Portfolio Optimization with Digitized-Counterdiabatic Quantum Algorithms

We consider digitized-counterdiabatic quantum computing as an advanced paradigm to approach quantum advantage for industrial applications in the NISQ era. We apply this concept to investigate a discrete mean-variance portfolio optimization problem, showing its usefulness in a key finance application. Our analysis shows a drastic improvement in the success probabilities of the resulting digital quantum algorithm when approximate counterdiabatic techniques are introduced. Along these lines, we discuss the enhanced performance of our methods over variational quantum algorithms like QAOA and DC-QAOA.Comment: 8 pages, 4 figure

AUTOLOGOUS OSTEOCHONDRAL GRAFTING FOR OSTEOCHONDRITIS DESSICANS A CASE REPORT

Osteochondral defects are common injuries among the young population. Athletes are more prone to these injuries given the amount the stress and strain they put on their lower limbs. The viscoelastic nature of cartilage, which allows load bearing, is disrupted. Early recognition and treatment is needed to prevent Early Osteoarthritis. We are presenting one such case, where a 25 year old male patient with Grade 4 OCD was treated with Autologous osteochondral graft taken from the Non weight bearing part of the femur

AUTOLOGOUS OSTEOCHONDRAL GRAFTING FOR OSTEOCHONDRITIS DESSICANS A CASE REPORT

Osteochondral defects are common injuries among the young population. Athletes are more prone to these injuries given the amount the stress and strain they put on their lower limbs. The viscoelastic nature of cartilage, which allows load bearing, is disrupted. Early recognition and treatment is needed to prevent Early Osteoarthritis. We are presenting one such case, where a 25 year old male patient with Grade 4 OCD was treated with Autologous osteochondral graft taken from the Non weight bearing part of the femur

Differential Pre-mRNA Splicing Regulates Nnat Isoforms in the Hypothalamus after Gastric Bypass Surgery in Mice

Background Neuronatin (NNAT) is an endoplasmic reticulum proteolipid implicated in intracellular signalling. Nnat is highly-expressed in the hypothalamus, where it is acutely regulated by nutrients and leptin. Nnat pre-mRNA is differentially spliced to create Nnat-α and -β isoforms. Genetic variation of NNAT is associated with severe obesity. Currently, little is known about the long-term regulation of Nnat. Methods Expression of Nnat isoforms were examined in the hypothalamus of mice in response to acute fast/feed, chronic caloric restriction, diet-induced obesity and modified gastric bypass surgery. Nnat expression was assessed in the central nervous system and gastrointestinal tissues. RTqPCR was used to determine isoform-specific expression of Nnat mRNA. Results Hypothalamic expression of both Nnat isoforms was comparably decreased by overnight and 24-h fasting. Nnat expression was unaltered in diet-induced obesity, or subsequent switch to a calorie restricted diet. Nnat isoforms showed differential expression in the hypothalamus but not brainstem after bypass surgery. Hypothalamic Nnat-β expression was significantly reduced after bypass compared with sham surgery (P = 0.003), and was positively correlated with post-operative weight-loss (R2 = 0.38, P = 0.01). In contrast, Nnat-α expression was not suppressed after bypass surgery (P = 0.19), and expression did not correlate with reduction in weight after surgery (R2 = 0.06, P = 0.34). Hypothalamic expression of Nnat-β correlated weakly with circulating leptin, but neither isoform correlated with fasting gut hormone levels post- surgery. Nnat expression was detected in brainstem, brown-adipose tissue, stomach and small intestine. Conclusions Nnat expression in hypothalamus is regulated by short-term nutrient availability, but unaltered by diet-induced obesity or calorie restriction. While Nnat isoforms in the hypothalamus are co-ordinately regulated by acute nutrient supply, after modified gastric bypass surgery Nnat isoforms show differential expression. These results raise the possibility that in the radically altered nutrient and hormonal milieu created by bypass surgery, resultant differential splicing of Nnat pre-mRNA may contribute to weight-loss

FastMRI Prostate: A Publicly Available, Biparametric MRI Dataset to Advance Machine Learning for Prostate Cancer Imaging

The fastMRI brain and knee dataset has enabled significant advances in exploring reconstruction methods for improving speed and image quality for Magnetic Resonance Imaging (MRI) via novel, clinically relevant reconstruction approaches. In this study, we describe the April 2023 expansion of the fastMRI dataset to include biparametric prostate MRI data acquired on a clinical population. The dataset consists of raw k-space and reconstructed images for T2-weighted and diffusion-weighted sequences along with slice-level labels that indicate the presence and grade of prostate cancer. As has been the case with fastMRI, increasing accessibility to raw prostate MRI data will further facilitate research in MR image reconstruction and evaluation with the larger goal of improving the utility of MRI for prostate cancer detection and evaluation. The dataset is available at https://fastmri.med.nyu.edu.Comment: 4 pages, 1 figur

Digitized-counterdiabatic quantum approximate optimization algorithm

The quantum approximate optimization algorithm (QAOA) has proved to be an e ective classical-quantum algorithm serving multiple purposes, from solving combinatorial optimization problems to finding the ground state of many-body quantum systems. Since QAOA is an ansatz-dependent algorithm, there is always a need to design ansatz for better optimization. To this end, we propose a digitized version of QAOA enhanced via the use of shortcuts to adiabaticity. Specifically, we use a counterdiabatic (CD) driving term to design a better ansatz, along with the Hamiltonian and mixing terms, enhancing the global performance. We apply our digitizedcounterdiabatic QAOA to Ising models, classical optimization problems, and the P-spin model, demonstrating that it outperforms standard QAOA in all cases we study

Consensus report from the 8th International Forum for Liver Magnetic Resonance Imaging.

ObjectivesThe 8th International Forum for Liver Magnetic Resonance Imaging (MRI), held in Basel, Switzerland, in October 2017, brought together clinical and academic radiologists from around the world to discuss developments in and reach consensus on key issues in the field of gadoxetic acid-enhanced liver MRI since the previous Forum held in 2013.MethodsTwo main themes in liver MRI were considered in detail at the Forum: the use of gadoxetic acid for contrast-enhanced MRI in patients with liver cirrhosis and the technical performance of gadoxetic acid-enhanced liver MRI, both opportunities and challenges. This article summarises the expert presentations and the delegate voting on consensus statements discussed at the Forum.Results and conclusionsIt was concluded that gadoxetic acid-enhanced MRI has higher sensitivity for the diagnosis of hepatocellular carcinoma (HCC), when compared with multidetector CT, by utilising features of hyperenhancement in the arterial phase and hypointensity in the hepatobiliary phase (HBP). Recent HCC management guidelines recognise an increasing role for gadoxetic acid-enhanced MRI in early diagnosis and monitoring post-resection. Additional research is needed to define the role of HBP in predicting microvascular invasion, to better define washout during the transitional phase in gadoxetic acid-enhanced MRI for HCC diagnosis, and to reduce the artefacts encountered in the arterial phase. Technical developments are being directed to shortening the MRI protocol for reducing time and patient discomfort and toward utilising faster imaging and non-Cartesian free-breathing approaches that have the potential to improve multiphasic dynamic imaging.Key points• Gadoxetic acid-enhanced MRI provides higher diagnostic sensitivity than CT for diagnosing HCC. • Gadoxetic acid-enhanced MRI has roles in early-HCC diagnosis and monitoring post-resection response. • Faster imaging and free-breathing approaches have potential to improve multiphasic dynamic imaging

Metabolic state alters economic decision making under risk in humans

Background: Animals' attitudes to risk are profoundly influenced by metabolic state (hunger and baseline energy stores). Specifically, animals often express a preference for risky (more variable) food sources when below a metabolic reference point (hungry), and safe (less variable) food sources when sated. Circulating hormones report the status of energy reserves and acute nutrient intake to widespread targets in the central nervous system that regulate feeding behaviour, including brain regions strongly implicated in risk and reward based decision-making in humans. Despite this, physiological influences per se have not been considered previously to influence economic decisions in humans. We hypothesised that baseline metabolic reserves and alterations in metabolic state would systematically modulate decision-making and financial risk-taking in humans. Methodology/Principal Findings: We used a controlled feeding manipulation and assayed decision-making preferences across different metabolic states following a meal. To elicit risk-preference, we presented a sequence of 200 paired lotteries, subjects' task being to select their preferred option from each pair. We also measured prandial suppression of circulating acyl-ghrelin (a centrally-acting orexigenic hormone signalling acute nutrient intake), and circulating leptin levels (providing an assay of energy reserves). We show both immediate and delayed effects on risky decision-making following a meal, and that these changes correlate with an individual's baseline leptin and changes in acyl-ghrelin levels respectively. Conclusions/Significance: We show that human risk preferences are exquisitely sensitive to current metabolic state, in a direction consistent with ecological models of feeding behaviour but not predicted by normative economic theory. These substantive effects of state changes on economic decisions perhaps reflect shared evolutionarily conserved neurobiological mechanisms. We suggest that this sensitivity in human risk-preference to current metabolic state has significant implications for both real-world economic transactions and for aberrant decision-making in eating disorders and obesity