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.

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.

Objective To investigate the correlation between the expression of the activator of HSP90 ATPase-1(AHA1),lysyl oxidase like-2 protein(LOXL2)in osteosarcoma tissues with mRNA expression of invasion and metastasis genes and their clinical significance.Methods A total of 90 osteosarcoma patients diagnosed and treated in North China Medical and Health Group Fengfeng General Hospital from February 2016 to March 2017 were selected as the research object.The expression of AHA1 mRNA,LOXL2 mRNA and invasion and metastasis genes Wnt family member 9A(Wnt9a)mRNA,zinc finger E-box binding homologous box 1(ZEB1)mRNA,zinc finger E-box binding homologous box 1(ZEB2)mRNA,N-cadherin(N-cad)mRNA,and vimentin(Vim)mRNA in tissues were detected by real-time fluorescence quantitative PCR.Pearson correlation analysis was used for correlation analysis.The differences in expression of AHA1 mRNA and LOXL2 mRNA in osteosarcoma patients among different clinical characteristics were compared.Kaplan-Meier survival analysis was used to analyze the effect of AHA1 mRNA and LOXL2 mRNA on the prognosis of osteosarcoma patients.The prognostic factors of osteosarcoma patients were analyzed by univariate and multivariate COX regression.Results The expressions of AHA1 mRNA(3.16±0.59),LOXL2 mRNA(2.84±0.44)and invasion and metastasis genes[Wnt9a mRNA(3.23±0.42),ZEB1 mRNA(2.73±0.39),ZEB2 mRNA(2.52±0.56),N-cad mRNA(2.71±0.65)and Vim mRNA(2.81±0.73)]in osteosarcoma tissues were higher than those in paracancerous tissues(1.10±0.21,0.95±0.18,0.79±0.15,0.64±0.11,0.98±0.19,0.68±0.14,0.72±0.15),and the differences were statissically significant(t=31.206,37.716,51.903,48.931,24.706,28.964,26.605,all P<0.05).There was a significant positive correlation between AHA1 mRNA and LOXL2 mRNA expression in osteosarcoma(r=0.712,P<0.05).The expressions of AHA1 mRNA and LOXL2 mRNA were significantly positively correlated with the expressions of invasion and metastasis genes(Wnt9a,ZEB1,ZEB2,N-cad,and Vim mRNA)in tumor tissue of osteosarcoma group(r=0.504～0.720,all P<0.05).The expressions of AHA1 mRNA and LOXL2 mRNA in osteosarcoma tissues with Eneeking stage Ⅲ,soft tissue infiltration,and lung metastasis were higher than those in patients with Eneeking stage Ⅰ～Ⅱ,no soft tissue infiltration,and no lung metastasis,with significant differences(t=14.122～171.054,all P<0.05).The 5-year survival rates of patients in the AHA1 mRNA high expression group and low expression group were 36.36%(16/44)and 78.26%(36/46),respectively.The 5-year cumulative survival rate of patients in the AHA1 mRNA high expression group was significantly lower than that in the low expression group(Log-rank χ2=16.081,P<0.05).The 5-year survival rates of patients with high and low expression of LOXL2 mRNA were 34.88%(15/43)and 78.72%(37/47),respectively.The 5-year cumulative survival rate of patients in the LOXL2 mRNA high expression group was significantly lower than that in the low expression group(Log-rank χ2=15.880,P<0.05).Lung metastasis(OR=1.921,P<0.05),Eneeking stage Ⅲ(OR=1.906,P<0.05),AHA1 mRNA high expression(OR=1.405,P<0.05),and LOXL2 mRNA high expression(OR=1.733,P<0.05)were independent risk factors affecting the poor survival prognosis of osteosarcoma patients.Conclusion The expressions of AHA1 mRNA and LOXL2 mRNA in osteosarcoma were increased,and they were correlated with the expression of invasion and metastasis genes,indicating they may be independent risk factors affecting the poor survival and prognosis of osteosarcoma patients.

Objective:To investigate the relationship between preoperative plasma fibrin degradation products (FDP) level and clinicopathological features of patients with completely resected non-small cell lung cancer (NSCLC).Methods:A retrospective case series study was performed. The clinical data of 521 patients who were pathologically diagnosed with NSCLC in Beijing Friendship Hospital Affiliated to Capital Medical University from January 2016 to December 2017 were retrospectively analyzed. Among 521 cases, 406 cases were postoperatively pathologically confirmed as non-lymph node and non-distant metastasis (non-metastasis group) and 115 cases were postoperatively pathologically confirmed as lymph node or distant metastasis (metastasis group). The preoperative FDP level and clinicopathological characteristics as well as the clinicopathological characteristics of NSCLC patients with different FDP levels were compared between the two groups. The correlation between preoperative FDP level and TNM staging was analyzed by using Spearman correlation analysis.Results:Among 521 NSCLC patients, 266 cases were female, 255 cases were male; the age [ M( Q1, Q3)] was 59 years (54 years, 65 years); 441 cases were adenocarcinoma and 70 cases were squamous cell carcinoma. The preoperative median FDP level was 2.78 mg/L (2.35 mg/L, 3.13 mg/L) and 2.99 mg/L (2.56 mg/L, 4.16 mg/L), respectively of NSCLC patients in non-metastasis group and metastasis group, and the difference was statistically significant ( Z = 6.13, P < 0.001). The preoperative FDP level was 2.56 mg/L (2.35 mg/L, 3.20 mg/L) and 2.99 mg/L (2.56 mg/L, 3.20 mg/L), respectively in the early-stage NSCLC (stage Ⅰ-Ⅱ) and advanced NSCLC (stage Ⅲ-Ⅳ) patients, and the difference was statistically significant ( Z = 8.42, P < 0.001). Spearman correlation analysis showed that preoperative FDP level was positively correlated with tumor diameter ( r = 0.287, P < 0.001). There was a positive correlation between preoperative FDP level and the number of metastatic lymph nodes in 115 patients with lymph node metastasis ( r = 0.679, P < 0.001). According to the preoperative median FDP (2.78 mg/L), all patients were divided into FDP ≤2.78 mg/L group and FDP >2.78 mg/L, and there were statistically significant differences in age, metastasis, tumor staging, tumor diameter, the metastatic number of lymph node and histological types of NSCLC patients in both groups (all P < 0.05). Conclusions:The increase of preoperative plasma FDP level may be related to the tumor metastasis and clinical stage of NSCLC patients

As the foremost among the four examinations in traditional Chinese medicine （TCM）， inspection and related equipment research face challenges in landing and transformation due to variations in evidence quality， lack of standardization， insufficient algorithm transparency， and poor reliability and stability of decision-making. Against the backdrop of rapid development of emerging technologies such as big data， the internet of things， and artificial intelligence， coupled with macro policy support from the government， digital and intelligent generalized inspection in TCM has emerged， with the aim of utilizing digital technologies to overcome the limitations of naked-eye inspection and comprehensively perceive and analyze facial and bodily expressions. The research in this field intelligently correlates Zang-fu organ functions with health conditions and disease progression and establishes a technical system for digital and intelligent inspection， multi-dimensional and multimodal perception， fusion analysis， and decision-making. This system aims to enhance the accuracy of disease risk warning and diagnosis， bridging the gap between inspection equipment and assistance in clinical decision-making. From an evidence-based perspective， this paper systematically examines the research ideas of digital and intelligent inspection and the development of related equipment， deeply explores how to propose clinical practice-oriented key scientific issues， comprehensively acquire and co-apply multi-dimensional data， establish precise inspection models driven by digital intelligence， optimize standards to enhance equipment interoperability and reliability， construct post-effect evaluation mechanisms to promote improvement， and actively address potential risks such as the black box nature and information security in the application of intelligent technology. This paper not only demonstrates the tremendous potential of digital technologies in improving the accuracy and clinical application efficiency of inspection but also provides new perspectives and ideas for the modernization of inspection in TCM， paving the way for the application of inspection in the global medical and health field.

Stress is a non-specific adaptive response of organisms to internal and external stimuli,which helps maintain the homeostasis of the body's internal environment.However,when the stress response exceeds the body's adaptation threshold,a variety of diseases will be induced.The morbidity and mortality of breast cancer rank the highest among female malignant tumors.Professor LIN Yi,the first master of traditional Chinese medicine(TCM)in the field of breast diseases who founded the theory of'treating breast diseases from the perspective of six stagnations',believes that six stagnations are the core pathogenesis of breast cancer,and six stagnations are closely related to the body's stress response system.TCM has unique advantages in adjusting the balance of stress homeostasis.By reviewing the classical TCM theory,the theory of'treating breast diseases from the perspective of six depressions'and the modern stress theory,this paper put forward the theory of'stress-based breast cancer prevention & treatment',and expounded the pathogenesis features,pathogenic characteristics and molecular mechanism of stress factors in mediating the development and progression of breast cancer.Moreover,the core idea and treatment principle based on the regulation of stress homeostasis were proposed,and the prescription and medication guided by the theory of'stress-based breast cancer prevention & treatment'were summarized.The establishment of the theory of'stress-based breast cancer prevention & treatment'enriches the theoretical system of breast cancer in TCM,and is expected to provide a new approach for improving the clinical prognosis of breast cancer patients.

Objective:To summarize the key prenatal ultrasound diagnosis features of Apert syndrome, analyze the causes of missed diagnosis and misdiagnosis, and propose corresponding preventive strategies.Methods:A retrospective analysis was made on the medical records and prenatal ultrasound images of 15 fetuses (including 14 cases referred from other hospitals) who underwent prenatal ultrasound examination in Guangdong Women and Children Hospital from August 2014 to May 2022 and were eventually clinically confirmed as Apert syndrome by induction or after birth. By conducting a comparative analysis, particularly focusing on the initial and final diagnoses of referral cases, the key ultrasound diagnostic points of Apert syndrome and the causes for missed and misdiagnosis were summarized.Results:①Diagnostic accuracy: Among the 15 fetuses, 11 cases (73.3%) were correctly diagnosed by prenatal ultrasound and 4 cases (26.7%) were missed diagnosis and misdiagnosis. For the 14 referral cases, only 2 cases (14.3%) were correctly identified in the initial diagnosis at the referring hospital (14.3%), and 12 cases (85.7%) were missed missed diagnosis and misdiagnosis. ②Detection rate of ultrasound signs: In the 15 fetuses with Apert syndrome, the detection rate of " cloverleaf" skull was 13.3% (2/15), premature coronal suture was 66.7% (10/15), the " brain shadowing sign" and flat occiput were both 93.3% (14/15), prominent forehead, hypertelorism and bilateral syndactyly of hands were all 100% (15/15), and bilateral syndactyly of feet was 73.3% (11/15). ③Analysis of missed diagnosis and misdiagnosis: Among the 4 cases of missed diagnosis and misdiagnosis in our hospital, premature closure of coronal suture, " brain shadowing sign", flat occiput and hypertelorism were all not recognized. Among these, 3 cases also missed the prominent forehead, bilateral syndactyly of hands and feet. Additionally, 1 case of bilateral syndactyly of hands was misdiagnosed as partial absence of metacarpals and phalangess.Conclusions:In the prenatal ultrasound diagnosis of fetal Apert syndrome, the symmetric syndactyly of both hands serves as an extremely important diagnostic clue. The " cloverleaf" skull is not common. The premature closure of coronal suture as a direct diagnostic sign with a high detection rate, highlighting its significance in the diagnostic of Apert syndrome. Furthermore, the high detection rates of characteristic ultrasound features such as prominent forehead, flat occiput, " brain shadowing sign" and hypertelorism could help to improve the accuracy of prenatal ultrasound diagnosis for Apert syndrome and effectively reduce missed and misdiagnosis.

Objective To explore the biomarkers and potential mechanisms of chronic restraint stress-induced myocardial injury in hyperlipidemia ApoE-/-mice.Methods The hyperlipidemia combined with the chronic stress model was established by restraining the ApoE-/-mice.Proteomics and bioinformatics techniques were used to describe the characteristic molecular changes and related regulatory mechanisms of chronic stress-induced myocardial injury in hyperlipidemia mice and to explore potential diagnostic biomarkers.Results Proteomic analysis showed that there were 43 significantly up-regulated and 58 sig-nificantly down-regulated differentially expressed proteins in hyperlipidemia combined with the restraint stress group compared with the hyperlipidemia group.Among them,GBP2,TAOK3,TFR1 and UCP1 were biomarkers with great diagnostic potential.KEGG pathway enrichment analysis indicated that fer-roptosis was a significant pathway that accelerated the myocardial injury in hyperlipidemia combined with restraint stress-induced model.The mmu_circ_0001567/miR-7a/Tfr-1 and mmu_circ_0001042/miR-7a/Tfr-1 might be important circRNA-miRNA-mRNA regulatory networks related to ferroptosis in this model.Conclusion Chronic restraint stress may aggravate myocardial injury in hyperlipidemia mice via ferrop-tosis.Four potential biomarkers are selected for myocardial injury diagnosis,providing a new direction for sudden cardiac death(SCD)caused by hyperlipidemia combined with the restraint stress.