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Innovation is the source of social progress, and all walks of life need to cultivate innovative talents. Therefore, it is also very important to cultivate innovative ability in physical education students in colleges and universities. The purpose of this paper is to study the cultivation of students’ innovative ability of physical education majors in colleges and universities based on the multimedia environment of the Internet of things and to open up a new path for the cultivation of college students’ innovative ability. In this paper, a terminal collaborative indoor positioning algorithm based on RSSI fingerprint optimization was proposed to study the innovation ability of physical education students in colleges and universities. Through experimental analysis, college A was taken as the research object, and 1500 students were investigated. Innovation had a very important position in the hearts of 76.21% of students, and 3.83% of students believed that innovation was not important. In the minds of most people, innovation was still very important, which showed that schools still had a certain effect on the education of students’ innovative consciousness. The experimental results obtained showed that the Internet of things technology played an important role in the research on the innovation ability of students majoring in physical education in colleges and universities.

Clustered regularly interspaced short palindromic repeats (CRISPR) system provides adaptive immunity against plasmids and phages in prokaryotes. This system inspires the development of a powerful genome engineering tool, the CRISPR/CRISPR-associated nuclease 9 (CRISPR/Cas9) genome editing system. Due to its high efficiency and precision, the CRISPR/Cas9 technique has been employed to explore the functions of cancer-related genes, establish tumor-bearing animal models and probe drug targets, vastly increasing our understanding of cancer genomics. Here, we review current status of CRISPR/Cas9 gene editing technology in oncological research. We first explain the basic principles of CRISPR/Cas9 gene editing and introduce several new CRISPR-based gene editing modes. We next detail the rapid progress of CRISPR screening in revealing tumorigenesis, metastasis, and drug resistance mechanisms. In addition, we introduce CRISPR/Cas9 system delivery vectors and finally demonstrate the potential of CRISPR/Cas9 engineering to enhance the effect of adoptive T cell therapy (ACT) and reduce adverse reactions.

Vehicle detection is one of the important applications of object detection in intelligent transportation systems. It aims to extract specific vehicle-type information from pictures or videos containing vehicles. To solve the problems of existing vehicle detection, such as the lack of vehicle-type recognition, low detection accuracy, and slow speed, a new vehicle detection model YOLOv2_Vehicle based on YOLOv2 is proposed in this paper. The k-means++ clustering algorithm was used to cluster the vehicle bounding boxes on the training dataset, and six anchor boxes with different sizes were selected. Considering that the different scales of the vehicles may influence the vehicle detection model, normalization was applied to improve the loss calculation method for length and width of bounding boxes. To improve the feature extraction ability of the network, the multi-layer feature fusion strategy was adopted, and the repeated convolution layers in high layers were removed. The experimental results on the Beijing Institute of Technology (BIT)-Vehicle validation dataset demonstrated that the mean Average Precision (mAP) could reach 94.78%. The proposed model also showed excellent generalization ability on the CompCars test dataset, where the “vehicle face” is quite different from the training dataset. With the comparison experiments, it was proven that the proposed method is effective for vehicle detection. In addition, with network visualization, the proposed model showed excellent feature extraction ability.

Objective Natural killer (NK) cells play a critical role in the innate antitumor immune response. Recently, NK cell dysfunction has been verified in various malignant tumors, including hepatocellular carcinoma (HCC). However, the molecular biological mechanisms of NK cell dysfunction in human HCC are still obscure. Methods The expression of circular ubiquitin-like with PHD and ring finger domain 1 RNA (circUHRF1) in HCC tissues, exosomes, and cell lines was detected by qRT-PCR. Exosomes were isolated from the culture medium of HCC cells and plasma of HCC patients using an ultracentrifugation method and the ExoQuick Exosome Precipitation Solution kit and then characterized by transmission electronic microscopy, NanoSight and western blotting. The role of circUHRF1 in NK cell dysfunction was assessed by ELISA. In vivo circRNA precipitation, RNA immunoprecipitation, and luciferase reporter assays were performed to explore the molecular mechanisms of circUHRF1 in NK cells. In a retrospective study, the clinical characteristics and prognostic significance of circUHRF1 were determined in HCC tissues. Results Here, we report that the expression of circUHRF1 is higher in human HCC tissues than in matched adjacent nontumor tissues. Increased levels of circUHRF1 indicate poor clinical prognosis and NK cell dysfunction in patients with HCC. In HCC patient plasma, circUHRF1 is predominantly secreted by HCC cells in an exosomal manner, and circUHRF1 inhibits NK cell-derived IFN-γ and TNF-α secretion. A high level of plasma exosomal circUHRF1 is associated with a decreased NK cell proportion and decreased NK cell tumor infiltration. Moreover, circUHRF1 inhibits NK cell function by upregulating the expression of TIM-3 via degradation of miR-449c-5p. Finally, we show that circUHRF1 may drive resistance to anti-PD1 immunotherapy in HCC patients. Conclusions Exosomal circUHRF1 is predominantly secreted by HCC cells and contributes to immunosuppression by inducing NK cell dysfunction in HCC. CircUHRF1 may drive resistance to anti-PD1 immunotherapy, providing a potential therapeutic strategy for patients with HCC.

Active-phase engineering is regularly utilized to tune the selectivity of metal nanoparticles (NPs) in heterogeneous catalysis. However, the lack of understanding of the active phase in electrocatalysis has hampered the development of efficient catalysts for CO 2 electroreduction. Herein, we report the systematic engineering of active phases of Pd NPs, which are exploited to select reaction pathways for CO 2 electroreduction. In situ X-ray absorption spectroscopy, in situ attenuated total reflection-infrared spectroscopy, and density functional theory calculations suggest that the formation of a hydrogen-adsorbed Pd surface on a mixture of the α- and β-phases of a palladium-hydride core (α+β PdH x @PdH x ) above −0.2 V (vs. a reversible hydrogen electrode) facilitates formate production via the HCOO* intermediate, whereas the formation of a metallic Pd surface on the β-phase Pd hydride core (β PdH x @Pd) below −0.5 V promotes CO production via the COOH* intermediate. The main product, which is either formate or CO, can be selectively produced with high Faradaic efficiencies (>90%) and mass activities in the potential window of 0.05 to −0.9 V with scalable application demonstration.

Lung cancer is one of the major causes of cancer-related deaths due to its aggressive nature and delayed detections at advanced stages. Early detection of lung cancer is very important for the survival of an individual, and is a significant challenging problem. Generally, chest radiographs (X-ray) and computed tomography (CT) scans are used initially for the diagnosis of the malignant nodules; however, the possible existence of benign nodules leads to erroneous decisions. At early stages, the benign and the malignant nodules show very close resemblance to each other. In this paper, a novel deep learning-based model with multiple strategies is proposed for the precise diagnosis of the malignant nodules. Due to the recent achievements of deep convolutional neural networks (CNN) in image analysis, we have used two deep three-dimensional (3D) customized mixed link network (CMixNet) architectures for lung nodule detection and classification, respectively. Nodule detections were performed through faster R-CNN on efficiently-learned features from CMixNet and U-Net like encoder–decoder architecture. Classification of the nodules was performed through a gradient boosting machine (GBM) on the learned features from the designed 3D CMixNet structure. To reduce false positives and misdiagnosis results due to different types of errors, the final decision was performed in connection with physiological symptoms and clinical biomarkers. With the advent of the internet of things (IoT) and electro-medical technology, wireless body area networks (WBANs) provide continuous monitoring of patients, which helps in diagnosis of chronic diseases—especially metastatic cancers. The deep learning model for nodules’ detection and classification, combined with clinical factors, helps in the reduction of misdiagnosis and false positive (FP) results in early-stage lung cancer diagnosis. The proposed system was evaluated on LIDC-IDRI datasets in the form of sensitivity (94%) and specificity (91%), and better results were obatined compared to the existing methods.

Electrochemical CO 2 reduction reaction (CO 2 RR) occurring at the electrode/electrolyte interface is sensitive to both the potential and concentration polarization. Compared to static electrolysis at a fixed potential, pulsed electrolysis with alternating anodic and cathodic potentials is an intriguing approach that not only reconstructs the surface structure, but also regulates the local pH and mass transport from the electrolyte side in the immediate vicinity of the cathode. Herein, via a combined online mass spectrometry investigation with sub-second temporal resolution and 1-dimensional diffusion profile simulations, we reveal that heightened surface CO 2 concentration promotes CO 2 RR over H 2 evolution for both polycrystalline Ag and Cu electrodes after anodic pulses. Moreover, mild oxidative pulses generate a roughened surface topology with under-coordinated Ag or Cu sites, delivering the best CO 2 -to-CO and CO 2 -to-C 2+ performance, respectively. Surface-enhanced infrared absorption spectroscopy elucidates the potential dependence of *CO and *OCHO species on Ag as well as the gradually improved *CO consumption rate over under-coordinated Cu after oxidative pulses, directly correlating apparent CO 2 RR selectivity with dynamic interfacial chemistry at the molecular level. How pulsed electrolysis impacts the electrochemical CO2 reduction reaction remains unclear. Here, authors present a molecular-level picture on the complex interactions between cathode surfaces, adsorbates, and local reaction environment to elucidate the promotional effect of pulsed electrolysis.

Statins play an important role in the treatment of diabetic nephropathy. Increasing attention has been given to the relationship between statins and insulin resistance, but many randomized controlled trials confirm that the therapeutic effects of statins on diabetic nephropathy are more beneficial than harmful. However, further confirmation of whether the beneficial effects of chronic statin administration on diabetic nephropathy outweigh the detrimental effects is urgently needed. Here, we find that long-term statin administration may increase insulin resistance, interfere with lipid metabolism, leads to inflammation and fibrosis, and ultimately fuel diabetic nephropathy progression in diabetic mice. Mechanistically, activation of insulin-regulated phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin signaling pathway leads to increased fatty acid synthesis. Furthermore, statins administration increases lipid uptake and inhibits fatty acid oxidation, leading to lipid deposition. Here we show that long-term statins administration exacerbates diabetic nephropathy via ectopic fat deposition in diabetic mice. Huang et al. investigated the effects of long-term statins administration in a mouse model for diabetes and found that it can worsen insulin resistance, renal inflammation and fibrosis. Statins increased renal lipid uptake and inhibited fatty acid oxidation, contributing to diabetic nephropathy.

Background The relationship between vitamin D status and mortality in patients with osteoarthritis (OA) is unknown. This study investigated the associations of serum 25-hydroxyvitamin D [25(OH)D] concentrations with all-cause and cause-specific mortality among American adults with OA. Methods This study included 2556 adults with OA from the National Health and Nutrition Examination Survey (2001–2014). Death outcomes were ascertained by linkage to National Death Index (NDI) records through 31 December 2015. Cox proportional hazards model and two-piecewise Cox proportional hazards model were used to elucidate the nonlinear relationship between serum 25(OH)D concentrations and mortality in OA patients, and stratified analyses were performed to identify patients with higher mortality risk. Results During 16,606 person-years of follow-up, 438 all-cause deaths occurred, including 74 cardiovascular disease (CVD)-related and 78 cancer deaths. After multivariable adjustment, lower serum 25(OH)D levels were significantly and nonlinearly associated with higher risks of all-cause and CVD mortality among participants with OA. Furthermore, we discovered L-shaped associations between serum 25(OH)D levels and all-cause and CVD mortality, with mortality plateauing at 54.40 nmol/L for all-cause mortality and 27.70 nmol/L for CVD mortality. Compared to participants with 25(OH)D levels below the inflection points, those with higher levels had a 2% lower risk for all-cause mortality (hazard ratio [HR] 0.98, 95% confidence interval [CI] 0.96–0.99) and 17% lower risk for CVD mortality (HR 0.83, 95% CI 0.72–0.95). Conclusions Nonlinear associations of serum 25(OH)D levels with all-cause and CVD mortality were observed in American patients with OA. The thresholds of 27.70 and 54.40 nmol/L for CVD and all-cause mortality, respectively, may represent intervention targets for lowering the risk of premature death and cardiovascular disease, but this needs to be confirmed in large clinical trials.

In this paper, a novel compact bandpass filter (BPF) with a wide out-of-band rejection is proposed. It can achieve broadband characteristics by combining hollow bowtie-type spoof surface plasmon polaritons (SSPPs) with complementary H-type defected grounded structures (DGSs) through aperture coupling. Compared with the conventional SSPP unit cells, the hollow bowtie-type structure exhibits much better slow-wave characteristics. The introduced slant antenna type port-coupling can produce a very strong high-performance rejection outside the high frequency stopband. Simulation results show that the SSPPs-DGS-based BPF has an excellent band pass characteristics in a broadband range with − 3dB fractional bandwidth of 43.5% at center frequency f 0 of 2.04 GHz. The return loss in the passband is better than − 12 dB. Furthermore, because of the multiple transmission zeros generated in upper-stop-band, the designed BPF has an extremely strong out-of-band rejection of -40dB from 1.5 f 0 to 4 f 0 ( f 0 is the center frequency). The designed SSPPs-DGS-based BPF is fabricated by conventional printed circuit board (PCB) technology with a compact size of only 0.68λ g *0.34λ g (λ g is the wavelength at the center frequency). The measured results have a good agreement with the simulation ones, which verifies the rationality and feasibility of the design. The miniaturized wideband BPF with broad out-of-band rejection may make it has good application prospect in the new generation microwave communication field.