Continuous-time Mean-Variance Portfolio Selection with Stochastic Parameters

This paper studies a continuous-time market {under stochastic environment} where an agent, having specified an investment horizon and a target terminal mean return, seeks to minimize the variance of the return with multiple stocks and a bond. In the considered model firstly proposed by [3], the mean returns of individual assets are explicitly affected by underlying Gaussian economic factors. Using past and present information of the asset prices, a partial-information stochastic optimal control problem with random coefficients is formulated. Here, the partial information is due to the fact that the economic factors can not be directly observed. Via dynamic programming theory, the optimal portfolio strategy can be constructed by solving a deterministic forward Riccati-type ordinary differential equation and two linear deterministic backward ordinary differential equations

Causal relationships between COVID-19 and osteoporosis: a two-sample Mendelian randomization study in European population

IntroductionThe causal relationship between Coronavirus disease 2019 (COVID-19) and osteoporosis (OP) remains uncertain. We aimed to assess the effect of COVID-19 severity (severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, COVID-19 hospitalization, and severe COVID-19) on OP by a two-sample Mendelian randomization (MR) study.MethodsWe conducted a two-sample MR analysis using publicly available genome-wide association study (GWAS) data. Inverse variance weighting (IVW) was used as the main analysis method. Four complementary methods were used for our MR analysis, which included the MR–Egger regression method, the weighted median method, the simple mode method, and the weighted mode method. We utilized the MR-Egger intercept test and MR pleiotropy residual sum and outlier (MR-PRESSO) global test to identify the presence of horizontal pleiotropy. Cochran’s Q statistics were employed to assess the existence of instrument heterogeneity. We conducted a sensitivity analysis using the leave-one-out method.ResultsThe primary results of IVW showed that COVID-19 severity was not statistically related to OP (SARS-CoV-2 infection: OR (95% CI) = 0.998 (0.995 ~ 1.001), p = 0.201403; COVID-19 hospitalization: OR (95% CI) =1.001 (0.999 ~ 1.003), p = 0.504735; severe COVID-19: OR (95% CI) = 1.000 (0.998 ~ 1.001), p = 0.965383). In addition, the MR-Egger regression, weighted median, simple mode and weighted mode methods showed consistent results. The results were robust under all sensitivity analyses.ConclusionThe results of the MR analysis provide preliminary evidence that a genetic causal link between the severity of COVID-19 and OP may be absent

Inhibition of Proliferation and Induction of Apoptosis in Multiple Myeloma Cell Lines by CD137 Ligand Signaling

BACKGROUND: Multiple myeloma (MM) is a malignancy of terminally-differentiated plasma cells, and the second most prevalent blood cancer. At present there is no cure for MM, and the average prognosis is only three to five years. Current treatments such as chemotherapy are able to prolong a patient's life but rarely prevent relapse of the disease. Even hematopoietic stem cell transplants and novel drug combinations are often not curative, underscoring the need for a continued search for novel therapeutics. CD137 and its ligand are members of the Tumor Necrosis Factor (TNF) receptor and TNF superfamilies, respectively. Since CD137 ligand cross-linking enhances proliferation and survival of healthy B cells we hypothesized that it would also act as a growth stimulus for B cell cancers. METHODOLOGY/PRINCIPAL FINDINGS: Proliferation and survival of B cell lymphoma cell lines were not affected or slightly enhanced by CD137 ligand agonists in vitro. But surprisingly, they had the opposite effects on MM cells, where CD137 ligand signals inhibited proliferation and induced cell death by apoptosis. Furthermore, secretion of the pro-inflammatory cytokines, IL-6 and IL-8 were also enhanced in MM but not in non-MM cell lines in response to CD137 ligand agonists. The secretion of these cytokines in response to CD137 ligand signaling was consistent with the observed activation of the classical NF-kappaB pathway. We hypothesize that the induction of this pathway results in activation-induced cell death, and that this is the underlying mechanism of CD137-induced MM cell death and growth arrest. CONCLUSIONS/SIGNIFICANCE: These data point to a hitherto unrecognized role of CD137 and CD137 ligand in MM cell biology. The selective inhibition of proliferation and induction of cell death in MM cells by CD137 ligand agonists may also warrant a closer evaluation of their therapeutic potential

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Modelling ordinal categorical data : A Gibbs sampler approach

This thesis presents a study of statistical models for ordered categorical data. The generalized linear model plays an essential role in this approach. A Gibbs sampler method is used to estimate model parameters for a Bayesian formulation of a random effects generalized linear model. The adaptive rejection sampling (ARS) method introduced by Gilks and Wild (1992) is used in the Gibbs sampling scheme. Good resulted are obtained in simulations and we applied this model to analyze data concerning telephone connection quality supplied by British Telecom (BT). The concept of latent residuals introduced by Albert and Chib (1995) is used for diagnostic checking.A random effects cumulative logit model is employed to analyze longitudinal ordinal responses and a Bayesian approach to the cumulative logit model is considered. The adaptive rejection sampling (ARS) technique is again used to estimate model parameters. Simulation results as well as results from a real application are presented. A new cumulative logit model is developed to cater for a particular set of ordinal categorical data. The main reason is that in the telephone connection quality experiment, each subject has his/her personal scale in mind. At the same time, the underlying stochastic ordering structure needs to be maintained for the model. This model is used to model the telephone connection quality data. A continuation-ratio model and cumulative probit model with serial correlation are also considered.</p

Time series analysis of meteorological data: wind speed and direction

tocabstractpublished_or_final_versionStatisticsMasterMaster of Philosoph