Ebstein anomaly (EA) is a rare type of congenital heart defect. Its incidence ranges from 0.005‰ to 0.025‰ among live-born fetuses. It is characterized by the displacement of the septal and posterior leaflets of the tricuspid valve toward the apex of the right ventricle, along with the atrialization and thinning of the right ventricle. Based on the severity of these anatomical features, EA can be classified into four types. The degree of hemodynamic abnormalities mainly depends on factors such as the volume of the atrialized right ventricle, tricuspid regurgitation, and right ventricular function. The main clinical manifestations include: heart failure, cyanosis, and arrhythmia. Echocardiography is the first-choice examination method for confirming the diagnosis. In addition, cardiac magnetic resonance is recognized as the gold standard for evaluating tricuspid regurgitation index and right ventricular function, and it holds significant value in the preoperative diagnosis of EA, treatment decision-making, and postoperative follow-up. Surgical intervention is the primary treatment approach. Although multiple surgical methods exist, the current Cone reconstruction technique is the preferred surgical procedure for this disease. Based on evidence-based data from literature and expert opinions, this article provides a comprehensive summary and recommendations regarding the clinical classification, diagnostic criteria, surgical treatment strategies, management of complications, and prognosis evaluation of EA.

BACKGROUND: Motion sickness is a common transportation issue worldwide. Vestibular dysfunction has been reported to be a key etiology of motion sickness. However, there are limited technologies for alleviating motion sickness. METHODS: The most appropriate frequency (Hz) and level (dBZ) of pure tone for modulation of vestibular function were determined by an ex vivo study using murine utricle explants. The preventive effects of the selected pure tone on motion sickness were then confirmed by using a beam balance test in mice. The alleviating effects of pure tone on motion sickness induced by a swing, driving simulator or real car were objectively assessed by using posturography and electrocardiography (ECG) and were subjectively assessed by using the Motion Sickness Assessment Questionnaire (MSAQ) in humans. RESULTS: The effect of short-term (≤5 min) exposure to a pure tone of 80-85 dBZ (= 60.9-65.9 dBA) at 100 Hz on motion sickness was investigated in mice and humans. A mouse study showed a long-lasting (≥120 min) alleviative effect on shaking-mediated exacerbated beam test scores by 5-min exposure to a pure tone of 85 dBZ at 100 Hz, which was ex vivo determined as a sound activating vestibular function, before shaking. Human studies further showed that 1-min exposure to a pure tone of 80-85 dBZ (= 60.9-65.9 dBA) at 100 Hz before shaking improved the increased envelope areas in posturography caused by the shakings of a swing, a driving simulator and a vehicle. Driving simulator-mediated activation of sympathetic nerves assessed by the heart rate variable (HRV) and vehicle-mediated increased scores of the MSAQ were improved by pure tone exposure before the shaking. CONCLUSION: Since the exacerbated results of posturography and HRV reflect shaking-mediated imbalance and autonomic dysfunction, respectively, the results suggest that the imbalance and autonomic dysregulation in motion sickness could be improved by just 1-min exposure to a pure tone with daily exposable sound pressure levels. TRIAL REGISTRATION Registration number: UMIN000022413 (2016/05/23-2023/04/19) and UMIN000053735 (2024/02/29-present).
Motion Sickness/therapy* ; Animals ; Mice ; Humans ; Male ; Adult ; Female ; Sound ; Middle Aged ; Young Adult ; Mice, Inbred C57BL

Depression,as a severe psychological and psychiatric disorder,significantly impairs the long-term physical and mental health of patients.Current depression detection methods are plagued by strong subjectivity,limited techniques,and inadequate intelligence.Previous studies have mostly relied on single-modal signal analysis,making it difficult to comprehensively reflect the multidimensional characteristics of depression.Based on the independently developed intelligent depression detection system,wearable devices are used to collect prefrontal dual-lead EEG signals,PPG signals,and single-lead ECG signals.Data from 30 patients with depression and 40 healthy controls are collected and analyzed.A multimodal depression recognition model named RBLF-Net is proposed,which integrates spatiotemporal features,weighted attention,and random forests to utilize the multi-signal features for depression recognition.The model exhibits superior performance in the five-fold cross-validation,achieving a classification accuracy of 81.43%,a precision of 81.02%,and a recall rate of 81.25%,outperforming other comparative models,and thus providing an intelligent analysis approach for depression recognition from the perspective of multi-modal fusion.

Objective To analyze changes in intestinal microbiota composition and metabolites in mice with nitrous oxide poisoning using 16S rDNA sequencing and metabolomics,and to examine correlations between gut microbes and metabolites in order to explore the mechanisms of nitrous oxide poisoning.Methods C57BL/6 mice were randomly divided into a control group and a nitrous oxide poisoning group(n=6).The poisoning group was exposed to 90,000 ppm nitrous oxide twice daily for 1 h over 28 days,while the control group was exposed to air.Fecal samples were collected 24 h after the last exposure.16S rDNA sequencing was used to analyze structural differences in microbial communities and identify significantly different taxa.Metabolomics analysis was performed to detect changes in fecal metabolites and identify differential metabolites.Correlation analysis was conducted between differential microbiota and metabolites.Results 16S rDNA sequencing showed that the poisoning group had increased microbial abundance compared with controls,while species diversity remained unchanged.Significant differences were observed in gut microbiota structure between groups.Metabolomics identified 112 differential metabolites related to nitrous oxide poisoning,mainly involving the cAMP signaling pathway and sphingolipid metabolism.Spearman correlation analysis revealed a strong association between differential microbiota and differential metabolites.Conclusion Nitrous oxide poisoning alters the structure and metabolic profiles of intestinal microbiota.Changes in microbial abundance affect multiple metabolic pathways,which may be related to damage to the nervous and hematological systems.These findings provide a basis for further research on the mechanisms of nitrous oxide poisoning and for clinical treatment.

Objective:To investigate gut microbiota differences between individuals with and without colorectal adenoma(CRA)and to identify gut microbes associated with CRA.Methods:This cross-sectional study analyzed the gut microbiota of 100 patients with CRA and 68 individuals without CRA(aged 40-75 years)who underwent colonoscopies between March 2021 and March 2022 at Tianjin Nankai Hospital.Fecal samples were sequenced for the V3-V4 region of the bacterial 16S rRNA gene using the Illumina NovaSeq platform.Results:Compared to the non-CRA group,the CRA group exhibited reduced relative abundances of identified and unidentified Lachnospiraceae,with increased Faecalibacterium and Streptococcus.In the non-CRA group,the relative abundances of Coprococcus,unidentified Clostridiaceae,and Clostridium were higher.LEfSe analysis revealed significant enrichment of Gammaproteobacteria,Proteobacteria,Enterobacteriales,and Faecalibacterium in the CRA group,while the non-CRA group was enriched for Moraxellaceae,Acinetobacter,and Anaerostipes.Conclusions:These findings suggest a discernible disparity in the gut microbiota structure between CRA patients and individuals without adenoma.The enrichment of potential pathogenic taxa,such as Faecalibacterium and Streptococcus,in the CRA group suggests a possible association with adenoma development.

Objective To study the plasma metabolomics of mice poisoned by different dosage of the combination of diazepam and ethanol,and to reveal the toxicological mechanisms of combined poisoning of diazepam and ethanol.Methods Female Kunming mice were randomly divided into blank group,single and combined poisoning group(n=6),Based on the LD50 of diazepam co-administered with graded ethanol doses,mice in the single-drug and combined groups received oral gavage at 1/2,1,and 2 × LD50.Retro-orbital blood samples(～500 μL)were collected within 24 hours post-administration and analyzed by UPLC-QE-MS technology.Principal component analysis and orthogonal partial least squares discriminant analysis were used to identify differential metabolites and associated metabolic pathways.Results A total of 387 differential metabolites were identified in the combined poisoning group of diazepam and ethanol implicating the key pathways including tryptophan metabolism,phenylalanine metabolism,arginine and proline metabolism,Glycerophospholipid metabolism,phenylalanine,tyrosine and tryptophan biosynthesis.Conclusion Combined diazepam and ethanol poisoning exerts significant systemic effects by disrupting neurotransmitters conduction,exacerbating oxidative stress response and dysregulating energy metabolism.

Objective To establish a high-throughput non-targeted screening and prioritization method for emerging pollutants(EPs)in sewage using direct injection high-resolution mass spectrometry(HRMS).Methods The sewage samples were filtered by membrane filter and directly subjected to the liquid chromatography-time-of-flight mass spectrometer based on a method modified from our previous study.A C18 chromatographic column was applied for a gradient elution separation,and accurate mass and mass spectral fragment information were obtained through the MS full scan mode and MS/MS DIA data collection mode.After peak detection and alignment,the features from the raw data through open source software MZmine 3,and then high-throughput screening strategies such as MassBank and PubChem databases were used for compound annotation.Finally,the candidate features were confirmed with chemical standards by compared their retention time and mass spectrum fragmentation ion peaks.Results 13 EPs were identified,including 7 industrial chemicals,4 pharmaceuticals,1 pesticide and 1 metabolite.High detection rates were observed for metformin(86.2％),2-hydroxybenzothiazole(79.3％),1,2-benzisothiazole-3-one(72.4％),and 1,2-benzisothiazole-3-one(72.4％).The quantitative concentration range of EPs was 1.37～19.05 ng/mL,with the high concentrations observed for melamine(19.05 ng/mL)and furosemide(18.49 ng/mL).Ecological risk assessment identified 1,2-benzisothiazol-3-one,4-aminoacetophenone,creatinine,2-hydroxybenzothiazole,and furosemide as key pollutants.Conclusion This direct injection coupled with HRMS workflow enables efficient non-targeted screening and prioritization of emerging EPs in sewage samples,highlighting five ecotoxicologically critical EPs.The methodology enhances environmental monitoring capabilities and provide critical technical support for interdisciplinary research such as environmental forensics and health risk assessment.

Objective:To investigate gut microbiota differences between individuals with and without colorectal adenoma(CRA)and to identify gut microbes associated with CRA.Methods:This cross-sectional study analyzed the gut microbiota of 100 patients with CRA and 68 individuals without CRA(aged 40-75 years)who underwent colonoscopies between March 2021 and March 2022 at Tianjin Nankai Hospital.Fecal samples were sequenced for the V3-V4 region of the bacterial 16S rRNA gene using the Illumina NovaSeq platform.Results:Compared to the non-CRA group,the CRA group exhibited reduced relative abundances of identified and unidentified Lachnospiraceae,with increased Faecalibacterium and Streptococcus.In the non-CRA group,the relative abundances of Coprococcus,unidentified Clostridiaceae,and Clostridium were higher.LEfSe analysis revealed significant enrichment of Gammaproteobacteria,Proteobacteria,Enterobacteriales,and Faecalibacterium in the CRA group,while the non-CRA group was enriched for Moraxellaceae,Acinetobacter,and Anaerostipes.Conclusions:These findings suggest a discernible disparity in the gut microbiota structure between CRA patients and individuals without adenoma.The enrichment of potential pathogenic taxa,such as Faecalibacterium and Streptococcus,in the CRA group suggests a possible association with adenoma development.

Objective To study the plasma metabolomics of mice poisoned by different dosage of the combination of diazepam and ethanol,and to reveal the toxicological mechanisms of combined poisoning of diazepam and ethanol.Methods Female Kunming mice were randomly divided into blank group,single and combined poisoning group(n=6),Based on the LD50 of diazepam co-administered with graded ethanol doses,mice in the single-drug and combined groups received oral gavage at 1/2,1,and 2 × LD50.Retro-orbital blood samples(～500 μL)were collected within 24 hours post-administration and analyzed by UPLC-QE-MS technology.Principal component analysis and orthogonal partial least squares discriminant analysis were used to identify differential metabolites and associated metabolic pathways.Results A total of 387 differential metabolites were identified in the combined poisoning group of diazepam and ethanol implicating the key pathways including tryptophan metabolism,phenylalanine metabolism,arginine and proline metabolism,Glycerophospholipid metabolism,phenylalanine,tyrosine and tryptophan biosynthesis.Conclusion Combined diazepam and ethanol poisoning exerts significant systemic effects by disrupting neurotransmitters conduction,exacerbating oxidative stress response and dysregulating energy metabolism.

Objective To establish a high-throughput non-targeted screening and prioritization method for emerging pollutants(EPs)in sewage using direct injection high-resolution mass spectrometry(HRMS).Methods The sewage samples were filtered by membrane filter and directly subjected to the liquid chromatography-time-of-flight mass spectrometer based on a method modified from our previous study.A C18 chromatographic column was applied for a gradient elution separation,and accurate mass and mass spectral fragment information were obtained through the MS full scan mode and MS/MS DIA data collection mode.After peak detection and alignment,the features from the raw data through open source software MZmine 3,and then high-throughput screening strategies such as MassBank and PubChem databases were used for compound annotation.Finally,the candidate features were confirmed with chemical standards by compared their retention time and mass spectrum fragmentation ion peaks.Results 13 EPs were identified,including 7 industrial chemicals,4 pharmaceuticals,1 pesticide and 1 metabolite.High detection rates were observed for metformin(86.2％),2-hydroxybenzothiazole(79.3％),1,2-benzisothiazole-3-one(72.4％),and 1,2-benzisothiazole-3-one(72.4％).The quantitative concentration range of EPs was 1.37～19.05 ng/mL,with the high concentrations observed for melamine(19.05 ng/mL)and furosemide(18.49 ng/mL).Ecological risk assessment identified 1,2-benzisothiazol-3-one,4-aminoacetophenone,creatinine,2-hydroxybenzothiazole,and furosemide as key pollutants.Conclusion This direct injection coupled with HRMS workflow enables efficient non-targeted screening and prioritization of emerging EPs in sewage samples,highlighting five ecotoxicologically critical EPs.The methodology enhances environmental monitoring capabilities and provide critical technical support for interdisciplinary research such as environmental forensics and health risk assessment.