Identifying the Predictors for Financial Crisis Using Gibbs Sampler

The Asian financial crisis broke out in Thailand in July 1997, and rapidly spread throughout the neighboring countries. An important question then arises? Is it possible to predict next financial crisis? If yes, then what are the predictors? The answer lies in combined usage of economic theory and econometric methods. By using the economic theory, one can locate possible potential crisis predictors whereas appropriate econometric models can pinpoint effective ones. In this paper we suggest using the Stochastic Search Variable Selection (SSVS) developed by George and McCulloch (1993) to identify the crisis predictors. As is suggested by the name, SSVS stochastically searches for practically significant variables. Each variable coefficient is assumed to come from a mixture of two normal variates with respectively large and small variances. For the former case, this variable is considered as insignificant and should be excluded from the model whereas for the latter, this variable is significant and should be included in the model. SSVS is not affected by the ordering of the candidate variables and is particularly effective when the sample size is much smaller than the number of all possible models. By employing SSVS method, we conclude that annual growth rate of money supply, $M_2$, and the ratio of government debt to GDP are promising predictors for financial crisis. It is worth mentioning that the frequently mentioned factors, such as ratio of total foreign reserve to GDP and the ratio of current deficit to GDP are not selected by our analysis. Our empirical analysis implies that monetary and fiscal policy play a crucial role in exploring the Asian financial crisis.early warning

Identifying the Predictors for Financial Crisis Using Gibbs Sampler

The Asian financial crisis broke out in Thailand in July 1997, and rapidly spread throughout the neighboring countries. An important question then arises? Is it possible to predict next financial crisis? If yes, then what are the predictors? The answer lies in combined usage of economic theory and econometric methods. By using the economic theory, one can locate possible potential crisis predictors whereas appropriate econometric models can pinpoint effective ones. In this paper we suggest using the Stochastic Search Variable Selection (SSVS) developed by George and McCulloch (1993) to identify the crisis predictors. As is suggested by the name, SSVS stochastically searches for practically significant variables. Each variable coefficient is assumed to come from a mixture of two normal variates with respectively large and small variances. For the former case, this variable is considered as insignificant and should be excluded from the model whereas for the latter, this variable is significant and should be included in the model. SSVS is not affected by the ordering of the candidate variables and is particularly effective when the sample size is much smaller than the number of all possible models. By employing SSVS method, we conclude that annual growth rate of money supply, $M_2$, and the ratio of government debt to GDP are promising predictors for financial crisis. It is worth mentioning that the frequently mentioned factors, such as ratio of total foreign reserve to GDP and the ratio of current deficit to GDP are not selected by our analysis. Our empirical analysis implies that monetary and fiscal policy play a crucial role in exploring the Asian financial crisis.Financial crisis, early warning

Liquid biopsy genotyping in lung cancer: ready for clinical utility?

Liquid biopsy is a blood test that detects evidence of cancer cells or tumor DNA in the circulation. Despite complicated collection methods and the requirement for technique-dependent platforms, it has generated substantial interest due, in part, to its potential to detect driver oncogenes such as epidermal growth factor receptor (EGFR) mutants in lung cancer. This technology is advancing rapidly and is being incorporated into numerous EGFR tyrosine kinase inhibitor (EGFR-TKI) development programs. It appears ready for integration into clinical care. Recent studies have demonstrated that biological fluids such as saliva and urine can also be used for detecting EGFR mutant DNA through application other user-friendly techniques. This review focuses on the clinical application of liquid biopsies to lung cancer genotyping, including EGFR and other targets of genotype-directed therapy and compares multiple platforms used for liquid biopsy

Mechanisms of Visible Light Photocatalysis in N-Doped Anatase TiO2 with Oxygen Vacancies from GGA+U Calculations

We have systematically studied the photocatalytic mechanisms of nitrogen doping in anatase TiO2 using first-principles calculations based on density functional theory, employing Hubbard U (8.47 eV) on-site correction. The impurity formation energy, charge density, and electronic structure properties of TiO2 supercells containing substitutional nitrogen, interstitial nitrogen, or oxygen vacancies were evaluated to clarify the mechanisms under visible light. According to the formation energy, a substitutional N atom is better formed than an interstitial N atom, and the formation of an oxygen vacancy in N-doped TiO2 is easier than that in pure TiO2. The calculated results have shown that a significant band gap narrowing may only occur in heavy nitrogen doping. With light nitrogen doping, the photocatalysis under visible light relies on N-isolated impurity states. Oxygen vacancies existence in N-doped TiO2 can improve the photocatalysis in visible light because of a band gap narrowing and n-type donor states. These findings provide a reasonable explanation of the mechanisms of visible light photocatalysis in N-doped TiO2

The Emergent Landscape of Detecting EGFR Mutations Using Circulating Tumor DNA in Lung Cancer.

The advances in targeted therapies for lung cancer are based on the evaluation of specific gene mutations especially the epidermal growth factor receptor (EGFR). The assays largely depend on the acquisition of tumor tissue via biopsy before the initiation of therapy or after the onset of acquired resistance. However, the limitations of tissue biopsy including tumor heterogeneity and insufficient tissues for molecular testing are impotent clinical obstacles for mutation analysis and lung cancer treatment. Due to the invasive procedure of tissue biopsy and the progressive development of drug-resistant EGFR mutations, the effective initial detection and continuous monitoring of EGFR mutations are still unmet requirements. Circulating tumor DNA (ctDNA) detection is a promising biomarker for noninvasive assessment of cancer burden. Recent advancement of sensitive techniques in detecting EGFR mutations using ctDNA enables a broad range of clinical applications, including early detection of disease, prediction of treatment responses, and disease progression. This review not only introduces the biology and clinical implementations of ctDNA but also includes the updating information of recent advancement of techniques for detecting EGFR mutation using ctDNA in lung cancer

Induction of HSPA4 and HSPA14 by NBS1 overexpression contributes to NBS1-induced in vitro metastatic and transformation activity

<p>Abstract</p> <p>Background</p> <p>Nijmegen breakage syndrome (NBS) is a chromosomal-instability syndrome associated with cancer predisposition, radiosensitivity, microcephaly, and growth retardation. The NBS gene product, NBS1 (p95) or nibrin, is a part of the MRN complex, a central player associated with double-strand break (DSB) repair. We previously demonstrated that NBS1 overexpression contributes to transformation through the activation of PI 3-kinase/Akt. NBS1 overexpression also induces epithelial-mesenchymal transition through the Snail/MMP2 pathway.</p> <p>Methods</p> <p>RT-PCR, Western blot analysis, <it>in vitro </it>migration/invasion, soft agar colony formation, and gelatin zymography assays were performed.</p> <p>Results</p> <p>Here we show that heat shock protein family members, A4 and A14, were induced by NBS1 overexpression. siRNA mediated knockdown of HSPA4 or HSPA14 decreased the <it>in vitro </it>migration, invasion, and transformation activity in H1299 cells overexpressing NBS1. However, HSPA4 or HSPA14 induced activity was not mediated through MMP2. NBS1 overexpression induced the expression of heat shock transcription factor 4b (HSF4b), which correlated with the expression of HSPA4 and HSPA14.</p> <p>Conclusion</p> <p>These results identify a novel pathway (NBS1-HSF4b-HSPA4/HSPA14 axis) to induce migration, invasion, and transformation, suggesting the activation of multiple signaling events induced by NBS1 overexpression.</p