A Comparative Study for 2D and 3D Computer-aided Diagnosis Methods for Solitary Pulmonary Nodules

Many computer-aided diagnosis (CAD) methods, including 2D and 3D approaches, have been proposed for solitary pulmonary nodules (SPNs). However, the detection and diagnosis of SPNs remain challenging in many clinical circumstances. One goal of this work is to investigate the relative diagnostic accuracy of 2D and 3D methods. An additional goal is to develop a two-stage approach that combines the simplicity of 2D and the accuracy of 3D methods. The experimental results show statistically significant differences between the diagnostic accuracy of 2D and 3D methods. The results also show that with a very minor drop in diagnostic performance the two-stage approach can significantly reduce the number of nodules needed to be processed by the 3D method, streamlining the computational demand

Gender Determination using Fingerprint Features

Several previous studies have investigated the gender difference of the fingerprint features. However, regarding to the statistical significance of such differences, inconsistent results have been obtained. To resolve this problem and to develop a method for gender determination, this work proposes and tests three fingertip features for gender determination. Fingerprints were obtained from 115 normal healthy adults comprised of 57 male and 58 female volunteers. All persons were born in Taiwan and were of Han nationality. The age range was18-35 years. The features of this study are ridge count, ridge density, and finger size, all three of which can easily be determined by counting and calculation. Experimental results show that the tested ridge density features alone are not very effective for gender determination. However, the proposed ridge count and finger size features of left little fingers are useful, achieving a classification accuracy of 75% (P-valu

FAM129B, an antioxidative protein, reduces chemosensitivity by competing with Nrf2 for Keap1 binding.

BackgroundThe transcription factor Nrf2 is a master regulator of antioxidant response. While Nrf2 activation may counter increasing oxidative stress in aging, its activation in cancer can promote cancer progression and metastasis, and confer resistance to chemotherapy and radiotherapy. Thus, Nrf2 has been considered as a key pharmacological target. Unfortunately, there are no specific Nrf2 inhibitors for therapeutic application. Moreover, high Nrf2 activity in many tumors without Keap1 or Nrf2 mutations suggests that alternative mechanisms of Nrf2 regulation exist.MethodsInteraction of FAM129B with Keap1 is demonstrated by immunofluorescence, colocalization, co-immunoprecipitation and mammalian two-hybrid assay. Antioxidative function of FAM129B is analyzed by measuring ROS levels with DCF/flow cytometry, Nrf2 activation using luciferase reporter assay and determination of downstream gene expression by qPCR and wester blotting. Impact of FAM129B on in vivo chemosensitivity is examined in mice bearing breast and colon cancer xenografts. The clinical relevance of FAM129B is assessed by qPCR in breast cancer samples and data mining of publicly available databases.FindingsWe have demonstrated that FAM129B in cancer promotes Nrf2 activity by reducing its ubiquitination through competition with Nrf2 for Keap1 binding via its DLG and ETGE motifs. In addition, FAM129B reduces chemosensitivity by augmenting Nrf2 antioxidative signaling and confers poor prognosis in breast and lung cancer.InterpretationThese findings demonstrate the important role of FAM129B in Nrf2 activation and antioxidative response, and identify FMA129B as a potential therapeutic target. FUND: The Chang Gung Medical Foundation (Taiwan) and the Ministry of Science and Technology (Taiwan)

Distinct patterns of temporal and directional connectivity among intrinsic networks in the human brain

To determine the spatiotemporal relationships among intrinsic networks of the human brain, we recruited seven neurosurgical patients (four males and three females) who were implanted with intracranial depth electrodes. We first identified canonical resting-state networks at the individual subject level using an iterative matching procedure on each subject's resting-state fMRI data. We then introduced single electrical pulses to fMRI pre-identified nodes of the default network (DN), frontoparietal network (FPN), and salience network (SN) while recording evoked responses in other recording sites within the same networks. We found bidirectional signal flow across the three networks, albeit with distinct patterns of evoked responses within different time windows. We used a data-driven clustering approach to show that stimulation of the FPN and SN evoked a rapid (&lt;70 ms) response that was predominantly higher within the SN sites, whereas stimulation of the DN led to sustained responses in later time windows (85–200 ms). Stimulations in the medial temporal lobe components of the DN evoked relatively late effects (&gt;130 ms) in other nodes of the DN, as well as FPN and SN. Our results provide temporal information about the patterns of signal flow between intrinsic networks that provide insights into the spatiotemporal dynamics that are likely to constrain the architecture of the brain networks supporting human cognition and behavior.SIGNIFICANCE STATEMENTDespite great progress in the functional neuroimaging of the human brain, we still do not know the precise set of rules that define the patterns of temporal organization between large-scale networks of the brain. In this study, we stimulated and then recorded electrical evoked potentials within and between three large-scale networks of the brain, the default network (DN), frontoparietal network (FPN), and salience network (SN), in seven subjects undergoing invasive neurosurgery. Using a data-driven clustering approach, we observed distinct temporal and directional patterns between the three networks, with FPN and SN activity predominant in early windows and DN stimulation affecting the network in later windows. These results provide important temporal information about the interactions between brain networks supporting human cognition and behavior.</jats:p

Key Users and Box Office Analysis in an Interest Based Virtual Community

In recent years, with the growth of the Internet technology, the users of virtual community not only play the role of the information receiver but also a very important one to provide information. However, there is large amount of information aggregated daily and therefore information overloading has become a very serious problem. Under this situation, how to find information efficiently is also a very important issue. In this paper, we believe users in a virtual community may affect each other, especially those with high influence who have been called as Key Users. Therefore, we observe the biggest virtual community of movies on the Internet which is named IMDb (The Internet Movie Database). An architecture also has been proposed that combines Social Networks Analysis and the features of IMDb to discover those users who have high influence in the virtual community. We collected 17 months (January 2010 to May 2011) from IMDb including 17 366 users and 243 074 reviews. By applying the method we proposed, there are about 22 key users and 111 reviews were discovered. We also use the box office of the movies to justify our results