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This meta-analysis was performed to determine the effects of continuous positive airway pressure (CPAP) on blood pressure (BP) in patients with systemic hypertension and obstructive sleep apnea (OSA). A systematic search was conducted using PubMed, Embase, Web of Science, Cochrane Library, and clinicaltrials.gov, without language restrictions. Randomized controlled trials on the treatment of hypertension and OSA with CPAP, compared with sham CPAP or no CPAP, were reviewed. Studies were pooled to obtain weighted mean differences (WMDs) with 95% confidence intervals (CIs). Nineteen trials (enrolling 1904 participants) met the inclusion criteria. CPAP had significant effects on 24-h systolic blood pressure (SBP) (WMD -5.01 mmHg, 95% CI -6.94 to -3.08; P 0.00001), 24-h diastolic blood pressure (DBP) (WMD -3.30 mmHg, 95% CI -4.32 to -2.28; P 0.00001), daytime SBP (WMD -4.34 mmHg, 95% CI -6.27 to -2.40; P 0.0001), daytime DBP (WMD -2.97 mmHg, 95% CI -3.99 to -1.95; P 0.00001), nighttime SBP (WMD -3.55 mmHg, 95% CI -5.08 to -2.03; P 0.00001), nighttime DBP (WMD -2.33 mmHg, 95% CI -3.27 to -1.40; P 0.00001), office SBP (WMD -3.67 mmHg, 95% CI -5.76 to -1.58; P = 0.0006), office DBP (WMD -2.61 mmHg, 95% CI -4.25 to -0.97; P = 0.002), and heart rate (WMD -2.79 beats/min, 95% CI -4.88 to -0.71; P = 0.009). CPAP treatment was associated with BP reduction in patients with systemic hypertension and OSA, except when the follow-up period was shorter than 3 months.

The Coronavirus disease-2019 (COVID-19) pandemic continues, and the death toll continues to surge. This meta-analysis aimed to determine the efficacy of anakinra on mortality in patients with COVID-19. A systematic search was made of PubMed, Embase, Cochrane Library, and clinicaltrials.gov, without language restrictions. Randomized controlled trials on treatment of COVID-19 with anakinra, compared with placebo or blank, were reviewed. Studies were pooled to risk ratios (RRs), with 95% confidence intervals (CIs). Five Randomized controlled trials (enrolling 1859 participants) met the inclusion criteria. There was no statistically significant difference in 14-day mortality (RR 0.78, 95% CI 0.43-1.39; P = 0.40), 28-day mortality (RR 1.06, 95% CI 0.89-1.26; P = 0.51), and 90-day mortality (RR 1.01, 95% CI 0.73-1.39; P = 0.97) between the two groups. Sensitivity analyses further confirmed these results. Anakinra was not associated with reduced mortality in hospitalised patients with COVID-19. Anakinra probably should not be used routinely in COVID-19 patients.

Chestnut (Castanea mollissima Bl.) is an economically important tree species that is primarily utilized for nut and timber production. The protein phosphatase 2C (PP2C) gene family contributes largely to stress responses and developmental processes in several plants. However, the classification, characteristics, and functions of chestnut PP2C genes are unknown. Here, we provide comprehensive analyses and expression profiles of PP2C genes in the chestnut genome. A total of 68 genes were identified, whose protein length (PL), molecular weights (MW) and isoelectric points (IP) are 186 ~ 1079 amino acids, 20.31 ~ 119.40 kDa, and 4.66 ~ 9.30, respectively. They are randomly distributed on 12 chromosomes. These genes formed 12 phylogenetic clusters. Most CmPP2C (PP2C in chestnut) proteins within a subgroup had similar compositions of amino acid sequences of motifs, conserved domains, and exon/introns, according to phylogenetic analyses. The expression profile analysis revealed both significant CmPP2C expression levels in leaves and seeds, and the clear involvement of CmPP2C22 in seed development and multiple abiotic stresses. These findings indicate that CmPP2C genes play potential vital roles in chestnut response to multiple abiotic stresses and provide new insights into the function of CmPP2C genes.

The Coronavirus disease-2019 (COVID-19) pandemic continues, and the death toll continues to surge. Ozone therapy has long been used in the treatment of a variety of infectious diseases, probably through its antioxidant properties and the supply of oxygen to hypoxic tissues. This systematic review and meta-analysis aimed to determine the efficacy of ozone on mortality in patients with COVID-19.A systematic search was made of PubMed, Embase, Cochrane Library, and clinicaltrials.gov, without language restrictions. Prospective controlled trials on treatment of COVID-19 with ozone, compared with placebo or blank, were reviewed. Studies were pooled to risk ratios (RRs) and weighted mean differences (WMDs), with 95% confidence intervals (CIs).Eight trials (enrolling 371 participants) met the inclusion criteria. Ozone therapy showed significant effects on mortality (RR 0.38, 95% CI 0.17-0.85; P = 0.02), length of hospital stay (WMD -1.63 days, 95% CI -3.05 to -0.22 days; P = 0.02), and polymerase chain reaction (PCR) positivity (RR 0.07, 95% CI 0.01-0.34; P = 0.001).Ozone therapy significantly reduced mortality, PCR positivity, and length of stay in hospitalized patients with COVID-19. Ozone therapy should be considered for COVID-19 patients.

Purpose We aimed to report the clinical characteristics of 194 cases coronavirus disease-19 (COVID-19) in Huanggang, Hubei and Taian, Shandong. Methods We retrospectively investigated the clinical, laboratory characteristics and CT imaging of confirmed cases of COVID-19 from January 22 to February 28, 2020 in Huanggang Central Hospital and The Second Affiliated Hospital of Shandong First Medical University. Real time PCR was used to detect the new coronavirus in respiratory samples. Immunohistochemical staining was used to detect the expressions of ACE2 in tissues. Results Among the 194 patients infected with COVID-19, 108 patients were male, with a median age of 48.3 years. The average preclinical period was 7.44 day. Except for 37 severe or critically ill patients, the rest of the 157 patients exhibited mild or moderate symptoms. 190 (97.94%) patients were confirmed during the three times nucleic acid test. The main clinical symptom of the patients were fever, sore throat and cough, which accounted for 146 cases (75.26%), 98 (50.52%) and 86 cases (44.33%), respectively. 30 patients (15.46%) showed liver dysfunction. Imaging examination showed that 141 patients (72.68%) showed abnormal density shadow, while 53 cases (27.32%) had no obvious abnormality in the parenchyma of both lungs. Up to now, 109 cases have been discharged from the hospital, and 9 patients died. The ACE2 expression levels were up-regulated in patients of severe type and critically ill type. Conclusion Clinical symptoms, laboratory tests and CT imaging should be combined for comprehensive analysis to diagnose COVID-19. ACE2 may be the receptor of COVID-19. Electronic supplementary material The online version of this article (10.1007/s15010-020-01440-5) contains supplementary material, which is available to authorized users.

Aiming at the real-time requirements for industrial control systems, we proposed a corresponding trust chain method for industrial control system application software and a component analysis method based on security sensitivity weights. A dynamic length trust chain structure is also proposed in this paper. Based on this, the industrial control system software integrity measurement method is constructed. Aimed at the validity of the model, a simulation attack experiment was performed, and the performance of the model was repeated from multiple perspectives to verify the performance of the method. Experiments show that this method can effectively meet the integrity measurement under the condition of high real-time performance, protect the integrity of files, and improve the software credibility of industrial control system.

The coverage of test cases is an important indicator for the security and robustness test of industrial control protocols. It is an important research topic to complete the test with less use cases. Taking Modbus protocol as an example, a calculation method of case similarity and population dispersion based on weight division is proposed in this paper. The method can describe the similarity of use cases and the dispersion degree of individuals in the population more accurately. Genetic algorithm is used to generate and optimize test cases, and individual similarity and population dispersion are used as fitness functions of genetic algorithm. Experimental results show that the proposed method can increase the population dispersion by 3.45% compared with the conventional methods and effectively improve the coverage of test cases.

This systematic review and meta-analysis was performed to determine the safety of long-term use of ICS in patients with asthma.A systematic search was made of PubMed, Embase, Web of Science, Cochrane Library, and clinicaltrials.gov, without language restrictions. Randomized controlled trials (RCTs) on treatment of asthma with ICS, compared with non-ICS treatment (placebo or other active drugs), were reviewed.Eighty-six RCTs (enrolling 51,538 participants) met the inclusion criteria. Oral or oropharyngeal candidiasis (RR 2.58, 95% CI 2.00 to 3.33), and dysphonia/hoarseness (RR 1.56, 95% CI 1.31 to 1.85) were less frequent in the control group. There was no statistically significant difference in the risk of upper respiratory tract infection, lower respiratory tract infection, influenza, decline in bone mineral density, and fractures between the two groups.In addition to the mild local adverse events, the long-term use of ICS was safe in patients with asthma.

The Industrial Internet of Things (IIoT) enables massive industrial control terminals to be interconnected. In order to avoid the intrusion of illegal terminals into the system, the terminals must be accurately identified. Aiming at the problem of low recognition accuracy of current terminal recognition scheme, a feature extraction and recognition method of industrial control terminal based on MGA-SVM dimension reduction is proposed. By collecting the message information returned by the scanned object from all kinds of terminals in the scanning network, a hybrid method of multi parent cross mutation genetic algorithm and support vector machine is proposed to extract and optimize the acquired data to obtain the best subset that can mark the terminal features. On this basis, the method of industrial control terminal recognition based on integrated learning is proposed. Experimental results show that this method can effectively improve the recognition accuracy.

In today's information age, in order to meet the requirement of high efficiency outlier detection in the production process of industrial control system, the intrusion characteristics are analyzed and warned in time to prevent from happening. An intrusion detection scheme (IGR-MEM) based on information gain ratio feature selection and maximum entropy model is proposed. The collected industrial control data are normalized and a new information gain ratio feature selection method considering feature correlation and redundancy is proposed to choose the best feature subset from the network connection data. According to the extracted training sample feature subset, the maximum entropy model is devoted to construct the classifier, and finally the trained classifier is applied for intrusion detection. The test results express that the IGR-MEM scheme is able to select the best feature collection, improve the detection efficiency, and improve the accuracy of ICS security monitoring and reduce the false alarm rate compared with other algorithms.

PURPOSE: This meta-analysis was performed to determine the effects of continuous positive airway pressure (CPAP) treatment on glycemic control and insulin resistance in patients with type 2 diabetes and obstructive sleep apnea (OSA). METHODS: A systematic search was made of MEDLINE, SCOPUS, ISI Web of Science, Cochrane databases, and clinicaltrials.gov, without language restrictions. Randomized controlled trials on treatment of type 2 diabetes and OSA with CPAP, compared with sham CPAP or no CPAP, were reviewed. Studies were pooled to standardized mean differences (SMD), with 95% confidence interval (CI). RESULTS: Seven trials (enrolling 691 participants) met the inclusion criteria. CPAP presented significant effects on glycated hemoglobin (HbA1c) (SMD -0.32; 95% CI -0.60 to -0.03; p = 0.029), fasting glucose (SMD -0.39; 95% CI -0.76 to -0.02; p = 0.040), Homeostasis Model Assessment-Insulin Resistance (HOMA-IR) (SMD -1.05; 95% CI -1.91 to -0.19; p = 0.016), systolic blood pressure (SBP) (SMD -1.18; 95% CI -2.29 to -0.07 mmHg; p = 0.037), and diastolic blood pressure (DBP) (SMD -1.29; 95% CI -2.48 to -0.09; p = 0.035). ConclusionsCPAP treatment significantly improved glycemic control and insulin resistance which is indicated by the decreased levels of HbA1c, fasting glucose, and HOMA-IR in patients with type 2 diabetes and contemporary OSA. This article is protected by copyright. All rights reserved.

In view of the security threats caused by the code execution vulnerability of the industrial control system, design the trusted security architecture of the industrial control system based on the embedded system. From the trusted startup of industrial control equipment, the safety protection for industrial control system is completed. The scheme is based on TPM and Xilinx Zynq-7030 to build an industrial trusted computing environment and complete the trusted startup process. Experiment shows that this method can effectively prevent the destruction of malicious code during the startup process of embedded system and provide technical support for the construction of trusted computing environment of industrial control system.

Aiming at the current lack of certification capability in domestic industrial control systems, an industrial control system authentication scheme based on identity cryptography algorithm is proposed. When authenticating between control system devices, the scheme integrates the identity-based digital signature algorithm into the SSL/TLS handshake protocol to complete identity authentication between the engineering station and the trusted PLC. At the same time, when the connection is established for the first time between devices, the connection authentication is selected by the challenge/response based method. The authentication technology based on the identity cryptographic algorithm no longer requires the existence of a public key certificate. This eliminates the need to revoke, store, and issue certificates, simplifies the certification process and reduces the amount of computation required by the authentication process. At the same time, the improved handshake protocol is universal in industrial control systems. The authentication technology based on the identity and password algorithm no longer requires the existence of a public key certificate, eliminating the need for certificate revocation, storage, and issuance, simplifying authentication steps, and reducing system maintenance. Finally, by establishing a test environment, the improved handshake protocol is implemented, and the feasibility of the authentication scheme is verified and analyzed.

Six-transmembrane epithelial antigen of prostate-1 (STEAP1) is a relatively newly identified gene target from prostate cancer, breast cancer, and gastric cancer. However, functions of STEAP1 in lung adenocarcinoma (LUAD) are still unknown. In the present study, we explored the molecular and cellular mechanisms of STEAP1 in LUAD. Western blot and Q-PCR were conducted to detect the protein and mRNA expressions respectively. The cell proliferation was tested by CCK8 assay. The effects of STEAP1 on the metastasis and epithelial–mesenchymal transition (EMT) of LUAD were evaluated by EdU assay, wound healing assay, and transwell migratory assay. H1650, H358, HCC827, H1299, H23, A549, H1693 were selected as human LUAD cell lines in the study. Results have shown that STEAP1 expression was up-regulated in LUAD cells compared with normal lung epithelial cells. Knockdowning of STEAP1 suppressed the proliferation, migration, and invasion of LUAD epithelial cells. Importantly, after comparing the proliferation, migration, and invasion of LUAD to the corresponding control groups treated in STAT3 inhibitor ADZ1480, we found that STEAP1 regulates EMT via Janus kinase 2/signal transducer and activator of transcription 3 (JAK2/STAT3) signaling pathway. In conclusion, STEAP1 can serve as a therapeutic target, and it may have important clinical implications for LUAD treatment.

Software Defined Networking (SDN) is a new type of network architecture, which provides an important way to implement automated network deployment and flexible management. However, security problems in SDN are also inevitable. DDoS attack belongs to one of the most serious attack types, which is fairly common for today’s Internet. In SDN security fields, DDoS attack detection research has been received more and more attention. In this paper, a DDoS attack detection method based on one-class SVM in SDN is proposed, which provides a better detection accuracy. Furthermore, two new feature vectors, including middle value of flow table item’s duration and protocol data traffic percentage, are extracted to integrate into the item of 11 feature vectors. Additionally, basing on selection and construction method of the 11 feature vectors, a DDoS attack behavior model is established by using one-class SVM algorithm, and the self-adaptation genetic algorithm is designed to optimize the corresponding parameters of the Gaussian kernel of one-class SVM. The experimental results in SDN show that, the proposed new feature vectors are shown to more better detection accuracy, and the proposed method is more feasible by comparing with the BP neural network and RBF neural network algorithms under the same 11 features vectors.

As the development of smart grid, Wireless Sensor Network (WSN) is applied in many electrical and environmental parameter measurement scenarios. Since wireless sensor nodes have limited energy supply, energy-efficient communication scheme is required in the WSNs. Edge computing is a useful technique to reduce the energy consumption for sinks or aggregation nodes. However, the energy-saving problem for the ordinary sensor nodes remains unsolved. In the electric communication network, the measurements of wireless sensor nodes will be quantized and encrypted before transmitting. Because the ciphertext is much longer than the original messages, extra communication overhead is caused by the data encryption. In this paper, we propose the Energy Minimum Encrypted Data Aggregation (EMEDA) scheme to reduce the overhead from data encryption. EMEDA can minimize the ciphertext data length of each sensor node through scheduling quantization data length of A/D convertor. As a result, the communication overhead between sensor node and Edge Computing Node (ECN) can be reduced.

Due to the growing dependencies of information network technology, networked control systems are undergoing a severe blow of cyberattacks, and simply modeling cyberattacks is inadequate and impractical for the detection requirements, because of various vulnerabilities in these systems and the diversities of cyberattacks. Actually, a feasible viewpoint is to identify misbehaviors by constructing a normal model of industrial communication behaviors. However, one of the chief difficulties is how to completely and appropriately summarize industrial communication behaviors according to the specific communication characteristics. In view of process control and data acquisition, this paper associates industrial communication characteristics with the time sequence, and further extracts two distinct behaviors: function control behavior and process data behavior. Based on these double behavior characteristics, we introduce one-class classification to detect the corresponding anomalies, respectively. Besides, we also present the weighted mixed Kernel function and parameter optimization method to improve classification performance. Experimental results clearly demonstrate that the proposed approach has significant advantages of classification accuracy and detection efficiency.

Attacks on industrial control systems have different types and various intensities. Predicting the development trend of security state for updating defense strategy in time is important. Every single prediction model has its different emphases, and the accuracy of single prediction model may be reduced when the system is attacked. Combined prediction model integrates the prediction results of multiple single prediction models to improve the overall prediction accuracy. The weight of the combined model is determined by the mean square error of every single model. It is taken a logarithmic function of the mean square error of each single model to enlarge the difference between the superior and inferior models. Then, the simple weight function is taken to determine the weight of each model based on the logarithm result of each model.This approach makes greater use of accurate model information. Through the comparative analysis of the model, the error of the combined prediction method is obviously reduced. Through the comparison and analysis of the weighted method, the error of the weighted method of the combined prediction model proposed in this paper is the minimum. The combined prediction method can provide more accurate defense opinions for network security administrators.

Information security risk assessment for industrial control system is usually influenced by uncertain factors. For effectively dealing with problem that the uncertainty and quantification difficulties are caused by subjective and objective factors in the assessment process, an information security risk assessment method based on attack tree model with fuzzy set theory and probability risk assessment technology is proposed, which is applied in a risk scenario of ship control system. Firstly, potential risks of the control system are analyzed and the attack tree model is established. Then triangular fuzzy numbers and expert knowledge are used to determine the factors that influence the probability of a leaf node and the leaf nodes are quantified to obtain the interval probability. Finally, the fuzzy arithmetic is used to determine the interval probability of the root node and the attack path. After defuzzification, the potential risks of the system and the probability of occurrence of each attack path are obtained. Compared with other methods, the proposed method can greatly reduce the impact of subjectivity on the risk assessment of industrial control systems and get more stable, reliable, and scientific evaluation results.