Simulating Quantum Mean Values in Noisy Variational Quantum Algorithms: A Polynomial-Scale Approach

Large-scale variational quantum algorithms possess an expressive capacity that is beyond the reach of classical computers and is widely regarded as a potential pathway to achieving practical quantum advantages. However, the presence of quantum noise might suppress and undermine these advantages, which blurs the boundaries of classical simulability. To gain further clarity on this matter, we present a novel polynomial-scale method that efficiently approximates quantum mean values in variational quantum algorithms with bounded truncation error in the presence of independent single-qubit depolarizing noise. Our method is based on path integrals in the Pauli basis. We have rigorously proved that, for a fixed noise rate $\lambda$, our method's time and space complexity exhibits a polynomial relationship with the number of qubits $n$, the circuit depth $L$, the inverse truncation error $\frac{1}{\varepsilon}$, and the inverse success probability $\frac{1}{\delta}$. Furthermore, We also prove that computational complexity becomes $\mathrm{Poly}\left(n,L\right)$ when the noise rate $\lambda$ exceeds $\frac{1}{\log{L}}$ and it becomes exponential with $L$ when the noise rate $\lambda$ falls below $\frac{1}{L}$

Toward accurate cerebral blood flow estimation in mice after accounting for anesthesia

Purpose: To improve the accuracy of cerebral blood flow (CBF) measurement in mice by accounting for the anesthesia effects.Methods: The dependence of CBF on anesthesia dose and time was investigated by simultaneously measuring respiration rate (RR) and heart rate (HR) under four different anesthetic regimens. Quantitative CBF was measured by a phase-contrast (PC) MRI technique. RR was evaluated with a mouse monitoring system (MouseOX) while HR was determined using an ultrashort-TE MRI sequence. CBF, RR, and HR were recorded dynamically with a temporal resolution of 1 min in a total of 19 mice. Linear regression models were used to investigate the relationships among CBF, anesthesia dose, RR, and HR.Results: CBF, RR, and HR all showed a significant dependence on anesthesia dose (p < 0.0001). However, the dose in itself was insufficient to account for the variations in physiological parameters, in that they showed a time-dependent change even for a constant dose. RR and HR together can explain 52.6% of the variations in CBF measurements, which is greater than the amount of variance explained by anesthesia dose (32.4%). Based on the multi-parametric regression results, a model was proposed to correct the anesthesia effects in mouse CBF measurements, specifically CBFcorrected=CBF+0.58RR−0.41HR−32.66Dose. We also reported awake-state CBF in mice to be 142.0 ± 8.8 mL/100 g/min, which is consistent with the model-predicted value.Conclusion: The accuracy of CBF measurement in mice can be improved by using a correction model that accounts for respiration rate, heart rate, and anesthesia dose

Research on the influence of the nature of the weathered bedrock zone on the roof water bursting and sand bursting: taking Zhaogu No. 1 Mine as an example

Based on Zhaogu No. 1 Mine’s characters that are the overlying thick alluvium, multi-aquifers (groups) and thin bedrock, the water pressure of the gravel aquifer under the alluvial layer reaches 4.0 MPa, defined a high-pressure aquifer. To determine the influence of bedrock properties on roof water inrush and sand bursting, and ensure the normal mining around the thin bedrock area under groups, there were tests, point loading, dry saturated water absorption rate and indoor disintegration, of bedrock samples taken from hydrological survey holes to determine those properties and influence on retaining sand-proof pillars by analyzing the variation curves of various indexes of them with depth. The experiments’ results showed that the weathering depth of bedrock exceeds 20 m; the dry saturated water absorption rate of mudstone in the vertical depth ranging of 0−6.5 m from the bottom interface of the alluvial layer is greater than 15%. The mudstone exposed to water features muddy disintegration, broken rock fragments and mud blocks, which means it is good water-proof performance of effective bridging mining cracks and a protective layer for waterproof coal pillars; as the strength of weathered mudstone below the alluvial layer 0 to 11.4 m is lower than it of the fine gravel aquifer in the lower that of 4.0 MPa, the sand control coal pillar’s protective layer that is greater more than 11.4 m is cannot be entirely composed of weathered mudstone; due to strong resistance to disintegration and lower dry saturated water absorption rate of sandstone, the protective layer cannot be entirely composed of weathered sandstone. The compressive strength of weathered sandstone, when it is higher than 4.0 MPa, can effectively resist the overlying water head pressure

Aldehyde Dehydrogenase-2 Attenuates Myocardial Remodeling and Contractile Dysfunction Induced by a High-Fat Diet

Background/Aims: Consumption of a high-fat (HF) diet exacerbates metabolic cardiomyopathy through lipotoxic mechanisms. In this study, we explored the role of aldehyde dehydrogenase-2 (ALDH2) in myocardial damage induced by a HF diet. Methods: Wild-type C57 BL/6J mice were fed a HF diet or control diet for 16 weeks. ALDH2 overexpression was achieved by injecting a lentiviral ALDH2 expression vector into the left ventricle. Results: Consumption of a HF diet induced metabolic syndrome and myocardial remodeling, and these deleterious effects were attenuated by ALDH2 overexpression. In addition, ALDH2 overexpression attenuated the cellular apoptosis and insulin resistance associated with a HF diet. Mechanistically, ALDH2 overexpression inhibited the expression of c-Jun N-terminal kinase (JNK)-1, activated protein 1 (AP-1), insulin receptor substrate 1 (IRS-1), 4- hydroxynonenal, caspase 3, transforming growth factor β1, and collagen I and III, and enhanced Akt phosphorylation. Conclusion: ALDH2 may effectively attenuate myocardial remodeling and contractile defects induced by a HF diet through the regulation of the JNK/AP-1 and IRS-1/Akt signaling pathways. Our study demonstrates that ALDH2 plays an essential role in protecting cardiac function from lipotoxic cardiomyopathy

Predicting progression of white matter hyperintensity using coronary artery calcium score based on coronary CT angiography—feasibility and accuracy

ObjectiveCoronary artery disease (CAD) usually coexists with subclinical cerebrovascular diseases given the systematic nature of atherosclerosis. In this study, our objective was to predict the progression of white matter hyperintensity (WMH) and find its risk factors in CAD patients using the coronary artery calcium (CAC) score. We also investigated the relationship between the CAC score and the WMH volume in different brain regions.MethodsWe evaluated 137 CAD patients with WMH who underwent coronary computed tomography angiography (CCTA) and two magnetic resonance imaging (MRI) scans from March 2018 to February 2023. Patients were categorized into progressive (n = 66) and nonprogressive groups (n = 71) by the change in WMH volume from the first to the second MRI. We collected demographic, clinical, and imaging data for analysis. Independent risk factors for WMH progression were identified using logistic regression. Three models predicting WMH progression were developed and assessed. Finally, patients were divided into groups based on their total CAC score (0 to <100, 100 to 400, and > 400) to compare their WMH changes in nine brain regions.ResultsAlcohol abuse, maximum pericoronary fat attenuation index (pFAI), CT-fractional flow reserve (CT-FFR), and CAC risk grade independently predicted WMH progression (p < 0.05). The logistic regression model with all four variables performed best (training: AUC = 0.878, 95% CI: 0.790, 0.938; validation: AUC = 0.845, 95% CI: 0.734, 0.953). An increased CAC risk grade came with significantly higher WMH volume in the total brain, corpus callosum, and frontal, parietal and occipital lobes (p < 0.05).ConclusionThis study demonstrated the application of the CCTA-derived CAC score to predict WMH progression in elderly people (≥60 years) with CAD

Mechanistic insights into inositol-mediated rumen function promotion and metabolic alteration using in vitro and in vivo models

Inositol is a bioactive factor that is widely found in nature; however, there are few studies on its use in ruminant nutrition. This study investigated the effects of different inositol doses and fermentation times on rumen fermentation and microbial diversity, as well as the levels of rumen and blood metabolites in sheep. Rumen fermentation parameters, microbial diversity, and metabolites after different inositol doses were determined in vitro. According to the in vitro results, six small-tailed Han sheep fitted with permanent rumen fistulas were used in a 3 × 3 Latin square feeding experiment where inositol was injected into the rumen twice a day and rumen fluid and blood samples were collected. The in vitro results showed that inositol could increase in vitro dry matter digestibility, in vitro crude protein digestibility, NH3-N, acetic acid, propionic acid, and rumen microbial diversity and affect rumen metabolic pathways (p < 0.05). The feeding experiment results showed that inositol increased the blood concentration of high-density lipoprotein and IgG, IgM, and IL-4 levels. The rumen microbial composition was significantly affected (p < 0.05). Differential metabolites in the rumen were mainly involved in ABC transporters, biotin metabolism, and phenylalanine metabolism, whereas those in the blood were mainly involved in arginine biosynthesis and glutathione and tyrosine metabolism. In conclusion, inositol improves rumen function, affects rumen microorganisms and rumen and blood metabolites and may reduce inflammation, improving animal health

Artificial intelligence-aided rapid and accurate identification of clinical fungal infections by single-cell Raman spectroscopy

Integrating artificial intelligence and new diagnostic platforms into routine clinical microbiology laboratory procedures has grown increasingly intriguing, holding promises of reducing turnaround time and cost and maximizing efficiency. At least one billion people are suffering from fungal infections, leading to over 1.6 million mortality every year. Despite the increasing demand for fungal diagnosis, current approaches suffer from manual bias, long cultivation time (from days to months), and low sensitivity (only 50% produce positive fungal cultures). Delayed and inaccurate treatments consequently lead to higher hospital costs, mobility and mortality rates. Here, we developed single-cell Raman spectroscopy and artificial intelligence to achieve rapid identification of infectious fungi. The classification between fungi and bacteria infections was initially achieved with 100% sensitivity and specificity using single-cell Raman spectra (SCRS). Then, we constructed a Raman dataset from clinical fungal isolates obtained from 94 patients, consisting of 115,129 SCRS. By training a classification model with an optimized clinical feedback loop, just 5 cells per patient (acquisition time 2 s per cell) made the most accurate classification. This protocol has achieved 100% accuracies for fungal identification at the species level. This protocol was transformed to assessing clinical samples of urinary tract infection, obtaining the correct diagnosis from raw sample-to-result within 1 h

Defining the sizes of airborne particles that mediate influenza transmission in ferrets

Epidemics and pandemics of influenza are characterized by rapid global spread mediated by non-mutually exclusive transmission modes. The relative significance between contact, droplet, and airborne transmission is yet to be defined, a knowledge gap for implementing evidence-based infection control measures. We devised a transmission chamber that separates virus-laden particles by size and determined the particle sizes mediating transmission of influenza among ferrets through the air. Ferret-to-ferret transmission was mediated by airborne particles larger than 1.5 µm, consistent with the quantity and size of virus-laden particles released by the donors. Onward transmission by donors was most efficient before fever onset and may continue for 5 days after inoculation. Multiple virus gene segments enhanced the transmissibility of a swine influenza virus among ferrets by increasing the release of virus-laden particles into the air. We provide direct experimental evidence of influenza transmission via droplets and fine droplet nuclei, albeit at different efficiency