Filling the Missing: Exploring Generative AI for Enhanced Federated Learning over Heterogeneous Mobile Edge Devices

Distributed Artificial Intelligence (AI) model training over mobile edge networks encounters significant challenges due to the data and resource heterogeneity of edge devices. The former hampers the convergence rate of the global model, while the latter diminishes the devices' resource utilization efficiency. In this paper, we propose a generative AI-empowered federated learning to address these challenges by leveraging the idea of FIlling the MIssing (FIMI) portion of local data. Specifically, FIMI can be considered as a resource-aware data augmentation method that effectively mitigates the data heterogeneity while ensuring efficient FL training. We first quantify the relationship between the training data amount and the learning performance. We then study the FIMI optimization problem with the objective of minimizing the device-side overall energy consumption subject to required learning performance constraints. The decomposition-based analysis and the cross-entropy searching method are leveraged to derive the solution, where each device is assigned suitable AI-synthesized data and resource utilization policy. Experiment results demonstrate that FIMI can save up to 50% of the device-side energy to achieve the target global test accuracy in comparison with the existing methods. Meanwhile, FIMI can significantly enhance the converged global accuracy under the non-independently-and-identically distribution (non-IID) data.Comment: 13 pages, 5 figures. Submitted to IEEE for possible publicatio

MiR-34a Enhances Chondrocyte Apoptosis, Senescence and Facilitates Development of Osteoarthritis by Targeting DLL1 and Regulating PI3K/AKT Pathway

Background/Aims: Osteoarthritis (OA) is the prevalent degenerative disease caused by various factors. MicroRNAs are important regulators in the inflammation and immune response. The aim of this study was to investigate the effect of microRNA-34a (MiR-34a) on the death of chondrocytes, senescence, as well as its role in OA progression. Methods: A series of experiments involving CCK-8, flow cytometry, β-galactosidase staining and wound healing assays were conducted to determine the cellular capabilities of proliferation, cell apoptosis, senescence and the ability of cells to recover from injury, respectively. Binding sites between miR-34a and delta-like protein 1 (DLL1) were identified using a luciferase reporter system, whereas mRNA and protein expression of target genes was determined by RT-PCR and immunoblot, respectively. OA model was generated via surgery. Results: We found that miR-34a expression was increased in the cartilage of OA patients. In rat chondrocytes and chondrosarcoma cells, miR-34a transfections noticeably inhibited the expression of DLL1, triggered cell death and senescence, suppressed proliferation, and prevented scratch assay wound closure. However, transfection of a miR-34a inhibitor displayed adverse effects. Additionally, secretion and expression of factors associated with cartilage degeneration were altered via miR-34a. Moreover, miR-34a directly inhibits DLL1 mRNA. Furthermore, concentrations of DLL1, total PI3K, and p-AKT declined in chondrocytes that overexpress miR-34a. DLL1 overexpression elevated PI3K and p-AKT levels, and eliminated cell death triggered by a miR-34a mimic. In vivo, miR-34a remarkably inhibited miR-34a up-regulation, while enhanced the level of DLL1 expression. In the knee joints of surgery-induced OA rats, articular chondrocyte death and loss of cartilage were attenuated via miR-34a antagomir injection. Conclusions: These findings indicate that miR-34a contributes to chondrocyte death, causing OA progression through DLL1 and modulation of the PI3K/AKT pathway

Analysis of white matter tract integrity using diffusion kurtosis imaging reveals the correlation of white matter microstructural abnormalities with cognitive impairment in type 2 diabetes mellitus

BackgroundThis study aimed to identify disruptions in white matter integrity in type 2 diabetes mellitus (T2DM) patients by utilizing the white matter tract integrity (WMTI) model, which describes compartment-specific diffusivities in the intra- and extra-axonal spaces, and to investigate the relationship between WMTI metrics and clinical and cognitive measurements.MethodsA total of 73 patients with T2DM and 57 healthy controls (HCs) matched for age, sex, and education level were enrolled and underwent diffusional kurtosis imaging and cognitive assessments. Tract-based spatial statistics (TBSS) and atlas-based region of interest (ROI) analysis were performed to compare group differences in diffusional metrics, including fractional anisotropy (FA), mean diffusivity (MD), axonal water fraction (AWF), intra-axonal diffusivity (Daxon), axial extra-axonal space diffusivity (De,//), and radial extra-axonal space diffusivity (De,⊥) in multiple white matter (WM) regions. Relationships between diffusional metrics and clinical and cognitive functions were characterized.ResultsIn the TBSS analysis, the T2DM group exhibited decreased FA and AWF and increased MD, De,∥, and De,⊥ in widespread WM regions in comparison with the HC group, which involved 56.28%, 32.07%, 73.77%, 50.47%, and 75.96% of the mean WM skeleton, respectively (P < 0.05, TFCE-corrected). De,⊥ detected most of the WM changes, which were mainly located in the corpus callosum, internal capsule, external capsule, corona radiata, posterior thalamic radiations, sagittal stratum, cingulum (cingulate gyrus), fornix (stria terminalis), superior longitudinal fasciculus, and uniform fasciculus. Additionally, De,⊥ in the genu of the corpus callosum was significantly correlated with worse performance in TMT-A (β = 0.433, P < 0.001) and a longer disease duration (β = 0.438, P < 0.001).ConclusionsWMTI is more sensitive than diffusion tensor imaging in detecting T2DM-related WM microstructure abnormalities and can provide novel insights into the possible pathological changes underlying WM degeneration in T2DM. De,⊥ could be a potential imaging marker in monitoring disease progression in the brain and early intervention treatment for the cognitive impairment in T2DM

Endothelial Senescence: From Macro- to Micro-Vasculature and Its Implications on Cardiovascular Health

Endothelial cells line at the most inner layer of blood vessels. They act to control hemostasis, arterial tone/reactivity, wound healing, tissue oxygen, and nutrient supply. With age, endothelial cells become senescent, characterized by reduced regeneration capacity, inflammation, and abnormal secretory profile. Endothelial senescence represents one of the earliest features of arterial ageing and contributes to many age-related diseases. Compared to those in arteries and veins, endothelial cells of the microcirculation exhibit a greater extent of heterogeneity. Microcirculatory endothelial senescence leads to a declined capillary density, reduced angiogenic potentials, decreased blood flow, impaired barrier properties, and hypoperfusion in a tissue or organ-dependent manner. The heterogeneous phenotypes of microvascular endothelial cells in a particular vascular bed and across different tissues remain largely unknown. Accordingly, the mechanisms underlying macro- and micro-vascular endothelial senescence vary in different pathophysiological conditions, thus offering specific target(s) for therapeutic development of senolytic drugs

Сравнение ростовых характеристик тихоокеанской трески Gadus Macrocephalus российских вод Японского моря : выпускная бакалаврская работа по направлению подготовки: 060301 - Биология биоразнообразие

Triacylglycerols are considered one of the most promising feedstocks for biofuels. Phospholipid:diacylglycerol acyltransferase (PDAT), responsible for the last step of triacylglycerol synthesis in the acyl-CoA-independent pathway, has attracted much attention by catalyzing membrane lipid transformation. However, due to lack of biochemical and enzymatic studies, PDAT has not carried forward in biocatalyst application. Here, the PDAT from Saccharomyces cerevisiae was expressed in Pichia pastoris. The purified enzymes were studied using different acyl donors and acceptors by thin layer chromatography and gas chromatography. In addition of the preferred acyl donor of PE and PC, the results identified that ScPDAT was capable of using broad acyl donors such as PA, PS, PG, MGDG, DGDG, and acyl-CoA, and ScPDAT was more likely to use unsaturated acyl donors comparing 18:0/18:1 to 18:0/18:0 phospholipids. With regard to acyl acceptors, ScPDAT preferred 1,2 to 1,3-diacylglycerol (DAG), while 12:0/12:0 DAG was identified as the optimal acyl acceptor, followed by 18:1/18:1 and 18:1/16:0 DAG. Additionally, ScPDAT reveals esterification activity that can utilize methanol as acyl acceptor to generate fatty acid methyl esters. The results fully expand the enzymatic selectivity of ScPDAT and provide fundamental knowledge for synthesis of triacylglycerol-derived biofuels

Altering Emulsion Stability with Heterogeneous Surface Wettability

Emulsions–liquid droplets dispersed in another immiscible liquid–are widely used in a broad spectrum of applications, including food, personal care, agrochemical, and pharmaceutical products. Emulsions are also commonly present in natural crude oil, hampering the production and quality of petroleum fuels. The stability of emulsions plays a crucial role in their applications, but controlling the stability without external driving forces has been proven to be difficult. Here we show how heterogeneous surface wettability can alter the stability and dynamics of oil-in-water emulsions, generated by a co-flow microfluidic device. We designed a useful methodology that can modify a micro-capillary of desired heterogeneous wettability (e.g., alternating hydrophilic and hydrophobic regions) without changing the hydraulic diameter. We subsequently investigated the effects of flow rates and heterogeneous wettability on the emulsion morphology and motion. The experimental data revealed a universal critical timescale of advective emulsions, above which the microfluidic emulsions remain stable and intact, whereas below they become adhesive or inverse. A simple theoretical model based on a force balance can be used to explain this critical transition of emulsion dynamics, depending on the droplet size and the Capillary number–the ratio of viscous to surface effects. These results give insight into how to control the stability and dynamics of emulsions in microfluidics with flow velocity and different wettability

Simulation of Rock Electrical Properties in Deep Reservoirs Based on Digital Rock Technology

Deep reservoirs are in a high-pressure and high-temperature (HPHT) environment, while the experimental conditions for rock electrical properties that meet the deep reservoir conditions are harsh and costly. Although digital rock technology can simulate the electrical properties of rocks, it is limited to electrical simulation studies under normal temperature and pressure conditions (NPT), which limits their ability to capture the electrical characteristics of deep hydrocarbon reservoirs. This limitation affects the accuracy of saturation prediction based on resistivity logging. To simulate the rock electrical properties under HPHT conditions, we proposed a low-cost and high-efficiency HPHT digital rock electrical simulation workflow. Firstly, samples from deep formations were CT-scanned and used to construct multi-component digital rocks that reflect the real microstructure of the samples. Then, mathematical morphology was used to simulate the overburden correction under high-pressure conditions, and the changes in the conductivity of formation water and clay minerals at different temperatures were used to simulate the conductivity changes of rock components under high-temperature conditions. To carry out the electrical simulation of digital rock in deep reservoirs, a numerical simulation condition for HPHT in deep layers was established, and the finite element method (FEM) was used. Finally, based on the equivalent changes in the conductivity of different components, the effects of clay minerals and formation water under HPHT conditions on rock electrical properties were studied and applied to predict the water saturation based on well logging data. We found that considering the influence of temperature, salinity, and clay type, the saturation index (n) of the rock depends on the ratio of the clay conductivity to the formation water conductivity. The larger the ratio is, the smaller the value of n. In addition, the average relative error between the predicted water saturation under HPHT conditions and the sealed coring analysis was 6.8%, which proved the accuracy of the proposed method. Overall, this method can effectively simulate the pressure and temperature environment of deep formations, reveal the electrical conductivity mechanisms of rocks under formation pressure and temperature conditions, and has promising prospects for the study of rock physical properties and reservoir evaluation in deep formations