Objective To observe the value of artificial intelligence ultrasound combined with serum hyaluronic acid synthase 2(HAS2)and trefoil factor-1(TFF1)for early diagnosis of breast cancer.Methods Totally 176 patients with suspected breast cancer were retrospective enrolled and divided into malignant group(n=50)and benign group(n=126)according to pathological results.Artificial intelligence ultrasound and convolutional neural network algorithms were used to automatically label suspicious breast lesions.The lesions were manually graded based on breast imaging reports and data systems,classifying 0-3 grades as benign lesions,4-5 grades as malignant lesions.Clinical data and artificial intelligence ultrasound manifestations were compared between groups.Receiver operating characteristic curve was drawn,the area under the curve(AUC)was calculated to evaluate the efficacy of HAS2,TFF1,artificial intelligence ultrasound and their combination for diagnosing breast cancer.Results HAS2,TFF1,as well as the proportions of abnormal glandular thickness,low-echo lesions and abnormal blood flow morphology in malignant group were all higher than those in benign group(all P＜0.001).AUC of serum HAS2,TFF1 and artificial intelligence ultrasound for diagnosing breast cancer was 0.772,0.754 and 0.859,respectively.The combined diagnostic efficacy of the above three(AUC=0.925)was higher than single diagnostic efficacy(all P＜0.05).Conclusion Artificial intelligence ultrasound combined with serum HAS2 and TFF1 had good efficacy for early diagnosis of breast cancer.

Objective To observe the value of artificial intelligence ultrasound combined with serum hyaluronic acid synthase 2(HAS2)and trefoil factor-1(TFF1)for early diagnosis of breast cancer.Methods Totally 176 patients with suspected breast cancer were retrospective enrolled and divided into malignant group(n=50)and benign group(n=126)according to pathological results.Artificial intelligence ultrasound and convolutional neural network algorithms were used to automatically label suspicious breast lesions.The lesions were manually graded based on breast imaging reports and data systems,classifying 0-3 grades as benign lesions,4-5 grades as malignant lesions.Clinical data and artificial intelligence ultrasound manifestations were compared between groups.Receiver operating characteristic curve was drawn,the area under the curve(AUC)was calculated to evaluate the efficacy of HAS2,TFF1,artificial intelligence ultrasound and their combination for diagnosing breast cancer.Results HAS2,TFF1,as well as the proportions of abnormal glandular thickness,low-echo lesions and abnormal blood flow morphology in malignant group were all higher than those in benign group(all P＜0.001).AUC of serum HAS2,TFF1 and artificial intelligence ultrasound for diagnosing breast cancer was 0.772,0.754 and 0.859,respectively.The combined diagnostic efficacy of the above three(AUC=0.925)was higher than single diagnostic efficacy(all P＜0.05).Conclusion Artificial intelligence ultrasound combined with serum HAS2 and TFF1 had good efficacy for early diagnosis of breast cancer.

Objective To investigate the therapeutic effects of bone marrow mesenchymal stem cells (BMSCs) for radiation-induced lung injury (RILI) and the underlying mechanism. Methods Forty-five healthy adult male C57BL/6 mice were randomly divided into control, model, and BMSCs groups. The model and BMSCs groups received a single irradiation dose of 20 Gy to the chest, while the control group did not receive X-ray irradiation. For the BMSCs group, an injection of 1 × 10⁶ BMSCs cells was administered via the tail vein within 6 h after irradiation. In the 5th week, the lung tissue was taken to observe pathological changes with HE staining; examine the expression of the inflammatory factors interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) with immunohistochemical staining; observe the polarization of macrophages with immunofluorescence staining; and measure the expression of the epithelial-mesenchymal transition markers E-cadherin, N-cadherin, and vimentin proteins by Western blot. Results After radiation, the model group developed pulmonary vasodilation and congestion with septal thickening and inflammatory cell infiltration, and these changes were markedly reduced in the BMSCs group. The model group showed significantly down-regulated expression of IL-6 and TNF-α compared with significantly increased levels in the model group (P < 0.01, P < 0.05). Treatment with BMSCs significantly increased the polarization of lung macrophages towards the M2 type, while significantly decreasing the abnormally increased N-cadherin and vimentin levels in RILI mice (P < 0.05, P < 0.01). Conclusion BMSCs have therapeutic effects for RILI mice, which may be through promoting macrophage polarization from M1 to M2.

Objective To investigate the role of hydrogen therapy in reducing radiation-induced lung injury and the specific mechanism. Methods Forty C57BL/6 mice were randomly divided into four groups: normal control group, model group, hydrogen therapy group I, and hydrogen therapy group II. A mouse model of radiation-induced lung injury was established. The pathological changes in the lung tissue of the mice were examined with HE staining. Immunofluorescence staining was used to detect the expression of surface markers of M1 and M2 macrophages to observe macrophage polarization. The expression of interleukin (IL)-6, tumor necrosis factor-α (TNF-α), and IL-10 in the lung tissue was measured by immunohistochemistry. The expression of nuclear factor-kappa B (NF-κB) p65 and phosphorylated NF-κB (P-NF-κB) p65 was measured by Western blot. Results HE staining showed that compared with the control group, the model group exhibited alveolar septal swelling and thickening, vascular dilatation and congestion, and inflammatory cell infiltration in the lung tissue; the hydrogen groups had significantly reduced pathological damage and inflammatory response than the model group, with more improvements in hydrogen group II than in hydrogen group I. Immunohistochemical results showed that compared with those in the control group, the levels of the inflammatory cytokines IL-6 and TNF-α were significantly increased in the model group; the hydrogen groups showed significantly decreased IL-6 and TNF-α levels and a significantly increased level of the anti-inflammatory factor IL-10 than the model group, which were more marked in hydrogen group II than in hydrogen group I. Immunofluorescence results showed that compared with the control group, the expression of the surface marker of M1 macrophages in the model group was significantly upregulated; the hydrogen groups showed significantly downregulated M1 marker and significantly upregulated M2 marker, and hydrogen group II showed significantly increased M2 marker compared with hydrogen group I. Western blot results showed that compared with that in the control group, the ratio of P-NF-κB p65/NF-κB p65 in the model group was significantly increased; the P-NF-κB p65/NF-κB p65 ratio was significantly reduced in the hydrogen groups than in the model group, and was significantly lower in hydrogen group II than in hydrogen group I. Conclusion Hydrogen inhalation therapy may reduce the inflammatory response of radiation-induced lung injury by inhibiting the NF-κB signaling pathway to promote the polarization of the macrophage M1 subtype to the M2 subtype.

Objective To investigate the changes in the expression of cold-inducible RNA-binding protein (CIRBP) in a radiation-induced lung injury model. Methods Thirty male C57BL/6 mice were randomly divided by body weight into control group (no intervention) and model group (single chest X-ray irradiation with a dose of 20 Gy to build a radiation-induced lung injury model). The mice were dissected five weeks after irradiation. Hematoxylin-eosin staining and Masson staining were used to observe the pathological changes of the lung tissue and the deposition of collagen fibers. Immunohistochemistry was used to measure the expression of the inflammatory factors interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) in the lung tissue. qRT-PCR was used to measure the expression of CIRBP mRNA in the lung tissue. The expression of CIRBP protein in the lung tissue was determined by the immunofluorescence assay and Western blot. Results Compared with the control group, the model group showed significant pulmonary vascular congestion, significant inflammatory cell infiltration, significant thickening of some alveolar septa, significantly increased IL-6 expression [(129.41 ± 5.58) vs (187.22 ± 34.77), t = 3.179, P < 0.05], significantly increased TNF-α expression [(137.52 ± 23.53) vs (187.02 ± 19.16), t = 5.069, P < 0.05], significantly increased CIRBP mRNA expression [(1 ± 0.08) vs (1.97 ± 0.39), t = 3.45, P < 0.05], and significantly increased CIRBP protein expression [(9.32 ± 1.26) vs (14.76 ± 1.61), t = 3.751, P < 0.05], by the immunofluorescence assay; [(1.13 ± 0.17) vs (1.49 ± 0.14), t = 2.819, P < 0.05], by Western blot). Conclusion The expression of CIRBP is significantly increased in the radiation-induced lung injury model, which may be an important pro-inflammatory factor in radiation-induced lung injury.

The research shows that personality assessment can be achieved by regression model based on electroencephalogram (EEG). Most of existing researches use event-related potential or power spectral density for personality assessment, which can only represent the brain information of a single region. But some research shows that human cognition is more dependent on the interaction of brain regions. In addition, due to the distribution difference of EEG features among subjects, the trained regression model can not get accurate results of cross subject personality assessment. In order to solve the problem, this research proposes a personality assessment method based on EEG functional connectivity and domain adaption. This research collected EEG data from 45 normal people under different emotional pictures (positive, negative and neutral). Firstly, the coherence of 59 channels in 5 frequency bands was taken as the original feature set. Then the feature-based domain adaptation was used to map the feature to a new feature space. It can reduce the distribution difference between training and test set in the new feature space, so as to reduce the distribution difference between subjects. Finally, the support vector regression model was trained and tested based on the transformed feature set by leave-one-out cross-validation. What's more, this paper compared the methods used in previous researches. The results showed that the method proposed in this paper improved the performance of regression model and obtained better personality assessment results. This research provides a new method for personality assessment.
Algorithms ; Brain ; Electroencephalography/methods* ; Emotions ; Humans ; Personality Assessment

Objective To study effects of temperature on learning and memory of Drosophila melanogaster.Methods Food was put in two centrifuge tubes.Drosophila can smell and eat food through pores in one centrifuge tube but Drosophila can only smell but not eat food through pores in another centrifuge tube with obstacle.After Drosophila were bred at different temperatures,the variation of the numbers of Drosophila in two tubes were observed.Results The number of Drosophila bred at high temperature entering the tube and eating the food was fewer than that at normal temperature and low temperature.Conclusion High temperature can decrease the learning and memory behavior of Drosophila.