As an important part of Chinese traditional culture， the processing technology of traditional Chinese medicine（TCM） carries the wisdom of TCM for thousands of years， and its process is complex and rigorous. With the popularization of modern production technology， traditional processing techiques are facing the dual pressures from technological innovation and production standardization under the perspective of intangible cultural heritage. The modernization of TCM processing technology is an inevitable trend for industrial upgrading， but it cannot be separated from the foundation of traditional skills and ignore the core concepts and cultural values it embodies. Therefore， by analyzing the core characteristics of TCM processing technology and its differences with modern production， this paper discusses the establishment of a synergistic innovation mechanism between traditional techniques and modern technologies， the promotion of joint research and development between scientific research institutes and the industry， the strengthening of standardization of processing techniques， and the enhancement of social education and industry training to improve the recognition and inheritance of processing techniques in order to achieve the goal of innovation and protection of TCM processing technologies in the context of modernization， and to promote the high-quality development of the TCM processing industry.

BACKGROUND: Hepatic inflammatory cell accumulation and the subsequent systematic inflammation drive acute-on-chronic liver failure (ACLF) development. Previous studies showed that the vagus nerve exerts anti-inflammatory activity in many inflammatory diseases. Here, we aimed to identify the key molecule mediating the inflammatory process in ACLF and reveal the neuroimmune communication arising from the vagus nerve and immunological disorders of ACLF. METHODS: Proteomic analysis was performed and validated in ACLF model mice or patients, and intervention animal experiments were conducted using neutralizing antibodies. PNU-282987 (acetylcholine receptor agonist) and vagotomy were applied for perturbing vagus nerve activity. Single-cell RNA sequencing (scRNA-seq), flow cytometry, immunohistochemical and immunofluorescence staining, and clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9) technology were used for in vivo or in vitro mechanistic studies. RESULTS: The unbiased proteomics identified C-X-C motif chemokine ligand 9 (CXCL9) as the greatest differential protein in the livers of mice with ACLF and its relation to the systematic inflammation and mortality were confirmed in patients with ACLF. Interventions on CXCL9 and its receptor C-X-C chemokine receptor 3 (CXCR3) improved liver injury and decreased mortality of ACLF mice, which were related to the suppressing of hepatic immune cells' accumulation and activation. Vagus nerve stimulation attenuated while vagotomy aggravated the expression of CXCL9 and the severity of ACLF. Blocking CXCL9 and CXCR3 ameliorated liver inflammation and increased ACLF-associated mortality in ACLF mice with vagotomy. scRNA-seq revealed that hepatic macrophages served as the major source of CXCL9 in ACLF and were validated by immunofluorescence staining and flow cytometry analysis. Notably, the expression of CXCL9 in macrophages was modulated by vagus nerve-mediated cholinergic signaling. CONCLUSIONS Our novel findings highlighted that the neuroimmune communication of the vagus nerve-macrophage-CXCL9 axis contributed to ACLF development. These results provided evidence for neuromodulation as a promising approach for preventing and treating ACLF.
Animals ; Mice ; Chemokine CXCL9/metabolism* ; Vagus Nerve/physiology* ; Acute-On-Chronic Liver Failure/metabolism* ; Humans ; Male ; Mice, Inbred C57BL ; Proteomics ; Flow Cytometry ; Receptors, CXCR3/metabolism*

Existing emotion recognition research is typically limited to static laboratory settings and has not fully handle the changes in emotional states in dynamic scenarios. To address this problem, this paper proposes a method for dynamic continuous emotion recognition based on electroencephalography (EEG) and eye movement signals. Firstly, an experimental paradigm was designed to cover six dynamic emotion transition scenarios including happy to calm, calm to happy, sad to calm, calm to sad, nervous to calm, and calm to nervous. EEG and eye movement data were collected simultaneously from 20 subjects to fill the gap in current multimodal dynamic continuous emotion datasets. In the valence-arousal two-dimensional space, emotion ratings for stimulus videos were performed every five seconds on a scale of 1 to 9, and dynamic continuous emotion labels were normalized. Subsequently, frequency band features were extracted from the preprocessed EEG and eye movement data. A cascade feature fusion approach was used to effectively combine EEG and eye movement features, generating an information-rich multimodal feature vector. This feature vector was input into four regression models including support vector regression with radial basis function kernel, decision tree, random forest, and K-nearest neighbors, to develop the dynamic continuous emotion recognition model. The results showed that the proposed method achieved the lowest mean square error for valence and arousal across the six dynamic continuous emotions. This approach can accurately recognize various emotion transitions in dynamic situations, offering higher accuracy and robustness compared to using either EEG or eye movement signals alone, making it well-suited for practical applications.
Humans ; Electroencephalography/methods* ; Emotions/physiology* ; Eye Movements/physiology* ; Signal Processing, Computer-Assisted ; Support Vector Machine ; Algorithms

Current studies on electroencephalogram (EEG) emotion recognition primarily concentrate on discrete stimulus paradigms under controlled laboratory settings, which cannot adequately represent the dynamic transition characteristics of emotional states during multi-context interactions. To address this issue, this paper proposes a novel method for emotion transition recognition that leverages a cross-modal feature fusion and global perception network (CFGPN). Firstly, an experimental paradigm encompassing six types of emotion transition scenarios was designed, and EEG and eye movement data were simultaneously collected from 20 participants, each annotated with dynamic continuous emotion labels. Subsequently, deep canonical correlation analysis integrated with a cross-modal attention mechanism was employed to fuse features from EEG and eye movement signals, resulting in multimodal feature vectors enriched with highly discriminative emotional information. These vectors are then input into a parallel hybrid architecture that combines convolutional neural networks (CNNs) and Transformers. The CNN is employed to capture local time-series features, whereas the Transformer leverages its robust global perception capabilities to effectively model long-range temporal dependencies, enabling accurate dynamic emotion transition recognition. The results demonstrate that the proposed method achieves the lowest mean square error in both valence and arousal recognition tasks on the dynamic emotion transition dataset and a classic multimodal emotion dataset. It exhibits superior recognition accuracy and stability when compared with five existing unimodal and six multimodal deep learning models. The approach enhances both adaptability and robustness in recognizing emotional state transitions in real-world scenarios, showing promising potential for applications in the field of biomedical engineering.
Humans ; Emotions/physiology* ; Electroencephalography ; Neural Networks, Computer ; Eye Movements ; Perception

Achieving precise restoration of tooth function and personalized restoration of natural tooth esthetics has always been a significant challenge in direct restorative dentistry. The traditional direct restorative techniques are limited by the subjective operations of dentists, resulting in high technical sensitivity, long operation time, and unpredictable restoration results, making it difficult to meet patients' personalized demands for restoration outcomes. An innovative flowable resin injection technique was introduced in this study. By combining digital design with personalized restoration guides, this technique achieves precise and personalized tooth restoration, thus revolutionizing the traditio-nal paradigm of direct tooth restoration. Specifically, this technique is guided by the patient's subjective aesthetic needs. It utilizes digital technology to pre-design the restoration result and creates a personalized restoration guide. During clinical operation, the dentist needs to only precisely inject the flowable resin into the guide, allowing for rapid completion of the restoration, thereby significantly reducing the operation time and improving the precision and predictability of the restoration. The perfect combination of digital design and flowable resin injection not only significantly improves the precision and predictability of direct tooth restoration but also remarkably shortens the clinical operation time and reduces the requirements for the dentist's technical level, making it widely applicable to the restoration of various tooth defects. Thus, it improves patient satisfaction and reduces the workload of dentists. This innovative restoration technique is expected to become a new productive force in future clinical direct adhesive restorations.
Humans ; Dental Restoration, Permanent/methods* ; Esthetics, Dental ; Composite Resins ; Computer-Aided Design ; Injections

Primary ciliary dyskinesia (PCD) is a clinically rare, genetically and phenotypically heterogeneous condition characterized by chronic respiratory tract infections, male infertility, tympanitis, and laterality abnormalities. PCD is typically resulted from variants in genes encoding assembly or structural proteins that are indispensable for the movement of motile cilia. Here, we identified a novel nonsense mutation, c.466G>T, in cilia- and flagella-associated protein 300 ( CFAP300 ) resulting in a stop codon (p.Glu156*) through whole-exome sequencing (WES). The proband had a PCD phenotype with laterality defects and immotile sperm flagella displaying a combined loss of the inner dynein arm (IDA) and outer dynein arm (ODA). Bioinformatic programs predicted that the mutation is deleterious. Successful pregnancy was achieved through intracytoplasmic sperm injection (ICSI). Our results expand the spectrum of CFAP300 variants in PCD and provide reproductive guidance for infertile couples suffering from PCD caused by them.
Adult ; Female ; Humans ; Male ; Pregnancy ; China ; Ciliary Motility Disorders/genetics* ; Codon, Nonsense ; East Asian People/genetics* ; Exome Sequencing ; Homozygote ; Infertility, Male/genetics* ; Kartagener Syndrome/genetics* ; Pedigree ; Sperm Injections, Intracytoplasmic ; Cytoskeletal Proteins/genetics*

OBJECTIVES: To explore the effect of quercetin for mitigating HIV-1 gp120-induced astrocyte neurotoxicity and its underlying mechanism. METHODS: Primary rat astrocytes were isolated and treated with quercetin, HIV-1 gp120, or gradient concentrations of quercetin combined with HIV-1 gp120. The formation of stress granules (SGs) in the treated cells was observed with immunofluorescence assay, and the levels of oxidative stress markers and protein expressions were measured using specific assay kits and Western blotting. HIV-1 gp120 transgenic mice were treated with quercetin (50 mg/kg) by gavage for 4 weeks, and the changes in cognitive functions and oxidative stress levels were examined by behavioral assessments, oxidative stress index analysis in serum, and immunohistochemical and Western blotting of the brain tissue. RESULTS: In primary rat astrocytes, treatment with quercetin significantly reduced HIV-1 gp120-induced SG formation, increased the levels of antioxidant indexes, decreased the levels of oxidative substances, and up-regulated protein level associated with SG depolymerization. In the transgenic mouse models, quercetin obviously improved the cognitive function of the rats, reduced oxidative stress levels, and promoted the expression of proteins associate with SG depolymerization in the brain tissues. CONCLUSIONS Quercetin mitigates HIV-1 gp120-induced astrocyte neurotoxicity and cognitive function impairment by inhibiting oxidative stress, enhancing expressions of SG depolymerization-related proteins, and promoting SG disassembly, suggesting the value of quercetin as a potential therapeutic agent for neuroprotection in HIV-associated neurocognitive disorders.
Animals ; Quercetin/pharmacology* ; Astrocytes/metabolism* ; HIV Envelope Protein gp120 ; Oxidative Stress/drug effects* ; Rats ; Stress Granules/drug effects* ; Mice ; Mice, Transgenic ; Rats, Sprague-Dawley ; Cells, Cultured

The prevalence of Class III malocclusion varies among different countries and regions. The populations from Southeast Asian countries (Chinese and Malaysian) showed the highest prevalence rate of 15.8%, which can seriously affect oral function, facial appearance, and mental health. As anterior crossbite tends to worsen with growth, early orthodontic treatment can harness growth potential to normalize maxillofacial development or reduce skeletal malformation severity, thereby reducing the difficulty and shortening the treatment cycle of later-stage treatment. This is beneficial for the physical and mental growth of children. Therefore, early orthodontic treatment for Class III malocclusion is particularly important. Determining the optimal timing for early orthodontic treatment requires a comprehensive assessment of clinical manifestations, dental age, and skeletal age, and can lead to better results with less effort. Currently, standardized treatment guidelines for early orthodontic treatment of Class III malocclusion are lacking. This review provides a comprehensive summary of the etiology, clinical manifestations, classification, and early orthodontic techniques for Class III malocclusion, along with systematic discussions on selecting early treatment plans. The purpose of this expert consensus is to standardize clinical practices and improve the treatment outcomes of Class III malocclusion through early orthodontic treatment.
Humans ; Malocclusion, Angle Class III/classification* ; Orthodontics, Corrective/methods* ; Consensus ; Child

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.