery of isoform-selective HDACi by providing structural insights into different HDACs and their catalytic folds based on their classes and individual landscape. The development of inhibitors in accordance with the differential expression of HDAC isoforms exhibited in breast cancer cells is a promising strategy to rationally design selective and effective inhibitors, adopting a 'personalized-medicine' approach.

New insights into the structure and function of an emerging drug target CysE.

The antimicrobial resistant strains of several pathogens are major culprits of hospital-acquired nosocomial infections. An active and urgent action is necessary against these pathogens for the development of unique therapeutics. The cysteine biosynthetic pathway or genes (that are absent in humans) involved in the production of L-cysteine appear to be an attractive target for developing novel antibiotics. CysE, a Serine Acetyltransferase (SAT), catalyzes the first step of cysteine synthesis and is reported to be essential for the survival of persistence in several microbes including Mycobacterium tuberculosis. Structure determination provides fundamental insight into structure and function of protein and aid in drug design/discovery efforts. This review focuses on the overview of current knowledge of structure function, regulatory mechanism, and potential inhibitors (active site as well as allosteric site) of CysE. Despite having conserved structure, slight modification in CysE structure lead to altered the regulatory mechanism and hence affects the cysteine production. Due to its possible role in virulence and vital metabolism of pathogens makes it a potential target in the quest to develop novel therapeutics to treat multi-drug-resistant bacteria.

Heterogeneous ensemble with information theoretic diversity measure for human epithelial cell image classification.

In this work, we propose a heterogeneous committee (ensemble) of diverse members (classification approaches) to solve the problem of human epithelial (HEp-2) cell image classification using indirect Immunofluorescence (IIF) imaging. We hypothesize that an ensemble involving different feature representations can enable higher performance if individual members in the ensemble are sufficiently varied. These members are of two types: (1) CNN-based members, (2) traditional members. For the CNN members, we have employed the well-established ResNet, DenseNet, and Inception models, which have distinctive salient aspects. For the traditional members, we incorporate class-specific features which are characterized depending on visual morphological attributes, and some standard texture features. To select the members which are discriminating and not redundant, we use an information theoretic measure which considers the trade-off between individual accuracies and diversity among the members. For all selected members, a compelling fusion required to combine their outputs to reach a final decision. Thus, we also investigate various fusion methods that combine the opinion of the committee at different levels: maximum voting, product, decision template, Bayes, Dempster-Shafer, etc. The proposed method is evaluated using ICPR-2014 data which consists of more images than some previous datasets ICPR-2012 and demonstrate state-of-the-art performance. To check the effectiveness of the proposed methodology for other related datasets, we test our methodology with newly compiled large-scale HEp-2 dataset with 63K cell images and demonstrate comparable performance even with less number of training samples. The proposed method produces 99.80% and 86.03% accuracy respectively when tested on ICPR-2014 and a new large-scale data containing 63K samples. Graphical Abstract Overview of the proposed methodology.

A chromosome-scale assembly of allotetraploid Brassica juncea (AABB) elucidates comparative architecture of the A and B genomes.

Brassica juncea (AABB), commonly referred to as mustard, is a natural allopolyploid of two diploid species-B. rapa (AA) and B. nigra (BB). We report a highly contiguous genome assembly of an oleiferous type of B. juncea variety Varuna, an archetypical Indian gene pool line of mustard, with ~100× PacBio single-molecule real-time (SMRT) long reads providing contigs with an N50 value of >5 Mb. Contigs were corrected for the misassemblies and scaffolded with BioNano optical mapping. We also assembled a draft genome of B. nigra (BB) variety Sangam using Illumina short-read sequencing and Oxford Nanopore long reads and used it to validate the assembly of the B genome of B. juncea. Two different linkage maps of B. juncea, containing a large number of genotyping-by-sequencing markers, were developed and used to anchor scaffolds/contigs to the 18 linkage groups of the species. The resulting chromosome-scale assembly of B. juncea Varuna is a significant improvement over the previous draft assembly of B. juncea Tumida, a vegetable type of mustard. The assembled genome was characterized for transposons, centromeric repeats, gene content and gene block associations. In comparison to the A genome, the B genome contains a significantly higher content of LTR/Gypsy retrotransposons, distinct centromeric repeats and a large number of B. nigra specific gene clusters that break the gene collinearity between the A and the B genomes. The B. juncea Varuna assembly will be of major value to the breeding work on oleiferous types of mustard that are grown extensively in south Asia and elsewhere.

Homology modeling, structural insights and in-silico screening for selective inhibitors of mycobacterial CysE.

Tuberculosis posses a major threat for health practitioners due to lengthy treatment regimen, increase in the drug-resistant strains of Mycobacterium tuberculosis (M. tb) and unavailability of drugs for its persistent form. Therefore, there is an urgent need for discovery of new and improved anti-tubercular drugs. In M. tb, the two step de novo biosynthesis of L-cysteine, an essential metabolic pathway is reported to be up-regulated in the persistent phase of the organism, involves two enzymes CysE and CysK. Although, structural insights for rational drug discovery are available for the later, not much information is known for the former. This study proposes a 3-dimensional model of M. tb CysE followed by in-silico screening of 67,030 anti-tuberculosis bioactive compounds. Subsequently, post-processing of 1000 best hits was carried out and top 200 compounds thus obtained were docked into the active site cleft of E. coli homologue as a control, but revealed unexpected results. Differences in the active site architectures and comparative analysis of molecular electrostatic potentials between the two CysEs provide molecular basis for the compounds C1, C3, C4 and C7 exhibiting preferential binding for M. tb CysE. In addition, shorter N-terminus along with positive and irregular trimeric base of M. tb CysE indicates its biological assembly as trimer. Based on mapping of residues involved in cysteine sensitivity on to the model structure of M. tb CysE, it is hypothesized that feedback inhibition of this homologue by cysteine may be affected.Communicated by Ramaswamy H. Sarma.

Truncation of C-Terminal Intrinsically Disordered Region of Mycobacterial Rv1915 Facilitates Production of "Difficult-to-Purify" Recombinant Drug Target.

Availability of purified drug target is a prerequisite for its structural and functional characterization. However, aggregation of recombinant protein as inclusion bodies (IBs) is a common problem during the large scale production of overexpressed protein in heterologous host. Such proteins can be recovered from IB pool using some mild solubilizing agents such as low concentration of denaturants or detergents, alcohols and osmolytes. This study reports optimization of solubilization buffer for recovery of soluble and biologically active recombinant mycobacterial Rv1915/ICL2a from IBs. Even though the target protein could be solubilized successfully with mild agents (sarcosine and ßME) without using denaturants, it failed to bind on Ni-NTA resin. The usual factors such as loss of His6-tag due to proteolysis, masking of the tag due to its location or protein aggregation were investigated, but the actual explanation, provided through bioinformatics analysis, turned out to be presence of intrinsically disordered protein regions (IDPRs) at the C-terminus. These regions due to their inability to fold into ordered structure may lead to non-specific protein aggregation and hence reduced binding to Ni-NTA affinity matrix. With this rationale, 90 residues from the C-terminal of Rv1915/ICL2 were truncated, the variant successfully purified and characterized for ICL and MICL activities, supporting the disordered nature of Rv1915/ICL2a C-terminal. When a region that has definite structure associated in some mycobaterial strains such as CDC 1551 and disorder in others for instance Mycobacterium tuberculosis H37Rv, it stands to reason that larger interface in the later may have implication in binding to other cellular partner.

Validation of an Associative Transcriptomics platform in the polyploid crop species Brassica juncea by dissection of the genetic architecture of agronomic and quality traits.

The development of more productive crops will be key to addressing the challenges that climate change, population growth and diminishing resources pose to global food security. Advanced 'omics techniques can help to accelerate breeding by facilitating the identification of genetic markers for use in marker-assisted selection. Here, we present the validation of a new Associative Transcriptomics platform in the important oilseed crop Brassica juncea. To develop this platform, we established a pan-transcriptome reference for B. juncea, to which we mapped transcriptome data from a diverse panel of B. juncea accessions. From this panel, we identified 355 050 single nucleotide polymorphism variants and quantified the abundance of 93 963 transcripts. Subsequent association analysis of functional genotypes against a number of important agronomic and quality traits revealed a promising candidate gene for seed weight, BjA.TTL, as well as additional markers linked to seed colour and vitamin E content. The establishment of the first full-scale Associative Transcriptomics platform for B. juncea enables rapid progress to be made towards an understanding of the genetic architecture of trait variation in this important species, and provides an exemplar for other crops.