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"Sun, Zhe"
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Immunosuppressive tumor microenvironment and immunotherapy of hepatocellular carcinoma: current status and prospectives
Hepatocellular carcinoma (HCC) is a major health concern worldwide, with limited therapeutic options and poor prognosis. In recent years, immunotherapies such as immune checkpoint inhibitors (ICIs) have made great progress in the systemic treatment of HCC. The combination treatments based on ICIs have been the major trend in this area. Recently, dual immune checkpoint blockade with durvalumab plus tremelimumab has also emerged as an effective treatment for advanced HCC. However, the majority of HCC patients obtain limited benefits. Understanding the immunological rationale and exploring novel ways to improve the efficacy of immunotherapy has drawn much attention. In this review, we summarize the latest progress in this area, the ongoing clinical trials of immune-based combination therapies, as well as novel immunotherapy strategies such as chimeric antigen receptor T cells, personalized neoantigen vaccines, oncolytic viruses, and bispecific antibodies.
Journal Article
Progress on the application of supercomputer brain simulation technology
High performance computing (HPC) is transforming the field of large⁃scale brain simulation by enabling the integration of multi⁃scale computational modeling with massive neuroscience data. With advanced HPC resources, researchers can simulate neural activities from ion⁃channel dynamics to whole⁃brain network interactions, thereby illuminating the mechanisms underlying cognition, neural disorders, and emerging neuromorphic intelligence. This review examines the theoretical principles and technical foundations of supercomputer brain simulation, including distributed parallel algorithms, graphics processing unit (GPU)⁃based acceleration, and multimodal data management. It also surveys prominent simulation platforms such as NEST, NEURON, and The Virtual Brain (TVB), highlighting their strengths in modeling spiking neuronal network (SNN), multicompartmental neurons, and large⁃scale functional connectivity, respectively. Furthermore, we discuss the practical applications of these simulations in elucidating disease mechanisms in Alzheimer's disease (AD), Parkinson's disease (PD), autism spectrum disorder (ASD), schizophrenia, and epilepsy. Special emphasis is placed on how supercomputer brain simulation assists in virtual drug screening, optimizing deep brain stimulation parameters, and supporting digital twin approaches for personalized medicine. Finally, we address the critical challenges and future directions in this rapidly evolving domain, including the trade⁃off between computational cost and biological realism, data integration and validation, and the necessity for interdisciplinary collaboration. The advent of exascale supercomputers and the convergence of neuroinformatics and machine learning (ML) are poised to propel brain simulation research toward unprecedented clinical and scientific breakthroughs.
Journal Article
Regulating electron configuration of single Cu sites via unsaturated N,O-coordination for selective oxidation of benzene
Developing highly efficient catalyst for selective oxidation of benzene to phenol (SOBP) with low H
2
O
2
consumption is highly desirable for practical application, but challenge remains. Herein, we report unique single-atom Cu
1
-N
1
O
2
coordination-structure on N/C material (Cu-N
1
O
2
SA/CN), prepared by water molecule-mediated pre-assembly-pyrolysis method, can efficiently boost SOBP reaction at a 2:1 of low H
2
O
2
/benzene molar ratio, showing 83.7% of high benzene conversion with 98.1% of phenol selectivity. The Cu
1
-N
1
O
2
sites can provide a preponderant reaction pathway for SOBP reaction with less steps and lower energy barrier. As a result, it shows an unexpectedly higher turnover frequency (435 h
−1
) than that of Cu
1
-N
2
(190 h
−1
), Cu
1
-N
3
(90 h
−1
) and Cu nanoparticle (58 h
−1
) catalysts, respectively. This work provides a facile and efficient method for regulating the electron configuration of single-atom catalyst and generates a highly active and selective non-precious metal catalyst for industrial production of phenol through selective oxidation of benzene.
Developing highly efficient catalysts for selective oxidation of benzene to phenol with low H
2
O
2
consumption remains challenging. Here the authors report a highly active and selective non-noble metal catalyst for selective oxidation of benzene to phenol with low H2O2 addition via regulating the electron configuration of single-atom Cu catalyst.
Journal Article
Valley-polarized exciton currents in a van der Waals heterostructure
Valleytronics is an appealing alternative to conventional charge-based electronics that aims at encoding data in the valley degree of freedom, that is, the information as to which extreme of the conduction or valence band carriers are occupying. The ability to create and control valley currents in solid-state devices could therefore enable new paradigms for information processing. Transition metal dichalcogenides (TMDCs) are a promising platform for valleytronics due to the presence of two inequivalent valleys with spin–valley locking1 and a direct bandgap2,3, which allows optical initialization and readout of the valley state4,5. Recent progress on the control of interlayer excitons in these materials6–8 could offer an effective way to realize optoelectronic devices based on the valley degree of freedom. Here, we show the generation and transport over mesoscopic distances of valley-polarized excitons in a device based on a type-II TMDC heterostructure. Engineering of the interlayer coupling results in enhanced diffusion of valley-polarized excitons, which can be controlled and switched electrically. Furthermore, using electrostatic traps, we can increase the exciton concentration by an order of magnitude, reaching densities in the order of 1012 cm−2, opening the route to achieving a coherent quantum state of valley-polarized excitons via Bose–Einstein condensation.
Journal Article
Assembly and comparative analysis of the complete mitochondrial genome of Bupleurum chinense DC
Background
Bupleurum chinense
(
B. chinense)
is a plant that is widely distributed globally and has strong pharmacological effects. Though the chloroplast(cp) genome of
B. chinense
has been studied, no reports regarding the mitochondrial(mt) genome of
B. chinense
have been published yet.
Results
The mt genome of
B.chinense
was assembled and functionally annotated. The circular mt genome of
B. chinense
was 435,023 bp in length, and 78 genes, including 39 protein-coding genes, 35 tRNA genes, and 4 rRNA genes, were annotated. Repeat sequences were analyzed and sites at which RNA editing would occur were predicted. Gene migration was observed to occur between the mt and cp genomes of
B. chinense
via the detection of homologous gene fragments. In addition, the sizes of plant mt genomes and their GC content were analyzed and compared. The sizes of mt genomes of plants varied greatly, but their GC content was conserved to a greater extent during evolution. Ka/Ks analysis was based on code substitutions, and the results showed that most of the coding genes were negatively selected. This indicates that mt genes were conserved during evolution.
Conclusion
In this study, we assembled and annotated the mt genome of the medicinal plant
B. chinense
. Our findings provide extensive information regarding the mt genome of
B. chinense
, and help lay the foundation for future studies on the genetic variations, phylogeny, and breeding of
B. chinense
via an analysis of the mt genome.
Journal Article
Understanding electro-mechanical-thermal coupling in solid-state lithium metal batteries via phase-field modeling
Solid-state batteries, based on a solid electrolyte and an energy-dense metal anode, are considered promising next-generation energy-storage devices. Phase-filed method, as a mesoscale method, covers a much wider range of length scales, from the atomic to the continuum scale, compared with those of first principles and finite-element methods. However, phase-field modeling strategies of conventional lithium-ion batteries cannot be directly applied to solid-state systems with strong coupling between different physical fields. A timely review on phase-field modeling of solid-state batteries that discusses the principles, strengths, and limitations of such a simulation method is therefore critical. This review will provide a brief introduction for electrochemists who are new to the phase-field method as well as simulation scientists who are new to solid-state batteries. We hope that this review will motivate further studies in multiphysics coupling effects, e.g., chemo-mechanical, and chemo-thermal, which is critical to fully unlocking the potential of solid-state batteries.
Graphical abstract
Journal Article
A Novel Reinforcement Learning Collision Avoidance Algorithm for USVs Based on Maneuvering Characteristics and COLREGs
Autonomous collision avoidance technology provides an intelligent method for unmanned surface vehicles’ (USVs) safe and efficient navigation. In this paper, the USV collision avoidance problem under the constraint of the international regulations for preventing collisions at sea (COLREGs) was studied. Here, a reinforcement learning collision avoidance (RLCA) algorithm is proposed that complies with USV maneuverability. Notably, the reinforcement learning agent does not require any prior knowledge about USV collision avoidance from humans to learn collision avoidance motions well. The double-DQN method was used to reduce the overestimation of the action-value function. A dueling network architecture was adopted to clearly distinguish the difference between a great state and an excellent action. Aiming at the problem of agent exploration, a method based on the characteristics of USV collision avoidance, the category-based exploration method, can improve the exploration ability of the USV. Because a large number of turning behaviors in the early steps may affect the training, a method to discard some of the transitions was designed, which can improve the effectiveness of the algorithm. A finite Markov decision process (MDP) that conforms to the USVs’ maneuverability and COLREGs was used for the agent training. The RLCA algorithm was tested in a marine simulation environment in many different USV encounters, which showed a higher average reward. The RLCA algorithm bridged the divide between USV navigation status information and collision avoidance behavior, resulting in successfully planning a safe and economical path to the terminal.
Journal Article
Lorentz-violating type-II Dirac fermions in transition metal dichalcogenide PtTe2
Topological semimetals have recently attracted extensive research interests as host materials to condensed matter physics counterparts of Dirac and Weyl fermions originally proposed in high energy physics. Although Lorentz invariance is required in high energy physics, it is not necessarily obeyed in condensed matter physics, and thus Lorentz-violating type-II Weyl/Dirac fermions could be realized in topological semimetals. The recent realization of type-II Weyl fermions raises the question whether their spin-degenerate counterpart—type-II Dirac fermions—can be experimentally realized too. Here, we report the experimental evidence of type-II Dirac fermions in bulk stoichiometric PtTe
2
single crystal. Angle-resolved photoemission spectroscopy measurements and first-principles calculations reveal a pair of strongly tilted Dirac cones along the Γ-A direction, confirming PtTe
2
as a type-II Dirac semimetal. Our results provide opportunities for investigating novel quantum phenomena (e.g., anisotropic magneto-transport) and topological phase transition.
Whether the spin-degenerate counterpart of Lorentz-violating Weyl fermions, the Dirac fermions, can be realized remains as an open question. Here, Yan et al. report experimental evidence of such type-II Dirac fermions in bulk PtTe
2
single crystal with a pair of strongly tilted Dirac cones.
Journal Article
Electrostatic self-assembly cellulose nanofibers/MXene/nickel chains for highly stable and efficient seawater evaporation and purification
Seawater evaporation and purification powered by solar energy are considered as a promising approach to alleviate the global freshwater crisis, and the development of photothermal materials with high efficiency is imminent. In this study, cellulose nanofiber (CNF)/MXene/Ni chain (CMN) aerogels were successfully synthesized by electrostatic force and hydrogen bond interaction force. CMN
10
achieved a favorable evaporation rate as high as 1.85 kg m
−2
h
−1
in pure water, and the corresponding evaporation efficiency could be up to 96.04%. Even if it is applied to seawater with multiple interference factors, its evaporation rate can still be 1.81 kg m
−2
h
−1
. The superior seawater evaporation activity origins from the promoted separation of photoexcited charges and photothermal conversion by the synergy of Ni chain and MXene, as well as the water transport channel supported by the 3D structure frame of CNF. Most importantly, CMN aerogel can maintain water vapor evaporation rates above 1.73 kg m
−2
h
−1
under extreme conditions such as acidic (pH 2) and alkaline (pH 12) conditions. In addition, various major ions, heavy metals and organic pollutants in seawater can be rejected by CMN
10
during desalination, and the rejection rates can reach more than 99.69%, ensuring the purity of water resources after treatment. This work shows the great potential of CMN aerogel as a high-efficiency solar evaporator and low-cost photothermal conversion material.
Graphical abstract
Cellulose nanofiber (CNF)/MXene/Ni chain (CMN) aerogels demonstrated high evaporation of water from sea water.
Journal Article