The rapid development of deep learning (DL) has driven single image super-resolution (SR) into a new era. However, in most existing DL based image SR networks, the information flows are solely feedforward, and the high-level features cannot be fully explored. In this paper, we propose the gated multiple feedback network (GMFN) for accurate image SR, in which the representation of low-level features are efficiently enriched by rerouting multiple high-level features. We cascade multiple residual dense blocks (RDBs) and recurrently unfolds them across time. The multiple feedback connections between two adjacent time steps in the proposed GMFN exploits multiple high-level features captured under large receptive fields to refine the low-level features lacking enough contextual information. The elaborately designed gated feedback module (GFM) efficiently selects and further enhances useful information from multiple rerouted high-level features, and then refine the low-level features with the enhanced high-level information. Extensive experiments demonstrate the superiority of our proposed GMFN against stateof-the-art SR methods in terms of both quantitative metrics and visual quality. Code is available at https://github.com/liqilei/GMFN.

Dysfunctional default mode network (DMN) has been observed in various mental disorders, including epilepsy (see review Broyd et al. [2009]: Neurosci Biobehav Rev 33:279–296). Because interictal epileptic discharges may affect DMN, resting-state fMRI was used in this study to determine DMN functional connectivity in 14 healthy controls and 12 absence epilepsy patients. To avoid interictal epileptic discharge effects, testing was performed within interictal durations when there were no interictal epileptic discharges. Cross-correlation functional connectivity analysis with seed at posterior cingulate cortex, as well as region-wise calculation in DMN, revealed decreased integration within DMN in the absence epilepsy patients. Region-wise functional connectivity among the frontal, parietal, and temporal lobe was significantly decreased in the patient group. Moreover, functional connectivity between the frontal and parietal lobe revealed a significant negative correlation with epilepsy duration. These findings indicated DMN abnormalities in patients with absence epilepsy, even during resting interictal durations without interictal epileptic discharges. Abnormal functional connectivity in absence epilepsy may reflect abnormal anatomo-functional architectural integration in DMN, as a result of cognitive mental impairment and unconsciousness during absence seizure.

Absence epilepsy is believed to be associated with the abnormal interactions between the cerebral cortex and thalamus. Besides the direct coupling, anatomical evidence indicates that the cerebral cortex and thalamus also communicate indirectly through an important intermediate bridge–basal ganglia. It has been thus postulated that the basal ganglia might play key roles in the modulation of absence seizures, but the relevant biophysical mechanisms are still not completely established. Using a biophysically based model, we demonstrate here that the typical absence seizure activities can be controlled and modulated by the direct GABAergic projections from the substantia nigra pars reticulata (SNr) to either the thalamic reticular nucleus (TRN) or the specific relay nuclei (SRN) of thalamus, through different biophysical mechanisms. Under certain conditions, these two types of seizure control are observed to coexist in the same network. More importantly, due to the competition between the inhibitory SNr-TRN and SNr-SRN pathways, we find that both decreasing and increasing the activation of SNr neurons from the normal level may considerably suppress the generation of spike-and-slow wave discharges in the coexistence region. Overall, these results highlight the bidirectional functional roles of basal ganglia in controlling and modulating absence seizures, and might provide novel insights into the therapeutic treatments of this brain disorder.

TFE3-translocation renal cell carcinoma (TFE3-tRCC) is a rare and heterogeneous subtype of kidney cancer with no standard treatment for advanced disease. We describe comprehensive molecular characteristics of 63 untreated primary TFE3-tRCCs based on whole-exome and RNA sequencing. TFE3-tRCC is highly heterogeneous, both clinicopathologically and genotypically. ASPSCR1-TFE3 fusion and several somatic copy number alterations, including the loss of 22q, are associated with aggressive features and poor outcomes. Apart from tumors with MED15-TFE3 fusion, most TFE3-tRCCs exhibit low PD-L1 expression and low T-cell infiltration. Unsupervised transcriptomic analysis reveals five molecular clusters with distinct angiogenesis, stroma, proliferation and KRAS down signatures, which show association with fusion patterns and prognosis. In line with the aggressive nature, the high angiogenesis/stroma/proliferation cluster exclusively consists of tumors with ASPSCR1-TFE3 fusion. Here, we describe the genomic and transcriptomic features of TFE3-tRCC and provide insights into precision medicine for this disease.

Soft neural electrode arrays that are mechanically matched between neural tissues and electrodes offer valuable opportunities for the development of disease diagnose and brain computer interface systems. Here, a thermal release transfer printing method for fabrication of stretchable bioelectronics, such as soft neural electrode arrays, is presented. Due to the large, switchable and irreversible change in adhesion strength of thermal release tape, a low‐cost, easy‐to‐operate, and temperature‐controlled transfer printing process can be achieved. The mechanism of this method is analyzed by experiments and fracture‐mechanics models. Using the thermal release transfer printing method, a stretchable neural electrode array is fabricated by a sacrificial‐layer‐free process. The ability of the as‐fabricated electrode array to conform different curvilinear surfaces is confirmed by experimental and theoretical studies. High‐quality electrocorticography signals of anesthetized rat are collected with the as‐fabricated electrode array, which proves good conformal interface between the electrodes and dura mater. The application of the as‐fabricated electrode array on detecting the steady‐state visual evoked potentials research is also demonstrated by in vivo experiments and the results are compared with those detected by stainless‐steel screw electrodes.