Unified Architecture Adaptation for Compressed Domain Semantic Inference.

Advances in both lossy image compression and semantic content understanding have been greatly fueled by deep learning techniques, yet these two tasks have been developed separately for the past decades. In this work, we address the problem of directly executing semantic inference from quantized latent features in the deep compressed domain without pixel reconstruction. Although different methods have been proposed for this problem setting, they either are restrictive to a specific architecture, or are sub-optimal in terms of compressed domain task accuracy. In contrast, we propose a lightweight, plug-and-play solution which is generally compliant with popular learned image coders and deep vision models, making it attractive to vast applications. Our method adapts prevalent pixel domain neural models that are deployed for various vision tasks to directly accept quantized latent features (other than pixels). We further suggest training the compressed domain model by transferring knowledge from its corresponding pixel domain counterpart. Experiments show that our method is compliant with popular learned image coders and vision task models. Under fair comparison, our approach outperforms a baseline method by a) more than 3% top-1 accuracy for compressed domain classification, and b) more than 7% mIoU for compressed domain semantic segmentation, at various data rates.

Mechanisms of Endoplasmic Reticulum Protein Homeostasis in Plants.

Maintenance of proteome integrity is essential for cell function and survival in changing cellular and environmental conditions. The endoplasmic reticulum (ER) is the major site for the synthesis of secretory and membrane proteins. However, the accumulation of unfolded or misfolded proteins can perturb ER protein homeostasis, leading to ER stress and compromising cellular function. Eukaryotic organisms have evolved sophisticated and conserved protein quality control systems to ensure protein folding fidelity via the unfolded protein response (UPR) and to eliminate potentially harmful proteins via ER-associated degradation (ERAD) and ER-phagy. In this review, we summarize recent advances in our understanding of the mechanisms of ER protein homeostasis in plants and discuss the crosstalk between different quality control systems. Finally, we will address unanswered questions in this field.

Characterization and Anti-Aging Activity of Polysaccharides from Akebia trifoliata Fruit Separated by an Aqueous Two-Phase System.

Bioactive polysaccharides have numerous pharmacological effects that are beneficial to human health. Akebia trifoliata (Thunb.) Koidz. has great development prospects as a food resource with medicinal value. The polysaccharides (ATFP) were extracted from A. trifoliata fruit by an aqueous two-phase system. ATFP-3, purified with DEAE-52 and Sephadex G-200 from ATFP, was mainly composed of glucose (47.55%) and galactose (20.39%). Its hydroxyl radical scavenging rate was 89.30% at 1.60 mg/mL and its IC50 was 0.29 mg/mL. ATFP-3 significantly enhanced the survival rate of Caenorhabditis elegans under thermal or oxidative stress. Furthermore, ATFP-3 could prolong the lifespan of C. elegans and improve the activities of the antioxidant enzyme, while also decrease the accumulation of lipofuscin and the level of malondialdehyde (MDA) in aging worms. Thus, ATFP-3 has application potential in health benefits for humans.

[Mechanism of Chaenomelis Fructus in treatment of rheumatoid arthritis based on network pharmacology and experimental verification].

The material basis and mechanism of Chaenomelis Fructus in the treatment of rheumatoid arthritis(RA) were explored by network pharmacology, and the potential anti-RA targets of Chaenomelis Fructus were verified by molecular docking and animal experiments. The active components and targets of Chaenomelis Fructus were searched against the Traditional Chinese Medicine System Pharmacology Database and Analysis Platform. GeneCards, DisGeNET, and OMIM were used to obtain RA-related targets. The common targets shared by Chaenomelis Fructus and RA were considered as the potential targets of Chaenomelis Fructus in the treatment of RA. Cytoscape 3.9.0 was employed to establish a "traditional Chinese medicine-active component-common target-disease" network. The protein-protein interaction(PPI) network was established by STRING, and the core genes were visualized by RStudio 4.1.0. DAVID was used for Gene Ontology(GO) annotation and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment to predict and visualize the involved signaling pathways. Molecular docking was carried out with the active components screened out as ligands and RA core genes as the targets. Finally, the prediction results were verified by animal experiments. Four main active components of Chaenomelis Fructus were obtained, which corresponded to 137 targets. Chaenomelis Fructus and RA shared 37 common targets. GO annotation yielded 239 terms(P<0.05), and KEGG pathway enrichment analysis screened out 94 signaling pathways(P<0.05), mainly involving interleukin-17(IL-17), tumor necrosis factor, Toll-like receptor, and nuclear factor-kappa B(NF-κB) signaling pathways. Molecular docking results showed that the main active components of Chaenomelis Fructus bound well with the core targets of RA. The results of animal experiments proved that Chaenomelis Fructus can alleviate joint swelling in the mice with RA. The results of ELISA showed that Chaenomelis Fructus lowered the levels of interleukin-6(IL-6) and interleukin-1ß(IL-1ß). Western blot showed that Chaenomelis Fructus down-regulated the protein level of vascular endothelial growth factor A(VEGFA). Chaenomelis Fructus exerts anti-inflammatory effect and reduces pannus formation by regulating the core targets such as VEGFA, IL-1ß, and IL6 in the treatment of RA. The findings of this study provide new ideas for the future treatment of RA with Chaenomelis Fructus.

Selection and validation of reference genes for measuring gene expression in Toona ciliata under different experimental conditions by quantitative real-time PCR analysis.

BACKGROUND: Before studying gene expression of different organisms, it is important to determine the best reference gene. At present, the most accurate method of detecting gene expression is quantitative real-time PCR (RT-qPCR). With this method, reference genes that are stable in different biological systems and under different conditions can be obtained. Toona ciliata Roem (T. ciliata). is a valuable and fast-growing timber specie. In this study, 20 reference genes were identified using RT-qPCR, as a primary prerequisite for future gene expression analysis. Four different methods, geNorm, NormFinder, BestKeeper, and RankAggreg were used to evaluate the expression stability of the 20 candidate reference genes in various tissues under different conditions. RESULTS: The experimental results showed that TUB-α was the most stably expressed reference gene across all samples and UBC17 was the most stable in leaves and young stems under Hypsipyla robusta (H. robusta) and methyl jasmonate (MeJA) treatments. In addition, PP2C59 and UBC5B were the best-performing genes in leaves under H. robusta treatment, while HIS1 and ACT7 were the best reference genes in young stems. The two best reference genes were 60S-18 and TUB-α after treatment at 4 °C. The expression of HIS6 and MUB1 was the most stable under PEG6000 treatment. The accuracy of the selected reference genes was verified using the transcription factor MYB3 (TcMYB3) gene. CONCLUSIONS: This is the first report to verify the best reference genes for normalizing gene expression in T. ciliata under different conditions, which will facilitate future elucidation of gene regulations in this species.

Balancing the Encoder and Decoder Complexity in Image Compression for Classification.

This paper presents a study on the computational complexity of coding for machines, with a focus on image coding for classification. We first conduct a comprehensive set of experiments to analyze the size of the encoder (which encodes images to bitstreams), the size of the decoder (which decodes bitstreams and predicts class labels), and their impact on the rate-accuracy trade-off in compression for classification. Through empirical investigation, we demonstrate a complementary relationship between the encoder size and the decoder size, i.e., it is better to employ a large encoder with a small decoder and vice versa. Motivated by this relationship, we introduce a feature compression-based method for efficient image compression for classification. By compressing features at various layers of a neural network-based image classification model, our method achieves adjustable rate, accuracy, and encoder (or decoder) size using a single model. Experimental results on ImageNet classification show that our method achieves competitive results with existing methods while being much more flexible. The code will be made publicly available.

QARV: Quantization-Aware ResNet VAE for Lossy Image Compression.

This paper addresses the problem of lossy image compression, a fundamental problem in image processing and information theory that is involved in many real-world applications. We start by reviewing the framework of variational autoencoders (VAEs), a powerful class of generative probabilistic models that has a deep connection to lossy compression. Based on VAEs, we develop a new scheme for lossy image compression, which we name quantization-aware ResNet VAE (QARV). Our method incorporates a hierarchical VAE architecture integrated with test-time quantization and quantization-aware training, without which efficient entropy coding would not be possible. In addition, we design the neural network architecture of QARV specifically for fast decoding and propose an adaptive normalization operation for variable-rate compression. Extensive experiments are conducted, and results show that QARV achieves variable-rate compression, high-speed decoding, and better rate-distortion performance than existing baseline methods.

Exploring the potential molecular mechanism of Gualou Guizhi decoction in the treatment of rheumatoid arthritis based on network pharmacology and molecular docking.

BACKGROUND: Traditional Chinese medicine (TCM) has been used in China for a long time and is gradually gaining more and more recognition worldwide. Gualou Guizhi Decoction (GGD) has long been used as a folk medicine for the treatment of rheumatic diseases, but its bioactive components and therapeutic mechanisms are still unclear. METHODS: An integrated approach using network pharmacology and molecular docking and using methotrexate as a positive control drug. RESULTS: We obtained 157 active ingredients of GGD, 7542 RA disease targets and 49 intersecting targets. GO and KEGG enrichment analysis revealed that their functions were mainly related to cytokine active metal ion binding, enzyme binding and DNA binding, and enriched in TNF signaling pathway, T cell receptor signaling pathway, Toll-like receptor signaling pathway, RA pathway and other signaling pathways that are closely related to RA. The molecular docking results show that the effector components of GGD bind better to the core targets of RA, and some are even better than methotrexate. CONCLUSION: The therapeutic effect of GGD for RA is achieved by affecting the core targets such as VEGFA, IL-1ß, IL6, CXCL8, CCL2, and JUN, which together interfere with the tumor necrosis factor signaling pathway and RA pathway to treat RA. The above study provides new ideas for further exploration of this classic formula in the future.

Macronutrient digestion and polyphenol bioaccessibility in oat milk tea products: an in vitro gastrointestinal tract study.

People are increasingly preparing milk tea using plant-based milks rather than cow's milk, e.g., vegans, those with lactose intolerance, and those with flavor preferences. However, adding plant-based milks to tea may impact the digestion, release, and bioaccessibility of nutrients and nutraceuticals in both the tea and milk. In this study, oat milk tea model systems (OMTMSs) containing different fat and tea polyphenol concentrations were used to explore the impact of tea on macronutrient digestion in oat milk, as well as the impact of oat milk matrix on the polyphenol bioaccessibility in the tea. An in vitro gastrointestinal model that mimics the mouth, stomach, and small intestine was used. Tea polyphenols (>0.25%) significantly reduced the glucose and free fatty acids released from oat milk after intestinal digestion. Tea polyphenols (>0.10%) also inhibited protein digestion in oat milk during gastric digestion but not during intestinal digestion. The bioaccessibility of the polyphenols in the tea depended on the fat content of oat milk, being higher for medium-fat (3.0%) and high-fat (5.8%) oat milk than low-fat (1.5%) oat milk. Liquid chromatography-tandem mass spectrometry (UPLC-ESI-MS/MS) analysis showed that lipids improved the tea polyphenol bioaccessibility by influencing the release of flavonoids and phenolic acids from the food matrices. These results provide important information about the impact of tea on the gastrointestinal fate of oat milk, and vice versa, which may be important for enhancing the healthiness of plant-based beverages.

Fabrication, characterization, and bioactivity of self-assembled carrier-free colloidal dispersions from Citrus × Limon 'Rosso' essential oil and tea polyphenols.

Carrier-free nanodelivery systems are fully self-assembled from active ingredients through interactions, offering the advantages of green, safe, and large-scale manufacturing. To improve the dispersion of Citrus × limon 'Rosso' peel essential oil (CEO) in water and boost the biological activity of CEO and tea polyphenols (TP), self-assembled CEO-TP colloidal dispersions (CEO-TP Colloids) were fabricated through sonication without surfactants or carriers. The optimal CEO and TP concentrations in the CEO-TP Colloids were determined to be 10.0 and 20.0 mg/mL by particle size and stability analyzer, respectively. The CEO self-assembled with TP to form spherical nanoparticles through hydrophobic and hydrogen-bonding interactions, whereas the CEO in CEO-TP Colloids weakened TP intramolecular aggregation. Meanwhile, the CEO-TP Colloids showed synergistic effects with better antibacterial, cellular antioxidant, and anti-inflammatory activities than single components. This study opens up the possibility of carrier-free co-delivery of hydrophobic and hydrophilic active components developed into food-grade formulations with multiple bioactivities.

Predicting the Progress of Tuberculosis by Inflammatory Response-Related Genes Based on Multiple Machine Learning Comprehensive Analysis.

Background: Tuberculosis (TB), caused by the bacterium Mycobacterium tuberculosis, affects approximately one-quarter of the global population and is considered one of the most lethal infectious diseases worldwide. The prevention of latent tuberculosis infection (LTBI) from progressing into active tuberculosis (ATB) is crucial for controlling and eradicating TB. Unfortunately, currently available biomarkers have limited effectiveness in identifying subpopulations that are at risk of developing ATB. Hence, it is imperative to develop advanced molecular tools for TB risk stratification. Methods: The TB datasets were downloaded from the GEO database. Three machine learning models, namely LASSO, RF, and SVM-RFE, were used to identify the key characteristic genes related to inflammation during the progression of LTBI to ATB. The expression and diagnostic accuracy of these characteristic genes were subsequently verified. These genes were then used to develop diagnostic nomograms. In addition, single-cell expression clustering analysis, immune cell expression clustering analysis, GSVA analysis, immune cell correlation, and immune checkpoint correlation of characteristic genes were conducted. Furthermore, the upstream shared miRNA was predicted, and a miRNA-genes network was constructed. Candidate drugs were also analyzed and predicted. Results: In comparison to LTBI, a total of 96 upregulated and 26 downregulated genes related to the inflammatory response were identified in ATB. These characteristic genes have demonstrated excellent diagnostic performance and significant correlation with many immune cells and immune sites. The results of the miRNA-genes network analysis suggested a potential role of hsa-miR-3163 in the molecular mechanism of LTBI progressing into ATB. Moreover, retinoic acid may offer a potential avenue for the prevention of LTBI progression to ATB and for the treatment of ATB. Conclusion: Our research has identified key inflammatory response-related genes that are characteristic of LTBI progression to ATB and hsa-miR-3163 as a significant node in the molecular mechanism of this progression. Our analyses have demonstrated the excellent diagnostic performance of these characteristic genes and their significant correlation with many immune cells and immune checkpoints. The CD274 immune checkpoint presents a promising target for the prevention and treatment of ATB. Furthermore, our findings suggest that retinoic acid may have a role in preventing LTBI from progressing to ATB and in treating ATB. This study provides a new perspective for differential diagnosis of LTBI and ATB and may uncover potential inflammatory immune mechanisms, biomarkers, therapeutic targets, and effective drugs in the progression of LTBI into ATB.

Fabrication and characterization of l-ascorbyl palmitate and phospholipid-based hybrid liposomes and their impacts on the stability of loaded hydrophobic polyphenols.

The aim of this study was to evaluate the influence of l-ascorbyl palmitate (LAP) as an additive to liposome formulations by self-assembling with soy lecithin to form hybrid liposomes, in order to enhance the physical stability and bioactivator-loaded retention ratio of the LAP incorporated liposomes (LAP-LP). The addition of LAP significantly increased its surface negative charge and strong hydrophobic interactions occurred between the hydrophobic tails of LAP and phospholipids resulting in more compactly ordered, rigid and hydrophobic phospholipid bilayers as indicated by surface tension, fluorescence probes and DSC. These changes enhanced the stability of hydrophobic polyphenol loaded LAP-LP during storage. Particularly, after four weeks storage at 37 °C for naringenin loaded liposomes, the retention ratio of pure liposome decreased dramatically to 12.5 %, while the LAP-LP remained above 74.5 %. This study opens up the potential for the LAP-LP to be developed as a food-grade multifunctional formulation for encapsulating and delivering bioactivators.

Exploring the chondroprotective effect of Chaenomeles speciosa on Glucose-6-Phosphate Isomerase model mice using an integrated approach of network pharmacology and experimental validation.

ETHNOPHARMACOLOGICAL RELEVANCE: Traditional Chinese medicine (TCM) has been used in China for a long time and is gradually gaining more and more recognition worldwide. Chaenomeles speciosa (CSP) (Chinese Pinyin: mugua) is a medicinal and food herb that has long been used as a folk medicine for rheumatic diseases, yet its bioactive components and therapeutic mechanisms are not clear. AIM OF THE STUDY: Exploring anti-inflammatory and chondroprotective effects of CSP on rheumatoid arthritis (RA) and its possible targets of action. MATERIALS AND METHODS: In this study, we performed an integrated approach of network pharmacology, molecular docking and experimental studies to explore the potential mechanism of action of CSP in the treatment of cartilage damage in RA. RESULTS: Studies have shown that Quercetin, ent-Epicatechin and Mairin may be the main active compounds of CSP in the treatment of RA, while AKT1, VEGFA, IL-1ß, IL-6, MMP9 etc. are considered as core target proteins to which the main active compounds in CSP bind, as further confirmed by molecular docking. In addition, the potential molecular mechanism of CSP for the treatment of cartilage damage in RA predicted by network pharmacology analysis was validated by in vivo experiments. CSP was found to downregulate the expression of AKT1, VEGFA, IL-1ß, IL-6, MMP9, ICAM1, VCAM1, MMP3, MMP13 and TNF-α and increase the expression of COL-2 in the joint tissue of Glucose-6-Phosphate Isomerase (G6PI) model mice. Thus CSP contributes to the treatment of rheumatoid arthritis cartilage destruction. CONCLUSION: This study showed that CSP has multi-component, multi-target and multi-pathway characteristics in treating cartilage damage in RA, which can achieve the effect of treating RA by inhibiting the expression of inflammatory factors, reducing neovascularization and alleviating the damage to cartilage caused by the diffusion of synovial vascular opacities, and reducing the degradation of cartilage by MMPs to play a protective role in RA cartilage damage. In conclusion, this study indicates that CSP is a candidate Chinese medicine for further research in treating cartilage damage in RA.

Transcriptome profiling of Toona ciliata young stems in response to Hypsipyla robusta Moore.

Toona ciliata is a traditional woody plant that can be used as a medicinal material in China. The extracts of its roots, stems, leaves, and flowers all have a wide range of bioactive compounds. However, T. ciliata has been facing an unresolved pest problem caused by Hypsipyla robusta Moore (HRM), which seriously affects its growth and development. In this study, the expression level of TcMYB3 gene reached the maximum (28-fold) at 12 h and transcriptome sequencing of young stems eaten by HRM for 0, 3, 12, and 21 h were performed. A large number of differentially expressed genes (DEGs) were identified including jointly up-regulated genes (263) and down-regulated genes (378). JA synthesis and signaling transduction, terpene biosynthesis, and MAPKs signaling pathway were analyzed in depth and found that TcOPR3, TcJAR1, TcJAZs, and TcTPS9 genes possessed anti-insect potential. Moreover, MYB and ERF transcription factor (TF) families were significantly strengthened to the point that they may participate in induced defense mechanisms in T. ciliata. These data not only provide insights into the molecular mechanisms in resistance of T. ciliata to HRM but also helps to explore the new biocontrol strategies against insects in eco-friendly woody plants.