Multiband task related components enhance rapid cognition decoding for both small and similar objects

The cortically-coupled target recognition system based on rapid serial visual presentation (RSVP) has a wide range of applications in brain computer interface (BCI) fields such as medical and military. However, in the complex natural environment backgrounds, the identification of event-related potentials (ERP) of both small and similar objects that are quickly presented is a research challenge. Therefore, we designed corresponding experimental paradigms and proposed a multi-band task related components matching (MTRCM) method to improve the rapid cognitive decoding of both small and similar objects. We compared the areas under the receiver operating characteristic curve (AUC) between MTRCM and other 9 methods under different numbers of training sample using RSVP-ERP data from 50 subjects. The results showed that MTRCM maintained an overall superiority and achieved the highest average AUC (0.6562 ± 0.0091). We also optimized the frequency band and the time parameters of the method. The verification on public data sets further showed the necessity of designing MTRCM method. The MTRCM method provides a new approach for neural decoding of both small and similar RSVP objects, which is conducive to promote the further development of RSVP-BCI.

Assessment of rTMS treatment effects for methamphetamine use disorder based on EEG microstates

Microstates have been proposed as topographical maps representing large-scale resting-state networks and have recently been suggested as markers for methamphetamine use disorder (MUD). However, it is unknown whether and how they change after repetitive transcranial magnetic stimulation (rTMS) intervention. This study included a comprehensive subject population to investigate the effect of rTMS on MUD microstates. 34 patients with MUD underwent a 4-week randomized, double-blind rTMS intervention (active=17, sham=17). Two resting-state EEG recordings and VAS evaluations were conducted before and after the intervention period. Additionally, 17 healthy individuals were included as baseline controls. The modified k-means clustering method was used to calculate four microstates (MS-A∼MS-D) of EEG, and the FC network was also analyzed. The differences in microstate indicators between groups and within groups were compared. The durations of MS-A and MS-B microstates in patients with MUD were significantly lower than that in HC but showed significant improvements after rTMS intervention. Changes in microstate indicators were found to be significantly correlated with changes in craving level. Furthermore, selective modulation of the resting-state network by rTMS was observed in the FC network. The findings indicate that changes in microstates in patients with MUD are associated with craving level improvement following rTMS, suggesting they may serve as valuable evaluation markers.

An SSVEP-based BCI with 112 targets using frequency spatial multiplexing

Objective.Brain-computer interface (BCI) systems with large directly accessible instruction sets are one of the difficulties in BCI research. Research to achieve high target resolution (⩾100) has not yet entered a rapid development stage, which contradicts the application requirements. Steady-state visual evoked potential (SSVEP) based BCIs have an advantage in terms of the number of targets, but the competitive mechanism between the target stimulus and its neighboring stimuli is a key challenge that prevents the target resolution from being improved significantly.Approach.In this paper, we reverse the competitive mechanism and propose a frequency spatial multiplexing method to produce more targets with limited frequencies. In the proposed paradigm, we replicated each flicker stimulus as a 2 × 2 matrix and arrange the matrices of all frequencies in a tiled fashion to form the interaction interface. With different arrangements, we designed and tested three example paradigms with different layouts. Further we designed a graph neural network that distinguishes between targets of the same frequency by recognizing the different electroencephalography (EEG) response distribution patterns evoked by each target and its neighboring targets.Main results.Extensive experiment studies employing eleven subjects have been performed to verify the validity of the proposed method. The average classification accuracies in the offline validation experiments for the three paradigms are 89.16%, 91.38%, and 87.90%, with information transfer rates (ITR) of 51.66, 53.96, and 50.55 bits/min, respectively.Significance.This study utilized the positional relationship between stimuli and did not circumvent the competing response problem. Therefore, other state-of-the-art methods focusing on enhancing the efficiency of SSVEP detection can be used as a basis for the present method to achieve very promising improvements.

[Metagenomic next-generation sequencing-based retrospective investigation of the drug resistance sites of Mycoplasma pneumoniae in children]

Objective: To analyze the drug-resistant gene loci of Mycoplasma pneumoniae (MP) using metagenomic next-generation sequencing (mNGS). Methods: From November 2022 to October 2023, 697 clinical samples (including sputum, alveolar lavage fluid and blood) of 686 children with Mycoplasma pneumoniae positive detected by mNGS were retrospectively analyzed. Samples were divided into intensive care unit (ICU) group and non-ICU group, Chi-square test was used to compare groups, and Mann-Kendall trend test was used to analyze the change trend of the detection rate of drug resistance gene loci over time. Results: Of the 697 samples, 164 were from the ICU group and 533 were from the non-ICU group. The detection rate of Mycoplasma pneumoniae resistance gene was 44.3% (309/697), and all detected drug-resistant gene loci of MP were A2063G. The detection rate of Mycoplasma pneumoniae in ICU group was 50.0% (82/164), and the detection rates of Mycoplasma pneumoniae resistance gene loci in sputum, alveolus lavage fluid and blood samples were 75.0% (18/24) and 48.4% (62/128), respectively. The detection rate in sputum was higher than alveolus lavage fluid samples (χ2=5.72,P=0.017). The detection rate of Mycoplasma pneumoniae in non-ICU group was 42.6% (227/533), the detection rate of Mycoplasma pneumoniae resistance gene loci in sputum and alveolar lavage fluid was 40.0% (16/40), 44.3% (201/454), and no detection rate in blood samples (0/12). There was no significant difference in the detection rate of alveolar lavage fluid and sputum (χ2=0.27, P=0.602). From November 2022 to October 2023, the detection rate of submitted samples showed an increasing trend month by month (overall: Z=3.99, ICU inspection group: Z=2.93, non-ICU group: Z=3.01, all P<0.01). Among the bacteria commonly detected with Mycoplasma pneumoniae, Streptococcus pneumoniae accounted for the highest proportion, the detection rate was 15.5% (108/697), and Epstein-Barr virus accounted for the highest proportion of 17.6% (123/697). Conclusions: From November 2022 to October 2023, the detection rate of Mycoplasma pneumoniae drug resistance gene loci showed an increasing trend. The detection rate of drug resistance gene loci in sputum samples of ICU group was higher than alveolus lavage fluid. No new drug resistance site were detected.

Picosecond Spin Current Generation from Vicinal Metal-Antiferromagnetic Insulator Interfaces

We report the picosecond spin current generation from the interface between a heavy metal and a vicinal antiferromagnet insulator Cr_{2}O_{3} by laser pulses at room temperature and zero magnetic field. It is converted into a detectable terahertz emission in the heavy metal via the inverse spin Hall effect. The vicinal interfaces are apparently the source of the picosecond spin current, as evidenced by the proportional terahertz signals to the vicinal angle. We attribute the origin of the spin current to the transient magnetic moment generated by an interfacial nonlinear magnetic-dipole difference-frequency generation. We propose a model based on the in-plane inversion symmetry breaking to quantitatively explain the terahertz intensity with respect to the angles of the laser polarization and the film azimuth. Our work opens new opportunities in antiferromagnetic and ultrafast spintronics by considering symmetry breaking.

[Effect of salvia miltiorrhiza combined with roxadustat on wound healing of full-thickness skin defects in diabetic rats and its mechanism]

Objective: To explore the effect of salvia miltiorrhiza combined with roxadustat on wound healing of full-thickness skin defects in diabetic rats and its mechanism. Methods: This study was an experimental study. Twenty male 8-week-old Sprague-Dawley rats were used to successfully establish diabetic model, then full-thickness skin defect wounds on their backs were made. The rats were divided into normal saline group, roxadustat alone group, salvia miltiorrhiza alone group, and roxadustat+salvia miltiorrhiza group according to the random number table, with 5 rats in each group. Immediately after injury, the rats in normal saline group were given 5 mL normal saline by gavage, the rats in roxadustat alone group were given 1.5 mg/mL roxadustat suspension by gavage at 25 mg/kg, the rats in salvia miltiorrhiza alone group were given 18 mg/mL salvia miltiorrhiza suspension by gavage at 300 mg/kg, and the rats in roxadustat+salvia miltiorrhiza group were given 19.5 mg/mL roxadustat and salvia miltiorrhiza suspension at roxadustat 25 mg/kg and salvia miltiorrhiza 300 mg/kg. All were administered once a day for 2 weeks. The wounds at 0 (immediately), 4, 8, and 12 d after injury were observed, and the wound healing rates at 4, 8, and 12 d after injury were calculated (n=5). At 14 d after injury, abdominal aortic blood was collected, and hemoglobin, red cell count, and white blood cell count were detected (n=5). The wound tissue was collected for hematoxylin-eosin staining to observe inflammatory infiltration, skin tissue structure, and neovascularization, for Masson staining to observe the proportion of collagen fiber (n=3), for Western blotting to detect the protein expression levels of vascular endothelial growth factor (VEGF), CD31, interleukin 6 (IL-6), tumor necrosis factor α (TNF-α), and IL-1β (n=3), and for immunohistochemical staining to determine the protein expression levels of epidermal growth factor receptor (EGFR), hypoxia-inducible factor 1α (HIF-1α), and proliferating cell nuclear antigen (PCNA), with sample number of 3. Results: From 0 to 12 d after injury, the wound areas of rats in 4 groups were gradually decreased. At 4 d after injury, the wound healing rates of rats in salvia miltiorrhiza alone group and roxadustat+salvia miltiorrhiza group were significantly higher than those in normal saline group and roxadustat alone group (P<0.05). At 8 d after injury, the wound healing rates of rats in roxadustat alone group and salvia miltiorrhiza alone group were significantly higher than the rate in normal saline group (P<0.05), and the wound healing rate of rats in roxadustat+salvia miltiorrhiza group was significantly higher than the rates in the other 3 groups (with P values all <0.05). At 12 d after injury, the wound healing rates of rats in roxadustat alone group, salvia miltiorrhiza alone group, and roxadustat+salvia miltiorrhiza group were significantly higher than the rate in normal saline group (P<0.05). At 14 d after injury, there were no statistically significant differences in the hemoglobin or red blood cell count of rats in 4 groups (P<0.05). The white blood cell count of rats in roxadustat alone group, salvia miltiorrhiza alone group, and roxadustat+salvia miltiorrhiza group were respectively (24.3±1.2)×109/L, (26.3±2.4)×109/L, and (15.0±0.7)×109/L, which were significantly lower than (33.8±2.7)×109/L in normal saline group (P<0.05); the white blood cell count of rats in roxadustat+salvia miltiorrhiza group was significantly lower than that in roxadustat alone group and salvia miltiorrhiza alone group (with P values both <0.05). At 14 d after injury, a large number of inflammatory cell infiltration, disordered skin tissue structure, and few new blood vessels were observed in the wounds of rats in normal saline group; while a small amount of inflammatory cell infiltration, tight skin tissue structure, and rich neovascularization were observed in the wounds of rats in the other 3 groups. There were no statistically significant differences in the proportion of collagen fiber of wounds in rats among the 4 groups (P>0.05). At 14 d after injury, the protein expression levels of VEGF and CD31 in the wound tissue of rats in roxadustat alone group, salvia miltiorrhiza alone group, and roxadustat+salvia miltiorrhiza group were significantly higher than those in normal saline group (P<0.05), the protein expression level of CD31 in the wound tissue of rats in roxadustat+salvia miltiorrhiza group was significantly higher than the levels in roxadustat alone group and salvia miltiorrhiza alone group (with P values both <0.05). At 14 d after injury, the protein expression levels of IL-6, TNF-α, and IL-1β in the wound tissue of rats in roxadustat alone group, salvia miltiorrhiza alone group, and roxadustat+salvia miltiorrhiza group were significantly lower than those in normal saline group (P<0.05); the protein expression levels of IL-6 and IL-1β in the wound tissue of rats in roxadustat+salvia miltiorrhiza group were significantly lower than those in roxadustat alone group and salvia miltiorrhiza alone group (P<0.05); the protein expression level of TNF-α in the wound tissue of rats in roxadustat+salvia miltiorrhiza group was significantly lower than that in salvia miltiorrhiza alone group (P<0.05). At 14 d after injury, the protein expression level of EGFR in the wound tissue of rats in roxadustat+salvia miltiorrhiza group was significantly higher than the levels in the other 3 groups (with P values all <0.05); the protein expression levels of HIF-1α in the wound tissue of rats in roxadustat alone group and roxadustat+salvia miltiorrhiza group were significantly higher than the level in normal saline group (P<0.05), and the protein expression level of HIF-1α in the wound tissue of rats in roxadustat+salvia miltiorrhiza group was significantly higher than that in salvia miltiorrhiza alone group (P<0.05); there were no statistically significant differences in the protein expression level of PCNA in the wound tissue of rats in 4 groups (P>0.05). Conclusions: Roxadustat combined with salvia miltiorrhiza can promote the wound healing of full-thickness skin defects in diabetic rats by promoting blood vessel regeneration and reducing inflammatory response.

Rehabilitation with brain-computer interface and upper limb motor function in ischemic stroke: A randomized controlled trial

BACKGROUND

Upper limb motor dysfunction is a major problem in the rehabilitation of patients with stroke. Brain-computer interface (BCI) is a kind of communication system that converts the "ideas" in the brain into instructions and has been used in stroke rehabilitation. This study aimed to investigate the efficacy and safety of BCI in rehabilitation training on upper limb motor function among patients with ischemic stroke.

METHODS

This was an investigator-initiated, multicenter, randomized, open-label, blank-controlled clinical trial with blinded outcome assessment conducted at 17 centers in China. Patients were assigned in a 1:1 ratio to the BCI group or the control group based on traditional rehabilitation training. The primary efficacy outcome is the difference in improvement of the Fugl-Meyer Assessment upper extremity (FMA-UE) score between two groups at month 1 after randomization. The safety outcomes were any adverse events within 3 months.

FINDINGS

A total of 296 patients with ischemic stroke were enrolled and randomly allocated to the BCI group (n = 150) and the control group (n = 146). The primary efficacy outcomes of FMA-UE score change from baseline to 1 month were 13.17 (95% confidence interval [CI], 11.56-14.79) in the BCI group and 9.83 (95% CI, 8.19-11.47) in the control group (mean difference between groups was 3.35; 95% CI, 1.05-5.65; p = 0.0045). Adverse events occurred in 33 patients (22.00%) in the BCI group and in 31 patients (21.23%) in the control group.

CONCLUSIONS

BCI rehabilitation training can further improve upper limb motor function based on traditional rehabilitation training in patients with ischemic stroke. This study was registered at ClinicalTrials.gov: NCT04387474.

FUNDING

This work was supported by the National Key R&D Program of China (2018YFC1312903), the National Key Research and Development Program of China (2022YFC3600600), the Training Fund for Open Projects at Clinical Institutes and Departments of Capital Medical University (CCMU2022ZKYXZ009), the Beijing Natural Science Foundation Haidian original innovation joint fund (L222123), the Fund for Young Talents of Beijing Medical Management Center (QML20230505), and the high-level public health talents (xuekegugan-02-47).

[Association between unhealthy lifestyles and diabetic dyslipidemia in occupational population and network analysis]

Objective: To understand the influence of unhealthy lifestyle on diabetic dyslipidemia and the key influencing factors in occupational population and provided scientific evidence for the prevention of diabetic dyslipidemia. Methods: Based on baseline data and follow-up data of Southwest Occupational Population Cohort from China Railway Chengdu Group Co., Ltd. during 2021. Diabetic dyslipidemia was defined as diabetes plus one or more forms of dyslipidemia, and unhealthy lifestyle factors included smoking, alcohol consumption, unhealthy dietary patterns, low physical activity, and abnormal BMI. Multivariate logistic regression model was used to analyze the relationship between unhealthy lifestyle scores and diabetic dyslipidemia, network analysis was used to find and explore the key lifestyles influencing glycolipid metabolism. Results: A total of 25 631 subjects were included. People with unhealthy lifestyle score 2 and 3 were 1.93 (95%CI: 1.31-2.86) times and 2.37 (95%CI: 1.60-3.50) times more likely to have diabetes with ≥1 forms of dyslipidemia than those with scores of 0; People with unhealthy lifestyle score 1, 2 and 3 were 1.98 (95%CI: 1.08-3.61) times, 2.87 (95%CI: 1.60-5.14) times and 3.95 (95%CI: 2.22-7.06) times more likely to have diabetes with ≥2 forms of dyslipidemia than those with score 0. Network analysis found that abnormal BMI and HDL-C were the "bridge nodes" that link unhealthy lifestyles with diabetic dyslipidemia. Conclusion: The higher the score of unhealthy lifestyle, the higher the risk for diabetic dyslipidemia, abnormal BMI and HDL-C are key factors influencing the association between unhealthy lifestyle and diabetic dyslipidemia.

[Association between unhealthy lifestyles and hyperuricemia in occupational population and modification effect of hypertension and dyslipidemia]

Objective: To understand the relationship between unhealthy lifestyle and hyperuricemia, as well as the modification effects of hypertension and dyslipidemia in occupational population and provide a theoretical basis for the prevention of hyperuricemia. Methods: A cross-sectional survey design was adopted, based on baseline data from the Southwest Occupational Population Cohort from China Railway Chengdu Group Co., Ltd., which included the population in 28 prefectures from Sichuan Province and Guizhou Province, and 33 districts (counties) from Chongqing Municipality between October and December 2021. This study collected the information about the demographics characteristics, lifestyles, and prevalence of chronic non-communicable diseases of the study subjects through questionnaire, physical measurement and laboratory biochemical test. The unhealthy lifestyle score was scored based on smoking, alcohol consumption, dietary patterns, physical activity, and low weight or overweight, with higher scores being associated with more unhealthy lifestyles. The multivariate logistic regression model was used to analyze the relationship between unhealthy lifestyle score, smoking, alcohol consumption, other factors and hyperuricemia, and the stratified analysis was used to explore the modification effect of hypertension and other diseases on the relationship between unhealthy lifestyle and hyperuricemia. Results: A total of 11 748 participants were included in this study, the prevalence of hyperuricemia was 34.4%. Multivariate logistic regression model showed that current/previous smoking, current/previous alcohol consumption and BMI abnormality were risk factors for hyperuricemia, and the unhealthy lifestyle score showed a "cumulative" effect on the risk for hyperuricemia, with higher score increasing the risk of hyperuricemia, and the OR increased from 1.64 (95%CI: 1.34-2.00) to 2.89 (95%CI: 2.39-3.50). Stratified analysis showed that unhealthy lifestyles had a greater impact on the risk for hyperuricemia in people with hypertension and dyslipidemia. Conclusions: The coexistence of multiple unhealthy lifestyles might increase the risk of hyperuricemia, and this effect was stronger in participants with hypertension and dyslipidemia. Timely correction of unhealthy lifestyles, and control of hypertension and dyslipidemia might reduce the risk for hyperuricemia.

[Mediating effects of body mass index and lipid levels on the association between alcohol consumption and hypertension in occupational population]

Objective: To investigate the association between alcohol consumption and hypertension and SBP, DBP and the mediating effects of body mass index (BMI) and lipid level in occupational population, and provide reference for the intervention and prevention of hypertension. Methods: Based on the data of Southwest Occupational Population Cohort from China Railway Chengdu Group Co., Ltd., the information about the demographic characteristics, behavior and lifestyle, blood pressure and lipids level of the participants were collected through questionnaire survey, physical examination and blood biochemical test. Logistic/linear regression was used to analyze the association between alcohol consumption and hypertension, SBP and DBP. The individual and joint mediating effects of BMI, HDL-C, LDL-C, TG, and TC were explored through causal mediating analysis. A network analysis was used to explore the correlation between alcohol consumption, BMI and lipid levels, and hypertension. Results: A total of 22 887 participants were included, in whom 1 825 had newly detected hypertension. Logistic regression analysis found that current/former drinkers had a 33% increase of risk for hypertension compared with never-drinkers (OR=1.33, 95%CI:1.19-1.48). Similarly, alcohol consumption could increase SBP (β=1.05, 95%CI:0.69-1.40) and DBP (β=1.10, 95%CI:0.83-1.38). Overall, BMI and lipid levels could mediate the associations between alcohol consumption and hypertension, SBP and DBP by 21.91%, 28.40% and 22.64%, respectively. BMI and TG were the main mediators, and they were also the two nodes with the highest edge weight and bridge strength centrality in the network of alcohol consumption, BMI, lipid levels and hypertension. Conclusions: Alcohol consumption was associated with increased risk for hypertension, and BMI and TG were important mediators and key nodes in the network. It is suggested that paying attention to the alcohol consumption, BMI and TG might help prevent hypertension in occupational population.

[Association between work environment noise perception and cardiovascular diseases, depressive symptoms, and their comorbidity in occupational population]

Objective: To explore the association between occupational noise perception and cardiovascular disease (CVD), depression symptoms, as well as their comorbidity in occupational population and provide evidence for the prevention and control of physical and mental illnesses. Methods: A cross-sectional survey design was adopted, based on baseline data in population in 28 prefectures in Sichuan Province and Guizhou Province, and 33 districts (counties) in Chongqing municipality from Southwest Occupational Population Cohort from China Railway Chengdu Group Co., Ltd. during October to December 2021. A questionnaire survey was conducted to collect information about noise perception, depressive symptoms, and the history of CVD. Latent profile analysis model was used to determine identify noise perception type, and multinomial logistic regression analysis was conducted to explore the relationship between different occupational noise perception types and CVD, depression symptoms and their comorbidity. Results: A total of 30 509 participants were included, the mean age was (36.6±10.5) years, and men accounted for 82.0%. The direct perception of occupational noise, psychological effects and hearing/sleep impact of occupational noise increased the risk for CVD, depressive symptoms, and their comorbidity. By using latent profile analysis, occupational noise perception was classified into four levels: low, medium, high, and very high. As the level of noise perception increased, the association with CVD, depressive symptoms, and their comorbidity increased. In fact, very high level occupational noise perception were found to increase the risk for CVD, depressive symptoms, and their comorbidity by 2.14 (95%CI: 1.73-2.65) times, 8.80 (95%CI: 7.91-9.78) times, and 17.02 (95%CI: 12.78-22.66) times respectively compared with low-level occupational noise perception. Conclusions: Different types of occupational noise perception are associated with CVD and depression symptom, especially in the form of CVD complicated with depression symptom. Furthermore, the intensity of occupational noise in the work environment should be reduced to lower the risk for physical and mental health.

Achievement of Target Gain Larger than Unity in an Inertial Fusion Experiment

On December 5, 2022, an indirect drive fusion implosion on the National Ignition Facility (NIF) achieved a target gain G_{target} of 1.5. This is the first laboratory demonstration of exceeding "scientific breakeven" (or G_{target}>1) where 2.05 MJ of 351 nm laser light produced 3.1 MJ of total fusion yield, a result which significantly exceeds the Lawson criterion for fusion ignition as reported in a previous NIF implosion [H. Abu-Shawareb et al. (Indirect Drive ICF Collaboration), Phys. Rev. Lett. 129, 075001 (2022)PRLTAO0031-900710.1103/PhysRevLett.129.075001]. This achievement is the culmination of more than five decades of research and gives proof that laboratory fusion, based on fundamental physics principles, is possible. This Letter reports on the target, laser, design, and experimental advancements that led to this result.

Development and validation of a nomogram and risk stratification system to predict overall survival after surgical repair for pediatric patients with medulloblastoma based on easily accessible variables

OBJECTIVE

This study aimed to develop and validate a nomogram and risk stratification system for the overall survival of pediatric patients with medulloblastoma after surgical repair.

PATIENTS AND METHODS

In this multicenter, retrospective study, consecutive patients who underwent surgery for medulloblastoma at Shanghai Children's Medical Center and the First Affiliated Hospital of Fujian Medical University from 2010 to 2022 formed the training and external validation datasets, respectively. Univariable and multivariable Cox regression analyses were performed to identify variables associated with mortality in the training dataset. A nomogram prediction model was developed based on independent variables in the multivariable Cox regression analysis to predict the 1-, 3-, and 5-year overall survival. The area under receiver operating characteristic curve (AUC) and calibration curve were used to evaluate the discrimination and calibration of the nomogram. A risk stratification system based on the median risk score was also established to divide patients into two risk groups.

RESULTS

In the training dataset, Cox regression analyses identified tumor size, brainstem involvement and chemotherapy as independent predictors for overall survival. The AUC of the nomogram was 0.75 at 1 year, 0. 75 at 3 years, 0.77 at 5 years in the training dataset, 0.74 at 1 year, 0.70 at 3 years, and 0.70 at 5 years in the validation dataset. The calibration curve for the probability of 1-, 3-, and 5-year survival showed good agreement between the nomogram prediction and actual observation in the training and validation datasets. The risk stratification system could perfectly classify patients into two risk groups, and the overall survival in the two groups had a good division.

CONCLUSIONS

This low-cost, convenient, and noninvasive nomogram can be translated into clinical practice as a tool for risk stratification and individualized prognosis prediction for children with medulloblastoma.

M-FANet: Multi-Feature Attention Convolutional Neural Network for Motor Imagery Decoding

Motor imagery (MI) decoding methods are pivotal in advancing rehabilitation and motor control research. Effective extraction of spectral-spatial-temporal features is crucial for MI decoding from limited and low signal-to-noise ratio electroencephalogram (EEG) signal samples based on brain-computer interface (BCI). In this paper, we propose a lightweight Multi-Feature Attention Neural Network (M-FANet) for feature extraction and selection of multi-feature data. M-FANet employs several unique attention modules to eliminate redundant information in the frequency domain, enhance local spatial feature extraction and calibrate feature maps. We introduce a training method called Regularized Dropout (R-Drop) to address training-inference inconsistency caused by dropout and improve the model's generalization capability. We conduct extensive experiments on the BCI Competition IV 2a (BCIC-IV-2a) dataset and the 2019 World robot conference contest-BCI Robot Contest MI (WBCIC-MI) dataset. M-FANet achieves superior performance compared to state-of-the-art MI decoding methods, with 79.28% 4-class classification accuracy (kappa: 0.7259) on the BCIC-IV-2a dataset and 77.86% 3-class classification accuracy (kappa: 0.6650) on the WBCIC-MI dataset. The application of multi-feature attention modules and R-Drop in our lightweight model significantly enhances its performance, validated through comprehensive ablation experiments and visualizations.

Measuring the 3-30-300 rule to help cities meet nature access thresholds

The 3-30-300 rule offers benchmarks for cities to promote equitable nature access. It dictates that individuals should see three trees from their dwelling, have 30 % tree canopy in their neighborhood, and live within 300 m of a high-quality green space. Implementing this demands thorough measurement, monitoring, and evaluation methods, yet little guidance is currently available to pursue these actions. To overcome this gap, we employed an expert-based consensus approach to review the available ways to measure 3-30-300 as well as each measure's strengths and weaknesses. We described seven relevant data and processes: vegetation indices, street level analyses, tree inventories, questionnaires, window view analyses, land cover maps, and green space maps. Based on the reviewed strengths and weaknesses of each measure, we presented a suitability matrix to link recommended measures with each component of the rule. These recommendations included surveys and window-view analyses for the '3 component', high-resolution land cover maps for the '30 component', and green space maps with network analyses for the '300 component'. These methods, responsive to local situations and resources, not only implement the 3-30-300 rule but foster broader dialogue on local desires and requirements. Consequently, these techniques can guide strategic investments in urban greening for health, equity, biodiversity, and climate adaptation.

Estrogen as a guardian of auditory health: Tsp1-CD47 axis regulation and noise-induced hearing loss

OBJECTIVES

This study aimed to analyze the role of estrogen in noise-induced hearing loss (NIHL) and uncover underlying mechanisms.

METHODS

An ovariectomized Sprague-Dawley rat model (OVX) was constructed to investigate the hearing threshold and auditory latency before and after noise exposure using the auditory brainstem response (ABR) test. The morphological changes were assessed using immunofluorescence, scanning electron microscopy and transmission electron microscopy. Proteomics and bioinformatics were used to analyze the mechanism. The findings were further verified through western blot and Luminex liquid suspension chip technology.

RESULTS

After noise exposure, OVX rats exhibited substantially elevated hearing thresholds. A conspicuous delay in ABR wave I latency was observed, alongside increased loss of outer hair cells, severe collapse of stereocilia and pronounced deformation of the epidermal plate. Accordingly, OVX rats with estrogen supplementation exhibited tolerance to NIHL. Additionally, a remarkable upregulation of the thrombospondin 1 (Tsp1)-CD47 axis in OVX rats was discovered and verified.

CONCLUSIONS

OVX rats were more susceptible to NIHL, and the protective effect of estrogen was achieved through regulation of the Tsp1-CD47 axis. This study presents a novel mechanism through which estrogen regulates NIHL and offers a potential intervention strategy for the clinical treatment of NIHL.

[Clinical and imaging features of acute encephalopathy with biphasic seizures and late reduced diffusion in children]

Objective: To explore the clinical and imaging features of acute encephalopathy with biphasic seizures and late reduced diffusion(AESD) in children. Methods: For the case series study, 21 children with AESD from Peking University First Hospital, Provincial Children's Hospital Affiliated to Anhui Medical University, Children's Hospital of Fudan University, and Shanxi Children's Hospital who were diagnosed and treated from October 2021 to July 2023 were selected. Clinical data were collected to summarize their clinical information, imaging, and laboratory tests, as well as treatment and prognostic characteristics. Descriptive statistical analysis was applicated. Results: Of the 21 cases with AESD, 11 were males and 10 were females, with the age of onset of 2 years and 6 months (1 year and 7 months, 3 years and 6 months). Of the 21 cases, 18 were typical cases with biphasic seizures. All typical cases had early seizures within 24 hours before or after fever onset. Among them, 16 cases had generalized seizures, 2 cases had focal seizures, and 7 cases reached the status epilepticus. Of the 21 cases, 3 atypical cases had late seizures in biphasic only. The late seizures in the 21 cases occurred on days 3 to 9. The types of late seizures included focal seizures in 12 cases, generalized seizures in 6 cases, and both focal and generalized seizures in 3 cases. Diffusion-weighted imaging (DWI) test on days 3 to 11 showed reduced diffusion of subcortical white matter which was named "bright tree sign" in all cases. The diffuse cerebral atrophy predominantly presented in the front-parietal-temporal lobes was found in 19 cases between day 12 and 3 months after the onset of the disease. Among 21 cases, 20 had been misdiagnosed as autoimmune encephalitis, central nervous system infection, febrile convulsions, posterior reversible encephalopathy syndrome, acute disseminated encephalomyelitis, and hemiconvulsion-hemiplegia-epilepsy syndrome. All the cases received high-dose gammaglobulin and methylprednisolone pulse therapy with poor therapeutic effect. By July 2023, 18 cases were under follow-up. Among them, 17 cases were left with varying degrees of neurologic sequelae, including 11 cases with post-encephalopathic epilepsy; 1 recovered completely. Conclusions: AESD is characterized by biphasic seizures clinically and "bright tree sign" on DWI images. Symptomatic and supportive treatments are recommended. The immunotherapy is ineffective. The prognosis of AESD is poor, with a high incidence of neurological sequelae and a low mortality.

Improving Bond Strength of Translucent Zirconia Through Surface Treatment With SiO2-ZrO2 Coatings

BACKGROUND

Translucent monolithic zirconia ceramics have been applied in dental clinics due to their esthetic translucent formulations and mechanical properties. Considering inherent ceramic brittleness, adhesive bonding with resin composite increases the fracture resistance of ceramic restorations. However, zirconia is a chemically stable material that is difficult to adhesively bond with resin.

OBJECTIVES

To investigate the influences of SiO2-ZrO2 coatings on adhesive bonding of zirconia and the surface characterization of those coatings.

METHODS AND MATERIALS

Translucent zirconia discs were classified into groups based on surface treatments: CT (control), SB (sandblasting), C21(SiO2:ZrO2=2:1), C11(SiO2:ZrO2=1:1), and C12 (SiO2:ZrO2=1:2) (n=10). Surface characterization of coatings on zirconia were analyzed by scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), surface roughness assessment (Ra), X-ray diffraction (XRD), water contact angle (WCA), translucency parameter (TP), and shear bond strength (SBS). Two-way ANOVA for shear bond strength results and ANOVA for Ra and WCA were performed.

RESULTS

SEM images revealed SiO2 islands on zirconia disks coated with SiO2-ZrO2. Surface roughness of C12, C11, and C21 groups was significantly larger than those of groups SB and CT (p<0.05). XRD results showed that phase transformation of zirconia disks was detected only in the SB group. In addition, SiO2-ZrO2 coatings reduced WCA. The translucency decreased only in group C21. Group C11 showed the highest shear bond strength under both aging conditions.

CONCLUSION

SiO2-ZrO2 coating is a promising method to enhance the adhesive resin bonding of translucent zirconia without causing phase transformation of translucent zirconia.

Aided diagnosis of cervical spondylotic myelopathy using deep learning methods based on electroencephalography

Cervical spondylotic myelopathy (CSM) is the most severe type of cervical spondylosis. It is challenging to achieve early diagnosis with current clinical diagnostic tools. In this paper, we propose an end-to-end deep learning approach for early diagnosis of CSM. Electroencephalography (EEG) experiments were conducted with patients having spinal cord cervical spondylosis and age-matched normal subjects. A Convolutional Neural Network with Long Short-Term Memory Networks (CNN-LSTM) model was employed for the classification of patients versus normal individuals. In contrast, a Convolutional Neural Network with Bidirectional Long Short-Term Memory Networks and attention mechanism (CNN-BiLSTM-attention) model was used to classify regular, mild, and severe patients. The models were trained using focal Loss instead of traditional cross-entropy Loss, and cross-validation was performed. Our method achieved a classification accuracy of 92.5 % for the two-class classification among 40 subjects and 72.2 % for the three-class classification among 36 subjects. Furthermore, we observed that the proposed model outperformed traditional EEG decoding models. This paper presents an effective computer-aided diagnosis method that eliminates the need for manual extraction of EEG features and holds potential for future auxiliary diagnosis of spinal cord-type cervical spondylosis.

[Management of radiation-induced intestinal injury:from multi-disciplinary team team to holistic integrative management]

Radiation-induced intestinal injury is a radiation injury of the colon and rectum after radiotherapy for pelvic malignant tumors. This condition affects multiple organs in the pelvis, making treatment challenging. In clinical practice, the most effective protocol is often determined through discussion by a multi-disciplinary team (MDT). However, due to the severity and complexity of radiation enteritis, many patients still experience poor diagnosis and treatment outcomes. Holistic integrative management (HIM) is a rapidly developing concept that has greatly enhanced clinical medicine in recent years. It improves the level of diagnosis, treatment, prevention, and rehabilitation from multiple dimensions of prevention, screening, diagnosis, treatment, and rehabilitation. In the context of radiation-induced intestinal injury, HIM also calls for the implementation of an individualized management system that focuses on the patient as a whole within the healthcare team. From the perspective of HIM, this article introduces some of the latest progress of radiation-induced intestinal injury in recent years.

Application of the Ion Chamber Array in Magnetic Resonance Accelerator QA

PURPOSE/OBJECTIVE(S)

The magnetic resonance accelerator (MR-Linac) is gradually widely used due to high-quality soft tissue contrast and real-time tracking. However, the special dosimetry characteristics and wide field sizes of MR-Linac increase the QA difficulty with conventional measurement method. The purpose of this study was to confirm an ion chamber array could be used for measuring the beam quality, the profiles, as well as the positioning accuracy of all MLC leaves efficiently, by comparing results with the conventional method. To propose a new QA approach for solving the common problem in data acquisition caused by the wide fields of MR-Linac.

MATERIALS/METHODS

The research was based on a MR-Linac fixed with 1.5T MR and 7MeV energy photon beam. The conventional QA method adopted the MR water tank with a gantry angle of 0°and an SSD of 133.5 cm, both microdiamond and ionization chamber detector were used to acquire the dose profiles (PDD, inline, crossline and diagonal). Field sizes 1 × 1 cm2, 2 × 2 cm2, 3 × 3 cm2, 5 × 5 cm2, 10 × 10 cm2, 15 × 15 cm2, 22 × 22 cm2, 40 × 22 cm2,57 × 22 cm2 were measured with depth 13mm, 50mm, 100mm for vertical beam. As for the wide fields (larger than 15 × 15 cm2), two profiles of x axis (one from left to right, the other from right to left) needed to be gathered and then stitched into one final profile. A boot phantom with an ionization chamber detector was used for measuring beam quality. We defined the profiles measured by conventional method as the baseline. An ion chamber array was adopted to acquire TPR, PDD, profiles and MLC positioning, comparing to the conventional method. The center of ion chamber array was placed to the isocenter of MR-Linac, the array could move to the right and left offset positions through engaging the pin into correct hole of QA platform, such 'once positioning and twice movements' operation could finish within 3 minutes. The central detector of the ion chamber array was used for measuring beam quality. TPRs for different depths were acquired by stacking solid water on the ion chamber array. As for the profiles, we could get the final profile by 'once positioning and twice movements' efficiently. As for the positioning accuracy of MLC leaves, firstly the central leaf pair was put on y = 0 to measure 'open profile' under the open field. Then we moved the MLC leaves to different positions to get the n profile (n for different leaf positions). The ratio of n profile to open profile could show the positioning accuracy of MLC.

RESULTS

We adopted 2D gamma (1mm / 2%) to compare the profiles between the ion chamber array and the conventional method, the results were within 98%. The beam quality consistency of ion chamber array comparing to the wedge tank was within 1% according to daily measurement. The ion chamber array could reflect the MLC positioning differences, the sensitivity was 0.5 mm.

CONCLUSION

The ion chamber array showed a convenient QA method both for the dosimetry and for the MLC positioning accuracy which did reduce the overall measurement time, it was recommended for daily and monthly QA for MR-Linac.

Prediction of Anatomical Presentation during Radiotherapy of Nasopharyngeal Carcinoma Using GAN-LSTM for Plan Adaption Decision

PURPOSE/OBJECTIVE(S)

During treatment, patients frequently undergo anatomical changes that might result in dose degradation. Adaptive radiation therapy (ART) is now available to overcome this problem. However, this method is time-consuming, and the lack of criteria to trigger replanning prevents its widespread use. To overcome these obstacles, anatomical presentation models are necessary. In this study, we developed a novel deep-learning method to make a series of predictions for the remaining treatment course.

MATERIALS/METHODS

Total 230 nasopharyngeal carcinoma patients who received radiotherapy in 33 fractions were enrolled. The data included cone-beam computed tomography (CBCT) and planning CT images. CBCT image quality was improved to CT level using an in-house software. A generative adversarial network-long short-term memory network model was proposed, with the generation abilities of the former network and forecasting abilities of the latter. To predict the anatomical presentation for 3-6 weeks, we trained four models. The planning CT and CBCT acquired earlier were used as the input. Physicians segmented the gross target volume (GTVnx) and parotid glands on prediction and real CBCT (ground truth). Contours, dosimetry parameters, and plan adaptation decision were used to evaluate the models.

RESULTS

The table shows the overall performance of the test set (18 cases). The anatomical changes were predicted over the treatment course with a dice similarity coefficient (DSC) of 0.96, 0.90 and 0.92 and mean distance to agreement (MDA, in mm) of 0.37, 0.70, and 0.60 for GTVnx, left parotid, and right parotid, respectively. Bland-Altman analysis revealed that dosimetry parameters did not show significant difference between prediction and ground truth. The prescription coverage (%) of GTVnx, V30 of the left parotid, and V30 of the right parotid had mean absolute biases of 0.09, 1.09, and 0.27, respectively. At week 6, there were two cases that required plan adaptation, and the model effectively triggered replanning one week in advance.

CONCLUSION

We developed a framework that predicts the anatomical changes occurring in future fractions. Establishing such a framework provides a proactive approach to ART and saves clinical time by anticipating and preparing for treatment strategies in advance.

Performance Evaluation in Automatic Plan Generation for Ethos Intelligent Optimization Engine

PURPOSE/OBJECTIVE(S)

To evaluate the automatic optimization performance and clinical feasibility of the Intelligent Optimization Engine (IOE) of Ethos online adaptive radiotherapy platform.

MATERIALS/METHODS

Eleven patients with cervical cancer treated with Halcyon accelerator were retrospectively selected. All the patients manually planned with four full arc volume rotating intensity modulated radiotherapy (VMAT) (Manual-4Arc), and the prescription dose was 45 Gy/25F. All patient images and structures were imported into Ethos simulator, and clinical goals were added appropriately based on clinical requirements. The target coverage was normalized to 95%. 7F, 9F, 12F IMRT plans and 2Arc, 3Arc VMAT plans were automatically generated by IOE. Dosimetric index comparisons were made among the Manual-4Arc plans and five group IOE generated plan to evaluate the automatic optimization performance of IOE.

RESULTS

In terms of hot dose area, for PTV, D1% of IMRT-12F plans was the lowest, and there were significant differences between IMRT-12F plans and Manual-4Arc plans (46.936 ± 0.241 vs 48.639 ± 2.395, p = 0.004); In terms of target coverage, the CTVs of all groups meet clinical requirements. Although the Ethos online adaptive plans have been normalized during planning, the PTV coverage is slightly insufficient (12F: 94.913 ± 0.154; 9F: 94.585 ± 1.148). For OARs close to target, such as bladder, V30Gy, V40Gy and Dmean have significant differences among the six group plans. The order of bladder dose is basically followed by IMRT-12F

CONCLUSION

The plans automatically generated by Ethos IOE can achieve similar performance as the manual plan, and the automatically generated IMRT-12F and 9F plans are preferred for clinical use.

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More Efficient Auto-Segmentation Framework Using Patient-Specific Information for CBCT-Guided Adaptive Radiotherapy

PURPOSE/OBJECTIVE(S)

Accurate and fast delineation of regions of interest (ROIs) is critical for online adaptive radiotherapy (ART). Due to the noise, artifacts and low contrast of soft tissue on cone-beam computed tomography (CBCT), the CBCT-guided ART (CBCTgART) needs an effective tool to assist the segmentation of ROIs. This study aims to develop an efficient auto-segmentation workflow with personalized modeling for CBCTgART based on deep learning (DL) model.

MATERIALS/METHODS

Five hundred fifty-two patients with nasopharyngeal carcinoma were enrolled in this study. At the beginning, a cycle consistent adversarial network (CycleGAN) model was trained on 172 patients' CBCT/CT paired images to improve the image quality of CBCT to CT level. A generalized segmentation model was trained using the planning CT (pCT) and contour data from 530 patients. For personalized modeling, the generalized segmentation model was fine-tuned on the specific patient's pCT and contour to get the personalized model. When CBCT images were available, the trained CycleGAN model transformed the CBCT to synthetic pCT. Then the personalized auto-segmentation model generated the contour of ROIs on the synthetic pCT. We randomly selected 22 patients for model test. The proposed method (DL-personalized) was compared with other DL methods based on the same architecture of network: regular deep learning method (DL-regular), which was trained on the CBCT and corresponding contours, and generalized model in our framework (DL-generalized). So, 22 personalized, 1 generalized and 1 regular DL models were tested. The paired t-test was performed to test the significance for mean dice similarity coefficient (DSC), mean distance to agreement (MDA), and Hausdorff distance (HD) between the alternative and proposed methods.

RESULTS

Two ROIs were included: the clinical target volume (CTV) and nasopharynx gross tumor volume (GTVnx). The proposed DL-personalized model achieved better results compared with others as shown in the table. The accuracy and robustness of our proposed framework was reliable. All of p values were under 0.01, which indicated the statistically significant difference.

CONCLUSION

The proposed framework utilizing patient-specific information can improve the segmentation accuracy of ART. This method has potential to be integrated into the ART workflow to improve efficiency.

Dose DIBH Really Reduce the Subclinical Cardiac Acute Injury? Analysis of Clinical Real World from Our Institute

PURPOSE/OBJECTIVE(S)

The study is aim to investigate whether Deep-inspirational breath-hold (DIBH), compared with free breathing (FB), could provide a short-term cardiac benefit in patients with early left breast cancer after breast-conserving surgery combined whole breast radiotherapy.

MATERIALS/METHODS

A total of 78 patients with early stage left breast cancer treated with radiotherapy between 2021-2022 after breast-conserving surgery were enrolled. Among them, 32 cases were treated with DIBH technique and 46 cases were treated with free breathing. Patients with previous cardiac disease such as coronary artery disease were excluded. We performed myocardial enzymes, ECG, and ECHO in all patients within 2 weeks before, during, and 6 months after radiotherapy. The results of the two groups were compared using nonparametric tests and chi-square tests, and P < 0.05 indicated statistical significance. Where subclinical acute cardiac injury was defined as new above-normal myocardial enzymes and/or electrocardiographic ST-T or T-wave changes and/or ECHO abnormalities after the start of radiotherapy.

RESULTS

The median follow-up of patients was 6 months and the mean age of patients was 52.3 years for FB and 44.9 years for DIBH. There were no significant differences in staging, molecular subtype, chemotherapy and endocrine therapy history. The proportion of subclinical acute cardiac injury was smaller in the DIBH group compared to the FB group (DIBH = 31/46 and FB = 28/32, p = 0.042). The most sensitive of the subclinical acute cardiac injury events were detected by myocardial enzymes rising, with cTnI (p = 0.034) and NT-proBNP (p = 0.023) appearing significantly lower in the DIBH patients during radiotherapy. The difference of cTnI between 2 groups at 6 months after radiotherapy became non-significant. In contrast, CK-MB was higher in DIBH compared with FB only 6 months after radiotherapy (p = 0.006). The differences in ECG and ECHO were not significant between the two groups.

CONCLUSION

After breast-conserving surgery combined with radiotherapy for left early breast cancer, DIBH compared to FB reduces the proportion of acute subclinical cardiac injury that occurs with the most sensitive changes in myocardial enzymes. Subsequent studies will explore the relationship between the short-term subclinical injury and irradiated dose, as well as long term cardiac injury.

A multiline fitting method for measuring ethylene concentration based on WMS-2f/1f

Coal spontaneous combustion risk assessment is a global technical challenge for the sustainable development of deep mining technology, and C2H4 is a key indicator for early warning of coal spontaneous combustion. Tunable diode laser absorption spectroscopy (TDLAS) has the advantages of high selectivity, high sensitivity, high accuracy and real-time on-line measurement, and it can detect multiple gases simultaneously, so it has significant advantages in the accurate detection of coal spontaneous combustion indicator gases. To address the problem of cross-interference between the near-infrared absorption lines of CH4 and C2H4, which are the indicator gases of spontaneous combustion in coal, a multi-line fitting method was proposed in this study to calibrate the concentration of C2H4. The high-precision Environics2000 automatic standard gas dispenser from the United States, which has a built-in CPU computer control and data control and processing system, was used. Its gas concentration accuracy: ± 1.0%, gas flow accuracy: ± 1.0%, gas repeatability accuracy: ± 1.0%, flow linearity accuracy: ± 0.5%, and inlet operating pressure: minimum 10 psig (0.67 bar) ~ 75 psig (5.04 bar). The measured and simulated WMS-2f/1f signals were multilinearly fitted using a multilinear fitting algorithm and wavelength modulation spectroscopy (WMS), and the measurement of C2H4 concentration was achieved based on the extracted spectral line information. The results show that the maximum relative error of C2H4 concentration measurement is 2.40%, which is 54% lower than that of the conventional 2f peak measurement method, thus demonstrating the effectiveness of the multilinear fitting algorithm in the inversion of C2H4 concentration under the interference of absorption lines. In addition, this study has far-reaching implications for the application of TDLAS technology in the accurate detection of coal spontaneous combustion indicator gases.

Temporal-frequency-phase feature classification using 3D-convolutional neural networks for motor imagery and movement

Recently, convolutional neural networks (CNNs) have been widely applied in brain-computer interface (BCI) based on electroencephalogram (EEG) signals. Due to the subject-specific nature of EEG signal patterns and the multi-dimensionality of EEG features, it is necessary to employ appropriate feature representation methods to enhance the decoding accuracy of EEG. In this study, we proposed a method for representing EEG temporal, frequency, and phase features, aiming to preserve the multi-domain information of EEG signals. Specifically, we generated EEG temporal segments using a sliding window strategy. Then, temporal, frequency, and phase features were extracted from different temporal segments and stacked into 3D feature maps, namely temporal-frequency-phase features (TFPF). Furthermore, we designed a compact 3D-CNN model to extract these multi-domain features efficiently. Considering the inter-individual variability in EEG data, we conducted individual testing for each subject. The proposed model achieved an average accuracy of 89.86, 78.85, and 63.55% for 2-class, 3-class, and 4-class motor imagery (MI) classification tasks, respectively, on the PhysioNet dataset. On the GigaDB dataset, the average accuracy for 2-class MI classification was 91.91%. For the comparison between MI and real movement (ME) tasks, the average accuracy for the 2-class were 87.66 and 80.13% on the PhysioNet and GigaDB datasets, respectively. Overall, the method presented in this paper have obtained good results in MI/ME tasks and have a good application prospect in the development of BCI systems based on MI/ME.

Local and global convolutional transformer-based motor imagery EEG classification

Transformer, a deep learning model with the self-attention mechanism, combined with the convolution neural network (CNN) has been successfully applied for decoding electroencephalogram (EEG) signals in Motor Imagery (MI) Brain-Computer Interface (BCI). However, the extremely non-linear, nonstationary characteristics of the EEG signals limits the effectiveness and efficiency of the deep learning methods. In addition, the variety of subjects and the experimental sessions impact the model adaptability. In this study, we propose a local and global convolutional transformer-based approach for MI-EEG classification. The local transformer encoder is combined to dynamically extract temporal features and make up for the shortcomings of the CNN model. The spatial features from all channels and the difference in hemispheres are obtained to improve the robustness of the model. To acquire adequate temporal-spatial feature representations, we combine the global transformer encoder and Densely Connected Network to improve the information flow and reuse. To validate the performance of the proposed model, three scenarios including within-session, cross-session and two-session are designed. In the experiments, the proposed method achieves up to 1.46%, 7.49% and 7.46% accuracy improvement respectively in the three scenarios for the public Korean dataset compared with current state-of-the-art models. For the BCI competition IV 2a dataset, the proposed model also achieves a 2.12% and 2.21% improvement for the cross-session and two-session scenarios respectively. The results confirm that the proposed approach can effectively extract much richer set of MI features from the EEG signals and improve the performance in the BCI applications.

Machine Learning Advances in Predicting Peptide/Protein-Protein Interactions Based on Sequence Information for Lead Peptides Discovery

Peptides have shown increasing advantages and significant clinical value in drug discovery and development. With the development of high-throughput technologies and artificial intelligence (AI), machine learning (ML) methods for discovering new lead peptides have been expanded and incorporated into rational drug design. Predictions of peptide-protein interactions (PepPIs) and protein-protein interactions (PPIs) are both opportunities and challenges in computational biology, which will help to better understand the mechanisms of disease and provide the impetus for the discovery of lead peptides. This paper comprehensively reviews computational models for PepPI and PPI predictions. It begins with an introduction of various databases of peptide ligands and target proteins. Then it discusses data formats and feature representations for proteins and peptides. Furthermore, classical ML methods and emerging deep learning (DL) methods that can be used to train prediction models of PepPI and PPI are classified into four categories, and their advantages and disadvantages are analyzed. To assess the relative performance of different models, different validation protocols and evaluation indexes are discussed. The goal of this review is to help researchers quickly get started to develop computational frameworks using these integrated resources and eventually promote the discovery of lead peptides.

Herbicide residues in soil decrease microbe-mediated plant protection

The residues of glyphosate are found to remain in soils longer than previously reported, affecting rhizosphere microbes. This may adversely affect crop and other non-target plants because the plant's resilience and resistance largely rely on plant-associated microbes. Ubiquitous glyphosate residues in soil and how they impact mutualistic microbes inhabiting the aboveground plant parts are largely unexplored. We studied the effects of herbicide residues in soil on Epichloë sp., which are common endophytic symbionts inhabiting aerial parts of cool-season grasses. In this symbiosis, the obligate symbiont subsists entirely on its host plant, and in exchange, it provides alkaloids conferring resistance to herbivores for the host grass that invests little in its own chemical defence. We first show decreased growth of Epichloë endophytes in vitro when directly exposed to two concentrations of glyphosate or glyphosate-based herbicides. Second, we provide evidence for a reduction of Epichloë-derived, insect-toxic loline alkaloids in endophyte-symbiotic meadow fescue (F. pratensis) plants growing in soil with a glyphosate history. Plants were grown for 2 years in an open field site, and natural herbivore infestation was correlated with the glyphosate-mediated reduction of loline alkaloid concentrations. Our findings indicate that herbicides residing in soil not only affect rhizosphere microbiota but also aerial plant endophyte functionality, which emphasizes the destructive effects of glyphosate on plant symbiotic microbes, here with cascading effects on plant-pest insect interactions.

[Outcome of surgical repair for aortic coarctation with coexisting descending aortic aneurysm in adult patients]

Objective: To evaluate the efficacy of surgical treatment of aortic coarctation combined with descending aortic aneurysm in adult patients. Methods: This is a retrospective cohort study. Adult patients with aortic coarctation who were hospitalized in Beijing Anzhen Hospital from January 2015 to April 2019 were enrolled. The aortic coarctation was diagnosed by aortic CT angiography, and the included patients were divided into the combined descending aortic aneurysm group and the uncomplicated descending aortic aneurysm group based on descending aortic diameter. General clinical data and surgery-related data were collected from the included patients, and death and complications were recorded at 30 days after surgery, and upper limb systolic blood pressure was measured in all patients at discharge. Patients were followed up after discharge by outpatient visit or telephone call for their survival and the occurrence of repeat interventions and adverse events, which included death, cerebrovascular events, transient ischemic attack, myocardial infarction, hypertension, postoperative restenosis, and other cardiovascular-related interventions. Results: A total of 107 patients with aortic coarctation aged (34.1±15.2) years were included, and 68 (63.6%) were males. There were 16 cases in the combined descending aortic aneurysm group and 91 cases in the uncomplicated descending aortic aneurysm group. In the combined descending aortic aneurysm group, 6 cases (6/16) underwent artificial vessel bypass, 4 cases (4/16) underwent thoracic aortic artificial vessel replacement, 4 cases (4/16) underwent aortic arch replacement+elephant trunk procedure, and 2 cases (2/16) underwent thoracic endovascular aneurysm repair. There was no statistically significant difference between the two groups in the choice of surgical approach (all P>0.05). In the combined descending aortic aneurysm group at 30 days after surgery, one case underwent re-thoracotomy surgery, one case developed incomplete paraplegia of the lower extremity, and one case died; and the differences in the incidence of endpoint events at 30 days after surgery were similar between the two groups (P>0.05). Systolic blood pressure in the upper extremity at discharge was significantly lower in both groups compared with the preoperative period (in the combined descending aortic aneurysm group: (127.3±16.3) mmHg vs. (140.9±16.3) mmHg, P=0.030, 1 mmHg=0.133 kPa; in the uncomplicated descending aortic aneurysm group: (120.7±13.2) mmHg vs. (151.8±26.3) mmHg, P=0.001). The follow-up time was 3.5 (3.1, 4.4) years. There were no new deaths in the combined descending aortic aneurysm group, no transient ischemic attack, myocardial infarction or re-thoracotomy surgery, and one patient (1/15) suffered cerebral infarction and 10 patients (10/15) were diagnosed with hypertension. The differences in the occurrence of endpoint events during postoperative follow-up were similar between the two groups (P>0.05). Conclusion: In experienced centers, long-term prognosis of patients with aortic coarctation combined with descending aortic aneurysm is satisfactory post surgical intervention.

Effect of ripening temperature on the chemical composition of lingonberries (Vaccinium vitis-idaea L.) of northern and southern origin

Lingonberries (Vaccinium vitis-idaea L.) from two locations, northern (69°N, 18°E) and southern (59°N, 10°E) Norway, were grown under controlled conditions in a phytotron at two temperatures (9 and 15 °C) to study the effects of the ripening temperature and origin on the chemical composition of the berries. The concentrations of phenolic compounds, sugars, and organic acids as well as the profile of volatile organic compounds (VOCs) were determined using chromatographic and mass spectrometric methods. Five anthocyanins, eleven flavonols, eight cinnamic acid derivatives, three flavan-3-ols, three sugars, three organic acids, and 77 VOCs were identified, of which 40 VOCs had not previously been reported in lingonberries. Berries from both locations, were found to have higher contents of anthocyanins and cinnamic acid derivatives when ripened at lower temperature (9 °C), compared to the higher temperature (15 °C). Lingonberries of northern origin had a different VOC profile and higher contents of anthocyanins and organic acids than berries originating from the south. Lingonberries from the northern location also had higher proportions of cyanidin-3-O-glucoside and cyanidin-3-O-arabinoside than lingonberries from the southern location. The results show that the composition of lingonberries is influenced by both the environment and the origin of the plants, with phenolic compounds mainly influenced by the growth temperature and VOCs mainly influenced by plant origin.

Clinical Relevance of Plaque Distribution for Basilar Artery Stenosis

BACKGROUND AND PURPOSE

There is no clear association between plaque distribution and postoperative complications in patients with basilar artery atherosclerotic stenosis. The aim of this study was to determine whether plaque distribution and postoperative complications after endovascular treatment for basilar artery stenosis are related.

MATERIALS AND METHODS

Our study enrolled patients with severe basilar artery stenosis who were scanned with high-resolution MR imaging and followed by DSA before the intervention. According to high-resolution MR imaging, plaques can be classified as ventral, lateral, dorsal, or involved in 2 quadrants. Plaques affecting the proximal, distal, or junctional segments of the basilar artery were classified according to DSA. An experienced independent team assessed ischemic events after the intervention using MR imaging. Further analysis was conducted to determine the relationship between plaque distribution and postoperative complications.

RESULTS

A total of 140 eligible patients were included in the study, with a postoperative complication rate of 11.4%. These patients were an average age of 61.9 (SD, 7.7) years. Dorsal wall plaques accounted for 34.3% of all plaques, and plaques distal to the anterior-inferior cerebellar artery accounted for 60.7%. Postoperative complications of endovascular treatment were associated with plaques located at the lateral wall (OR = 4.00; 95% CI, 1.21-13.23; P = .023), junctional segment (OR = 8.75; 95% CI, 1.16-66.22; P = .036), and plaque burden (OR = 1.03; 95% CI, 1.01-1.06; P = .042).

CONCLUSIONS

Plaques with a large burden located at the junctional segment and lateral wall of the basilar artery may increase the likelihood of postoperative complications following endovascular therapy. A larger sample size is needed for future studies.

Recognizable Rehabilitation Movements of Multiple Unilateral Upper Limb: an fMRI Study of Motor Execution and Motor Imagery

BACKGROUND

This paper presents a study investigating the recognizability of multiple unilateral upper limb movements in stroke rehabilitation.

METHODS

A functional magnetic experiment is employed to study motor execution (ME) and motor imagery (MI) of four movements for the unilateral upper limb: hand-grasping, hand-handling, arm-reaching, and wrist-twisting. The functional magnetic resonance imaging (fMRI) images of ME and MI tasks are statistically analyzed to delineate the region of interest (ROI). Then parameter estimation associated with ROIs for each ME and MI task are evaluated, where differences in ROIs for different movements are compared using analysis of covariance (ANCOVA).

RESULTS

All movements of ME and MI tasks activate motor areas of the brain, and there are significant differences (p<0.05) in ROIs evoked by different movements. The activation area is larger when executing the hand-grasping task instead of the others.

CONCLUSION

The four movements we propose can be adopted as MI tasks, especially for stroke rehabilitation, since they are highly recognizable and capable of activating more brain areas during MI and ME.

Uncovering and engineering the mechanical properties of the adhesion GPCR ADGRG1 GAIN domain

Key cellular functions depend on the transduction of extracellular mechanical signals by specialized membrane receptors including adhesion G-protein coupled receptors (aGPCRs). While recently solved structures support aGPCR activation through shedding of the extracellular GAIN domain, the molecular mechanisms underpinning receptor mechanosensing remain poorly understood. When probed using single-molecule atomic force spectroscopy and molecular simulations, ADGRG1 GAIN dissociated from its tethered agonist at forces significantly higher than other reported signaling mechanoreceptors. Strong mechanical resistance was achieved through specific structural deformations and force propagation pathways under mechanical load. ADGRG1 GAIN variants computationally designed to lock the alpha and beta subdomains and rewire mechanically-induced structural deformations were found to modulate the GPS-Stachel rupture forces. Our study provides unprecedented insights into the molecular underpinnings of GAIN mechanical stability and paves the way for engineering mechanosensors, better understanding aGPCR function, and informing drug-discovery efforts targeting this important receptor class.

[Current practices in the harmonisation of autoantibodies test]

Standardisation and harmonisation of the detection of autoantibodies is important for the clinical application of autoantibodies. However, achieving complete standardisation is difficult and involves several challenges due to the complexity and particularity of autoantibody detection. Harmonisation is feasible and valued, but it involves all aspects and processes of autoantibody detection. Based on the consensus and practice of the clinical application of autoantibody detection in recent years, we discuss harmonisation in this review.

[Changes of serum calcium and bone turnover markers in maintenance hemodialysis patients treated with denosumab]

A total of 20 patients (8 males and 12 females) aged (64.8±13.9) years who underwent regular hemodialysis and had bone loss or osteoporosis in Peking University People's Hospital from July to December 2021 were recruited. Sixty milligrams of denosumab were given subcutaneously. The average serum calcium decreased by 0.31 mmol/L and 40% (8/20) of the patients had hypocalcemia one month after treatment. The markers of bone turnover began to decrease 3 days after treatment, and continued to decrease until 5 months after denosumab medication. Multivariate logistic regression analysis failed to detect any independent risk factor for hypocalcemia (R²=0.516, P=0.021). Therefore, denosumab can significantly inhibit bone turnover in hemodialysis patients, however, patients with denosumab medication are more prone to hypocalcemia.

EEG assessment of brain dysfunction for patients with chronic primary pain and depression under auditory oddball task

In 2019, the International Classification of Diseases 11th Revision International Classification of Diseases (ICD-11) put forward a new concept of "chronic primary pain" (CPP), a kind of chronic pain characterized by severe functional disability and emotional distress, which is a medical problem that deserves great attention. Although CPP is closely related to depressive disorder, its potential neural characteristics are still unclear. This paper collected EEG data from 67 subjects (23 healthy subjects, 22 patients with depression, and 22 patients with CPP) under the auditory oddball paradigm, systematically analyzed the brain network connection matrix and graph theory characteristic indicators, and classified the EEG and PLI matrices of three groups of people by frequency band based on deep learning. The results showed significant differences in brain network connectivity between CPP patients and depressive patients. Specifically, the connectivity within the frontoparietal network of the Theta band in CPP patients is significantly enhanced. The CNN classification model of EEG is better than that of PLI, with the highest accuracy of 85.01% in Gamma band in former and 79.64% in Theta band in later. We propose hyperexcitability in attentional control in CPP patients and provide a novel method for objective assessment of chronic primary pain.

[Exploration of pathogenesis and clinical diagnosis and treatment for portal vein thrombosis formation]

Portal vein thrombosis (PVT) refers to the thrombosis of the main portal vein and/or branches, with or without mesenteric vein and splenic vein thrombosis, and is the most common cause of extrahepatic portal vein obstruction. It is latent under chronic conditions and is often detected accidentally during physical examinations or liver cancer screenings. Notably, the understanding of PVT management is still limited, both at home and abroad. Therefore, the purpose of this article is to provide a reference for clinical diagnosis and treatment of PVT formation by summarizing the basis and standards for clinical diagnosis and treatment based on representative research with a large sample size and new perspectives with recent guidelines and consensus.

[Evaluation of diagnostic efficacy of digital liquid chip method for detection of specific antineutrophil cytoplasmic antibodies]

To explore the clinical diagnostic efficacy of antineutrophil cytoplasmic antibody associated vasculitis (AAV) by comparing the consistency and coincidence rate of serum anti-myeloperoxidase (MPO) antibody and anti-protease 3 (PR3) antibody detected by digital liquid chip method (DLCM) and enzyme-linked immunosorbent assay (ELISA). To provide reference for the selection of detection methods of anti-MPO antibody and anti-PR3 antibody in clinical laboratory. This study is a cross-sectional study, a total of 307 cases of antineutrophil cytoplasmic antibodies were detected in the Department of Clinical Immunology, West China Hospital of Sichuan University from January to March 2021. The serum samples and related clinical information were collected. At the same time, the levels of anti-MPO antibody and anti-PR3 antibody in serum samples were detected by ELISA and DLCM, indirect immunofluorescence (IIF) was used to re-test the differential samples between the two methods. SPSS 26.0 was used to analyze the test results, Cohen's kappa coefficient analysis was used to compare the consistency of the two methods, and paired chi-square test was used to compare the sensitivity and specificity of the two methods to AAV. The results showed that the positive cases of anti-MPO antibody detected by ELISA and DLCM were 63 and 44, and the negative cases were 244 and 263; the positive cases of anti-PR3 antibody detected by ELISA and DLCM were 34 and 28, and the negative cases were 273 and 279. The results of anti-MPO antibody and anti-PR3 antibody detected by the two methods had good consistency and coincidence rate, in which the total coincidence rate of anti-MPO antibody was 92.51%, the positive coincidence rate was 66.67%, and the negative coincidence rate was 99.18%. The results of consistency analysis showed that kappa=0.741 had well consistency. The total coincidence rate of anti-PR3 antibody is 96.74%, the positive coincidence rate is 76.47%, and the negative coincidence rate is 99.27%. The consistency analysis results show that kappa=0.821 had strong consistency. The results of IIF re-test of differential samples showed that the coincidence rate between DLCM and IIF was higher. The results of comparative analysis of anti-MPO antibody and anti-PR3 antibody showed that the specificity of DLCM was better than that of ELISA, and its sensitivity was lower than that of ELISA. In conclusion, the results of anti-MPO antibody and anti-PR3 antibody detected by DLCM were consistent with those of ELISA. In the combined detection of anti-MPO antibody and anti-PR3 antibody, the specificity of DLCM is better than that of ELISA.

A few-shot learning-based eye diseases screening method

OBJECTIVE

This study aims to construct a brand-new ophthalmic disease screening task and establish a practically valuable ophthalmic disease screening model in the case of insufficient data.

MATERIALS AND METHODS

The main methods are as follows: firstly, we mixed data from different sources (these data may come from different cameras, including different fundus diseases) to get a new dataset. Based on this dataset, we conducted subsequent experiments on fundus multi-disease screening. However, in the past public datasets, each dataset often only corresponded to the screening diagnosis of one disease. Secondly, we proposed a method to simulate the characteristics of different fundus cameras by using a method based on style transfer, and to augment the training data, so that the model could learn the features of ophthalmic diseases in a more comprehensive way. Finally, a robust disease screening model based on few-shot learning was constructed on the combined dataset, and compared with benchmark algorithms.

RESULTS

We focused on the study of eye disease screening methods based on the metric-based few-shot learning model, data augmentation methods, and focus on key technologies such as data augmentation based on style transfer. Experiments have shown that our method can significantly improve the generalization ability of the disease screening model.

CONCLUSIONS

By introducing few-shot learning theory and data augmentation based on style transfer into ophthalmic disease screening, the generalization ability of the model is greatly improved, and it has certain practical value.