Rosmarinic acid suppresses the progression of COPD Syk by modulating airway inflammation and epithelial apoptosis and .

Rosmarinic acid (RosA), a hydrophilic phenolic compound found in various plants, has several biological effects such as anti-inflammatory and anti-apoptosis activities. However, its potential impact on chronic obstructive pulmonary disease (COPD) and its underlying mechanism has not been investigated. In this study, we explored the potential therapeutic effects and mechanism of RosA on COPD airway inflammation and alveolar epithelial apoptosis and .

New phenols and one aminobenzoic acid derivative isolated from the roots of Rhus chinensis Mill.

Four new phenols and one new aminobenzoic acid derivative, with five known phenols were isolated from the roots of Rhus chinensis Mill. Their structures were elucidated by UV, IR, HRESIMS, 1D and 2D NMR spectra, as well as optical rotations. Compound 4 significantly inhibited mouse ear inflammation (inhibitory rate of 44.

Lottery Jackpots Exist in Pre-Trained Models.

Network pruning is an effective approach to reduce network complexity with acceptable performance compromise. Existing studies achieve the sparsity of neural networks via time-consuming weight training or complex searching on networks with expanded width, which greatly limits the applications of network pruning. In this paper, we show that high-performing and sparse sub-networks without the involvement of weight training, termed "lottery jackpots", exist in pre-trained models with unexpanded width.

Phenolic glycosides and indole alkaloids isolated from the roots and rhizomes of Clematis chinensis and their anti-inflammatory activity.

Six undescribed compounds, including three phenolic glycosides (1-3) and three indole alkaloids (4-6), together with ten known alkaloids (7-16) and three known phenolic glycosides (17-19), were isolated from 70% EtOH aqueous extracts of the roots and rhizomes of Clematis chinensis Osbeck. The structures were elucidated by NMR, HRESIMS and X-ray diffraction spectroscopies. The anti-inflammatory activity of these compounds was evaluated, and twelve compounds showed significant inhibitory activity against TNF-α with an inhibition ratio from 47.

Training Compact CNNs for Image Classification Using Dynamic-Coded Filter Fusion.

The mainstream approach for filter pruning is usually either to force a hard-coded importance estimation upon a computation-heavy pretrained model to select "important" filters, or to impose a hyperparameter-sensitive sparse constraint on the loss objective to regularize the network training. In this paper, we present a novel filter pruning method, dubbed dynamic-coded filter fusion (DCFF), to derive compact CNNs in a computation-economical and regularization-free manner for efficient image classification. Each filter in our DCFF is first given an inter-similarity distribution with a temperature parameter as a filter proxy, on top of which, a fresh Kullback-Leibler divergence based dynamic-coded criterion is proposed to evaluate the filter importance.

Prioritized Subnet Sampling for Resource-Adaptive Supernet Training.

A resource-adaptive supernet adjusts its subnets for inference to fit the dynamically available resources. In this paper, we propose prioritized subnet sampling to train a resource-adaptive supernet, termed PSS-Net. We maintain multiple subnet pools, each of which stores the information of substantial subnets with similar resource consumption.

Reactive Oxygen Species-Responsive Polypeptide Drug Delivery System Targeted Activated Hepatic Stellate Cells to Ameliorate Liver Fibrosis.

Hepatic fibrosis is a chronic liver disease that lacks effective pharmacotherapeutic treatments. As part of the disease's mechanism, hepatic stellate cells (HSCs) are activated by damage-related stimuli to secrete excessive extracellular matrix, leading to collagen deposition. Currently, the drug delivery system that targets HSCs in the treatment of liver fibrosis remains an urgent challenge due to the poor controllability of drug release.

SiMaN: Sign-to-Magnitude Network Binarization.

Binary neural networks (BNNs) have attracted broad research interest due to their efficient storage and computational ability. Nevertheless, a significant challenge of BNNs lies in handling discrete constraints while ensuring bit entropy maximization, which typically makes their weight optimization very difficult. Existing methods relax the learning using the sign function, which simply encodes positive weights into +1s, and -1s otherwise.

1xN Pattern for Pruning Convolutional Neural Networks.

Though network pruning receives popularity in reducing the complexity of convolutional neural networks (CNNs), it remains an open issue to concurrently maintain model accuracy as well as achieve significant speedups on general CPUs. In this paper, we propose a novel 1×N pruning pattern to break this limitation. In particular, consecutive N output kernels with the same input channel index are grouped into one block, which serves as a basic pruning granularity of our pruning pattern.

Pruning Networks With Cross-Layer Ranking & k-Reciprocal Nearest Filters.

This article focuses on filter-level network pruning. A novel pruning method, termed CLR-RNF, is proposed. We first reveal a "long-tail" pruning problem in magnitude-based weight pruning methods and then propose a computation-aware measurement for individual weight importance, followed by a cross-layer ranking (CLR) of weights to identify and remove the bottom-ranked weights.

Distilling a Powerful Student Model via Online Knowledge Distillation.

Existing online knowledge distillation approaches either adopt the student with the best performance or construct an ensemble model for better holistic performance. However, the former strategy ignores other students' information, while the latter increases the computational complexity during deployment. In this article, we propose a novel method for online knowledge distillation, termed feature fusion and self-distillation (FFSD), which comprises two key components: FFSD, toward solving the above problems in a unified framework.

A full set of 8,4'-oxy-8'-phenylneolignan stereoisomers from Sophora tonkinensis and their absolute configurations by TDDFT.

A full set of 8,4'-oxy-8'-phenylneolignans with four chiral carbons, named (+)/(-)-leptolepisols D1‒D2 and (+)/(-)-sophorols A‒F, were isolated from the roots and rhizomes of Sophora tonkinensis Gagnep., including 14 previously undescribed stereoisomers, along with 2 known leptolepisol D diastereomers. Their planar structures and relative configurations were elucidated by detailed spectroscopic analysis (HRESIMS and NMR).

Carrying Out CNN Channel Pruning in a White Box.

Channel pruning has been long studied to compress convolutional neural networks (CNNs), which significantly reduces the overall computation. Prior works implement channel pruning in an unexplainable manner, which tends to reduce the final classification errors while failing to consider the internal influence of each channel. In this article, we conduct channel pruning in a white box.

Perilla Leaf Extract (PLE) Attenuates COPD Airway Inflammation the TLR4/Syk/PKC/NF-κB Pathway and .

Chronic obstructive pulmonary disease (COPD) is a complex and heterogeneous disease characterized by persistent airflow limitation but still lacking effective treatments. Britt. an important traditional medicinal plant with excellent antioxidant and anti-inflammatory properties, is widely used for the treatment of respiratory disease in China.

Design, synthesis, and pharmacological evaluation of sinomenine derivatives on rings A and C: Novel compounds screening for aplastic anemia targeting on cytotoxic T lymphocyte.

Cytotoxic T lymphocyte (CTL), a key effector cell in aplastic anemia (AA) immune injury, is shown to be a potential target for AA drug therapy. However, there is no candidate for this target till now. Oriented by the inhibition activity of CTL and macrophage derived nitric oxide (NO), a series of novel sinomenine derivatives on rings A and C are designed, synthesized and screened.

Filter Sketch for Network Pruning.

We propose a novel network pruning approach by information preserving of pretrained network weights (filters). Network pruning with the information preserving is formulated as a matrix sketch problem, which is efficiently solved by the off-the-shelf frequent direction method. Our approach, referred to as FilterSketch, encodes the second-order information of pretrained weights, which enables the representation capacity of pruned networks to be recovered with a simple fine-tuning procedure.

Prenylaromadendrane-type diterpenoids from the gum resin of flueck and their cytotoxic effects.

Two new prenylaromadendrane-type diterpenoids, and three known analogues, were isolated from the ethanol extract of the gum resin of Flueck. The structures of the new compounds were elucidated using 1 D and 2 D NMR spectroscopic analyses, mass spectrometric data, circular dichroism spectra, and comparison with the other compounds in the literature. One diterpenoid represents the first example of an acetoxyl-substituted prenylaromadendranoid in frankincense.

Network Pruning Using Adaptive Exemplar Filters.

Popular network pruning algorithms reduce redundant information by optimizing hand-crafted models, and may cause suboptimal performance and long time in selecting filters. We innovatively introduce adaptive exemplar filters to simplify the algorithm design, resulting in an automatic and efficient pruning approach called EPruner. Inspired by the face recognition community, we use a message-passing algorithm Affinity Propagation on the weight matrices to obtain an adaptive number of exemplars, which then act as the preserved filters.

Syk-Targeted, a New 3-Arylbenzofuran Derivative EAPP-2 Blocks Airway Inflammation of Asthma-COPD Overlap in vivo and in vitro.

Introduction: Asthma-chronic obstructive pulmonary (COPD) overlap (ACO) coexists with asthma and COPD syndrome characteristics, with more frequent exacerbations, heavier disease burden, higher medical utilization, and even lower quality of life. However, the ACO standard medications supported by evidence-based medicine have not yet appeared.

Methods: By using an ACO mouse model established previously and LPS-stimulated RAW264.

Perilla Leaf Extract Attenuates Asthma Airway Inflammation by Blocking the Syk Pathway.

(L.) Britton is a classic herbal plant used widely against asthma in China. But its mechanism of beneficial effect remains undermined.

Polycyclic polyprenylated acylphloroglucinol derivatives from Hypericum pseudohenryi.

Seven previously unidentified polycyclic polyprenylated acylphloroglucinol (PPAP) derivatives hypseudohenrins A-G, along with six known analogs, were isolated from the aerial portion of Hypericum pseudohenryi. Their structures were determined by NMR, ECD and X-ray crystallographic spectroscopy. These compounds were screened for anti-inflammatory activity, and hypseudohenrins B and G (at the concentration of 10 μM) showed NO production inhibition ratios of 52.

Comparative RNA-Seq Transcriptome Analysis on Pulmonary Inflammation in a Mouse Model of Asthma-COPD Overlap Syndrome.

Asthma-chronic obstructive pulmonary disease (COPD) overlap (ACO) is a severe clinical syndrome characterized to describe patients with both asthma and COPD clinical characteristics, which has posed a serious threat to patients' quality of life and life safety. However, there are many difficulties and uncertainties in its diagnosis and treatment in clinic; especially, its animal model has not been fully and thoroughly established, and the evaluation of therapeutic drugs is still in its infancy. Here, we used ovalbumin (OVA), lipopolysaccharide (LPS), and smoke costimulation to establish an ACO mouse model and then used RNA-seq technology to detect gene expression in mouse lung tissue.