Exploiting Non-Linearities in GDP Growth for Forecasting and Anticipating Regime Changes

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Efficient Likelihood Evaluation of State-Space Representations

We develop a numerical procedure that facilitates efficient likelihood evaluation in applications involving non-linear and non-Gaussian state-space models. The procedure employs continuous approximations of filtering densities, and delivers unconditionally optimal global approximations of targeted integrands to achieve likelihood approximation. Optimized approximations of targeted integrands are constructed via efficient importance sampling. Resulting likelihood approximations are continuous functions of model parameters, greatly enhancing parameter estimation. We illustrate our procedure in applications to dynamic stochastic general equilibrium models.Adaption, dynamic stochastic general equilibrium model, efficient importance sampling, kernel density approximation, particle filter.

Secreted Frizzled-Related Protein 4 expression is positively associated with responsiveness to Cisplatin of ovarian cancer cell lines in vitro and with lower tumour grade in mucinous ovarian cancers

Ovarian cancer is one of the most lethal malignancies in women, as it is frequently detected at an advanced stage, and cancers often become refractory to chemotherapy. Evidence suggests that dysregulation of pro-apoptotic genes plays a key role in the onset of chemoresistance. The secreted Frizzled-Related Protein (sFRP) family is pro-apoptotic and also a negative modulator of the Wnt signalling cascade. Studies have demonstrated that the re-expression of sFRPs, in particular sFRP4, is associated with a better prognosis, and that experimentally induced expression results in cell death

Impact of perioperative period on disease-free survival among carcinoma ovary patients treated with the interval cyto-reductive surgery at a tertiary cancer centre in Kerala, India: a retrospective study

Background: Global incidence of ovarian malignancies is 300,000 as per GLOBOCAN 2018. The treatment protocol for advanced ovarian malignancies (stage IIIc and stage IV) includes neo-adjuvant chemotherapy and surgery followed by adjuvant chemotherapy. Aims of the study was to determine the effect of duration of chemo interruption on disease free survival of ovarian malignancies treated by interval cytoreduction followed by surgery.Methods: A total 48 patients were studied for events such as recurrence, death, patient’s status on last follow up, peri-operative period between 3rd cycle of chemo therapy and 4th cycle of chemo therapy. Based on the median duration of peri operative period patients was classified as early or delayed receivers of adjuvant chemo therapy. Difference in duration of over-all survival and disease-free survival was analysed through Kaplan Meier survival analysis using log-rank test. Hazard ratio adjusted for background characteristics such as staging, performance status, grade of tumour were analysed using cox proportional hazard model.Results: The two peri operative period categories based on mean value (85 days) didn’t show any significant association to disease free interval (minimum-21days, maximum-146 days, Hr = 1.3, p-value = 0.52). Other established factors like stage, extent of resection, response to chemotherapy, also didn’t show any significant association. Serum marker level showed a significant negative correlation with disease free survival (minimum-9 days, maximum-30659, p-value =.04, Hr = 3.19).Conclusions: The study could not establish any correlation between peri operative period and median disease-free survival. The small sample size is a limiting factor, well controlled randomized trials may needed for further clarification

Stemness, Pluripotentiality, and Wnt Antagonism: sFRP4, a Wnt antagonist Mediates Pluripotency and Stemness in Glioblastoma

Background: Chemotherapeutic resistance of glioblastoma has been attributed to a self-renewing subpopulation, the glioma stem cells (GSCs), which is known to be maintained by the Wnt β−catenin pathway. Our previous findings demonstrated that exogeneous addition of the Wnt antagonist, secreted fizzled-related protein 4 (sFRP4) hampered stem cell properties in GSCs. Methods: To understand the molecular mechanism of sFRP4, we overexpressed sFRP4 (sFRP4 OE) in three human glioblastoma cell lines U87MG, U138MG, and U373MG. We also performed chromatin immunoprecipitation (ChIP) sequencing of sFRP4 OE and RNA sequencing of sFRP4 OE and sFRP4 knocked down U87 cells. Results: We observed nuclear localization of sFRP4, suggesting an unknown nuclear role. ChIP-sequencing of sFRP4 pulldown DNA revealed a homeobox Cphx1, related to the senescence regulator ETS proto-oncogene 2 (ETS2). Furthermore, miRNA885, a p53-mediated apoptosis inducer, was upregulated in sFRP4 OE cells. RNA sequencing analysis suggested that sFRP4-mediated apoptosis is via the Fas-p53 pathway by activating the Wnt calcium and reactive oxygen species pathways. Interestingly, sFRP4 OE cells had decreased stemness, but when knocked down in multipotent mesenchymal stem cells, pluripotentiality was induced and the Wnt β-catenin pathway was upregulated. Conclusions: This study unveils a novel nuclear role for sFRP4 to promote apoptosis by a possible activation of DNA damage machinery in glioblastoma

A framework for feature extraction from hospital medical data with applications in risk prediction

Background: Feature engineering is a time consuming component of predictive modeling. We propose a versatile platform to automatically extract features for risk prediction, based on a pre-defined and extensible entity schema. The extraction is independent of disease type or risk prediction task. We contrast auto-extracted features to baselines generated from the Elixhauser comorbidities. Results: Hospital medical records was transformed to event sequences, to which filters were applied to extract feature sets capturing diversity in temporal scales and data types. The features were evaluated on a readmission prediction task, comparing with baseline feature sets generated from the Elixhauser comorbidities. The prediction model was through logistic regression with elastic net regularization. Predictions horizons of 1, 2, 3, 6, 12 months were considered for four diverse diseases: diabetes, COPD, mental disorders and pneumonia, with derivation and validation cohorts defined on non-overlapping data-collection periods. For unplanned readmissions, auto-extracted feature set using socio-demographic information and medical records, outperformed baselines derived from the socio-demographic information and Elixhauser comorbidities, over 20 settings (5 prediction horizons over 4 diseases). In particular over 30-day prediction, the AUCs are: COPD-baseline: 0.60 (95% CI: 0.57, 0.63), auto-extracted: 0.67 (0.64, 0.70); diabetes-baseline: 0.60 (0.58, 0.63), auto-extracted: 0.67 (0.64, 0.69); mental disorders-baseline: 0.57 (0.54, 0.60), auto-extracted: 0.69 (0.64,0.70); pneumonia-baseline: 0.61 (0.59, 0.63), auto-extracted: 0.70 (0.67, 0.72). Conclusions: The advantages of auto-extracted standard features from complex medical records, in a disease and task agnostic manner were demonstrated. Auto-extracted features have good predictive power over multiple time horizons. Such feature sets have potential to form the foundation of complex automated analytic tasks

Epigenetic regulation of the secreted frizzled-related protein family in human glioblastoma multiforme

Glioblastoma multiforme (GBM) are intracranial tumors of the central nervous system and the most lethal among solid tumors. Current therapy is palliative and is limited to surgical resection followed by radiation therapy and temozolomide treatment. Aberrant WNT pathway activation mediates not only cancer cell proliferation but also promotes radiation and chemotherapeutic resistance. WNT antagonists such as the secreted frizzled-related protein (sFRP) family have an ability to sensitize glioma cells to chemotherapeutics, decrease proliferation rate and induce apoptosis. During tumor development, sFRP genes (1–5) are frequently hypermethylated, causing transcriptional silencing. We investigated a possible involvement of methylation-mediated silencing of the sFRP gene family in human GBM using four human glioblastoma cell lines (U87, U138, A172 and LN18). To induce demethylation of the DNA, we inhibited DNA methyltransferases through treatment with 5-azacytidine. Genomic DNA, RNA and total protein were isolated from GBM cells before and after treatment. We utilized bisulfite modification of genomic DNA to examine the methylation status of the respective sFRP promoter regions. Pharmacological demethylation of the GBM cell lines demonstrated a loss of methylation in sFRP promoter regions, as well as an increase in sFRP gene-specific mRNA abundance. Western blot analysis demonstrated an increased protein expression of sFRP-4 and increased levels of phosphorylated-ß-catenin. These data indicate an important role of methylation-induced gene silencing of the sFRP gene family in human GBM