Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantum control of topological defects in magnetic systems

Energy-efficient classical information processing and storage based on topological defects in magnetic systems have been studied over past decade. In this work, we introduce a class of macroscopic quantum devices in which a quantum state is stored in a topological defect of a magnetic insulator. We propose non-invasive methods to coherently control and readout the quantum state using ac magnetic fields and magnetic force microscopy, respectively. This macroscopic quantum spintronic device realizes the magnetic analog of the three-level rf-SQUID qubit and is built fully out of electrical insulators with no mobile electrons, thus eliminating decoherence due to the coupling of the quantum variable to an electronic continuum and energy dissipation due to Joule heating. For a domain wall sizes of $10-100$~nm and reasonable material parameters, we estimate qubit operating temperatures in the range of $0.1-1$~K, a decoherence time of about $0.01-1$~$\mu$s, and the number of Rabi flops within the coherence time scale in the range of $10^{2}-10^{4}$.
Cell-type annotation with accurate unseen cell-type identification using multiple references

The recent advances in single-cell RNA sequencing (scRNA-seq) techniques have stimulated efforts to identify and characterize the cellular composition of complex tissues. With the advent of various sequencing techniques, automated cell-type annotation using a well-annotated scRNA-seq reference becomes popular but relies on the diversity of cell types in the reference. There are generally unseen cell types in the query data of interest because most data atlases are obtained for different purposes and techniques. When annotating new query data, identifying unseen cell types is fundamental not only for improving annotation accuracy but also for novel biological discoveries. Here, we propose mtANN (multiple-reference-based scRNA-seq data annotation), a new method to automatically annotate query data while accurately identifying unseen cell types with the aid of multiple references. Key innovations of mtANN include the integration of deep learning and ensemble learning to improve prediction accuracy, and the introduction of a new metric defined from three complementary aspects to distinguish between unseen cell types and shared cell types. In addition, a data-driven method is provided to adaptively select threshold for unseen cell-type identification. We demonstrate the advantages of mtANN over state-of-the-art methods for unseen cell-type identification and cell-type annotation on two benchmark dataset collections, as well as its predictive power on a collection of COVID-19 datasets. The source code and tutorial are available at https://github.com/Zhangxf-ccnu/mtANN. Author summary Single-cell transcriptomics is rapidly advancing our understanding of the cellular composition of complex tissues and organisms. With the advent of various sequencing techniques, automatic cell-type annotation using well-annotated single-cell RNA sequencing (scRNA-seq) references has become popular. Compared with unsupervised cell-type annotation methods, it can be more easily applied to different data, saving labor and time costs. However, it relies on the diversity of cell types in the reference so there are generally unseen cell types in the query data. These unseen cell types need to be identified when annotating new sequencing data not only for improving annotation accuracy but also for novel biological discoveries. To address these issues, we propose mtANN, a new method to automatically annotate query data while accurately identify unseen cell types with the help of multiple references. We demonstrate the annotation performance of mtANN in PBMC and Pancreas collections when different proportions of unseen cell types are present in the query dataset. We also verify the practical application of mtANN in a collection of COVID-19 datasets for patients with different symptoms. When there are unseen cell types in the query dataset, mtANN is able to identify the unseen cell types and accurately annotate the shared cell types, especially the two cell types that are biologically similar.
Standardization of Data Analysis for RT-QuIC-Based Detection of Chronic Wasting Disease

Chronic wasting disease (CWD) is a disease affecting cervids and is caused by prions accumulating as pathogenic fibrils in lymphoid tissue and the central nervous system. Approaches for detecting CWD prions historically relied on antibody-based assays. However, recent advancements in protein amplification technology provided the foundation for a new class of CWD diagnostic tools. In particular, real-time quaking-induced conversion (RT-QuIC) has rapidly become a feasible option for CWD diagnosis. Despite its increased usage for CWD-focused research, there lacks consensus regarding the interpretation of RT-QuIC data for diagnostic purposes. It is imperative then to identify a standardized and replicable method for determining CWD status from RT-QuIC data. Here, we assessed variables that could impact RT-QuIC results and explored the use of maxpoint ratios (maximumRFU/backgroundRFU) to improve the consistency of RT-QuIC analysis. We examined a variety of statistical analyses to retrospectively analyze CWD status based on RT-QuIC and ELISA results from 668 white-tailed deer lymph nodes. Our results revealed an MPR threshold of 2.0 for determining the rate of amyloid formation, and MPR analysis showed excellent agreement with independent ELISA results. These findings suggest that the use of MPR is a statistically viable option for normalizing between RT-QuIC experiments and defining CWD status.
KDM5A/B promotes HIV-1 latency and KDM5 inhibitors promote HIV-1 lytic reactivation

Combinational antiretroviral therapy (cART) effectively suppresses HIV-1 infection, replication, and pathogenesis in HIV-1 patients. However, the patient’s HIV-1 reservoir still cannot be eliminated by current cART or other therapies. One putative HIV-1 eradication strategy is “shock and kill”, which reactivates HIV-1 in latently-infected cells and induces their cytopathic effect or immune clearance to decrease the patients’ reservoir size. KDM5A and KDM5B act as the HIV-1 latency-promoting genes, decreasing the HIV-1 viral gene transcription and reactivation in infected cells. Depletion of KDM5 A/B by siRNA knockdown (KD) increases H3K4 trimethylation (H3K4me3) in HIV-1 Tat-mediated transactivation. We also found that the KDM5-specific inhibitor JQKD82 can increase H3K4me3 at the HIV-1 LTR region during HIV-1 reactivation and induce cytopathic effects. We applied the JQKD82 in combination with the non-canonical NF-κB activator AZD5582, which synergistically induced HIV-1 reactivation and cell apoptosis in HIV-1 infected cells. These results suggested that the KDM5 inhibition can be a putative HIV-1 latency-reversing strategy for the HIV-1 “shock and kill” eradication therapy.
Statistically unbiased prediction enables accurate denoising of voltage imaging data

Here we report SUPPORT (Statistically Unbiased Prediction utilizing sPatiOtempoRal information in imaging daTa), a self-supervised learning method for removing Poisson-Gaussian noise in voltage imaging data. SUPPORT is based on the insight that a pixel value in voltage imaging data is highly dependent on its spatially neighboring pixels in the same time frame, even when its temporally adjacent frames do not provide useful information for statistical prediction. Such spatiotemporal dependency is captured and utilized to accurately denoise voltage imaging data in which the existence of the action potential in a time frame cannot be inferred by the information in other frames. Through simulation and experiments, we show that SUPPORT enables precise denoising of voltage imaging data while preserving the underlying dynamics in the scene.
Integration of event experiences to build relational knowledge in the human brain

We investigated how the human brain integrates experiences of specific events to build general knowledge about typical event structure. We examined an episodic area important for temporal relations, anterior-lateral entorhinal cortex (alEC), and a semantic area important for action concepts, middle temporal gyrus (MTG). Participants underwent fMRI while watching sequences of novel events and recalling their temporal relations over two sessions one week apart. Across different contexts, the roles of these events could either be consistent, or conflict; integrative representations should weaken in the conflicting condition. We found integrative representations that emerged quickly in alEC, and only subsequently in MTG, which showed a significant change across sessions. Thus, alEC is important in building integrative representations early in learning and may be a gateway to semantic knowledge in MTG. We suggest that both episodic and semantic systems participate in integrating new information when it is aligned with their content specializations.
Anticipatory and evoked visual cortical dynamics of voluntary temporal attention

We can often anticipate the precise moment when a stimulus will be relevant for our behavioral goals. Voluntary temporal attention, the prioritization of sensory information at task-relevant time points, enhances visual perception. However, the neural mechanisms of voluntary temporal attention have not been isolated from those of temporal expectation, which reflects timing predictability rather than relevance. Here we used time-resolved steady-state visual evoked responses (SSVER) to investigate how temporal attention dynamically modulates visual activity when temporal expectation is controlled. We recorded MEG while observers directed temporal attention to one of two sequential grating targets with predictable timing. Meanwhile, we used a co-localized SSVER probe to continuously track visual cortical modulations both before and after the target stimuli. In the pre-target period, the SSVER gradually ramped up as the targets approached, reflecting temporal expectation. Furthermore, we found a low-frequency modulation of the SSVER, which shifted approximately half a cycle in phase according to which target was attended. In the post-target period, temporal attention to the first target transiently modulated the SSVER shortly after target onset. Thus, temporal attention dynamically modulates visual cortical responses via both periodic pre-target and transient post-target mechanisms to prioritize sensory information at precise moments.
Concepts for a Muon Accelerator Front-End

We present a muon capture front-end scheme for muon based applications. In this Front-End design, a proton bunch strikes a target and creates secondary pions that drift into a capture channel, decaying into muons. A series of rf cavities forms the resulting muon beams into a series of bunches of differerent energies, aligns the bunches to equal central energies, and initiates ionization cooling. We also discuss the design of a chicane system for the removal of unwanted secondary particles from the muon capture region and thus reduce activation of the machine. With the aid of numerical simulations we evaluate the performance of this Front-End scheme as well as study its sensitivity against key parameters such as the type of target, the number of rf cavities and the gas pressure of the channel.
A proposed methodology for trip recovery training without a specialized treadmill

Falls are the leading cause of accidental injuries among adults aged 65 years and older. Perturbation-based balance training is a novel exercise-based fall prevention intervention that has shown promise in reducing falls. Trip recovery training is a form of perturbation-based balance training that targets trip-induced falls. Trip recovery training typically requires the use of a specialized treadmill, the cost of which may present a barrier for use in some settings. The goal of this paper is to present a methodology for trip recovery training that does not require a specialized treadmill. A trial is planned in the near future to evaluate its effectiveness. If effective, non-treadmill trip recovery training could provide a lower cost method of perturbation-based balance training, and facilitate greater implementation outside of the research environment.
Heterochromatin in the fungal plant pathogen, Zymoseptoria tritici: Control of transposable elements, genome plasticity and virulence

Heterochromatin is a repressive chromatin state that plays key roles in the functional organisation of eukaryotic genomes. In fungal plant pathogens, effector genes that are required for host colonization tend to be associated with heterochromatic regions of the genome that are enriched with transposable elements. It has been proposed that the heterochromatin environment silences effector genes in the absence of host and dynamic chromatin remodelling facilitates their expression during infection. Here we discuss this model in the context of the key wheat pathogen, Zymoseptoria tritici. We cover progress in understanding the deposition and recognition of heterochromatic histone post translational modifications in Z. tritici and the role that heterochromatin plays in control of genome plasticity and virulence.
Screening the immune-related circRNAs and genes in mice of spinal cord injury by RNA sequencing

Spinal cord injury (SCI) is a pathological condition that leading to serious nerve damage, disability and even death. Increasing evidence have revealed that circular RNAs (circRNAs) and mRNA are widely involved in the regulation of the pathological process of neurological diseases by sponging microRNAs (miRNAs). Nevertheless, the potential biological functions and regulatory mechanisms of circRNAs in the subacute stage of SCI remain unclear. We analyzed the expression and regulatory patterns of circRNAs and mRNAs in SCI mice models using RNA-sequencing and bioinformatics analysis. A total of 24 circRNAs and 372 mRNAs were identified to be differentially expressed. Then we identifying the immune-related genes (IRGs) from them. The protein-protein interaction network were constructed based on the STRING database and Cytoscape software. Furthermore, Go and KEGG enrichment analysis were conducted to predict the functions of the IRGs and host genes of DECs. These findings will contribute to elucidate the pathophysiology of SCI and provide effective therapeutic targets for SCI patients.
Ferroptosis increases obesity: Crosstalk between adipocytes and the neuroimmune system

Ferroptosis requires not only the accumulation of iron ions, but also changes in many ferroptosis-related regulators, including a decrease in GPX4 and inhibition of SLC7A11 for classical ferroptosis, a deletion of FSP1 or GCH1. Surprisingly, adipose tissue (AT) in the obesity conditions is also accompanied by iron buildup, decreased GSH, and increased ROS. On the neurological side, the pro-inflammatory factor released by AT may have first caused ferroptosis in the vagus nerve by inhibiting of the NRF2-GPX4 pathway, resulting in disorders of the autonomic nervous system. On the immune side, obesity may cause M2 macrophages ferroptosis due to damage to iron-rich ATMs (MFehi) and antioxidant ATMs (Mox), and lead to Treg cells ferroptosis through reductions in NRF2, GPX4, and GCH1 levels. At the same time, the reduction in GPX4 may also trigger the ferroptosis of B1 cells. In addition, some studies have also found the role of GPX4 in neutrophil autophagy, which is also worth pondering whether there is a connection with ferroptosis. In conclusion, this review summarizes the associations between neuroimmune regulation associated with obesity and ferroptosis, and on the basis of this, highlights their potential molecular mechanisms, proposing that ferroptosis in one or more cells in a multicellular tissue changes the fate of that tissue.
Pre-operative anemia was associated with all-cause mortality in patients with vertebral fracture who underwent percutaneous vertebroplasty

Purpose We investigated the association between pre-operative anemia and long-term all-cause mortality in patients with vertebral fracture who underwent a vertebroplasty. Materials and methods We retrospectively selected patients who were admitted for vertebroplasty for vertebral compression fracture between 2013 and 2020. Patients who had pathologic fractures or had no assessment of bone mineral density were excluded. Relevant information was collected from electronic medical records. Patients’ survival status was confirmed at the end of March 2021. Cox-proportional hazard models were conducted to examine the effects of anemia (<12 g/dL vs. ≥12 g/dL) and pre-operative hemoglobin levels (as a continuous variable) on all-cause mortality with multivariate adjustments. Results A total of 167 patients were analyzed (mean age 75.8 ± 9.3 years, male 25.7%). After a median follow-up duration of 2.1 years, pre-operative anemia (hemoglobin <12 g/dL vs. ≥12 g/dL) was independently associated with a higher risk of all-cause mortality (hazard ratio 2.762, 95% CI 1.184 to 6.442, p = 0.019). An increase in pre-operative hemoglobin was associated with a lower risk of all-cause mortality after multivariate adjustment (hazard ratio 0.775, 95% CI 0.606 to 0.991, p = 0.042). Conclusion Pre-operative anemia (<12 g/dL) was independently associated with survival outcome among patients with vertebral compression fractures who underwent vertebroplasty. Our findings highlight anemia as a risk factor of long-term mortality in this elderly surgical population.
Performance measures to benchmark the grasping, manipulation, and assembly of deformable objects typical to manufacturing applications

The National Institute of Standards and Technology is developing performance tests and associated artifacts to benchmark research in the area of robotic assembly. Sets of components consistent with mechanical assemblies including screws, gears, electrical connectors, wires, and belts are configured for assembly or disassembly using a task board concept. Test protocols accompany the task boards and are designed to mimic low-volume, high-mixture assembly challenges typical to small and medium sized manufacturers. In addition to the typical rigid components found in assembled products, the task boards include many non-rigid component operations representative of wire harness and belt drive assemblies to support research in the area of grasping and manipulation of deformable objects, an area still considered to be an emerging research problem in robotics. A set of four primary task boards as well as competition task boards are presented as benchmarks along with scoring metrics and a method to compare robot system assembly times with human performance. Competitions are used to raise awareness to these benchmarks. Tools to progress and compare research are described along with emphasis placed on system competition-based solutions to grasp and manipulate deformable task board components.
Cellular memory of rapid growth is sensitive to nutrient depletion during starvation

Bacteria frequently encounter nutrient fluctuations in natural environments, yet we understand little about their ability to maintain physiological memory of previous food sources. Starvation is a particularly acute case, in which cells must balance adaptation to stresses with limited nutrient supply. Here, we show that Escherichia coli cells immediately accelerate and decelerate in growth upon transitions from spent to fresh media and vice versa, respectively, and memory of rapid growth can be maintained for many hours under constant flow of spent medium. However, after transient exposure of stationary-phase cells to fresh medium, subsequent aerobic incubation in increasingly spent medium led to lysis and limited growth when rejuvenated in fresh medium. Growth defects were avoided by incubation in anaerobic spent medium or water, suggesting that defects were caused by respiration during the process of nutrient depletion in spent medium. These findings highlight the importance of respiration for stationary phase survival and underscore the broad range of starvation outcomes depending on environmental history.
Memory function performance in individuals classified as overweight, obese, and normal weight

Evidence accumulated to date about the relationship between cognitive impairments and adults who are overweight and obese suggests that excess weight has a great impact on memory function. Nevertheless, most of the literature has focused only on studying the influences on working memory and episodic memory. This study aimed to examine the potential associations of clinical and anthropometric measures [body mass index (BMI), WHR, body fat, visceral fat, muscle mass, and hypertension] with six memory domains, including contextual memory, short-term visual memory, short-term memory, non-verbal memory, short-term phonological memory, and working memory, in a sample of 124 individuals classified as overweight (n = 33), obese (n = 53), and normal weight (n = 38). The results obtained showed that, after controlling for employment situations, people classified as obese had poorer short-term phonological memory and working memory than those with normal weights. Bivariate correlations showed that measures of weight, BMI, waist–hip ratio index, body fat, and visceral fat were inversely associated with memory function. However, muscle mass was not a significant predictor of memory function. Higher systolic blood pressure was also associated with worse memory function. The study provides evidence of the importance of adiposity in health and memory function.
Socio-technical context for insertable devices

In this article, we show that voluntarily inserting devices inside the body is contested and seek to understand why. This article discusses insertables as a source of contestation. To describe and understand the social acceptability, reactions toward, and rhetoric surrounding insertable devices, we examine (i) the technical capabilities of insertable devices (the technical context), (ii) human reactions toward insertables (the social context), and (iii) the regulatory environment. The paper offers explanations to the misperceptions about insertables.
Pathogenic bacteria significantly increased under oxygen depletion in coastal waters: A continuous observation in the central Bohai Sea

The spread of pathogenic bacteria in coastal waters endangers the health of the local people and jeopardizes the safety of the marine environment. However, their dynamics during seasonal hypoxia in the Bohai Sea (BHS) have not been studied. Here, pathogenic bacteria were detected from the 16S rRNA gene sequencing database and were used to explore their dynamics and driving factors with the progressively deoxygenating in the BHS. Our results showed that pathogenic bacteria were detected in all samples, accounting for 0.13 to 24.65% of the total number of prokaryotic sequences in each sample. Pathogenic Proteobacteria was dominated in all samples, followed by Firmicutes, Actinobacteria, Tenericutes, and Bacteroidetes, etc. β-diversity analysis showed that pathogenic bacteria are highly temporally heterogeneous and regulated by environmental factors. According to RDA analysis, these variations may be influenced by salinity, ammonia, DO, phosphate, silicate, and Chl a. Additionally, pathogenic bacteria in surface water and hypoxia zone were found to be significantly separated in August. The vertical distribution of pathogenic bacterial communities is influenced by several variables, including DO and nutrition. It is noteworthy that the hypoxia zones increase the abundance of certain pathogenic genera, especially Vibrio and Arcobacter, and the stability of the pathogenic bacterial community increased from May to August. These phenomena indicate that the central Bohai Sea is threatened by an increasingly serious pathogenic community from May to August. And the developing hypoxia zone in the future may intensify this phenomenon and pose a more serious threat to human health. This study provides new insight into the changes of pathogenic bacteria in aquatic ecosystems and may help to make effective policies to control the spread of pathogenic bacteria.