Search

The microRNAs and phasiRNAs of plant are small non-coding RNAs with important functions through regulating gene expression at the post-transcriptional level. However, identifying miRNAs, phasiRNAs and their target genes from numerous sequencing raw data requires multiple software and command-line operations, which are time-consuming and labor-intensive for non-model plants. Therefore, we present CsMPDB (miRNAs and phasiRNAs database of Camellia sinensis), an interactive web application with multiple analysis modules developed to visualize and explore miRNA and phasiRNA in tea plants based on 259 sRNA-seq samples and 24 degradome-seq samples in NCBI. The source code for the CsMPDB was written in R/shiny. It is compatible, extendable, and portable to be easily set up on different operating systems, and can be accessed at http://myshiny.cpolar.io/CsMPDB. This application plays an important role in accelerating the functional study of sRNAs in the transcriptional regulation of tea plants, and has important reference value for the development of sRNA databases of other species., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025 Elsevier B.V. All rights reserved.)

tRNA-derived small RNA (tsRNA) is a recently discovered small non-coding RNA (ncRNA) molecule that widely exists in prokaryotic and eukaryotic transcriptomes and is produced by specific cleavage of mature tRNA or precursor tRNA. In recent years, with the development of high-throughput sequencing technology, tsRNA has been found to have a variety of biological functions, including gene expression regulation, stress signal activation, etc. In addition, it has been found that these molecules are abnormally expressed in various diseases and participate in various pathological processes, which play an important role. At present, more and more studies have shown that the expression level of tsRNA changes significantly during the development of neurogenetic diseases. This review provides an overview of the classification and biological functions of tsRNAs, with a particular emphasis on their roles in neurogenetic disorders and their potential as diagnostic biomarkers and therapeutic targets. Despite the nascent stage of tsRNA research, their relevance to the diagnosis and treatment of neurogenetic diseases warrants further investigation., Competing Interests: Declarations. Ethics Approval and Consent to Participate: Not applicable. Consent for Publication: Not applicable. Competing Interests: The authors declare no competing interests., (© 2025. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The precise spatiotemporal control of reactive oxygen species (ROS) generation and scavenging remains pivotal for infected wound healing. However, conventional nanozymes fail to adaptively regulate ROS dynamics across inflammatory and proliferative phases. A near-infrared (NIR)-activated inverse oxide/alloy-structured nanozyme (Co 7 Fe 3 /ZnO@C) is developed, featuring enzymatic cascade activities to tune ROS homeostasis through synergistic chemodynamic (CDT), photodynamic (PDT), and photothermal (PTT) therapies. The nanozyme orchestrates a self-regulated cascade: peroxidase (POD)-like activity initially generates bactericidal hydroxyl radicals in acidic wounds, while subsequent NIR triggers hot electron transfer from Co 7 Fe 3 to ZnO, facilitating synchronized superoxide dismutase (SOD)-like, catalase (CAT)-like and hydroxyl radical antioxidant capacity (HORAC) activities to scavenge residual ROS. This cascaded network dynamically balances ROS production (POD) and scavenging (NIR-driven SOD/CAT/HORAC), eradicating bacteria while resolving inflammation. In vitro/vivo studies have shown that the proposed method for maintaining ROS homeostasis can markedly enhance the rate of wound healing by the regulation of the inflammatory environment within the injured tissue and the facilitation of rapid re-epithelialization. This work provides an intelligent nanozyme platform that simulates the function of natural enzymes and constructs a cascade reaction strategy to balance the antibacterial and anti-inflammatory demands in the wound microenvironment., (© 2025 Wiley‐VCH GmbH.)

The microstructure of 40CrMnMoA during hot forging determines its macroscopic mechanical properties. Dynamic recrystallization (DRX) behavior is commonly used to refine grains and improve the microstructure of materials; therefore, it is important to be able to predict mechanical behavior during hot forging and the microstructure evolution during dynamic recrystallization. In order to accurately determine the DRX model parameters of 40CrMnMoA steel, an inverse optimization method is proposed in this work. The uniaxial isothermal compression experiment of 40CrMnMoA steel was carried out on a Gleeble-1500D thermal simulation tester (Dynamic Systems Inc. (DSI), Poestenkill, NY, USA) under the temperature range of 900~1200 °C and the strain rate range of 0.005 to 5 s -1 . Based on the true stress-strain data obtained by a compression test, the DRX model of 40CrMnMoA was initially established using the traditional averaging method. Subsequently, the DRX model parameters calculated by the conventional averaging method were used as the initial values, the mean-square error between the experimental and calculated values of the DRX volume fraction was set as the objective function, and the DRX model parameters were optimized by the adaptive simulated annealing (ASA) algorithm. By comparing the correlation coefficient R , average absolute relative error ( AARE ), and the root mean square error ( RMSE ) of the predicted DRX percentage with the experimental values before and after optimization, it was found that the optimized model achieved an R -value of 0.992, with AARE and RMSE decreased by 34% and 2%, respectively, which verified the accuracy of the optimized DRX model. Through the program's secondary development, the optimized DRX model of 40CrMnMoA was integrated into finite element software Forge ® 3.2 to simulate the isothermal compression process. The comparison between grain size from the central region of simulation results and actual samples revealed that the relative error is less than 3%. This result demonstrated that the inverse optimization method can accurately identify the DRX model parameters of 40CrMnMoA alloy steel., Competing Interests: The authors declare no conflicts of interest.

For quantum-dot light-emitting diodes (QLED), electrical aging commonly introduces collective aging sources across all layers, making it difficult to isolate the impact of each layer on electroluminescence (EL) degradation. In this work, a layer-selective aging method using active photoexcitation is proposed, in which the photoexcitation wavelength is used to selectively target specific layers for exciton generation, and an electrical bias is applied to induce photocurrent and create charges. An iterative aging-sampling (A-S) procedure is used to link aging conditions to EL degradation. It is found that photo-aging leads to strong but reversible quenching of EL intensity, which is interpreted as being caused by electrical field screening due to trapped charges in the quantum dot (QD) layer and requires electrical activation before the sampling (S) step. Repeated A-S cycles in a model red QLED system show that excitations in the QD layer result in negligible EL degradation. In contrast, aging of the hole-transport (HT) layer enables an acceleration of aging rate by 3 orders of magnitude compared to standard aging and is interpreted as a result of photo-charge accumulation in the HT layer, particularly related to electrons and low electron mobility., (© 2025 Wiley‐VCH GmbH.)

The ever-growing interest in MXenes has been driven by their distinct electrical, thermal, mechanical, and optical properties. In this context, further revealing their physicochemical attributes remains the key frontier of MXene materials. Herein, we report the anisotropic localized surface plasmon resonance (LSPR) features in Ti 3 C 2 T x MXene as well as site-selective photocatalysis enabled by the photophysical anisotropy. Both experimental and theoretical studies provide direct evidence of the occurrence of transverse and longitudinal dipolar plasmon resonance modes, respectively, driven by in-plane and out-of-plane vibrations of the two-dimensional (2D) MXene nanoflakes. Wavelength-controlled excitation of the two LSPR modes is demonstrated to activate either the on-edge or the in-plane active sites for plasmonic charge carrier-induced site-selective catalysis. Our findings uncover the presence as well as the mechanism of the anisotropic plasmon resonance in nonmetallic 2D nanomaterials and provide intriguing design principles for next-generation plasmonic nanocatalysts.

Introduction: Timely and accurate diagnosis is crucial for the effective treatment and prevention of brucellosis. Current serological diagnostics, primarily based on lipopolysaccharide (LPS), suffer from cross-reactivity with other Gram-negative bacteria, which limits their specificity. Periplasmic protein 26 (BP26), a highly immunogenic antigen found in Brucella , has emerged as a promising alternative for enhancing diagnostic specificity. This study aimed to develop and evaluate a competitive enzyme-linked immunosorbent assay (C-ELISA) utilizing monoclonal antibodies against BP26 for the diagnosis of human brucellosis, thereby providing a more accurate and specific diagnostic approach., Methods: The study produced monoclonal antibody (mAb) against the BP26 protein through traditional mouse hybridoma technology and developed the C-ELISA method, and compared with a C-ELISA method based on LPS mAb. The detection performance was validated through the analysis of 190 human serum samples, which included 95 brucellosis serum samples and 95 negative serum samples collected by the Xuzhou Center for Disease Control and Prevention, and a comparative analysis was conducted on the diagnostic efficacy of indirect ELISA for brucellosis using both BP26 and LPS-based methods., Results: The BP26 mAb based C-ELISA achieved 100% sensitivity and specificity in detecting human brucellosis, significantly outperforming the C-ELISA based LPS mAb. Furthermore, the accuracy of the indirect enzyme-linked immunosorbent assay (I-ELISA) using BP26 protein was 98.95%, compared to an accuracy of LPS diagnosis was 99.47%. These results indicated that the BP26 mAb can effectively and accurately detected human brucellosis infections., Conclusion: This study successfully developed and evaluated a BP26 protein-based C-ELISA method for diagnosing human brucellosis, establishing a foundation for identifying alternative diagnostic antigens for brucellosis., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2025 Xie, Lin, Guo, Qi, Zhao, Pei, Chen, Wu, Wang, Yao and Yin.)

The increasing demand for air pollution control has driven the application of low-cost sensors (LCS) in air quality monitoring, enabling higher observation density and improved air quality predictions. However, the inherent limitations in data quality from LCS necessitate the development of effective methodologies to optimize their application. This study established a hybrid framework to enhance the accuracy of spatiotemporal predictions of PM 2.5 , standard instrument measurements were employed as reference data for the remote calibration of LCS. To account for local emission characteristics, the calibration model was trained using statistical values from LCS during periods of reduced anthropogenic emissions. This calibration approach significantly improved data quality, increasing R 2 values of LCS data from 0.60 to 0.85. Subsequently, an advanced predictive model, STXGBoost, was developed, combining Kriging interpolation technology with high-density LCS data to integrate temporal trends and geographic spatial correlations. The STXGBoost model effectively captured the spatiotemporal variability of PM 2.5 data, producing accurate and high spatiotemporal resolution PM 2.5 prediction maps, with R 2 values of 0.96, 0.92, and 0.89 for 1-h, 4-h, and 48-h predictions, respectively. These findings demonstrate the feasibility of generating high-resolution urban air pollution maps by integrating high-density ground monitoring data with advanced computational approaches. This framework provides valuable support for precise management and informed decision-making in urban atmospheric environments., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

With China's proposed carbon reduction goals, many carbon monitoring pilot city projects have been launched, involving greenhouse gas (GHG) inverse estimate analysis based on GHG observations. For the evaluation of emissions estimates in a targeted urban area, the contributions of extra-urban fluxes on urban GHG observations must be excluded, especially for core cities within urban agglomerations, which face more severe emission interference from adjacent cities. In this study, we quantified the impact of external emissions on urban carbon dioxide (CO 2 ) mole fraction observations across different seasons in the central downtown area of Zhengzhou, a core city of the Central Plains Urban Agglomeration in China. Results showed that 60% of the CO 2 enhancement from the 500-km square area including the city originated outside the core urban area in autumn and winter, predominantly originating from far-field sources (>50 km) in the northeast, west, and northwest of Zhengzhou. To design an optimal monitoring network that accurately accounts for CO 2 mole fractions entering the urban domain of interest, three different selection methods (distance, meteorological trajectory, and multiple regression) were used to select background station locations, and the resulting background values were evaluated through the application of observing system simulation experiments, including synthetic flux inverse estimate. Results indicated that the background stations selected by meteorological trajectories more effectively captured CO 2 variability, introducing the smallest errors to inverse estimate flux (-8%). This study provides a valuable reference for designing background monitoring stations in dense urban agglomerations, thereby improving the accuracy of high-resolution urban GHG emission inverse estimates., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

A differential scanning calorimeter (DSC) is widely used for measuring the thermal properties of phase-change materials (PCMs). Optimizing test conditions based on material characteristics is essential for accurate results. This study investigates the effects of experimental parameters, including sample mass, heating rate, measurement modes, and atmosphere flow rate, on the phase-change enthalpy and phase-change temperature results. The findings indicate that variations in sample mass and heating rate lead to significant changes in phase-change temperatures, while an increase in purge gas flow rate reduces the phase-change enthalpy of the PCM. Based on the measurements, this study optimizes the DSC parameters and provides a reference for the accurate measurement of paraffin-based phase-change materials.

Parasitic emission or leakage emission caused by electron leakage to a hole transport layer in quantum-dot light-emitting diodes (QLEDs) critically impacts device efficiency and operational stability. The buildup dynamics of such emission channels, however, was insufficiently researched. Herein, we investigate transient electroluminescence dynamics of leakage emission in red/green/blue (R/G/B) QLEDs and reveal notable contrast for R and G. In RQLEDs, leakage emission exhibits delayed turning-on than primary emission, which is attributed to much slower filling up from lower-energy electron states and the initial quenching by nonradiative recombination with trapped holes. For GQLEDs, leakage emission turns on much more concurrently, and emission preferably starts from higher energy states. For R/G QLEDs, under varied offset voltage modulation, the current efficiency of primary emission is invert-correlated to leakage emission, reconfirming leakage emission as a loss indicator.

Cloud-based training and edge-based inference modes for Artificial Intelligence of Medical Things (AIoMT) applications suffer from accuracy degradation due to physiological signal variations among patients. On-chip learning can overcome this issue by online adaptation of neural network parameters for user-specific tasks. However, existing on-chip learning processors have limitations in terms of versatility, resource utilization, and energy efficiency. We propose HybMED, which is a novel neural signal processor that supports on-chip hybrid neural network training using a composite direct feedback alignment-based paradigm. HybMED is suitable for general-purpose health monitoring AIoMT devices. It improves resource utilization and area efficiency by the reconfigurable homogeneous core with heterogeneous data flow and enhances energy efficiency by exploiting sparsity at different granularities. The chip was fabricated by TSMC 40nm process and tested in multiple physiological signal processing tasks, demonstrating an average improvement in accuracy of 41.16% following online few-shot learning. The chip demonstrates an area efficiency of 1.17 GOPS/mm 2 and an energy efficiency of 1.58 TOPS/W. Compared to the previous state-of-the-art physiological signal processors with on-chip learning, the chip achieves a 65 × improvement in area efficiency and 1.48 × improvement in energy efficiency, respectively.

A high purine diet emerges as a significant risk factor for hyperuricemia, and this diet may potentiate hyperuricemia nephropathy. Despite this, the mechanistic underpinnings of kidney damage precipitated by a high purine diet warrant further research. In the current investigation, a hyperuricemia nephropathy rat model was developed through induction via a high purine diet. Subsequently, metabolomic and proteomic analyses were employed to explore the metabolic characteristics of the kidney and shed light on the corresponding mechanistic pathway. Finally, fluorescence imaging and 18 F-fluorodeoxyglucose positron emission tomography computed tomography ( 18 F-FDG-PET/CT) were utilized to validate the overarching energy metabolism state. The results revealed extensive damage to the kidneys of hyperuricemia nephropathy rats following eight weeks of induction via a high purine diet. We used metabolomic to found that acyl carnitines and L-carnitine reduced in high purine diet group, indicated abnormal fatty acid metabolism. Irregularities were discerned in metabolites and enzymes associated with fatty acid β-oxidation, glycolysis, and oxidative phosphorylation within the kidneys of hyperuricemia nephropathy rats by proteomic and co-expression network analysis. The application of fluorescence imaging and 18 F-FDG-PET/CT substantiated the inhibition of fatty acid β-oxidation and glycolysis within the kidneys of hyperuricemia nephropathy rats. On the contrary, a compensatory enhancement in the function of oxidative phosphorylation was observed. Given that the primary energy supply for renal function was derived from the metabolic pathway of fatty acids β-oxidation, any disruption within this pathway could contribute to a deficit in the energy provision to the kidneys. Such an energy insufficiency potentially laid the groundwork for eventual renal impairment. In addition, inhibition of the peroxisome proliferator-activated receptors signaling pathway was noted in the present findings, which could further exacerbate the impediment in the β-oxidation function. In conclusion, it was discerned that a deficiency in energy supply plays a critical role in the kidney injury in hyperuricemia nephropathy rats, thereby endorsing paying more attention to renal energy supply in the therapy of hyperuricemia nephropathy., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors. Published by Elsevier B.V.)

Peach tree is one of the most important fruit trees in the world, and it has been cultivated for more than 7,500 years. In recent years, the genome and population resequencing of peach trees have been published continuously, which has effectively promoted the research of peach tree genetics and breeding. In order to promote the further mining and utilization of these data, we integrated and constructed a comprehensive peach genome and variation database (PPGV, http://peachtree.work/home ). The PPGV contains 10 sets of published peach tree genome data, as well as genomic variation information for 1,378 peach tree samples (the resequencing data of 1,378 samples were aligned with the high-quality genomes of Lovell, CN14 and Chinesecling, respectively, for mutation detection). A variety of useful and flexible tools, such as BLAST, Gene ID Convert, KEGG/GO Enrichment, Primer Design and Gene function, were also specially designed for searching data and assisting in breeding., (© 2024. The Author(s).)

In clinical practice, tumor-targeting diagnosis and immunotherapy against programmed death ligand 1 (PD-L1) have a significant impact. In this research, a PD-L1-antagonistic affibody dimer (Z PD-L1 ) was successfully prepared through Escherichia coli expression system, and conjugated with the photosensitizer of ICG via N-hydroxysuccinimide (NHS) ester to develop a novel tumor-targeting agent (ICG-Z PD-L1 ) for both tumor imaging diagnosis and photothermal-immunotherapy simultaneously. In vitro, Z PD-L1 could specifically bind to PD-L1-positive LLC and MC38 tumor cells, and ICG-Z PD-L1 -mediated photothermal therapy (PTT) also showed excellent phototoxicity to these tumor cells. In vivo, ICG-Z PD-L1 selectively enriched into the PD-L1-positive MC38 tumor tissues, and the high-contrast optical imaging of tumors was obtained. ICG-Z PD-L1 -mediated PTT exhibited a potent anti-tumor effect in vivo due to its remarkable photothermal properties. Furthermore, ICG-Z PD-L1 -mediated PTT significantly induced the immunogenic cell death (ICD) of primary tumors, promoted maturation of dendritic cells (DCs), up-regulated anti-tumor immune response, enhanced immunotherapy, and superiorly inhibited the growth of metastatic tumors. In addition, ICG-Z PD-L1 showed favorable biosafety throughout the brief duration of treatment. In summary, these results suggest that ICG-Z PD-L1 is a multifunctional tumor-targeting drug integrating tumor imaging diagnosis and photothermal-immunotherapy, and has great guiding significance for the diagnosis and treatment of clinical PD-L1-positive tumor patients., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

DNA methyltransferases (Dnmts) are responsible for DNA methylation which influences patterns of gene expression and plays a crucial role in response to environmental changes. In this study, 7 LcDnmt genes were identified in the genome of large yellow croaker (Larimichthys crocea). The comprehensive analysis was conducted on gene structure, protein and location site of LcDnmts. LcDnmt proteins belonged to three groups (Dnmt1, Dnmt2, and Dnmt3) according to their conserved domains and phylogenetic analysis. Although Dnmt3 can be further divided into three sub groups (Dnmt3a, Dnmt3b, and Dnmt3l), there is no Dnmnt3l member in the large yellow croaker. Phylogenetic analysis revealed that the Dnmt family was highly conserved in teleosts. Expression patterns derived from the RNA-seq, qRT-PCR and Western blot analysis revealed that 2 LcDnmt genes (LcDnmt1 and LcDnmt3a2) significantly regulated under salinity stress in the liver, which was found to be dominantly expressed in the intestine and brain, respectively. These two genes may play an important role in the salinity stress of large yellow croaker and represent candidates for future functional analysis. Our results revealed the conservation of Dnmts during evolution and indicated a potential role of Dnmts in epigenetic regulation of response to salinity stress., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Implantable neuromodulation devices have significantly advanced treatments for neurological disorders such as Parkinson's disease, epilepsy, and depression. Traditional open-loop devices like deep brain stimulation (DBS) and spinal cord stimulators (SCS) often lead to overstimulation and lack adaptive precision, raising safety and side-effect concerns. Next-generation closed-loop systems offer real-time monitoring and on-device diagnostics for responsive stimulation, presenting a significant advancement for treating a range of brain diseases. However, the high false alarm rates of current closed-loop technologies limit their efficacy and increase energy consumption due to unnecessary stimulations. In this study, we introduce an artificial intelligence-integrated circuit co-design that targets these issues and using an online demonstration system for closed-loop seizure prediction to showcase its effectiveness. Firstly, two neural network models are obtained with neural-network search and quantization strategies. A binary neural network is optimized for minimal computation with high sensitivity and a convolutional neural network with a false alarm rate as low as 0.1/h for false alarm rejection. Then, a dedicated low-power processor is fabricated in 55 nm technology to implement the two models. With reconfigurable design and event-driven processing feature the resulting application-specific integrated circuit (ASIC) occupies only 5mm 2 silicon area and the average power consumption is 142 μW. The proposed solution achieves a significant reduction in both false alarm rates and power consumption when benchmarked against state-of-the-art counterparts., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Yang, Zhao, Wang, Lin, Hou and Sawan.)

Background: The ILD-GAP scoring system is known to be useful in predicting prognosis in patients with interstitial lung disease (ILD). An elevated monocyte count was associated with increased risks of IPF poor prognosis. We examined whether the ILD-GAP scoring system combined with the monocyte ratio (ILD-GAPM) is superior to the conventional ILD-GAP model in predicting ILD prognosis., Methods: In patients with ILD treated between April 2013 and April 2017, we were retrospectively assessed the relationships between baseline clinical parameters, including age, sex, Charlson Comorbidity Index score (CCIS), ILD diagnosis, blood biomarkers, pulmonary function test results, and disease outcomes. In ILD patients were included idiopathic pulmonary fibrosis (IPF), idiopathic nonspecific interstitial pneumonia (iNSIP), collagen vascular disease-related interstitial pneumonia (CVD-IP), chronic hypersensitivity pneumonitis (CHP), and unclassifiable ILD (UC-ILD). We also assessed the ability to predict prognosis was compared between the ILD-GAP and ILD-GAPM models., Results: A total of 179 patients (mean age, 73 years) were assessed. All of them were taken pulmonary function test, including percentage predicted diffusion capacity for carbon monoxide. ILD patients included 56 IPF cases, 112 iNSIP and CVD-IP cases, 6 CHP cases and 5 UC-ILD cases. ILD-GAPM provided a greater area under the receiver-operating characteristic curve (0.747) than ILD-GAP (0.710) for predicting 3-year ILD-related events. Furthermore, the log-rank test showed that the Kaplan-Meier curves in ILD-GAPM were significantly different by stage (P = 0.015), but not by stage in ILD-GAP (P = 0.074)., Conclusions: The ILD-GAPM model may be a more accurate predictor of prognosis for ILD patients than the ILD-GAP model., (© 2024. The Author(s).)

Pyrocytosis is involved in the development of abdominal aortic aneurysm (AAA), we explored the pyrocytosis-related hub genes in AAA and conducted a diagnostic model based on the pyrocytosis-related genes score (PRGs). A total of 2 bulk RNA-seq (GSE57691 and GSE47472) datasets and pyrocytosis-related genes were integrated to obtain 24 pyrocytosis-related different expression genes (DEGs). The LASSO Cox regression analysis was conducted to filter out 7 genes and further establish the nomogram signature based on the PRGs that exhibited a good diagnosis value. Weighted gene co-expression network analysis (WGCNA) established 14 gene modules and further identified 6 hub genes which were involved in the regulatory process of pyrocytosis in AAA. At the single cell level, we further identified 3 immune cells were highly associated with the pyrocytosis process in AAA. Finally, the cell-cell communication demonstrated that fibroblasts and endothelial cells and myeloid cells maintained close communications. Here, we identified the dysfunctional expressed pyrocytosis-related genes and immune cells in AAA, which provide a comprehensive understanding of the pathogenesis of AAA.

Background: The prevalence of abnormal weight is on the rise, presenting serious health risks and socioeconomic problems. Nonetheless, there is a lack of studies on the medical cost savings that can be attained through the mitigation of abnormal weight. The aim of this study was to estimate the impact of abnormal weight on healthcare costs in China., Methods: The study employed a 4-wave panel data from China Family Panel Studies (CFPS) between 2012 and 2018 (11,209 participants in each wave). Inpatient, non-inpatient and total healthcare costs were outcome variables. Abnormal weight is categorized based on body mass index (BMI). Initially, the two-part model was employed to investigate the impact of overweight/obesity and underweight on healthcare utilisation and costs, respectively. Subsequently, the estimated results were utilised to calculate the overweight/obesity attributable fraction (OAF) and the underweight attributable fraction (UAF)., Results: In 2018, healthcare costs per person for overweight and obese population were estimated to be $607.51 and $639.28, respectively, and the underweight population was $755.55. In comparison to people of normal weight, individuals who were overweight/obese (OR = 1.067, p < 0.05) was more likely to utilise healthcare services. Overweight/obesity attributable fraction (OAF) was 3.90% of total healthcare costs and 4.31% of non-inpatient costs. Overweight/obesity does not result in additional healthcare expenditures for young people but increases healthcare costs for middle-aged adults (OAF = 7.28%) and older adults (OAF = 6.48%). The non-inpatient cost of underweight population was significantly higher than that of normal weight population (β = 0.060,p < 0.1), but the non-inpatient health service utilisation was not significantly affected., Conclusions: Abnormal weight imposes a huge economic burden on individuals, households and the society. Abnormal weight in Chinese adults significantly increased healthcare utilisation and costs, particular in non-inpatient care. It is recommended that government and relevant social agencies provide a better social environment to enhance individual self-perception and promote healthy weight., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Implementing neural networks (NN) on edge devices enables AI to be applied in many daily scenarios. The stringent area and power budget on edge devices impose challenges on conventional NNs with massive energy-consuming Multiply Accumulation (MAC) operations and offer an opportunity for Spiking Neural Networks (SNN), which can be implemented within sub-mW power budget. However, mainstream SNN topologies varies from Spiking Feedforward Neural Network (SFNN), Spiking Recurrent Neural Network (SRNN), to Spiking Convolutional Neural Network (SCNN), and it is challenging for the edge SNN processor to adapt to different topologies. Besides, online learning ability is critical for edge devices to adapt to local environments but comes with dedicated learning modules, further increasing area and power consumption burdens. To alleviate these problems, this work proposed RAINE, a reconfigurable neuromorphic engine supporting multiple SNN topologies and a dedicated trace-based rewarded spike-timing-dependent plasticity (TR-STDP) learning algorithm. Sixteen Unified-Dynamics Learning-Engines (UDLEs) are implemented in RAINE to realize a compact and reconfigurable implementation of different SNN operations. Three topology-aware data reuse strategies are proposed and analyzed to optimize the mapping of different SNNs on RAINE. A 40-nm prototype chip is fabricated, achieving energy-per-synaptic-operation (SOP) of 6.2 pJ/SOP at 0.51 V, and power consumption of 510 μW at 0.45 V. Finally, three examples with different SNN topologies, including SRNN-based ECG arrhythmia detection, SCNN-based 2D image classification, and end-to-end on-chip learning for MNIST digit recognition, are demonstrated on RAINE with ultra-low energy consumption of 97.7nJ/step, 6.28 μJ/sample, and 42.98 μJ/sample respectively. These results show the feasibility of obtaining high reconfigurability and low power consumption simultaneously on a SNN processor.

Versatile and energy-efficient neural signal processors are in high demand in brain-machine interfaces and closed-loop neuromodulation applications. In this paper, we propose an energy-efficient processor for neural signal analyses. The proposed processor utilizes three key techniques to efficiently improve versatility and energy efficiency. 1) Hybrid neural network design: The processor supports artificial neural network (ANN)- and spiking neural network (SNN)-based neuromorphic processing where ANN is used to support the processing of ExG signals and SNN is used for handling neural spike signals. 2) Event-driven processing: The processor can perform always-on binary neural network (BNN)-based event detection with low-energy consumption, and it only switches to the high-accuracy convolutional neural network (CNN)-based recognition mode when events are detected. 3) Reconfigurable architecture: By exploiting the computational similarity of different neural networks, the processor supports critical BNN, CNN, and SNN operations with the same processing elements, achieving significant area reduction and energy efficiency improvement over those of a naive implementation. It achieves 90.05% accuracy and 4.38 uJ/class in a center-out reaching task with an SNN and 99.4% sensitivity, 98.6% specificity, and 1.93 uJ/class in an EEG-based seizure prediction task with dual neural network-based event-driven processing. Moreover, it achieves a classification accuracy of 99.92%, 99.38%, and 86.39% and energy consumption of 1.73, 0.99, and 1.31 uJ/class for EEG-based epileptic seizure detection, ECG-based arrhythmia detection, and EMG-based gesture recognition, respectively.

Low power consumption associated with data transmission and processing of wearable/implantable devices is crucial to ensure the usability of continuous health monitoring systems. In this paper, we propose a novel health monitoring framework where the signal acquired is compressed in a task-aware manner to preserve task-relevant information at the sensor end with a low computation cost. The resulting compressed signals can be transmitted with significantly lower bandwidth, analyzed directly without a dedicated reconstruction process, or reconstructed with high fidelity. Also, we propose a dedicated hardware architecture with sparse Booth encoding multiplication and the 1-D convolution pipeline for the task-aware compression and the analysis modules, respectively. Extensive experiments show that the proposed framework is accurate, with a seizure prediction accuracy of 89.70 % under a signal compression ratio of 1/16. The hardware architecture is implemented on an Alveo U250 FPGA board, achieving a power of 0.207 W at a clock frequency of 100 MHz.

Highly accurate classification methods for multi-task biomedical signal processing are reported, including neural networks. However, reported works are computationally expensive and power-hungry. Such bottlenecks make it hard to deploy existing approaches on edge platforms such as mobile and wearable devices. Gaining motivation from the good performance and high energy-efficiency of spiking neural networks (SNNs), a generic neuromorphic framework for edge healthcare and biomedical applications are proposed and evaluated on various tasks, including electroencephalography (EEG) based epileptic seizure prediction, electrocardiography (ECG) based arrhythmia detection, and electromyography (EMG) based hand gesture recognition. This approach, NeuroCARE, uses a unique sparse spike encoder to generate spike sequences from raw biomedical signals and makes classifications using the spike-based computing engine that combines the advantages of both CNN and SNN. An adaptive weight mapping method specifically co-designed with the spike encoder can efficiently convert CNN to SNN without performance deterioration. The evaluation results show that the overall performance, including the classification accuracy, sensitivity and F1 score, achieve 92.7, 96.7, and 85.7% for seizure prediction, arrhythmia detection and hand gesture recognition, respectively. In comparison with CNN topologies, the computation complexity is reduced by over 80.7% while the energy consumption and area occupation are reduced by over 80% and over 64.8%, respectively, indicating that the proposed neuromorphic computing approach is energy and area efficient and of high precision, which paves the way for deployment at edge platforms., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Tian, Yang, Zhao and Sawan.)

In the process of adapting to the environment, tea plants ( Camellia sinensis ) endow tea with unique flavor and health functions, which should be attributed to secondary metabolites, including catechins, L-theanine, caffeine and terpene volatiles. Since the content of these flavor-contributing metabolites are mainly determined by the growth of tea plant, it is very important to understand their alteration and regulation mechanisms. In the present work, we first summarize the distribution, change characteristics of the main flavor-contributing metabolites in different cultivars, organs and under environmental stresses of tea plant. Subsequently, we discuss the regulating mechanisms involved in the biosynthesis of these metabolites based on the existing evidence. Finally, we propose the remarks and perspectives on the future study relating flavor-contributing metabolites. This review would contribute to the acceleration of research on the characteristic secondary metabolites and the breeding programs in tea plants.

An undesirable psychological state may deteriorate individual's weight management-related behaviors. This study aims to see if ineffective weight control measures were linked to depressive symptoms during pregnancy. We conducted a cross-sectional questionnaire survey of 784 pregnant women and collected information on sociodemographic factors, maternal characteristics, depression, and weight management activities throughout pregnancy (exercise management, dietary management, self-monitoring regulation, and management objectives). About 17.5% of pregnant women exhibited depressive symptoms. The mean score on dietary management was upper-middle, exercise management and self-monitoring regulation were medium, and management objectives were lower-middle. Multivariable linear regression analysis revealed that pregnant women with depressive symptoms had lower levels of exercise management (β = -1.585, p = 0.005), dietary management (adjusted β = -0.984, p = 0.002), and management objectives (adjusted β = -0.726, p = 0.009). However, there was no significant relationship between depressive symptoms and pregnant women's self-monitoring regulating behavior ( p > 0.05). The findings indicated the inverse association between depressive symptoms and gestational weight management behaviors. These results offer important indications for pregnancy weight management professionals by highlighting the need for mental health interventions for pregnant women experiencing depressive symptoms., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Zhao, Peng, Zhou, Ge, Zhou, Walker and You.)

Background: Cold exposure is one of the most important risk factors for atrial fibrillation (AF), and closely related to the poor prognosis of AF patients. However, the mechanisms underlying cold-related AF are poorly understood., Methods: Various techniques including 16S rRNA gene sequencing, fecal microbiota transplantation, and electrophysiological examination were used to determine whether gut microbiota dysbiosis promotes cold-related AF. Metabonomics were performed to investigate changes in fecal trimethylamine (TMA) and plasma trimethylamine N-oxide (TMAO) during cold exposure. The detailed mechanism underlying cold-related AF were examined in vitro. Transgenic mice were constructed to explore the role of pyroptosis in cold-related AF. The human cohort was used to evaluate the correlation between A. muciniphila and cold-related AF., Findings: We found that cold exposure caused elevated susceptibility to AF and reduced abundance of Akkermansia muciniphila (A. muciniphila) in rats. Intriguingly, oral supplementation of A. muciniphila ameliorated the pro-AF property induced by cold exposure. Mechanistically, cold exposure disrupted the A. muciniphila, by which elevated the level of trimethylamine N-oxide (TMAO) through modulation of the microbial enzymes involved in trimethylamine (TMA) synthesis. Correspondingly, progressively increased plasma TMAO levels were validated in human subjects during cold weather. Raised TMAO enhanced the infiltration of M1 macrophages in atria and increased the expression of Casp1-p20 and cleaved-GSDMD, ultimately causing atrial structural remodeling. Furthermore, the mice with conditional deletion of caspase1 exhibited resistance to cold-related AF. More importantly, a cross-sectional clinical study revealed that the reduction of A. muciniphila abundance was an independent risk factor for cold-related AF in human subjects., Interpretation: Our findings revealed a novel causal role of aberrant gut microbiota and metabolites in pathogenesis of cold-related AF, which raises the possibility of selectively targeting microbiota and microbial metabolites as a potential therapeutic strategy for cold-related AF., Funding: This work was supported by grants from the State Key Program of National Natural Science Foundation of China (No.81830012), and National Natural Science Foundation of China (No.82070336, No.81974024), Youth Program of the National Natural Science Foundation of China (No.81900374, No.81900302), and Excellent Young Medical Talents supporting project in the First Affiliated Hospital of Harbin Medical University (No. HYD2020YQ0001)., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Epilepsy is a life-threatening disease affecting millions of people all over the world. Artificial intelligence epileptic predictors offer excellent potential to improve epilepsy therapy. Particularly, deep learning models such as convolutional neural networks (CNN) can be used to accurately detect ictogenesis through deep structured learning representations. In this work, a tiny one-dimensional stacked convolutional neural network (1DSCNN) is proposed based on short-time Fourier transform (STFT) to predict epileptic seizure. The results demonstrate that the proposed method obtains better performance compared to recent state-of-the-art methods, achieving an average sensitivity of 94.44%, average false prediction rate (FPR) of 0.011/h and average area under the curve (AUC) of 0.979 on the test set of the American Epilepsy Society Seizure Prediction Challenge dataset, while featuring a model size of only 21.32kB. Furthermore, after adapting the model to 4-bit quantization, its size is significantly decreased by 7.08x with only 0.51% AUC score precision loss, which shows excellent potential for hardware-friendly wearable implementation.

Anaerobic granular sludge (AnGS) was cultured to treat high-strength perchlorate (reaching to 4800 mg/L) wastewater by an anaerobic baffled reactor (ABR) system with five equal-volume compartments (C1-C5 compartments). Inoculated sludge completely granulated on day 104 with granule size of 0.50-0.75 mm and perchlorate removal efficiency reaching to 97% (influent perchlorate of 2000-4800 mg/L). The Cyclic voltammetry (CV) capacitance increased from 487.5, 465.8 and 407.8 μF to 576.5, 552.4, 549.6 μF in C1, C3 and C5 compartments of ABR system, respectively, suggesting the electron transfer capacity was enhanced under high-strength perchlorate stress. Meanwhile, adenosine triphosphate (ATP) value and electron transport system activity (ETSA) increased to 25.05, 22.87, 20.43 and 6.22, 4.87, 3.95 of C1, C3 and C5 compartments, respectively. The results suggested that high-strength perchlorate stress improved the microbial metabolic activity, which promoted secretion of extracellular polymeric substances (EPS). The more EPS could facilitate the formation and stability of AnGS under high-strength perchlorate stress. In addition, more reasonable metabolic division of labor in functional bacterial (Thauera and Comamonas) was beneficial to AnGS formation, which achieved high-strength perchlorate efficient removal. Finally, a positive feedback mechanism between AnGS formation and high-strength perchlorate removal was established through EPS, microbial metabolic activity and electron transfer characteristic in ABR system. However, excessive perchlorate (5800 mg/L) would exceed the treatment capacity of AnGS, which resulted in the deterioration of removal performance. This work provided an effective information for AnGS application to treat high-strength perchlorate wastewater., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier B.V.)

The aerobic granular sludge simultaneous partial nitrification, denitrification and phosphorus removal (AGS-SPNDPR) process was carried out via tapered aeration in sequencing batch reactor (SBR) for treating low strength and low COD/TN ratio municipal wastewater. The results showed that aerobic granular sludge was successfully cultivated with good sedimentation performance when treating the municipal wastewater. Meanwhile, the median granule size increased to 270 (R1) and 257 (R2) μm on day 80. The excellent removal performance of COD (92%) and NH 4 + -N (95%) were achieved under different aeration modes, while the higher TN removal efficiency (76%) was achieved by tapered aeration. The accumulation of NO 2 - -N in R2 indicated that the tapered aeration was beneficial to achieve simultaneously partial nitrification and denitrification. Meanwhile, the high-efficiency phosphorus (95%) removal was realized via additional carbon source, and SPNDPR process was formed under tapered aeration. The bacterial community analysis indicated denitrifying glycogen-accumulating organisms (DGAOs) Candidatus&#95;Competibacter and ammonia-oxidizing bacteria (AOB) Nitrosomonas were more effectively enriched via tapered aeration, while phosphorus-accumulating organisms (PAOs) Candidatus&#95;Accumulibacter were effectively enriched under additional organic carbon. AOB, denitrifying bacteria and PAOs were simultaneously enriched by tapered aeration and additional carbon source, which was beneficial to nutrients removal. This study might be conducive to the application of AGS-SPNDPR system for treating low strength and low COD/TN ratio municipal wastewater under tapered aeration., (Copyright © 2022. Published by Elsevier Inc.)

CsPbCl 3 perovskite is an attractive semiconductor material with characteristics such as a wide bandgap, high chemical stability, and excellent optoelectronic properties, which broaden its application prospects for ultraviolet (UV) and violet photodetectors (PDs). However, large-area CsPbCl 3 films with high coverage, large grains, and controllable thickness are still difficult to prepare by using the solution method due to the extremely low solubility of their precursors in conventional solvents. Herein, a water-assisted confined re-growth method is developed, and a CsPbCl 3 microcrystalline film with an area of 3 cm × 3 cm is grown, the thickness of which is controllable within a range of several microns. The as-prepared thin film exhibits a flat and smooth surface, large grains, and enhanced photoluminescence. Furthermore, the fabricated violet PDs based on the prepared CsPbCl 3 film show a high responsivity of 2.17 A W -1 , external quantum efficiency of 664%, on/off ratio of 2.58 × 10 3 , and good stability. This study provides a prospective solution for the growth of large-area, large-grain, and surface-smooth CsPbCl 3 films for high-performance UV and violet PDs., (© 2022 IOP Publishing Ltd.)

Flavan-3-ols are abundant in the tea plant (Camellia sinensis) and confer tea with flavor and health benefits. We recently found that alternative splicing of genes is likely involved in the regulation of flavan-3-ol biosynthesis; however, the underlying regulatory mechanisms remain unknown. Here, we integrated metabolomics and transcriptomics to construct metabolite-gene networks in tea leaves, collected over five different months and from five spatial positions, and found positive correlations between endogenous jasmonic acid (JA), flavan-3-ols, and numerous transcripts. Transcriptome mining further identified CsJAZ1, which is negatively associated with flavan-3-ols formation and has three CsJAZ1 transcripts, one full-length (CsJAZ1-1), and two splice variants (CsJAZ1-2 and -3) that lacked 3' coding sequences, with CsJAZ1-3 also lacking the coding region for the Jas domain. Confocal microscopy showed that CsJAZ1-1 was localized to the nucleus, while CsJAZ1-2 and CsJAZ1-3 were present in both the nucleus and the cytosol. In the absence of JA, CsJAZ1-1 was bound to CsMYC2, a positive regulator of flavan-3-ol biosynthesis; CsJAZ1-2 functioned as an alternative enhancer of CsJAZ1-1 and an antagonist of CsJAZ1-1 in binding to CsMYC2; and CsJAZ1-3 did not interact with CsMYC2. In the presence of JA, CsJAZ1-3 interacted with CsJAZ1-1 and CsJAZ1-2 to form heterodimers that stabilized the CsJAZ1-1-CsMYC2 and CsJAZ1-2-CsMYC2 complexes, thereby repressing the transcription of four genes that act late in the flavan-3-ol biosynthetic pathway. These data indicate that the alternative splicing variants of CsJAZ1 coordinately regulate flavan-3-ol biosynthesis in the tea plant and improve our understanding of JA-mediated flavan-3-ol biosynthesis., (© 2022 Society for Experimental Biology and John Wiley & Sons Ltd.)

Aims: Ageing is the most significant contributor to the increasing prevalence of atrial fibrillation (AF). The gut microbiota dysbiosis is involved in age-related diseases. However, whether the aged-associated dysbiosis contributes to age-related AF is still unknown. Direct demonstration that the aged gut microbiota is sufficient to transmit the enhanced AF susceptibility in a young host via microbiota-intestinal barrier-atria axis has not yet been reported. This study aimed to determine whether gut microbiota dysbiosis affects age-related AF., Methods and Results: Herein, by using a faecal microbiota transplantation (FMT) rat model, we demonstrated that the high AF susceptibility of aged rats could be transmitted to a young host. Specially, we found the dramatically increased levels of circulating lipopolysaccharide (LPS) and glucose led to the up-regulated expression of NOD-like receptor protein (NLRP)-3 inflammasome, promoting the development of AF, which depended on the enhanced atrial fibrosis in recipient host. Inhibition of inflammasome by a potent and selective inhibitor of the NLRP3 inflammasome, MCC950, resulted in a lower atrial fibrosis and AF susceptibility. Then, we conducted cross-sectional clinical studies to explore the effect of ageing on the altering trends with glucose levels and circulating LPS among clinical individuals in two China hospitals. We found that both of serum LPS and glucose levels were progressively increased in elderly patients as compared with those young. Furthermore, the ageing phenotype of circulating LPS and glucose levels, intestinal structure and atrial NLRP3-inflammasome of rats were also confirmed in clinical AF patients. Finally, aged rats colonized with youthful microbiota restored intestinal structure and atrial NLRP3-inflammasome activity, which suppressed the development of aged-related AF., Conclusions: Collectively, these studies described a novel causal role of aberrant gut microbiota in the pathogenesis of age-related AF, which indicates that the microbiota-intestinal barrier-atrial NLRP3 inflammasome axis may be a rational molecular target for the treatment of aged-related arrhythmia disease., (Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2021. For permissions, please email: journals.permissions@oup.com.)

Inappropriate gestational weight gain has become a public health concern that threatens maternal and child health. Pregnant women's ability to manage their weight during pregnancy directly impacts their weight gain. In this study, we integrated the protection motivation theory and the information-motivation-behavioral skills model to develop an integrative theoretical model suitable for pregnancy weight management and reveal significant explainable factors of weight management behaviors during pregnancy. Based on a cross-sectional survey of 550 pregnant women from Jiangsu province, we came up with our findings. The results showed that several factors influenced pregnancy weight management behavior. According to the research, information, self-efficacy, response costs, and behavioral skills were significantly associated with weight management behaviors during pregnancy, while behavioral skills were also significant mediators of information, self-efficacy, and behavior. Furthermore, the information related to pregnancy weight management had the biggest impact on weight management behavior during pregnancy. The results of the model fit were acceptable and the integrative model could explain 30.6% of the variance of weight management behavior during pregnancy, which implies that the integrative theoretical model can effectively explain and predict weight management behaviors during pregnancy. Our study provides practical implications for the integrative model in improving pregnancy weight management behavior and offers a theoretical base for the weight management of pregnant women., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Ge, Zhao, Peng, Walker, Yang, Zhou, Wang, Zhang, Zhou and You.)

Introduction: Excessive gestational weight gain poses a significant threat to maternal and child health. The healthy behaviour theory has been increasingly applied to weight management during pregnancy, but research is still insufficient. The successful application of the protection motivation theory (PMT) and the information-motivation-behavioural skills (IMB) model in the field of healthy behaviour laid the foundation for this intervention study. The overall aim of this study is to test the effectiveness of interventions based on the behaviour model integrated with the PMT and IMB model (PMT-IMB model) on weight management and provide feasible methods for weight management during pregnancy., Methods and Analysis: This prospective, single-centre, randomised controlled trial involves two steps. First, based on the PMT-IMB model, evaluation tools and intervention materials will be developed. Second, more than 800 women in the first trimester of pregnancy will be randomly assigned to two groups and will be followed until 1 week after delivery. The control group will receive standardised antenatal care (ANC), whereas the experimental group will receive both standardised ANC and interventions based on the PMT-IMB model. After three surveys (at enrolment, at 28 weeks of gestation, and on the day of hospitalisation for delivery), primary outcomes (scores of the subscales of the PMT-IMB model, scores of the pregnancy weight management strategy scale, and gestational weight gain) and secondary outcomes (pregnancy outcomes and pregnancy complications) will be obtained. Differences in outcomes between the two groups will be analysed to evaluate the effectiveness of the intervention., Ethics and Dissemination: The study protocol has been approved by the ethics committee of Nanjing Medical University. All participants will sign an informed consent form prior to enrolment. The findings of the study will be published in peer-reviewed journals and presented at conferences., Trial Registration Number: ChiCTR2100043231., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Seizure prediction for drug-refractory epilepsy patients can improve their quality of life, reduce their anxiety, and help them take the necessary precautions. Nowadays, numerous deep learning algorithms have been proposed to predict seizure onset and obtain better performance than traditional machine learning methods. However, these methods require a large set of parameters and large hardware resources; they also have high energy consumption. Therefore, these methods cannot be implemented on compact, low-power wearable, or implantable medical devices. The devices should operate on a real-time basis to continually inform the epileptic patients. In this paper, we describe energy-efficient and hardware-friendly methods to predict the epileptic seizures. A model of only 45 kB was obtained by the neural architecture search and was evaluated across three datasets. The overall sensitivity, false prediction rate, and area under receiver operating characteristic curve were 99.81%, 0.005/h, 1 and 93.48%, 0.063/h, 0.977 and 85.19%, 0.116/h, 0.933, respectively, for three public datasets. This model was further reduced with several methods for model compression. The performances for the model sizes less than 50 kB for scalp EEG data and less than 10 kB for intracranial EEG data outperformed all the other models of similar model sizes. In particular, the energy consumption estimation was less than 10 mJ per inference for scalp EEG signal and less than 0.5 mJ per inference for intracranial EEG signal, which meet the requirements for low-power wearable and implantable devices, respectively.

Emerging evidence indicates that long non-coding RNAs (lncRNAs) serve as a critical molecular regulator in various cardiovascular diseases. Here, we aimed to identify and functionally characterize lncRNAs as potential mediators in the development of thoracic aortic dissection (TAD). We identified that a novel lncRNA, lnc-C2orf63-4-1, was lowly expressed in aortic samples of TAD patients and angiotensin II (Ang II)-challenged vascular smooth muscle cells (VSMCs), which was correlated with clinically aortic expansion. Besides, overexpression of lnc-C2orf63-4-1 significantly attenuated Ang II-induced apoptosis, phenotypic switching of VSMCs and degradation of extracellular matrix both in vitro and in vivo . A customized transcription factor array identified that signal transducer and activator of transcription 3 (STAT3) functioned as the main downstream effector. Mechanistically, dual-luciferase report analysis and RNA antisense purification (RAP) assay indicated that lnc-C2orf63-4-1 directly decreased the expression of STAT3, which was depend on the reduced stabilization of STAT3 mRNA. Importantly, up-regulation of STAT3 efficiently reversed the protective role of lnc-C2orf63-4-1 against Ang II-mediated vascular remodeling. Therefore, lnc-C2orf63-4-1 negatively regulated the expression of STAT3 and prevented the development of aortic dissection. Our study revealed that lnc-C2orf63-4-1 played a critical role in vascular homeostasis, and its dysfunction exacerbated Ang II-induced pathological vascular remodeling., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Zhang, Zhao, Han, Zhang, Jin, Yuan, Zhao, Luo, Zhou, Gao, Yu, Sun, Xu, Yan, Gong and Li.)

Objective: To investigate the determinants of willingness and practice of physicians' online medical services (OMS) uptake based on social ecosystem theory, so as to formulate OMS development strategies., Design: Cross-sectional survey., Setting: Research was conducted in two comprehensive hospitals and two community hospitals in Jiangsu, China, and the data were gathered from 1 June to 31 June 2020., Participants: With multistage sampling, 707 physicians were enrolled in this study., Outcome Measure: Descriptive statistics were reported for the basic characteristics. χ 2 test, Mann-Whitney U test and Spearman's correlation analysis were used to perform univariate analysis. Linear regression and logistic regression were employed to examine the determinants of physicians' OMS uptake willingness and actual uptake, respectively., Results: The mean score of the physicians' OMS uptake willingness was 17.33 (range 5-25), with an SD of 4.39, and 53.3% of them reported having conducted OMS. In the micro system, factors positively associated with willingness included holding administrative positions (b=1.03, p<0.05), OMS-related awareness (b=1.32, p<0.001) and OMS-related skills (b=4.88, p<0.001); the determinants of actual uptake included holding administrative positions (OR=2.89, 95% CI 1.59 to 5.28, p<0.01), OMS-related awareness (OR=1.90, 95% CI 1.22 to 2.96, p<0.01), OMS-related skills (OR=2.25, 95% CI 1.35 to 3.74, p<0.01) and working years (OR=2.44, 95% CI 1.66 to 3.59, p<0.001). In the meso system, the hospital's incentive mechanisms (b=0.78, p<0.05) were correlated with willingness; hospital advocated for OMS (OR=2.34, 95% CI 1.21 to 4.52, p<0.05), colleagues' experiences (OR=3.81, 95% CI 2.25 to 6.45, p<0.001) and patients' consultations (OR=2.93, 95% CI 2.02 to 4.25, p<0.001) were determinants of actual uptake. In the macro system, laws and policies were correlated with willingness (b=0.73, p<0.05) and actual uptake (OR=1.98, 95% CI 1.31 to 2.99, p<0.01); media orientation was also associated with willingness (b=0.74, p<0.05)., Conclusion: Multiple determinants influence physicians' OMS application. Comprehensive OMS promotion strategies should be put forward from multidimensional perspectives including the micro, meso and macro levels., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

CsPbCl 3 is an attractive wide-bandgap perovskite semiconductor. Herein, we have grown hopper-shaped CsPbCl 3 crystals in a solution droplet dripped on a heated substrate. During the growth, we have observed the impacts of the coffee ring effect and Marangoni flow, which may result in the hopper shape. Their photoluminescence spectra feature double peaks, which are located at 413.9 nm and 422.0 nm, respectively, and the latter increases faster in intensity than the former as the excitation power increases. We believe that the higher-energy peak originates from the excitonic emission and the lower-energy one is from the polaritons' emission, where the polaritons are generated in the exciton-exciton inelastic scattering process. Based on such an explanation, the exciton binding energy of CsPbCl 3 is estimated to be 76.7 meV in our experiments, consistent with the previous reports., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

Gray blight (GB) is one of the most destructive diseases of tea plants, causing considerable damage and productivity losses; however, the dynamic roles of defense genes during pathogen infection remain largely unclear. To explore the numerous molecular interactions associated with GB stress in tea plants, we employed transcriptome, sRNAome and degradome sequencing from 1 to 13 days post-inoculation (dpi) at 3-day intervals. The transcriptomics results showed that differentially expressed genes (DEGs) related to flavonoid synthesis, such as chalcone synthase (CHS) and phenylalanine ammonia-lyase (PAL), were particularly induced at 4 dpi. Consistent with this, the contents of catechins (especially gallocatechin), which are the dominant flavonoids in tea plants, also increased in the leaves of tea plants infected with GB. Combined analysis of the sRNAome and degradome revealed that microRNAs could mediate tea plant immunity by regulating DEG expression at the post-transcriptional level. Co-expression network analysis demonstrated that miR530b-ethylene responsive factor 96 (ERF96) and miRn211-thaumatin-like protein (TLP) play crucial roles in the response to GB. Accordingly, gene-specific antisense oligonucleotide assays suggested that suppressing ERF96 decreased the levels of reactive oxygen species (ROS), whereas suppressing TLP increased the levels of ROS. Furthermore, ERF96 was induced, but TLP was suppressed, in susceptible tea cultivars. Our results collectively demonstrate that ERF96 is a negative regulator and TLP is a positive regulator in the response of tea plants to GB. Taken together, our comprehensive integrated analysis reveals a dynamic regulatory network linked to GB stress in tea plants and provides candidate genes for improvement of tea plants., (© 2021 Society for Experimental Biology and John Wiley & Sons Ltd.)

Anthocyanins are natural colorants that have attracted increasing attention because of their extensive range of antioxidant, antimutagenic, and health-promoting properties. The mechanism of anthocyanin synthesis has been studied in "Zijuan" tea, a representative anthocyanin-rich tea plant. However, the molecular basis underlying the transformation and degradation of anthocyanins is less-thoroughly understood. In this study, we compare "Zijuan" with a similar variety, "Yunkang 10", for transcriptome and metabolite analysis. In total, four glycosylated anthocyanins were identified in "Zijuan", including delphinidin-3- O -galactoside, cyanidin-3- O -galactoside, delphinidin 3- O -(6- O - p -coumaroyl) galactoside, and cyanidin 3- O -(6- O - p -coumaroyl) galactoside, and the glycosyl might determine the stable accumulation of anthocyanins. Several differentially expressed genes and transcription factors regulating the anthocyanin metabolism were identified, in which the significantly upregulated ANS , 3GT , 3AT , MYB , and WRKY were determined to be responsible for increasing and transforming anthocyanins. Moreover, by comparing the different positions of leaves in "Zijuan" and "Ziyan", we found that the pivotal genes regulating the biosynthesis of anthocyanins in "Zijuan" and "Ziyan" were different, and the degradation genes played different roles in the hydrolyzation of anthocyanins. These results provide further information on the molecular regulation of anthocyanin balance in tea plants.

Current guidelines favor dual anti-platelet therapy with ticagrelor 90 mg BID (T90BID) over clopidogrel 75 mg QD (C75QD) in addition to aspirin for acute coronary syndrome. However, an increased risk of ticagrelor-related adverse events prompted the evaluation of low-dose regimens. This study (NCT03381742) retrospectively analyzed the data from 11 hospitals on 3,043 patients with coronary artery disease, who received C75QD, T90BID, ticagrelor 45 mg BID (T45BID), or ticagrelor 90 mg QD (T90QD). Compared with C75QD, both T45BID and T90QD showed significantly higher inhibition of platelet aggregation ( P < .0001) and lower platelet-fibrin clot strength ( P < .0001) induced by adenosine diphosphate. Furthermore, compared with T90BID, two low-dose regimens had a much lower minor bleeding rate and a significantly higher proportion of patients within the therapeutic window for P2Y 12 receptor reactivity. There were no significant differences between T45BID and T90QD in the trough plasma concentrations of ticagrelor and its active metabolite. Similar efficacy and safety outcomes were observed in the propensity score-matched analysis. In conclusion, the low-dose ticagrelor regimen, either T45BID or T90QD, may provide a more attractive benefit-risk profile than C75QD or T90BID.

Camellia sinensis var. sinensis (CSS) and C. sinensis var. assamica (CSA) are the two most economically important tea varieties. They have different characteristics and geographical distribution. Their genetic diversity and differentiation are unclear. Here, we identified 18,903,625 single nucleotide polymorphisms (SNPs) and 7,314,133 insertion-deletion mutations (indels) by whole-genome resequencing of 30 cultivated and three wild related species. Population structure and phylogenetic tree analyses divided the cultivated accessions into CSS and CSA containing 6,440,419 and 6,176,510 unique variations, respectively. The CSS subgroup possessed higher genetic diversity and was enriched for rare alleles. The CSA subgroup had more non-synonymous mutations and might have experienced a greater degree of balancing selection. The evolution rate (dN/dS) and KEGG enrichment indicated that genes involved in the synthesis and metabolism of flavor substances were positively selected in both CSS and CSA subpopulations. However, there are extensive genome differentiation regions (2959 bins and approximately 148 M in size) between the two subgroups. Compared with CSA (141 selected regions containing 124 genes), the CSS subgroup (830 selected regions containing 687 genes) displayed more selection regions potentially related to environmental adaptability. Fifty-three pairs of polymorphic indel markers were developed. Some markers were located in hormone-related genes with distinct alleles in the two cultivated subgroups. These identified variations and selected regions provide clues for the differentiation and adaptive evolution of tea varieties. The newly developed indel markers will be valuable in further genetic research on tea plants., (Copyright © 2020 An, Mi, Zhao, Guo, Xia, Liu and Wei.)

To get a more detailed understanding of the interaction between tea plant (Camellia sinensis) and tea geometrids (Ectropis obliqua), transcriptomic profile in undamaged adjacent leaf (TGL) of tea geometrids fed local leaves (LL) was investigated for the first time. Here, approximately 245 million clean reads contained 39.39 Gb of sequence data were obtained from TGL. Further analysis revealed that systemic response was induced in TGL after tea geometrids feeding on LL, although the defense response was weaker than that in LL. The differentially expressed genes (DEGs) identification analysis showed little overlap of DEGs between TGL and LL. Comparative transcriptome analysis suggested that JA signal regulated resistant pathway was induced in LL; whereas primary metabolism pathway was activated in TGL in response to tea geometrids feeding. This study reveals a novel resistance mechanism of TGL to tea geometrids feeding., Competing Interests: Declaration of Competing Interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Based on the abundance of taste compounds in leaves at different leaf positions on the same shoot, green tea made from one bud and one leaf, or even just one bud, has the best quality. To elucidate the mechanism underlying the regulation of the biosynthesis of these compounds, we profiled the metabolome, transcriptome, sRNA, degradome, and WGCNA using leaves from five leaf positions of shoots. Through this analysis, we found 139 miRNA-target pairs related to taste compound biosynthesis and 96 miRNA-target pairs involved in phytohormone synthesis or signal transduction. Moreover, miR166- HD-ZIP , miR169- NF-YA , IAA, ZA, ABA, and JA were positively related to the accumulation of gallated catechin, caffeine, and theanine. However, miR396- GRF , miR393- bHLH , miR156- SBP , and SA were negatively correlated with these compounds. Among these important pairs, the miR396- GRF and miR156- SBP pairs were further validated by using qRT-PCR, Northern blots, and cotransformation. This is the first report describing that miRNA-TF pairs and phytohormones might synergistically regulate the biosynthesis of taste compounds in the leaves of tea plants.

Plant hormones play an important role in the chemical metabolism of postharvest plants. However, alterations in plant hormones of postharvest tea and their potential modulation of quality-related metabolites are unknown. In this study, the dynamic alterations of abscisic acid (ABA), salicylic acid (SA), jasmonic acid (JA), and critical metabolites, such as catechins, theanine, and caffeine, in tea leaves were analyzed during withering from 0 to 24 h. It was found that the ABA content increased from 0 to 9 h but decreased thereafter, JA continuously increased, and the SA content showed no significant change. With the exception of gallocatechin (GC) and epicatechin (EC), the amounts of other critical components were significantly reduced at 24 h. Transcriptome analysis showed that compared with 0 h, 2256, 3654, and 1275 differentially expressed genes (DEGs) were identified at 9, 15, and 24 h, respectively. For all comparisons, DEGs corresponding to the pathways of "phenylalanine, tyrosine, and tryptophan biosynthesis" and "phenylalanine metabolism", involved in the biosynthesis of catechins, were significantly enriched. Weighted correlation network analysis (WGCNA) of co-expression genes indicated that many of the modules were only correlated with a specific trait during the withering process; the dark olive-green module, however, was correlated with two traits, ABA and theanine. Our study indicates that withering induced dramatic alterations in gene transcription as well as levels of hormones (ABA, JA, and SA) and important components, and that ABA regulated theanine metabolism during this process., Competing Interests: The authors declare no conflicts of interest.

Diabetic nephropathy (DN) is a frequently occurred microvascular complication associated with type I and type II diabetes mellitus. The participation of long noncoding RNAs (lncRNAs) in diabetes-related microvascular complications has been reported extensively. We attempted to unveil the possible regulatory mechanism of lncRNA growth arrest-specific transcript 5 (GAS5) and matrix metalloproteinase 9 (MMP9), an important inflammatory protein, in the progression of DN. A rat DN model was induced by streptozocin (STZ). The low expression of GAS5 and high expression of MMP9 in DN rats with DN was then determined by RT-qPCR and western blot analysis, and lentivirus-mediated GAS5 overexpression was shown to ameliorate STZ-induced renal interstitial fibrosis (RIF) and inflammatory reaction in the kidney of DN rats. Moreover, MMP9 was found to be upregulated in STZ-induced DN, while MMP9 silencing induced by lentivirus expressing shRNA against MMP9 reduced RIF and suppressed inflammation in the kidney of DN rats. RIP, RNA pull-down, and ChIP assays demonstrated that GAS5 downregulated MMP9 via recruiting enhancer of zeste homolog 2 (EZH2) in the promoter region of MMP9. Overall, our study reveals that GAS5 downregulates MMP9 expression through recruiting EZH2 to MMP9 promoter region and alleviates the progression of renal fibrosis in DN rats, which sheds new light on the therapeutic potential of GAS5-targeted therapies in combating that disease., (© 2020 Federation of American Societies for Experimental Biology.)

Background: Alternative splicing (AS) may generate multiple mRNA splicing isoforms from a single mRNA precursor using different splicing sites, leading to enhanced diversity of transcripts and proteins. AS has been implicated in cold acclimation by affecting gene expression in various ways, yet little information is known about how AS influences cold responses in tea plant (Camellia sinensis)., Results: In this study, the AS transcriptional landscape was characterized in the tea plant genome using high-throughput RNA-seq during cold acclimation. We found that more than 41% (14,103) of genes underwent AS events. We summarize the possible existence of 11 types of AS events, including the four common types of intron retention (IR), exon skipping (ES), alternative 5' splice site (A5SS), and alternative 3' splice site (A3SS); of these, IR was the major type in all samples. The number of AS events increased rapidly during cold treatment, but decreased significantly following de-acclimation (DA). It is notable that the number of differential AS genes gradually increased during cold acclimation, and these genes were enriched in pathways relating to oxidoreductase activity and sugar metabolism during acclimation and de-acclimation. Remarkably, the AS isoforms of bHLH transcription factors showed higher expression levels than their full-length ones during cold acclimation. Interestingly, the expression pattern of some AS transcripts of raffinose and sucrose synthase genes were significantly correlated with sugar contents., Conclusion: Our findings demonstrated that changes in AS numbers and transcript expression may contribute to rapid changes in gene expression and metabolite profile during cold acclimation, suggesting that AS events play an important regulatory role in response to cold acclimation in tea plant.

Flavonoids are the major class of characteristic secondary compounds in Camellia sinensis that affect quality of tea. However, the temporal variation and the underlying regulatory mechanism of flavonoid biosynthesis during different growth months require a further investigation. Here, we combined analyses of the metabolomics and transcriptomics to tea leaves freshly collected during five different months for a comprehensive understanding of flavonoid metabolism regulation in tea plants. Through loading plot analysis, significant changes in the contents of metabolites during growing months were discovered, and further co-expression and association analysis indicated that one flavone glycoside (naringenin-7-O-glucoside) and two flavonol glycosides (quercetin-3-O-galactoside and kaemferol-3-O-(6″-O-p-courmaroyl)-glucoside) were evaluated as growth markers, which may explain the high bitterness and astringency of August teas; additionally, the high levels of two flavan-3-ols (gallocatechin and catechin gallate) may contribute to the flavor formation of April tea. Meanwhile, multiple flavonoid-related structural genes, MYB and bHLH transcription factors exhibit specific expression patterns to modulate the biosynthesis of these key flavonoids. A co-expression regulatory sub-network was constructed based on profiles of differentially expressed genes; one CsbHLH and six transcription factors (three CsbHLHs and three CsMYBs) exhibited negative and positive roles in the regulation of flavonoid biosynthetic genes, respectively. Taken together, our results provide new insights into the regulation of principle flavonoids for unique flavor of tea regulated by many flavonoid-related structural genes and transcription factors during different growth months., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Organic-inorganic halide perovskites have achieved remarkable success in various optoelectronic devices. A high-quality CH 3 NH 3 PbBr 3 single-crystalline thin film has been directly grown in a micrometer gap between a pair of distributed reflectors with over 99.9% reflectivity, which naturally form a vertical cavity surface-emitting laser device with a single mode or several modes. The single-crystalline perovskite has an exciton lifetime of 426 ns and evidence of the exciton-photon coupling is observed. At room temperature and under continuous-wave optical pumping conditions, this device lases at a threshold of 34 mW cm -2 in the green gap. The extremely low lasing threshold suggests that polariton lasing may occur in the strongly confined optical cavity comprising the high-quality single-crystalline perovskite., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)