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Glioblastoma frequently exhibits therapy-associated subtype transitions to mesenchymal phenotypes with adverse prognosis. Here, we perform multi-omic profiling of 60 glioblastoma primary tumours and use orthogonal analysis of chromatin and RNA-derived gene regulatory networks to identify 38 subtype master regulators, whose cell population-specific activities we further map in published single-cell RNA sequencing data. These analyses identify the oligodendrocyte precursor marker and chromatin modifier SOX10 as a master regulator in RTK I-subtype tumours. In vitro functional studies demonstrate that SOX10 loss causes a subtype switch analogous to the proneural–mesenchymal transition observed in patients at the transcriptomic, epigenetic and phenotypic levels. SOX10 repression in an in vivo syngeneic graft glioblastoma mouse model results in increased tumour invasion, immune cell infiltration and significantly reduced survival, reminiscent of progressive human glioblastoma. These results identify SOX10 as a bona fide master regulator of the RTK I subtype, with both tumour cell-intrinsic and microenvironmental effects. Glioblastoma is divided into four subtypes based on molecular profiling at the methylome and transcriptome level. Here the authors perform an integrative analysis of these subtypes resulting in the identification of SOX10 whose loss induces a mesenchymal phenotype and promotes tumour progression.

Atherosclerosis and atherothrombosis, the major contributors to cardiovascular diseases (CVDs), represent the leading cause of death worldwide. Current pharmacological therapies have been associated with side effects or are insufficient at halting atherosclerotic progression effectively. Pioneering work harnessing the passive diffusion or endocytosis properties of nanoparticles and advanced biotechnologies in creating recombinant proteins for site-specific delivery have been utilized to overcome these limitations. Since CVDs are complex diseases, the most challenging aspect of developing site-specific therapies is the identification of an individual and unique antigenic epitope that is only expressed in lesions or diseased areas. This review focuses on the pathological mechanism of atherothrombosis and discusses the unique targets that are important during disease progression. We review recent advances in site-specific therapy using novel targeted drug-delivery and nanoparticle-carrier systems. Furthermore, we explore the limitations and future perspectives of site-specific therapy for CVDs. Graphical Abstract

DNA-double strand break (DSB), detected by immunostaining of key proteins orchestrating repair, like γH2AX and 53BP1, is well established as a surrogate for tissue radiosensitivity. We hypothesized that the generation of normal brain 3D organoids (“mini-brains”) from human induced pluripotent stem cells (hiPSC) combined with detection of DNA damage repair (DDR) may hold the promise towards developing personalized models for the determination of normal tissue radiosensitivity. In this study, cerebral organoids, an in vitro model that stands in its complexity between 2D cellular system and an organ, have been used. To quantify radiation-induced response, immunofluorescent staining with γH2AX and 53BP1 were applied at early (30 min, initial damage), and late time points (18 and 72 h, residual damage), following clinical standard 2 Gy irradiation. Based on our findings, assessment of DDR kinetics as a surrogate for radiosensitivity in hiPSC derived cerebral organoids is feasible. Further development of mini-brains recapitulating mature adult neuronal tissue and implementation of additional signaling and toxicity surrogates may pave the way towards development of next-generation personalized assessment of radiosensitivity in healthy neuronal tissue.

Two-dimensional nanomaterials hold great promise as electrode materials for the construction of excellent electrochemical energy storage and transformation apparatuses. In the study, metallic layered cobalt sulfide was, firstly, applied to the area of energy storage as a supercapacitor electrode. By a facile and scalable method for cathodic electrochemical exfoliation, metallic layered cobalt sulfide bulk can be exfoliated into high-quality and few-layered nanosheets with size distributions in the micrometer scale range and thickness in the order of several nanometers. With a two-dimensional thin sheet structure of metallic cobalt sulfide nanosheets, not only was a larger active surface area created, but also, the insertion/extraction of ions in the procedure of charge and discharge were enhanced. The exfoliated cobalt sulfide was applied as a supercapacitor electrode with obvious improvement compared with the original sample, and the specific capacitance increased from 307 F∙g−1 to 450 F∙g−1 at the current density of 1 A∙g−1. The capacitance retention rate of exfoliated cobalt sulfide enlarged to 84.7% from the original 81.9% of unexfoliated samples while the current density multiplied by 5 times. Moreover, a button-type asymmetric supercapacitor assembled using exfoliated cobalt sulfide as the positive electrode exhibits a maximum specific energy of 9.4 Wh∙kg−1 at the specific power of 1520 W∙kg−1.

Unikernels provide an efficient and lightweight way to deploy cloud computing services in application-specialized and single-address-space virtual machines (VMs). They can efficiently deploy hundreds of unikernel-based VMs in a single physical server. In such a cloud computing platform, main memory is the primary bottleneck resource for high-density application deployment. Recently, non-volatile memory (NVM) technologies has become increasingly popular in cloud data centers because they can offer extremely large memory capacity at a low expense. However, there still remain many challenges to utilize NVMs for unikernel-based VMs, such as the difficulty of heterogeneous memory allocation and high performance overhead of address translations. In this paper, we present UCat, a heterogeneous memory management mechanism that support multi-grained memory allocation for unikernels. We propose front-end/back-end cooperative address space mapping to expose the host memory heterogeneity to unikernels. UCat exploits large pages to reduce the cost of two-layer address translation in virtualization environments, and leverages slab allocation to reduce memory waste due to internal memory fragmentation. We implement UCat based on a popular unikernel--OSv and conduct extensive experiments to evaluate its efficiency. Experimental results show that UCat can reduce the memory consumption of unikernels by 50% and TLB miss rate by 41%, and improve the throughput of real-world benchmarks such as memslap and YCSB by up to 18.5% and 14.8%, respectively.

The growth of a tumor is tightly linked to the distribution of its cells along a continuum of activation states. Here, we systematically decode the activation state architecture (ASA) in a glioblastoma (GBM) patient cohort through comparison to adult murine neural stem cells. Modelling of these data forecasts how tumor cells organize to sustain growth and identifies the rate of activation as the main predictor of growth. Accordingly, patients with a higher quiescence fraction exhibit improved outcomes. Further, DNA methylation arrays enable ASA-related patient stratification. Comparison of healthy and malignant gene expression dynamics reveals dysregulation of the Wnt-antagonist SFRP1 at the quiescence to activation transition. SFRP1 overexpression renders GBM quiescent and increases the overall survival of tumor-bearing mice. Surprisingly, it does so through reprogramming the tumor’s stem-like methylome into an astrocyte-like one. Our findings offer a framework for patient stratification with prognostic value, biomarker identification, and therapeutic avenues to halt GBM progression. Understanding the growth dynamics of GBMs can help expand therapeutic options. Here, authors use a cross-species computational approach to compare GBM cells to healthy neural stem cells, identifying predictors and modulators of tumour growth, including the Wnt antagonist, SFRP1, which stalls growth in preclinical xenograft models.

Non-volatile memories (NVMs) have aroused vast interest in hybrid memory systems due to their promising features of byte-addressability, high storage density, low cost per byte, and near-zero standby energy consumption. However, since NVMs have limited write endurance, high write latency, and high write energy consumption, it is still challenging to directly replace traditional dynamic random access memory (DRAM) with NVMs. Many studies propose to utilize NVM and DRAM in a hybrid memory system, and explore sophisticated memory management schemes to alleviate the impact of slow NVM on the performance of applications. A few studies architected DRAM and NVM in a cache/memory hierarchy. However, the storage and performance overhead of the cache metadata (i.e., tags) management is rather expensive in this hierarchical architecture. Some other studies architected NVM and DRAM in a single (flat) address space to form a parallel architecture. However, the hot page monitoring and migration are critical for the performance of applications in this architecture. In this paper, we propose Transformer, an OS-supported reconfigurable hybrid memory architecture to efficiently use DRAM and NVM without redesigning the hardware architecture. To identify frequently accessed (hot) memory pages for migration, we propose to count the number of page accesses in OSes by sampling the access bit of pages periodically. We further migrate the identified hot pages from NVM to DRAM to improve the performance of hybrid memory system. More importantly, Transformer can simulate a hierarchical hybrid memory architecture while DRAM and NVM are physically managed in a flat address space, and can dynamically shift the logical memory architecture between parallel and hierarchical architectures according to applications’ memory access patterns. Experimental results show that Transformer can improve the application performance by 62% on average (up to 2.7×) compared with an NVM-only system, and can also improve performance by up to 79% and 42% (21% and 24% on average) compared with hierarchical and parallel architectures, respectively.

Human induced pluripotent stem cells (hiPSCs) may provide potential resource for regenerative medicine research, including generation of insulin-producing cells for diabetes research and insulin production. Testosterone (T) is an androgen hormone which promotes protein synthesis and improves the management of type 2 diabetes in clinical studies. Concurrently, co-existed hyperandrogenism and hyperinsulinism is frequently observed in polycystic ovary syndrome, congenital adrenal hyperplasia and some of Wermer's syndrome. However, the relationship among androgens, insulin and the differentiation of pancreatic β cells is still not fully clear. Here we find that T improves the differentiation efficiency of insulin-producing cells from hiPSCs. The addition of T into routine differentiation formula for pancreatic β cells increases the differentiation efficiency from 12% to 35%. The administration of T promotes the expression of key genes associated with β cells differentiation including NGN3, NEUROD1 and INS. This finding benefits the ongoing process to optimize the differentiation protocol of pancreatic β cells from hiPSCs, and provides some degree of understanding the clinical management of T for type 2 diabetes.

Congenital hyperinsulinism (CHI) is a rare genetic disorder characterized by excess insulin secretion, which results in hypoglycemia. Mutation of sulfonylurea receptor 1 (SUR1), encoded by the ABCC8 gene, is the main cause of CHI. Here, we captured the phenotype of excess insulin secretion through pancreatic differentiation of ABCC8 -deficient stem cells generated by the CRISPR/Cas9 system. ABCC8- deficient insulin-producing cells secreted higher insulin than their wild-type counterparts, and the excess insulin secretion was rescued by nifedipine, octreotide and nicorandil. Further, we tested the role of SUR1 in response to different potassium levels and found that dysfunction of SUR1 decreased the insulin secretion rate in low and high potassium environments. Hence, pancreatic differentiation of ABCC8- deficient cells recapitulated the CHI disease phenotype in vitro , which represents an attractive model to further elucidate the function of SUR1 and to develop and screen for novel therapeutic drugs.