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Ultra-selective and fast transport of K

The salinity gradient between seawater and river water is a clean energy source and an alternative solution for the increasing energy demands. A membrane-based reverse electrodialysis technique is a promising strategy to convert osmotic energy to electricity. To overcome the limits of traditional membranes with low efficiency and high resistance, nanofluidic is an emerging technique to promote osmotic energy harvesting. Here, we engineer a high-performance nanofluidic device with a hybrid membrane composed of a silk nanofibril membrane and an anodic aluminum oxide membrane. The silk nanofibril membrane, as a screening layer with condensed negative surface and nanochannels, dominates the ion transport; the anodic aluminum oxide membrane, as a supporting substrate, offers tunable channels and amphoteric groups. Thus, a nanofluidic membrane with asymmetric geometry and charge polarity is established, showing low resistance, high-performance energy conversion, and long-term stability. The system paves avenues for sustainable power generation, water purification, and desalination., Membrane-based reverse electrodialysis is promising for salinity gradient power generation, but achieving efficiency and stability is challenging. Here the authors design silk nanofibril-based hybrid membranes to realize high-performance capture of osmotic energy from ambient waters.

Retinal screening contributes to early detection of diabetic retinopathy and timely treatment. To facilitate the screening process, we develop a deep learning system, named DeepDR, that can detect early-to-late stages of diabetic retinopathy. DeepDR is trained for real-time image quality assessment, lesion detection and grading using 466,247 fundus images from 121,342 patients with diabetes. Evaluation is performed on a local dataset with 200,136 fundus images from 52,004 patients and three external datasets with a total of 209,322 images. The area under the receiver operating characteristic curves for detecting microaneurysms, cotton-wool spots, hard exudates and hemorrhages are 0.901, 0.941, 0.954 and 0.967, respectively. The grading of diabetic retinopathy as mild, moderate, severe and proliferative achieves area under the curves of 0.943, 0.955, 0.960 and 0.972, respectively. In external validations, the area under the curves for grading range from 0.916 to 0.970, which further supports the system is efficient for diabetic retinopathy grading., As the leading cause of vision loss in working-age adults, diabetic retinopathy requires routinely retinal screening. Here the authors develop a deep learning system that can facilitate the screening by providing real-time image quality assessment, lesions detection, and grades across the disease spectrum.

Profound global loss of DNA methylation is a hallmark of many cancers. One potential consequence of this is the reactivation of transposable elements (TEs) which could stimulate the immune system via cell-intrinsic antiviral responses. Here, we develop REdiscoverTE, a computational method for quantifying genome-wide TE expression in RNA sequencing data. Using The Cancer Genome Atlas database, we observe increased expression of over 400 TE subfamilies, of which 262 appear to result from a proximal loss of DNA methylation. The most recurrent TEs are among the evolutionarily youngest in the genome, predominantly expressed from intergenic loci, and associated with antiviral or DNA damage responses. Treatment of glioblastoma cells with a demethylation agent results in both increased TE expression and de novo presentation of TE-derived peptides on MHC class I molecules. Therapeutic reactivation of tumor-specific TEs may synergize with immunotherapy by inducing inflammation and the display of potentially immunogenic neoantigens., Treatment with demethylation agents can reactivate transposable elements. Here in glioblastoma, the authors also show that this is accompanied by de novo presentation of TE-derived peptides on MHC class I molecules.

Transcriptional deregulation has a vital role in glioblastoma multiforme (GBM). Thus, identification of epigenetic modifiers essential for oncogenic transcriptional programs is a key to designing effective therapeutics for this deadly disease. Here we report that Protein Arginine Methyltransferase 2 (PRMT2) is highly expressed in GBM and correlated with poor prognosis. The silencing or inactivation of PRMT2 inhibits GBM cell growth and glioblastoma stem cell self-renewal in vitro, and suppresses orthotopic tumor growth, accompanied with significant deregulation of genes mainly associated with cell cycle progression and pathways in cancer. Mechanistically PRMT2 is responsible for H3R8 asymmetric methylation (H3R8me2a), whose enrichment at promoters and enhancers is closely correlated with known active histone marks and is required for the maintenance of target gene expression. Together, this study demonstrates that PRMT2 acts as a transcriptional co-activator for oncogenic gene expression programs in GBM pathogenesis and provides a rationale for PRMT2 targeting in aggressive gliomas., The role of protein arginine methyltransferases (PRMTs) in epigenetic regulation in cancer is still poorly understood. Here, the authors show that PRMT2 is highly expressed in Glioblastoma multiforme (GBM) and provide evidence that PRMT2 acts as a transcriptional co-activator for oncogenic gene expression programs, at least partly dependent on its H3R8me2a activity, in GBM pathogenesis.