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The genetic modification of microorganisms is conducive to the selection of high-yield producers of high-value-added chemicals, but a lack of genetic tools hinders the industrialization of most wild species. Therefore, it is crucial to develop host-independent gene editing tools that can be used for genetic manipulation-deprived strains. The Tn7-like transposon from Scytonema hofmanni has been shown to mediate homologous recombination-independent genomic integration after heterologous expression in Escherichia coli, but the integration efficiency of heterologous sequences larger than 5 kb remains suboptimal. Here, we constructed a versatile Cas12k-based genetic engineering toolkit (C12KGET) that can achieve genomic integration of fragments up to 10 kb in size with up to 100% efficiency in challenging strains. Using C12KGET, we achieved the first example of highly efficient genome editing in Sinorhizobium meliloti, which successfully solved the problem that industrial strains are difficult to genetically modify, and increased vitamin B12 production by 25%. In addition, Cas12k can be directly used for transcriptional regulation of genes with up to 92% efficiency due to its naturally inactivated nuclease domain. The C12KGET established in this study is a versatile and efficient marker-free tool for gene integration as well as transcriptional regulation that can be used for challenging strains with underdeveloped genetic toolkits.

In this study two colorimetric and fluorometric sensors were prepared for lead ions based on conjugated polydiacetylenes.

optical breast spectroscopy (OBS) can predict breast density and can be used for risk assessment of breast cancer (BC). We have used this method to study the classification and prediction of breast hyperplasia. In this paper, the collected spectral data of clinical breast hyperplasia and normal human breast were classified and predicted by using machine learning Bayesian model, decision tree and k-nearest neighbor model (KNN). The research shows that the accuracy of machine learning algorithm for classification and diagnosis of breast hyperplasia can reach 93%. The combination of machine learning algorithm and practical medical diagnosis technology is of great significance, and it can be further developed to improve the efficiency and accuracy of clinical diagnosis.

Breast cancer has seriously threatened the health of women in China, however, the conventional detection method has its limitations, so it is of great significance to explore a rapid, noninvasive and sensitive detection technology. In recent years, spectroscopy has been explored as a tool for not using molybdenum targets to determine breast density, and then predict the occurrence of the breast cancer. Based on this idea, this study attempts to do preliminary processing and analysis on the actual spectral data collected by experiments, building models and comparing three classification methods which based on machine learning, which are logical regression, support vector machine(SVM) and random forest algorithm. The accuracy achieved 90.48%(logical regression), 85.71% (SVM) and 95.24%(random forest) in the recognition of breast hyperplasia. In addition, the prediction method of combining spectral data with breast cancer risk factor data was explored, and the accuracy of SVM method was 77.8%. In this study, the random forest algorithm is characterized as the best in the analysis with the participation of only mammary gland spectrum, and in the analysis with the participation of spectral data and risk data SVM shows the better performance than random forest although there is still no ideal effect and needs more data support. This study provides a new idea for the spectral detection of breast cancer in China and provides a possibility for the development of a new breast cancer detection method.

Background: Calcified lumbar disc herniation (CLDH) is considered to be a special type of lumbar disc herniation (LDH). Percutaneous endoscopic interlaminar discectomy (PEID), with safety and efficacy, has been proved to be a minimally invasive surgery for LDH. However, there are few studies on PEID in the treatment of CLDH at L5-S1 level. This research aimed to analyze the clinical efficacy of PEID for L5-S1 CLDH.Methods: From August 2016 to April 2020, we retrospectively analyzed 28 consecutive patients (17 males; 11 females) with L5-S1 CLDH treated with PEID at our institution. All the patients were followed up for greater than 1 year postoperatively. The demographic characteristics, surgical results and clinical outcomes estimated by the visual analog scale (VAS) for leg pain, Oswestry disability index (ODI) and modified MacNab criteria were collected.Results: All patients were successfully performed by PEID. The mean operative time and intraoperative blood loss were 65.36 ± 5.26 minutes and 13.21 ± 4.35 ml, respectively. The VAS for leg pain and ODI scores improved remarkably from 7.54 ± 0.96 to 1.50 ± 0.51 (P < 0.05) and from 69.29 ± 9.91 to 17.43 ± 3.69 (P < 0.05) a year after operation, respectively. According to the modified MacNab criteria of the last follow-up, the excellent and good rates are 92.86%. Two of the patients had complications, one had nerve root injury and the other had postoperative dysesthesia.Conclusions: PEID achieved good clinical outcomes in the treatment of L5-S1 CLDH. And PEID was a safe and effective minimally invasive surgery for L5-S1 CLDH.

Background: Percutaneous endoscopic lumbar discectomy (PELD) is a relatively safe and effective minimally invasive surgery in the treatment of calcified lumbar disc herniation (CLDH). However, studies on percutaneous endoscopic interlaminar discectomy (PEID) and percutaneous endoscopic transforaminal discectomy (PETD) for CLDH have rarely been reported. This research aimed to compare the clinical efficacy of PEID and PETD for L5-S1 CLDH.Methods: We retrospectively analyzed 42 consecutive patients with L5-S1 CLDH treated with PELD at our institution from August 2016 to December 2019. Patients were divided into PEID group (n = 24) and PETD (n = 18) group according to the surgical methods. The demographic characteristics and surgical results of the two groups were compared. Clinical outcomes were estimated by the visual analog scale (VAS) for leg pain, Oswestry disability index (ODI) and modified MacNab criteria.Results: All patients were successfully operated on by PEID or PETD. No significant differences in the demographic characteristics, intraoperative blood loss, postoperative hospital stay and complication rate were noted between the PEID and PETD groups (P > 0.05). The excellent and good rates in the PEID group were similar to those in the PETD group (91.67% vs 88.89%, P > 0.05), whereas the PEID group exhibited superior results for operative time (m) (64.58 ± 5.88 vs 85.56 ± 9.06, P < 0.05) and fluoroscopy times (n) (2.96 ± 0.96 vs 13.33 ± 2.64, P < 0.05) compared with the PETD group.Conclusions: PEID had achieved good clinical efficacy as PETD for L5-S1 CLDH. Compared with PETD, PEID had the advantages of shorter operative time and a reduced number of fluoroscopy times in the treatment of CLDH.

With the development of deep learning, skeleton-based action recognition has achieved great progress in recent years. However, most of the current works focus on extracting more informative spatial representations of the human body, but haven't made full use of the temporal dependencies already contained in the sequence of human action. To this end, we propose a novel transformer-based model called Motion-Transformer to sufficiently capture the temporal dependencies via self-supervised pre-training on the sequence of human action. Besides, we propose to predict the motion flow of human skeletons for better learning the temporal dependencies in sequence. The pre-trained model is then fine-tuned on the task of action recognition. Experimental results on the large scale NTU RGB+D dataset shows our model is effective in modeling temporal relation, and the flow prediction pre-training is beneficial to expose the inherent dependencies in time dimensional. With this pre-training and fine-tuning paradigm, our final model outperforms previous state-of-the-art methods.

BACKGROUND: Piloting an aircraft is a complex cognitive task. Human error represents a major contributing factor in aviation accidents. Emotion plays an important role in aviation safety. We performed a functional magnetic resonance imaging (fMRI) study to explore whether pilots and nonpilots may differ in the neural mechanisms responsible for the processing of conflict emotional information.METHODS: A total of 27 civil aviation pilots and 24 nonpilot controls performed the emotional Stroop task, in which participants were required to identify the facial expressions of the stimuli while ignoring the congruent or incongruent emotional words superimposed on the faces. Neural responses to the stimuli were compared between pilots and controls. Also, a psychophysiological interaction (PPI) analysis was performed to explore whether there were differences in effective connectivity between pilots and nonpilots.RESULTS: Behavioral data showed that pilots (21.23 ms) and nonpilots (26.78 ms) had equivalent congruency effects. Nevertheless, their neural activation patterns differed. Compared with pilots, nonpilots exhibited neural activity in the right supramarginal gyrus when processing incongruent stimuli, and more regions were activated in the process of conflict monitoring. The PPI analysis showed greater activity between the right supramarginal gyrus and the right lingual gyrus when nonpilots confronted incongruent vs. congruent stimuli. However, this effective connectivity was not found in pilots.CONCLUSION: These results suggest different mechanisms underlying emotional conflict control between pilots and the general population.Jiang H, Xu K, Chen X, Wang Q, Yang Y, Fu C, Guo X, Chen X, Yang J. The neural underpinnings of emotional conflict control in pilots. Aerosp Med Hum Perform. 2020; 91(10):798805.

Background Airlines occupy an increasingly important place in the economy of many countries. Because air disasters may cause substantial losses, comprehensive surveys of the psychophysiological mechanism of flying are needed; however, relatively few studies have focused on pilots. The default mode network (DMN) is an important intrinsic connectivity network involved in a range of functions related to flying. This study aimed to examine functional properties of the DMN in pilots. Method Resting-state functional magnetic resonance imaging data from 26 pilots and 24 controls were collected. Independent component analysis, a data-driven approach, was combined with functional connectivity analysis to investigate functional properties of the DMN in pilots. Results The pilot group exhibited increased functional integration in the precuneus/posterior cingulate cortex (PCC) and left middle occipital gyrus. Subsequent functional connectivity analysis identified enhanced functional connection between the precuneus/PCC and medial superior frontal gyrus. Conclusion The pilot group exhibited increased functional connections within the DMN. These findings highlight the importance of the DMN in the neurophysiological mechanism of flying.

Impactful regioselectivity control is crucial for cost-effective chemical synthesis. By using cheap and abundant iron(iii) salts, the hydroxycarbonylations of both aromatic and aliphatic alkenes were significantly enhanced in both reactivity and selectivity (iso/n or n/iso up to >99 : 1). Moreover, Pd-catalyzed carbonylation selectivity can be switched from branched to linear by using different Fe(iii) salts. In addition, similar results were obtained for the carbonylation of secondary alcohols.

The titanate, is a material of interest for various energy applications, including photovoltaics, catalysts, and high-rate energy storage devices. Herein, its related materials, CuO/CaTi4O9 [CCTO] thin films, were successfully fabricated on SrTiO3 (100) substrates by RF magnetron sputtering assisted with subsequent oxygen annealing. This obtained CCTO thin films were then systemically studied by X-ray powder diffraction (XRD), atomic force microscopy (AFM), scan electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS) and high-resolution transmission electron microscopy (HRTEM). It was found that CuO and CaTi4O9 (001) particles were closely accumulated together on the surface of the substrate in the annealing process after comparing with that of the as-prepared thin film, which was verified by SEM and AFM results. Furthermore, we investigated the third-order nonlinear optical (NLO) properties of the as-prepared and annealed CCTO thin film by means of the Z-scan technique using 650 nm femtosecond laser pulse. Post-deposition oxygen annealing was found to modify the morphological characteristics of the films, resulting in enhancing their NLO properties. The observation of NLO performance of annealed CCTO thin film indicates that RF magnetron sputtering is a feasible method for the fabrication of optical thin films, which can be expanded to fabricate other NLO materials from the corresponding dispersions. Naturally, we concluded that the CCTO thin film occupy a better NLO property, and thus enlarge its application in nonlinear optics.

In this work, poly-crystalline CaCuO 2 /CaCu 2 O 3 thin films were deposited on quartz substrates using radio frequency (RF) magnetron sputtering and subsequent annealing. The deposition process was performed at room temperature under an oxygen partial pressure of 4 × 10 −2 Pa at a speed of 2 A/s. The crystalline structure, distribution of the particles and size of the elements of the as-prepared and CaCuO 2 /CaCu 2 O 3 thin films were individually acquired and discussed in detail. Subsequent annealing was found to modify the composition, structure and morphological characteristics of the as-prepared thin film, resulting in changes of the film quality and, thereby, improving the nonlinear optical (NLO) response of the film. The sign and magnitude of third-order nonlinear susceptibility χ (3) of the as-prepared and CaCuO 2 /CaCu 2 O 3 thin films were determined using the top-hat Z-scan technique performed at 532 nm with a laser duration of 190 fs. The results show that annealed CaCuO 2 /CaCu 2 O 3 thin film exhibits a fast NLO response with a third-order nonlinear susceptibility χ (3) of 1.1 × 10 −12 esu, which is higher than that of the as-prepared thin film. The results indicate that CaCuO 2 /CaCu 2 O 3 thin films have potential applications in nonlinear optics.

Recent studies have shown remarkable advances in 3D human pose estimation from monocular images, with the help of large-scale in-door 3D datasets and sophisticated network architectures. However, the generalizability to different environments remains an elusive goal. In this work, we propose a geometry-aware 3D representation for the human pose to address this limitation by using multiple views in a simple auto-encoder model at the training stage and only 2D keypoint information as supervision. A view synthesis framework is proposed to learn the shared 3D representation between viewpoints with synthe- sizing the human pose from one viewpoint to the other one. Instead of performing a direct transfer in the raw image- level, we propose a skeleton-based encoder-decoder mechanism to distil only pose-related representation in the latent space. A learning-based representation consistency constraint is further introduced to facilitate the robustness of latent 3D representation. Since the learnt representation encodes 3D geometry information, mapping it to 3D pose will be much easier than conventional frameworks that use an image or 2D coordinates as the input of 3D pose estimator. We demonstrate our approach on the task of 3D human pose estimation. Comprehensive experiments on three popular benchmarks show that our model can significantly improve the performance of state-of-the-art methods with simply injecting the representation as a robust 3D prior.

A two-step synthetic method was used to obtain a Pb glass film containing micro-crystalline Ca2CuO3 particles on a K9 glass substrate. The Ca2CuO3 micro-crystals were prepared for the first time by a high-temperature solid state method. The synthesized films were obtained on K9 glass substrates by screen-printing and co-sintering techniques, using Pb glass powder and Ca2CuO3 micro-crystals as reagents under different sintering temperatures. Secondly, micro-crystalline Ca2CuO3 Pb-glass films with different thickness were obtained by mechanical polishing for various times. The analysis of the surface structure, purity of the Ca2CuO3 phase and confirmation of the Pb-glass components in the given composites were provided by X-ray powder diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS) and X-ray photoelectron spectroscopy (XPS). The interactions between phonons and atoms of the micro-crystalline Ca2CuO3 particles embedded in the Pb-glass matrix were characterized by means of Raman scattering spectra. Moreover, the nonlinear optical property of the film was detected by a top-hat Z-scan technique with a laser duration of 190 ns at 532 nm. The results showed that the film polished for 120 min exhibited a large third-order non-linear susceptibility χ(3) of 6.1×10−12 esu, suggesting its potential application in all-optical switches and integrated electron devices.

Civil aviation is a distinctive career. Pilots need to monitor the entire system in real time. However, the psychophysiological mechanism of flying is largely unknown. The human brain is a large-scale interconnected organization, and many stable intrinsic large-scale brain networks have been identified. Among them are three core neurocognitive networks: default mode network (DMN), central executive network (CEN), and salience network (SN). These three networks play a critical role in human cognition. This study aims to examine the dynamic properties of the three large-scale brain networks in civil aviation pilots. We collected resting-state functional magnetic resonance imaging data from pilots. Independent component analysis, which is a data-driven approach, was combined with sliding window dynamic functional connectivity analysis to detect the dynamic properties of large-scale brain networks. Our results revealed that pilots exhibit an increased interaction of the CEN with the DMN and the SN along with a decreased interaction within the CEN. In addition, the temporal properties of functional dynamics (number of transitions) increased in pilots compared to healthy controls. In general, pilots exhibited increased between-network functional connectivity, decreased within-network functional connectivity, and a higher number of transitions. These findings suggest that pilots might have better functional dynamics and cognitive flexibility.

Biothiols, such as glutathione (GSH) and cysteine (Cys), play important roles in many physiological processes, and variations in their levels are related to different diseases. Many fluorescence probes have been developed to understand the function of biothiols, but only few of such probes can detect both Cys and GSH. Herein, a new strategy for specific colorimetric and fluorescent detection of Cys and GSH by different cascade reactions was developed. By utilizing this strategy, we designed and synthesized two fluorescent probes, namely, CR1 and CR2, for detection of Cys and GSH under physiological conditions. CR1 contains a stronger electron-withdrawing substituent group and provides high selectivity and sensitivity for Cys and GSH. This probe is based on the mechanism of Cys-induced native-chemical-ligation-cyclization and GSH-induced transthioesterification–cyclization cascade reactions, with detection limits of 0.029 and 0.371 μM, respectively. CR1 can be successfully applied for imaging Cys and GSH in living cells with low cell toxicity.

In this paper, we propose a two-stage depth ranking based method (DRPose3D) to tackle the problem of 3D human pose estimation. Instead of accurate 3D positions, the depth ranking can be identified by human intuitively and learned using the deep neural network more easily by solving classification problems. Moreover, depth ranking contains rich 3D information. It prevents the 2D-to-3D pose regression in two-stage methods from being ill-posed. In our method, firstly, we design a Pairwise Ranking Convolutional Neural Network (PRCNN) to extract depth rankings of human joints from images. Secondly, a coarse-to-fine 3D Pose Network(DPNet) is proposed to estimate 3D poses from both depth rankings and 2D human joint locations. Additionally, to improve the generality of our model, we introduce a statistical method to augment depth rankings. Our approach outperforms the state-of-the-art methods in the Human3.6M benchmark for all three testing protocols, indicating that depth ranking is an essential geometric feature which can be learned to improve the 3D pose estimation.

In the inflamed microenvironment of peri-implantitis, limited osteogenesis on the implant surface impedes well-established reosseointegration using current clinical therapies. MicroRNAs (miRNAs) function as potent molecular managers that may simultaneously regulate multiple endogenous processes such as inflammation and osteogenesis. The delivery of miRNAs may provide a way to effectively treat some diseases. In this study, we showed that miR-27a was differentially downregulated in samples from a canine peri-implantitis model. We found that overexpressing miR-27a positively regulated osteogenesis-angiogenesis coupling by ameliorating the TNF-α inhibition of bone formation in vitro. Mechanistically, we identified Dickkopf2 (DKK2) and secreted frizzled related protein 1 (SFRP1) as two essential direct miR-27a targets that were osteogenic and angiogenic. Furthermore, we constructed a miR-27a-enhanced delivery system to repair the bone defect around implants in a canine peri-implantitis model. The results demonstrated that the miR-27a-treated group could optimize new bone formation and reosseointegration in vivo. Our assay provides evidence that this strategy exerts therapeutic effects on peri-implantitis, suggesting that it represents a feasible method to maintain the stability and masticatory function of dental implants. © 2018 American Society for Bone and Mineral Research.

Peri-implantitis, which is characterized by dense inflammatory infiltrates and increased osteoclast activity, can lead to alveolar bone destruction and implantation failure. miRNAs participate in the regulation of various inflammatory diseases, such as periodontitis and osteoporosis. Therefore, the present study aimed to investigate the differential expression of miRNAs in canine peri-implantitis and to explore the functions of their target genes. An miRNA sequence analysis was used to identify differentially expressed miRNAs in peri-implantitis. Under the criteria of a fold-change >1.5 and P

Four new species of the subgenus Stegana (Steganina) are found from southern China: S. (S.) clavispinuta sp. nov., S. (S.) cyclophylla sp. nov., S. (S.) euryphylla sp. nov. and S. (S.) lepismina spp. nov., they can not to be placed under four species groups established. A key to the species of uncertain affinity among species group from China is provided.

miRNAs play a number of roles in bone, including mediating the pathological effects of inflammation. Here, we found that miR-33a-5p expression was significantly increased after TNF-α treatment during BMP-2-induced osteogenic differentiation of hBMSCs. Luciferase reporter assays and western blotting demonstrated that special AT-rich sequence-binding protein 2 (SATB2) is a target of miR-33a-5p. Moreover, we show that BMP-2 induces SATB2 expression by interacting with SATB2 directly via the BMP-2-RUNX2 pathway. However, TNF-α first decreases SATB2 expression by inhibiting miR-33a-5p degradation. We thus conclude that miR-33a-5p plays a central role in this complex regulatory network. These findings will help to understand the regulatory role of miR-33a-5p in the inflammatory process.

The disproportion in natural resource and power load results in lots of 500kV transmission lines in southern China. These transmission lines are seriously influenced by lightning because of the complex terrain and frequent lightning activities in southern China. In this paper, lightning performance of six 500kV transmission lines in southern China is analyzed with the help of Lightning Protection Analyzing System for Transmission Line (LPTL). The simulation is based on the method recommended by IEEE standard, considering the geographical environment and structure of each tower. The results show the existing difference in lightning performance of each tower. Then comparative analysis is made between the simulation results and operation experience on flashover rate of entire line. It indicates that the IEEE method considering practical situation is available to the lightning performance assessment of 500KV transmission lines in southern China.

A new tool has been developed for the evaluation of the lightning performance of overhead transmission lines. The tool can take into account actual ground flash density distribution along line corridor, cumulative probability function of the lightning current, geometric parameters, insulator string configuration and the topography for each tower of the entire line, etc. Moreover, the tool incorporates several lightning attachment models and a method of ATP-based automated simulation for lightning surge analysis. An application to a typical 500 kV double circuit line of the Chinese transmission system shows that it is convenient for estimating the lightning performance of a total line and studying the effects of different models and criteria on the lightning performance of the line.