Objective:To explore the clinical application value of convolutional neural network（CNN）based on deep learning in the automatic measurement of dynamic pelvic floor ultrasound video parameters and the diagnosis and classification of cystocele.Methods:A retrospective analysis was conducted on dynamic pelvic floor ultrasound videos from 398 postpartum women who underwent examinations at the First People's Hospital of Foshan between June 2020 and June 2022. The lowest point of the posterior bladder wall（PWB），urethral rotation angle（URA），and retrovesical angle（RVA）were manually measured by a senior radiologist（R1）and a junior radiologist（R2），and cystocele was classified according to the Green standard. The CNN model was employed to automatically extract the above parameters and to diagnose and classify cystocele. Using R1 measurements as a reference，intraclass correlation coefficient（ICC）was used to evaluate the consistency between the CNN model and R1，as well as between R2 and R1. The Kappa value was used to assess the agreement between the CNN model，R2，and R1 in the diagnosis and classification of cystocele. Additionally，the time consumption of the three measurement methods was compared.Results:The CNN model showed good consistency with R1 in measuring PWB and URA（ICC = 0.983，0.894），while its consistency in measuring RVA was moderate（ICC = 0.614）. The ICC between R2 and R1 in measuring PWB，URA，and RVA was 0.979，0.815，and 0.627，respectively. In the measurement of PWB and URA，the consistency between the CNN model and R1 was superior to that between R2 and R1. For cystocele diagnosis，the Kappa value between the CNN model and R1 was 0.924，which was higher than that between R2 and R1（0.904）. In cystocele classification，the Kappa value between the CNN model and R1 was 0.503，also higher than that between R2 and R1（0.426）. The CNN model processed a single video in 2.5（0.6）s，significantly faster than R1［59.9（16.9）s］and R2［56.8（11.2）s］（all P < 0.001）. Conclusions:The CNN model demonstrates high accuracy and efficiency in the measurement，diagnosis，and classification of cystocele，outperforming a junior radiologist and showing potential for clinical application.

Objective:To explore the clinical application value of convolutional neural network（CNN）based on deep learning in the automatic measurement of dynamic pelvic floor ultrasound video parameters and the diagnosis and classification of cystocele.Methods:A retrospective analysis was conducted on dynamic pelvic floor ultrasound videos from 398 postpartum women who underwent examinations at the First People's Hospital of Foshan between June 2020 and June 2022. The lowest point of the posterior bladder wall（PWB），urethral rotation angle（URA），and retrovesical angle（RVA）were manually measured by a senior radiologist（R1）and a junior radiologist（R2），and cystocele was classified according to the Green standard. The CNN model was employed to automatically extract the above parameters and to diagnose and classify cystocele. Using R1 measurements as a reference，intraclass correlation coefficient（ICC）was used to evaluate the consistency between the CNN model and R1，as well as between R2 and R1. The Kappa value was used to assess the agreement between the CNN model，R2，and R1 in the diagnosis and classification of cystocele. Additionally，the time consumption of the three measurement methods was compared.Results:The CNN model showed good consistency with R1 in measuring PWB and URA（ICC = 0.983，0.894），while its consistency in measuring RVA was moderate（ICC = 0.614）. The ICC between R2 and R1 in measuring PWB，URA，and RVA was 0.979，0.815，and 0.627，respectively. In the measurement of PWB and URA，the consistency between the CNN model and R1 was superior to that between R2 and R1. For cystocele diagnosis，the Kappa value between the CNN model and R1 was 0.924，which was higher than that between R2 and R1（0.904）. In cystocele classification，the Kappa value between the CNN model and R1 was 0.503，also higher than that between R2 and R1（0.426）. The CNN model processed a single video in 2.5（0.6）s，significantly faster than R1［59.9（16.9）s］and R2［56.8（11.2）s］（all P < 0.001）. Conclusions:The CNN model demonstrates high accuracy and efficiency in the measurement，diagnosis，and classification of cystocele，outperforming a junior radiologist and showing potential for clinical application.

Objective::Calcific aortic valve disease (CAVD) affects millions of elderly people, and there is currently no effective way to stop or slow down its progression. Therefore, exploring the pathogenesis of CAVD is very important for prevention and treatment. Cartilage oligomeric matrix protein (COMP) have important role in cell phenotype change. This study is aimed to confirm whether COMP participate in CAVD and try to find the possible mechanisms.Methods::Human aortic valve tissues from Nanjing First Hospital (CAVD group, n=20; control group, n=11) were harvested. The expression level of COMP was tested by western blot and immunohistochemistry. Dual immunofluorescence staining was used for locating COMP. Bone morphogenetic protein-2 (BMP2) signalling were tested by western blot. The animal model was also used to detect COMP level by immunohistochemistry. Results::The results showed that the expression level of COMP was significantly increased in the calcific valve samples when compared with that of the control valve ( P<0.05); COMP was expressed near the calcific nodules and co-localized with α-smooth muscle actin (α-SMA). The protein levels of BMP2 and p-Smads 1/5/9 were markedly more highly expressed in the CAVD group than the control group ( P<0.05). Furthermore, immunofluorescence detection showed that COMP and BMP2 were co-located in calcific valves. Conclusions::The above results suggested that upregulation of COMP and BMP2 may be associated with aortic valve calcification and that COMP may become a potential therapeutic target in human CAVD.

Objective::Calcific aortic valve disease (CAVD) affects millions of elderly people, and there is currently no effective way to stop or slow down its progression. Therefore, exploring the pathogenesis of CAVD is very important for prevention and treatment. Cartilage oligomeric matrix protein (COMP) have important role in cell phenotype change. This study is aimed to confirm whether COMP participate in CAVD and try to find the possible mechanisms.Methods::Human aortic valve tissues from Nanjing First Hospital (CAVD group, n=20; control group, n=11) were harvested. The expression level of COMP was tested by western blot and immunohistochemistry. Dual immunofluorescence staining was used for locating COMP. Bone morphogenetic protein-2 (BMP2) signalling were tested by western blot. The animal model was also used to detect COMP level by immunohistochemistry. Results::The results showed that the expression level of COMP was significantly increased in the calcific valve samples when compared with that of the control valve ( P<0.05); COMP was expressed near the calcific nodules and co-localized with α-smooth muscle actin (α-SMA). The protein levels of BMP2 and p-Smads 1/5/9 were markedly more highly expressed in the CAVD group than the control group ( P<0.05). Furthermore, immunofluorescence detection showed that COMP and BMP2 were co-located in calcific valves. Conclusions::The above results suggested that upregulation of COMP and BMP2 may be associated with aortic valve calcification and that COMP may become a potential therapeutic target in human CAVD.

Objective To explore the association of serum cytokine levels with disease activity in patients with dermatomyositis (DM) and clinically amyopathic dermatomyositis (CADM),especially their association with skin lesions and interstitial lung disease (ILD).Methods Enzyme-linked immunosorbent assay (ELISA) and cytometric beads array (CBA)were performed to detect the serum levels of interleukin (IL)-2,IL-4,IL-6,IL-10,IL-17A,IL-18,tumor necrosis factor (TNF) and interferon (IFN)-γin 40 patients with DM or CADM,as well as in 16 health checkup examinees (healthy control group).Then,the association of serum cytokine levels with skin lesions,inflammatory biomarkers and severity of ILD was analyzed.Results The patients with DM/CADM showed significantly higher serum levels of IL-6 (37.8 ±45.8 pg/ml),IL-10 (16.1 ± 7.2 pg/ml) and IL-18 (492.0 ± 193.1 pg/ml) compared with the healthy controls (12.0 ± 2.7 pg/ml,7.7 ± 1.4 pg/ml,191.1 ± 39.2 pg/ml,respectively,all P ＜ 0.001),and there were no significant differences in the serum levels of the other 5 cytokines between the above 2 groups.The serum level of IL-6 was significantly higher in patients with elevated erythrocyte sedimentation rate (ESR) than in those with normal ESR (49.7 ± 46.8 pg/ml vs.29.1 ± 45.4 pg/ml,P =0.008).The patients with raised C-reactive protein (CRP) levels showed significantly higher serum levels of IL-6 (68.7 ± 59.7 pg/ml) and IL-18 (635.1 ± 232.8 pg/ml) compared with those with normal CRP levels (IL-6:30.6 ± 40.3 pg/ml,P =0.013;IL-18:440.2 ± 164.7 pg/ml,P =0.020).Moreover,the patients with elevated levels of lactate dehydrogenase (LDH) showed significantly higher serum levels of IL-10 (18.4 ± 6.9 pg/ml),IL-17A (19.6 ±6.7 pg/ml) and IL-18 (529.4 ± 197.2 pg/ml) compared with those with normal LDH levels (IL-10:10.7 ±4.8 pg/ml,P ＜ 0.001;IL-17A:11.4 ± 6.6 pg/ml,P =0.001;IL-18:404.9 ± 158.0 pg/ml,P =0.037).No significant difference in the cytokine levels was observed between the patients with elevated creatine kinase (CK) levels and those with normal CK levels.The patients with Gottron's papules/sign showed significantly higher serum levels of IL-18 (513.7 ± 187.2 pg/ml) compared with those without Gottron's papules/sign (297.1 ± 140.4 pg/ml,P ＜ 0.05).The serum levels of IL-10 and IL-18 were significantly higher in the patients with DM/CADM complicated by ILD (18.0 ± 6.7 pg/ml,552.3 ± 192.8 pg/ml,respectively) than in those without ILD (11.6 ± 6.5 pg/ml,351.4 ± 101.0 pg/ml,respectively,both P =0.001).Conclusion Serum levels of IL-6,IL-10 and IL-18 are highly associated with inflammatory biomarkers,skin lesions and ILD in patients with DM/CADM.

Objective　To develop a new method to induce the gene transfection in high efficiency for eukaryotic cells in vitro. Methods　 Four kinds of p14ARF gene primarily deleted human carcinoma cell line including H460,A549,U251,and PC-3 were transfected with the human p14ARF expression vector (pCI-neo-p14ARF) by using the new nonliposomal transfection reagent Fugene 6. The efficiency of gene transfer was determined by screening the cells in G418. Results　 After 21 days' selection, G418-resistant clones were shown in all the transfected plate. PCR product of p14ARF gene was positive in all the G418-resistant clones. Cytotoxicity of Fugene 6 was detected. The cell proliferation activity was not affected when it was cultured in a high dose of Fugene 6. Conclusion　 These results demonstrate that Fugene 6 is a rapid, feasible, reproducible, and noncytotoxic gene transfection approach for eukaryotic expression vector in vitro.

Objective　To examine whether wild-type p14ARF gene is a candidate suppressor gene for lung cancer. Methods　Human lung cancer cell lines having various endogenous backgrounds in INK4a, p53 and Rb genes were used as the recipients of the wild-type p14ARF gene. The expression of p14ARF mRNA and protein was detected with RT-PCR, immunohistochemistry and Western blot after G418 selection. Clones which expressed both p14ARF mRNA and protein were identified and selected for further experiements. By comparing with the parental and negative control cells treated with empty vectors, the effects of exogenously transfected p14ARF on cell division rate, cell cycle distribution and morphologic alteration were analyzed. In vivo evaluation of the growth rate was also made with the experiment of nude mice tumor formation. Results　Upon transfection with p14ARF gene, cells were arrested at G1 or G1／G2 phase of cell cycle in three wtp53 lung cancer cell lines and their proliferation rates were also inhibited. Conclusion　Human wild-type p14ARF gene has suppressive effect on abnormal proliferation of lung cancer cells, especially in some wtp53 lung cancer cells, and it might be an ideal candidate for gene therapy of human lung cancer.