Transcriptional Profiling of Chondrodysplasia Growth Plate Cartilage Reveals Adaptive ER-Stress Networks That Allow Survival but Disrupt Hypertrophy

Metaphyseal chondrodysplasia, Schmid type (MCDS) is characterized by mild short stature and growth plate hypertrophic zone expansion, and caused by collagen X mutations. We recently demonstrated the central importance of ER stress in the pathology of MCDS by recapitulating the disease phenotype by expressing misfolding forms of collagen X (Schmid) or thyroglobulin (Cog) in the hypertrophic zone. Here we characterize the Schmid and Cog ER stress signaling networks by transcriptional profiling of microdissected mutant and wildtype hypertrophic zones. Both models displayed similar unfolded protein responses (UPRs), involving activation of canonical ER stress sensors and upregulation of their downstream targets, including molecular chaperones, foldases, and ER-associated degradation machinery. Also upregulated were the emerging UPR regulators Wfs1 and Syvn1, recently identified UPR components including Armet and Creld2, and genes not previously implicated in ER stress such as Steap1 and Fgf21. Despite upregulation of the Chop/Cebpb pathway, apoptosis was not increased in mutant hypertrophic zones. Ultrastructural analysis of mutant growth plates revealed ER stress and disrupted chondrocyte maturation throughout mutant hypertrophic zones. This disruption was defined by profiling the expression of wildtype growth plate zone gene signatures in the mutant hypertrophic zones. Hypertrophic zone gene upregulation and proliferative zone gene downregulation were both inhibited in Schmid hypertrophic zones, resulting in the persistence of a proliferative chondrocyte-like expression profile in ER-stressed Schmid chondrocytes. Our findings provide a transcriptional map of two chondrocyte UPR gene networks in vivo, and define the consequences of UPR activation for the adaptation, differentiation, and survival of chondrocytes experiencing ER stress during hypertrophy. Thus they provide important insights into ER stress signaling and its impact on cartilage pathophysiology

Mutant IDH inhibits HNF-4α to block hepatocyte differentiation and promote biliary cancer

Mutations in isocitrate dehydrogenase 1 (IDH1) and IDH2 are among the most common genetic alterations in intrahepatic cholangiocarcinoma (IHCC), a deadly liver cancer1, 2, 3, 4, 5. Mutant IDH proteins in IHCC and other malignancies acquire an abnormal enzymatic activity allowing them to convert α-ketoglutarate (αKG) to 2-hydroxyglutarate (2HG), which inhibits the activity of multiple αKG-dependent dioxygenases, and results in alterations in cell differentiation, survival, and extracellular matrix maturation6, 7, 8, 9, 10. However, the molecular pathways by which IDH mutations lead to tumour formation remain unclear. Here we show that mutant IDH blocks liver progenitor cells from undergoing hepatocyte differentiation through the production of 2HG and suppression of HNF-4α, a master regulator of hepatocyte identity and quiescence. Correspondingly, genetically engineered mouse models expressing mutant IDH in the adult liver show an aberrant response to hepatic injury, characterized by HNF-4α silencing, impaired hepatocyte differentiation, and markedly elevated levels of cell proliferation. Moreover, IDH and Kras mutations, genetic alterations that co-exist in a subset of human IHCCs4, 5, cooperate to drive the expansion of liver progenitor cells, development of premalignant biliary lesions, and progression to metastatic IHCC. These studies provide a functional link between IDH mutations, hepatic cell fate, and IHCC pathogenesis, and present a novel genetically engineered mouse model of IDH-driven malignancy

Anti-hyperglycemic and anti-hyperlipidaemic effect of Arjunarishta in high-fat fed animals

Background: Arjunarishta (AA), a formulation used as cardiotonic is a hydroalcoholic formulation of Terminalia arjuna (Roxb.) Wight and Arn. (TA) belonging to family Combretaceae. Objective: To evaluate the anti-hyperglycemic and anti-hyperlipidemic effect of Arjunarishta on high-fat diet fed animals. Materials and methods: High-fat diet fed (HFD) Wistar rats were randomly divided into three groups and treated with phytochemically standardized Arjunarishta (1.8 ml/kg), and hydroalcoholic extract of T. arjuna (TAHA) (250 mg/kg) and rosuvastatin (10 mg/kg), for 3 months. Intraperitoneal glucose tolerance test, blood biochemistry, liver triglyceride and systolic blood pressure were performed in all the groups. Effect of these drugs on the expression of tumor necrosis factor-α (TNF-α) and insulin receptor substrate-1 (IRS-1) and peroxisome proliferators activated receptor γ coactivator 1-α (PGC-1α) were studied in liver tissue using Quantitative Real-time PCR. Results: HFD increased fasting blood glucose, liver triglyceride, systolic blood pressure and gene expression of TNF-α, IRS-1 and PGC-1α. Treatment of AA and TAHA significantly reduced fasting blood glucose, systolic blood pressure, total cholesterol and triglyceride levels. These treatments significantly decreased gene expression of TNF-α (2.4, 2.2 and 2.6 fold change); increased IRS-1 (2.8, 2.9 and 2.8 fold change) and PGC-1α (2.9, 3.7 and 3.3 fold change) as compared to untreated HFD. Conclusion: Anti-hyperglycemic, anti-hyperlipidemic effect of Arjunarishta may be mediated by decreased TNF-α and increased PGC-1α and IRS-1. Keywords: Rosuvastatin, Type 2 diabetes, Insulin sensitizer genes, Arjunarisht

Barriers to the Adoption of Blockchain Technology in Business Supply Chains: A Total Interpretive Structural Modelling (TISM) approach

Blockchain is an emerging technology with a wide array of potential applications. This technology, which underpins cryptocurrency, provides an immutable, decentralised, and transparent distributed database of digital assets for use by firms in supply chains. However, not all firms are appropriately suited to adopt blockchain in the existing supply chain primarily due to their lack of knowledge on the benefits of this technology. Using Total Interpretive Structural Modelling (TISM) and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC), this paper identifies the adoption barriers, examines the interrelationships between them to the adoption of blockchain technology, which has the potential to revolutionise supply chains. The TISM technique supports developing a contextual relationship based structural model to identify the influential barriers. MICMAC classifies the barriers in blockchain adoption based on their strength and dependence. The results of this research indicate that the lack of business awareness and familiarity with blockchain technology on what it can deliver for future supply chains, are the most influential barriers that impede blockchain adoption. These barriers hinder and impact businesses decision to establish a blockchain-enabled supply chain and that other barriers act as secondary and linked variables in the adoption process

Genetic diversity across natural populations of three montane plant species from the Western Ghats, India revealed by intersimple sequence repeats

We analysed genetic diversity across the natural populations of three montane plant species in the Western Ghats, India; Symplocos laurina, Gaultheria fragrantissima and Eurya nitida using intersimple sequence repeat (ISSR) markers. These markers revealed genetic diversity within the populations of these plants from Nilgiri and also between two populations of S. laurina from Nilgiri and Amboli. Genetic variation within and between populations was analysed using various parameters such as total heterozygosity (HT), heterozygosity within population (HS), diversity between populations (DST), coefficient of population differentiation (GST), genetic distance (D) and gene flow (Nm). Total heterozygosity (HT) was higher for S. laurina (0.238) than for G. fragrantissima (0.172) and E. nitida (0.182). Two populations of S. laurina, separated by > 1000 km, showed a high within-population variation (53.7%) and a low gene flow (Nm = 0.447). upgma phenograms depicted a tendency of accessions to group according to their geographical locations in all the three plant species. The insight gained into the genetic structure of these plant populations might have implications in developing in situ and ex situ conservation strategies