RNAmut: robust identification of somatic mutations in acute myeloid leukemia using RNA-sequencing.

Acute myeloid leukemia (AML) is an aggressive malignancy of haematopoietic stem cells driven by a well-defined set of somatic mutations.1,2 Identifying the mutations driving individual cases is important for assigning the patient to a recognized World Health Organisation category, establishing prognostic risk and tailoring post-consolidation therapy.3 As a result, AML research and diagnostic laboratories apply diverse methodologies to detect important mutations and many are introducing next-generation sequencing (NGS) approaches to study extended panels of genes in order to refine genomic classification and prognostic category.1 Besides the implications of these developments on costs, expertise and reliance on commercial providers, they also do not capture gene expression data, which have independent prognostic value that cannot be inferred from somatic mutation profiles. The ability to detect AML gene mutations as well as gene expression profiles from a single assay, could provide a holistic tool that accelerates research, simplifies diagnostic work-up and helps develop integrated algorithms to refine individual patient prognosis. Here, we show that AML RNA sequencing (RNA-seq) data can be used to reliably detect all types of clinically important mutations and develop a bespoke fast and easy-to-use software (RNAmut) for this purpose that can be readily used by teams/laboratories without in-house bioinformatic expertise

Antiulcer, wound healing and hepatoprotective activities of the seaweeds Gracilaria crassa, Turbinaria ornata and Laurencia papillosa from the southeast coast of India

Seaweeds have bioactive compounds of interest in the pharmaceutical industry. In India, seaweeds are used exclusively for phycocolloids production and have not yet received consideration as a dietary supplement. So, it has become imperative to explore the biomedical potential of seaweeds and promote their utilization as a functional food. The seaweeds Turbinaria ornata, Gracillaria crassa and Laurencia papillosa, collected from the Tuticorin coast of the Southeast coast of India and selected based on preliminary screening, were extracted with acetone and evaluated for antiulcer, wound healing and hepatoprotective activities. L. papillosa showed the highest level of gastric protection activity (81%) at 200 mg/kg, comparable to the standard drug ranitidine (90%). G. crassa followed with 76%. G. crassa and L. papillosa, showed marked wound-healing activity. G. crassa at 200 mg/kg, showed a marked effect on the serum marker enzymes indicating prominent hepatoprotective activity. The noteworthy wound-healing and hepato-protective properties of G. crassa besides anti-ulcer activity next to L. papillosa were indicative of its potential for further consideration

Relational approaches to poverty in rural India: social, ecological and technical dynamics

Poverty is now widely recognised as multidimensional, with indicators including healthcare, housing and sanitation. Yet, relational approaches that foreground political-cultural processes remain marginalised in policy discourses. Focusing on India, we review a wide range of relational approaches to rural poverty. Beginning with early approaches that focus on structural reproduction of class, caste and to a lesser extent gender inequality, we examine new relational approaches developed in the last two decades. The new approaches examine diverse ways in which poverty is experienced and shapes mobilisations against deprivation. They draw attention to poor people’s own articulations of deprivation and alternate conceptions of well-being. They also show how intersecting inequalities of class, caste and gender shape governance practices and political movements. Despite these important contributions, the new relational approaches pay limited attention to technologies and ecologies in shaping the experience of poverty. Reviewing studies on the Green Revolution and wider agrarian transformations in India, we then sketch the outlines of a hybrid relational approach to poverty that combines socio-technical and -ecological dynamics. We argue that such an approach is crucial to challenge narrow economising discourses on poverty and to bridge the policy silos of poverty alleviation and (environmentally) sustainable development

Preleukemic single-cell landscapes reveal mutation-specific mechanisms and gene programs predictive of AML patient outcomes

Acute myeloid leukemia (AML) and myeloid neoplasms develop through acquisition of somatic mutations that confer mutation-specific fitness advantages to hematopoietic stem and progenitor cells. However, our understanding of mutational effects remains limited to the resolution attainable within immunophenotypically and clinically accessible bulk cell populations. To decipher heterogeneous cellular fitness to preleukemic mutational perturbations, we performed single-cell RNA sequencing of eight different mouse models with driver mutations of myeloid malignancies, generating 269,048 single-cell profiles. Our analysis infers mutation-driven perturbations in cell abundance, cellular lineage fate, cellular metabolism, and gene expression at the continuous resolution, pinpointing cell populations with transcriptional alterations associated with differentiation bias. We further develop an 11-gene scoring system (Stem11) on the basis of preleukemic transcriptional signatures that predicts AML patient outcomes. Our results demonstrate that a single-cell-resolution deep characterization of preleukemic biology has the potential to enhance our understanding of AML heterogeneity and inform more effective risk stratification strategies

Change in Allosteric Network Affects Binding Affinities of PDZ Domains: Analysis through Perturbation Response Scanning

The allosteric mechanism plays a key role in cellular functions of several PDZ domain proteins (PDZs) and is directly linked to pharmaceutical applications; however, it is a challenge to elaborate the nature and extent of these allosteric interactions. One solution to this problem is to explore the dynamics of PDZs, which may provide insights about how intramolecular communication occurs within a single domain. Here, we develop an advancement of perturbation response scanning (PRS) that couples elastic network models with linear response theory (LRT) to predict key residues in allosteric transitions of the two most studied PDZs (PSD-95 PDZ3 domain and hPTP1E PDZ2 domain). With PRS, we first identify the residues that give the highest mean square fluctuation response upon perturbing the binding sites. Strikingly, we observe that the residues with the highest mean square fluctuation response agree with experimentally determined residues involved in allosteric transitions. Second, we construct the allosteric pathways by linking the residues giving the same directional response upon perturbation of the binding sites. The predicted intramolecular communication pathways reveal that PSD-95 and hPTP1E have different pathways through the dynamic coupling of different residue pairs. Moreover, our analysis provides a molecular understanding of experimentally observed hidden allostery of PSD-95. We show that removing the distal third alpha helix from the binding site alters the allosteric pathway and decreases the binding affinity. Overall, these results indicate that (i) dynamics plays a key role in allosteric regulations of PDZs, (ii) the local changes in the residue interactions can lead to significant changes in the dynamics of allosteric regulations, and (iii) this might be the mechanism that each PDZ uses to tailor their binding specificities regulation

Prediction of properties of rubber by using artificial neural networks

Different rubber formulations were designed using nitrile rubber and a mixed crosslinking system consisting of sulfur/accelerator and electron beam radiation. Based on the experimental results, an artificial neural network (ANN) was constructed to simulate the mechanical properties and volume fraction of rubber. The ANN could predict accurately the above properties for a series of nitrile rubber compounds. However, the number of training data played a key role in the ANN predictive quality. In addition, the more complex the nonlinear relation between input and output was, the larger was the number of training dataset required. The predicted results were further validated using another mathematical model. The constructed ANN was verified with a completely different styrene butadiene rubber system. The prediction was found to be extremely good

The antinomies of audit: opacity, instability and charisma in the economic governance of a Hooghly shipyard

This paper rethinks audit regimes from the shadow-land of outsourcing in India. This is the arena of informalized work environments that are connected to global value chains and the revenue streams of an extractive liberalization state focused on public debt repayment. Based on ethnography of one such work-place, Venture Ltd shipyard in Howrah, it argues that in such settings audit creates opacity, disorders the work process and is part of value chains supported by diverse forms of charisma and racial distinction. As a result of these antinomies, testing events are times of friction rather than of the enactment of a shared calculative reason. Overall this case suggests that we need to focus more on the disordered capitalism supported by audit regimes