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IntroductionThe volume conduction effect and high dimensional characteristics triggered by the excessive number of channels of EEG cap-acquired signals in BCI systems can increase the difficulty of classifying EEG signals and the lead time of signal acquisition. We aim to combine transfer learning to decode EEG signals in the few-channel case, improve the classification performance of the motor imagery BCI system across subject cases, reduce the cost of signal acquisition performed by the BCI system, and improve the usefulness of the system.MethodsDataset2a from BCI CompetitionIV(2008) was used as Dataset1, and our team's self-collected dataset was used as Dataset2. Dataset1 acquired EEG signals from 9 subjects using a 22-channel device with a sampling frequency of 250 Hz. Dataset2 acquired EEG signals from 10 healthy subjects (8 males and 2 females; age distribution between 21-30 years old; mean age 25 years old) using an 8-channel system with a sampling frequency of 1000 Hz. We introduced EA in the data preprocessing process to reduce the signal differences between subjects and proposed VFB-RCSP in combination with RCSP and FBCSP to optimize the effect of feature extraction.ResultsExperiments were conducted on Dataset1 with EEG data containing only 8 channels and achieved an accuracy of 78.01 and a kappa coefficient of 0.54. The accuracy exceeded most of the other methods proposed in recent years, even though the number of channels used was significantly reduced. On Dataset 2, an accuracy of 59.77 and a Kappa coefficient of 0.34 were achieved, which is a significant improvement compared to other poorly improved classical protocols.DiscussionOur work effectively improves the classification of few-channel EEG data. It overcomes the dependence of existing algorithms on the number of channels, the number of samples, and the frequency band, which is significant for reducing the complexity of BCI models and improving the user-friendliness of BCI systems.

Coronavirus disease 2019 (COVID‐19), caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), has become a global pandemic worldwide. Long non‐coding RNAs (lncRNAs) are a subclass of endogenous, non‐protein‐coding RNA, which lacks an open reading frame and is more than 200 nucleotides in length. However, the functions for lncRNAs in COVID‐19 have not been unravelled. The present study aimed at identifying the related lncRNAs based on RNA sequencing of peripheral blood mononuclear cells from patients with SARS‐CoV‐2 infection as well as health individuals. Overall, 17 severe, 12 non‐severe patients and 10 healthy controls were enrolled in this study. Firstly, we reported some altered lncRNAs between severe, non‐severe COVID‐19 patients and healthy controls. Next, we developed a 7‐lncRNA panel with a good differential ability between severe and non‐severe COVID‐19 patients using least absolute shrinkage and selection operator regression. Finally, we observed that COVID‐19 is a heterogeneous disease among which severe COVID‐19 patients have two subtypes with similar risk score and immune score based on lncRNA panel using iCluster algorithm. As the roles of lncRNAs in COVID‐19 have not yet been fully identified and understood, our analysis should provide valuable resource and information for the future studies.

Glioblastoma (GBM) is the most common malignant craniocerebral tumor. The treatment of this cancer is difficult due to its high heterogeneity and immunosuppressive microenvironment. Ferroptosis is a newly found non-apoptotic regulatory cell death process that plays a vital role in a variety of brain diseases, including cerebral hemorrhage, neurodegenerative diseases, and primary or metastatic brain tumors. Recent studies have shown that targeting ferroptosis can be an effective strategy to overcome resistance to tumor therapy and immune escape mechanisms. This suggests that combining ferroptosis-based therapies with other treatments may be an effective strategy to improve the treatment of GBM. Here, we critically reviewed existing studies on the effect of ferroptosis on GBM therapies such as chemotherapy, radiotherapy, immunotherapy, and targeted therapy. In particular, this review discussed the potential of ferroptosis inducers to reverse drug resistance and enhance the sensitivity of conventional cancer therapy in combination with ferroptosis. Finally, we highlighted the therapeutic opportunities and challenges facing the clinical application of ferroptosis-based therapies in GBM. The data generated here provide new insights and directions for future research on the significance of ferroptosis-based therapies in GBM.

Tumor-derived exosomes carrying unique surface proteins have shown great promise as novel biomarkers for liquid biopsies. However, point-of-care analysis for tumor-derived exosomes in the blood with low-cost and easy processing is still challenging. Herein, we develop an integrated approach, homogenous magneto-fluorescent exosome (hMFEX) nanosensor, for rapid and on-site tumor-derived exosomes analysis. Tumor-derived exosomes are captured immunomagnetically, which further initiates the aptamer-triggered assembly of DNA three-way junctions in homogenous solution containing aggregation-induced emission luminogens and graphene oxide, resulting in an amplified fluorescence signal. By integrating magnetic isolation and enhanced fluorescence measurement, the hMFEX nanosensor detects tumor-derived exosomes in the dynamic range spanning 5 orders of magnitude with high specificity, and the limit of detection is 6.56 × 104 particles/μL. Analyzing tumor-derived exosomes in limited volume plasma from breast cancer patients demonstrates the excellent clinical diagnostic efficacy of the hMFEX nanosensor. This study provides new insights into the point-of-care testing of tumor-derived exosomes for cancer diagnostics.

Understanding the origins and migration routes of phytopathogen inoculum is essential in predicting disease development and formulating control strategies. Puccinia striiformis f. sp. tritici (Pst), the causal agent of wheat stripe rust, is an airborne fungal pathogen threatening wheat production by long-distance migration. Due to large variation in geographic features, climatic conditions, and wheat production systems, inter-regional Pst dispersal routes in China remain largely unknown. In the present research, we sequenced 154 Pst isolates sampled from all the major wheat-growing regions in China to study the Pst population structure. Western Qinling Mountains, Himalayan region, and Guizhou Plateau were found to be centers of Pst origin in China. Combined with trajectory tracking and field disease surveys, long-distance Pst migration routes from individual origins were proposed. The present findings will improve current understanding of Pst origin and migration in China and emphasize the need for managing stripe rust at the national scale.

BACKGROUND: Due to the high false-positive rate of the high-fluorescence body fluid (HF-BF) cell parameter of the hematology analyzer in BF mode, a novel algorithm based on the Mindray BC-6800 Plus hematology analyzer (BC-6800Plus), with higher diagnostic accuracy compared to that of the traditional HF-BF algorithm, was used to screen for malignant tumor cells in clinical BF samples. In this study, the body fluid mode of BC-6800Plus was applied to investigate the ability of its available parameters and characteristic regional particles in tumor cells screening. METHODS: A total of 220 BF samples (including pleural effusion and ascites) were randomly classified into a training cohort (154 samples) and a validation cohort (66 samples), and detected on the BC-6800Plus in BF mode. Based on the scatter plot analysis of the instrument, a novel gating algorithm, malignant cell algorithm-body fluid (MA-BF), was designed to detect the aggregated cells expressing highest fluorescence (FL) signals and side-scatter (SS) signals than other cells. BF collection and analyses were performed in compliance with the CLSI H56-A guideline. tumor cell-positive samples were defined as greater than or equal to confirIIIb (Papanicolaou class system) by the pathological examination. The diagnostic accuracy of HF-BF and MA-BF were determined by the receiver operating characteristic (ROC) curve analysis. RESULTS: When the cutoff values of the absolute count (HF-BF#) and relative count (HF-BF%) were set as 0.022×10(9)/L and 3.0%, respectively, the area under curve (AUC), sensitivity, and specificity were 0.76, 0.85 and 0.55 for HF-BF#, and were 0.70, 0.85, and 0.49 for HF-BF%, respectively. The new parameters, the absolute tumor cell count (MA-BF#) and relative count (MA-BF%), were established in the training cohort using the novel algorithm. We confirmed the cutoff values of MA-HF# and MA-HF% in BF were set as 0.006×10(9)/L and 0.2% in the training cohort, respectively. In the validation cohort, the AUC, sensitivity, and specificity were 0.89, 0.93, and 0.78 for MA-BF#, and were 0.89, 0.87 and 0.75 for MA-BF%, respectively. CONCLUSIONS: The MA-BF parameters of the novel algorithm output had better diagnostic accuracy for BF tumor cells than the traditional HF-BF parameters.

To study the influence of control parameters under cold-start and low-load conditions on the performance of a heavy-oil, two-stroke, direct-injection, ignition engine for use in aviation, the operation of a two-stroke, direct-injection engine was studied in a bench test. The results were as follows: ① When the ambient temperature is 15 °C, the battery voltage is 12.4 V, and the peak speed of the starting motor is 1200 r/min. As the concentration factor increases, the cold-start speed increases, and the fuel consumption increases. The influence on the cold start is reduced after reaching a certain concentration. The cold-start time decreases with the increasing magnetization pulse width. The cold-start time is the shortest at an oil–gas interval of 6 ms. ② Under small-load conditions of 3000 r/min and 14% to 16% throttle, a higher ignition energy increases the engine power. Pollutant emissions are the lowest when the fuel injection is 7.5 mg and the excess air coefficient is approximately 1.1.

Software Defined Networking (SDN) is an emerging network technology where network control plane, which is programmable, is decoupled from the data forwarding plane and moved to the SDN controller. Originally, an SDN network is controlled by a single controller. As the SDN architecture becomes more complex with multiple SDN domains and corresponding domain controllers, inter-domain routing becomes an important design issue. There are a number of approaches for SDN inter-domain routing. The most popular approach is the hierarchical approach where a central controller coordinates with lower level domain controllers to control the data flow. The main drawback of the hierarchical approach is that it is not scalable, and the central controller represents a single point of failure. In this thesis, we proposed and designed a distributed inter-domain routing mechanism. The distributed approach enables domain controllers to exchange information with each other directly instead of communicating through the central controller. We also proposed and designed a new load balancing scheme which makes use of the network traffic information to choose a less-congested path among equal-cost multiple paths. We successfully implement the proposed inter-domain routing mechanism and load balancing scheme using Python/Java in the OpenDayLight SDN controller, which is a popular open-source SDN platform. In addition, the test result of the proposed load-balancing scheme shows that it performs better than the scheme based on the roundrobin mechanism.

To study the influence of injection time and injection volume on the working process of a two-stroke kerosene direct injection engine, an experimental study was carried out on an improved two-stroke inline three-cylinder gasoline engine, combined with calculations and analysis with GT-POWER and AVL FIRE software. The results showed that when the injection end angle increased from 50° to 70° before the top dead center (BTDC), the average pressure and temperature in the cylinder increased rapidly, the peak value of pressure and temperature and the cumulative heat release increased, and the combustion process in the cylinder was more sufficient. The fuel injection volume was set to 7.5 mg, 8 mg, and 8.5 mg. With increasing fuel injection volume, the average pressure and average temperature first increased and then decreased, the peak value gradually increased, the heat release rate and cumulative heat release increased sharply, the corresponding time gradually advanced, and the peak value gradually increased. With increasing fuel injection volume, CO, NO, and soot gradually increased, while CO2 slightly decreased.

Xiumei Hu,1,* Changmeng Wu,1,* Bo Situ,1,* Peifu Tian,2,* Taixue An,1 Qiang Li,1 Weilun Pan,1 Ruyi Zhang,1 Biao Yang,3 Dehua Sun,1 Yuhai Hu,2 Qian Wang,1,3 Lei Zheng1 1Department of Laboratory Medicine, Nanfang Hospital, Southern Medical University, Guangzhou 510515, People’s Republic of China; 2Department of Medicine Laboratory, Hankou Hospital of Wuhan, Wuhan 430010, People’s Republic of China; 3Department of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong 510280, People’s Republic of China*These authors contributed equally to this workCorrespondence: Lei Zheng; Qian Wang Email nfyyzhenglei@smu.edu.cn; wangqian@smu.edu.cnObjective: The coronavirus disease (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is now rapidly spreading globally. Serological tests are an important method to assist in the diagnosis of COVID-19, used for epidemiological investigations. In this study, we aimed to investigate the impact of different types of vacuum collection tubes on the detection of SARS-CoV-2 IgM and IgG antibodies, using the colloidal gold immunochromatographic assay (GICA).Patients and Methods: A total of 112 patients with COVID-19 and 200 healthy control subjects with no infection were enrolled in this study. Their serum and plasma were collected into four different types of vacuum blood collection tubes. SARS-CoV-2 IgM and IgG specific antibodies in the plasma and serum were then detected by GICA and chemiluminescence assay (CA), respectively. In addition, the particle sizes of different colloidal gold solutions in the presence of different anticoagulants and coagulants were evaluated by both laser diffraction (Malvern) and confocal laser microscope, respectively.Results: Our results revealed that anticoagulated plasma with EDTA-K2 improved the positive detection rate of SARS-CoV-2 IgM antibodies. Furthermore, our results shown that the detection results by GICA and CA were highly consistent, especially, the results of EDTA-K2 anticoagulated plasma detected by GICA was more consistent with CA results. We confirmed that EDTA-K2 could improve the detection sensitivity of SARS-CoV-2 IgG antibodies by chelating excessive colloidal gold compared with sodium citrate or lithium heparin, these methodologies did not appear to cause false positives. Colloidal gold particles could be chelated and aggregated by EDTA-K2, but not by sodium citrate, lithium heparin and coagulants.Conclusion: GICA is widely used to detect antibodies for the advantages of convenient, fast, low cost, suitable for screening large sample and require minimal equipment. In this study, we found that EDTA-K2 amplified the positive antibody signal by chelating colloidal gold and improved the detection sensitivity of SARS-CoV-2 IgM and IgG antibodies when using the GICA. Therefore, we suggested that EDTA-K2 anticoagulated plasma was more suitable for the detection of SARS-CoV-2 antibodies.Keywords: EDTA-K2, SARS-CoV-2, antibodies, gold immunochromatographic assay; GICA

The detection of serum antibodies to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is emerging as a new tool for the coronavirus disease-2019 (COVID-19) diagnosis. Since many coronaviruses are sensitive to heat, heating inactivation of samples at 56 °C prior to testing is considered a possible method to reduce the risk of transmission, but the effect of heating on the measurement of SARS-CoV-2 antibodies is still unclear. By comparing the levels of SARS-CoV-2 antibodies before and after heat inactivation of serum at 56 °C for 30 minutes using a quantitative fluorescence immunochromatographic assay, we shown that heat inactivation significantly interferes with the levels of antibodies to SARS-CoV-2. The IgM levels of all the 34 serum samples (100%) from COVID-19 patients decreased by an average level of 53.56%. The IgG levels were decreased in 22 of 34 samples (64.71%) by an average level of 49.54%. Similar changes can also be observed in the non-COVID-19 diseases group (n=9). Of note, 44.12% of the detected IgM levels were dropped below the cut-off value after heating, suggesting heat inactivation can lead to false-negative results of these samples. Our results indicate that heat inactivation of serum at 56 °C for 30 minutes interferes with the immunoanalysis of antibodies to SARS-CoV-2. Heat inactivation prior to immunoanalysis is not recommended and the possibility of false-negative results should be considered if the sample was pre-inactivated by heating.

In order to promote the intelligent and standardized production of green light-weight wall materials in prefabricated buildings, an electrical automation control system for light-weight wall panels based on PLC technology was proposed. The process flow of the wall panel production line is analyzed, and the hardware system of the control system is determined through the selection of hardware such as motors and cylinders. The batching system, extrusion molding system, cutting system, palletizing system, transfer and maintenance system, etc. can be programmed through PLC technology. and automated production of wall panels can be accomplished by utilizing sensors and limit switches.

Exosomes shed by tumor cells have been recognized as promising biomarkers for cancer diagnostics due to their unique composition and functions. Quantification of low concentrations of specific exosomes present in very small volumes of clinical samples may be used for noninvasive cancer diagnosis and prognosis. We developed an immunosorbent assay for digital qualification of target exosomes using droplet microfluidics. The exosomes were immobilized on magnetic microbeads through sandwich ELISA complexes tagged with an enzymatic reporter that produces a fluorescent signal. The constructed beads were further isolated and encapsulated into a sufficient number of droplets to ensure only a single bead was encapsulated in a droplet. Our droplet-based single-exosome-counting enzyme-linked immunoassay (droplet digital ExoELISA) approach enables absolute counting of cancer-specific exosomes to achieve unprecedented accuracy. We were able to achieve a limit of detection (LOD) down to 10 enzyme-labeled exosome complexes per microliter (∼10