Field-free switching of perpendicular magnetization by two-dimensional PtTe2/WTe2 van der Waals heterostructures with high spin Hall conductivity.

The key challenge of spin-orbit torque applications lies in exploring an excellent spin source capable of generating out-of-plane spins while exhibiting high spin Hall conductivity. Here we combine PtTe2 for high spin conductivity and WTe2 for low crystal symmetry to satisfy the above requirements. The PtTe2/WTe2 bilayers exhibit a high in-plane spin Hall conductivity σs,y ≈ 2.32 × 105 × h/2e Ω-1 m-1 and out-of-plane spin Hall conductivity σs,z ≈ 0.25 × 105 × h/2e Ω-1 m-1, where h is the reduced Planck's constant and e is the value of the elementary charge. The out-of-plane spins in PtTe2/WTe2 bilayers enable the deterministic switching of perpendicular magnetization at room temperature without magnetic fields, and the power consumption is 67 times smaller than that of the Pt control case. The high out-of-plane spin Hall conductivity is attributed to the conversion from in-plane spin to out-of-plane spin, induced by the crystal asymmetry of WTe2. Our work establishes a low-power perpendicular magnetization manipulation based on wafer-scale two-dimensional van der Waals heterostructures.

The landscape of different molecular modules in an immune microenvironment during tuberculosis infection.

Tuberculosis is a chronic inflammatory disease caused by Mycobacterium tuberculosis. When tuberculosis invades the human body, innate immunity is the first line of defense. However, how the innate immune microenvironment responds remains unclear. In this research, we studied the function of each type of cell and explained the principle of an immune microenvironment. Based on the differences in the innate immune microenvironment, we modularized the analysis of the response of five immune cells and two structural cells. The results showed that in the innate immune stress response, the genes CXCL3, PTGS2 and TNFAIP6 regulated by the nuclear factor kappa B(NK-KB) pathway played a crucial role in fighting against tuberculosis. Based on the active pathway algorithm, each immune cell showed metabolic heterogeneity. Besides, after tuberculosis infection, structural cells showed a chemotactic immunity effect based on the co-expression immunoregulatory module.

Calculation of high-order harmonic generation of atoms and molecules by combining time series prediction and neural networks.

High-order harmonic generation (HHG) from the interaction of ultra-intense laser pulses with atoms is an important tabletop short-wave coherent light source. Accurate quantum simulations of it present large computational difficulties due to multi-electron multidimensional effects. In this paper, the time-dependent response of hydrogen atoms is calculated using a time-series prediction scheme, the HHG spectrum is reconstructed very accurately. The accuracy of the forecasting is further improved by using a neural network scheme. This scheme is also applied to the simulation of the harmonic emission on multi-electron systems, and the applicability of the scheme is confirmed by the harmonic calculation of complex systems. This method is expected to simulate the nonlinear dynamic process of multi-electron atoms and molecules irradiated by intense laser pulses quickly and accurately.

Minimum Distribution Support Vector Clustering.

Support vector clustering (SVC) is a boundary-based algorithm, which has several advantages over other clustering methods, including identifying clusters of arbitrary shapes and numbers. Leveraged by the high generalization ability of the large margin distribution machine (LDM) and the optimal margin distribution clustering (ODMC), we propose a new clustering method: minimum distribution for support vector clustering (MDSVC), for improving the robustness of boundary point recognition, which characterizes the optimal hypersphere by the first-order and second-order statistics and tries to minimize the mean and variance simultaneously. In addition, we further prove, theoretically, that our algorithm can obtain better generalization performance. Some instructive insights for adjusting the number of support vector points are gained. For the optimization problem of MDSVC, we propose a double coordinate descent algorithm for small and medium samples. The experimental results on both artificial and real datasets indicate that our MDSVC has a significant improvement in generalization performance compared to SVC.

Regression analysis of informative current status data with the additive hazards model.

This paper discusses regression analysis of current status failure time data arising from the additive hazards model in the presence of informative censoring. Many methods have been developed for regression analysis of current status data under various regression models if the censoring is noninformative, and also there exists a large literature on parametric analysis of informative current status data in the context of tumorgenicity experiments. In this paper, a semiparametric maximum likelihood estimation procedure is presented and in the method, the copula model is employed to describe the relationship between the failure time of interest and the censoring time. Furthermore, I-splines are used to approximate the nonparametric functions involved and the asymptotic consistency and normality of the proposed estimators are established. A simulation study is conducted and indicates that the proposed approach works well for practical situations. An illustrative example is also provided.

Estimation of accelerated hazards models based on case K informatively interval-censored failure time data.

The accelerated hazards model is one of the most commonly used models for regression analysis of failure time data and this is especially the case when, for example, the hazard functions may have monotonicity property. Correspondingly a large literature has been established for its estimation or inference when right-censored data are observed. Although several methods have also been developed for its inference based on interval-censored data, they apply only to limited situations or rely on some assumptions such as independent censoring. In this paper, we consider the situation where one observes case K interval-censored data, the type of failure time data that occur most in, for example, medical research such as clinical trials or periodical follow-up studies. For inference, we propose a sieve borrow-strength method and in particular, it allows for informative censoring. The asymptotic properties of the proposed estimators are established. Simulation studies demonstrate that the proposed inference procedure performs well. The method is applied to a set of real data set arising from an AIDS clinical trial.

A comparison of two models for detecting inconsistency in network meta-analysis.

The application of network meta-analysis is becoming increasingly widespread, and for a successful implementation, it requires that the direct comparison result and the indirect comparison result should be consistent. Because of this, a proper detection of inconsistency is often a key issue in network meta-analysis as whether the results can be reliably used as a clinical guidance. Among the existing methods for detecting inconsistency, two commonly used models are the design-by-treatment interaction model and the side-splitting models. While the original side-splitting model was initially estimated using a Bayesian approach, in this context, we employ the frequentist approach. In this paper, we review these two types of models comprehensively as well as explore their relationship by treating the data structure of network meta-analysis as missing data and parameterizing the potential complete data for each model. Through both analytical and numerical studies, we verify that the side-splitting models are specific instances of the design-by-treatment interaction model, incorporating additional assumptions or under certain data structure. Moreover, the design-by-treatment interaction model exhibits robust performance across different data structures on inconsistency detection compared to the side-splitting models. Finally, as a practical guidance for inconsistency detection, we recommend utilizing the design-by-treatment interaction model when there is a lack of information about the potential location of inconsistency. By contrast, the side-splitting models can serve as a supplementary method especially when the number of studies in each design is small, enabling a comprehensive assessment of inconsistency from both global and local perspectives.

A Comparison of Minimally Invasive Surgical Techniques and Standard Open Discectomy for Lumbar Disc Herniation: A Network Meta-analysis.

BACKGROUND: Lumbar disc herniation is a common spinal disease that causes low back pain; surgery is required when conservative treatment is ineffective. There is a growing demand for minimally invasive surgery in younger patient populations due to their fear of significant damage and a long recovery period following standard open discectomy. The development history of minimally invasive surgery is relatively short, and no gold standard has been established. OBJECTIVES: We aimed to find, via a network meta-analysis, the best treatment for low back pain in younger patient populations. STUDY DESIGN: Network meta-analysis. METHODS: The PubMed, Embase, Cochrane Library, and Web of Science databases were searched. Data quality was evaluated using RevMan 5.3 (The Nordic Cochrane Centre for The Cochrane Collaboration), while STATA 14.0 (StataCorp LLC) was used for the network meta-analysis and to merge data on the Visual Analog Scale (VAS) score, Oswestry Disability Index (ODI) score, complication, blood loss, reoperation rate, and function score. RESULTS: We included 50 randomized controlled trials, involving 7 interventions; heterogeneity and inconsistency were acceptable. Comparatively, microendoscopic discectomy and percutaneous endoscopic lumbar discectomy were the best surgical procedures from the aspects of VAS score and ODI score, while standard open discectomy was the worst one from the aspect of ODI score. Regarding complications, tubular discectomy was preferred with the fewest complications. Additionally, microendoscopic discectomy outperformed other surgical procedures in reducing blood loss and reoperation rate. LIMITATIONS: First, follow-up data were not reported in all included studies, and the follow-up time varied from several months to 8 years, which affected the results accuracy of our study to some extent. Second, there were some nonsurgical factors that also affected the self-reported outcomes, such as rehabilitation and pain management, which also brought a certain bias in our study results. CONCLUSIONS: Compared to standard open discectomy, minimally invasive surgical procedures not only achieve satisfactory efficacy, but also microendoscopic discectomy and percutaneous endoscopic lumbar discectomy can obtain a more satisfactory short-term VAS score and ODI score. Microendoscopic discectomy has significant advantages in blood loss and reoperation rate, and tubular discectomy has fewer postoperative complications.

Field-free spin-orbit torque switching in ferromagnetic trilayers at sub-ns timescales.

Current-induced spin torques enable the electrical control of the magnetization with low energy consumption. Conventional magnetic random access memory (MRAM) devices rely on spin-transfer torque (STT), this however limits MRAM applications because of the nanoseconds incubation delay and associated endurance issues. A potential alternative to STT is spin-orbit torque (SOT). However, for practical, high-speed SOT devices, it must satisfy three conditions simultaneously, i.e., field-free switching at short current pulses, short incubation delay, and low switching current. Here, we demonstrate field-free SOT switching at sub-ns timescales in a CoFeB/Ti/CoFeB ferromagnetic trilayer, which satisfies all three conditions. In this trilayer, the bottom magnetic layer or its interface generates spin currents with polarizations in both in-plane and out-of-plane components. The in-plane component reduces the incubation time, while the out-of-plane component realizes field-free switching at a low current. Our results offer a field-free SOT solution for energy-efficient scalable MRAM applications.

Dynamic immune status analysis of peripheral blood mononuclear cells in patients with Klebsiella pneumoniae bloodstream infection sepsis using single-cell RNA sequencing.

Background: Klebsiella pneumoniae is a common Gram-negative bacterium. Blood infection caused by K. pneumoniae is one of the most common causes of human sepsis, which seriously threatens the life of patients. The immune status of peripheral blood mononuclear cells (PBMCs) based on single-cell RNA sequencing (scRNA-seq) in acute stage and recovery stage of sepsis caused by K. pneumoniae bloodstream infection has not been studied. Methods: A total of 13 subjects were included in this study, 3 healthy controls, 7 patients with K. pneumoniae bloodstream infection in the acute stage (4 patients died), and 3 patients in the recovery stage. Peripheral blood of all patients was collected and PBMCs were isolated for scRNA-seq analysis. We studied the changes of PBMCs components, signaling pathways, differential genes, and cytokines in acute and recovery stages. Results: During K. pneumoniae acute infection we observed a decrease in the proportion of T cells, most probably due to apoptosis and the function of T cell subtypes was disorder. The proportion of monocytes increased in acute stage. Although genes related to their phagocytosis function were upregulated, their antigen presentation capacity-associated genes were downregulated. The expression of IL-1ß, IL-18, IFNGR1 and IFNGR2 genes was also increased in monocytes. The proportion of DCs was depleted during the acute stage and did not recover during sepsis recovery. DCs antigen presentation was weakened during the acute stage but recovered fast during the recovery stage. pDCs response to MCP-1 chemokine was weakened, they recovered it quickly during the recovery stage. B cells showed apoptosis both in the acute stage and recovery stage. Their response to complement was weakened, but their antigen presentation function was enhanced. The proportion of NK cells stable during all disease's stages, and the expression of IFN-γ gene was upregulated. Conclusion: The proportion of PBMCs and their immune functions undergo variations throughout the course of the disease, spanning from the acute stage to recovery. These findings provide new insights into the mechanism of PBMCs immune function during K. pneumoniae bloodstream infection sepsis and recovery and sets the basis for further understanding and treatment.

Spin-orbit torque manipulation of sub-terahertz magnons in antiferromagnetic α-Fe2O3.

The ability to electrically manipulate antiferromagnetic magnons, essential for extending the operating speed of spintronic devices into the terahertz regime, remains a major challenge. This is because antiferromagnetic magnetism is challenging to perturb using traditional methods such as magnetic fields. Recent developments in spin-orbit torques have opened a possibility of accessing antiferromagnetic magnetic order parameters and controlling terahertz magnons, which has not been experimentally realised yet. Here, we demonstrate the electrical manipulation of sub-terahertz magnons in the α-Fe2O3/Pt antiferromagnetic heterostructure. By applying the spin-orbit torques in the heterostructure, we can modify the magnon dispersion and decrease the magnon frequency in α-Fe2O3, as detected by time-resolved magneto-optical techniques. We have found that optimal tuning occurs when the Néel vector is perpendicular to the injected spin polarisation. Our results represent a significant step towards the development of electrically tunable terahertz spintronic devices.

Above-room-temperature chiral skyrmion lattice and Dzyaloshinskii-Moriya interaction in a van der Waals ferromagnet Fe3-xGaTe2.

Skyrmions in existing 2D van der Waals (vdW) materials have primarily been limited to cryogenic temperatures, and the underlying physical mechanism of the Dzyaloshinskii-Moriya interaction (DMI), a crucial ingredient for stabilizing chiral skyrmions, remains inadequately explored. Here, we report the observation of Néel-type skyrmions in a vdW ferromagnet Fe3-xGaTe2 above room temperature. Contrary to previous assumptions of centrosymmetry in Fe3-xGaTe2, the atomic-resolution scanning transmission electron microscopy reveals that the off-centered FeΙΙ atoms break the spatial inversion symmetry, rendering it a polar metal. First-principles calculations further elucidate that the DMI primarily stems from the Te sublayers through the Fert-Lévy mechanism. Remarkably, the chiral skyrmion lattice in Fe3-xGaTe2 can persist up to 330 K at zero magnetic field, demonstrating superior thermal stability compared to other known skyrmion vdW magnets. This work provides valuable insights into skyrmionics and presents promising prospects for 2D material-based skyrmion devices operating beyond room temperature.

Variable selection for mixed panel count data under the proportional mean model.

Mixed panel count data have attracted increasing attention in medical research based on event history studies. When such data arise, one either observes the number of event occurrences or only knows whether the event has happened or not over an observation period. In this article, we discuss variable selection in event history studies given such complex data, for which there does not seem to exist an established procedure. For the problem, we propose a penalized likelihood variable selection procedure and for the implementation, an expectation-maximization algorithm is developed with the use of the coordinate descent algorithm in the M-step. Furthermore, the oracle property of the proposed method is established, and a simulation study is performed and indicates that the proposed method works well in practical scenarios. Finally, the method is applied to identify the risk factors associated with medical non-adherence arising from the Sequenced Treatment Alternatives to Relieve Depression Study.

A preliminary screening system for diabetes based on in-car electronic nose.

Studies have found differences in the concentration of volatile organic compounds in the breath of diabetics and healthy people, prompting attention to the use of devices such as electronic noses to detect diabetes. In this study, we explored the design of a non-invasive diabetes preliminary screening system that uses a homemade electronic nose sensor array to detect respiratory gas markers. In the algorithm part, two feature extraction methods were adopted, gradient boosting method was used to select promising feature subset, and then particle swarm optimization algorithm was introduced to extract 24 most effective features, which reduces the number of sensors by 56% and saves the system cost. Respiratory samples were collected from 120 healthy subjects and 120 diabetic subjects to assess the system performance. Random forest algorithm was used to classify and predict electronic nose data, and the accuracy can reach 93.33%. Experimental results show that on the premise of ensuring accuracy, the system has low cost and small size after the number of sensors is optimized, and it is easy to install on in-car. It provides a more feasible method for the preliminary screening of diabetes on in-car and can be used as an assistant to the existing detection methods.

Risk Assessment of the Possible Intermediate Host Role of Pigs for Coronaviruses with a Deep Learning Predictor.

Swine coronaviruses (CoVs) have been found to cause infection in humans, suggesting that Suiformes might be potential intermediate hosts in CoV transmission from their natural hosts to humans. The present study aims to establish convolutional neural network (CNN) models to predict host adaptation of swine CoVs. Decomposing of each ORF1ab and Spike sequence was performed with dinucleotide composition representation (DCR) and other traits. The relationship between CoVs from different adaptive hosts was analyzed by unsupervised learning, and CNN models based on DCR of ORF1ab and Spike were built to predict the host adaptation of swine CoVs. The rationality of the models was verified with phylogenetic analysis. Unsupervised learning showed that there is a multiple host adaptation of different swine CoVs. According to the adaptation prediction of CNN models, swine acute diarrhea syndrome CoV (SADS-CoV) and porcine epidemic diarrhea virus (PEDV) are adapted to Chiroptera, swine transmissible gastroenteritis virus (TGEV) is adapted to Carnivora, porcine hemagglutinating encephalomyelitis (PHEV) might be adapted to Primate, Rodent, and Lagomorpha, and porcine deltacoronavirus (PDCoV) might be adapted to Chiroptera, Artiodactyla, and Carnivora. In summary, the DCR trait has been confirmed to be representative for the CoV genome, and the DCR-based deep learning model works well to assess the adaptation of swine CoVs to other mammals. Suiformes might be intermediate hosts for human CoVs and other mammalian CoVs. The present study provides a novel approach to assess the risk of adaptation and transmission to humans and other mammals of swine CoVs.

Role of Long Noncoding RNAs in Smoking-Induced Lung Cancer: An In Silico Study.

The prevalence of lung cancer induced by cigarette smoking has increased over time. Long noncoding (lnc) RNAs, regulatory factors that play a role in human diseases, are commonly dysregulated in lung cancer. Cigarette smoking is closely related to changes in lncRNA expression, which can affect lung cancer. Herein, we assess the mechanism of lung cancer initiation induced by smoking. To calculate the impact of smoking on the survival of patients with lung cancer, we extracted data from The Cancer Genome Atlas and Gene Expression Omnibus databases and identified the differentially expressed genes in the lung cancer tissue compared to the normal lung tissue. Genes positively and negatively associated with smoking were identified. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Cytoscape analyses were performed to determine the function of the genes and the effects of smoking on the immune microenvironment. lncRNAs corresponding to smoking-associated genes were identified, and a smoking-related lncRNA model was constructed using univariate and multivariate Cox analyses. This model was used to assess the survival of and potential risk in patients who smoked. During screening, 562 differentially expressed genes were identified, and we elucidated that smoking affected the survival of patients 4.5 years after the diagnosis of lung cancer. Furthermore, genes negatively associated with smoking were closely associated with immunity. Twelve immune cell types were also found to infiltrate differentially in smokers and nonsmokers. Thus, the smoking-associated lncRNA model is a good predictor of survival and risk in smokers and may be used as an independent prognostic factor for lung cancer.

Curative efficacy of surgical procedures for older patients with femoral neck fracture: a network meta-analysis and systematic review.

BACKGROUND: Femoral neck fractures have a higher incidence in older people with poor prognosis, inducing serious social problems. Common treatment methods include total hip arthroplasty, bipolar hemiarthroplasty, double-screw fixation, multiple-screw fixation, and dynamic hip system. METHODS: We searched through four electronic databases, including PubMed, Web of Science, Cochrane Library, and Embase databases, for articles regarding femoral neck fractures, bone screw, and hip prosthesis published up to February 11, 2020. All included articles were used for quality evaluation and data extraction. Extracted data were expressed as odds ratios or weighted mean differences, with 95% confidence intervals. We conducted a network meta-analysis for Harris hip score, complications, 1-year mortality rate, reoperation rate, intraoperative blood loss, and duration of operation using STATA version 16.0 software. RESULTS: Twenty-two randomized controlled trials and nine cohort studies included in this study involved 3861 patients. Total hip arthroplasty significantly improved the postoperative function of patients with femoral neck fractures. The surface under the cumulative ranking curve value of the Harris hip score for more than 1 year after total hip arthroplasty was 98.2. CONCLUSIONS: This meta-analysis indicated no significant difference in mortality among different treatment groups. Total hip arthroplasty can provide satisfactory outcomes in hip joint function, and double-screw fixation results in the lowest intraoperative risk. In general, total hip arthroplasty results in a lower incidence of adverse events and is especially recommended for patients with femoral neck fractures. This article has been retrospectively registered on the International Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY) on November 27, 2020. Registration number: INPLASY2020110123.

Enhanced Energy Density at a Low Electric Field in PVDF-Based Heterojunctions Sandwiched with High Ion-Polarized BTO Films.

Inorganic/organic dielectric composites with outstanding energy storage properties at a low electric field possess the advantages of low operating voltage and small probability of failure. Composites filled with two-dimensional inorganic nanosheets have attracted much attention owing to their fewer interfacial defects caused by the agglomeration of fillers. Continuous oxide films with a preferred orientation can play a significant role in enhancing energy storage. The challenge is to prepare large-sized, freestanding, single-crystal, ferroelectric oxide films and to combine them with polymers. In this work, a well-developed water-dissolvent process was used to transfer millimeter-sized (100)-oriented BaTiO3 (BTO) films. Poly(vinylidene fluoride) (PVDF)-based heterojunctions sandwiched with the single-crystal films were synthesized via the transferring process and an optimized hot-pressing technique. By virtue of high ion displacement polarization and inhibited conductive path formation of single-crystal BTO films, the energy storage density and efficiency of BTO/PVDF heterojunctions reach 1.56 J cm-3 and 71.2% at a low electric field of 120 MV m-1, which are much higher than those of pure PVDF and BTO nanoparticles/PVDF composite films, respectively. A finite-element simulation was employed to further confirm the experimental results. This work provides an effective approach to enhance energy storage properties in various polymer-based composites and opens the door to advanced dielectric capacitors.

Regression Analysis of Case-cohort Studies in the Presence of Dependent Interval Censoring.

The case-cohort design is widely used as a means of reducing the cost in large cohort studies, especially when the disease rate is low and covariate measurements may be expensive, and has been discussed by many authors. In this paper, we discuss regression analysis of case-cohort studies that produce interval-censored failure time with dependent censoring, a situation for which there does not seem to exist an established approach. For inference, a sieve inverse probability weighting estimation procedure is developed with the use of Bernstein polynomials to approximate the unknown baseline cumulative hazard functions. The proposed estimators are shown to be consistent and the asymptotic normality of the resulting regression parameter estimators are established. A simulation study is conducted to assess the finite sample properties of the proposed approach and indicates that it works well in practical situations. The proposed method is applied to an HIV/AIDS case-cohort study that motivated this investigation.

Gene expression barcode values reveal a potential link between Parkinson's disease and gastric cancer.

Gastric cancer is a disease that develops from the lining of the stomach, whereas Parkinson's disease is a long-term degenerative disorder of the central nervous system that mainly affects the motor system. Although these two diseases seem to be distinct from each other, increasing evidence suggests that they might be linked. To explore the linkage between these two diseases, differentially expressed genes between the diseased people and their normal controls were identified using the barcode algorithm. This algorithm transforms actual gene expression values into barcode values comprised of 1's (expressed genes) and 0's (silenced genes). Once the overlapped differentially expressed genes were identified, their biological relevance was investigated. Thus, using the gene expression profiles and bioinformatics methods, we demonstrate that Parkinson's disease and gastric cancer are indeed linked. This research may serve as a pilot study, and it will stimulate more research to investigate the relationship between gastric cancer and Parkinson's disease from the perspective of gene profiles and their functions.