FOXD2-AS1 promotes malignant cell behavior in oral squamous cell carcinoma via the miR-378 g/CRABP2 axis.

BACKGROUND: Oral squamous cell cancer (OSCC) is a prevalent malignancy in oral cavity, accounting for nearly 90% of oral malignancies. It ranks sixth among the most common types of cancer worldwide and is responsible for approximately 145,000 deaths each year. It is widely accepted that noncoding RNAs participate cancer development in competitive regulatory interaction, knowing as competing endogenous RNA (ceRNA) network, whereby long non-coding RNA (lncRNA) function as decoys of microRNAs to regulate gene expression. LncRNA FOXD2-AS1 was reported to exert an oncogenic role in OSCC. Nevertheless, the ceRNA network mediated by FOXD2-AS1 was not investigated yet. This study aimed to explore the effect of FOXD2-AS1 on OSCC cell process and the underlying ceRNA mechanism. METHODS: FOXD2-AS1 expression in OSCC cells were determined via reverse transcription and quantitative polymerase chain reaction. Short hairpin RNA targeting FOXD2-AS1 was transfected into OSCC cells to silence FOXD2-AS1 expression. Then, loss-of-function experiments (n = 3 each assay) were performed to measure cell proliferation, apoptosis, migration, and invasion using colony formation, TdT-mediated dUTP Nick-End Labeling, wound healing and Transwell assays, respectively. RNA binding relation was verified by RNA immunoprecipitation and luciferase reporter assays. Rescue experiments were designed to validate whether FOXD2-AS1 affects cell behavior via the gene cellular retinoic acid binding protein 2 (CRABP2). Statistics were processed by GraphPad Prism 6.0 Software and SPSS software. RESULTS: FOXD2-AS1 was significantly upregulated in Cal27 and SCC9 cells (6.8 and 6.4 folds). In response to FOXD2-AS1 knockout, OSCC cell proliferation, migration and invasion were suppressed (approximately 50% decrease) while OSCC cell apoptosis was enhanced (more than two-fold increase). FOXD2-AS1 interacted with miR-378 g to alter CRABP2 expression. CRABP2 upregulation partly rescued (*p < 0.05, **p < 0.01, ***p < 0.001) the inhibitory impact of FOXD2-AS1 depletion on malignant characteristics of OSCC cells. CONCLUSION: FOXD2-AS1 enhances OSCC malignant cell behaviors by interacting with miR-378 g to regulate CRABP2 expression.

A Federated Learning Multi-Task Scheduling Mechanism Based on Trusted Computing Sandbox.

At present, some studies have combined federated learning with blockchain, so that participants can conduct federated learning tasks under decentralized conditions, sharing and aggregating model parameters. However, these schemes do not take into account the trusted supervision of federated learning and the case of malicious node attacks. This paper introduces the concept of a trusted computing sandbox to solve this problem. A federated learning multi-task scheduling mechanism based on a trusted computing sandbox is designed and a decentralized trusted computing sandbox composed of computing resources provided by each participant is constructed as a state channel. The training process of the model is carried out in the channel and the malicious behavior is supervised by the smart contract, ensuring the data privacy of the participant node and the reliability of the calculation during the training process. In addition, considering the resource heterogeneity of participant nodes, the deep reinforcement learning method was used in this paper to solve the resource scheduling optimization problem in the process of constructing the state channel. The proposed algorithm aims to minimize the completion time of the system and improve the efficiency of the system while meeting the requirements of tasks on service quality as much as possible. Experimental results show that the proposed algorithm has better performance than the traditional heuristic algorithm and meta-heuristic algorithm.

Distributed Fault Detection Based on Credibility and Cooperation for WSNs in Smart Grids.

Due to the increasingly important role in monitoring and data collection that sensors play, accurate and timely fault detection is a key issue for wireless sensor networks (WSNs) in smart grids. This paper presents a novel distributed fault detection mechanism for WSNs based on credibility and cooperation. Firstly, a reasonable credibility model of a sensor is established to identify any suspicious status of the sensor according to its own temporal data correlation. Based on the credibility model, the suspicious sensor is then chosen to launch fault diagnosis requests. Secondly, the sending time of fault diagnosis request is discussed to avoid the transmission overhead brought about by unnecessary diagnosis requests and improve the efficiency of fault detection based on neighbor cooperation. The diagnosis reply of a neighbor sensor is analyzed according to its own status. Finally, to further improve the accuracy of fault detection, the diagnosis results of neighbors are divided into several classifications to judge the fault status of the sensors which launch the fault diagnosis requests. Simulation results show that this novel mechanism can achieve high fault detection ratio with a small number of fault diagnoses and low data congestion probability.

A Fault Tolerance Mechanism for On-Road Sensor Networks.

On-Road Sensor Networks (ORSNs) play an important role in capturing traffic flow data for predicting short-term traffic patterns, driving assistance and self-driving vehicles. However, this kind of network is prone to large-scale communication failure if a few sensors physically fail. In this paper, to ensure that the network works normally, an effective fault-tolerance mechanism for ORSNs which mainly consists of backup on-road sensor deployment, redundant cluster head deployment and an adaptive failure detection and recovery method is proposed. Firstly, based on the N - x principle and the sensors' failure rate, this paper formulates the backup sensor deployment problem in the form of a two-objective optimization, which explains the trade-off between the cost and fault resumption. In consideration of improving the network resilience further, this paper introduces a redundant cluster head deployment model according to the coverage constraint. Then a common solving method combining integer-continuing and sequential quadratic programming is explored to determine the optimal location of these two deployment problems. Moreover, an Adaptive Detection and Resume (ADR) protocol is deigned to recover the system communication through route and cluster adjustment if there is a backup on-road sensor mismatch. The final experiments show that our proposed mechanism can achieve an average 90% recovery rate and reduce the average number of failed sensors at most by 35.7%.

Identification of DNA-binding proteins by Kernel Sparse Representation via L2,1-matrix norm.

An understanding of DNA-binding proteins is helpful in exploring the role that proteins play in cell biology. Furthermore, the prediction of DNA-binding proteins is essential for the chemical modification and structural composition of DNA, and is of great importance in protein functional analysis and drug design. In recent years, DNA-binding protein prediction has typically used machine learning-based methods. The prediction accuracy of various classifiers has improved considerably, but researchers continue to spend time and effort on improving prediction performance. In this paper, we combine protein sequence evolutionary information with a classification method based on kernel sparse representation for the prediction of DNA-binding proteins, and based on the field of machine learning, a model for the identification of DNA-binding proteins by sequence information was finally proposed. Based on the confirmation of the final experimental results, we achieved good prediction accuracy on both the PDB1075 and PDB186 datasets. Our training result for cross-validation on PDB1075 was 81.37%, and our independent test result on PDB186 was 83.9%, both of which outperformed the other methods to some extent. Therefore, the proposed method in this paper is proven to be effective and feasible for predicting DNA-binding proteins.

MiR-223-3p alleviates trigeminal neuropathic pain in the male mouse by targeting MKNK2 and MAPK/ERK signaling.

BACKGROUND: Trigeminal neuralgia (TN) is a neuropathic pain that occurs in branches of the trigeminal nerve. MicroRNAs (miRNAs) have been considered key mediators of neuropathic pain. This study was aimed to elucidate the pathophysiological function and mechanisms of miR-223-3p in mouse models of TN. METHODS: Infraorbital nerve chronic constriction injury (CCI-ION) was applied in male C57BL/6J mice to establish mouse models of TN. Pain responses were assessed utilizing Von Frey method. The expression of miR-223-3p, MKNK2, and MAPK/ERK pathway protein in trigeminal ganglions (TGs) of CCI-ION mice was measured using RT-qPCR and Western blotting. The concentrations of inflammatory cytokines were evaluated using Western blotting. The relationship between miR-223-3p and MKNK2 was tested by a luciferase reporter assay. RESULTS: We found that miR-223-3p was downregulated, while MKNK2 was upregulated in TGs of CCI-ION mice. MiR-223-3p overexpression by an intracerebroventricular injection of Lv-miR-223-3p attenuated trigeminal neuropathic pain in CCI-ION mice, as well as reduced the protein levels of pro-inflammatory cytokines in TGs of CCI-ION mice. MKNK2 was verified to be targeted by miR-223-3p. Additionally, miR-223-3p overexpression decreased the phosphorylation levels of ERK1/2, JNK, and p38 protein in TGs of CCI-ION mice to inhibit MAPK/ERK signaling. CONCLUSIONS: Overall, miR-223-3p attenuates the development of TN by targeting MKNK2 to suppress MAPK/ERK signaling.

Three-Dimensional Printing-Assisted Masquelet Technique in the Treatment of Calcaneal Defects.

OBJECTIVE: The aim of the present study was to summarize the clinical efficacy of three-dimensional (3D) printing technology combined with the Masquelet technique in the treatment of calcaneal defects. METHODS: From January 2018 to April 2019, 3D printing combined with induced masquelet technology was used to treat four patients with calcaneal defects, including two men and two women. The patients were aged 22-52 years old, with an average age of 36 years. There were two cases of traffic accident injuries, there was one case of a fall from height, and there was one case of crush injury. CT scans were used to reconstruct the bilateral calcaneus, mirror technology was used to construct the bone defect area, and Materialise 3-matic software was used to design the calcaneus shaper mold and 3D print the mold. During the operation, the mold was used to shape the bone cement and fill the bone defect. In the second stage, the bone cement was removed and autologous bone was implanted to repair the bone defect. All patients were followed up to observe the effect. RESULTS: All four patients were followed up for 14 months (range, 10-18 months). There were three cases of infectious bone defects: two cases of Escherichia coli and one case of Pseudomonas aeruginosa. The 3D printed mold was used to shape the bone cement. During the operation, it was found to have a high degree of matching with the defect area of calcaneus. There is no need to adjust it again, and the wound healed well after the first stage. In the second stage of surgery, it was found that the induced membrane formed was complete and of appropriate size; the bone cement was easily removed during the operation. The fracture healing time was 3-6 months, with an average of 4 months. At the last follow up, there was no pain and the patients walked with full weight bearing. The Maryland score was 94 points (range, 88-98 points); three cases were excellent and one case was good. The AOFAS score ranged from 86 to 98, with an average of 92.8 points; three cases were excellent and one case was good. CONCLUSION: Three-dimensional printing technology combined with induced membrane technology is an effective approach for treating calcaneal bone defects.

[Treatment of the fifth metacarpal neck fracture with elastic intramedullary nail under the guidance of high frequency ultrasound].

OBJECTIVE: To analyze the feasibility and effectiveness of elastic intramedullary nail fixation for the fifth metacarpal neck fracture under the guidance of high frequency ultrasound. METHODS: The clinical data of 30 patients with the fifth metacarpal neck fractures who were treated with elastic intramedullary nails fixation under the guidance of high frequency ultrasound and met the selection criteria between May 2013 and September 2017 were retrospectively analysed. There were 24 males and 6 females, the age ranged from 18 to 58 years, with an average of 31.4 years. The head-shaft angle of the fifth metacarpal was (55.6±11.3)°. The time from injury to operation was 12 hours to 8 days, with an average of 2.4 days. The operation time, number of intraoperative fluoroscopy, fracture reduction, complications, and fracture healing time were recorded. The head-shaft angle of the fifth metacarpal on the affected side after fracture healing were measured and compared with the healthy side. At last follow-up, the active range of motion of the fifth metacarpophalangeal joint of both sides were measured, and the function was evaluated by using the total active movement (TAM) evaluation standard of the Hand Surgery Association of Chinese Medical Association. RESULTS: The operation time was 22-40 minutes, with an average of 32.4 minutes; the intraoperative fluoroscopy was performed once; ultrasound images and X-ray fluoroscopy showed that the fracture was well reduced and no adjustment was required. The incisions healed well after operation, without tendon adhesion or local numbness. All 30 patients were followed up 8-16 months, with an average of 11.7 months. The fracture healing time was 4-8 weeks, with an average of 5.6 weeks. The head-shaft angle of the fifth metacarpal was (13.2±1.4)°, which was significantly improved when compared with preoperative value ( t=-20.02, P=0.00); and there was no significant difference ( t=1.94, P=0.06) when compared with the healthy side [(12.6±1.0)°]. At last follow-up, the active range of motion of the fifth metacarpophalangeal joint on the affected side was (89.4±2.4)°, showing no significant difference ( t=-1.58, P=0.13) when compared with the healthy side [(90.3±2.0)°]. According to the TAM evaluation standard of the Hand Surgery Association of Chinese Medical Association, all patients were considered to be excellent. CONCLUSION: The effectiveness of elastic intramedullary nail fixation for the fifth metacarpal neck fracture under the guidance of high frequency ultrasound is definite. It can dynamically observe the fracture reduction from different angles, reduce ionizing radiation and postoperative complications.

Automatic Lung Segmentation Based on Texture and Deep Features of HRCT Images with Interstitial Lung Disease.

Lung segmentation in high-resolution computed tomography (HRCT) images is necessary before the computer-aided diagnosis (CAD) of interstitial lung disease (ILD). Traditional methods are less intelligent and have lower accuracy of segmentation. This paper develops a novel automatic segmentation model using radiomics with a combination of hand-crafted features and deep features. The study uses ILD Database-MedGIFT from 128 patients with 108 annotated image series and selects 1946 regions of interest (ROI) of lung tissue patterns for training and testing. First, images are denoised by Wiener filter. Then, segmentation is performed by fusion of features that are extracted from the gray-level co-occurrence matrix (GLCM) which is a classic texture analysis method and U-Net which is a standard convolutional neural network (CNN). The final experiment result for segmentation in terms of dice similarity coefficient (DSC) is 89.42%, which is comparable to the state-of-the-art methods. The training performance shows the effectiveness for a combination of texture and deep radiomics features in lung segmentation.

[Manual reduction and traction fixation for the treatment of metacarpal neck fractures under ultrasound-guided].

OBJECTIVE: To study clinical efficacy of manual reduction and traction fixation for the treatment of metacarpal neck fracture under ultrasound-guided. METHODS: From April 2013 to August 2016, 30 patients with metacarpal neck fractures were treated with manual reduction and traction fixation under ultrasound-guided, including 26 males and 4 females aged from 14 to 56 years old with an average of (25.6±1.6) years old, the courses of diseases ranged from 7 h to 5 d with an average of (2.7±0.6) d. Twenty patients were the fifth metacarpal neck fracture, 7 patients were the 4th and 5th metacarpal neck fractures, 3 patients were the second metacarpal neck fracture. Fracture healing, angle of bilateral head shaft angle and active range of metacarpophalangeal joints was measured, and DASH score was applied to evaluate function. RESULTS: Twenty-seven patients were followed up from 6 to 11 months with an average of(7.2±0.8) months. Fracture were healed from 5 to 8 weeks with an average of (5.6±0.4) weeks. The affected shaft angle was (15.1±1.8)°, and health head shaft angle was (13.5±2.8)°, while there was no significant difference (t=1.54, P>0.05). The affected range motion of metacarpophalangealjoint was(86.3±2.6)°, health active range motion of metacarpophalangeal joint was(91.8±1.6)°, and no significant difference between both side (t=1.16, P>0.05). DASH score was 4.3±1.5 at 7 months after operation. CONCLUSIONS: Manual reduction and traction fixation for the treatment of metacarpal neck fracture under ultrasound-guided could dynamic observe fracture position in time, high patients' acceptability and is a feasible method for the treatment of metacarpal neck fracture.