SUMMARY Hypoxic and VHL-deficient cells use glutamine to generate citrate and lipids through reductive carboxylation (RC) of α-ketoglutarate. To gain insights into the role of HIF and the molecular mechanisms underlying RC, we took advantage of a panel of disease-associated VHL mutants and showed that HIF expression is necessary and sufficient for the induction of RC in human renal cell carcinoma (RCC) cells. HIF expression drastically reduced intracellular citrate levels. Feeding VHL-deficient RCC cells with acetate or citrate or knocking down PDK-1 and ACLY restored citrate levels and suppressed RC. These data suggest that HIF-induced low intracellular citrate levels promote the reductive flux by mass action to maintain lipogenesis. Using [1–13C] glutamine, we demonstrated in vivo RC activity in VHL-deficient tumors growing as xenografts in mice. Lastly, HIF rendered VHL-deficient cells sensitive to glutamine deprivation in vitro, and systemic administration of glutaminase inhibitors suppressed the growth of RCC cells as mice xenografts.

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Brain-inspired neuromorphic computing is expected to revolutionize the architecture of conventional digital computers and lead to a new generation of powerful computing paradigms, where memristors with analog resistive switching are considered to be potential solutions for synapses. Here we propose and demonstrate a novel approach to engineering the analog switching linearity in TaOx based memristors, that is, by homogenizing the filament growth/dissolution rate via the introduction of an ion diffusion limiting layer (DLL) at the TiN/TaOx interface. This has effectively mitigated the commonly observed two-regime conductance modulation behavior and led to more uniform filament growth (dissolution) dynamics with time, therefore significantly improving the conductance modulation linearity that is desirable in neuromorphic systems. In addition, the introduction of the DLL also served to reduce the power consumption of the memristor, and important synaptic learning rules in biological brains such as spike timing dependent plasticity were successfully implemented using these optimized devices. This study could provide general implications for continued optimizations of memristor performance for neuromorphic applications, by carefully tuning the dynamics involved in filament growth and dissolution.

Targeted therapies and the consequent adoption of “personalized” oncology have achieved notable successes in some cancers; however, significant problems remain with this approach. Many targeted therapies are highly toxic, costs are extremely high, and most patients experience relapse after a few disease-free months. Relapses arise from genetic heterogeneity in tumors, which harbor therapy-resistant immortalized cells that have adopted alternate and compensatory pathways (i.e., pathways that are not reliant upon the same mechanisms as those which have been targeted). To address these limitations, an international task force of 180 scientists was assembled to explore the concept of a low-toxicity “broad-spectrum” therapeutic approach that could simultaneously target many key pathways and mechanisms. Using cancer hallmark phenotypes and the tumor microenvironment to account for the various aspects of relevant cancer biology, interdisciplinary teams reviewed each hallmark area and nominated a wide range of high-priority targets (74 in total) that could be modified to improve patient outcomes. For these targets, corresponding low-toxicity therapeutic approaches were then suggested; many of which were phytochemicals. Proposed actions on each target and all of the approaches were further reviewed for known effects on other hallmark areas and the tumor microenvironment. Potential contrary or procarcinogenic effects were found for 3.9% of the relationships between targets and hallmarks, and mixed evidence of complementary and contrary relationships was found for 7.1%. Approximately 67% of the relationships revealed potentially complementary effects, and the remainder had no known relationship. Among the approaches, 1.1% had contrary, 2.8% had mixed and 62.1% had complementary relationships. These results suggest that a broad-spectrum approach should be feasible from a safety standpoint. This novel approach has potential to help us address disease relapse, which is a substantial and longstanding problem, so a proposed agenda for future research is offered.

The platelet-derived growth factor (PDGF) signaling system contributes to tumor angiogenesis and vascular remodeling. Here we show in mouse tumor models that PDGF-BB induces erythropoietin (EPO) mRNA and protein expression by targeting stromal and perivascular cells that express PDGF receptor-β (PDGFR-β). Tumor-derived PDGF-BB promoted tumor growth, angiogenesis and extramedullary hematopoiesis at least in part through modulation of EPO expression. Moreover, adenoviral delivery of PDGF-BB to tumor-free mice increased both EPO production and erythropoiesis, as well as protecting from irradiation-induced anemia. At the molecular level, we show that the PDGF-BB-PDGFR-bβ signaling system activates the EPO promoter, acting in part through transcriptional regulation by the transcription factor Atf3, possibly through its association with two additional transcription factors, c-Jun and Sp1. Our findings suggest that PDGF-BB-induced EPO promotes tumor growth through two mechanisms: first, paracrine stimulation of tumor angiogenesis by direct induction of endothelial cell proliferation, migration, sprouting and tube formation, and second, endocrine stimulation of extramedullary hematopoiesis leading to increased oxygen perfusion and protection against tumor-associated anemia.

Memory cells have always been an important element of information technology. With emerging technologies like big data and cloud computing, the scale and complexity of data storage has reached an unprecedented peak with a much higher requirement for memory technology. As is well known, better data storage is mostly achieved by miniaturization. However, as the size of the memory device is reduced, a series of problems, such as drain gate‐induced leakage, greatly hinder the performance of memory units. To meet the increasing demands of information technology, novel and high‐performance memory is urgently needed. Fortunately, emerging memory technologies are expected to improve memory performance and drive the information revolution. This review will focus on the progress of several emerging memory technologies, including two‐dimensional material‐based memories, resistance random access memory (RRAM), magnetic random access memory (MRAM), and phase‐change random access memory (PCRAM). Advantages, mechanisms, and applications of these diverse memory technologies will be discussed in this review.

promising concepts have emerged to address this need, including neuromorphic computing drawing inspiration from the architecture and principle of human brains [5][6][7] as well as in-memory computing that performs logic and memory operations in the same physical devices. [8][9][10] For both technologies it is of fundamental importance to fabricate scalable devices that can meet the respective memory and computing requirements.In order to achieve the ambitious goal of brain like computing, extensive efforts have been devoted to developing nanodevices capable of mimicking the plasticity of biological synapses, including memristive devices, [6,[11][12][13][14][15] atomic switches, [16,17] phase change memories, [18][19][20] and magnetic tunnel junctions. [21] These devices have successfully emulated several synaptic learning rules in biological systems, such as spike timing dependent plasticity, [6,7,12,14,22] spike rate dependent plasticity, [16,[22][23][24] paired pulse facilitation, [13,25] etc. However, it should be pointed out that most previous studies were limited to the implementation of homosynaptic plasticity, meaning the synaptic behavior is both enabled and sensed by the same pair of terminals, corresponding to the two electrodes of the abovementioned devices. A fundamentally distinct form of learning rule is the so-called heterosynaptic plasticity, where the synaptic activity between the pre-and post-synaptic terminals can be effectively modulated by a third terminal, which was found to be essential for a large number of key biological functions including associative learning, long-term memory, and elimination of synaptic runaway dynamics. [26,27] Recently, heterosynaptic plasticity was demonstrated using physically evolving networks (PENs) with a planar configuration, which can spontaneously and adaptively evolve depending on the stimuli fed from multi-terminals. [28] Nevertheless, the planar configuration of the PENs placed an essential constraint on device scalability, a critical issue for potential applications in integrated neuromorphic systems.Besides neuromorphic computing, an alternative approach to addressing the von Neumann bottleneck is to perform logic operations using emerging nonvolatile memory devices, e.g., memristors, [8,9] thereby enabling fused logic and memory. This concept has been firstly fulfilled via sequential logic operations employing a set of memristors either in parallel [8] or serial [29] The development of smart, scalable, and power efficient computers relies on innovative technologies that can distribute memory alongside processing, such as emerging neuromorphic computing and in-memory logic technologies. Here, a type of vertical 3-terminal oxide based nanoionic device capable of implementing heterosynaptic plasticity and nonvolatile Boolean logic simultaneously is demonstrated. The heterosynaptic plasticity endows the devices with facilely tunable synaptic kinetics via tailoring modulatory signals, which is shown to be crucial for achieving optimized learning scheme, the...