Objective:To establish a model based on the characteristics of breast cancer ultrasound images through deep learning methods to predict the risk of axillary lymph node metastasis（ALNM）in patients with breast cancer（maximum diameter ≤2.5 cm）before surgery.Methods:A total of 419 patients（3 433 breast tumor ultrasound images）with breast cancer（maximum diameter ≤2.5 cm）who underwent axillary lymph node dissection at Beijing Tiantan Hospital，Capital Medical University from January 2019 to December 2024 were retrospectively included. According to the pathological results of axillary lymph nodes，they were divided into 220 cases in the ALNM occurrence group（positive group）and 199 cases in the non-ALNM occurrence group（negative group）. The breast cancer ultrasound images of the two groups of cases were randomly classified into the training set（2 404 images），the validation set（687 images）and the test set（342 images）according to a ratio of 7∶2∶1. YOLOv8 was used as the basic model of You Only Look Once（YOLO）and optimized. The optimized model was applied to locate and capture the potential ultrasound features of breast cancer cases in the training set. A prediction model was constructed based on the captured ultrasound features. The model was adjusted and optimized through the validation set，and then matched with the case images in the test set. The confusion classification matrix graph and the curve graph for measuring the model performance were used to evaluate the model prediction performance and interpret the model，and the efficacy of this model in identifying breast cancer patients at risk of ALNM was analyzed.Results:There were statistically significant differences between the positive and negative groups in terms of the pathological maximum diameter of breast tumors，pathological T staging，the differentiation degree，the presence of distant metastasis，the maximum diameter measured by ultrasound，the quadrant of breast tumor occurrence，the Breast Imaging - Reporting and Data System（BI-RADS）classification of breast tumors，and the presence of abnormal ultrasound features of lymph node（all P<0.05）. The established deep learning model could automatically perform bounding box localization for the breast cancer of patients.The breast tumors in the positive group had potential ultrasound features that could be captured by the model compared with those in the negative group. The mean average precision（mAP）50 was 0.883，mAP 50-95 was 0.636，PR-AUC was 0.884 5，strict PR-AUC was 0.636 4，the sensitivity was 90.5%，and the specificity was 91.2%，and it had a good predictive efficacy. Conclusions:This prediction model based on the ultrasound characteristics of breast cancer through deep learning can effectively predict breast cancer（maximum diameter ≤ 2.5 cm）with the risk of ALNM，providing an effective basis for the clinical management of axillary lymph nodes in breast cancer patients.

Objective:To investigate the role of the Smad3 signaling pathway in the process of silica-induced epithelial-mesenchymal transition (EMT) .Methods:In September 2022, lung epithelial cells (BEAS-2B) were exposed to different concentrations of silica suspension (0, 50, 100, and 150 μg/ml) for 6 and 12 hours. Additionally, SIS3, a specific inhibitor of phosphorylated Smad3 (p-Smad3) , was utilized to establish the p-Smad3 inhibition model. The cells were divided into four groups: blank control gruop, silica group, SIS3 intervention group, and SIS3 +silica group. Cell morphology was observed using an inverted fluorescence microscope, while cell viability was assessed using a Cell Counting Kit-8 (CCK-8) . The mRNA and protein expression levels of E-cadherin (E-Cad) , N-cadherin (N-Cad) , Vimentin, Smad3, and p-Smad3 were analyzed by Quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting, respectively. Differences between two groups were compared using Student's t-test, and multiple group comparisons were analyzed using a one-way analysis of variance with the Student-Newman-Keuls test.Results:Compared with the blank control group, the morphology of BEAS-2B cells shifted from epithelial to mesenchymal cell-like following silica exposure, and the cell viability of BEAS-2B cells declined after exposure to 150 μg/ml silica for 6 and 12 hours. Furthermore, silica exposure led to significant reductions in mRNA and protein expression levels of the epithelial cellular marker (E-Cad) in BEAS-2B cells, accompanied by increased expressions of interstitial cellular markers (N-Cad and Vimentin) . Importantly, the level of p-Smad3/Smad3 expression levels was also elevated in silica-treated cells ( P<0.05) . Compared to the blank control group, the level of p-Smad3/Smad3 expression levels was significantty reduced. Moreover, compared to the silica group, the protein expression levels of N-Cad and Vimentin in the cell of the SIS3+silica group were significantly reduced, while the E-Cad expression was increased ( P<0.05) . Conclusion:Silica exposure can prmote the epithelial mesenchymaol transformotion process by activating smod3 signa ling pathuay, and in hibiting smad3 signa ling pathuay can effctively alleviate the occurrence of epithelial mesenchymal transformation process.

Purpose To explore the value of amide proton transfer(APT)imaging combined with diffusion kurtosis imaging(DKI)in the differential diagnosis of prostate carcinoma and benign prostatic hyperplasia.Materials and Methods A retrospective analysis was conducted on 120 patients who underwent multi-parameter prostate MRI and pathological biopsy at the First Affiliated Hospital of Xinxiang Medical University from January 2020 to August 2021,including 66 cases of benign prostatic hyperplasia and 54 cases of prostate carcinoma.The parameters of APT imaging and DKI,including magnetization transfer ratio asymmetry(MTRasym),mean kurtosis(MK),mean diffusion coefficient(MD)and fraction anisotropy were measured,and the parameters between the two groups were compared and analyzed.The receiver operating characteristic curve and Delong test were used to analyze the efficacy of each parameter,APT or DKI sequence alone and their combined diagnosis,and the correlation among the parameters was analyzed.Results Compared with the benign prostatic hyperplasia group,the MTRasym,MK and fraction anisotropy of the prostate carcinoma group were significantly higher,while the MD was significantly lower,with statistical significance(t=8.23,12.53,2.20,-11.12,all P<0.05).The areas under the curve for the above parameters were 0.852,0.933,0.615 and 0.910,respectively.The diagnostic efficacy of APT combined with DKI for differentiating prostate carcinoma from benign prostatic hyperplasia is numerically higher than that of APT alone or DKI alone,with the areas under the curve being 0.994,0.988 and 0.852,respectively,as well as a sensitivity of 96.30%and a specificity of 98.48%.There was a statistically significant difference in efficacy between the APT+DKI combined approach and APT alone(Z=4.387,P<0.05),while no statistically significant difference exists between the combined approach and DKI alone(Z=1.375,P>0.05).MTRasym was positively correlated with MK(r=0.45,P<0.001).MD was negatively correlated with MTRasym and MK(r=-0.439,-0.500,both P<0.001).Conclusion The parameters MTRasym,MK and MD of APT and DKI have relatively high value in distinguishing prostate carcinoma from benign prostatic hyperplasia,and the combined diagnostic efficiency of the two sequences tends to increase,with some parameters showing correlation.

Purpose To explore the value of magnetic resonance amide proton transfer(APT)imaging combined with diffusion weighted imaging(DWI)in the differential diagnosis of prostate cancer and benign prostatic hyperplasia.Materials and Methods A retrospective analysis was made on 52 patients with prostate cancer and 60 patients with benign prostatic hyperplasia in the First Affiliated Hospital of Xinxiang Medical University from February 2020 to August 2021.The APT parameter values magnetization transfer ratio asymmetry(MTRasym)and DWI parameter values apparent diffusion coefficient(ADC)of the two groups were measured,respectively.The parameter differences between the two groups were compared and analyzed,the significant parameters and the efficacy of their joint diagnosis were evaluated.Then compared the performance of each parameter and joint diagnosis,and analyze the correlation between the two parameters.Results The MTRasym in the prostate cancer group[(3.70±0.94)%]was significantly higher than that in the prostate hyperplasia group[(2.35±0.60)%](t=8.89,P＜0.05);ADC value in prostate cancer group[(0.93±0.15)×10-3 mm2/s]was significantly lower than that in the prostate hyperplasia group[(1.32±0.22)×10-3 mm2/s](t=-11.01,P＜0.05).The areas under the curve for identifying prostate cancer and benign prostatic hyperplasia using MTRasym value,ADC value and their combination were 0.886,0.914 and 0.966,respectively.There was no statistically significant difference in the diagnostic efficacy between the MTRasym value and the ADC value(P＞0.05),and the combined diagnostic efficacy of the two was superior to the individual diagnostic efficacy of the MTRasym value and ADC value(Z=3.125,2.776,P＜0.05).The MTRasym was negatively correlated with the ADC value(r=-0.469,P＜0.001).Conclusion APT and DWI have high efficacy in distinguishing between prostate cancer and benign prostatic hyperplasia.The combination of the two sequences has higher diagnostic efficacy.

Objective In response to the clinical needs for personalized wrist orthoses,a topological optimization design method was proposed to achieve an integrated macro-and micro-structural optimization of a personalized,lightweight,and comfortable wrist orthosis.Methods A composite biomechanical finite element model of the wrist orthosis and upper limb was established to quantify the effects of the orthosis geometry on its fixation performance and comfort.A multi-condition topological optimization and microstructure design approach was employed to optimize the non-load-bearing areas of the orthosis.The orthosis was manufactured using three-dimensional(3D)-printed polyether ether ketone(PEEK),and the feasibility of the design was validated.Results While maintaining mechanical strength,the weight of the 3D-printed PEEK orthosis was reduced by 28％compared to the traditional orthoses.Both the pressure at the skin contact interface and the results of a subjective questionnaire indicated that test subjects experienced a high level of comfort wearing the orthosis.Conclusions The orthosis design achieved personalization,lightweight structure,and high comfort while ensuring mechanical strength and fixation performance.

Objective In response to the clinical needs for personalized wrist orthoses,a topological optimization design method was proposed to achieve an integrated macro-and micro-structural optimization of a personalized,lightweight,and comfortable wrist orthosis.Methods A composite biomechanical finite element model of the wrist orthosis and upper limb was established to quantify the effects of the orthosis geometry on its fixation performance and comfort.A multi-condition topological optimization and microstructure design approach was employed to optimize the non-load-bearing areas of the orthosis.The orthosis was manufactured using three-dimensional(3D)-printed polyether ether ketone(PEEK),and the feasibility of the design was validated.Results While maintaining mechanical strength,the weight of the 3D-printed PEEK orthosis was reduced by 28％compared to the traditional orthoses.Both the pressure at the skin contact interface and the results of a subjective questionnaire indicated that test subjects experienced a high level of comfort wearing the orthosis.Conclusions The orthosis design achieved personalization,lightweight structure,and high comfort while ensuring mechanical strength and fixation performance.

Purpose To explore the value of amide proton transfer(APT)imaging combined with diffusion kurtosis imaging(DKI)in the differential diagnosis of prostate carcinoma and benign prostatic hyperplasia.Materials and Methods A retrospective analysis was conducted on 120 patients who underwent multi-parameter prostate MRI and pathological biopsy at the First Affiliated Hospital of Xinxiang Medical University from January 2020 to August 2021,including 66 cases of benign prostatic hyperplasia and 54 cases of prostate carcinoma.The parameters of APT imaging and DKI,including magnetization transfer ratio asymmetry(MTRasym),mean kurtosis(MK),mean diffusion coefficient(MD)and fraction anisotropy were measured,and the parameters between the two groups were compared and analyzed.The receiver operating characteristic curve and Delong test were used to analyze the efficacy of each parameter,APT or DKI sequence alone and their combined diagnosis,and the correlation among the parameters was analyzed.Results Compared with the benign prostatic hyperplasia group,the MTRasym,MK and fraction anisotropy of the prostate carcinoma group were significantly higher,while the MD was significantly lower,with statistical significance(t=8.23,12.53,2.20,-11.12,all P<0.05).The areas under the curve for the above parameters were 0.852,0.933,0.615 and 0.910,respectively.The diagnostic efficacy of APT combined with DKI for differentiating prostate carcinoma from benign prostatic hyperplasia is numerically higher than that of APT alone or DKI alone,with the areas under the curve being 0.994,0.988 and 0.852,respectively,as well as a sensitivity of 96.30%and a specificity of 98.48%.There was a statistically significant difference in efficacy between the APT+DKI combined approach and APT alone(Z=4.387,P<0.05),while no statistically significant difference exists between the combined approach and DKI alone(Z=1.375,P>0.05).MTRasym was positively correlated with MK(r=0.45,P<0.001).MD was negatively correlated with MTRasym and MK(r=-0.439,-0.500,both P<0.001).Conclusion The parameters MTRasym,MK and MD of APT and DKI have relatively high value in distinguishing prostate carcinoma from benign prostatic hyperplasia,and the combined diagnostic efficiency of the two sequences tends to increase,with some parameters showing correlation.

Purpose To explore the value of magnetic resonance amide proton transfer(APT)imaging combined with diffusion weighted imaging(DWI)in the differential diagnosis of prostate cancer and benign prostatic hyperplasia.Materials and Methods A retrospective analysis was made on 52 patients with prostate cancer and 60 patients with benign prostatic hyperplasia in the First Affiliated Hospital of Xinxiang Medical University from February 2020 to August 2021.The APT parameter values magnetization transfer ratio asymmetry(MTRasym)and DWI parameter values apparent diffusion coefficient(ADC)of the two groups were measured,respectively.The parameter differences between the two groups were compared and analyzed,the significant parameters and the efficacy of their joint diagnosis were evaluated.Then compared the performance of each parameter and joint diagnosis,and analyze the correlation between the two parameters.Results The MTRasym in the prostate cancer group[(3.70±0.94)%]was significantly higher than that in the prostate hyperplasia group[(2.35±0.60)%](t=8.89,P＜0.05);ADC value in prostate cancer group[(0.93±0.15)×10-3 mm2/s]was significantly lower than that in the prostate hyperplasia group[(1.32±0.22)×10-3 mm2/s](t=-11.01,P＜0.05).The areas under the curve for identifying prostate cancer and benign prostatic hyperplasia using MTRasym value,ADC value and their combination were 0.886,0.914 and 0.966,respectively.There was no statistically significant difference in the diagnostic efficacy between the MTRasym value and the ADC value(P＞0.05),and the combined diagnostic efficacy of the two was superior to the individual diagnostic efficacy of the MTRasym value and ADC value(Z=3.125,2.776,P＜0.05).The MTRasym was negatively correlated with the ADC value(r=-0.469,P＜0.001).Conclusion APT and DWI have high efficacy in distinguishing between prostate cancer and benign prostatic hyperplasia.The combination of the two sequences has higher diagnostic efficacy.

Objective:To establish a model based on the characteristics of breast cancer ultrasound images through deep learning methods to predict the risk of axillary lymph node metastasis（ALNM）in patients with breast cancer（maximum diameter ≤2.5 cm）before surgery.Methods:A total of 419 patients（3 433 breast tumor ultrasound images）with breast cancer（maximum diameter ≤2.5 cm）who underwent axillary lymph node dissection at Beijing Tiantan Hospital，Capital Medical University from January 2019 to December 2024 were retrospectively included. According to the pathological results of axillary lymph nodes，they were divided into 220 cases in the ALNM occurrence group（positive group）and 199 cases in the non-ALNM occurrence group（negative group）. The breast cancer ultrasound images of the two groups of cases were randomly classified into the training set（2 404 images），the validation set（687 images）and the test set（342 images）according to a ratio of 7∶2∶1. YOLOv8 was used as the basic model of You Only Look Once（YOLO）and optimized. The optimized model was applied to locate and capture the potential ultrasound features of breast cancer cases in the training set. A prediction model was constructed based on the captured ultrasound features. The model was adjusted and optimized through the validation set，and then matched with the case images in the test set. The confusion classification matrix graph and the curve graph for measuring the model performance were used to evaluate the model prediction performance and interpret the model，and the efficacy of this model in identifying breast cancer patients at risk of ALNM was analyzed.Results:There were statistically significant differences between the positive and negative groups in terms of the pathological maximum diameter of breast tumors，pathological T staging，the differentiation degree，the presence of distant metastasis，the maximum diameter measured by ultrasound，the quadrant of breast tumor occurrence，the Breast Imaging - Reporting and Data System（BI-RADS）classification of breast tumors，and the presence of abnormal ultrasound features of lymph node（all P<0.05）. The established deep learning model could automatically perform bounding box localization for the breast cancer of patients.The breast tumors in the positive group had potential ultrasound features that could be captured by the model compared with those in the negative group. The mean average precision（mAP）50 was 0.883，mAP 50-95 was 0.636，PR-AUC was 0.884 5，strict PR-AUC was 0.636 4，the sensitivity was 90.5%，and the specificity was 91.2%，and it had a good predictive efficacy. Conclusions:This prediction model based on the ultrasound characteristics of breast cancer through deep learning can effectively predict breast cancer（maximum diameter ≤ 2.5 cm）with the risk of ALNM，providing an effective basis for the clinical management of axillary lymph nodes in breast cancer patients.

Objective:To investigate the role of the Smad3 signaling pathway in the process of silica-induced epithelial-mesenchymal transition (EMT) .Methods:In September 2022, lung epithelial cells (BEAS-2B) were exposed to different concentrations of silica suspension (0, 50, 100, and 150 μg/ml) for 6 and 12 hours. Additionally, SIS3, a specific inhibitor of phosphorylated Smad3 (p-Smad3) , was utilized to establish the p-Smad3 inhibition model. The cells were divided into four groups: blank control gruop, silica group, SIS3 intervention group, and SIS3 +silica group. Cell morphology was observed using an inverted fluorescence microscope, while cell viability was assessed using a Cell Counting Kit-8 (CCK-8) . The mRNA and protein expression levels of E-cadherin (E-Cad) , N-cadherin (N-Cad) , Vimentin, Smad3, and p-Smad3 were analyzed by Quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting, respectively. Differences between two groups were compared using Student's t-test, and multiple group comparisons were analyzed using a one-way analysis of variance with the Student-Newman-Keuls test.Results:Compared with the blank control group, the morphology of BEAS-2B cells shifted from epithelial to mesenchymal cell-like following silica exposure, and the cell viability of BEAS-2B cells declined after exposure to 150 μg/ml silica for 6 and 12 hours. Furthermore, silica exposure led to significant reductions in mRNA and protein expression levels of the epithelial cellular marker (E-Cad) in BEAS-2B cells, accompanied by increased expressions of interstitial cellular markers (N-Cad and Vimentin) . Importantly, the level of p-Smad3/Smad3 expression levels was also elevated in silica-treated cells ( P<0.05) . Compared to the blank control group, the level of p-Smad3/Smad3 expression levels was significantty reduced. Moreover, compared to the silica group, the protein expression levels of N-Cad and Vimentin in the cell of the SIS3+silica group were significantly reduced, while the E-Cad expression was increased ( P<0.05) . Conclusion:Silica exposure can prmote the epithelial mesenchymaol transformotion process by activating smod3 signa ling pathuay, and in hibiting smad3 signa ling pathuay can effctively alleviate the occurrence of epithelial mesenchymal transformation process.