Self-supervised contrastive learning for EEG-based cross-subject motor imagery recognition.

Objective. The extensive application of electroencephalography (EEG) in brain-computer interfaces (BCIs) can be attributed to its non-invasive nature and capability to offer high-resolution data. The acquisition of EEG signals is a straightforward process, but the datasets associated with these signals frequently exhibit data scarcity and require substantial resources for proper labeling. Furthermore, there is a significant limitation in the generalization performance of EEG models due to the substantial inter-individual variability observed in EEG signals.Approach. To address these issues, we propose a novel self-supervised contrastive learning framework for decoding motor imagery (MI) signals in cross-subject scenarios. Specifically, we design an encoder combining convolutional neural network and attention mechanism. In the contrastive learning training stage, the network undergoes training with the pretext task of data augmentation to minimize the distance between pairs of homologous transformations while simultaneously maximizing the distance between pairs of heterologous transformations. It enhances the amount of data utilized for training and improves the network's ability to extract deep features from original signals without relying on the true labels of the data.Main results. To evaluate our framework's efficacy, we conduct extensive experiments on three public MI datasets: BCI IV IIa, BCI IV IIb, and HGD datasets. The proposed method achieves cross-subject classification accuracies of 67.32%, 82.34%, and 81.13%on the three datasets, demonstrating superior performance compared to existing methods.Significance. Therefore, this method has great promise for improving the performance of cross-subject transfer learning in MI-based BCI systems.

Robust deep learning from incomplete annotation for accurate lung nodule detection.

Deep learning plays a significant role in the detection of pulmonary nodules in low-dose computed tomography (LDCT) scans, contributing to the diagnosis and treatment of lung cancer. Nevertheless, its effectiveness often relies on the availability of extensive, meticulously annotated dataset. In this paper, we explore the utilization of an incompletely annotated dataset for pulmonary nodules detection and introduce the FULFIL (Forecasting Uncompleted Labels For Inexpensive Lung nodule detection) algorithm as an innovative approach. By instructing annotators to label only the nodules they are most confident about, without requiring complete coverage, we can substantially reduce annotation costs. Nevertheless, this approach results in an incompletely annotated dataset, which presents challenges when training deep learning models. Within the FULFIL algorithm, we employ Graph Convolution Network (GCN) to discover the relationships between annotated and unannotated nodules for self-adaptively completing the annotation. Meanwhile, a teacher-student framework is employed for self-adaptive learning using the completed annotation dataset. Furthermore, we have designed a Dual-Views loss to leverage different data perspectives, aiding the model in acquiring robust features and enhancing generalization. We carried out experiments using the LUng Nodule Analysis (LUNA) dataset, achieving a sensitivity of 0.574 at a False positives per scan (FPs/scan) of 0.125 with only 10% instance-level annotations for nodules. This performance outperformed comparative methods by 7.00%. Experimental comparisons were conducted to evaluate the performance of our model and human experts on test dataset. The results demonstrate that our model can achieve a comparable level of performance to that of human experts. The comprehensive experimental results demonstrate that FULFIL can effectively leverage an incomplete pulmonary nodule dataset to develop a robust deep learning model, making it a promising tool for assisting in lung nodule detection.

Multi modality fusion transformer with spatio-temporal feature aggregation module for psychiatric disorder diagnosis.

Bipolar disorder (BD) is characterized by recurrent episodes of depression and mild mania. In this paper, to address the common issue of insufficient accuracy in existing methods and meet the requirements of clinical diagnosis, we propose a framework called Spatio-temporal Feature Fusion Transformer (STF2Former). It improves on our previous work - MFFormer by introducing a Spatio-temporal Feature Aggregation Module (STFAM) to learn the temporal and spatial features of rs-fMRI data. It promotes intra-modality attention and information fusion across different modalities. Specifically, this method decouples the temporal and spatial dimensions and designs two feature extraction modules for extracting temporal and spatial information separately. Extensive experiments demonstrate the effectiveness of our proposed STFAM in extracting features from rs-fMRI, and prove that our STF2Former can significantly outperform MFFormer and achieve much better results among other state-of-the-art methods.

Role of Chinese Acupuncture in the Treatment for Chemotherapy-Induced Cognitive Impairment in Older Patients With Cancer: Protocol for a Randomized Controlled Trial.

BACKGROUND: Older patients with cancer experience cognitive impairment and a series of neurocognitive symptoms known as chemobrain due to chemotherapy. Moreover, older populations are disproportionately affected by chemobrain and heightened negative mental health outcomes after cytotoxic chemical drug therapy. Chinese acupuncture is an emerging therapeutic option for chemotherapy-induced cognitive impairment in older patients with cancer, despite limited supporting evidence. OBJECTIVE: Our study aims to directly contribute to the existing knowledge of this novel Chinese medicine mode in older patients with cancer enrolled at the Department of Oncology/Chinese Medicine, Nanjing First Hospital, China, thereby establishing the basis for further research. METHODS: This study involves a 2-arm, prospective, randomized, assessor-blinded clinical trial in older patients with cancer experiencing chemobrain-related stress and treated with Chinese acupuncture from September 30, 2023, to December 31, 2025. We will enroll 168 older patients with cancer with clinically confirmed chemobrain. These participants will be recruited through screening by oncologists for Chinese acupuncture therapy and evaluation. Electroacupuncture will be performed by a registered practitioner of Chinese medicine. The electroacupuncture intervention will take about 30 minutes every session (2 sessions per week over 8 weeks). For the experimental group, the acupuncture points are mainly on the head, limbs, and abdomen, with a total of 6 pairs of electrically charged needles on the head, while for the control group, the acupuncture points are mainly on the head and limbs, with only 1 pair of electrically charged needles on the head. RESULTS: Eligible participants will be randomized to the control group or the experimental group in 1:1 ratio. The primary outcome of this intervention will be the scores of the Montreal Cognitive Assessment. The secondary outcomes, that is, attentional function and working memory will be determined by the Digit Span Test scores. The quality of life of the patients and multiple functional assessments will also be evaluated. These outcomes will be measured at 2, 4, 6, and 8 weeks after the randomization. CONCLUSIONS: This efficacy trial will explore whether Chinese electroacupuncture can prevent chemobrain, alleviate the related symptoms, and improve the quality of life of older patients with cancer who are undergoing or are just going to begin chemotherapy. The safety of this electroacupuncture intervention for such patients will also be evaluated. Data from this study will be used to promote electroacupuncture application in patients undergoing chemotherapy and support the design of further real-world studies. TRIAL REGISTRATION: ClinicalTrials.gov NCT05876988; https://clinicaltrials.gov/ct2/show/NCT05876988. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/53853.

Solution blow spun bilayer chitosan/polylactic acid nanofibrous patch with antibacterial and anti-inflammatory properties for accelerating acne healing.

The quercetin (QC) loaded chitosan (CS) nanofibrous patch (CSQC) was designed and fabricated successfully by solution blow spinning (SBS). And it was employed to explore a functional double-layer nanofibrous patch (CSQC/PLA) with polylactic acid (PLA) for overcoming the resistance of acne-causing bacteria to antibiotics and local cutaneous irritation. The nanofibrous patch possessed a fluffy bilayer structure with good air permeability, which may be befitted from the SBS method. The 10 % QC loaded CSQC0.10/PLA had sustained release ability of QC for 24 h. A high free radical clearance rate (91.18 ± 2.26 %) and robust antibacterial activity against P. acnes (94.4 %) were achieved for CSQC0.10/PLA with excellent biocompatibility. Meanwhile, E. coli and S. aureus were also suppressed with 99.4 % and 99.2 %, respectively. Moreover, the expression of pro-inflammatory cytokines (IL-6 and TNF-α) was significantly reduced, conducive to acne healing. Therefore, the CSQC0.10/PLA bilayer nanofibrous patch designed here may shed some light on developing multifunctional materials for treating acne infectious wounds.

ChatGPT Performs on the Chinese National Medical Licensing Examination.

ChatGPT, a language model developed by OpenAI, uses a 175 billion parameter Transformer architecture for natural language processing tasks. This study aimed to compare the knowledge and interpretation ability of ChatGPT with those of medical students in China by administering the Chinese National Medical Licensing Examination (NMLE) to both ChatGPT and medical students. We evaluated the performance of ChatGPT in three years' worth of the NMLE, which consists of four units. At the same time, the exam results were compared to those of medical students who had studied for five years at medical colleges. ChatGPT's performance was lower than that of the medical students, and ChatGPT's correct answer rate was related to the year in which the exam questions were released. ChatGPT's knowledge and interpretation ability for the NMLE were not yet comparable to those of medical students in China. It is probable that these abilities will improve through deep learning.

An ultrasensitive NIR-IIa' fluorescence-based multiplex immunochromatographic strip test platform for antibiotic residues detection in milk samples.

INTRODUCTION: Widely used in livestock breeding, residues of antibiotic drugs in milk have become a threat to food safety and human health. Current rapid detection technologies using colorimetric immunochromatographic strip tests (IST) lack the necessary sensitivity for on-site trace monitoring. Fluorescence-based detection in the near-infrared IIa' (NIR-IIa') region (1000 âˆ¼ 1300 nm) has enormous potential due to greatly minimized auto-fluorescence and light scattering. OBJECTIVES: The aim of this work is to develop an ultrasensitive IST platform using NIR-IIa' fluorescent nanoparticles as labels for multiplex antibiotic residues detection in milk. METHODS: NIR-IIa' fluorescent nanoparticles were assembled by encapsulating synthesized NIR-IIa' fluorophores into carboxyl - modified polystyrene nanoparticles. The NIR-IIa' nanoparticles were subsequently used as labels in an IST platform to detect sulfonamides, quinolones, and lincomycin simultaneously in milk. A portable fluorescent reader was fabricated to provide on-site detection. To further validate the developed IST platform, the detection was compared with LC-MS/MS in 22 real milk samples. RESULTS: Fluorescent nanoparticles were synthesized with low energy emission (1030 nm) and large Stokes shift (>250 nm) showing a much higher signal-to-noise ratio compared with fluorophores emitting in the NIR-I region. The developed IST platform yielded a highly sensitive, simultaneous quantification of sulfonamides, quinolones, and lincomycin in milk with detection limits of 46.7, 27.6 and 51.4 pg/mL, respectively, achieving a wide detection range (up to 50 ng/mL). The IST platform showed good accuracy, reproducibility, and specificity with the portable fluorescent reader which could rapidly quantify in 10 s. These results were better than reported immunochromatographic assays using fluorescent labels, and remarkably, showed a higher recognition ability than LC-MS/MS for real samples. CONCLUSION: The utility of NIR-IIa' fluorescence-based IST platform for the fast, sensitive, and accurate detection of antibiotics in milk was demonstrated, successfully verifying the potential of this platform in detecting trace materials in complex matrices.

The formation process and mechanism of gastrointestinal anastomosis after retrieval anchor-assisted endoscopic ultrasound-guided gastroenterostomy: a preclinical study.

BACKGROUND AND AIMS: Endoscopic ultrasound-guided gastroenterostomy (EUS-GE) is a promising method of treating gastric outlet obstruction. However, no study has investigated gastrointestinal anastomosis formation after EUS-GE. We aimed to evaluate the formation of gastrointestinal anastomosis after EUS-GE in a porcine model. METHODS: Retrieval anchor-assisted EUS-GE was performed on 15 Bama mini pigs. Five pigs each were randomly euthanized 3, 7, and 14 days postoperatively to evaluate the formation of gastrointestinal anastomosis and measure the anastomotic distance. The expression of transforming growth factor-ß1(TGF-ß1) and Smad3 in the anastomosis site were examined by immunohistochemistry. RESULTS: EUS-GE was successfully performed in all 15 pigs. The mean procedure time was 29.2 ± 6.0 (range 18-40) minutes. The anastomotic distance was 34.0 ± 3.6 cm in 14 pigs. The site of gastroenterostomy of one pig was at the ileum. For pigs euthanized 3 days postoperatively, the structure was mechanically maintained by a stent. For pigs euthanized 7 or 14 days postoperatively, the stomach and small intestine were anastomosed to form a stable structure. The level of TGF-ß1 and Smad3 in the anastomosis site gradually increased from 3 to 14 days after EUS-GE. TGF-ß1 and Smad3 expression had a significant difference between 3 days, 7 days, and 14 days after EUS-GE (P < 0.05). CONCLUSIONS: For EUS-GE, the stomach and small intestine were initially linked together mechanically and spontaneously anastomosed to form a stable structure 7 days postoperatively. TGF-ß1 and Smad3 play an important role in the formation of a stable structure of gastrointestinal anastomosis.

Breaking the Electronic Conductivity Bottleneck of Manganese Oxide Family for High-Power Fluorinated Graphite Composite Cathode by Ligand-Field High-Dimensional Constraining Strategy.

Primary lithium fluorinated graphite (Li/CFx ) batteries with superior energy density are an indispensable energy supply for multiple fields but suffer from sluggish reaction kinetics of the CFx cathode. Designing composite cathodes emerges as a solution to this problem. Despite the optimal composite component for CFx , the manganese oxide family represented by MnO2 is still faced with an intrinsic electronic conductivity bottleneck, which severely limits the power density of the composite cathode. Here, a cation-induced high-dimensional constraining strategy from the perspective of ligand-field stacking structure topological design, which breaks the molecular orbital hybridization of pristine semiconductive oxides to transform them into the high-conductivity metallic state while competitively maintaining structural stability, is proposed. Through first-principles phase diagram calculations, mixed-valent Mn5 O8 ( Mn 2 2 + Mn 3 4 + O 8 ${\rm{Mn}}_2^{2 + }{\rm{Mn}}_3^{4 + }{{\rm{O}}_8}$ ) is explored as an ideal high-dimensional constraining material with satisfied conductivity and large-scale production feasibility. Experiments demonstrate that the as-proposed CFx  @ Mn5 O8 composite cathode achieves 2.36 times the power density (11399 W kg-1 ) of pristine CFx and a higher CFx conversion ratio (86%). Such a high-dimensional field-constraining strategy is rooted in the established four-quadrant electronic structure tuning framework, which fundamentally changes the orbital symmetry under the ligand field to overcome the common conductivity challenge of wide transition metal oxide materials.

Multiplexed evaluation of immunity against SARS-CoV-2 variants using surface enhanced fluorescence from a nanostructured plasmonic chip.

Generated by the immune system post-infection or through vaccination, the effectiveness of antibodies against emerging SARS-CoV-2 variants is crucial for protecting individuals from the COVID-19 pandemic. Herein, a platform for the multiplexed evaluation of SARS-CoV-2 neutralizing antibodies against various variants was designed on the basis of near-infrared (NIR) surface enhanced fluorescence by nano-plasmonic gold chip (pGOLD). Antibody level across variants (Wild-type, Alpha, Beta, Delta, Omicron) was confirmed by the sera from recovered-individuals who were unvaccinated and had infected with Wild-type, Delta, Omicron variants. However, the neutralizing activity against Omicron variant was markedly decreased for individuals infected by Wild-type (~ 5.6-fold) and Delta variant (~ 19.1-fold). To the opposite, neutralizing antibody from individuals recovered from Omicron variant infection showed weak binding strength against non-Omicron variants. Antibody evolution over time was studied with individuals 196-530 days post Wild-type infection. Decreasing IgG antibody titer accompanied by increasing IgG binding avidity with elongated post-infection period were observed for the sera from Wild-type recovered-individuals with different post-infection times, suggesting that after the primary infection, a great number of antibodies were generated and then gradually decreased, while the antibody matured over time. By comparing the IgG level of individuals vaccinated for 27-51 days with individual post-infection, we found that ca. 1 month after two doses of vaccination, the antibody level was comparable to that of 500 days post-infection, and vaccination could enhance IgG avidity more efficiently. This work demonstrated a platform for the multiplexed, high-throughput and rapid screening of acquired immunity against SARS-CoV-2 variants, providing a new approach for the analysis of vaccine effectiveness, immunity against emerging variants, and related serological study.

What makes helpful online mental health information? Empirical evidence on the effects of information quality and responders' effort.

Although online health communities are popular in supporting mental health, factors leading to the helpfulness of mental health information are still under-investigated. Based on the elaboration likelihood model and motivation theory, we incorporate two types of health information-related constructs, i.e., information quality (central route) and responders' effort (peripheral route), and adopt reputation as an extrinsic motivation to build our model. We crawl data from a Chinese online mental health community and extract 11 key variables, and then analyze the model with negative binomial regression. The empirical results indicate that the effect of the length of health information on its helpfulness votes is positively significant, while the effect of readability of health information on its helpfulness votes is relatively negative. In terms of responders' effort, both the timelines of the response and interactive feedback have a significant positive impact on helpfulness of health information votes, while these effects are negatively moderated by the online reputation of responders. This study contributes to the literature on information evaluation mechanisms in online health communities.

Identification and Expression Analysis of the NPF Genes in Cotton.

The NPF (NITRATE TRANSPORTER 1/PEPTIDE TRANSPORTER FAMILY) transports various substrates, including nitrogen (N), which is essential for plant growth and development. Although many NPF homologs have been identified in various plants, limited studies on these proteins have been reported in cotton. This study identified 75, 71, and 150 NPF genes in Gossypium arboreum, G. raimondii, and G. hirsutum, respectively, via genome-wide analyses. The phylogenetic tree indicated that cotton NPF genes are subdivided into eight subgroups, closely clustered with Arabidopsis orthologues. The chromosomal location, gene structure, motif compositions, and cis-elements have been displayed. Moreover, the collinearity analysis showed that whole-genome duplication event has played an important role in the expansion and diversification of the NPF gene family in cotton. According to the transcriptome and qRT-PCR analyses, several GhNPFs were induced by the nitrogen deficiency treatment. Additional functional experiments revealed that virus-induced silencing (VIGS) of the GhNPF6.14 gene affects the growth and N absorption and accumulation in cotton. Thus, this study lays the foundation for further functional characterization of NPF genes in cotton.

Application of the clearance rate of inflammatory markers for evaluation of the therapeutic effect in adult bacterial bloodstream infection.

BACKGROUND: Bloodstream infection (BSI) is a serious systemic infectious disease. This study aimed to investigate the application of the clearance rate of interleukin-6, procalcitonin, and C-reactive protein for the evaluation of antimicrobial efficacy in adult bacterial BSI without other inflammatory factors. METHODS: Patients with positive blood culture and without other inflammatory factors in The First Hospital of Hebei Medical University from January 2017 to December 2019, who received continuous detection interleukin-6, procalcitonin, and C-reactive protein, were selected. The clearance rate of these inflammatory markers was calculated, and the consistency test (kappa test) was performed to analyze the clinical outcomes (cure, improvement, delay, deterioration, or death). RESULTS: For adult patients with bacterial BSI without other inflammatory factors, the testing speculation based on the clearance rate of interleukin-6 and C-reactive protein was consistent with the clinical outcome of the patients, with kappa values of 0.784 and 0.714, respectively (P=0.000). The testing speculation based on the procalcitonin clearance rate was generally consistent with the clinical outcome, with a kappa value of 0.685 (P=0.000). The testing speculation based on the procalcitonin clearance rate showed good consistency with the clinical outcome of patients with Gram-positive cocci infection, kappa =0.813 (P=0.000); for patients with gram-negative bacilli infection, the consistency of clinical outcomes was general, kappa =0.649 (P=0.000). CONCLUSIONS: In adult patients with bacterial BSI without other inflammatory factors, the clearance rate of interleukin-6, procalcitonin, and C-reactive protein can predict the clinical outcome within 24 hours, among which the procalcitonin clearance rate can better predict the clinical outcome of patients with Gram-negative bacilli infection. This approach can be used to evaluate the effectiveness of anti-infection treatment in early-stage BSI.

The CC-NB-LRR protein BSR1 from Brachypodium confers resistance to Barley stripe mosaic virus in gramineous plants by recognising TGB1 movement protein.

Although some nucleotide binding, leucine-rich repeat immune receptor (NLR) proteins conferring resistance to specific viruses have been identified in dicot plants, NLR proteins involved in viral resistance have not been described in monocots. We have used map-based cloning to isolate the CC-NB-LRR (CNL) Barley stripe mosaic virus (BSMV) resistance gene barley stripe resistance 1 (BSR1) from Brachypodium distachyon Bd3-1 inbred line. Stable BSR1 transgenic Brachypodium line Bd21-3, barley (Golden Promise) and wheat (Kenong 199) plants developed resistance against BSMV ND18 strain. Allelic variation analyses indicated that BSR1 is present in several Brachypodium accessions collected from countries in the Middle East. Protein domain swaps revealed that the intact LRR domain and the C-terminus of BSR1 are required for resistance. BSR1 interacts with the BSMV ND18 TGB1 protein in planta and shows temperature-sensitive antiviral resistance. The R390 and T392 residues of TGB1ND (ND18 strain) and the G196 and K197 residues within the BSR1 P-loop motif are key amino acids required for immune activation. BSR1 is the first cloned virus resistance gene encoding a typical CNL protein in monocots, highlighting the utility of the Brachypodium model for isolation and analysis of agronomically important genes for crop improvement.

Sensitively detecting antigen of SARS-CoV-2 by NIR-II fluorescent nanoparticles.

Early detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is an efficient way to prevent the spread of coronavirus disease 2019 (COVID-19). Detecting SARS-CoV-2 antigen can be rapid and convenient, but it is still challenging to develop highly sensitive methods for effective diagnosis. Herein, a lateral flow assay (LFA) based on fluorescent nanoparticles emitting in the second near-infrared (NIR-II) window is developed for sensitive detection of SARS-CoV-2 antigen. Benefiting from the NIR-II fluorescence with high penetration and low autofluorescence, such NIR-II based LFA allows enhanced signal-to-background ratio, and the limit of detection is down to 0.01 ng·mL-1 of SARS-CoV-2 antigen. In the clinical swab sample tests, the NIR-II LFA outperforms the colloidal gold LFA with higher overall percent agreement with the polymerase chain reaction test. The clinical samples with low antigen concentrations (∼ 0.015-∼ 0.068 ng·mL-1) can be successfully detected by the NIR-II LFA, but fail for the colloidal gold LFA. The NIR-II LFA can provide a promising platform for highly sensitive, rapid, and cost-effective method for early diagnosis and mass screening of SARS-CoV-2 infection. Electronic Supplementary Material: Supplementary material (the operation procedure and cost of the materials needed of NIR-II lateral flow assays, the dynamic light scattering spectrum of the NIR-II nanoparticles, the components and testing principle, optimization of main parameters pertaining to the LFA performance, the colloidal gold LFA strip, the fluorescence intensity distribution curves and the T/C values of the strips for clinical samples by NIR-II LFA, and results of clinical swab samples detected by colloidal gold LFA) is available in the online version of this article at 10.1007/s12274-022-4351-1.

The necessarity of treatment for small gastric subepithelial tumors (1-2 cm) originating from muscularis propria: an analysis of 972 tumors.

BACKGROUND AND OBJECTIVES: Up till now, there are still controversies about the specific indication of endoscopic resection for small gastric subepithelial tumors (gSETs) originating from muscularis propria. We aimed to investigate the safety of endoscopic resection and postoperative pathology analysis. METHOD: The patients with primary small gSETs originating from muscularis propria, treated by endoscopic resection in the endoscopic center of Shengjing Hospital between January, 2011 and September, 2019 were enrolled. The complete resection rate, adverse events and clinicopathological features were recorded. RESULT: A total of 936 patients with 972 gastric SETs ≤ 2 cm originating from muscularis propria were included in our study. All the lesions were successfully treated by endoscopic resection. Nearly half of lesions were proved to be gastrointestinal stromal tumor (GIST) [n = 411 (42.3%)] according to postoperative pathology. All the objects were further subdivided into 2 groups, ≤ 1 cm, > 1 and ≤ 2 cm gSETs. The risk of gastric GIST of intermediate/high risk in the group (> 1 and ≤ 2 cm gSETs) is 8.41 times as that of gastric GIST in the group (the size of gastric ≤ 1 cm gSETs) (P < 0.05). CONCLUSION: Endoscopic resection is a safe and effective treatment for small gSETs. gSETs (1-2 cm) is more risky than gSETs (≤ 1 cm) and should be resected. This should be evaluated by further studies.