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"Cheng, Yi"
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Predictive biomarkers of colon cancer immunotherapy: Present and future
Immunotherapy has revolutionized colon cancer treatment. Immune checkpoint inhibitors (ICIs) have shown clinical benefits for colon cancer patients, especially those with high microsatellite instability (MSI-H). In 2020, the US Food and Drug Administration (FDA)-approved ICI pembrolizumab as the first-line treatment for metastatic MSI-H colon cancer patients. Additionally, neoadjuvant immunotherapy has presented efficacy in treating early-stage colon cancer patients. Although MSI has been thought of as an effective predictive biomarker for colon cancer immunotherapy, only a small proportion of colon cancer patients were MSI-H, and certain colon cancer patients with MSI-H presented intrinsic or acquired resistance to immunotherapy. Thus, further search for predictive biomarkers to stratify patients is meaningful in colon cancer immunotherapy. Except for MSI, other biomarkers, such as PD-L1 expression level, tumor mutation burden (TMB), tumor-infiltrating lymphocytes (TILs), certain gut microbiota, ctDNA, and circulating immune cells were also proposed to be correlated with patient survival and ICI efficacy in some colon cancer clinical studies. Moreover, developing new diagnostic techniques helps identify accurate predictive biomarkers for colon cancer immunotherapy. In this review, we outline the reported predictive biomarkers in colon cancer immunotherapy and further discuss the prospects of technological changes for biomarker development in colon cancer immunotherapy.
Journal Article
Grain boundary motions of low temperature and low pressure copper to copper direct bonding by electroplating ultra-fine-grain (UFG) Cu
Cu–Cu direct bonding using electroplated ultrafine-grain Cu (107.24 nm) was studied in air at 110–150 °C. Unstable grain boundaries enabled ultrafast grain growth across the bonding interface, analyzed via coincidence site lattice (CSL) boundaries using EBSD. Above 125 °C, the Σ3 boundary length exceeded 40%, while below 120 °C it rapidly declined, transforming into Σ27a, indicating a critical transition dominated by the {115} plane. A temperature–time-dependent grain growth model was developed, incorporating CSL effects. Simulations showed grain evolution and timing of CSL boundary formation, with transition times from 316 to 190 s as temperature increased.
Journal Article
Neuro-inspired optical sensor array for high-accuracy static image recognition and dynamic trace extraction
Neuro-inspired vision systems hold great promise to address the growing demands of mass data processing for edge computing, a distributed framework that brings computation and data storage closer to the sources of data. In addition to the capability of static image sensing and processing, the hardware implementation of a neuro-inspired vision system also requires the fulfilment of detecting and recognizing moving targets. Here, we demonstrated a neuro-inspired optical sensor based on two-dimensional NbS
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hybrid films, which featured remarkable photo-induced conductance plasticity and low electrical energy consumption. A neuro-inspired optical sensor array with 10 × 10 NbS
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phototransistors enabled highly integrated functions of sensing, memory, and contrast enhancement capabilities for static images, which benefits convolutional neural network (CNN) with a high image recognition accuracy. More importantly, in-sensor trajectory registration of moving light spots was experimentally implemented such that the post-processing could yield a high restoration accuracy. Our neuro-inspired optical sensor array could provide a fascinating platform for the implementation of high-performance artificial vision systems.
Neuro-inspired vision systems hold great promise to address the growing demands of mass data processing for edge computing. Here the authors, develop a neuro-inspired optical sensor based on NbS
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films that can operate with monolithically integrated functions of static image enhancement and dynamic trajectory registration.
Journal Article
Leaders in Social Networks, the Delicious Case
Finding pertinent information is not limited to search engines. Online communities can amplify the influence of a small number of power users for the benefit of all other users. Users' information foraging in depth and breadth can be greatly enhanced by choosing suitable leaders. For instance in delicious.com, users subscribe to leaders' collection which lead to a deeper and wider reach not achievable with search engines. To consolidate such collective search, it is essential to utilize the leadership topology and identify influential users. Google's PageRank, as a successful search algorithm in the World Wide Web, turns out to be less effective in networks of people. We thus devise an adaptive and parameter-free algorithm, the LeaderRank, to quantify user influence. We show that LeaderRank outperforms PageRank in terms of ranking effectiveness, as well as robustness against manipulations and noisy data. These results suggest that leaders who are aware of their clout may reinforce the development of social networks, and thus the power of collective search.
Journal Article
Observation of Fermi arc surface states in a topological metal
The topology of the electronic structure of a crystal is manifested in its surface states. Recently, a distinct topological state has been proposed in metals or semimetals whose spin-orbit band structure features three-dimensional Dirac quasiparticles. We used angle-resolved photoemission spectroscopy to experimentally observe a pair of spin-polarized Fermi arc surface states on the surface of the Dirac semimetal Na3Bi at its native chemical potential. Our systematic results collectively identify a topological phase in a gapless material. The observed Fermi arc surface states open research frontiers in fundamental physics and possibly in spintronics.
Journal Article
Light-induced reversal of ion segregation in mixed-halide perovskites
Bandgap instability due to light-induced phase segregation in mixed-halide perovskites presents a major challenge for their future commercial use. Here we demonstrate that photoinduced halide-ion segregation can be completely reversed at sufficiently high illumination intensities, enabling control of the optical bandgap of a mixed-halide perovskite single crystal by optimizing the input photogenerated carrier density. We develop a polaron-based two-dimensional lattice model that rationalizes the experimentally observed phenomena by assuming that the driving force for photoinduced halide segregation is dependent on carrier-induced strain gradients that vanish at high carrier densities. Using illumination sources with different excitation intensities, we demonstrate write–read–erase experiments showing that it is possible to store information in the form of latent images over several minutes. The ability to control the local halide-ion composition with light intensity opens opportunities for the use of mixed-halide perovskites in concentrator and tandem solar cells, as well as in high-power light-emissive devices and optical memory applications.
Depending on its intensity, light irradiation is shown to induce not only segregation but also remixing of halide ions in mixed-halide perovskites, enabling in situ and localized control of chemical composition and optical bandgap in these materials.
Journal Article