ObjectiveTo elucidate the critical role of rehabilitation medical records (including electronic records) in rehabilitation medicine's clinical practice and management, comprehensively analyzed the structure, core content and data standards of rehabilitation medical records, to develop a standardized medical record data architecture and core dataset suitable for rehabilitation medicine and to explore the application of rehabilitation data in performance evaluation and payment. MethodsBased on the regulatory documents Basic Specifications for Medical Record Writing and Basic Specifications for Electronic Medical Records (Trial) issued by National Health Commission of China, and referencing the World Health Organization (WHO) Family of International Classifications (WHO-FICs) classifications, International Classification of Diseases (ICD-10/ICD-11), International Classification of Functioning, Disability and Health (ICF), and International Classification of Health Interventions (ICHI Beta-3), this study constructed the data architecture, core content and data standards for rehabilitation medical records. Furthermore, it explored the application of rehabilitation record summary sheets (home page) data in rehabilitation medical statistics and payment methods, including Diagnosis-related Groups (DRG), Diagnosis-Intervention Packet (DIP) and Case Mix Index. ResultsThis study proposed a systematic standard framework for rehabilitation medical records, covering key components such as patient demographics, rehabilitation diagnosis, functional assessment, rehabilitation treatment prescriptions, progress evaluations and discharge summaries. The research analyzed the systematic application methods and data standards of ICD-10/ICD-11, ICF and ICHI Beta-3 in the fields of medical record terminology, coding and assessment. Constructing a standardized data structure and data standards for rehabilitation medical records can significantly improve the quality of data reporting based on the medical record summary sheet, thereby enhancing the quality control of rehabilitation services, effectively supporting the optimization of rehabilitation medical insurance payment mechanisms, and contributing to the establishment of rehabilitation medical performance evaluation and payment based on DRG and DIP. ConclusionStructured rehabilitation records and data standardization are crucial tools for quality control in rehabilitation. Systematically applying the three reference classifications of the WHO-FICs, and aligning with national medical record and electronic health record specifications, facilitate the development of a standardized rehabilitation record architecture and core dataset. Standardizing rehabilitation care pathways based on the ICF methodology, and developing ICF- and ICD-11-based rehabilitation assessment tools, auxiliary diagnostic and therapeutic systems, and supporting terminology and coding systems, can effectively enhance the quality of rehabilitation records and enable interoperability and sharing of rehabilitation data with other medical data, ultimately improving the quality and safety of rehabilitation services.

BACKGROUND:In recent years,deep learning technologies have been increasingly applied in the field of oral medicine,enhancing the efficiency and accuracy of oral imaging analysis and promoting the rapid development of intelligent oral medicine. OBJECTIVE:To elaborate the current research status,advantages,and limitations of deep learning based on oral imaging in the diagnosis and treatment decision-making of oral diseases,as well as future prospects,exploring new directions for the transformation of oral medicine under the backdrop of deep learning technology. METHODS:PubMed was searched for literature related to deep learning in oral medical imaging published from January 2017 to January 2024 with the search terms"deep learning,artificial intelligence,stomatology,oral medical imaging."According to the inclusion criteria,80 papers were finally included for review. RESULTS AND CONCLUSION:(1)Classic deep learning models include artificial neural networks,convolutional neural networks,recurrent neural networks,and generative adversarial networks.Scholars have used these models in competitive or cooperative forms to achieve more efficient interpretation of oral medical images.(2)In the field of oral medicine,the diagnosis of diseases and the formulation of treatment plans largely depend on the interpretation of medical imaging data.Deep learning technology,with its strong image processing capabilities,aids in the diagnosis of diseases such as dental caries,periapical periodontitis,vertical root fractures,periodontal disease,and jaw cysts,as well as preoperative assessments for procedures such as third molar extraction and cervical lymph node dissection,helping clinicians improve the accuracy and efficiency of decision-making.(3)Although deep learning is promising as an important auxiliary tool for the diagnosis and treatment of oral diseases,it still has certain limitations in model technology,safety ethics,and legal regulation.Future research should focus on demonstrating the scalability,robustness,and clinical practicality of deep learning,and finding the best way to integrate automated deep learning decision support systems into routine clinical workflows.

Objective: To explore the associations between caregivers nutrition literacy and pediatric nonalcoholic fatty liver disease (NAFLD), so as to provide scientific evidence for the key contents of family intervention measures. Methods: In September 2022, a study involving 1 609 thirdgrade students and their caregivers from six schools in Yinzhou, Haishu, and Zhenhai Districts of Ningbo City, Zhejiang Province, was conducted. Venous blood samples were collected to measure lipid profiles and investigate the prevalence of nonalcoholic fatty liver disease (NAFLD) among the children. Family Food Environment Questionnaire was used to assess the nutrition literacy levels of the caregivers. Generalized linear regression analysis was employed to explore the correlation between caregivers nutrition literacy levels and the prevalence of NAFLD in children. Results: Among the surveyed students, 191 were in the NAFLD group, whereas 1 418 were in the nonNAFLD group. The median nutrition literacy score of caregivers in the NAFLD group and nonNAFLD group all were 11.00 (9.00,12.00), which was not significantly different (Z=-0.40, P=0.71). The generalized linear regression results revealed that the level of nutrition literacy of caregivers had no significant effect on childrens Triglyceride-glucose (TyG) index and Triglyceride-glucose-Waisttoheight ratio (TyG-WHtR) [β(95%CI) were 0.001(-0.005-0.006) and 0.000(-0.014-0.014), P>0.05]. Conclusions The nutrition literacy level of caregivers has no significant correlation with the direct incidence of NAFLD in children. As for family intervention measures, it is necessary not only to improve the nutrition literacy level of caregivers but also to effectively apply nutritional knowledge in practice to optimize health management.

ObjectiveBased on ultra performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS）， network pharmacology， molecular docking and cell experiments， the active ingredients， possible targets and molecular mechanisms of Baoxin granules（BXG） regulating ferroptosis in the treatment of heart failure（HF） were explored. MethodsBXG intestinal absorption fluid was prepared by everted gut sac and the chemical composition contained therein were identified by UPLC-Q-TOF-MS. According to the obtained components， the potential targets of BXG were predicted， and the HF-related targets and related genes of ferroptosis were retrieved at the same time， and the intersecting targets were obtained by Venn diagram. In addition， the protein-protein interaction（PPI） network and the component-target network were constructed， and the core components and core targets were obtained by topological analysis. Then Gene Ontology（GO） function and Kyoto Encyclopedia of Genes and Genomes（KEGG） enrichment analysis were performed on the core targets， and molecular docking validation of the key targets and main components was carried out by AutoDockTools 1.5.7. H9c2 cells were used to establish a oxygen-glucose deprivation model， and the protective effect of BXG on cells was investigated by detecting cell viability， cell survival rate and reactive oxygen species（ROS） level. The protein expression levels of signal transducer and activator of transcription 3（STAT3）， phosphorylation（p）-STAT3 and glutathione peroxidase 4（GPX4） were detected by Western blot to clarify the regulatory effect of BXG on ferroptosis. ResultsA total of 61 chemical components in BXG intestinal absorption fluid were identified， and network pharmacology obtained 27 potential targets of BXG for the treatment of HF， as well as 139 signaling pathways. BXG may act on core targets such as STAT3， tumor protein p53（TP53）， epidermal growth factor receptor（EGFR）， JUN and prostaglandin-endoperoxide synthase 2（PTGS2） through core components such as glabrolide and limonin， which in turn intervene in lipid and atherosclerosis， phosphatidylinositol 3-kinase/protein kinase B（PI3K/Akt）， endocrine resistance and other signaling pathways to exert therapeutic effects on HF. Molecular docking showed that the docking results of multiple groups of targets and compounds were good. In vitro cell experiments showed that compared with the blank group， the cell viability and survival rate of the model group were significantly decreased， the level of ROS was significantly increased（P<0.01）， the expression levels of STAT3， p-STAT3， p-STAT3/STAT3 and GPX4 proteins were significantly decreased（P<0.05， P<0.01）. Compared with the model group， the cell viability and survival rate of the BXG group were significantly increased， the ROS level was significantly decreased（P<0.01）， the STAT3， p-STAT3， p-STAT3/STAT3 and GPX4 protein levels were significantly increased（P<0.05， P<0.01）. ConclusionBXG may inhibit the occurrence of ferroptosis by up-regulating the expression of STAT3 and GPX4， thus exerting a therapeutic effect on HF， and flavonoids may be the key components of this role.

ObjectiveBased on ultra performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS）， network pharmacology， molecular docking and cell experiments， the active ingredients， possible targets and molecular mechanisms of Baoxin granules（BXG） regulating ferroptosis in the treatment of heart failure（HF） were explored. MethodsBXG intestinal absorption fluid was prepared by everted gut sac and the chemical composition contained therein were identified by UPLC-Q-TOF-MS. According to the obtained components， the potential targets of BXG were predicted， and the HF-related targets and related genes of ferroptosis were retrieved at the same time， and the intersecting targets were obtained by Venn diagram. In addition， the protein-protein interaction（PPI） network and the component-target network were constructed， and the core components and core targets were obtained by topological analysis. Then Gene Ontology（GO） function and Kyoto Encyclopedia of Genes and Genomes（KEGG） enrichment analysis were performed on the core targets， and molecular docking validation of the key targets and main components was carried out by AutoDockTools 1.5.7. H9c2 cells were used to establish a oxygen-glucose deprivation model， and the protective effect of BXG on cells was investigated by detecting cell viability， cell survival rate and reactive oxygen species（ROS） level. The protein expression levels of signal transducer and activator of transcription 3（STAT3）， phosphorylation（p）-STAT3 and glutathione peroxidase 4（GPX4） were detected by Western blot to clarify the regulatory effect of BXG on ferroptosis. ResultsA total of 61 chemical components in BXG intestinal absorption fluid were identified， and network pharmacology obtained 27 potential targets of BXG for the treatment of HF， as well as 139 signaling pathways. BXG may act on core targets such as STAT3， tumor protein p53（TP53）， epidermal growth factor receptor（EGFR）， JUN and prostaglandin-endoperoxide synthase 2（PTGS2） through core components such as glabrolide and limonin， which in turn intervene in lipid and atherosclerosis， phosphatidylinositol 3-kinase/protein kinase B（PI3K/Akt）， endocrine resistance and other signaling pathways to exert therapeutic effects on HF. Molecular docking showed that the docking results of multiple groups of targets and compounds were good. In vitro cell experiments showed that compared with the blank group， the cell viability and survival rate of the model group were significantly decreased， the level of ROS was significantly increased（P<0.01）， the expression levels of STAT3， p-STAT3， p-STAT3/STAT3 and GPX4 proteins were significantly decreased（P<0.05， P<0.01）. Compared with the model group， the cell viability and survival rate of the BXG group were significantly increased， the ROS level was significantly decreased（P<0.01）， the STAT3， p-STAT3， p-STAT3/STAT3 and GPX4 protein levels were significantly increased（P<0.05， P<0.01）. ConclusionBXG may inhibit the occurrence of ferroptosis by up-regulating the expression of STAT3 and GPX4， thus exerting a therapeutic effect on HF， and flavonoids may be the key components of this role.

Traditional development of small protein scaffolds has relied on display technologies and mutation-based engineering, which limit sequence and functional diversity, thereby constraining their therapeutic and application potential. Protein design tools have significantly advanced the creation of novel protein sequences, structures, and functions. However, further improvements in design strategies are still needed to more efficiently optimize the functional performance of protein-based drugs and enhance their druggability. Here, we extended an evolution-based design protocol to create a novel minibinder, BindHer, against the human epidermal growth factor receptor 2 (HER2). It not only exhibits super stability and binding selectivity but also demonstrates remarkable properties in tissue specificity. Radiolabeling experiments with ^99mTc, ⁶⁸Ga, and ¹⁸F revealed that BindHer efficiently targets tumors in HER2-positive breast cancer mouse models, with minimal nonspecific liver absorption, outperforming scaffolds designed through traditional engineering. These findings highlight a new rational approach to automated protein design, offering significant potential for large-scale applications in therapeutic mini-protein development.

High mobility group box 1 (HMGB1), when released extracellularly, plays a pivotal role in the development of spinal cord synapses and exacerbates autoimmune diseases within the central nervous system. In experimental autoimmune encephalomyelitis (EAE), a condition that models multiple sclerosis, the levels of extracellular HMGB1 and interleukin-33 (IL-33) have been found to be inversely correlated. However, the mechanism by which IL-33 deficiency enhances HMGB1 release during EAE remains elusive. Our study elucidates a potential signaling pathway whereby the absence of IL-33 leads to increased binding of P300/CBP-associated factor with HMGB1 in the nuclei of astrocytes, upregulating HMGB1 acetylation and promoting its release from astrocyte nuclei in the spinal cord of EAE mice. Conversely, the addition of IL-33 counteracts the TNF-α-induced increase in HMGB1 and acetylated HMGB1 levels in primary astrocytes. These findings underscore the potential of IL-33-associated signaling pathways as a therapeutic target for EAE treatment.
Animals ; Encephalomyelitis, Autoimmune, Experimental/metabolism* ; Astrocytes/metabolism* ; Interleukin-33/metabolism* ; HMGB1 Protein/metabolism* ; Acetylation ; Mice, Knockout ; Mice, Inbred C57BL ; p300-CBP Transcription Factors/metabolism* ; Mice ; Spinal Cord/metabolism* ; Cells, Cultured ; Female ; Signal Transduction

The biological nitrogen removal technology utilizing heterotrophic nitrification-aerobic denitrification (HN-AD) bacteria has shown effectiveness in wastewater treatment. However, the nitrogen removal efficiency of HN-AD bacteria significantly decreases as the salinity increases. To tackle the challenge of treating high-salt and high-nitrogen wastewater, we isolated a moderately halophilic HN-AD strain 5505 from a salt lake in Xinjiang. The strain was identified based on morphological, physiological, and biochemical characteristics and the 16S rRNA gene sequence. Single-factor experiments were carried out with NH₄⁺-N, NO₃^--N, and NO₂^--N as sole or mixed nitrogen sources to study the nitrifying effect, denitrifying effect, and nitrogen metabolism pathway of the strain. The strain was identified as Halomonas sp.. It can grow in the presence of 1%-25% (W/V) NaCl and exhibited efficient nitrogen removal ability in the presence of 3%-8% NaCl. At the optimal NaCl concentration (8%), the strain showed the NH₄⁺-N, NO₃^--N and NO₂^--N removal rates of 100.0%, 94.11% and 74.43%, respectively. Strain 5505 removed inorganic nitrogen mainly by assimilation, which accounted for over 62.68% of total nitrogen removal. In the presence of mixed nitrogen sources, strain 5505 showed a preference for utilizing ammonia, with a potential HN-AD pathway of NH₄⁺→NH₂OH→NO₂^-→NO₃^-→NO₂^-→NO/N₂O/N₂. The findings provide efficient salt-tolerant bacterial resources, enhance our understanding of biological nitrogen removal, and contribute to the nitrogen removal efficiency improvement in the treatment of high-salt and high-nitrogen wastewater.
Halomonas/classification* ; Nitrogen/isolation & purification* ; Denitrification ; Nitrification ; Wastewater/microbiology* ; Aerobiosis ; Biodegradation, Environmental ; Salinity

Vasovagal syncope is the common type of unexplained syncope,and non-drug therapy is the primary method for its treatment.Till now,there are obvious limitations of western medicine treatment.Vasovagal syncope can be attributed to the category of"syncope syndrome"in the field of traditional Chinese medicine.Professor Wu Wei believes that the fundamental pathogenesis of vasovagal syncope is due to the failure of spleen yang in ascending,and the therapeutic method is to elevate and flourish spleen yang.Professor Wu established the basic formula for elevating spleen yang,which is maily composed of Astragali Radix,Atractylodis Macrocephalae Rhizoma,Codonopsis Radix,Fici Simplicissimae Radix,Citri Reticulatae Pericarpium,Bupleuri Radix,salt-prepared Eucommiae Cortex,wine-prepared Corni Fructus,Psoraleae Fructus,Aconiti Lateralis Radix Preparata,Paeoniae Radix Alba and Zingiberis Rhizoma Recens.The formula has the primary actions of elevating and flourishing spleen yang,and also has the auxiliary effect on nourishing heart,soothing liver and warming kidney.The treatment of vasovagal syncope using the method of elevating and flourishing spleen yang by Professor Wu Wei has achieved satisfactory efficacy,and his experience can provide a reference for the clinical treatment of vasovagal syncope with Chinese medicine.

To address the current issues of data imbalance and scarcity in photoplethysmography (PPG) data for type 2 diabetes mellitus (T2DM) prediction, this study proposes an improved conditional Wasserstein generative adversarial network with gradient penalty (CWGAN-GP). The algorithm integrated gated recurrent unit (GRU) networks and self-attention mechanisms to construct a generator, aiming to produce high-quality PPG signals. Various data augmentation methods, including the improved CWGAN-GP, were employed to expand the PPG dataset, and multiple classifiers were applied for T2DM prediction analysis. Experimental results showed that the model trained on data generated by the improved CWGAN-GP achieved the optimal prediction performance. The highest accuracy reached 0.895 0, and compared with other data enhancement methods, this approach exhibited significant advantages in terms of precision and F1-score. The generated data notably enhances the accuracy and generalization ability of T2DM prediction models, providing a more reliable technical basis for non-invasive early T2DM screening based on PPG signals.
Photoplethysmography/methods* ; Diabetes Mellitus, Type 2/diagnosis* ; Humans ; Algorithms ; Neural Networks, Computer ; Signal Processing, Computer-Assisted ; Prediction Algorithms