Ultrasound Spectral Combined With Clinical Pathological Parameters in Prediction of Axillary Lymph Node Metastatic in Breast Cancer.

OBJECTIVES: To explore the clinical value of the nomogram based on ultrasound spectral combined with clinical pathological parameter in predicting axillary lymph node metastasis in breast cancer. METHODS: We prospectively gathered clinicopathologic and ultrasonic data from 240 patients confirmed breast cancer. The risk factors of axillary lymph node metastasis were analyzed by univariate and multivariate logistic regression, and the prediction model was established. The model calibration, predictive ability, and diagnostic efficiency in the training set and the testing set were analyzed by receiver operating characteristic curve and calibration curve analysis, respectively. RESULTS: Univariate analysis showed that lymph node metastasis was related with tumor size, Ki-67, axillary ultrasound, ultrasound spectral quantitative parameter, internal echo, and calcification (P < .05). Multivariate logistic regression analysis showed that the Ki-67, axillary ultrasound, quantitative parameter (the mean of the mid-band fit in tumor and posterior tumor) were independent risk factors of axillary lymph node metastasis (P < .05). The models developed using Ki-67, axillary ultrasound, and quantitative parameters for predicting axillary lymph node metastasis demonstrated an area under the receiver operating characteristic curve of 0.83. Additionally, the prediction model exhibited outstanding predictability for axillary lymph node metastasis, as evidenced by a Harrell C-index of 0.83 (95% confidence interval 0.73-0.93). CONCLUSION: Axillary ultrasound combined with Ki-67 and ultrasound spectral parameters has the potential to predict axillary lymph node metastasis in breast cancer, which is superior to axillary ultrasound alone.

Predicting axillary lymph node metastasis in breast cancer based on ultrasound radiofrequency time-series analysis.

BACKGROUND: The status of axillary lymph nodes (ALN) plays a critical role in the management of patients with breast cancer. It is an urgent demand to develop highly accurate, non-invasive methods for predicting ALN status. PURPOSE: To evaluate the efficacy of ultrasound radiofrequency (URF) time-series parameters, in combination with clinical data, in predicting ALN metastasis in patients with breast cancer. MATERIAL AND METHODS: We prospectively gathered clinicopathologic and ultrasonic data from patients diagnosed with breast cancer. Various machine-learning (ML) models were developed using all available features to determine the most efficient diagnostic model. Subsequently, distinct prediction models were created using the optimal ML model, and their diagnostic performances were evaluated and compared. RESULTS: The study encompassed 240 patients, of whom 88 had lymph node metastases. A leave-one-out cross-validation (LOOCV) method was used to split the entire dataset into training and testing subsets. The random forest ML model outperformed the other algorithms, with an area under the curve (AUC) of 0.92. Prediction models based on clinical, ultrasonic, URF parameters, clinical + ultrasonic, clinical + URF, and ultrasonic + URF parameters had AUCs of 0.56, 0.79, 0.78, 0.90, 0.80, and 0.84, respectively, in the testing set. The comprehensive diagnostic model (clinical + ultrasonic + URF parameters) demonstrated strong diagnostic capability, with an AUC of 0.94 in the testing set, exceeding any single prediction model. CONCLUSION: The combined model (clinical + ultrasonic + URF parameters) could be used preoperatively to predict lymph node status, offering valuable input for the design of individualized surgical approaches.

Artificial neural network prediction of postoperative complications in papillary thyroid microcarcinoma based on preoperative ultrasonographic features.

OBJECTIVE: To predict post-thyroidectomy complications in papillary thyroid microcarcinoma (PTMC) patients using a deep learning model based on preoperative ultrasonographic features. This study addresses the global rise in PTMC incidence and the challenges in treatment decision-making with high-resolution ultrasonography. METHOD: This study enrolled 1638 patients with clinically staged cN0 PTMC who received surgical treatment from 1997 to 2019 at Beijing Friendship Hospital. Deep learning model was developed using fully connected neural network. Feature selection included 1000 iterations of Bootstrap sampling and Recursive Feature Elimination (RFE) to identify the top 10 features. Data preprocessing involved normalization and imputation for missing values. SMOTE addressed class imbalance. The model was trained and tested on random data split, with performance metrics including Accuracy (ACC), Area Under the Curve (AUC), Sensitivity (SEN), and Specificity (SPE), visualized through a ROC curve and confusion matrix. RESULTS: The fully connected deep neural network model demonstrated high accuracy (ACC 0.81), Area Under the Curve (AUC 0.74), sensitivity (SEN 0.65), and specificity (SPE 0.83) and visualized by ROC curve and confusion matrix. These results highlight the model's reliability and potential as an effective tool in predicting postoperative complications and assisting in clinical decision-making for PTMC patients. CONCLUSION: This study highlights the potential of deep learning in enhancing medical predictions and personalized healthcare. Despite promising results, limitations include a single-center data source and unconsidered factors like lifestyle and genetics. Future research should expand data sources, include more influencing factors, and refine algorithms to improve accuracy and applicability in thyroid cancer treatment.

Divergent Synthesis of 17-nor-Cephalotane Diterpenoids through Developed Ynol-diene Cyclization.

On the basis of a novel ynol-diene cyclization developed as a rapid access to tropone unit, the first divergent strategy to 17-nor-cephalotane diterpenoids has been successfully established. Combining with a bioinspired stereoselective dual hydrogenation, the divergent total synthesis of (+)-3-deoxyfortalpinoid F, (+)-harringtonolide, (-)-fortalpinoids M/N/P, and analog (-)-20-deoxocephinoid P have been achieved in 14-17 linear longest steps starting from commercially available materials.

Spectral analysis enhanced net (SAE-Net) to classify breast lesions with BI-RADS category 4 or higher.

Early ultrasound screening for breast cancer reduces mortality significantly. The main evaluation criterion for breast ultrasound screening is the Breast Imaging-Reporting and Data System (BI-RADS), which categorizes breast lesions into categories 0-6 based on ultrasound grayscale images. Due to the limitations of ultrasound grayscale imaging, lesions with categories 4 and 5 necessitate additional biopsy for the confirmation of benign or malignant status. In this paper, the SAE-Net was proposed to combine the tissue microstructure information with the morphological information, thus improving the identification of high-grade breast lesions. The SAE-Net consists of a grayscale image branch and a spectral pattern branch. The grayscale image branch used the classical deep learning backbone model to learn the image morphological features from grayscale images, while the spectral pattern branch is designed to learn the microstructure features from ultrasound radio frequency (RF) signals. Our experimental results show that the best SAE-Net model has an area under the receiver operating characteristic curve (AUROC) of 12% higher and a Youden index of 19% higher than the single backbone model. These results demonstrate the effectiveness of our method, which potentially optimizes biopsy exemption and diagnostic efficiency.

Roundup® induces premature senescence of mouse granulosa cells via mitochondrial ROS-triggered NLRP3 inflammasome activation.

Roundup, a glyphosate-based herbicide widely used in agriculture, has raised concerns regarding its potential impact on human health due to the detection of its residues in human urine and serum. Granulosa cells are essential for oocyte growth and follicle development. Previous research has shown that Roundup could affect steroid synthesis, increases oxidative stress, and induces apoptosis in granulosa cells. However, little is known about the effects of Roundup on NLRP3 (nucleotide binding oligomerization domain-like receptor family pyrin-containing domain protein 3) inflammasome activation and cellular senescence in granulosa cells. Here, we provided evidence that exposure to Roundup induced premature senescence in mouse granulosa cells through the activation of NLRP3 inflammasome triggered by mitochondrial ROS. Our findings demonstrated that Roundup significantly reduced the viability of granulosa cells under in vitro culture conditions. It also disrupted mitochondrial function and induced oxidative stress in these cells. Subsequent investigations showed that NLRP3 inflammasome was activated in treated granulosa cells, as evidenced by the upregulation of inflammasome-related genes and the processing of inflammatory cytokines IL-1ß and IL-1α into their mature forms. Consequently, premature cellular senescence occurred in response to the challenge posed by Roundup. Notably, direct inhibition of NLRP3 inflammasome with MCC950 does not alleviate mitochondrial damage and oxidative stress. However, supplementation of resveratrol, which has been known to attenuate mitochondrial damage and oxidative stress, effectively mitigated the inflammatory response and the expression of senescence-related markers, and prevented the senescence in granulosa cells. These results suggested that mitochondrial function and oxidative homeostasis might play pivotal roles as upstream regulators of NLRP3 inflammasome. In summary, our findings indicated that the premature senescence of granulosa cells caused by mitochondrial ROS-triggered NLRP3 inflammasome activation might contribute to the ovarian toxicity of Roundup, in addition to its known effects on steroidogenesis and apoptosis. Supplementary Information: The online version contains supplementary material available at 10.1007/s43188-024-00229-0.

Dietary nutrition, intestinal microbiota dysbiosis and post-weaning diarrhea in piglets.

Weaning is a critical transitional point in the life cycle of piglets. Early weaning can lead to post-weaning syndrome, destroy the intestinal barrier function and microbiota homeostasis, cause diarrhea and threaten the health of piglets. The nutritional components of milk and solid foods consumed by newborn animals can affect the diversity and structure of their intestinal microbiota, and regulate post-weaning diarrhea in piglets. Therefore, this paper reviews the effects and mechanisms of different nutrients, including protein, dietary fiber, dietary fatty acids and dietary electrolyte balance, on diarrhea and health of piglets by regulating intestinal function. Protein is an essential nutrient for the growth of piglets; however, excessive intake will cause many harmful effects, such as allergic reactions, intestinal barrier dysfunction and pathogenic growth, eventually aggravating piglet diarrhea. Dietary fiber is a nutrient that alleviates post-weaning diarrhea in piglets, which is related to its promotion of intestinal epithelial integrity, microbial homeostasis and the production of short-chain fatty acids. In addition, dietary fatty acids and dietary electrolyte balance can also facilitate the growth, function and health of piglets by regulating intestinal epithelial function, immune system and microbiota. Thus, a targeted control of dietary components to promote the establishment of a healthy bacterial community is a significant method for preventing nutritional diarrhea in weaned piglets.

Diagnostic value of a novel salivary gland ultrasound scoring system in IgG4-related sialadenitis.

OBJECTIVES: To develop a novel ultrasound scoring system for the major salivary glands in patients with immunoglobulin G4-related sialadenitis (IgG4-RS) and assess its diagnostic value in a multicenter cohort of Chinese patients. METHODS: Twenty clinicians (rheumatologists, stomatologists, and radiologists) participated. The study was conducted in four steps: (1) defining the ultrasonography (US) elements, (2) developing a novel ultrasound scoring system for US of the salivary glands, (3) evaluation of inter- and intra-reader reliabilities using the new ultrasound scoring system, and (4) assessing the diagnostic value of this novel ultrasound scoring system in IgG4-RS patients in a Chinese multicenter cohort. RESULTS: A novel ultrasound scoring system for the salivary glands was developed, with total scores ranging from 0 to 34. The inter- and intra-reader reliabilities of the ultrasound scoring system were excellent (0.972 and 0.940, respectively). A total of 470 people were recruited in this study; 187 patients were diagnosed with IgG4-RS, and the remaining 283 people were diagnosed with non-IgG4-RS. Patients with IgG4-RS had significantly higher US scores than the non-IgG4-RS group (mean US score=16 vs. 4, P < 0.001). The calculated area under the curve (AUC) for the total US score was 0.852 (95% CI: 0.814-0.891). The total US scores≥9 showed a sensitivity of 75.4% and a specificity of 91.9%. Association analysis showed a positive correlation between total US scores and serum IgG4 levels and hypocomplementemia (r=0.221, r=0.349; P = 0.002) and a negative correlation between total US scores and serum C3 and C4 levels (r=-0.210, r=-0.303; P = 0.005, P < 0.001). CONCLUSIONS: A novel semiquantitative ultrasound scoring system for patients with IgG4-RS was developed, with good diagnostic performance. The inter- and intra-reader reliabilities were excellent. US scores were correlated with IgG4, C3, and C4 levels and hypocomplementemia.

DNDMH-mediated direct nitration of aryl alkenes.

N-nitro type reagents have been demonstrated as mild nitration tools in recent years. This work presents an exploration of direct nitration of aryl alkenes mediated by DNDMH, a novel N-nitro type reagent developed in our previous study. It exhibits herein a new property of DNDMH as an effective direct nitration reagent for aryl alkenes, through probably the delivery of nitro radicals with the aid of TEMPO and Cu(OAc)2.

Quantitative ultrasound parameters from scattering and propagation may reduce the biopsy rate for breast tumor.

Breast cancer has become the most common cancer worldwide, and early screening improves the patient's survival rate significantly. Although pathology with needle-based biopsy is the gold standard for breast cancer diagnosis, it is invasive, painful, and expensive. Meanwhile it makes patients suffer from misplacement of the needle, resulting in misdiagnosis and further assessment. Ultrasound imaging is non-invasive and real-time, however, benign and malignant tumors are hard to differentiate in grayscale B-mode images. We hypothesis that breast tumors exhibit characteristic properties, which generates distinctive spectral patterns not only in scattering, but also during propagation. In this paper, we propose a breast tumor classification method that evaluates the spectral pattern of the tissues both inside the tumor and beneath it. First, quantitative ultrasonic parameters of these spectral patterns were calculated as the representation of the corresponding tissues. Second, parameters were classified by the K-Nearest Neighbor machine learning model. This method was verified with an open access dataset as a reference, and applied to our own dataset to evaluate the potential for tumors assessment. With both datasets, the proposed method demonstrates accurate classification of the tumors, which potentially makes it unnecessary for certain patients to take the biopsy, reducing the rate of the painful and expensive procedure.

Clinical Significance of Contrast-Enhanced Ultrasound Galactography in Pre-operative Diagnosis of Patients With Pathologic Nipple Discharge.

OBJECTIVE: The aim of the work described here was to investigate the feasibility and diagnostic value of using contrast-enhanced ultrasound (CEUS) galactography with SonoVue in patients with pathologic nipple discharge (PND). METHODS: Twenty-eight patients who underwent breast surgery for PND from May 2019 to August 2021 were included. Routine ultrasound, ductoscopy and CEUS galactography were performed successively. Lesions were diagnosed and localized. The sensitivity, specificity and pre-operative localization value of each examination method were evaluated on post-operative pathology. RESULTS: CEUS galactography was successfully conducted in all 28 patients and revealed negative ductal ectasia, filling stop and filling defect. Ductoscopy revealed positive nodules in 21 cases and negative nodules in 7 cases. A total of 18 nodules were found by routine ultrasound, and the relationship between all nodules and the discharge duct was confirmed after CEUS galactography. Compared with the other two methods, CEUS galactography had higher sensitivity, positive predictive value and negative predictive value (100%, 81.82% and 100%, respectively), while it has the same specificity as routine ultrasound (both 60%). The pre-operative location of the nipple duct was consistent with the intra-operative findings in 28 patients after CEUS galactography. CONCLUSION: The ultrasound contrast agent SonoVue can be used for CEUS galactography in patients with PND. CEUS galactography can improve the detection of ductal nodules and locate the nipple discharge duct pre-operatively. As the technique does not emit radiation and SonoVue is easily metabolized and safe, CEUS galactography is better than conventional imaging for PND patients.

Status, evaluation, and influencing factors of biosecurity levels in pig farms in China.

BACKGROUND: Animal diseases have always been a serious threat to livestock breeding, and the establishment of a biosecurity barrier is important for disease prevention and control. Based on the investigations conducted in seven provinces located farms, this study aimed to explore the current biosecurity levels of farms in China, construct a biosecurity evaluation system, calculate the biosecurity levels of farms using the rank sum ratio comprehensive evaluation method, and develop an empirical analysis of the factors influencing biosecurity levels. RESULTS: The results show that the greater the cost of biosecurity invested, the greater the level of biosecurity. Male farmers, educational attainment and participation in technical training had a significant positive effect on biosecurity levels. In addition, biosecurity levels first decreased and then increased as the scale of farming increased. The study also found that the more people in the household engaged in farming, the higher the biosecurity level of the farm. And farms that joined cooperatives had higher levels of biosecurity. CONCLUSION: The rank sum ratio method can evaluate the index system, so as to obtain a comprehensive index RSR value that can be compared, and the operation steps are simple and effective. By taking measures such as improving the comprehensive quality of farmers and increasing the investment in human, material and financial resources for biosecurity, the biosecurity level of farms can be effectively improved and animal diseases can be effectively prevented and controlled.

Cellulose and JbKOBITO 1 mediate the resistance of NaHCO3-tolerant chlorella to saline-alkali stress.

Carbonate stress has profound impacts on both agricultural and industrial production. Although a number of salinity-tolerant genes have been reported and applied in plants, there is a lack of research on the role of cell wall-related genes in resistance to carbonate. Likewise, in industry, current strategies have not been able to more effectively address the conflict between stress-induced microalgal biofuel accumulation and microalgal growth inhibition. It is of great significance to study the adaptation mechanism of carbonate-tolerant organisms and to explore related genes for future genetic modification. In this study, the role of the cell wall in the NaHCO3-tolerant chlorella JB17 was investigated. We found that JB17 possesses a relatively thick cell wall with a thickness of 300-600 nm, which is much higher than that of the control chlorella with a thickness of about 100 nm. Determination of the cell wall polysaccharide fractions showed that the cellulose content in the JB17 cell wall increased by 10.48% after NaHCO3 treatment, and the decrease in cellulose levels by cellulase digestion inhibited its resistance to NaHCO3. Moreover, the saccharide metabolome revealed that glucose, rhamnose, and trehalose levels were higher in JB17, especially rhamnose and trehalose, which were almost 40 times higher than in control chlorella. Gene expression detection identified an up-regulated expressed gene after NaHCO3 treatment, JbKOBITO1, overexpression of which could improve the NaHCO3 tolerance of Chlamydomonas reinhardtii. As it encodes a glycosyltransferase-like protein that is involved in cellulose synthesis, the strong tolerance of JB17 to NaHCO3 may be partly due to the up-regulated expression of JbKOBITO 1 and JbKOBITO 1-mediated cellulose accumulation. The above results revealed a critical role of cellulose in the NaHCO3 resistance of JB17, and the identified NaHCO3-tolerance gene will provide genetic resources for crop breeding in saline-alkali soils and for genetic modification of microalgae for biofuel production.

Construction of the A-B-C Ring of Simplicissin through an Oxidative Dearomatization/Iodination/[3+2] Annulation Cascade.

As an attractive DMOA-derived spiromeroterpenoid, simplicissin shares a common A-B-C ring skeleton with other natural analogues. On the basis of the development of an oxidative dearomatization/iodination/[3+2] annulation cascade, a concise synthetic pathway to the A-B-C ring of simplicissin has been successfully established, and the substrate generality of the novel oxidative dearomatization/iodination/[3+2] annulation cascade has been checked.

Enantioselective Total Synthesis of (-)-Cephalotanin B.

Cephalotaxus diterpenoids are attractive natural products with intriguing molecular frameworks and promising biological features. As a structurally unusual member, (-)-cephalotanin B possesses an extraordinarily congested heptacyclic skeleton, three lactone units, and nine consecutive stereocenters. Herein, we report an enantioselective total synthesis of (-)-cephalotanin B based on a divergent asymmetric Michael addition reaction, a novel Pauson-Khand/deacyloxylation process discovered in the development of a second-generation stereoselective Pauson-Khand reaction protocol, and an epoxide-opening/elimination/dual-lactonization cascade to construct the challenging propeller-shaped A-B-C ring system as key transformations.

African Swine Fever Shock: China's Hog Industry's Resilience and Its Influencing Factors.

African swine fever has damaged the foundation of China's hog industry, caused a serious decline in hog production, highlighted the contradiction between supply and demand in the pork market, and led to major economic and social impacts. The industrial resilience of 31 Chinese provinces to African swine fever shock and its spatial and temporal differentiation characteristics from 2018 to 2021 were measured in this study from the two dimensions of resistance and recoverability. Using Geodetector, the key factors influencing the resilience of China's hog industry were explored. The results showed that 2018-2019 and 2020-2021 represented the resistance and recovery periods of the hog industry under African swine fever shock, respectively, with poor resilience characterizing the resistance period and improved resilience characterizing the recovery period. At the early stages of the African swine fever outbreak, the hog industries in Tianjin, Shanxi, Guangxi, and Yunnan had robust resistance due to the slaughter rate, economic level, mortality rate, carcass weight, and culling rate in those areas. At the most severe stage of the outbreak, resistance was generally poor in all provinces due to the slaughter rate, per capita consumption, and scale level at the time. During the period of rapid recovery in hog production, the recoverability of each province was very strong due to the industrial structure, culling rate, economic level, and resource carrying capacity at that time. During the reasonable adjustment period of hog production capacity, the recoverability based on the breeding sow inventory in 13 provinces, including Henan, Shandong, and other large hog-breeding provinces, was negative due to the scale level, slaughter rate, per capita consumption, and resource carrying at that time. Taking measures to enhance the resilience of the hog industry, strengthen the prevention and control of hog epidemics, improve the monitoring and early warning mechanisms, and enhance the ability of the hog industry to cope with major animal epidemics is recommended.

Risk Assessment and Response Strategy for Pig Epidemics in China.

Strengthening the analysis and risk assessment of the pig epidemic will help to better prevent and mitigate epidemic risks and promote the high-quality development of the pig industry. Based on a systematic understanding of live pig epidemics, a risk assessment index system was constructed, and the spatial and temporal variation characteristics of pig epidemics in China were explored by the entropy method. In recent years, the overall trend in pig epidemics over time first increased and then decreased; in space, the acceleration of the spread of epidemics across the country weakened. China still faces challenges, including many types and a wide range of diseases, large total livestock breeding and weak epidemic prevention and control capacity, and a large risk of introduced foreign animal epidemics. The spatial and temporal variations in the pig epidemic risk were obvious; one high-risk area, two medium-high-risk areas and 10 medium-risk areas have been found in recent years, during which time, the epidemic risk was highest in Beijing, Hainan, Liaoning, Tibet and Zhejiang. However, there were significant differences in the regional distribution of the risk level of pig epidemics in different years. To further build a secure "defense system" for the high-quality development of the pig industry, it is recommended to improve the monitoring and early warning system of pig epidemic risk, perfect the pig epidemic prevention and control system, and strengthen the regional collaboration mechanism of epidemic prevention and control.

Development and validation of a dynamic nomogram based on conventional ultrasound and contrast-enhanced ultrasound for stratifying the risk of central lymph node metastasis in papillary thyroid carcinoma preoperatively.

Purpose: The aim of this study was to develop and validate a dynamic nomogram by combining conventional ultrasound (US) and contrast-enhanced US (CEUS) to preoperatively evaluate the probability of central lymph node metastases (CLNMs) for patients with papillary thyroid carcinoma (PTC). Methods: A total of 216 patients with PTC confirmed pathologically were included in this retrospective and prospective study, and they were divided into the training and validation cohorts, respectively. Each cohort was divided into the CLNM (+) and CLNM (-) groups. The least absolute shrinkage and selection operator (LASSO) regression method was applied to select the most useful predictive features for CLNM in the training cohort, and these features were incorporated into a multivariate logistic regression analysis to develop the nomogram. The nomogram's discrimination, calibration, and clinical usefulness were assessed in the training and validation cohorts. Results: In the training and validation cohorts, the dynamic nomogram (https://clnmpredictionmodel.shinyapps.io/PTCCLNM/) had an area under the receiver operator characteristic curve (AUC) of 0.844 (95% CI, 0.755-0.905) and 0.827 (95% CI, 0.747-0.906), respectively. The Hosmer-Lemeshow test and calibration curve showed that the nomogram had good calibration (p = 0.385, p = 0.285). Decision curve analysis (DCA) showed that the nomogram has more predictive value of CLNM than US or CEUS features alone in a wide range of high-risk threshold. A Nomo-score of 0.428 as the cutoff value had a good performance to stratify high-risk and low-risk groups. Conclusion: A dynamic nomogram combining US and CEUS features can be applied to risk stratification of CLNM in patients with PTC in clinical practice.

Dinitro-5,5-Dimethylhydantoin: An Arene Nitration Reagent.

The development of a new N-nitro type compound, dinitro-5,5-dimethylhydantoin (DNDMH), has been reported as an arene nitration reagent. The exploration demonstrated that arene nitration with DNDMH exhibited good tolerance with diverse functional groups. It is notable that, among the two N-nitro units of DNDMH, only the N-nitro unit on N1 was delivered to the nitroarene products. The N-nitro type compound with a single N-nitro unit on N2 cannot promote the arene nitration.

Factors Influencing Disease Prevention and Control Behaviours of Hog Farmers.

Animal diseases are a serious threat to animal husbandry production and diet health, and effective prevention and control measures need to be explored. This study investigates the factors influencing the adoption of biosecurity prevention and the control behaviours of hog farmers towards African swine fever and provides appropriate recommendations. Using research data from Sichuan, Hubei, Jiangsu, Tianjin, Liaoning, Jilin, and Hebei, we employed a binary logistic model to empirically analyse these factors. Regarding individual farmer characteristics, male farmers emphasised biosecurity prevention and control in farms, with higher education actively influencing the adoption of prevention and control measures. Farmers who received technical training were actively inclined to adopt such behaviours. Furthermore, the longer the duration of farming, the more probable the farmers were to neglect biosecurity prevention and control. However, the bigger and more specialised the farm, the more inclined they were to adopt prevention and control behaviours. With respect to disease prevention and control awareness, the more risk-averse the farmers were, the more they actively adopted epidemic prevention behaviours. As the awareness of epidemic risk increased, the farmers tended to adopt active epidemic prevention behaviours by reporting suspected outbreaks. The following policy recommendations were made: learning about epidemic prevention and improving professional skills; large-scale farming, specialised farming; and timely dissemination of information to raise risk awareness.