Explore the vast range of titles available.

Emerging memories have been developed as new physical infrastructures for hosting neural networks owing to their low-power analog computing characteristics. However, accurately and efficiently programming devices in an analog-valued array is still largely limited by the intrinsic physical non-idealities of the devices, thus hampering their applications in in-situ training of neural networks. Here, we demonstrate a passive electrochemical memory (ECRAM) array with many important characteristics necessary for accurate analog programming. Different image patterns can be open-loop and serially programmed into our ECRAM array, achieving high programming accuracies without any feedback adjustments. The excellent open-loop analog programmability has led us to in-situ train a bilayer neural network and reached software-like classification accuracy of 99.4% to detect poisonous mushrooms. The training capability is further studied in simulation for large-scale neural networks such as VGG-8. Our results present a new solution for implementing learning functions in an artificial intelligence hardware using emerging memories. Memory devices with open-loop analog programmability are highly desired in training tasks. Here, the authors developed an electrochemical memory array that can be accurately programmed without any feedback, offering unique capabilities for training.

Visceral adipose tissue (VAT)—fat stored around the internal organs—has been suggested as an independent risk factor for cardiovascular and metabolic disease1–3, as well as all-cause, cardiovascular-specific and cancer-specific mortality4,5. Yet, the contribution of genetics to VAT, as well as its disease-related effects, are largely unexplored due to the requirement for advanced imaging technologies to accurately measure VAT. Here, we develop sex-stratified, nonlinear prediction models (coefficient of determination = 0.76; typical 95% confidence interval (CI) = 0.74–0.78) for VAT mass using the UK Biobank cohort. We performed a genome-wide association study for predicted VAT mass and identified 102 novel visceral adiposity loci. Predicted VAT mass was associated with increased risk of hypertension, heart attack/angina, type 2 diabetes and hyperlipidemia, and Mendelian randomization analysis showed visceral fat to be a causal risk factor for all four diseases. In particular, a large difference in causal effect between the sexes was found for type 2 diabetes, with an odds ratio of 7.34 (95% CI = 4.48–12.0) in females and an odds ratio of 2.50 (95% CI = 1.98–3.14) in males. Our findings bolster the role of visceral adiposity as a potentially independent risk factor, in particular for type 2 diabetes in Caucasian females. Independent validation in other cohorts is necessary to determine whether the findings can translate to other ethnicities, or outside the UK.

Macrophages originating from the yolk sac or bone marrow play essential roles in tissue homeostasis and disease. Bone marrow-derived monocytes differentiate into Ly6C hi and Ly6C lo macrophages according to the differential expression of the surface marker protein Ly6C. Ly6C hi and Ly6C lo cells possess diverse functions and transcriptional profiles and can accelerate the disease process or support tissue repair and reconstruction. In this review, we discuss the basic biology of Ly6C hi and Ly6C lo macrophages, including their origin, differentiation, and phenotypic switching, and the diverse functions of Ly6C hi and Ly6C lo macrophages in homeostasis and disease, including in injury, chronic inflammation, wound repair, autoimmune disease, and cancer. Furthermore, we clarify the differences between Ly6C hi and Ly6C lo macrophages and their connections with traditional M1 and M2 macrophages. We also summarize the limitations and perspectives for Ly6C hi and Ly6C lo macrophages. Overall, continued efforts to understand these cells may provide therapeutic approaches for disease treatment.

Although previous studies have recorded that tropical cyclones cause a significant increase in chlorophyll a concentration (Chl-a), most of these results were only based on surface Chl-a observed by satellite data. Using satellite, reanalysis and model data, this study investigated the response of the upper ocean and sea surface Chl-a to three different levels of tropical cyclones in the South China Sea. In our results, the severe tropical storm (STS) did not cause an increase in surface Chl-a or depth-integrated Chl-a in the short term (i.e., ~2 days); the typhoon (TY) increased the surface Chl-a from 0.12 mg·m−3 to 0.15 mg·m−3 in the short term, but the depth-integrated Chl-a did not increase significantly; the super typhoon (STY) caused the surface Chl-a to increase from 0.15 mg·m−3 to 0.37 mg·m−3 in the short term, and also increased the depth-integrated Chl-a from 40.41 mg·m−2 to 42.59 mg·m−2. These results suggest that the increase in the surface Chl-a after TY and STY were primarily caused by physical processes (e.g., vertical mixing). However, the increase in the depth-integrated Chl-a of STY may be due to the entrainment of both nutrients and phytoplankton through upwelling and turbulent mixing under the influence of STY.

Background Medical information has rapidly increased on the internet and has become one of the main targets of search engine use. However, medical information on the internet is subject to the problems of quality and accessibility, so ordinary users are unable to obtain answers to their medical questions conveniently. As a solution, researchers build medical question answering (QA) systems. However, research on medical QA in the Chinese language lags behind work on English-based systems. This lag is mainly due to the difficulty of constructing a high-quality knowledge base and the underutilization of medical corpora in the Chinese language. Results This study developed an end-to-end solution to implement a medical QA system for the Chinese language with low cost and time. First, we created a high-quality medical knowledge graph from hospital data (electronic health/medical records) in a nearly automatic manner that trained a supervised model based on data labeled using bootstrapping techniques. Then, we designed a QA system based on a memory-based neural network and attention mechanism. Finally, we trained the system to generate answers from the knowledge base and a QA corpus on the internet. Conclusions Bootstrapping and deep neural network techniques can construct a knowledge graph from electronic health/medical records with satisfactory precision and coverage. Our proposed context bridge mechanisms perform training with a variety of language features. Our QA system can achieve state-of-the-art quality in answering medical questions with constrained topics. As we evaluated, complex Chinese language processing techniques, such as segmentation and parsing, were not necessary for practice and complex architectures were not necessary to build the QA system. Lastly, we created an application using our method for internet QA usage.

Harmful algal blooms (HABs) induced by eutrophication is becoming a serious global environmental problem affecting public health and aquatic ecological sustainability. A novel strategy for the utilization of biomass from HABs was developed by converting the algae cells into hollow mesoporous bio-hydrochar microspheres via hydrothermal carbonization method. The hollow microspheres were used as microreactors and carriers for constructing CaO 2 core-mesoporous shell-CaO 2 shell microspheres (OCRMs). The CaO 2 shells could quickly increase dissolved oxygen to extremely anaerobic water in the initial 40 min until the CaO 2 shells were consumed. The mesoporous shells continued to act as regulators restricting the release of oxygen from CaO 2 cores. The oxygen-release time using OCRMs was 7 times longer than when directly using CaO 2 . More interestingly, OCRMs presented a high phosphate removal efficiency (95.6%) and prevented the pH of the solution from rising to high levels in comparison with directly adding CaO 2 due to the OH − controlled-release effect of OCRMs. The distinct core-double-shell micro/nanostructure endowed the OCRMs with triple functions for oxygen controlled-release, phosphorus removal and less impact on water pH. The study is to explore the possibility to prepare smarter bio-hydrochar materials by utilizing algal blooms.

Background Geriatric hip fractures pose a significant health burden, and inflammation may play a role in the short- and long-term prognosis. However, the prognostic significance of hematologic inflammatory markers in geriatric patients with fractures is not understood. The aim of this systematic review and meta-analysis was to assess the prognostic implications of systemic inflammatory markers on the long-term mortality of older patients with hip fractures. Methods PubMed, EMBASE, and Cochrane CENTRAL were searched from inception to December 19, 2023. Prospective, retrospective cohort, and case–control studies investigating the prognostic impact of hematologic inflammatory markers on mortality after hip fracture were eligible. Pooled hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) were calculated to determine the associations between the markers and mortality risk, with heterogeneity assessed by I 2 statistic. The quality of the studies was appraised using the Newcastle–Ottawa Scale. Results Ultimately, 7 retrospective studies involving a total of 7212 patients were included. The meta-analysis revealed that the neutrophil-to-lymphocyte ratio (NLR) (HR = 1.04, 95% CI 1.02–1.08), systemic immune–inflammatory index (SII) (HR = 1.03, 95% CI 1.01–1.05), and red cell distribution width (RDW) (HR = 1.07, 95% CI 1.01–1.14) independently correlated with increased long-term mortality. Conclusions Elevated NLR, SII, and RDW are independently associated with increased long-term mortality in older patients with hip fractures. These findings imply the potential value of incorporating these inflammatory indicators to aid in prognostic stratification of geriatric patients with hip fractures.

Bandpass filters play a core role in ECoG signal processing. Commonly used frequency bands such as alpha, beta, and gamma bands can reflect the normal rhythm of the brain. However, the universally predefined bands might not be optimal for a specific task. Especially the gamma band usually covers a wide frequency span (i.e., 30–200 Hz) which can be too coarse to capture features that appear in narrow bands. An ideal option is to find the optimal frequency bands for specific tasks in real-time and dynamically. To tackle this problem, we propose an adaptive band filter that selects the useful frequency band in a data-driven way. Specifically, we leverage the phase-amplitude coupling (PAC) of the coupled working mechanism of synchronizing neuron and pyramidal neurons in neuronal oscillations, in which the phase of slower oscillations modulates the amplitude of faster ones, to help locate the fine frequency bands from the gamma range, in a task-specific and individual-specific way. Thus, the information can be more precisely extracted from ECoG signals to improve neural decoding performance. Based on this, an end-to-end decoder (PACNet) is proposed to construct a neural decoding application with adaptive filter banks in a uniform framework. Experiments show that PACNet can improve neural decoding performance universally with different tasks.

The thalamic reticular nucleus (TRN), the major source of thalamic inhibition, regulates thalamocortical interactions that are critical for sensory processing, attention and cognition 1 – 5 . TRN dysfunction has been linked to sensory abnormality, attention deficit and sleep disturbance across multiple neurodevelopmental disorders 6 – 9 . However, little is known about the organizational principles that underlie its divergent functions. Here we performed an integrative study linking single-cell molecular and electrophysiological features of the mouse TRN to connectivity and systems-level function. We found that cellular heterogeneity in the TRN is characterized by a transcriptomic gradient of two negatively correlated gene-expression profiles, each containing hundreds of genes. Neurons in the extremes of this transcriptomic gradient express mutually exclusive markers, exhibit core or shell-like anatomical structure and have distinct electrophysiological properties. The two TRN subpopulations make differential connections with the functionally distinct first-order and higher-order thalamic nuclei to form molecularly defined TRN–thalamus subnetworks. Selective perturbation of the two subnetworks in vivo revealed their differential role in regulating sleep. In sum, our study provides a comprehensive atlas of TRN neurons at single-cell resolution and links molecularly defined subnetworks to the functional organization of thalamocortical circuits. A study integrating single-cell RNA-sequencing and electrophysiology data shows that in mouse, the cellular repertoire of the thalamic reticular nucleus is characterized by a transcriptomic gradient defined at its extremes by mutually exclusive expression of Spp1 and Ecel1 , providing insights into the organizational principles underlying the divergent functions of this brain region.