The Impact of Cardiovascular Disease Gene Polymorphism and Interaction with Homocysteine on Deep Vein Thrombosis.

Deep vein thrombosis (DVT) affects vascular health and can even threaten life; however, its pathogenesis remains unclear. Cardiovascular disease (CVD) and DVT share common risk factors, such as dyslipidemia, aging, etc. We aimed to investigate the loci of published CVD susceptibility genes and their association with environmental factors that might be related to DVT. Genotyping by Kompetitive Allele Specific PCR (KASP), collection of lifestyle information, and determination of blood biochemical markers were performed in 165 DVT cases and 164 controls. The impact of six single nucleotide polymorphisms (SNPs) and additional potential variables on DVT morbidity was evaluated using unconditional logistic regression (ULR). To explore the high-order interactions related to genetics and the body's internal environment exposure that affect DVT, ULR, crossover analysis, and multifactor dimensionality reduction/generalized multifactor dimensionality reduction (MDR/GMDR) were employed. Sensitivity analyses were performed using the EpiR package. The polymorphisms of FGB rs1800790 and PLAT rs2020918 were significantly associated with DVT. The optimum GMDR interaction model for gene-gene (G × G) consisted of THBD rs1042579, PLAT rs2020918, and PON1 rs662. The PLAT rs2020918 and MTHFR rs1801133 polymorphisms together eliminated the maximum entropy by the MDR method. The optimum GMDR interaction model for gene-environment (G × E) consisted of MTHFR rs1801133, FGB rs1800790, PLAT rs2020918, PON1 rs662, and total homocysteine (tHcy). Those with high tHcy levels and three risk genotypes significantly increased the DVT risk. In conclusion, certain CVD-related SNPs and their interactions with tHcy may contribute to DVT. These have implications for investigating DVT etiology and developing preventive treatment plans.

Norm Emergence through Conflict-Blocking Interactions in Industrial Internet of Things Environments.

Norms have been effectively utilized to facilitate smooth interactions among agents. Norms are usually the global data that agents cannot directly access in complex environments; instead, norms can only be indirectly accessed by agents via maintaining their own beliefs about norms. Establishing norms using decentralized interaction-based methods has attracted much attention. However, the current methods overlook Industrial Internet of Things (IIoT) environments. In IIoT, there is a prevalent feature called "conflict-blocking", where agents' conflicting action strategies can block an interaction from being completed or even cause danger. To facilitate norm emergence in IIoT, we propose a framework to support agent decisions in conflict-blocking interactions. The framework aids in achieving system scalability by integrating the fusion of agent beliefs about norms. We prove that the proposed framework guarantees norm emergence. We also theoretically and experimentally analyze the time required for norm emergence under the influence of various factors, such as the number of agents. A vehicle movement simulator is also developed to vividly illustrate the process of norm emergence.

Mental health of primary health care physicians and nurses following prolonged infection control rules: a national survey in China.

Introduction: This study examined the prevalence and correlates of probable mental health disorders, including psychological distress, somatization, depression, anxiety, phobic anxiety (PHO), obsessive-compulsive disorder (OCD), post-traumatic stress disorder (PTSD), and insomnia among Chinese primary health care (PHC) physicians and nurses amid the post-pandemic period in 2022. Method: Region-stratified sampling was conducted to recruit a national sample of 4,246 respondents from 31 July 2022 to 12 August 2022. A total of 692 primary healthcare institutions were identified in 30 provincial-level administrative regions of China. An online questionnaire was used for assessing probable mental health disorders using Symptoms Checklist-90-Revised (SCL-90-R) and PTSD Checklist for DSM-5 (PCL-5), and sleeping problems using Insomnia Severity Index (ISI). Data on demographics and work were also collected. Bivariate analysis and multiple logistic regression were conducted to identify significant correlates of probable mental health disorders. Results: A total of 4,246 valid questionnaires were identified. Results showed that relative to the prevalence of probable mental health disorders among health care workers at the early stage of the pandemic in China, there was an overall decreased prevalence except for somatization, PHO, and OCD among the current PHC physicians and nurses. Multiple logistic regressions showed that significant risk factors of common probable mental health disorders, namely psychological distress, SOM, DEP, ANX, PHO, OCD, PTSD, and insomnia, were female gender, multimorbidity, history of psychiatric disorders, quarantine experience, never asking anyone for help, and overtime work. Conclusion: Attention should be given to preexisting psychiatric and multimorbid conditions, social support, and work-related stressors. Regular assessment and psychological interventions are needed to enhance the mental health of PHC professionals even after public health crisis.

Application of λ esophagojejunostomy in total gastrectomy under laparoscopy: a modified technique for post-gastrectomy reconstruction.

Objective: Common gastrectomy methods can significantly affect patients' postoperative quality of life. This study investigated the safety, feasibility, and short-term efficacy of λ-type esophagojejunostomy in total gastrectomy under total laparoscopy. Methods: We retrospectively analyzed the clinical and follow-up data of 50 patients with adenocarcinoma of the gastric/gastroesophageal junction who underwent total laparoscopic radical gastrectomy with λ-type esophagojejunostomy at the Beijing Friendship Hospital from January 2021 to July 2022. Data are reported as mean ± standard deviation. Results: Patients comprised 27 males and 23 females, aged 42 to 76 (60.9 ± 5.6) years. There were 26 cases of gastroesophageal junction adenocarcinoma (16 Siewert type II and 10 Siewert type III) and 24 cases of adenocarcinoma of the proximal gastric body. All patients underwent radical total gastrectomy and D2 lymph node dissection with λ-type esophagojejunostomy for digestive tract reconstruction under total laparoscopy. The total operation time was 235-295 (249.4 ± 48.5) min, digestive tract reconstruction time was (48.2 ± 23.2) min, intraoperative blood loss was (63.4 ± 48.4) mL, recovery time of exhaust was (3.1 ± 2.2) d, first drinking or eating time was (4.1 ± 2.1) d, and hospital stay was (9.3 ± 4.4) d. Three patients had postoperative complications, including one with duodenal remnant leakage combined with abdominal infection. Anastomotic bleeding and postoperative inflammatory intestinal obstruction occurred in one patient each, all of whom were cured by conservative treatment. The Nutritional Risk Index of the whole group was 53.5 ± 8.4 preoperatively, 47.3 ± 5.6 one week postoperatively, 50.3 ± 5.6 six months postoperatively, and 52.4 ± 4.2 at 12 months postoperatively. Roux-en-Y stasis syndrome and bile reflux esophagitis occurred in one patient each (2.0%). There were no occurrences of recanalization of the closed end of the afferent loop of the esophagojejunostomy anastomosis, anastomotic stricture or obstruction, or tumor recurrence. Conclusion: λ-type esophagojejunostomy is safe and feasible for digestive tract reconstruction after total laparoscopic radical gastrectomy. This digestive tract reconstruction method not only maintains intestinal continuity but also simplifies surgical procedures, allowing patients to recover quickly with an excellent short-term effect.

Identification and Analysis of the Geohazards Located in an Alpine Valley Based on Multi-Source Remote Sensing Data.

Geohazards that have developed in densely vegetated alpine gorges exhibit characteristics such as remote occurrence, high concealment, and cascading effects. Utilizing a single remote sensing datum for their identification has limitations, while utilizing multiple remote sensing data obtained based on different sensors can allow comprehensive and accurate identification of geohazards in such areas. This study takes the Latudi River valley, a tributary of the Nujiang River in the Hengduan Mountains, as the research area, and comprehensively uses three techniques of remote sensing: unmanned aerial vehicle (UAV) Light Detection and Ranging (LiDAR), Small Baseline Subset interferometric synthetic aperture radar (SBAS-InSAR), and UAV optical remote sensing. These techniques are applied to comprehensively identify and analyze landslides, rockfalls, and debris flows in the valley. The results show that a total of 32 geohazards were identified, including 18 landslides, 8 rockfalls, and 6 debris flows. These hazards are distributed along the banks of the Latudi River, significantly influenced by rainfall and distribution of water systems, with deformation variables fluctuating with rainfall. The three types of geohazards cause cascading disasters, and exhibit different characteristics in the 0.5 m resolution hillshade map extracted from LiDAR data. UAV LiDAR has advantages in densely vegetated alpine gorges: after the selection of suitable filtering algorithms and parameters of the point cloud, it can obtain detailed terrain and geomorphological information on geohazards. The different remote sensing technologies used in this study can mutually confirm and complement each other, enhancing the capability to identify geohazards and their associated hazard cascades in densely vegetated alpine gorges, thereby providing valuable references for government departments in disaster prevention and reduction work.

Long-term outcomes of laparoscopic versus open distal gastrectomy for patients with advanced gastric cancer in North China: a multicenter randomized controlled trial.

BACKGROUND: Laparoscopic distal gastrectomy (LDG) has become a common procedure for treating advanced gastric cancer (AGC) in China. However, there is uncertainty regarding its oncological outcomes compared to open distal gastrectomy (ODG). This study aims to compare the 3-year disease-free survival (DFS) rates among patients who underwent surgery for AGC in northern China. METHODS: A multicenter, non-inferiority, open-label, parallel, randomized clinical trial was conducted to evaluate patients with AGC who were eligible for distal gastrectomy at five tertiary hospitals in North China. In this trial, patients were randomly assigned preoperatively to receive either LDG or ODG in a 1:1 allocation ratio. The primary endpoint was postoperative morbidity and mortality within 30 days and the secondary endpoint was the 3-year DFS rate. This trial has been registered at ClinicalTrials.gov (Identifier: NCT02464215). RESULTS: A total of 446 patients were randomly allocated to LDG (n = 223) or ODG group (n = 223) between March 2014 and August 2017. After screening, a total of 214 patients underwent the open surgical approach, while 216 patients underwent laparoscopic surgery. The 3-year DFS rate was 85.9% for the LDG group and 84.72% for the ODG group, with no significant statistical difference (Hazard ratio 1.12; 95% CI 0.68-1.84, P = 0.65). Body mass index (BMI) < 25 kg/m2, advanced pathologic T4, and pathologic N2-3 category were confirmed as independent risk factors for DFS in the Cox regression. CONCLUSIONS: In comparison to ODG, LDG with D2 lymphadenectomy yielded similar outcomes in terms of 3-year DFS rates among patients diagnosed with AGC.

Performance of four different microalgae-based technologies in antibiotics removal under multiple concentrations of antibiotics and strigolactone analogue GR24 administration.

The formation of symbionts by using different combinations of endophytic bacteria, microalgae, and fungi to purify antibiotics-containing wastewater is an effective and promising biomaterial technology. As it enhances the mixed antibiotics removal performance of the bio-system, this technology is currently extensively studied. Using exogenous supplementation of various low concentrations of the phytohormone strigolactone analogue GR24, the removal of various antibiotics from simulated wastewater was examined. The performances of Chlorella vulgaris monoculture, activated sludge-C. vulgaris-Clonostachys rosea, Bacillus licheniformis-C. vulgaris-C. rosea, and endophytic bacteria (S395-2)-C. vulgaris-C. rosea co-culture systems were systematically compared. Their removal capacities for tetracycline, oxytetracycline, and chlortetracycline antibiotics from simulated wastewater were assessed. Chlorella vulgaris-endophytic bacteria-C. rosea co-cultures achieved the best performance under 0.25 mg L-1 antibiotics, which could be further enhanced by GR24 supplementation. This result demonstrates that the combination of endophytic bacteria with microalgae and fungi is superior to activated sludge-B. licheniformis-microalgae-fungi systems. Exogenous supplementation of GR24 is an effective strategy to improve the performance of antibiotics removal from wastewater.

MicroRNA­17­5p alleviates sepsis­related acute kidney injury in mice by modulating inflammation and apoptosis.

Septic acute kidney injury (AKI) is considered as a severe and frequent complication that occurs during sepsis. Mounting evidence has confirmed the pivotal pathogenetic roles of microRNA (miRNA or miR) in sepsis­induced AKI; however, the role of miRNAs and their underlying mechanisms in sepsis­induced AKI have not been entirely understood. The present study aimed to elucidate the functions of special miRNAs during sepsis­induced AKI and its underlying mechanism. First, a number of differently expressed miRNAs was identified based on the microarray dataset GSE172044. Subsequently, lipopolysaccharide (LPS) was used to induce AKI in mice, and the role of miR­17­5p on AKI was clarified. Finally, the related molecular mechanisms were further examined by western blotting and immunohistochemical analysis. MiR­17­5p was found to be continuously decreased and reached the bottom at h 24 after AKI in mice. Functionally, injection of agomiR­17­5p could observably improve renal injury and survival rate, as well as inhibit inflammatory cytokine production and renal cell apoptosis in mice after AKI. On the contrary, injection of antagomiR­17­5p aggravated LPS­induced renal injury, inflammation and apoptosis in mice after AKI. Moreover, transforming growth factor ß receptor 2 (TGFßR2) was identified as a direct target of miR­17­5p, and its downstream phosphorylated Smad3 was also suppressed by miR­17­5p upregulation. Taken together, these results demonstrated that miR­17­5p overexpression may exhibit a beneficial effect by attenuating LPS­induced inflammation and apoptosis via regulating the TGFßR2/TGF­ß/Smad3 signaling pathway, indicating that miR­17­5p could act as a potential target for sepsis treatment.

Intestinal Piezo1 aggravates intestinal barrier dysfunction during sepsis by mediating Ca2+ influx.

INTRODUCTION: Intestinal barrier dysfunction is a pivotal factor in sepsis progression. The mechanosensitive ion channel Piezo1 is associated with barrier function; however, its role in sepsis-induced intestinal barrier dysfunction remains poorly understood. METHODS: The application of cecal ligation and puncture (CLP) modeling was performed on both mice of the wild-type (WT) variety and those with Villin-Piezo1flox/flox genetic makeup to assess the barrier function using in vivo FITC-dextran permeability measurements and immunofluorescence microscopy analysis of tight junctions (TJs) and apoptosis levels. In vitro, Caco-2 monolayers were subjected to TNF-α incubation. Moreover, to modulate Piezo1 activation, GsMTx4 was applied to inhibit Piezo1 activation. The barrier function, intracellular calcium levels, and mitochondrial function were monitored using calcium imaging and immunofluorescence techniques. RESULTS: In the intestinal tissues of CLP-induced septic mice, Piezo1 protein levels were notably elevated compared with those in normal mice. Piezo1 has been implicated in the sepsis-mediated disruption of TJs, apoptosis of intestinal epithelial cells, elevated intestinal mucosal permeability, and systemic inflammation in WT mice, whereas these effects were absent in Villin-Piezo1flox/flox CLP mice. In Caco-2 cells, TNF-α prompted calcium influx, an effect reversed by GsMTx4 treatment. Elevated calcium concentrations are correlated with increased accumulation of reactive oxygen species, diminished mitochondrial membrane potential, and TJ disruption. CONCLUSIONS: Thus, Piezo1 is a potential contributor to sepsis-induced intestinal barrier dysfunction, influencing apoptosis and TJ modification through calcium influx-mediated mitochondrial dysfunction.

Non-volatile 2 × 2 optical switch using multimode interference in an Sb2Se3-loaded waveguide.

We propose a non-volatile 2 × 2 photonic switch based on multimode interference in an Sb2Se3-loaded waveguide. The different modal symmetries of the TE0 and TE1 modes supported in the multimode region change their propagation constants distinctly upon the Sb2Se3 phase transition. Through careful optical design and FDTD optimization of the multimode waveguide dimensions, efficient switching is achieved despite the modest index contrast of Sb2Se3 relative to Ge2Sb2Te5. The fabricated optical switch demonstrates favorable characteristics, including low insertion loss of ∼1 dB, a compact length of ∼27 µm, and small cross talk below -15 dB across a 35 nm bandwidth. Such non-volatile and broadband components will be critical for future high-density programmable photonic-integrated circuits for optical communications and signal processing.

Microbiome convergence enables siderophore-secreting-rhizobacteria to improve iron nutrition and yield of peanut intercropped with maize.

Intercropping has the potential to improve plant nutrition as well as crop yield. However, the exact mechanism promoting improved nutrient acquisition and the role the rhizosphere microbiome may play in this process remains poorly understood. Here, we use a peanut/maize intercropping system to investigate the role of root-associated microbiota in iron nutrition in these crops, combining microbiome profiling, strain and substance isolation and functional validation. We find that intercropping increases iron nutrition in peanut but not in maize plants and that the microbiota composition changes and converges between the two plants tested in intercropping experiments. We identify a Pseudomonas secreted siderophore, pyoverdine, that improves iron nutrition in glasshouse and field experiments. Our results suggest that the presence of siderophore-secreting Pseudomonas in peanut and maize intercropped plays an important role in iron nutrition. These findings could be used to envision future intercropping practices aiming to improve plant nutrition.

The efficacy of sorafenib against hepatocellular carcinoma is enhanced by 5-aza-mediated inhibition of ID1 promoter methylation.

Sorafenib resistance greatly restricts its clinical application in patients with hepatocellular carcinoma (HCC). Numerous studies have reported that ID1 exerts a crucial effect in cancer initiation and development. Our previous research revealed an inhibitory role of ID1 in sorafenib resistance. However, the upstream regulatory mechanism of ID1 expression is unclear. Here, we discovered that ID1 expression is negatively correlated with promoter methylation, which is regulated by DNMT3B. Knockdown of DNMT3B significantly inhibited ID1 methylation status and resulted in an increase of ID1 expression. The demethylating agent 5-aza-2'-deoxycytidine (5-aza) remarkably upregulated ID1 expression. The combination of 5-aza with sorafenib showed a synergistic effect on the inhibition of cell viability.

Safe physical interaction with cobots: a multi-modal fusion approach for health monitoring.

Health monitoring is a critical aspect of personalized healthcare, enabling early detection, and intervention for various medical conditions. The emergence of cloud-based robot-assisted systems has opened new possibilities for efficient and remote health monitoring. In this paper, we present a Transformer-based Multi-modal Fusion approach for health monitoring, focusing on the effects of cognitive workload, assessment of cognitive workload in human-machine collaboration, and acceptability in human-machine interactions. Additionally, we investigate biomechanical strain measurement and evaluation, utilizing wearable devices to assess biomechanical risks in working environments. Furthermore, we study muscle fatigue assessment during collaborative tasks and propose methods for improving safe physical interaction with cobots. Our approach integrates multi-modal data, including visual, audio, and sensor- based inputs, enabling a holistic assessment of an individual's health status. The core of our method lies in leveraging the powerful Transformer model, known for its ability to capture complex relationships in sequential data. Through effective fusion and representation learning, our approach extracts meaningful features for accurate health monitoring. Experimental results on diverse datasets demonstrate the superiority of our Transformer-based multi- modal fusion approach, outperforming existing methods in capturing intricate patterns and predicting health conditions. The significance of our research lies in revolutionizing remote health monitoring, providing more accurate, and personalized healthcare services.

PD-L1 expression-related PI3K pathway correlates with immunotherapy efficacy in gastric cancer.

Background: The programed death ligand-1 combined positive score (PD-L1 CPS), the only FDA-approved biomarker for immune checkpoint inhibitor therapy in gastric cancer (GC) patients, is an important but imperfect predictive biomarker. The molecular characteristics of tumors that influence the PD-L1 CPS are largely unknown and would be helpful for screening patients who would benefit from immunotherapy. Methods: PD-L1 immunohistochemistry (IHC) and targeted next-generation sequencing techniques were used to compare genomic alterations in 492 GC patients in two groups (PD-L1 CPS ⩾ 1, positive; CPS < 1, negative). Screened PD-L1 expression-related factors were analyzed for immunotherapy efficacy in three distinct GC cohorts from public databases. Results: Positive PD-L1 expression occurred in 40% of GC patients and was associated with a higher proportion of phosphatidylinositol 3-kinase (PI3K), SWItch/Sucrose NonFermentable (SWI/SNF), lysine demethylase (KDM), and DNA (cytosine-5)-methyltransferase (DNMT) (all p < 0.01), pathway alterations. Compared to wild-type GC patients, those with PI3K pathway alterations had a higher response rate (p = 0.002) and durable clinical benefit rate with immunotherapy (p = 0.023, p = 0.038) as well as longer progression-free survival (p = 0.084, p = 0.0076) and overall survival (p = 0.2, p = 0.037) with immunotherapy. Conclusion: This study revealed PD-L1 expression-related factors in the tumor genome in a GC cohort. Alterations in the PI3K pathway associated with PD-L1 positivity were shown to be associated with better immunotherapy efficacy in three distinct GC cohorts from public databases. Our results provide a potential avenue for patient selection and rational immune combination development for GC patients.

Integration of natural and deep artificial cognitive models in medical images: BERT-based NER and relation extraction for electronic medical records.

Introduction: Medical images and signals are important data sources in the medical field, and they contain key information such as patients' physiology, pathology, and genetics. However, due to the complexity and diversity of medical images and signals, resulting in difficulties in medical knowledge acquisition and decision support. Methods: In order to solve this problem, this paper proposes an end-to-end framework based on BERT for NER and RE tasks in electronic medical records. Our framework first integrates NER and RE tasks into a unified model, adopting an end-to-end processing manner, which removes the limitation and error propagation of multiple independent steps in traditional methods. Second, by pre-training and fine-tuning the BERT model on large-scale electronic medical record data, we enable the model to obtain rich semantic representation capabilities that adapt to the needs of medical fields and tasks. Finally, through multi-task learning, we enable the model to make full use of the correlation and complementarity between NER and RE tasks, and improve the generalization ability and effect of the model on different data sets. Results and discussion: We conduct experimental evaluation on four electronic medical record datasets, and the model significantly out performs other methods on different datasets in the NER task. In the RE task, the EMLB model also achieved advantages on different data sets, especially in the multi-task learning mode, its performance has been significantly improved, and the ETE and MTL modules performed well in terms of comprehensive precision and recall. Our research provides an innovative solution for medical image and signal data.

Experimental Study on the Mechanical Properties and Influencing Factors of Glass Fiber-Reinforced Permeable Concrete.

In order to improve the mechanical properties and deformation characteristics of permeable concrete, glass fiber was added to this type of concrete. Based on an unconfined compressive strength test, non-contact full-field strain measurement system, and scanning electron microscopy test, the effects of aggregate particle composition, shaking time, fly ash content, fiber length, and fiber content on the strength and permeability of permeable concrete were studied. The results show that the strength and water permeability of permeable concrete are negatively correlated with an increase in shaking time. When the aggregate particle size is 5-10 mm, the permeable concrete has both good strength and permeability. Proper incorporation of fly ash improves the compactness inside the structure. The influence of different lengths of glass fiber on the strength of permeable concrete first increases and then decreases, and the permeable property decreases. With the same fiber length, the strength increases first and then decreases with an increase in the content, while the porosity and water permeability coefficient decrease. Under the test conditions, when the length of glass fiber is 6 mm, and the dosage is 2 kg/m3, the strength performance of permeable concrete is the best, and the permeability effect is good at the same time.

Insights into the Electronic Structure Effect of SnMnOx Nanorod Catalysts for Low-Temperature Catalytic Combustion of o-Dichlorobenzene.

For the catalytic combustion reaction of chlorinated volatile organic compounds (CVOCs), the redox properties and acid sites of the catalyst surface are key factors in determining the activity, selectivity, and chlorine-resistance stability. Herein, a series of SnMnOx catalysts for the catalytic combustion of CVOCs were prepared by the changing of Sn-doping way to regulate the electron valance state of Mn element, including reflux (R-SnMnOx ), co-precipitation (C-SnMnOx ) and impregnation (I-SnMnOx ). It was discovered that the R-SnMnOx catalyst had better activity and chlorine resistance than the R-MnOx , C-SnMnOx and I-SnMnOx catalyst, and we discovered that the doping ways of Sn in MnOx catalyst could regulate greatly the surface acidity, active oxygen species, the chemical state of Mnn+ species, and redox ability. Especially, the R-SnMnOx catalysts exhibit excellent water resistance, and the reasons were related to the strong interaction of Snn+ and Mnn+ , which could promote obviously the dispersion of active Mn species, form a large number of acid sites, provide the abundant lattice oxygen species, and own the excellent redox ability, which accelerate the rate of charge transfer between Snn+ and Mnn+ (Sn4+ +Mn2+ →Sn2+ +Mn4+ ) to produce the abundant active species and accelerate the rapid conversion of benzene and intermediates conversion.

MBGA-Net: A multi-branch graph adaptive network for individualized motor imagery EEG classification.

BACKGROUND AND OBJECTIVE: The development of deep learning has led to significant improvements in the decoding accuracy of Motor Imagery (MI) EEG signal classification. However, current models are inadequate in ensuring high levels of classification accuracy for an individual. Since MI EEG data is primarily used in medical rehabilitation and intelligent control, it is crucial to ensure that each individual's EEG signal is recognized with precision. METHODS: We propose a multi-branch graph adaptive network (MBGA-Net), which matches each individual EEG signal with a suitable time-frequency domain processing method based on spatio-temporal domain features. We then feed the signal into the relevant model branch using an adaptive technique. Through an enhanced attention mechanism and deep convolutional method with residual connectivity, each model branch more effectively harvests the features of the related format data. RESULTS: We validate the proposed model using the BCI Competition IV dataset 2a and dataset 2b. On dataset 2a, the average accuracy and kappa values are 87.49% and 0.83, respectively. The standard deviation of individual kappa values is only 0.08. For dataset 2b, the average classification accuracies obtained by feeding the data into the three branches of MBGA-Net are 85.71%, 85.83%, and 86.99%, respectively. CONCLUSIONS: The experimental results demonstrate that MBGA-Net could effectively perform the classification task of motor imagery EEG signals, and it exhibits strong generalization performance. The proposed adaptive matching technique enhances the classification accuracy of each individual, which is beneficial for the practical application of EEG classification.

Role of magnetic resonance imaging in the diagnosis of placenta accreta.

INTRODUCTION: To analyze the value of magnetic resonance imaging (MRI) in suspicious cases for prenatal detection of placenta accreta (PA). MATERIALS AND METHODS: A total of 50 placental MRI exams performed on a 1.5T scanner were retrospectively reviewed by two radiologists in consensus.HASTE(half-Fourier acquisition single-shot turbo spin echo)and True-FISP (true fast imaging with steady-state precession) sequences were acquired. Findings from MRI were compared with the final diagnosis, which was determined by clinical findings at delivery and pathological examination of specimens. RESULTS: Of 50 pregnant women in the analysis, 33 required cesarean hysterectomy, and 17 underwent cesarean delivery.MRI signs such as myometrial thinning, loss of T2 hypointense interface(loss of retroplacental clear space on US), heterogenous intraplacental sign, and intraplacental T2 dark bands were more likely to be seen in this group. In this group, the cases that were finally clinically and pathologically confirmed were 12, 16, and 22 cases of placenta accreta vera, placenta increta, and placenta percreta respectively. CONCLUSION: MRI is particularly useful in cases where US is inconclusive and to assess the extent to which the placenta penetrates the uterine serosa and invades outward into surrounding tissues.MRI has become a routine examination for patients with suspected PA in clinical practice.