Dysregulated autophagy is central to the pathogenesis and therapeutic development of cancer. However, how autophagy is regulated in cancer is not well understood and genes that modulate cancer autophagy are not fully defined. To gain more insights into autophagy regulation in cancer, we performed a large-scale RNA interference screen in K562 human chronic myeloid leukemia cells using monodansylcadaverine staining, an autophagy-detecting approach equivalent to immunoblotting of the autophagy marker LC3B or fluorescence microscopy of GFP-LC3B. By coupling monodansylcadaverine staining with fluorescence-activated cell sorting, we successfully isolated autophagic K562 cells where we identified 336 short hairpin RNAs. After candidate validation using Cyto-ID fluorescence spectrophotometry, LC3B immunoblotting, and quantitative RT-PCR, 82 genes were identified as autophagy-regulating genes. 20 genes have been reported previously and the remaining 62 candidates are novel autophagy mediators. Bioinformatic analyses revealed that most candidate genes were involved in molecular pathways regulating autophagy, rather than directly participating in the autophagy process. Further autophagy flux assays revealed that 57 autophagy-regulating genes suppressed autophagy initiation, whereas 21 candidates promoted autophagy maturation. Our RNA interference screen identifies identified genes that regulate autophagy at different stages, which helps decode autophagy regulation in cancer and offers novel avenues to develop autophagy-related therapies for cancer.

In the present study, the cascaded interactions between stimuli and neural and hemodynamic responses were modeled using linear systems. These models provided the theoretical hypotheses that were tested against the electroencephalography (EEG) and blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) data recorded from human subjects during prolonged periods of repeated visual stimuli with a variable setting of the inter-stimulus interval (ISI) and visual contrast. Our results suggest that (1) neural response is nonlinear only when ISI

Electro- or magnetoencephalography (EEG/MEG) are of utmost advantage in studying transient neuronal activity and its timing with respect to behavior in the working human brain. Direct localization of the neural substrates underlying EEG/MEG is commonly achieved by modeling neuronal activity as dipoles. However, the success of neural source localization with the dipole model has only been demonstrated in relatively simple localization tasks owing to the simplified model and its insufficiency in differentiating cortical sources with different extents. It would be of great interest to image complex neural activation with multiple sources of different cortical extensions directly from EEG/MEG. We have investigated this crucial issue by adding additional parameters to the dipole model, leading to the multipole model to better represent the extended sources confined to the convoluted cortical surface. The localization of multiple cortical sources is achieved by using the subspace source localization method with the multipole model. Its performance is evaluated with simulated data as compared with the dipole model, and further illustrated with the real data obtained during visual stimulations in human subjects. The interpretation of the localization results is fully supported by our knowledge about their anatomic locations and functional magnetic resonance imaging data in the same experimental setting. Methods for estimating multiple neuronal sources at cortical areas will facilitate our ability to characterize the cortical electrical activity from simple, early sensory components to more complex networks, such as in visual, motor, and cognitive tasks.

In the human visual system, the internal representation of the left and right visual hemifields is split at the midline of the two cerebral hemispheres. The present study aims to address the questions of when and where the lateralized cortical visual representations are merged to form an intact percept by using a multimodal neuroimaging approach. Visual evoked potential (VEP) and functional magnetic resonance imaging (fMRI) data were acquired from a group of healthy subjects presented with unilateral versus bilateral visual stimuli. Cortical activities involved in processing bilateral visual information are expected to be equally responsive to ipsilateral and contralateral stimuli, and demonstrate spatial nonlinearity in the response to bilateral stimuli. Utilizing these features, we performed integrative as well as separate analyses for both VEP and fMRI data. The present results suggest that i) the majority of cortical activity that integrates visual information across hemifields takes place at extrastriate areas during late visual processing, and that ii) the lateral occipito-temporal (LOT) regions (likely the MT+ complex) and the medial occipital cortex (i.e. V1) may contribute to bilateral visual integration during early visual processing. Our findings are generally in agreement with the bottom-up visual hierarchy, with the exception of the evidence suggesting an early activation of the higher-tier LOT areas and the influence from ipsilateral visual inputs upon the V1 response.

We present the 3-D EEG source images reconstructed by using the minimum norm least square (MNLS) method in combination with the functional magnetic resonance imaging (fMRI) statistical parametric mapping. For a group of five normal subjects, electroencephalogram (EEG) and fMRI signals responding to the full-view checkerboard pattern-reversal visual stimulation were recorded simultaneously and separately. The electrical activities in V1/V2 and V5 were successfully imaged in the N75-P100-N145 and P100-N145 components, respectively. The present results demonstrate the merits of high-resolution spatiotemporal functional neuroimaging by integrating the simultaneously recorded fMRI and EEG data.