Operational Currency Mismatch and Firm Level Performance: Evidence from India

This paper looks at the determinants and effects of exchange rate exposure using data on 500 Indian firms over the period 1995-2011. Unlike the existing papers in the literature, we use a measure of `operational` currency exposure based on foreign currency revenues and costs of firms. Among other factors, exchange rate volatility appears as a significant determinant of average firm level exposure with the direction of relationship supporting the presence of `Moral Hazard` in firm’s risk taking behavior. Further large `operational` exposure is associated with significantly lower output growth, profitability and capital expenditure during episodes of large currency depreciation at the firm level. Together this indicates that the policy makers must take into account the incentive effects of their intervention in foreign exchange markets.

Foreign Reserve Adequacy in Sub-Saharan Africa.

This paper looks at the question of adequacy of reserves in sub-Saharan African countries in light of the shocks faced by these countries. Literature on optimal reserves so far has not paid attention to the particular shocks facing low-income countries. We use a two-good endowment economy model facing terms of trade and aid shocks to derive the optimal level of reserves by comparing the cost of holding reserves with their benefits as an insurance against a shock. We find that the optimal level of reserves depends upon the size of these shocks, their probability, and the output cost associated with them.

The role of the Schwann cell in the induction of elongative central axonal growth

The factors underlying the failure of axon regeneration in the CNS are thought to comprise of both the lack of supportive factors as well as the presence of inhibitory ones. Transplantation work has shown that the PNS is able to provide some of the necessary criteria and with it an increased capacity to regenerate. Studies have further shown that the crucial ingredient to such peripheral grafts is the presence of Schwann cells (SCs), the major glial cell of the PNS. I have used an extrusion transplantation system, recently developed in this laboratory, to study the effects of a SC column placed into the origin of the septo-hippocampal cholinergic projection. These SC columns integrate with host glia with minimal tissue damage, form a tight and ordered column with aligned cellular processes, and are able to recruit modest numbers of axons. Immunostaining with a cholinergic axon marker suggests that these axons arise from the septal nuclei. Given the limited availability and yield of primary SCs that current preparation protocols offer, I have engineered neonatal SC lines by transfecting the SV40 large T antigen into a population of primary neonatal rat SCs. Characterisation of these cell lines, with the use of immunocytochemistry, Western blotting and RT-PCR, shows that they retain the immunophenotype of primary SCs in vitro, although in vivo studies have posed more difficult with the lack of a suitable marker. In addition, I have set up a retroviral transfection system with the use of a bicistronic vector containing the Green Fluorescent Protein. This would provide a means of unique and efficient labelling prior to transplantation, and moreover offer the potential for further transfections of an additional gene of interest within the same vector

Radiation Therapy in Metastatic Neuroblastoma

Neuroblastoma is the commonest extracranial solid tumor in children, and metastasis at presentation is seen in more than 50% of cases. The role of radiotherapy as a palliative modality in patients with advanced neuroblastoma provides better symptomatic relief. Palliative radiotherapy dose schedules can be given either in single hypofractionation from 4 to 8 Gy or fractionated radiotherapy that can range from 21 to 30.6 Gy. Dose-response relationship trend has been reported in the palliative setting of bone metastasis. Because of the proximity of tumor to critical organs, serious adverse effects can be avoided with conformal techniques. Although currently there is limited data available, new treatments with particle therapies are undergoing clinical evaluation and may offer new hope for good quality of life in these patients

Group Decision Diagrams (GDDs): A Data Structure for Mathematical Groups

Groups are an element of abstract algebra that are used in a number of different domains such as physics, chemistry, statistics and cryptography. Set operations like union, intersection and cartesian product on groups are fundamental to more complex algorithms and methods of analysis in the aforementioned fields. A concise representation of groups can help improve the speed and ease at which binary operations like taking union and intersection can be carried out on them. In abstract algebra, a group is an infinite or finite set of elements that satisfies the axioms of closure, associativity, inverse and identity. For the purpose of this project we will only consider finite abelian group. If the group operation is commutative over a group it is called an abelian group. According to the fundamental theorem of finitely-generated abelian groups, a finite abelian group has a unique decomposition that allows it to be expressed as the direct product of cyclic groups. Further, cyclic groups can be described using a single element that generates the group. The existence of a unique decomposition for finite abelian groups makes it ideal to use a decision tree for its representation. A decision tree is a data structure where each parent node represents a decision and each child node is one of the outcomes. Our decision tree for groups can have each node be the generator representing a cyclic group from its decomposition. This data structure is based on the prior work of Shin-ichi Minato on permutation decision diagrams, that is, binary decision tree for storing sets of permutations, and subsequent work we did last summer. The decision diagram for a set of permutations is a decision tree with each node representing elemental transpositions obtained using a decomposition algorithm where if a permutation has an accepting path through the diagram, it is a member of the set. This project models a similar data structure for storing groups which will allow set operations to be carried out with relative efficiency on them just like it did for large sets of permutations using Python. We also conducted time analysis on the operations and found that multiplying two groups together takes the most amount of time using our data structure, followed by the transpose function which swaps all two indexes of every permutation in the data structure. Overall we found that our data structure is considerably effective in taking intersections and unions of group. However, some work needs to be done for a more effective implementation of multip[ly and transpose operations

Developing an assay for easy and rapid detection of ALS biomarker(s): A Hypothesis

Background: Death of motor neurons is the key pathology underlying neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS). Biomarkers are chemical changes in the biological fluids. Biomarkers serving as a diagnostic tool should be specific to the concerned disease. Biomarkers indicating disease progression should be very sensitive to demonstrate changes during the disease process as well as therapeutics development. Biomarkers proposed for ALS include poly (GP) repeats in C9orf72, neurofilaments, miRNAs, glutathione and 4HNE in CSF, SOD1/TDP43 protein, poly (GP) repeats in C9orf72, neurofilaments, T regulatory cells, CRP, chitotriosidase, creatinine, creatinine kinase, miRNAs, glutamate, albumin, uric acid, glutathione, ferritin, 3-nitrotyrosine and 4HNE in blood, p75ECD, F2-isoprostane, collagen type 4, lucosylgalactosyl hydroxylysine, neoptrin and 8hydroxy-2`-deoxyguanosine in urine. Our hypothesis is to develop a kit-based assay for detection of ALS. Lateral flow immunoassays are one of the rapid, point-of-care diagnostic tests enabling high sensitivity and multiplexing. Methods: Leftover biological samples of ALS/Non-ALS individuals can be obtained from the clinics, age group 40-90. The samples can be evaluated for the expression of biomarkers and the levels can be compared between ALS and Non-ALS individuals. Using this preliminary data, kit-based assay can be developed that might be based on lateral flow principle. Result: The assay developed should be chromogenic and the intensity of chromogen should indicate the disease severity when compared to the reference. Conclusion: Development of a successful kit-based assay will enable its rapid and easy detection and establish a new milestone in the field of ALS

Systems Network Analysis of Protein Interaction Network (PIN) for deducing molecular mechanistic action of BaP induced carcinogenesis

Background: Benzo[a]pyrene (BaP), a polycyclic aromatic hydrocarbon, has been placed in group 1 by IARC which indicates that it is a potential carcinogen to human beings. It has shown tumorigenic properties in approximately all animal model systems. In the current study, we have tried to identify the most probable biomolecular targets of BaP using systems biology approach. Method: All the proteins that interact with BaP were extracted from T3DB. STRING-db was used to generate the Protein- protein interaction network (PPIN). Various apps of cytoscape software were used for network analysis, modulation and GO enrichment analysis. By developing biokinetic models, we then tried to find the impact of BaP on the top three most probable biomolecular targets and how whole of the cell cycle is getting perturbed which may ultimately lead to carcinogenesis. Apart from this, in this study we have also tried to propose a hypothesis of removing BaP from the cell vicinity by exploiting the scavenging properties of carbon based nanoparticles using in silico approach. Result: 4000 genes were extracted from T3DB for which network was generated. On network analysis, 2058 nodes were obtained that were connected by 13850 edges. MCODE created 65 clusters which had 411 seed proteins and enrichment analysis showed that most of the proteins present in the network participate in cell cycle regulatory pathways. On molecular docking analysis QSOX1, PTGS2 and NOS2 emerged out to be top three most probable biomolecular targets of BaP out of which PTGS2 is directly involved in cell cycle regulatory pathways. Biomolecular kinetics showed that when PTGS2 gets hampered by BaP, cell cycle regulation gets disturbed and cell may become cancerous. On in silico analysis of the scavenging potential of carbon based nanoparticles, BaP showed higher binding efficiencies for SWCNT and MWCNT as compared with QSOX1. Conclusion: Based on the in silico docking results we can hypothesize that carbon based nanoparticles can be used to scavenge BaP molecules from the cell vicinity