Background-The incidence of thyroid cancer is rising steadily because of overdiagnosis and overtreatment conferred by widespread use of sensitive imaging techniques for screening. This overall incidence growth is especially driven by increased diagnosis of indolent and welldifferentiated papillary subtype and early-stage thyroid cancer, whereas the incidence of advancedstage thyroid cancer has increased marginally. Thyroid ultrasound is frequently used to diagnose thyroid cancer. The aim of this study was to use deep convolutional neural network (DCNN) models to improve the diagnostic accuracy of thyroid cancer by analysing sonographic imaging data from clinical ultrasounds.Methods-We did a retrospective, multicohort, diagnostic study using ultrasound images sets from three hospitals in China. We developed and trained the DCNN model on the training set, 131 731 ultrasound images from 17 627 patients with thyroid cancer and 180 668 images from 25 325 controls from the thyroid imaging database at Tianjin Cancer Hospital. Clinical diagnosis of the training set was made by 16 radiologists from Tianjin Cancer Hospital. Images from anatomical sites that were judged as not having cancer were excluded from the training set and only individuals with suspected thyroid cancer underwent pathological examination to confirm diagnosis. The model's diagnostic performance was validated in an internal validation set from Tianjin Cancer Hospital (8606 images from 1118 patients) and two external datasets in China (the

p53, apoptosis, and senescence are frequently activated in preneoplastic lesions and are barriers to progression to malignancy. These barriers have been suggested to result from an ATM-mediated DNA damage response (DDR), which may follow oncogene-induced hyperproliferation and ensuing DNA replication stress. To elucidate the currently untested role of DDR in breast cancer initiation, we examined the effect of oncogene expression in several murine models of breast cancer. We did not observe a detectable DDR in early hyperplastic lesions arising in transgenic mice expressing several different oncogenes. However, DDR signaling was strongly induced in preneoplastic lesions arising from individual mammary cells transduced in vivo by retroviruses expressing either PyMT or ErbB2. Thus, activation of an oncogene after normal tissue development causes a DDR. Furthermore, in this somatic ErbB2 tumor model, ATM, and thus DDR, is required for p53 stabilization, apoptosis, and senescence. In palpable tumors in this model, p53 stabilization and apoptosis are lost, but unexpectedly senescence remains in many tumor cells. Thus, this murine model fully recapitulates early DDR signaling; the eventual suppression of its endpoints in tumorigenesis provides compelling evidence that ErbB2-induced aberrant mammary cell proliferation leads to an ATM-mediated DDR that activates apoptosis and senescence, and at least the former must be overcome to progress to malignancy. This in vivo study also uncovers an unexpected effect of ErbB2 activation previously known for its prosurvival roles, and suggests that protection of the ATM-mediated DDR-p53 signaling pathway may be important in breast cancer prevention.oncogene | DNA damage response | p53 | apoptosis | senescence

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The basal cell-like subtype is associated with a poor prognosis and a family history was a negative predictor in the basal cell-like subtype.

Medullary thyroid carcinoma (MTC) is highly malignant and quite different from the most common papillary thyroid carcinoma (PTC). However, most of the ultrasonic evaluation systems mainly aim at PTC at present. This study aims to evaluate the applicability of modified TI‐RADS in diagnosing MTC and compare the sonographic differences of MTC, PTC, and benign nodules. Three thousand two hundred and forty‐two thyroid nodules images confirmed by pathology were categorized according to modified TI‐RADS and ACR TI‐RADS classification. The performances of two TI‐RADS were assessed by ROC curves. The correlations between classifications with the pathology and the consistency of different doctors were evaluated. The ultrasonic differences of MTC, PTC, and benign nodules were analyzed. As a result, the number of high suspicious US features increased, the malignant risk of nodules also increased of two classifications, with significant differences between categories ( P < 0.001). Spearman correlation coefficients were 0.751 (modified TI‐TADS) and 0.744 (ACR TI‐RADS). Areas under the ROC curve of the modified TI‐RADS and ACR TI‐RADS were 0.960 and 0.872 ( P < 0.001). At Best cut off points, the diagnostic value of modified TI‐RADS was higher than that of ACR TI‐RADS with a higher specificity, PPV, accuracy, and Youden index). By using modified TI‐RADS to diagnose MTC and PTC, the sensitivity, specificity, NPV, accuracy, and Youden index were higher in MTC than PTC. The Kendall's correlation coefficients were 0.962, 0.930, and 0.987. MTC had special ultrasonography characters compared with PTC and benign nodules. These results suggest that modified TI‐RADS is better than ACR TI‐RADS in diagnosing thyroid carcinomas. Diagnostic value to MTC of modified TI‐RADS is slightly higher than that to PTC, and the categorical results of different doctors were consistent. MTC had several particular features contrast to PTC and benign nodules.

Fine-needle aspiration (FNA) is routinely used in the preoperative evaluation of thyroid nodules. However, approximately 5-20% of thyroid nodules are considered indeterminate or suspicious cases that do not meet clinical standards. The B-RAF(V600E) mutation has been reported in FNA specimens. We conducted a systematic review to evaluate the diagnostic value of testing for B-RAF(V600E) in thyroid nodules that are difficult to diagnose by FNA. A systematic literature search was performed from January 1, 2002 to June 30, 2012. Articles were obtained by searching two electronic databases (MEDLINE and EMBASE), hand searching selected journals, and contacting authors. Article quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) tool. Sensitivity, specificity, and other measures of accuracy were pooled using random effects models. Summary receiver operating characteristic (SROC) curves were used to summarize overall diagnostic accuracy. A total of 16 studies incorporating 1131 patients were included in a meta-analysis on diagnostic accuracy of B-RAF(V600E) tests. Pooled sensitivity was 0.60 (95% confidence interval [CI]: 0.556-0.634), pooled specificity was 0.99 (95% CI 0.976-0.997), and the area under the curve of the SROC curve was 0.8376. Q index value was 0.7696. Our data suggest a potentially useful adjunct to evaluating thyroid nodules that are difficult to diagnose. The B-RAF(V600E) test has a high positive predictive value and could help clinicians formulate a more individualized treatment schedule. When supplemented with other noninvasive test methods, the B-RAF(V600E) test could be a powerful adjunct with extensive clinical applications.

Wireless multimedia sensor networks (WMSNs) differ from the traditional wireless sensor networks (WSNs) due to their characteristic of directivity. In this work, by analyzing the virtual potential field-based algorithm, which can not really describe the coverage overlap of the node, we propose an electrostatic field-based coverage-enhancing algorithm (EFCEA). Firstly, we build the virtual field and grid in the sense sector and define the grid's number covered by every neighbor as charge and calculate the correlation degree of every neighbor for all sensors. Secondly, redundant sensors are shut off if their gird are wholly covered and waked up according to correlation degree to 'die out' sensor, coverage of networks can be enhanced although large numbers of redundant sensors are shut off by their 'centroid' point revolving round the sensor under the repel force based electrostatic field. Simulation results are presented for demonstrating the effectiveness of our approach.