Liver cancer is one of the most common malignant tumors in the digestive system and ranks sixth among newly diagnosed malignant tumors worldwide. Transforming growth factor-β （TGF-β） regulates cell differentiation， proliferation， apoptosis， and other physiological and pathological mechanisms and exerts cancer-suppressive and pro-cancerous dual effects in the process of tumor development. In recent years， with the continuous exploration of the mechanism of liver cancer， it has been found that the conversion of the cancer-suppressive effect into a pro-cancerous effect of this pathway plays a key role in the development of liver cancer. Traditional Chinese medicine （TCM） provides a unique perspective for the classification， diagnosis， and treatment of liver cancer with its comprehensive regulatory effects of multi-components， multi-targets， and multi-pathways. This paper summarized that the cancer-suppressive mechanisms of the TGF-β signaling pathway included promoting cancer cell cycle arrest， apoptosis， autophagy， et al， while the pro-cancerous mechanisms included promoting cancer cell proliferation， invasion and metastasis， immunosuppression， angiogenesis， et al. The TCM compounds intervening this pathway were sorted out， including Jianpi Huayu compound， Fuyang Baoyuan compound， Yipi Yanggan compound， Fuzheng Jiedu compound， compound Astragalus and Salvia， Biejia Jianwan， Dahuang Zhechong pill， and Qingxiang powder. The single TCMs mainly included Schizocapsa plantaginea， Dendrobii Caulis， Gleditsia sinensis， and Dracaena cochinchinensis. The active ingredients of TCM are mainly concentrated on flavonoids， alkaloids， glycosides， phenolics， terpenoids， polysaccharides， and other kinds of compounds. At the same time， it summarized that the liver cancer inhibition mechanism of TCM by regulating this pathway mainly included promoting apoptosis of liver cancer cells， blocking the cell cycle， and inhibiting liver cancer cell proliferation， migration， invasion， angiogenesis， immune escape， etc. The mechanism aims to give full play to the advantages of TCM and precisely regulate the TGF-β signal， thereby exerting positive anti-tumor effects， opening up a new direction for the precise targeted treatment of liver cancer， and providing a scientific basis and a new strategy for the application of TCM in the treatment of liver cancer.

Liver cancer is one of the most common malignant tumors in the digestive system and ranks sixth among newly diagnosed malignant tumors worldwide. Transforming growth factor-β （TGF-β） regulates cell differentiation， proliferation， apoptosis， and other physiological and pathological mechanisms and exerts cancer-suppressive and pro-cancerous dual effects in the process of tumor development. In recent years， with the continuous exploration of the mechanism of liver cancer， it has been found that the conversion of the cancer-suppressive effect into a pro-cancerous effect of this pathway plays a key role in the development of liver cancer. Traditional Chinese medicine （TCM） provides a unique perspective for the classification， diagnosis， and treatment of liver cancer with its comprehensive regulatory effects of multi-components， multi-targets， and multi-pathways. This paper summarized that the cancer-suppressive mechanisms of the TGF-β signaling pathway included promoting cancer cell cycle arrest， apoptosis， autophagy， et al， while the pro-cancerous mechanisms included promoting cancer cell proliferation， invasion and metastasis， immunosuppression， angiogenesis， et al. The TCM compounds intervening this pathway were sorted out， including Jianpi Huayu compound， Fuyang Baoyuan compound， Yipi Yanggan compound， Fuzheng Jiedu compound， compound Astragalus and Salvia， Biejia Jianwan， Dahuang Zhechong pill， and Qingxiang powder. The single TCMs mainly included Schizocapsa plantaginea， Dendrobii Caulis， Gleditsia sinensis， and Dracaena cochinchinensis. The active ingredients of TCM are mainly concentrated on flavonoids， alkaloids， glycosides， phenolics， terpenoids， polysaccharides， and other kinds of compounds. At the same time， it summarized that the liver cancer inhibition mechanism of TCM by regulating this pathway mainly included promoting apoptosis of liver cancer cells， blocking the cell cycle， and inhibiting liver cancer cell proliferation， migration， invasion， angiogenesis， immune escape， etc. The mechanism aims to give full play to the advantages of TCM and precisely regulate the TGF-β signal， thereby exerting positive anti-tumor effects， opening up a new direction for the precise targeted treatment of liver cancer， and providing a scientific basis and a new strategy for the application of TCM in the treatment of liver cancer.

OBJECTIVE To determine the species,quantity,and dispersion patterns of airborne pollen in two districts and five counties of Handan City,Hebei Province.METHODS The gravity sedimentation method was employed from October 1,2023,to September 30,2024,for daily and consecutive pollen exposure slides in two districts(Congtai District and Yongnian District)and five counties(Qiu County,Daming County,Cheng'an County,Cixian County,and She County)of Handan City,Hebei Province.The types of pollen were counted and identified under an optical microscope,and the pollen data were statistically analyzed.RESULTS The annual pollen quantity in the two districts and five counties of Handan City ranged from 24 031 grains/1 000 mm2 to 85 131 grains/1 000 mm2.The dissemination of major allergenic pollen presented two peaks.The first peak occurred in spring(March to April),mainly composed of Platanus(25.15％),Broussonetia(13.61％),Pinus(8.48％);the second peak occurred in(August to September),mainly consisting of Humulus/Cannabis(13.71％)and Artemisia(8.44％).Pollen in spring was significantly higher than that in summer and autumn.CONCLUSION The major allergenic airborne pollen in the two districts and five counties of Handan City exhibited two peaks in spring and summer-autumn,with Platanus pollen,Broussonetia pollen,Pinus pollen,Humulus/Cannabis pollen,and Artemisia pollne being the dominant pollen types.Among them,Platanus pollen was the absolute dominant pollen in this region.

Early screening of tumors is crucial for prevention and treatment of cancer,thus identifying effective biomarkers is of great importance for early diagnosis of tumors.In recent years,tumor-secreted exosomes(Exos)have attracted widespread attention as a novel biomarker for tumor liquid biopsy.Especially,some specific proteins contained in Exos play important roles in the occurrence,development,metastasis and microenvironment regulation of tumors,indicating their enormous potential as potential diagnostic biomarkers for tumors.Compared to traditional biopsy sample testing,exosome-based protein detection methods exhibit significant advantages in liquid biopsy,including rapid sampling,easy operation,non-invasiveness,and feasibility for early detection,holding important application value for clinical diagnosis of tumors.This review aimed to comprehensively summarize and discuss various detection strategies for exosomal proteins in liquid biopsy for tumors,while comprehensively evaluating the analytical performance of these methods.Meanwhile,new perspectives and strategies for early diagnosis and treatment of tumors were discussed.Additionally,the unique advantages of exosomal proteins as a new generation of non-invasive diagnostic biomarkers and insights into their promising prospects for future clinical applications were emphasized.

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.

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.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.