CMOS plus stochastic nanomagnets enabling heterogeneous computers for probabilistic inference and learning.

Extending Moore's law by augmenting complementary-metal-oxide semiconductor (CMOS) transistors with emerging nanotechnologies (X) has become increasingly important. One important class of problems involve sampling-based Monte Carlo algorithms used in probabilistic machine learning, optimization, and quantum simulation. Here, we combine stochastic magnetic tunnel junction (sMTJ)-based probabilistic bits (p-bits) with Field Programmable Gate Arrays (FPGA) to create an energy-efficient CMOS + X (X = sMTJ) prototype. This setup shows how asynchronously driven CMOS circuits controlled by sMTJs can perform probabilistic inference and learning by leveraging the algorithmic update-order-invariance of Gibbs sampling. We show how the stochasticity of sMTJs can augment low-quality random number generators (RNG). Detailed transistor-level comparisons reveal that sMTJ-based p-bits can replace up to 10,000 CMOS transistors while dissipating two orders of magnitude less energy. Integrated versions of our approach can advance probabilistic computing involving deep Boltzmann machines and other energy-based learning algorithms with extremely high throughput and energy efficiency.

Identification of an ADME-related gene for forecasting the prognosis and responding to immunotherapy in sarcomas.

There are more than 170 subtypes of sarcomas (SARC), which pose a challenge for diagnosis and patient management. Relatively simple or complex karyotypes play an indispensable role in the early diagnosis and effective treatment of SARC. The genes related to absorption, distribution, metabolism, and excretion (ADME) of a drug can serve as prognostic biomarkers of cancer and potential drug targets. In this study, a risk score signature was created. The SARC cohort was downloaded from The Cancer Genome Atlas (TCGA) database, and divided into high-risk group and low-risk group according to the median value of risk score. Compared with high-risk group, low-risk group has a longer survival time, which is also verified in osteosarcoma cohort from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. In addition, the relationship between the signature and immunophenotypes, including status of immune cell infiltration and immune checkpoint expression, was explored. Then, we found that high-risk group is in immunosuppressive status. Finally, we verified that PPARD played a role as a carcinogen in osteosarcoma, which provided a direction for targeted treatment of osteosarcoma in the future. Generally speaking, the signature can not only help clinicians predict the prognosis of patients with SARC, but also provide a theoretical basis for developing more effective targeted drugs in the future.

Enhanced Electrocatalytic Oxidation of Formate via Introducing Surface Reactive Oxygen Species to a CeO2 Substrate.

Direct formate fuel cells (DFFCs) as promising energy technologies have been applied for portable and wearable devices. However, for the formate oxidation reaction (FOR), the deficiency of catalysts has prevented DFFCs from practical applications. Herein, we prepared a Pd-loaded CeO2 catalyst through a simple steam treatment at 400 °C to enhance the catalytic FOR performance. In comparison with the counterpart of Pd/CeO2 without stream treatment, the as-prepared Pd/CeO2-ST catalyst has a lower onset potential of 381 mV and a lower peak potential of 0.64 V with a higher peak current of 10.62 mA cm-2. The experimental results show that the enhanced FOR properties of Pd/CeO2-ST are ascribed to the introduction of surface reactive oxygen species to the CeO2 substrate, which substantially promotes the desorption of adsorbed hydrogen (H*) intermediates. Density functional theory (DFT) calculations reveal that on the surface of CeO2, the abundant oxygen vacancies boost the OH* adsorption ability and accelerate the kinetics of the potential-limiting step. This work not only proposes a new strategy for enhancing the activity of FOR catalysts but also highlights the understanding of the FOR mechanism in alkaline media for DFFC applications.

Effects of titanium surface roughness on the mediation of osteogenesis via modulating the immune response of macrophages.

Osteoblastic lineage cells are commonly used to evaluate the in vitro osteogenic ability of bone biomaterials. However, contradictory results obtained from in vivo and in vitro studies are not uncommon. With the increasing understanding of osteoimmunology, the immune response has been recognized as playing an important role in bone regeneration. In this study, we examined the effect of submicron-scaled titanium surface roughness (ranging from approximately 100 to 400 nm) on the response of osteoblasts and macrophages. The results showed that osteoblast differentiation enhanced with increased surface roughness of titanium substrates. The cytoskeleton of macrophages altered with the variation in titanium surface roughness. The production of cytokines (TNF-α, IL-6, IL-4 and IL-10) could be regulated by titanium surface roughness. Moreover, macrophages cultured on titanium surfaces exhibited a tendency to polarize to M1 phenotype with the increase of surface roughness. Material/macrophage conditioned medium tended to promote osteoblast differentiation with the increase of surface roughness. The results indicate that increasing surface roughness in the submicron range is beneficial for osteogenesis via modulating the immune response of macrophages. Modifying biomaterial surfaces based on their immunomodulatory effects is considered as a novel strategy for the improvement of their biological performance.