This review is to summarize the reports published in the past 10 years on the protective mechanism of 74 different intervention methods on lung injury through restraining nuclear factor kappa-B (NF-[Formula: see text]B) signaling pathway. We summarized the experimental studies on animal lung injury models of NF-[Formula: see text]B, MAPK/NF-[Formula: see text]B, PI3K/Akt/NF-[Formula: see text]B, TLR4/NF-[Formula: see text]B, NF-[Formula: see text]B/NALP3, NF-[Formula: see text]B/NLRP3 and other NF-[Formula: see text]B-related signal pathways. Lung injury leads to high mortality worldwide. Many potential mechanisms for the treatment and prevention of lung injury are still unclear. In addition to the use of lung protection strategies, currently, there are no effective drugs for lung injury treatment. Preemptive NF-[Formula: see text]B inhibition protects cells from damage, but inhibition at the decomposition stage delays tissue repair. Therefore, we think there is a need to conduct further studies that can provide more insights for future treatment and prevention of lung injury.

The objective of this research is to study the effects of static resistance training of neck muscles on neck-type cervical spondylosis (NTCS) with upper cross syndrome (UCS). The NTCS patients with UCS were randomly divided into an observation group and a control group. The observation group was given conventional therapy plus static resistance training of neck muscles, while the control group was given conventional therapy plus ordinary cervical exercises. The scores of the visual analogue scale (VAS), neck disability index (NDI), and clinical assessment scale for cervical spondylosis (CASCS) and the cervical physiological curve were compared, and the overall efficacy was analyzed. After treatment, the VAS and NDI scores were lower in the observation group than in the control group. The cervical physiological curve was more significant in the observation group. The CASCS score was higher in the observation group than the control group after treatment. The observation group had obviously superior clinical efficacy. Therefore, in the treatment of NTCS with UCS, static resistance training of neck muscles can ameliorate the clinical symptoms of patients and restore the cervical physiological curve, with definite short-term efficacy, making it superior to ordinary cervical exercises, so it is worthy of clinical popularization.

Real-time driving scene parsing using semantic segmentation is an essential yet challenging task for an autonomous driving system, where both efficiency and accuracy need to be considered simultaneously. In this article, we propose an efficient and high-performance deep neural network called feature selective fusion network (FSFnet) for robust semantic segmentation of road scenes. Since the complex driving scene parsing usually requires the fusion of features in different levels or scales, we propose a feature selective fusion module (FSFM) to adaptively merge these features by generating correlated weight maps in both spatial and channelwise. Furthermore, a multiscale context enhancement module is designed based on an asymmetric nonlocal neural network to aggregate both multiscale and global context information. The proposed FSFnet obtains precise segmentation results in real time on Cityscapes and CamVid data sets. Specifically, the architecture achieves 77.1% mean pixel intersection-over-union (mIoU) on the Cityscapes test set at a speed of 53 frames per second (FPS) for a $1024\times 2048$ input and 75.1% mIoU on the CamVid test set at a speed of 123 FPS for a $960\times 720$ input on a single NVIDIA 2080 TI GPU.

Glioblastoma (GBM) tumor is the most common primary brain malignant tumor. The precise identification of GBM tumors is very important for diagnosis and treatment. Hyperspectral imaging is a fast, noncontact, accurate, and safe modern medical detection technology, which is expected to be a new tool of intraoperative diagnosis. In order to make full use of the spectral and spatial information of hyperspectral images (HSIs) to achieve accurate GBM tumor identification, a method based on the fusion of multiple deep models is proposed for in vivo human brain HSI classification. The proposed method includes the following major steps: 1) spectral phasor analysis and data oversampling; 2) 1-D deep neural network (1D-DNN)-based spectral HSI feature extraction and classification; 3) 2-D convolution neural network (2D-CNN)-based spectral–spatial HSI feature extraction and classification; 4) edge-preserving filtering-based classification result fusion and optimization; and 5) fully convolutional network (FCN)-based background segmentation. To verify the capabilities of the proposed method, experiments are performed on two real human brain hyperspectral datasets, including 36 in vivo HSIs captured from 16 different patients. The proposed method can achieve an overall accuracy of 96.69% for four-class classification and overall accuracy of 96.34% for GBM tumor identification. Experimental results demonstrate that the proposed method exhibits competitive classification performance and can generate satisfactory thematic maps of the location of the GBM tumor, which can provide the surgeon with guidance on successful and precise tumor resection.

A "closed-loop" insulin delivery system that can mimic the dynamic and glucose-responsive insulin secretion as islet β-cells is desirable for the therapy of type 1 and advanced type 2 diabetes mellitus (T1DM and T2DM). Herein, we introduced a kind of "core-shell"-structured glucose-responsive nanoplatform to achieve intravenous "smart" insulin delivery. A finely controlled one-pot biomimetic mineralization method was utilized to coencapsulate insulin, glucose oxidase (GOx), and catalase (CAT) into the ZIF-8 nanoparticles (NPs) to construct the "inner core", where an efficient enzyme cascade system (GOx/CAT group) served as an optimized glucose-responsive module that could rapidly catalyze glucose to yield gluconic acid to lower the local pH and effectively consume the harmful byproduct hydrogen peroxide (H2O2), inducing the collapse of pH-sensitive ZIF-8 NPs to release insulin. The erythrocyte membrane, a sort of natural biological derived lipid bilayer membrane which has intrinsic biocompatibility, was enveloped onto the surface of the "inner core" as the "outer shell" to protect them from elimination by the immune system, thus making the NPs intravenously injectable and could stably maintain a long-term existence in blood circulation. The in vitro and in vivo results indicate that our well-designed nanoplatform possesses an excellent glucose-responsive property and can maintain the blood glucose levels of the streptozocin (STZ)-induced type 1 diabetic mice at the normoglycemic state for up to 24 h after being intravenously administrated, confirming an intravenous insulin delivery strategy to overcome the deficits of conventional daily multiple subcutaneous insulin administration and offering a potential candidate for long-term T1DM treatment.