A Combined Technique for Randomisation of a Small Number of Participants with a Variety of Covariates into Treatment and Control Groups in Randomised Controlled Trials

Background: Randomised controlled trials are widely favoured in research design as the most rigorous way of determining the effectiveness of a treatment. For assigning a small number of participants who are identified before the start of the randomisation into treatment and control, the simple randomization technique can lead to imbalance of covariates among the groups. Furthermore while the stratified randomization method can control for the effect of covariates, in smaller clinical trials, the allocation of participants to groups by flip of a coin can result in uneven arms when the number of participants in each stratum in low. Despite the ability of covariate adaptive randomization technique in minimising the difference in covariate between the arms, the techniques comes with an unnecessary increase in the computational process specifically when number of covariates increases, and when all participants are identified prior to the randomisation. The purpose of this study was to propose a method of assigning small number of participants (68) who are identified before the start of randomisation, into treatment and control arms. Methods: The participants were first assigned into strata. For strata with even number of participants, the participants are sequentially pulled out of the strata on a random basis and assigned to arms by flip of a coin until half of the participants are assigned to any of the two arms. Then the remaining participants were assigned to the other arm. When the number of participants in a stratum is odd the first participants was pulled out of the stratum on a random basis and kept separate, then the remaining even number of participants were assigned to arms according to the method for strata that contain even number of participants. The first participants that were pulled out of the strata with odd number of participants were assigned sequentially using covariate adaptive randomisation method. Results: Two arms were created with minimal difference between the two arms and with the sum of absolute difference equal to 12. Conclusions: The method showed to be able to assign small number of participants into balanced arms with minimal computational costs when a number of covariates exist

Quantum dots coordinated with conjugated organic ligands: new nanomaterials with novel photophysics

CdSe quantum dots functionalized with oligo-(phenylene vinylene) (OPV) ligands (CdSe-OPV nanostructures) represent a new class of composite nanomaterials with significantly modified photophysics relative to bulk blends or isolated components. Single-molecule spectroscopy on these species have revealed novel photophysics such as enhanced energy transfer, spectral stability, and strongly modified excited state lifetimes and blinking statistics. Here, we review the role of ligands in quantum dot applications and summarize some of our recent efforts probing energy and charge transfer in hybrid CdSe-OPV composite nanostructures

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Distributed memory bounded path search algorithms for pervasive computing environments

10.1007/978-3-540-89197-0_37Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)5351 LNAI394-40

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Not AvailableSugarcane, the essential sugar and biofuel crop cultivated in tropics and subtropics worldwide, faces uncertainty in sustainable production and yield due to various biotic and abiotic factors. Among them, the fungal disease red rot (Colletotrichum falcatum) is a devastating disease that results in loss to farmers' economic livelihood and the elimination of cultivated varieties due to severe disease epidemics. Development of resistant varieties is a viable option for a sustainable solution. Studies in the past explored the sugarcane resistance mechanism that helped to understand the host defense and associated gene transcripts. In lieu of developing suitable markers associated with red rot resistance, we studied the temporal expression of nine selected red rot resistance-associated candidate gene transcripts in sugarcane x C. falcatum interaction on a set of sugarcane varieties after the pathogen challenge. The resulted expression analyses of the selected resistance-associated gene transcript showed differential expression during compatible and incompatible interactions. In the resistant variety it showed efficient defense responses as early recognition and defense response to the red rot pathogen compared to the susceptible one. Further, the selected resistance-associated gene transcripts have the potential to be explored for use in screening sugarcane varieties for red rot resistance traitsNot Availabl

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Not AvailableThe microRNAs role in various cellular and metabolic functions is gaining more limelight in line with second-generation NGS technology. For the validation of candidate miRNA genes, the quantitative real-time PCR is the widely trusted and efficient method to follow. Sugarcane miRNAs are less explored in sugarcane defense response during their interaction with Colletotrichum falcatum inciting red rot. Further, for RT-qPCR experiments involving sugarcane miRNAs expression studies, a stable internal reference gene is required. Hence we have taken a study involving 20 candidate genes to identify stable expressing reference genes using NormFinder, geNorm, BestKeeper, and delta Ct statistical algorithms. The candidate reference gene included miRNAs and protein-coding genes. The results indicated that there is a variation in ranking among the algorithms. We found miR1862c as the stably expressed miRNA reference gene among the candidates and miR444b.2 along miR1862c formed the best reference gene pair combination, which can be used in the experiments aiming to explore sugarcane miRNAs in the defense mechanism against C. falcatum. The stable miRNA reference gene was further validated with other lesser stable reference gene candidates to assess the effect of stable reference genes during normalization. The present study evaluating the sugarcane miRNAs as reference genes for normalizing RT-qPCR expression data involving miRNAs during sugarcane x C. falcatum interaction is the first of its kind. Further, this systematic approach can be followed to assess the reference gene in various experimental conditions involving sugarcane miRNAsNot Availabl

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Not AvailableSugarcane crop, the major source of sugar is a high value commercial crop. The importance of the crop is growing as it has the potential to boost the green fuel production and various other eco-friendly products. The fungal disease, red rot (Colletotrichum falcatum) is a dreadful one and studying the dynamics of host-pathogen interaction is essential to develop disease resistant varieties. Earlier, the role of 3-deoxyanthocyanidin phytoalexins in red rot resistance was established. Further studies were made to assess antifungal activities of these compounds against C. falcatum through in vitro assays. Since phenyl propanoid biosynthesis pathway is the major secondary metabolite producing pathway which leads to production of flavonoids, isoflavonoids and lignin, studies were made to explore expression dynamics in major gene transcripts involved in anthocyanidin pathway by qRT-PCR. Our studies showed antifungal nature of the sugarcane phytoalexins 3-deoxy anthocyanidins compounds, apigeninidin and luteolinidin along with differential expression of transcripts involved in the phytoalexin biosynthesis pathway during compatible and incompatible interactionsNot Availabl

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Not AvailableResistance against the fungal pathogen Colletotrichum falcatum causing red rot is one of the most desirable traits for sustainable crop cultivation in sugarcane. To gain new insight into the host defense mechanism against C. falcatum, we studied the role of sugarcane microRNAs during compatible and incompatible interactions by adopting the NGS platform. We have sequenced a total of 80 miRNA families that comprised 980 miRNAs, and the putative targets of the miRNAs include transcription factors, membrane-bound proteins, glutamate receptor proteins, lignin biosynthesis proteins, signaling cascade proteins, transporter proteins, mitochondrial proteins, ER proteins, defense-related, stress response proteins, translational regulation proteins, cell proliferation, and ubiquitination proteins. Further, qRT-PCR analyses of 8 differentially regulated miRNAs and 26 gene transcript targets expression indicated that these miRNAs have a regulatory effect on the expression of respective target genes in most of the cases. Also, the results suggest that certain miRNA regulates many target genes that are involved in inciting early responses to the pathogen infection, signaling pathways, endoplasmic reticulum stress, and resistance gene activation through feedback response from various cellular processes during the compatible and incompatible interaction with the red rot pathogen C. falcatum. The present study revealed the role of sugarcane miRNAs and their target genes during sugarcane - C. falcatum interaction and provided new insight into the miRNA mediated defense mechanism in sugarcane for the first timeNot Availabl

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Not AvailableMachine learning algorithms were employed for predicting the feed conversion efficiency (FCE), using the blood parameters and average daily gain (ADG) as predictor variables in buffalo heifers. It was observed that isotonic regression outperformed other machine learning algorithms used in study. Further, we also achieved the best performance evaluation metrics model with additive regression as the meta learner and isotonic regression as the base learner on 10-fold cross-validation and leaving-one-out cross-validation tests. Further, we created three separate partial least square regression (PLSR) models using all 14 parameters of blood and ADG as independent (explanatory) variables and FCE as the dependent variable, to understand the interactions of blood parameters, ADG with FCE each by inclusion of all FCE values (i), only higher FCE values (negative RFI) (ii), and inclusion of only lower FCE (positive RFI) values (iii). The PLSR model including only the higher FCE values was concluded the best, based on performance evaluation metrics as compared to PLSR models developed by inclusion of the lower FCE values and all types of FCE values. IGF1 and its interactions with the other blood parameters were found highly influential for higher FCE measures. The strength of the estimated interaction effects of the blood parameter in relation to FCE may facilitate understanding of intricate dynamics of blood parameters for growth.Not Availabl