Electromagnetic fields can regulate the fundamental biological processes involved in bone remodeling. As a non-invasive physical therapy, electromagnetic fields with specific parameters have demonstrated therapeutic effects on bone remodeling diseases, such as fractures and osteoporosis. Electromagnetic fields can be generated by the movement of charged particles or induced by varying currents. Based on whether the strength and direction of the electric field change over time, electromagnetic fields can be classified into static and time-varying fields. The treatment of bone remodeling diseases with static magnetic fields primarily focuses on fractures, often using magnetic splints to immobilize the fracture site while studying the effects of static magnetic fields on bone healing. However, there has been relatively little research on the prevention and treatment of osteoporosis using static magnetic fields. Pulsed electromagnetic fields, a type of time-varying field, have been widely used in clinical studies for treating fractures, osteoporosis, and non-union. However, current clinical applications are limited to low-frequency, and research on the relationship between frequency and biological effects remains insufficient. We believe that different types of electromagnetic fields acting on bone can induce various “secondary physical quantities”, such as magnetism, force, electricity, acoustics, and thermal energy, which can stimulate bone cells either individually or simultaneously. Bone cells possess specific electromagnetic properties, and in a static magnetic field, the presence of a magnetic field gradient can exert a certain magnetism on the bone tissue, leading to observable effects. In a time-varying magnetic field, the charged particles within the bone experience varying Lorentz forces, causing vibrations and generating acoustic effects. Additionally, as the frequency of the time-varying field increases, induced currents or potentials can be generated within the bone, leading to electrical effects. When the frequency and power exceed a certain threshold, electromagnetic energy can be converted into thermal energy, producing thermal effects. In summary, external electromagnetic fields with different characteristics can generate multiple physical quantities within biological tissues, such as magnetic, electric, mechanical, acoustic, and thermal effects. These physical quantities may also interact and couple with each other, stimulating the biological tissues in a combined or composite manner, thereby producing biological effects. This understanding is key to elucidating the electromagnetic mechanisms of how electromagnetic fields influence biological tissues. In the study of electromagnetic fields for bone remodeling diseases, attention should be paid to the biological effects of bone remodeling under different electromagnetic wave characteristics. This includes exploring innovative electromagnetic source technologies applicable to bone remodeling, identifying safe and effective electromagnetic field parameters, and combining basic research with technological invention to develop scientifically grounded, advanced key technologies for innovative electromagnetic treatment devices targeting bone remodeling diseases. In conclusion, electromagnetic fields and multiple physical factors have the potential to prevent and treat bone remodeling diseases, and have significant application prospects.

OBJECTIVE To explore the significance of pharmaceutical care through the diagnosis and treatment of a patient with exogenous insulin autoimmune syndrome （EIAS）， combined with the analysis of literature reports. METHODS Clinical pharmacist participated in the diagnosis and treatment process of one case of EIAS. Based on the characteristics of the patient’s condition， the pharmacist provided medication suggestions and formulated pharmaceutical monitoring measures. At the same time， the pharmacist searched for relevant literature on insulin autoimmune syndrome （IAS） and EIAS， extracted data （gender， age， occurrence time， laboratory tests， clinical symptoms， intervention and outcome）， and conducted analysis. RESULTS Based on the patient’s medication information in the past 3 years， clinical pharmacist determined that the EIAS was likely caused by insulin aspartate 30. The clinician adopted the clinical pharmacist’s suggestion to discontinue insulin and switch to oral hypoglycemic drugs. The patient improved after treatment. The literature analysis showed that among the 257 patients with IAS reported， 212 cases were caused by drugs； among them， 23 cases were caused by lipoic acid， and 56 cases were caused by exogenous insulin. There were no significant differences in age， glycosylated hemoglobin， and body mass index between the two groups. The lowest blood glucose level in the lipoic acid group was significantly lower than that in the exogenous insulin group （P＜0.05）. The proportion of females and the proportion of fasting insulin ≥ 1 000 μU/mL were significantly higher in the lipoic acid group than in the exogenous insulin group （P＜0.05）. CONCLUSIONS Compared with EIAS， lipoic acid-induced IAS usually causes more severe hypoglycemia， and the fasting insulin level is usually higher than 1 000 μU/mL， which is more common in female patients. The participation of clinical pharmacists in the diagnosis and treatment of EIAS can help improve the diagnosis and treatment level of similar rare diseases and ensure the safety of patients’ medication.

Objective To construct large medical model named by "Huaxi HongYi"and explore its application effectiveness in assisting medical record generation. Methods By the way of a full-chain medical large model construction paradigm of "data annotation - model training - scenario incubation", through strategies such as multimodal data fusion, domain adaptation training, and localization of hardware adaptation, "Huaxi HongYi" with 72 billion parameters was constructed. Combined with technologies such as speech recognition, knowledge graphs, and reinforcement learning, an application system for assisting in the generation of medical records was developed. Results Taking the assisted generation of discharge records as an example, in the pilot department, after using the application system, the average completion times of writing a medical records shortened (21 min vs. 5 min) with efficiency increased by 3.2 time, the accuracy rate of the model output reached 92.4%. Conclusion It is feasible for medical institutions to build independently controllable medical large models and incubate various applications based on these models, providing a reference pathway for artificial intelligence development in similar institutions.

Abstract Modern western medicine typically focuses on treating specific symptoms or diseases, and traditional Chinese medicine (TCM) emphasizes the interconnections of the body’s various systems under external environment and takes a holistic approach to preventing and treating diseases. Phenomics was initially introduced to the field of TCM in 2008 as a new discipline that studies the laws of integrated and dynamic changes of human clinical phenomes under the scope of the theories and practices of TCM based on phenomics. While TCM Phenomics 1.0 has initially established a clinical phenomic system centered on Zhenghou (a TCM definition of clinical phenome), bottlenecks remain in data standardization, mechanistic interpretation, and precision intervention. Here, we systematically elaborates on the theoretical foundations, technical pathways, and future challenges of integrating digital medicine with TCM phenomics under the framework of “TCM phenomics 2.0”, which is supported by digital medicine technologies such as artificial intelligence, wearable devices, medical digital twins, and multi-omics integration. This framework aims to construct a closed-loop system of “Zhenghou–Phenome–Mechanism–Intervention” and to enable the digitization, standardization, and precision of disease diagnosis and treatment. The integration of digital medicine and TCM phenomics not only promotes the modernization and scientific transformation of TCM theory and practice but also offers new paradigms for precision medicine. In practice, digital tools facilitate multi-source clinical data acquisition and standardization, while AI and big data algorithms help reveal the correlations between clinical Zhenghou phenomes and molecular mechanisms, thereby improving scientific rigor in diagnosis, efficacy evaluation, and personalized intervention. Nevertheless, challenges persist, including data quality and standardization issues, shortage of interdisciplinary talents, and insufficiency of ethical and legal regulations. Future development requires establishing national data-sharing platforms, strengthening international collaboration, fostering interdisciplinary professionals, and improving ethical and legal frameworks. Ultimately, this approach seeks to build a new disease identification and classification system centered on phenomes and to achieve the inheritance, innovation, and modernization of TCM diagnostic and therapeutic patterns.

The aim of this study was to investigate the contribution of lung zinc ions to pathogenesis of lung ischemia/reperfusion (I/R) injury in rats. Male Sprague Dawley (SD) rats were randomly divided into control group, lung I/R group (I/R group), lung I/R + low-dose zinc chloride group (LZnCl₂+I/R group), lung I/R + high-dose ZnCl₂ group (HZnCl₂+I/R group), lung I/R + medium-dose ZnCl₂ group (MZnCl₂+I/R group) and TPEN+MZnCl₂+I/R group (n = 8 in each group). Inductively coupled plasma mass spectrometry (ICP-MS) was used to measure the concentration of zinc ions in lung tissue. The degree of lung tissue injury was analyzed by observing HE staining, alveolar damage index, lung wet/dry weight ratio and lung tissue gross changes. TUNEL staining was used to detect cellular apoptosis in lung tissue. Western blot and RT-qPCR were used to determine the protein expression levels of caspase-3 and ZIP8, as well as the mRNA expression levels of zinc transporters (ZIP, ZNT) in lung tissue. The mitochondrial membrane potential (MMP) of lung tissue was detected by JC-1 MMP detection kit. The results showed that, compared with the control group, the lung tissue damage, lung wet/dry weight ratio and alveolar damage index were significantly increased in the I/R group. And in the lung tissue, the concentration of Zn²⁺ was markedly decreased, while the cleaved caspase-3/caspase-3 ratio and apoptotic levels were significantly increased. The expression levels of ZIP8 mRNA and protein were down-regulated significantly, while the mRNA expression of other zinc transporters remained unchanged. There was also a significant decrease in MMP. Compared with the I/R group, both MZnCl₂+I/R group and HZnCl₂+I/R group exhibited significantly reduced lung tissue injury, lung wet/dry weight ratio and alveolar damage index, increased Zn²⁺ concentration, decreased ratio of cleaved caspase-3/caspase-3 and apoptosis, and up-regulated expression levels of ZIP8 mRNA and protein. In addition, the MMP was significantly increased in the lung tissue. Zn²⁺ chelating agent TPEN reversed the above-mentioned protective effects of medium-dose ZnCl₂ on the lung tissue in the I/R group. The aforementioned results suggest that exogenous administration of ZnCl₂ can improve lung I/R injury in rats.
Animals ; Reperfusion Injury/pathology* ; Male ; Rats, Sprague-Dawley ; Rats ; Chlorides/administration & dosage* ; Lung/pathology* ; Zinc Compounds/administration & dosage* ; Apoptosis/drug effects* ; Caspase 3/metabolism* ; Cation Transport Proteins/metabolism*

Atractylodes lancea is a perennial herbaceous plant of Asteraceae, with rhizomes for medical use. However, A. lancea plants from different habitats have great variability, and the germplasm resources of A. lancea are unclear and mixed during production. Therefore, it is urgent to protect new varieties of A. lancea. The distinctness, uniformity, and stability(DUS) testing of new plant varieties is the foundation of plant variety protection, and the DUS testing guidelines are the technical basis for variety approval agencies to conduct DUS testing. In this study, the phenotypic traits of 94 germplasm accessions of A. lancea were investigated considering the breeding and variety characteristics of A. lancea in China. The traits were classified and described, and 24 traits were preliminarily determined, including 20 basic traits that must be tested and four traits selected to be tested. The 20 basic traits included 3 quality traits, 5 false quality traits, and 12 quantitative traits, corresponding to 1 plant traits, 2 stem traits, 8 leaf traits, 6 flower traits, and 3 seed traits. The measurement ranges and coefficients of variation of eight quantitative traits were determined, on the basis of which the grading criteria and codes of the traits were determined and assigned. The guidelines has guiding significance for the trait evaluation, utilization, and breeding of new varieties of A. lancea.
Atractylodes/growth & development* ; China ; Phenotype ; Guidelines as Topic ; Plant Breeding

This study explored the potential therapeutic targets and mechanisms of Danggui Shaoyao San(DSS) in the prevention and treatment of Alzheimer's disease(AD) through transcriptomics and metabolomics, combined with animal experiments. Fifty male C57BL/6J mice, aged seven weeks, were randomly divided into the following five groups: control, model, positive drug, low-dose DSS, and high-dose DSS groups. After the intervention, the Morris water maze was used to assess learning and memory abilities of mice, and Nissl staining and hematoxylin-eosin(HE) staining were performed to observe pathological changes in the hippocampal tissue. Transcriptomics and metabolomics were employed to sequence brain tissue and identify differential metabolites, analyzing key genes and metabolites related to disease progression. Reverse transcription-quantitative polymerase chain reaction(RT-qPCR) was employed to validate the expression of key genes. The Morris water maze results indicated that DSS significantly improved learning and cognitive function in scopolamine(SCOP)-induced model mice, with the high-dose DSS group showing the best results. Pathological staining showed that DSS effectively reduced hippocampal neuronal damage, increased Nissl body numbers, and reduced nuclear pyknosis and neuronal loss. Transcriptomics identified seven key genes, including neurexin 1(Nrxn1) and sodium voltage-gated channel α subunit 1(Scn1a), and metabolomics revealed 113 differential metabolites, all of which were closely associated with synaptic function, oxidative stress, and metabolic regulation. RT-qPCR experiments confirmed that the expression of these seven key genes was consistent with the transcriptomics results. This study suggests that DSS significantly improves learning and memory in SCOP model mice and alleviates hippocampal neuronal pathological damage. The mechanisms likely involve the modulation of synaptic function, reduction of oxidative stress, and metabolic balance, with these seven key genes serving as important targets for DSS in the treatment of AD.
Animals ; Alzheimer Disease/genetics* ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Mice ; Mice, Inbred C57BL ; Metabolomics ; Transcriptome/drug effects* ; Maze Learning/drug effects* ; Hippocampus/metabolism* ; Humans ; Disease Models, Animal ; Memory/drug effects*