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.

Studies have suggested that the nucleus accumbens (NAc) is implicated in the pathophysiology of major depression; however, the regulatory strategy that targets the NAc to achieve an exclusive and outstanding anti-depression benefit has not been elucidated. Here, we identified a specific reduction of cyclic adenosine monophosphate (cAMP) in the subset of dopamine D1 receptor medium spiny neurons (D1-MSNs) in the NAc that promoted stress susceptibility, while the stimulation of cAMP production in NAc D1-MSNs efficiently rescued depression-like behaviors. Ketamine treatment enhanced cAMP both in D1-MSNs and dopamine D2 receptor medium spiny neurons (D2-MSNs) of depressed mice, however, the rapid antidepressant effect of ketamine solely depended on elevating cAMP in NAc D1-MSNs. We discovered that a higher dose of crocin markedly increased cAMP in the NAc and consistently relieved depression 24 h after oral administration, but not a lower dose. The fast onset property of crocin was verified through multicenter studies. Moreover, crocin specifically targeted at D1-MSN cAMP signaling in the NAc to relieve depression and had no effect on D2-MSN. These findings characterize a new strategy to achieve an exclusive and outstanding anti-depression benefit by elevating cAMP in D1-MSNs in the NAc, and provide a potential rapid antidepressant drug candidate, crocin.

Polygonum multiflorum （PM）， a commonly used Chinese herbal medicine in clinical practice， has been associated with frequent reports of liver injury in recent years， and the medication safety of PM has attracted more and more attention in China and globally. This article reviews the recent research advances in the signaling pathways and mechanisms of PM in causing drug-induced liver injury （DILI） and aims to provide new ideas for the proper and rational use of PM in clinical practice. The results show that PM is involved in the regulation of various signaling pathways， and it leads to the death of hepatocytes by destroying mitochondrial function， exacerbating bile acid accumulation， and inducing immune response， oxidative stress， and endoplasmic reticulum stress， thereby inducing the development and progression of DILI through multiple targets， pathways， and levels.

Aim To investigate the effect of benzyl iso-thiocyanate (BITC) on the proliferation of mouse U14 cervical cancer cells and to explore the mechanism of cytotoxicity based on transcriptomic data analysis. Methods The effect of BITC on U14 cell activity was detected by MTT, nuclear morphological changes were observed by Hochest 33258 and fluorescent inverted microscope, cell cycle and apoptosis were determined by flow cytometry, and the transcriptome database of U14 cells before and after BITC (20 μmol · L