Tensor Robust PCA with Nonconvex and Nonlocal Regularization

Tensor robust principal component analysis (TRPCA) is a promising way for low-rank tensor recovery, which minimizes the convex surrogate of tensor rank by shrinking each tensor singular values equally. However, for real-world visual data, large singular values represent more signifiant information than small singular values. In this paper, we propose a nonconvex TRPCA (N-TRPCA) model based on the tensor adjustable logarithmic norm. Unlike TRPCA, our N-TRPCA can adaptively shrink small singular values more and shrink large singular values less. In addition, TRPCA assumes that the whole data tensor is of low rank. This assumption is hardly satisfied in practice for natural visual data, restricting the capability of TRPCA to recover the edges and texture details from noisy images and videos. To this end, we integrate nonlocal self-similarity into N-TRPCA, and further develop a nonconvex and nonlocal TRPCA (NN-TRPCA) model. Specifically, similar nonlocal patches are grouped as a tensor and then each group tensor is recovered by our N-TRPCA. Since the patches in one group are highly correlated, all group tensors have strong low-rank property, leading to an improvement of recovery performance. Experimental results demonstrate that the proposed NN-TRPCA outperforms some existing TRPCA methods in visual data recovery. The demo code is available at https://github.com/qguo2010/NN-TRPCA.Comment: 19 pages, 7 figure

Structure, Stability and Superconductivity of N-doped Lutetium Hydrides at kbar Pressures

The structure of the material responsible for the room temperature and near ambient pressure superconductivity reported in an N-doped lutetium hydride [Nature, 615, 244 (2023)] has not been conclusively determined. Herein, density functional theory calculations are performed in an attempt to uncover what it might be. Guided by a range of strategies including crystal structure prediction and modifications of existing structure types, we present an array of Lu-N-H phases that are dynamically stable at experimentally relevant pressures. Although none of the structures found are thermodynamically stable, and none are expected to remain superconducting above 17 K at 10 kbar, a number of metallic compounds with fcc Lu lattices -- as suggested by the experimental X-ray diffraction measurements of the majority phase -- are identified. The system whose calculated equation of states matches best with that measured for the majority phase is fluorite-type LuH2, whose 10 kbar superconducting critical temperature was estimated to be 0.09 K using the Allen-Dynes modified McMillan equation.Comment: 11 pages, 8 figure

Melanoma antigen-A11 regulates substrate-specificity of Skp2-mediated protein degradation

Melanoma antigen-A11 (MAGE-A11) is a proto-oncogene involved in androgen receptor signaling and androgen-dependent cell growth. In this report we provide evidence that MAGE-A11 interacts with Skp2 (S phase kinase-associated protein), the substrate recognition protein of the Skp1-Cullin1-F-box E3 ubiquitin ligase, and with Skp2 binding protein, cyclin A. A similar cyclin A binding motif in MAGE-A11 and Skp2 was consistent with a competitive relationship between MAGE-A11 and Skp2 in binding cyclin A. Skp2 inhibited MAGE-A11 interaction with cyclin A. Differential effects of MAGE-A11 on Skp2-mediated protein degradation were also revealed. MAGE-A11 increased Skp2-mediated degradation of cyclin A and retinoblastoma-related protein p130. In contrast, MAGE-A11 decreased Skp2-mediated degradation of E2F1 and Skp2 self-ubiquitination. Stabilization of E2F1 by MAGE-A11 was associated with sequestration and inactivation of Skp2 through the formation of an E2F1-MAGE-A11-Skp2 complex. We conclude that direct interactions of MAGE-A11 with Skp2 and cyclin A regulate the substrate-specificity of Skp2-mediated protein degradation

Effect of slickwater-alternate-slurry injection on proppant transport at field scales : a hybrid approach combining experiments and deep learning

Proppant transport in underground fractures plays a key role in mitigating sand screen-out and enhancing the stimulated production for hydraulic fracturing. The effects of field pumping schedules, however, are not fully studied. We investigate the effect of slickwater-alternate-slurry injection on proppant transport at field-practical scales. A new hybrid approach is proposed to directly connect experimental studies with field operations, which consists of observation experiments, calculations, and deep learning (DL) workflow. The experiments reveal that the alternate injection induces the unexpected proppant ridge. The modified calculations (considering the ridge height) are proposed to extract features for training the DL algorithm. The workflow predicts the downhole pressure (mainly governed by proppant injection) for error analyses. Approximately 20.2% of the error is eliminated by considering the proppant ridge, thus demonstrating its effect on proppant injection. The predictions are significantly improved in early and late periods of fracturing operations when the fracture is initially created and highly filled. The sensitivity analysis suggests that the pump rate may dominate the ridge height compared with other hydraulic parameters. The study of proppant ridge complements the mechanisms of proppant transport, which is essential for controlling fracturing pressure and boosting the proppant injection

Causal association of circulating cholesterol levels with dementia: a mendelian randomization meta-analysis

Prospective studies have shown that abnormally circulating cholesterol is associated with the risk of dementia. However, whether the association is causal or not remains unclear. We attempt to infer the causal association in a MR meta-analysis by using ApoE gene polymorphisms as instrument variables. Studies with dementia risk (27 studies) or circulating lipid levels (7 studies) were included, with totally 3136 dementia patients and 3103 healthy controls. The analyses showed that carriers of ε2 allele significantly were of decreased risk of AD (OR = 0.70; 95% CI: 0.58–0.84; P \u3c 0.01), whereas carriers of ε4 allele were of increased risk of AD (OR = 3.62; 95% CI: 3.03–4.32; P \u3c 0.05), compared to these of ε3 allele. Circulating TC was significantly reduced in carriers of ε2 allele (WMD = − 0.29 mmol/L; 95% CI: −0.54 to −0.03; P \u3c 0.05) and increased in carriers of ε4 allele (WMD = 0.42 mmol/l; 95% CI: 0.001–0.84; P \u3c 0.05). In addition, carriers of ε4 allele had reduction in circulating HDL-C (WMD = − 0.04 mmol/L; 95% CI: − 0.07 to −0.001; P \u3c 0.05). In comparing allele ε2 with ε3, the predicted OR of having AD for 1 mg/dL increment in circulating TC was 0.97 (95% CI: 0.86–0.98; P \u3c 0.05). Comparing allele ε4 with ε3, the predicted OR for a 1 mg/dL increment in TC was 1.08 (95% CI: 1.05–17.58; P \u3c 0.05), and reduction in HDL-C was 2.30 (95% CI: 1.51–43.99; P \u3c 0.05). Our findings demonstrate that high circulating TC and reduced HDL-C levels might be potential risk factors of the development of AD

PCR Techniques and Their Clinical Applications

Kary B. Mullis developed a revolutionary method name polymerase chain reaction (PCR) in 1983, which can synthesize new strand of DNA complementary to the template strand of DNA and produce billions of copies of a DNA fragment only in few hours. Denaturation, annealing, and extension are the three primary steps involved in the PCR process, which generally requires thermocyclers, DNA template, a pair of primers, Taq polymerase, nucleotides, buffers, etc. With the development of PCR, from traditional PCR, quantitative PCR, to next digital PCR, PCR has become a powerful tool in life sciences and medicine. Applications of PCR techniques for infectious diseases include specific or broad-spectrum pathogen detection, assessment and surveillance of emerging infections, early detection of biological threat agents, and antimicrobial resistance analysis. Applications of PCR techniques for genetic diseases include prenatal diagnosis and screening of neonatal genetic diseases. Applications of PCR techniques for cancer research include tumor-related gene detection. This chapter aimed to discuss about the different types of PCR techniques, including traditional PCR, quantitative PCR, digital PCR, etc., and their applications for rapid detection, mutation screen or diagnosis in infectious diseases, inherited diseases, cancer, and other diseases

Causal associations between COVID-19 and atrial fibrillation: A bidirectional Mendelian randomization study

Background and aims: Observational studies showed that coronavirus disease (2019) (COVID-19) attacks universally and its most menacing progression uniquely endangers the elderly with cardiovascular disease (CVD). The causal association between COVID-19 infection or its severity and susceptibility of atrial fibrillation (AF) remains unknown. Methods and results: The bidirectional causal relationship between COVID-19 (including COVID-19, hospitalized COVID-19 compared with not hospitalized COVID-19, hospitalized COVID-19 compared with the general population, and severe COVID-19) and AF are determined by using two-sample Mendelian randomization (MR) analysis. Genetically predicted severe COVID-19 was not significantly associated with the risk of AF [odds ratio (OR), 1.037; 95% confidence interval (CI), 1.005–1.071; P = 0.023, q = 0.115]. In addition, genetically predicted AF was also not causally associated with severe COVID-19 (OR, 0.993; 95% CI, 0.888–1.111; P = 0.905, q = 0.905). There was no evidence to support the association between genetically determined COVID-19 and the risk of AF (OR, 1.111; 95% CI, 0.971–1.272; P = 0.127, q = 0.318), and vice versa (OR, 1.016; 95% CI, 0.976–1.058; P = 0.430, q = 0.851). Besides, no significant association was observed for hospitalized COVID-19 with AF. MR-Egger analysis indicated no evidence of directional pleiotropy. Conclusion: Overall, this MR study provides no clear evidence that COVID-19 is causally associated with the risk of AF

Autophagic Degradation Deficit Involved in Sevoflurane-Induced Amyloid Pathology and Spatial Learning Impairment in APP/PS1 Transgenic Mice

The adverse effects of anesthetics on elderly people, especially those with brain diseases are very concerning. Whether inhaled anesthetics have adverse effects on Alzheimer’s disease (AD), which is the most common form of dementia with brain degenerative changes, remains controversial. Autophagy, a crucial biological degradation process, is extremely important for the pathogenesis of AD. In this study, the inhaled anesthetic sevoflurane elicited many enlarged autolysosomes and impaired the overall autophagic degradation in the hippocampus of an AD mouse model, which is involved in the accumulation of amyloid-β (Aβ) and spatial learning deficits. However, rapamycin treatment counteracted all these effects. The results suggested that inhaled anesthetics may accelerate the pathological process of AD, and enlarged autolysosomes may be a new marker for prediction and diagnosis of the neurotoxicity of anesthetics in AD

Distinct gut bacterial composition in Anoplophora glabripennis reared on two host plants

Anoplophora glabripennis (Coleoptera: Cerambycidae: Lamiinae) is an invasive wood borer pest that has caused considerable damage to forests. Gut bacteria are of great importance in the biology and ecology of herbivores, especially in growth and adaptation; however, change in the gut bacterial community of this pest feeding on different hosts is largely unknown. In this study, we investigated the gut bacterial communities of A. glabripennis larvae fed on different preferred hosts, Salix matsudana and Ulmus pumila, using 16S rDNA high-throughput sequencing technology. A total of 15 phyla, 25 classes, 65 orders, 114 families, 188 genera, and 170 species were annotated in the gut of A. glabripennis larvae fed on S. matsudana or U. pumila using a 97% similarity cutoff level. The dominant phyla were Firmicutes and Proteobacteria and the core dominant genera were Enterococcus, Gibbsiella, Citrobacter, Enterobacter, and Klebsiella. There was significantly higher alpha diversity in the U. pumila group than in the S. matsudana group, and principal co-ordinate analysis showed significant differences in gut bacterial communities between the two groups. The genera with significant abundance differences between the two groups were Gibbsiella, Enterobacter, Leuconostoc, Rhodobacter, TM7a, norank, Rhodobacter, and Aurantisolimonas, indicating that the abundance of larval gut bacteria was affected by feeding on different hosts. Further network diagrams showed that the complexity of the network structure and the modularity were higher in the U. pumila group than in the S. matsudana group, suggesting more diverse gut bacteria in the U. pumila group. The dominant role of most gut microbiota was related to fermentation and chemoheterotrophy, and specific OTUs positively correlated with different functions were reported. Our study provides an essential resource for the gut bacteria functional study of A. glabripennis associated with host diet