Improving Communication Efficiency of Federated Distillation via Accumulating Local Updates

As an emerging federated learning paradigm, federated distillation enables communication-efficient model training by transmitting only small-scale knowledge during the learning process. To further improve the communication efficiency of federated distillation, we propose a novel technique, ALU, which accumulates multiple rounds of local updates before transferring the knowledge to the central server. ALU drastically decreases the frequency of communication in federated distillation, thereby significantly reducing the communication overhead during the training process. Empirical experiments demonstrate the substantial effect of ALU in improving the communication efficiency of federated distillation.Comment: 2 pages, 3 figure

Activation of voltage-gated KCNQ/Kv7 channels by anticonvulsant retigabine attenuates mechanical allodynia of inflammatory temporomandibular joint in rats

<p>Abstract</p> <p>Background</p> <p>Temporomandibular disorders (TMDs) are characterized by persistent orofacial pain and have diverse etiologic factors that are not well understood. It is thought that central sensitization leads to neuronal hyperexcitability and contributes to hyperalgesia and spontaneous pain. Nonsteroidal anti-inflammatory drugs (NSAIDs) are currently the first choice of drug to relieve TMD pain. NSAIDS were shown to exhibit anticonvulsant properties and suppress cortical neuron activities by enhancing neuronal voltage-gated potassium KCNQ/Kv7 channels (M-current), suggesting that specific activation of M-current might be beneficial for TMD pain.</p> <p>Results</p> <p>In this study, we selected a new anticonvulsant drug retigabine that specifically activates M-current, and investigated the effect of retigabine on inflammation of the temporomandibular joint (TMJ) induced by complete Freund's adjuvant (CFA) in rats. The results show that the head withdrawal threshold for escape from mechanical stimulation applied to facial skin over the TMJ in inflamed rats was significantly lower than that in control rats. Administration of centrally acting M-channel opener retigabine (2.5 and 7.5 mg/kg) can dose-dependently raise the head withdrawal threshold of mechanical allodynia, and this analgesic effect can be reversed by the specific KCNQ channel blocker XE991 (3 mg/kg). Food intake is known to be negatively associated with TMJ inflammation. Food intake was increased significantly by the administration of retigabine (2.5 and 7.5 mg/kg), and this effect was reversed by XE991 (3 mg/kg). Furthermore, intracerebralventricular injection of retigabine further confirmed the analgesic effect of central retigabine on inflammatory TMJ.</p> <p>Conclusions</p> <p>Our findings indicate that central sensitization is involved in inflammatory TMJ pain and pharmacological intervention for controlling central hyperexcitability by activation of neuronal KCNQ/M-channels may have therapeutic potential for TMDs.</p

FedCache: A Knowledge Cache-driven Federated Learning Architecture for Personalized Edge Intelligence

Edge Intelligence (EI) allows Artificial Intelligence (AI) applications to run at the edge, where data analysis and decision-making can be performed in real-time and close to data sources. To protect data privacy and unify data silos among end devices in EI, Federated Learning (FL) is proposed for collaborative training of shared AI models across devices without compromising data privacy. However, the prevailing FL approaches cannot guarantee model generalization and adaptation on heterogeneous clients. Recently, Personalized Federated Learning (PFL) has drawn growing awareness in EI, as it enables a productive balance between local-specific training requirements inherent in devices and global-generalized optimization objectives for satisfactory performance. However, most existing PFL methods are based on the Parameters Interaction-based Architecture (PIA) represented by FedAvg, which causes unaffordable communication burdens due to large-scale parameters transmission between devices and the edge server. In contrast, Logits Interaction-based Architecture (LIA) allows to update model parameters with logits transfer and gains the advantages of communication lightweight and heterogeneous on-device model allowance compared to PIA. Nevertheless, previous LIA methods attempt to achieve satisfactory performance either relying on unrealistic public datasets or increasing communication overhead for additional information transmission other than logits. To tackle this dilemma, we propose a knowledge cache-driven PFL architecture, named FedCache, which reserves a knowledge cache on the server for fetching personalized knowledge from the samples with similar hashes to each given on-device sample. During the training phase, ensemble distillation is applied to on-device models for constructive optimization with personalized knowledge transferred from the server-side knowledge cache.Comment: 14 pages, 6 figures, 9 tables. arXiv admin note: text overlap with arXiv:2301.0038

Salivary signatures of oral-brain communication in sleep bruxers

IntroductionMicrobiota and their interaction with hosts have been of great interest in brain research in recent years. However, the role of oral microbiota in mental illness and the underlying mechanism of oral-brain communication remains elusive. Sleep bruxism (SB) is an oral parafunctional activity related to the nervous system and is considered a risk factor for harmful clinical consequences and severe systemic conditions. Exploring the connection between oral microbiota and sleep bruxism may deepen our understanding of the complex relationship between oral-brain axis and provide insights for treatment.MethodsIn this study, salivary samples were collected from 22 individuals with SB and 21 healthy controls, and metagenomics with metabolomics was performed. Nonparametric Wilcoxon test were applied for the statistical analysis between the two groups. Microbial dysbiosis and altered oral metabolites were found in the SB individuals.ResultsThe characteristic metabolite N-acetylglucosamine (GlcNAc) (VIP=8.4823, P&lt;0.05) was correlated to a statistically lower Streptococcus mitis level in SB individuals. Salivary IFN-g level and IFN-g/IL-4 ratio were detected with significant changes in a chip assay. Amino acid metabolism pathways were upregulated, and the pathway with the largest number of differentially expressed genes is related to amino-tRNA charging pathway, while the most significantly enriched pathway is related to arginine biosynthesis. Neurotransmitter-associated pathways with glutamatergic and GABAergic synapses and cardiovascular system-related pathways were enriched in the SB group.DiscussionThese results indicate a possible neuroimmune regulatory network of oral-brain communication in SB, which helps explain the mechanism of the oral microbiome with the host in sleep bruxers and provides a reference for early clinical and therapeutic intervention to improve the diagnosis and treatment of SB and similar diseases

The incidence and risk factors of acute pain after preoperative needle localization of pulmonary nodules: a cross-sectional study

Background: The incidence, severity and associated risk factors of acute pain after preoperative needle localization of pulmonary nodules are poorly characterized. We therefore conducted a cross-sectional study to quantify the acute pain induced by preoperative needle localization of small pulmonary nodules before video-assisted thoracoscopic surgery (VATS). Methods: We conducted this study at Shanghai Chest Hospital from September 2021 through December 2021. Eligible patients were between 18 and 75 years old and had small pulmonary nodules requiring preoperative CT-guided needle localization. The intensity of acute pain was assessed using the visual analogue scale (VAS) after preoperative needle localization. A VAS score ≥4 cm indicated moderate to severe pain. Patient demographics and CT-guided localization factors were collected to identify significant predictors associated with moderate to severe pain. Results: A total of 300 patients were included in the final analysis, with a mean (SD) age of 51 (SD =12) years old; 63% were female. Moderate to severe pain occurred in 50.8% of patients during deep breathing and 45.7% of patients during movement. Multivariate logistic regression analysis showed that multiple localization needles [multiple needle localizations vs. single needle localization, odds ratio (OR): 2.363, 95% confidence interval (CI): 1.157–4.825, P=0.018] and the specific location of needle puncture on the chest wall were significant predictors of moderate to severe pain after CT-guided needle localization (lateral chest wall vs. anterior chest wall OR: 2.235, 95% CI: 1.106–4.518, P=0.025; posterior chest wall vs. anterior chest wall OR: 1.198, 95% CI: 0.611–2.349, P=0.599). Conclusions: In adult patients receiving hookwire CT-guided localization, moderate to severe pain was common. Avoiding the localization route through lateral chest wall may be helpful and pharmacological medications or regional blockade is necessitated in high-risk population

Micro RNA expression profile and functional analysis reveal that mi R ‐382 is a critical novel gene of alcohol addiction

Alcohol addiction is a major social and health concern. Here, we determined the expression profile of microRNAs (miRNAs) in the nucleus accumbens (NAc) of rats treated with alcohol. The results suggest that multiple miRNAs were aberrantly expressed in rat NAc after alcohol injection. Among them, miR‐382 was down‐regulated in alcohol‐treated rats. In both cultured neuronal cells in vitro and in the NAc in vivo , we identified that the dopamine receptor D1 ( Drd1 ) is a direct target gene of miR‐382. Via this target gene, miR‐382 strongly modulated the expression of DeltaFosB. Moreover, overexpression of miR‐382 significantly attenuated alcohol‐induced up‐regulation of DRD1 and DeltaFosB, decreased voluntary intake of and preference for alcohol and inhibited the DRD1‐induced action potential responses. The results indicated that miRNAs are involved in and may represent novel therapeutic targets for alcoholism. The underlying molecular causes of alcohol addiction remain unclear. Many miRNAs are found modulated in the nucleus accumbens of rats chronically treated with alcohol. Specifically, miR‐382 is shown to regulate alcohol intake via DRD1 and DeltaFosB.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/99635/1/emmm201201900-sm-0001-Review_Process_File.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/99635/2/emmm201201900.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/99635/3/emmm201202100-sm-0006-SourceData-S5.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/99635/4/emmm201201900-sm-0002-SuppData-S1.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/99635/5/emmm201202100-sm-0005-SourceData-S4.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/99635/6/emmm201202100-sm-0004-SourceData-S3.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/99635/7/emmm201202100-sm-0003-SourceData-S2.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/99635/8/emmm201202100-sm-0007-SourceData-S6.pd

Suppression of MAPK11 or HIPK3 reduces mutant Huntingtin levels in Huntington's disease models.

Most neurodegenerative disorders are associated with accumulation of disease-relevant proteins. Among them, Huntington disease (HD) is of particular interest because of its monogenetic nature. HD is mainly caused by cytotoxicity of the defective protein encoded by the mutant Huntingtin gene (HTT). Thus, lowering mutant HTT protein (mHTT) levels would be a promising treatment strategy for HD. Here we report two kinases HIPK3 and MAPK11 as positive modulators of mHTT levels both in cells and in vivo. Both kinases regulate mHTT via their kinase activities, suggesting that inhibiting these kinases may have therapeutic values. Interestingly, their effects on HTT levels are mHTT-dependent, providing a feedback mechanism in which mHTT enhances its own level thus contributing to mHTT accumulation and disease progression. Importantly, knockout of MAPK11 significantly rescues disease-relevant behavioral phenotypes in a knockin HD mouse model. Collectively, our data reveal new therapeutic entry points for HD and target-discovery approaches for similar diseases

Multimodal Sensor Motion Intention Recognition Based on Three-Dimensional Convolutional Neural Network Algorithm

With the development of microelectronic technology and computer systems, the research of motion intention recognition based on multimodal sensors has attracted the attention of the academic community. Deep learning and other nonlinear neural network models have a wide range of applications in big data sets. We propose a motion intention recognition algorithm based on multimodal long-term and short-term spatiotemporal feature fusion. We divide the target data into multiple segments and use a three-dimensional convolutional neural network to extract the short-term spatiotemporal features. The three types of features of the same segment are fused together and input into the LSTM network for time-series modeling to further fuse the features to obtain multimodal long-term spatiotemporal features with higher discrimination. According to the lower limb movement pattern recognition model, the minimum number of muscles and EMG signal characteristics required to accurately recognize the movement state of the lower limbs are determined. This minimizes the redundant calculation cost of the model and ensures the real-time output of the system results

Simulation of Tennis Match Scene Classification Algorithm Based on Adaptive Gaussian Mixture Model Parameter Estimation

This paper presents an in-depth analysis of tennis match scene classification using an adaptive Gaussian mixture model parameter estimation simulation algorithm. We divided the main components of semantic analysis into type of motion, distance of motion, speed of motion, and landing area of the tennis ball. Firstly, for the problem that both people and tennis balls in the video frames of tennis matches from the surveillance viewpoint are very small, we propose an adaptive Gaussian mixture model parameter estimation algorithm, which has good accuracy and speed on small targets. Secondly, in this paper, we design a sports player tracking algorithm based on role division and continuously lock the target player to be tracked and output the player region. At the same time, based on the displacement information of the key points of the player’s body and the system running time, the distance and speed of the player’s movement are obtained. Then, for the problem that tennis balls are small and difficult to capture in high-speed motion, this paper designs a prior knowledge-based algorithm for predicting tennis ball motion and landing area to derive the landing area of tennis balls. Finally, this paper implements a prototype system for semantic analysis of real-time video of tennis matches and tests and analyzes the performance indexes of the system, and the results show that the system has good performance in real-time, accuracy, and stability

S-type Dissolved Oxygen Distribution along Water Depth in a Canyon-shaped and Algae Blooming Water Source Reservoir: Reasons and Control

Dissolved oxygen (DO) is a crucial indicator of water quality. DO usually shows a monotonic decrease along water depth during thermal stratification in reservoir, whereas metalimnetic oxygen minimum (MOM) is observed in some cases. Although MOM phenomena have been reported in different areas, the characteristics of different reservoirs are greatly different, and few comprehensive studies have been published regarding MOM in Chinese drinking water source reservoirs. The DO distribution along water depth was determined and the detailed reasons were clarified by two-years of field monitoring. In addition the effect of water lifting aerators (WLAs) on DO improvement was investigated in the Lijiahe Reservoir in Northwest China. A typical S-type DO distribution with two anaerobic water layers, below the epilimnion (10&ndash;25 m water depth) and above the sediment (bottom water), was observed derived from the decomposition of dead algae or organic matter and the restriction of DO vertical exchange. Moreover, after WLAs&rsquo; operation since 10 June 2018, the water body was completely mixed and DO was rich and uniform along water depth by eliminating the water stratification and inhibiting algae growth. The deep understanding of the DO distribution in a deep canyon-shaped reservoir and the technical support for reservoir restoration are meaningful for optimizing reservoir management