ObjectiveTo construct and validate a clinical prediction model for Qi deficiency and blood stasis syndrome in chronic heart failure （CHF），aiming to assist clinical diagnosis and provide tools and methods for individualized treatment of CHF. MethodsThe clinical data of patients with chronic heart failure treated at Dongzhimen Hospital of Beijing University of Chinese Medicine from January 2022 to January 2024 were retrospectively collected. The patients were randomly divided into a training group and a validation group with a ratio of 7∶3. First， the least absolute shrinkage and selection operator （LASSO） regression analysis was used to preliminarily screen the predictive factors affecting the diagnosis of Qi deficiency and blood stasis syndrome in CHF. Subsequently， the Logistic regression method was applied to conduct a more in-depth and detailed analysis of these factors. Variables with P<0.05 in the results of the multi-factor Logistic regression were carefully selected and included. Based on the regression coefficients obtained from this analysis， a model was constructed， and a nomogram was accurately drawn. Using R software，the receiver operating characteristic （ROC） curve，calibration curve，and decision curve analysis （DCA） were precisely drawn. These analyses were used to comprehensively evaluate the model from three crucial aspects： discrimination，calibration，and clinical applicability. Additionally， the accuracy，specificity，sensitivity，positive predictive value，and negative predictive value of the model were meticulously calculated to conduct a more all-round and comprehensive assessment. ResultsIn total， 168 cases were successfully obtained in the training group， and 71 cases were included in the validation group. After a thorough comparison， it was found that there were no statistically significant differences in the baseline data between the two groups. After being rigorously screened by the LASSO-multivariate logistic regression method， dark red tongue，smoking history，cardiac troponin I，and N-terminal pro-B-type natriuretic peptide （NT-ProBNP） were identified as the influencing factors for diagnosing patients with the Qi deficiency and blood stasis syndrome in CHF. The constructed model demonstrated an area under the curve （AUC） of 0.812 in the training group and 0.719 in the validation group. The calibration curve showed that the predicted curve of the model was close to the actual observed curve. DCA indicated that the model could provide substantial clinical benefits for patients at the decision thresholds ranging from 0.2 to 0.9. ConclusionThe clinical prediction model for Qi deficiency and blood stasis syndrome in chronic heart failure constructed in this study shows good performance. It has certain application value in clinical practice， which may contribute to the improvement of the diagnosis and treatment of CHF patients with this syndrome.

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:In the initial stage of growth plate injury inflammation,platelet-derived growth factor BB promotes the repair of growth plate injury by promoting mesenchymal progenitor cell infiltration,chondrogenesis,osteogenic response,and regulating bone remodeling. OBJECTIVE:To elucidate the action mechanism of platelet-derived growth factor BB after growth plate injury. METHODS:PubMed,VIP,WanFang,and CNKI databases were used as the literature sources.The search terms were"growth plate injury,bone bridge,platelet-derived growth factor BB,repair"in English and Chinese.Finally,66 articles were screened for this review. RESULTS AND CONCLUSION:Growth plate injury experienced early inflammation,vascular reconstruction,fibroossification,structural remodeling and other pathological processes,accompanied by the crosstalk of chondrocytes,vascular endothelial cells,stem cells,osteoblasts,osteoclasts and other cells.Platelet-derived growth factor BB,as an important factor in the early inflammatory response of injury,regulates the injury repair process by mediating a variety of cellular inflammatory responses.Targeting the inflammatory stimulation mediated by platelet-derived growth factor BB may delay the bone bridge formation process by improving the functional activities of osteoclasts,osteoblasts,and chondrocytes,so as to achieve the injury repair of growth plate.Platelet-derived growth factor BB plays an important role in angiogenesis and bone repair tissue formation at the injured site of growth plate and intrachondral bone lengthening function of uninjured growth plate.Inhibition of the coupling effect between angiogenesis initiated by platelet-derived growth factor BB and intrachondral bone formation may achieve the repair of growth plate injury.

ObjectiveTo investigate the effects of ethoxysanguinarine （ETH） on angiotensin Ⅱ （Ang Ⅱ）-mediated cardiomyocyte apoptosis and its regulatory effects of inositol-requiring enzyme 1 （IRE1）/regulated IRE1-dependent decay （RIDD） signaling pathway and endoplasmic reticulum stress. MethodsWestern blot was used to detect the establishment of the H9c2 model via Ang Ⅱ stimulation， which was identified as a cardiomyocyte apoptosis model. Subsequently， the inhibitory effect of ETH on cell proliferation was assessed using the cell counting Kit-8 （CCK-8） to determine the optimal effective dose of ETH. H9c2 cardiomyocytes were divided into a blank group， a model group （Ang Ⅱ， 1 mmol·L^-1）， and low-， medium-， and high-dose ETH groups （1.25， 2.5， and 5 mmol·L^-1）. Morphological changes in cardiomyocytes induced by Ang Ⅱ were detected using phalloidin staining. Cardiomyocyte apoptosis was assessed using terminal deoxynucleotidyl transferase dUTP nick and labeling （TUNEL） staining. The apoptosis cycle was detected by Annexin V/PI flow cytometry. Western blot was used to detect the expression levels of apoptosis-related proteins， endoplasmic reticulum stress， and IRE1/RIDD pathway-related proteins. ResultsWestern blot results showed that 1 mmol/mL Ang Ⅱ stimulation significantly increased the protein expression levels of Bip， p-IRE1， and Bid in H9c2 cells （P<0.05， P<0.01）， indicating the induction of endoplasmic reticulum stress， activation of the IRE1/RIDD signaling pathway， and initiation of the apoptosis process. Compared with the blank group， the model group showed a significant increase in the surface area of H9c2 cells and the apoptosis rate of cardiomyocytes， as well as in both early and late apoptosis rates （P<0.01）. The expression levels of Bid， Bax， cleaved-Caspase-3， and cleaved-Caspase-8 proteins were significantly increased， while the expression level of Bcl-2 protein was significantly decreased （P<0.01）. The expression levels of Bip， p-IRE1， and p-RIDD proteins were significantly increased （P<0.05， P<0.01）. Compared with those in the model group， the surface area of cardiomyocytes and the apoptosis rate of cardiomyocytes in all ETH groups were significantly decreased after drug intervention. Both early and late apoptosis rates were significantly decreased. The expression level of cleaved-Caspase-8 was significantly decreased in the low-dose ETH group （P<0.05）. The expression levels of Bid， Bax， and cleaved-Caspase-8 were significantly decreased in the medium-dose ETH group （P<0.05， P<0.01）. The high-dose ETH group significantly reduced the expression levels of Bid， Bax， cleaved-Caspase-3， and cleaved-Caspase-8 （P<0.05， P<0.01） and significantly increased the expression level of Bcl-2 （P<0.05）. The level of p-IRE1 protein in the medium-dose ETH group was significantly decreased （P<0.01）. The expression levels of Bip， p-IRE1， and p-RIDD proteins in the high-dose ETH group were significantly decreased （P<0.05， P<0.01）. ConclusionETH can alleviate Ang Ⅱ-mediated cardiomyocyte apoptosis by inhibiting the IRE1/RIDD signaling pathway and further alleviate the cardiac injury caused by hypertension.

ObjectiveTo investigate the effects of ethoxysanguinarine （ETH） on angiotensin Ⅱ （Ang Ⅱ）-mediated cardiomyocyte apoptosis and its regulatory effects of inositol-requiring enzyme 1 （IRE1）/regulated IRE1-dependent decay （RIDD） signaling pathway and endoplasmic reticulum stress. MethodsWestern blot was used to detect the establishment of the H9c2 model via Ang Ⅱ stimulation， which was identified as a cardiomyocyte apoptosis model. Subsequently， the inhibitory effect of ETH on cell proliferation was assessed using the cell counting Kit-8 （CCK-8） to determine the optimal effective dose of ETH. H9c2 cardiomyocytes were divided into a blank group， a model group （Ang Ⅱ， 1 mmol·L^-1）， and low-， medium-， and high-dose ETH groups （1.25， 2.5， and 5 mmol·L^-1）. Morphological changes in cardiomyocytes induced by Ang Ⅱ were detected using phalloidin staining. Cardiomyocyte apoptosis was assessed using terminal deoxynucleotidyl transferase dUTP nick and labeling （TUNEL） staining. The apoptosis cycle was detected by Annexin V/PI flow cytometry. Western blot was used to detect the expression levels of apoptosis-related proteins， endoplasmic reticulum stress， and IRE1/RIDD pathway-related proteins. ResultsWestern blot results showed that 1 mmol/mL Ang Ⅱ stimulation significantly increased the protein expression levels of Bip， p-IRE1， and Bid in H9c2 cells （P<0.05， P<0.01）， indicating the induction of endoplasmic reticulum stress， activation of the IRE1/RIDD signaling pathway， and initiation of the apoptosis process. Compared with the blank group， the model group showed a significant increase in the surface area of H9c2 cells and the apoptosis rate of cardiomyocytes， as well as in both early and late apoptosis rates （P<0.01）. The expression levels of Bid， Bax， cleaved-Caspase-3， and cleaved-Caspase-8 proteins were significantly increased， while the expression level of Bcl-2 protein was significantly decreased （P<0.01）. The expression levels of Bip， p-IRE1， and p-RIDD proteins were significantly increased （P<0.05， P<0.01）. Compared with those in the model group， the surface area of cardiomyocytes and the apoptosis rate of cardiomyocytes in all ETH groups were significantly decreased after drug intervention. Both early and late apoptosis rates were significantly decreased. The expression level of cleaved-Caspase-8 was significantly decreased in the low-dose ETH group （P<0.05）. The expression levels of Bid， Bax， and cleaved-Caspase-8 were significantly decreased in the medium-dose ETH group （P<0.05， P<0.01）. The high-dose ETH group significantly reduced the expression levels of Bid， Bax， cleaved-Caspase-3， and cleaved-Caspase-8 （P<0.05， P<0.01） and significantly increased the expression level of Bcl-2 （P<0.05）. The level of p-IRE1 protein in the medium-dose ETH group was significantly decreased （P<0.01）. The expression levels of Bip， p-IRE1， and p-RIDD proteins in the high-dose ETH group were significantly decreased （P<0.05， P<0.01）. ConclusionETH can alleviate Ang Ⅱ-mediated cardiomyocyte apoptosis by inhibiting the IRE1/RIDD signaling pathway and further alleviate the cardiac injury caused by hypertension.

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.

Objective To investigate the effectiveness of the integrated schistosomiasis control programme in Sichuan Province during the stage moving from transmission interruption to elimination (2015—2023), so as to provide insights into formulation of the schistosomiasis control measures during the post-elimination stage. Methods Schistosomiasis control data were retrospectively collected from departments of health, agriculture and rural affairs, forestry and grassland, water resources, and natural resources in Sichuan Province from 2015 to 2023, and a database was created to document examinations and treatments of human and livestock schistosomiasis, and snail survey and control, conversion of paddy fields to dry fields, ditch hardening, rivers and lakes management and building of forests for snail control and schistosomiasis prevention. The completion of schistosomiasis control measures was investigated, and the effectiveness was evaluated. Results A total of 20 545 155 person-times received human schistosomiasis examinations in Sichuan Province during the period from 2015 to 2023, and 232 157 person-times were seropositive, with a reduction in the seroprevalence from 2.10% (44 299/2 107 003) in 2015 to 1.12% (9 361/837 896) in 2023 (χ² = 7.68, P < 0.001). The seroprevalence of human schistosomiasis appeared a tendency towards a decline in Sichuan Province over years from 2015 to 2023 (b = −8.375, t = −10.052, P < 0.001); however, no egg positive individuals were identified during the period from 2018 to 2023, with the prevalence of human Schistosoma japonicum infections maintained at 0. Expanded chemotherapy was administered to 2 754 515 person-times, and medical assistance of advanced schistosomiasis was given to 6 436 persontimes, with the treatment coverage increasing from 46.80% (827/1 767) in 2015 to 64.87% (868/1 338) in 2023. Parasitological tests for livestock schistosomiasis were performed in 35 113 herd-times, and expanded chemotherapy was administered to 513 043 herd-times, while the number of fenced livestock decreased from 121 631 in 2015 to 103 489 in 2023, with a reduction of 14.92%. Snail survey covered 433 621.80 hm² in Sichuan Province from 2015 to 2023, with 204 602.81 hm² treated by chemical control and 4 637.74 hm² by environmental modifications. The area of snail habitats decreased from the peak of 5 029.80 hm² in 2016 to 3 709.72 hm² in 2023, and the actual area of snail habitats decreased from the peak of 8 585.48 hm² in 2016 to 473.09 hm² in 2023. The mean density of living snails remained low across the study period except in 2017 (0.62 snails/0.1 m²). Schistosomiasis control efforts by departments of agriculture and rural affairs in Sichuan Province included conversion of paddy fields to dry fields covering 153 346.93 hm², hardening of 6 110.31 km ditches, building of 70 356 biogas digesters, replacement of cattle with 227 161 sets of machines, and captive breeding of 21 161 070 livestock from 2015 to 2023, and the control efforts by departments of water resources included rivers and lakes management measuring 5 676.92 km and renovation of 2 331 irrigation areas, while the control efforts by departments of forestry and grassland included building of forests for snail control and schistosomiasis prevention covering 23 913.33 hm², renovation of snail control forests covering 8 720 hm² and newly building of shelterbelts covering 764 686.67 hm². All 63 endemic counties (cities and districts) had achieved the criterion for schistosomiasis elimination criteria in Sichuan Province by the end of 2023. Conclusion Following the integrated control efforts from 2015 to 2023, remarkable achievements have been obtained in the schistosomiasis control programme in Sichuan Province, with all endemic counties successfully attaining the schistosomiasis elimination target at the county level.

ObjectivePrimary liver cancer, predominantly hepatocellular carcinoma (HCC), is a significant global health issue, ranking as the sixth most diagnosed cancer and the third leading cause of cancer-related mortality. Accurate and early diagnosis of HCC is crucial for effective treatment, as HCC and non-HCC malignancies like intrahepatic cholangiocarcinoma (ICC) exhibit different prognoses and treatment responses. Traditional diagnostic methods, including liver biopsy and contrast-enhanced ultrasound (CEUS), face limitations in applicability and objectivity. The primary objective of this study was to develop an advanced, light-weighted classification network capable of distinguishing HCC from other non-HCC malignancies by leveraging the automatic analysis of brightness changes in CEUS images. The ultimate goal was to create a user-friendly and cost-efficient computer-aided diagnostic tool that could assist radiologists in making more accurate and efficient clinical decisions. MethodsThis retrospective study encompassed a total of 161 patients, comprising 131 diagnosed with HCC and 30 with non-HCC malignancies. To achieve accurate tumor detection, the YOLOX network was employed to identify the region of interest (ROI) on both B-mode ultrasound and CEUS images. A custom-developed algorithm was then utilized to extract brightness change curves from the tumor and adjacent liver parenchyma regions within the CEUS images. These curves provided critical data for the subsequent analysis and classification process. To analyze the extracted brightness change curves and classify the malignancies, we developed and compared several models. These included one-dimensional convolutional neural networks (1D-ResNet, 1D-ConvNeXt, and 1D-CNN), as well as traditional machine-learning methods such as support vector machine (SVM), ensemble learning (EL), k-nearest neighbor (KNN), and decision tree (DT). The diagnostic performance of each method in distinguishing HCC from non-HCC malignancies was rigorously evaluated using four key metrics: area under the receiver operating characteristic (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). ResultsThe evaluation of the machine-learning methods revealed AUC values of 0.70 for SVM, 0.56 for ensemble learning, 0.63 for KNN, and 0.72 for the decision tree. These results indicated moderate to fair performance in classifying the malignancies based on the brightness change curves. In contrast, the deep learning models demonstrated significantly higher AUCs, with 1D-ResNet achieving an AUC of 0.72, 1D-ConvNeXt reaching 0.82, and 1D-CNN obtaining the highest AUC of 0.84. Moreover, under the five-fold cross-validation scheme, the 1D-CNN model outperformed other models in both accuracy and specificity. Specifically, it achieved accuracy improvements of 3.8% to 10.0% and specificity enhancements of 6.6% to 43.3% over competing approaches. The superior performance of the 1D-CNN model highlighted its potential as a powerful tool for accurate classification. ConclusionThe 1D-CNN model proved to be the most effective in differentiating HCC from non-HCC malignancies, surpassing both traditional machine-learning methods and other deep learning models. This study successfully developed a user-friendly and cost-efficient computer-aided diagnostic solution that would significantly enhances radiologists’ diagnostic capabilities. By improving the accuracy and efficiency of clinical decision-making, this tool has the potential to positively impact patient care and outcomes. Future work may focus on further refining the model and exploring its integration with multimodal ultrasound data to maximize its accuracy and applicability.