Objective:To aid in the detection of thyroid cancer by using deep learning to differentiate the unique bioimpedance parameter patterns of different thyroid tissues.Methods:An electrical impedance system was designed to measure 331 ex-vivo thyroid specimens from 321 patients during surgery. The impedance data was then analyzed with one dimensional convolution neural (1D-CNN) combining with long short-term memory (LSTM) network models of deep learning. In the process of analysis, we assigned 80% of the data to training set (1072/1340) and the remaining 20% data to the test set (268/1340). The performance of final model was assessed using receiver operating characteristic (ROC) curves. In addition, sensitivity, specificity, positive predictive value, negative predictive value, Youden index were applied to compare impedance model with ultrasound results.Results:The ROC curve of the two-classification (malignant /non-malignant tissue) model showed a good performance (area-under-the-curve AUC=0.94), with an overall accuracy of 91.4%. To better fit clinical practice, we further performed a three-classification (malignant/ benign/ normal tissue) model, of which the areas under ROC curve were 0.91, 0.85, 0.92 for normal, benign, and malignant group, respectively. The results indicated that the area under micro-average ROC curve and the macro-average ROC curve were 0.91 and 0.90, respectively. Moreover, compared with ultrasound, the impedance model exhibited higher specificity.Conclusions:A deep learning model (CNN-LSTM) trained by thyroid electrical impedance spectroscopy (EIS) parameters shows an excellent performance in distinguishing among different in-vitro thyroid tissues, which is promising for applications. In future clinical utility, our study does not replace existing tests, but rather complements others, thus contributing to therapeutic decision-making and management of thyroid disease.

Purpose To explore the artificial intelligence(AI)-assisted diagnosis system of thyroid cancer based on deep transfer learning and evaluate its clinical application value.Methods The HE sections of 682 cases thyroid disease patients(including benign lesions,papillary carcinoma,follicular carci-noma,medullary carcinoma and undifferentiated carcinoma)in the Pathology Department of the Renmin Hospital of Wuhan Uni-versity were collected,scanned into digital sections,divided into training sets and internal test sets according to the ratio of 8 ∶ 2,and the training sets were labeled at the pixel level by patholo-gists.The thyroid cancer classification model was established u-sing VGG image classification algorithm model.In the process of model training,the parameters of the breast cancer region recog-nition model were taken as the initial values,and the parameters of the thyroid cancer region recognition model were optimized through the transfer learning strategy.Then the test set and 633 intraoperative frozen HE section images of thyroid disease in Jianli County People's Hospital,Jingzhou City,Hubei Province wereused as the external test set to evaluate the performance of the established AI-assisted diagnostic model.Results In the internal test set,without the use of the breast cancer region rec-ognition model transfer learning,the accuracy of the AI-assisted diagnosis model was 0.882,and the area under the Receiver op-erating characteristic(AUC)valuewas0.938;However,inthe use of the Transfer learning model,the accuracy of the AI-assis-ted diagnosis model for was 0.926,and the AUC value was 0.956.In the external test set,the accuracy of the zero learning model was 0.872,the AUC value was 0.915,and the accuracy of the Transfer learning model was 0.905,the AUC value was 0.930.Conclusion The AI-assisted diagnosis method for thy-roid cancer established in this study has good accuracy and gen-eralization.With the continuous development of pathological AI research,transfer learning can help improve the performance and generalization ability of the model,and improve the accura-cy of the diagnostic model.

Objective:The residual cancer burden (RCB) evaluation system was used to analyze the influencing factors of the efficacy of neoadjuvant therapy in breast cancer, and to explore the prognostic value of RCB evaluation in neoadjuvant therapy.Methods:Clinicopathologic data and postoperative RCB grading of 364 breast cancer patients who underwent neoadjuvant therapy in Renmin Hospital of Wuhan University from Nov. 2019 to Nov. 2022 were collected. Chi-square test was used to analyze the relationship between RCB grading and clinicopathological parameters, and Spearman’s rank correlation analysis was performed to evaluate the correlation between RCB grading and clinicopathological characteristics. Factors influencing pathologic complete response (pCR) were analyzed by Logistic regression. Kaplan-Meier survival analysis and log-rank test were used to evaluate cumulative survival.Results:Among the 364 patients who underwent neoadjuvant therapy, 129 cases of RCB grade 0 and 235 cases of RCB gradeⅠ-Ⅲ (including 46 cases of RCB gradeⅠ, 109 cases of RCB grade Ⅱ and 80 cases of RCB grade Ⅲ) were obtained after surgery. Histological classification ( χ 2=21.757, P=0.000), estrogen receptor (ER) ( χ 2=52.837, P=0.000), progesterone receptor (PR) ( χ 2=55.658, P=0.000), human epidermal growth factor receptor-2 (HER2) ( χ2=89.040, P=0.000), Ki67 expression ( χ2=12.927, P=0.005), molecular typing ( χ 2=80.793, P=0.000) and preoperative lymph node status ( χ 2=25.764, P=0.000) were all associated with postoperative RCB grading. Further correlation analysis showed that histological grade ( r=-0.229, P=0.000), HER2 expression ( r=-0.465, P=0.000) and Ki67 expression ( r=-0.179, P=0.000) were negatively correlated with RCB grading, while ER ( r=0.352, P=0.000), PR ( r=0.379, P=0.000) and lymph node metastasis ( r=0.214, P=0.000) were positively correlated with RCB grading. Logistic regression analysis showed that high histological grade, negative expression of ER, PR and AR, positive expression of HER2, high proliferation index of Ki67 and no lymph node metastasis were favorable factors for postoperative pCR, and PR, AR and HER2 were independent predictors of postoperative pCR. Kaplan-Meier survival analysis showed significant differences in postoperative cumulative survival among patients with different RCB grades ( P=0.004) . Conclusions:Postoperative RCB grading of breast cancer is closely related to many clinicopathological features before neoadjuvant therapy and survival prognosis. Clinicopathological factors closely related to RCB grading are also important influencing factors affecting the pCR of patients with neoadjuvant therapy. Therefors, RCB grading has a high prognostic value.

Objective:To investigate the role of Caspase-1/gasdermin D (GSDMD) -mediated cell pyroptosis in anti-tumor effect of cisplatin (DDP) in triple-negative breast cancer (TNBC) .Methods:HE staining and immunohistochemical staining were performed to detect the morphological changes and the expression of pyroptosis/apoptosis pathway related proteins in TNBC tissues before and after DDP-based neoadjuvant chemotherapy (NACT) . The TNBC cell line MDA-MB-231 was treated with DDP and the morphological changes were observed. The type of cell death induced by DDP was analyzed by Annexin V-FITC/PI double staining and flow cytometry. Lactate dehydrogenase (LDH) release assay and ELISA were performed to detect the release of LDH and inflammatory factors (IL-18 and IL-1β) in cell culture supernatant after DDP treatment. Western blot (WB) was performed to detect the expression of pyroptosis/apoptosis pathway related proteins in cells after DDP treatment. MDA-MB-231 cells treated with DDP were co-treated with caspase-1 specific inhibitor to inhibit pyroptois or co-treated with caspase-3 specific inhibitor to inhibit apoptosis. The effect of caspase-1 inhibitor or caspase-3 inhibitor on the anti-tumor effect of DDP was detected by MTT assay, clone formation assay, transwell assay and would healing test.Results:Reactive changes in the breast surgical specimen after DDP-based NACT included cell swelling and inflammatory cell aggregation around the tumor bed, which were more similar to pyroptosis. The up-regulation of key molecules of pyroptosis pathway post-NACT was significantly higher than that of key molecules of apoptosis pathway. Further experiments in vitro showed that DDP could induce MDA-MB-231 cells to show pyroptosis-like changes characterized by large bubbles blowing from the cellular membrane. Flow-cytometry analyses showed that the death type of MDA-MB-231 cells caused by DDP was mainly Annexin V +PI + cells (mainly lytic cells, such as pyroptosis) . Additionally, DDP treatment induced significant activation of caspase-1 and GSDMD, increased the release of LDH, IL-18 and IL-1β, however, the activation level of caspase-3, which dominates the apoptosis pathway, was significantly lower than that of caspase-1/GSDMD. Moreover, caspase-1 inhibitors (blocking the classical pyroptosis pathway) had a significantly greater inhibitory effect on the anti-tumor effect of DDP than caspase-3 inhibitors (blocking the apoptosis pathway) . Conclusion:Caspase-1/GSDMD mediated pyroptosis may play a leading role in the anti-tumor effect of DDP in triple-negative breast cancer.

Objective To develop plantar force model of patellofemoral pain (PFP), so as to provide theoretical references for the assessment of PFP rehabilitation. Methods The case-control study was conducted, and a total of 126 patients with PFP and 126 healthy controls matched by gender and age were enrolled in the study. The participants were tested for plantar force and pressure during level walking, and twelve plantar regions were divided and recorded. Whether the participants suffered PFP was analyzed as dependent variable, meanwhile the peak force and peak pressure in 12 plantar regions of participants at selected speed during level walking were analyzed as independent variables. Conditional logistic regression (CLR) equations of peak force and peak pressure with PFP were established, respectively. The receiver-operating characteristic (ROC) curve of the corresponding equations was derived, and the area under ROC curve was calculated to analyzed the validity of different equations on PFP assessment. Results The CLC equation of peak force in 12 plantar regions of the participants with FFP was constructed, and only peak force of lateral heel was in the equation. The CLC equation of peak pressure in each plantar region included medial heel, midfoot, 1st and 2nd metatarsals. Meanwhile, the area under ROC curve of the pressure equation was larger than that of the force equation. Conclusions Peak force and pressure at different plantar regions can be used to assess PFP during level walking, and peak pressure is more effective for assessment.

Isochrysis galbana is considered an ideal bait for functional foods and nutraceuticals of humans because of its high fucoxanthin(Fx)content.However,multi-omics analysis of the regula-tory networks for Fx biosynthesis in I.galbana has not been reported.In this study,we report a high-quality genome assembly of I.galbana LG007,which has a genome size of 92.73 Mb,with a contig N50 of 6.99 Mb and 14,900 protein-coding genes.Phylogenetic analysis confirmed the monophyly of Haptophyta,with I.galbana sister to Emiliania huxleyi and Chrysochromulina tobinii.Evolutionary analysis revealed an estimated divergence time between I.galbana and E.huxleyi of～133 million years ago.Gene family analysis indicated that lipid metabolism-related genes exhibited significant expansion,including IgPLMT,IgOAR1,and IgDEGS1.Metabolome analysis showed that the content of carotenoids in I.galbana cultured under green light for 7 days was higher than that under white light,and β-carotene was the main carotenoid,accounting for 79.09％of the total carotenoids.Comprehensive multi-omics analysis revealed that the content of β-carotene,antheraxanthin,zeaxanthin,and Fx was increased by green light induction,which was significantly correlated with the expression of IgMYB98,IgZDS,IgPDS,IgLHCX2,IgZEP,IgLCYb,and IgNSY.These findings contribute to the understanding of Fx biosynthesis and its regulation,pro-viding a valuable reference for food and pharmaceutical applications.

Decision-making aid for cancer patients is of great significance in the diagnosis and treatment for diseases. Breast cancer is one of the most common malignant tumors in women all over the world, and breast cancer patients have become the main target population for decision-aided research. Application of decision-making assistance for patients in Western countries has developed to a certain extent, while relevant research in China is still at the early stage. There are kinds of intervention forms for patients' decision aids, including traditional brochures and videos, decision aids systems, decision coaching, multidisciplinary breast cancer teams, etc. The tools for decision-making quality evaluation include the patients' awareness for decision-making, participation, decision-making conflict, decision-making satisfaction, decision-making regret, which can provide important guidance for the application of decision-making aid treatment in breast cancer patients in the future.
Breast Neoplasms/therapy* ; China ; Decision Making ; Emotions ; Female ; Humans ; Personal Satisfaction

The application of neoadjuvant therapy in treatment of breast cancer is increasing. Residual cancer burden (RCB) provides valuable prognosis information for patients, which can be used as the main end point of clinical trials. This review summarizes the difficulties and key points in the RCB evaluation, including the experience of tumor bed locating and sampling, and microscopic evaluation of the elements specific to RCB and the application of multidisciplinary cooperation in the whole process, and put forward some management methods to address these challenges, making it possible to standardize RCB evaluation and ordered quality control management.

Objective:To investigate the diagnostic value of GATA binding protein 3 (GATA3) , mammaglobin (MGB) and gross cystic disease fluid protein-15 (GCDFP-15) in breast cancer.Methods:Immunohistochemistry was performed to detect the expression of GATA3, MGB, GCDFP-15, estrogen receptor (ER) , progesterone receptor (PR) , human epidermal growth factor receptor 2 (HER2) and Ki-67 in breast cancer. The breast cancer was divided into primary/metastatic breast cancer, hormone receptor positive/negative, or different molecular types of breast cancer according to the tissue origin and immunophenotype. The positive rates of GATA3, MGB and GCDFP-15 were statistically analyzed.Results:The positive rate of GATA3 in primary/metastatic breast cancer (92.5%; 94.25%) was significantly higher than that of MGB (42.11%; 29.17%) and GCDFP-15 (55.77%; 31.34%) ( P<0.01) , and GATA3 had better sensitivity for evaluating the tumor of unknown origin, especially in malignant hydrops. In addition, the positive rate of MGB and GCDFP-15 in hormone receptor negative and triple negative breast cancer was low, which further increased the difficulty of diagnosis of these two kinds of metastatic breast cancer. However, the positive rate of GATA3 in hormone receptor negative (90.38%) or triple negative breast cancer (85.29%) was significantly higher than that of MGB (20.00%; 5.00%) and GCDFP-15 (35.09%; 33.33%) ( P<0.01) , suggesting that it had great potential diagnostic value in hormone receptor negative and triple negative metastatic breast cancer and was a specific marker superior to MGB and GCDFP-15. Conclusion:GATA3 has a higher diagnostic value than MGB and GCDFP-15 for the assessment of tumors of unknown origin, especially in malignant hydrops, or breast cancer with an immunophenotype of hormone receptor negative and triple negative breast cancer.

At present, the prevention and control situation of epidemics of Corona Virus Disease 2019 (COVID-19) is still serious, medical institutions should provide quality and safe routine medical services while doing their best in the prevention and control of this disease. The purpose of this article is to suggest a way to give quality and safe medical services to patients who need surgical treatment, especially to those who need emergency surgical treatment, with strict classified managements and standard precaution during perioperative period. With those suggestions, we may reduce the incidence of nosocomial infection and contribute to the prevention and control of COVID-19.