Quantum Algorithms for Solving Ordinary Differential Equations via Classical Integration Methods

Identifying computational tasks suitable for (future) quantum computers is an active field of research. Here we explore utilizing quantum computers for the purpose of solving differential equations. We consider two approaches: (i) basis encoding and fixed-point arithmetic on a digital quantum computer, and (ii) representing and solving high-order Runge-Kutta methods as optimization problems on quantum annealers. As realizations applied to two-dimensional linear ordinary differential equations, we devise and simulate corresponding digital quantum circuits, and implement and run a 6$^{\mathrm{th}}$ order Gauss-Legendre collocation method on a D-Wave 2000Q system, showing good agreement with the reference solution. We find that the quantum annealing approach exhibits the largest potential for high-order implicit integration methods. As promising future scenario, the digital arithmetic method could be employed as an "oracle" within quantum search algorithms for inverse problems

Genetic Markers of Toxicity From Capecitabine and Other Fluorouracil-Based Regimens: Investigation in the QUASAR2 Study, Systematic Review, and Meta-Analysis

Fluourouracil (FU) is a mainstay of chemotherapy, although toxicities are common. Genetic biomarkers have been used to predict these adverse events, but their utility is uncertain

Acute Muscular Sarcocystosis: An International Investigation Among Ill Travelers Returning From Tioman Island, Malaysia, 2011-2012

A large outbreak of acute muscular sarcocystosis (AMS) among international tourists who visited Tioman Island, Malaysia, is described. Clinicians evaluating travelers returning ill from Malaysia with myalgia, with or without fever, should consider AMS in their differential diagnosi

Targeting Nuclear Receptors with Lentivirus-Delivered Small RNAs in Primary Human Hepatocytes

Background: RNA interference (RNAi) has tremendous potential for investigating gene function and for developing new therapies. Primary human hepatocytes (PHH) are the “gold standard” for studying the regulation of hepatic metabolism in vitro. However, application of RNAi in PHH has some technical hurdles. The objective of this study was to develop effective and robust protocol for transduction of PHH with lentiviral vectors. Methods: We used lentiviral vectors to transduce PHH for introduction of short hairpin RNAs (shRNAs) targeting constitutive androstane receptor (CAR), peroxisome proliferator activated receptor alpha (PPARα), and microRNA, miR-143. Infection efficiency was quantitatively analyzed by flow cytometry and microscopy. Target gene expression was assessed using quantitative real-time (qRT-PCR) method. Results: Lentiviral vector transduction resulted in ≥95% of infected cells at low multiplicity of infection (MOI) of 3, which did not impair cellular viability. We demonstrated the feasibility of this technique in studies on targeting nuclear receptors, PPARα and CAR, with shRNAs as well as in lentivirus-mediated overexpression and knock-down of miRNA-143 experiments. Conclusions: We developed an efficient and robust protocol with standardized procedures for virus production, method of titer determination, and infection procedure for RNAi in primary human hepatocytes based on delivery of shRNAs, microRNAs or anti-microRNAs in different laboratory settings. This approach should be useful to study not only the regulation via nuclear receptors but also other biological, pharmacological, and toxicological aspects of drug metabolism