Irritable bowel syndrome with diarrhea （IBS-D）， as a prototypical disorder involving the microbiota-gut-brain axis， remains poorly understood in terms of its pathogenesis， posing ongoing challenges for clinical diagnosis. Omics technologies， leveraging their high-throughput detection and systematic analysis advantages， has emerged as a critical tool for deciphering the complex mechanisms underlying traditional Chinese medicine （TCM） treatment of IBS-D. This systematic review summarizes the research progress of transcriptomics， proteomics， metabolomics， microbiomics， and multi-omics integration techniques in TCM interventions for IBS-D. In single-omics studies， transcriptomics using techniques like RNA-seq， reveals the regulatory mechanisms of TCM on IBS-related signaling pathways. Proteomics， leveraging quantitative technologies such as 2D-difference gel electrophoresis and tandem mass tag， identifies differentially expressed proteins and elucidates the action targets of TCM in treating IBS-D. Metabolomics， employing methods like UPLC-Q-TOF-MS and LC-MS/MS， discovers metabolic pathways regulated by TCM to improve metabolic disturbances in IBS-D. Microbiomics， based on 16S rRNA sequencing， confirms that TCM can reshape the gut microbiota structure and restore the intestinal microecological balance， thereby improving IBS-D. Multi-omics integration further overcomes the limitations of single-omics approaches by synthesizing information from transcriptomics， proteomics， metabolomics， and microbiomics， enabling a more comprehensive and systematic elucidation of the complex mechanisms underlying TCM treatment for IBS-D. In the future， research related to IBS-D should be advanced from three aspects： stratified clinical research based on TCM syndrome types， multi-omics integration verification mechanisms， and emerging omics to explore new mechanisms， providing more innovative ideas for the precise diagnosis and treatment of this disease.

Objective: To develop a depression recognition model by integrating the spirit-expression diagnostic framework of traditional Chinese medicine (TCM) with machine learning algorithms. The proposed model seeks to establish a TCM-informed tool for early depression screening, thereby bridging traditional diagnostic principles with modern computational approaches. Methods: The study included patients with depression who visited the Shanghai Pudong New Area Mental Health Center from October 1, 2022 to October 1, 2023, as well as students and teachers from Shanghai University of Traditional Chinese Medicine during the same period as the healthy control group. Videos of 3 – 10 s were captured using a Xiaomi Pad 5, and the TCM spirit and expressions were determined by TCM experts (at least 3 out of 5 experts agreed to determine the category of TCM spirit and expressions). Basic information, facial images, and interview information were collected through a portable TCM intelligent analysis and diagnosis device, and facial diagnosis features were extracted using the Open CV computer vision library technology. Statistical analysis methods such as parametric and non-parametric tests were used to analyze the baseline data, TCM spirit and expression features, and facial diagnosis feature parameters of the two groups, to compare the differences in TCM spirit and expression and facial features. Five machine learning algorithms, including extreme gradient boosting (XGBoost), decision tree (DT), Bernoulli naive Bayes (BernoulliNB), support vector machine (SVM), and k-nearest neighbor (KNN) classification, were used to construct a depression recognition model based on the fusion of TCM spirit and expression features. The performance of the model was evaluated using metrics such as accuracy, precision, and the area under the receiver operating characteristic (ROC) curve (AUC). The model results were explained using the Shapley Additive exPlanations (SHAP). Results: A total of 93 depression patients and 87 healthy individuals were ultimately included in this study. There was no statistically significant difference in the baseline characteristics between the two groups (P > 0.05). The differences in the characteristics of the spirit and expressions in TCM and facial features between the two groups were shown as follows. (i) Quantispirit facial analysis revealed that depression patients exhibited significantly reduced facial spirit and luminance compared with healthy controls (P < 0.05), with characteristic features such as sad expressions, facial erythema, and changes in the lip color ranging from erythematous to cyanotic. (ii) Depressed patients exhibited significantly lower values in facial complexion L, lip L, and a values, and gloss index, but higher values in facial complexion a and b, lip b, low gloss index, and matte index (all P < 0.05). (iii) The results of multiple models show that the XGBoost-based depression recognition model, integrating the TCM “spirit-expression” diagnostic framework, achieved an accuracy of 98.61% and significantly outperformed four benchmark algorithms—DT, BernoulliNB, SVM, and KNN (P < 0.01). (iv) The SHAP visualization results show that in the recognition model constructed by the XGBoost algorithm, the complexion b value, categories of facial spirit, high gloss index, low gloss index, categories of facial expression and texture features have significant contribution to the model. Conclusion This study demonstrates that integrating TCM spirit-expression diagnostic features with machine learning enables the construction of a high-precision depression detection model, offering a novel paradigm for objective depression diagnosis.

As new evidence emerges, treatment strategies toward the functional cure of chronic hepatitis B are evolving. In 2019, a panel of national hepatologists published a Consensus Statement on the functional cure of chronic hepatitis B. Currently, an international group of hepatologists has been assembled to evaluate research since the publication of the original consensus, and to collaboratively develop the updated statements. The 2.0 Consensus was aimed to update the original consensus with the latest available studies, and provide a comprehensive overview of the current relevant scientific literatures regarding functional cure of hepatitis B, with a particular focus on issues that are not yet fully clarified. These cover the definition of functional cure of hepatitis B, its mechanisms and barriers, the effective strategies and treatment roadmap to achieve this endpoint, in particular new surrogate biomarkers used to measure efficacy or to predict response, and the appropriate approach to pursuing a functional cure in special populations, the development of emerging antivirals and immunomodulators with potential for curing hepatitis B. The statements are primarily intended to offer international guidance for clinicians in their practice to enhance the functional cure rate of chronic hepatitis B.

Methods: The clinical data of 26 patients diagnosed with irreducible atlantoaxial dislocation complicated by atlantodental bony obstruction were analyzed retrospectively. All patients underwent anterior retropharyngeal atlantodentoplasty, followed by posterior occipitocervical fusion. Details including surgical duration and blood loss volume were recorded. Radiographic data such as the anterior atlantodental interval, O–C2 angle, space available for the cord, clivus–canal angle, and cervical medullary angle, and clinical data including the Japanese Orthopedic Association (JOA) score were assessed. The fusion time of the grafted bone and the development of complications were examined. Results: In patients undergoing anterior retropharyngeal atlantodentoplasty, the surgical duration and blood loss volume were 120.1±16.4 minutes and 100.6±33.5 mL, respectively. The anterior atlantodental interval decreased significantly after the surgery (p <0.001). The O–C2 angle, space available for the cord, clivus–canal angle, and cervical medullary angle increased significantly after the surgery (p <0.001). The JOA score during the latest follow-up significantly increased compared with that before the surgery (p <0.001). The improvement rate of the JOA score was 80.8%±18.1%. The fusion time of the grafted bone was 3–8 months, with an average of 5.7±1.5 months. In total, 11 patients presented with postoperative dysphagia and three with irritating cough. However, none of them exhibited other major complications. Conclusions Anterior retropharyngeal atlantodentoplasty can anatomically reduce the atlantoaxial joint with a satisfactory clinical outcome in patients with irreducible atlantoaxial dislocation with atlantodental bony obstruction.

BACKGROUND:Traumatic brain injury is a condition in which the normal function of the brain is disrupted by a bump or impact to the head.It is necessary to find effective treatments and objective targets that can help doctors diagnose the injury status and restore the brain function of patients. OBJECTIVE:To explore the effect of electroacupuncture combined with low-frequency transcranial ultrasound stimulation on the electroencephalographic signals of rats with traumatic brain injury. METHODS:Forty 6-week-old SPF male Sprague-Dawley rats were randomly divided into five groups:sham group,model group,electroacupuncture group,low-frequency transcranial ultrasound stimulation group and combined group(electroacupuncture+low-frequency transcranial ultrasound stimulation),with eight rats in each group.Feeney weight-drop method was used to establish the animal model of traumatic brain injury.In the sham group,the bone window was only opened without impact.Interventions were started at 1 day after modeling.Electroacupuncture in the electroacupuncture group,low-frequency transcranial ultrasound stimulation in the low-frequency transcranial ultrasound stimulation group,and electroacupuncture+low-frequency transcranial ultrasound stimulation in the combined group were performed for days in total.The modified neurological severity scale score for assessing rats'neurological deficits was performed at 8 hours after modeling.The percentage of spontaneous alternation behavior in the Y-maze was measured at 7 days after modeling.Then,the electroencephalographic signals were collected and electroencephalographic data of α,β,θ,and δ waves were extracted by fast Fourier transform,and the value of oscillation amplitude and energy ratio were calculated in α,β,θ,and δ waves,as well as the Lempel-Ziv complexity and sample entropy. RESULTS AND CONCLUSION:Compared with the sham group,the modified neurological severity scale scores in the model group,electroacupuncture group,low-frequency transcranial ultrasound stimulation group and combined group were significantly increased at 8 hours after modeling(P<0.05).Compared with the sham group,the value of oscillation amplitude in δ wave and the value of δ energy ratio were significantly increased in the model group at 7 days after modeling,meanwhile the percentage of spontaneous alternation behavior in Y-maze,and the value of α/β energy ratio,Lempel-Ziv complexity,and sample entropy were significantly decreased(P<0.05).Compared with the model group,the value of oscillation amplitude in α and δ waves was significantly decreased in the combined group(P<0.05),while the value of α/β energy ratio was significantly increased(P<0.05)and the value of δ energy ratio was significantly decreased(P<0.05)in the electroacupuncture group,low-frequency transcranial ultrasound stimulation group and combined group.Compared with the electroacupuncture group and low-frequency transcranial ultrasound stimulation group,the value of δ energy ratio was significantly decreased in the combined group(P<0.05),while the percentage of spontaneous alternation behavior,the value of α/β energy ratio,the Lempel-Ziv complexity,and the sample entropy were significantly increased(P<0.05).To conclude,abnormal electroencephalographic signals can appear in rats with traumatic brain injury,while the electroacupuncture combined with low-frequency transcranial ultrasound stimulation can alleviate the abnormal electroencephalographic signals in rats,which suggests the electroencephalographic frequency domain value and nonlinear features can be used to assess the severity of traumatic brain injury.

Background Coal workers' pneumoconiosis is a serious occupational disease in China. Exhaled volatile organic compounds (VOCs) can serve as the "breath fingerprint" of internal pathological processes, which provides a theoretical basis for exhaled VOCs to be used as potential non-invasive biomarkers for early diagnosis of coal workers' pneumoconiosis. Objective To screen out the characteristic VOCs and important characteristic VOCs of exhaled air in patients with coal workers' pneumoconiosis, and to explore the potential of these VOCs as biomarkers for early non-invasive diagnosis of the disease. Methods In this study, 27 VOCs in the exhaled breath of 22 patients with stage I coal workers' pneumoconiosis, 77 workers exposed to dust, and 92 healthy controls were quantitatively detected by thermal desorption gas chromatography-mass spectrometry (TD-GC-MS). Substances with P<0.05 in univariate analysis and variable importance projection (VIP) >1 in supervised orthogonal partial least squares discriminant analysis (OPLS-DA) model were selected as the characteristic VOCs for early diagnosis of coal workers' pneumoconiosis. Age was included in the LASSO regression model as a covariate to screen out important characteristic VOCs, and the diagnostic performance was evaluated by receiver operating characteristic (ROC) curve. Spearman correlation was further used to explore the correlation between important characteristic VOCs and clinical lung function indicators. Results Through univariate analysis and OPLS-DA modeling, 8 VOCs were selected, including 2-methylpentane, 3-methylpentane, n-hexane, methylcyclopentane, n-heptane, methylcyclohexane, 4-methyl-2-pentanone, and 2-hexanone, in exhaled breath of patients with coal workers' pneumoconiosis. The concentrations of 4 VOCs, including 3-methylpentane, n-hexane, 4-methyl-2-pentanone, and 2-hexanone, showed a decreasing trend with the increase of dust exposure years. By LASSO regression, the important characteristic VOCs of the coal workers' pneumoconiosis group and the dust exposure group were n-hexane, methylcyclohexane and 4-methyl-2-pentanone, and the important characteristic VOCs of the coal workers' pneumoconiosis group and the healthy group were 2-methyl-pentane and 4-methyl-2-pentanone. The ROC analysis showed that the area under the curve (AUC) of n-hexane, methylcyclohexane, and 4-methyl-2-pentanone were 0.969, 0.909, and 0.956, respectively, and the AUC of combined diagnosis was 0.988 and its Youden index was 0.961, suggesting that these results can serve as a valuable reference for further research on early diagnosis. The Correlation analysis found that there was a positive correlation between n-hexane and lung function indicators in the important characteristic VOCs, indicating that it could indirectly reflect the obstruction of lung function ventilation, further proving that important characteristic VOCs have the potential to monitor lung function decline. Conclusion Three important characteristic VOCs selected in this study have the potential to be used as non-invasive biomarkers for early diagnosis and disease monitoring of coal workers' pneumoconiosis, and are worthy of further study and verification.

Methods: The clinical data of 26 patients diagnosed with irreducible atlantoaxial dislocation complicated by atlantodental bony obstruction were analyzed retrospectively. All patients underwent anterior retropharyngeal atlantodentoplasty, followed by posterior occipitocervical fusion. Details including surgical duration and blood loss volume were recorded. Radiographic data such as the anterior atlantodental interval, O–C2 angle, space available for the cord, clivus–canal angle, and cervical medullary angle, and clinical data including the Japanese Orthopedic Association (JOA) score were assessed. The fusion time of the grafted bone and the development of complications were examined. Results: In patients undergoing anterior retropharyngeal atlantodentoplasty, the surgical duration and blood loss volume were 120.1±16.4 minutes and 100.6±33.5 mL, respectively. The anterior atlantodental interval decreased significantly after the surgery (p <0.001). The O–C2 angle, space available for the cord, clivus–canal angle, and cervical medullary angle increased significantly after the surgery (p <0.001). The JOA score during the latest follow-up significantly increased compared with that before the surgery (p <0.001). The improvement rate of the JOA score was 80.8%±18.1%. The fusion time of the grafted bone was 3–8 months, with an average of 5.7±1.5 months. In total, 11 patients presented with postoperative dysphagia and three with irritating cough. However, none of them exhibited other major complications. Conclusions Anterior retropharyngeal atlantodentoplasty can anatomically reduce the atlantoaxial joint with a satisfactory clinical outcome in patients with irreducible atlantoaxial dislocation with atlantodental bony obstruction.

Patients suffering from stage Ⅳ periodontitis manifest substantial alveolar bone destruction and pronounced tooth loss,fre-quently accompanied by masticatory dysfunction,occlusal disorder and tooth displacement or torsion.Standard periodontal interventions alone are insufficient to stabilize the condition,address masticatory dysfunction,and enhance patients'quality of life.Hence,intricate reconstructive and interdisciplinary regimens,encompassing orthodontic treatment,are often indispensable.Orthodontic therapy can op-timize the masticatory function and esthetic appearance of patients,and promote periodontal well-being.However,individuals with stageⅣ periodontitis present with inadequate periodontal support tissue and a heightened risk profile,rendering their orthodontic management a considerable clinical challenge.This article reviews the orthodontic considerations and optimal timing for intervention in patients with stage Ⅳ periodontitis and presents a representative case of combined periodontal-orthodontic-orthognathic treatment for pe-riodontitis(stage Ⅳ,grade C),in order to provide reference for periodontists and orthodontists.

Nitrogen narcosis is a neurological syndrome that manifests when humans or animals encounter hyperbaric nitrogen, resulting in a range of motor, emotional, and cognitive abnormalities. The anterior cingulate cortex (ACC) is known for its significant involvement in regulating motivation, cognition, and action. However, its specific contribution to nitrogen narcosis-induced hyperlocomotion and the underlying mechanisms remain poorly understood. Here we report that exposure to hyperbaric nitrogen notably increased the locomotor activity of mice in a pressure-dependent manner. Concurrently, this exposure induced heightened activation among neurons in both the ACC and dorsal medial striatum (DMS). Notably, chemogenetic inhibition of ACC neurons effectively suppressed hyperlocomotion. Conversely, chemogenetic excitation lowered the hyperbaric pressure threshold required to induce hyperlocomotion. Moreover, both chemogenetic inhibition and genetic ablation of activity-dependent neurons within the ACC reduced the hyperlocomotion. Further investigation revealed that ACC neurons project to the DMS, and chemogenetic inhibition of ACC-DMS projections resulted in a reduction in hyperlocomotion. Finally, nitrogen narcosis led to an increase in local field potentials in the theta frequency band and a decrease in the alpha frequency band in both the ACC and DMS. These results collectively suggest that excitatory neurons within the ACC, along with their projections to the DMS, play a pivotal role in regulating the hyperlocomotion induced by exposure to hyperbaric nitrogen.
Animals ; Gyrus Cinguli/drug effects* ; Male ; Mice, Inbred C57BL ; Locomotion/drug effects* ; Neurons/drug effects* ; Mice ; Nitrogen/toxicity* ; Inert Gas Narcosis/physiopathology* ; Corpus Striatum/physiopathology*

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks