Presenting dual-functional peptides on implant surface to direct in vitro osteogenesis and in vivo osteointegration.

The complex biological process of osseointegration and the bio-inertness of bone implants are the major reasons for the high failure rate of long-term implants, and have also promoted the rapid development of multifunctional implant coatings in recent years. Herein, through the special design of peptides, we use layer-by-layer assembly technology to simultaneously display two peptides with different biological functions on the implant surface to address this issue. A variety of surface characterization techniques (ellipsometry, atomic force microscopy, photoelectron spectroscopy, dissipation-quartz crystal microbalance) were used to study in detail the preparation process of the dual peptide functional coating and the physical and chemical properties, such as the composition, mechanical modulus, stability, and roughness of the coating. Compared with single peptide functional coatings, dual-peptide functionalized coatings had much better performances on antioxidant, cellular adhesion in early stage, proliferation and osteogenic differentiation in long term, as well as in vivo osteogenesis and osseointegration capabilities. These findings will promote the development of multifunctional designs in bone implant coatings, as a coping strategy for the complexity of biological process during osteointegration.

Optimal decision-making in relieving global high temperature-related disease burden by data-driven simulation.

The rapid acceleration of global warming has led to an increased burden of high temperature-related diseases (HTDs), highlighting the need for advanced evidence-based management strategies. We have developed a conceptual framework aimed at alleviating the global burden of HTDs, grounded in the One Health concept. This framework refines the impact pathway and establishes systematic data-driven models to inform the adoption of evidence-based decision-making, tailored to distinct contexts. We collected extensive national-level data from authoritative public databases for the years 2010-2019. The burdens of five categories of disease causes - cardiovascular diseases, infectious respiratory diseases, injuries, metabolic diseases, and non-infectious respiratory diseases - were designated as intermediate outcome variables. The cumulative burden of these five categories, referred to as the total HTD burden, was the final outcome variable. We evaluated the predictive performance of eight models and subsequently introduced twelve intervention measures, allowing us to explore optimal decision-making strategies and assess their corresponding contributions. Our model selection results demonstrated the superior performance of the Graph Neural Network (GNN) model across various metrics. Utilizing simulations driven by the GNN model, we identified a set of optimal intervention strategies for reducing disease burden, specifically tailored to the seven major regions: East Asia and Pacific, Europe and Central Asia, Latin America and the Caribbean, Middle East and North Africa, North America, South Asia, and Sub-Saharan Africa. Sectoral mitigation and adaptation measures, acting upon our categories of Infrastructure & Community, Ecosystem Resilience, and Health System Capacity, exhibited particularly strong performance for various regions and diseases. Seven out of twelve interventions were included in the optimal intervention package for each region, including raising low-carbon energy use, increasing energy intensity, improving livestock feed, expanding basic health care delivery coverage, enhancing health financing, addressing air pollution, and improving road infrastructure. The outcome of this study is a global decision-making tool, offering a systematic methodology for policymakers to develop targeted intervention strategies to address the increasingly severe challenge of HTDs in the context of global warming.

A "solo-solvent de novo liquid-phase" method for synthesizing sulfide solid electrolyte Li6PS5Cl.

We report a "solo-solvent de novo liquid-phase" method of synthesizing a highly-favored sulfide electrolyte (Li6PS5Cl) for developing all-solid-state lithium batteries. The key chemistry for such a successful method is that tetrahydropyrrole enables in situ synthesis of the critical precursor Li2S from cheap and air-stable precursors of lithium chloride and sodium sulfide.

Logical Magic State Preparation with Fidelity beyond the Distillation Threshold on a Superconducting Quantum Processor.

Fault-tolerant quantum computing based on surface code has emerged as an attractive candidate for practical large-scale quantum computers to achieve robust noise resistance. To achieve universality, magic states preparation is a commonly approach for introducing non-Clifford gates. Here, we present a hardware-efficient and scalable protocol for arbitrary logical state preparation for the rotated surface code, and further experimentally implement it on the Zuchongzhi 2.1 superconducting quantum processor. An average of 0.8983±0.0002 logical fidelity at different logical states with distance three is achieved, taking into account both state preparation and measurement errors. In particular, the logical magic states |A^{π/4}⟩_{L}, |H⟩_{L}, and |T⟩_{L} are prepared nondestructively with logical fidelities of 0.8771±0.0009, 0.9090±0.0009, and 0.8890±0.0010, respectively, which are higher than the state distillation protocol threshold, 0.859 (for H-type magic state) and 0.827 (for T-type magic state). Our work provides a viable and efficient avenue for generating high-fidelity raw logical magic states, which is essential for realizing non-Clifford logical gates in the surface code.

CT features combined with RECIST 1.1 criteria improve progression assessments of sunitinib-treated gastrointestinal stromal tumors.

OBJECTIVES: To explore the auxiliary value of combining CT features with existing response evaluation criteria in the prediction of progressive disease (PD) in gastrointestinal stromal tumors (GIST) patients treated with sunitinib. MATERIAL AND METHODS: Eighty-one patients with GISTs who received sunitinib were included in this retrospective multicenter study and divided into training and external validation cohorts. Progression at six months was determined as a reference standard. The predictive performance of the RECIST 1.1 and Choi criteria was compared. CT features at baseline and the first follow-up were analyzed. Logistic regression analyses were used to determine the most significant predictors and develop modified criteria. RESULTS: A total of 216 lesions showed a good response and 107 showed a poor response in 81 patients. The RECIST 1.1 criteria performed better than the Choi criteria in predicting progression (AUC, 0.75 vs. 0.69, p = 0.04). The expanded/intensified high-enhancement area, blurred tumor-tissue interface, and progressive enlarged vessels feeding or draining the mass (EVFDM) differed significantly between lesions with good and poor responses in the training cohort (p = 0.001, 0.003, and 0.000, respectively). Multivariate analysis revealed that the expanded/intensified high-enhancement area (p = 0.001), progressive EVFDM (p = 0.000), and RECIST PD (p = 0.000) were independent predictive factors. Modified RECIST (mRECIST) criteria were developed and showed significantly higher AUCs in the training and external validation cohorts than the RECIST 1.1 criteria (training: 0.81 vs. 0.73, p = 0.002; validation: 0.82 vs. 0.77, p = 0.04). CONCLUSION: The mRECIST criteria, combining CT features with the RECIST 1.1 criteria, demonstrated superior performance in the prediction of early progression in GIST patients receiving sunitinib. CLINICAL RELEVANCE STATEMENT: The mRECIST criteria, which combine CT features with the RECIST 1.1 criteria, may facilitate the early detection of progressive disease in GIST patients treated with sunitinib, thereby potentially guiding the timely switch to late-line medications or combination with surgical excision. KEY POINTS: • The RECIST 1.1 criteria outperformed the Choi criteria in identifying progression of GISTs in patients treated with sunitinib. • GISTs displayed different morphologic features on CT depending on how they responded to sunitinib. • Combining CT morphologic features with the RECIST 1.1 criteria allowed for the prompt and accurate identification of progressing GIST lesions.

Generation of genuine entanglement up to 51 superconducting qubits.

Scalable generation of genuine multipartite entanglement with an increasing number of qubits is important for both fundamental interest and practical use in quantum-information technologies1,2. On the one hand, multipartite entanglement shows a strong contradiction between the prediction of quantum mechanics and local realization and can be used for the study of quantum-to-classical transition3,4. On the other hand, realizing large-scale entanglement is a benchmark for the quality and controllability of the quantum system and is essential for realizing universal quantum computing5-8. However, scalable generation of genuine multipartite entanglement on a state-of-the-art quantum device can be challenging, requiring accurate quantum gates and efficient verification protocols. Here we show a scalable approach for preparing and verifying intermediate-scale genuine entanglement on a 66-qubit superconducting quantum processor. We used high-fidelity parallel quantum gates and optimized the fidelitites of parallel single- and two-qubit gates to be 99.91% and 99.05%, respectively. With efficient randomized fidelity estimation9, we realized 51-qubit one-dimensional and 30-qubit two-dimensional cluster states and achieved fidelities of 0.637 ± 0.030 and 0.671 ± 0.006, respectively. On the basis of high-fidelity cluster states, we further show a proof-of-principle realization of measurement-based variational quantum eigensolver10 for perturbed planar codes. Our work provides a feasible approach for preparing and verifying entanglement with a few hundred qubits, enabling medium-scale quantum computing with superconducting quantum systems.

Efficacy and safety of ripretinib in Chinese patients with advanced gastrointestinal stromal tumors: a real-world, multicenter, observational study.

Introduction: Mutations in KIT proto-oncogene, receptor tyrosine kinase (KIT) and platelet-derived growth factor receptor-α (PDGFRA) render the available tyrosine kinase inhibitors (TKI) ineffective in treating advanced gastrointestinal stromal tumors (GIST). Ripretinib, a broad-spectrum switch-control kinase inhibitor, has shown increased efficacy and manageable safety, but real-world evidence remains scarce. This study evaluates the efficacy and safety of ripretinib among Chinese patients in a real-world setting. Methods: Advanced GIST patients (N=23) receiving ripretinib following progression on previous lines of TKI treatment were enrolled to determine the efficacy [progression-free survival (PFS) and overall survival (OS)]. Safety was assessed by the incidence and severity of adverse events (AEs). All statistical analyses were performed using SPSS version 20.0 and a p-value of <0.05 was considered significant. Results: The median PFS (mPFS) of efficacy analysis set (EAS) (N=21) was 7.1 months. mPFS of patients receiving ripretinib following ≤2 lines of previous TKI treatment and ≥3 prior lines of therapy were 7.1 and 9.2 months, respectively. The median OS (mOS) was 12.0 months and shorter interval between the end of the latest TKI and ripretinib therapy was correlated with longer median PFS and OS (p=0.054 and p=0.046), respectively. Alopecia and asthenia were the most common AEs observed. Conclusion: Compared to previous lines of TKI in advanced GIST patients, ripretinib showed superior efficacy with clinically manageable AEs. Real-world results are comparable to that of phase III INVICTUS study and its Chinese bridging study. Hence, ripretinib can be used for the clinical management of advanced GIST patients.

Quantum neuronal sensing of quantum many-body states on a 61-qubit programmable superconducting processor.

Classifying many-body quantum states with distinct properties and phases of matter is one of the most fundamental tasks in quantum many-body physics. However, due to the exponential complexity that emerges from the enormous numbers of interacting particles, classifying large-scale quantum states has been extremely challenging for classical approaches. Here, we propose a new approach called quantum neuronal sensing. Utilizing a 61-qubit superconducting quantum processor, we show that our scheme can efficiently classify two different types of many-body phenomena: namely the ergodic and localized phases of matter. Our quantum neuronal sensing process allows us to extract the necessary information coming from the statistical characteristics of the eigenspectrum to distinguish these phases of matter by measuring only one qubit and offers better phase resolution than conventional methods, such as measuring the imbalance. Our work demonstrates the feasibility and scalability of quantum neuronal sensing for near-term quantum processors and opens new avenues for exploring quantum many-body phenomena in larger-scale systems.

Quantum computational advantage via 60-qubit 24-cycle random circuit sampling.

To ensure a long-term quantum computational advantage, the quantum hardware should be upgraded to withstand the competition of continuously improved classical algorithms and hardwares. Here, we demonstrate a superconducting quantum computing systems Zuchongzhi 2.1, which has 66 qubits in a two-dimensional array in a tunable coupler architecture. The readout fidelity of Zuchongzhi 2.1 is considerably improved to an average of 97.74%. The more powerful quantum processor enables us to achieve larger-scale random quantum circuit sampling, with a system scale of up to 60 qubits and 24 cycles, and fidelity of FXEB=(3.66±0.345)×10-4. The achieved sampling task is about 6 orders of magnitude more difficult than that of Sycamore [Nature 574, 505 (2019)] in the classic simulation, and 3 orders of magnitude more difficult than the sampling task on Zuchongzhi 2.0 [arXiv:2106.14734 (2021)]. The time consumption of classically simulating random circuit sampling experiment using state-of-the-art classical algorithm and supercomputer is extended to tens of thousands of years (about 4.8×104 years), while Zuchongzhi 2.1 only takes about 4.2 h, thereby significantly enhancing the quantum computational advantage.

Corrigendum: Molecular Portrait of GIST Associated With Clinicopathological Features: A Retrospective Study With Molecular Analysis by a Custom 9-Gene Targeted Next-Generation Sequencing Panel.

[This corrects the article DOI: 10.3389/fgene.2022.864499.].

Realization of an Error-Correcting Surface Code with Superconducting Qubits.

Quantum error correction is a critical technique for transitioning from noisy intermediate-scale quantum devices to fully fledged quantum computers. The surface code, which has a high threshold error rate, is the leading quantum error correction code for two-dimensional grid architecture. So far, the repeated error correction capability of the surface code has not been realized experimentally. Here, we experimentally implement an error-correcting surface code, the distance-three surface code which consists of 17 qubits, on the Zuchongzhi 2.1 superconducting quantum processor. By executing several consecutive error correction cycles, the logical error can be significantly reduced after applying corrections, achieving the repeated error correction of surface code for the first time. This experiment represents a fully functional instance of an error-correcting surface code, providing a key step on the path towards scalable fault-tolerant quantum computing.

Molecular Portrait of GISTs Associated With Clinicopathological Features: A Retrospective Study With Molecular Analysis by a Custom 9-Gene Targeted Next-Generation Sequencing Panel.

Objectives: The study aims to investigate genetic characterization of molecular targets and clinicopathological features with gastrointestinal stromal tumors based on targeted next-generation sequencing. Materials and Methods: We selected 106 patients with GISTs from Sir Run Run Shaw Hospital between July 2019 and March 2021. FFPE samples and paired blood samples were obtained from these patients who underwent excision of the tumor. A customized targeted-NGS panel of nine GIST-associated genes was designed to detect variants in the coding regions and the splicing sites of these genes. Results: In total, 106 patients with a GIST were included in the study which presented with various molecular driver alterations in this study. KIT mutations occurred most often in GISTs (94/106, 95.92%), followed by point mutations in PDGFRA. KIT or PDGFRA mutations were detected to be mutually exclusive in the GIST. A total of eight patients with wide-type KIT/PDGFRA were characterized as WT-GISTs, according to clinical diagnosis which included six quadruple-WT GISTs, 1 BRAF-mutant, and 1 NF1-mutant GIST. In KIT exon 11, the most common mutation type was the codon Mutation (in-frame deletion or indels), whereas the missense mutation was the dominant type in KIT exon 13 and KIT exon 17. All variations in KIT exon 11 observed in this study were concentrated at a certain position of codon 550 to codon 576. Mutation in KIT exon 9 was mostly located at codon 502-503. Two germline pathogenic mutations were detected: NF1-R681* and KRAS-T58I. NF1-L591P was a germline mutation to be identified for the first time and is not recorded in the database. The frequency of driving mutations differed between the primary anatomical site in the GIST (p = 0.0206). KIT exon 11 mutants had a lower proliferation index of Ki67 (68.66%,≤5%), while 50.00% of KIT exon 9 mutants had the Ki67 status greater than 10%. Conclusion: The occurrence and development of a GIST is driven by different molecular variations. Resistance to TKIs arises mainly with resistance mutations in KIT or PDGFRA when they are the primary drivers. Targeted NGS can simultaneously and efficiently detect nine GIST-related gene mutations and provide reference for clinicians' individualized diagnosis and treatment. Our results have important implications for clinical management.

Observation of Thermalization and Information Scrambling in a Superconducting Quantum Processor.

Understanding various phenomena in nonequilibrium dynamics of closed quantum many-body systems, such as quantum thermalization, information scrambling, and nonergodic dynamics, is crucial for modern physics. Using a ladder-type superconducting quantum processor, we perform analog quantum simulations of both the XX-ladder model and the one-dimensional XX model. By measuring the dynamics of local observables, entanglement entropy, and tripartite mutual information, we signal quantum thermalization and information scrambling in the XX ladder. In contrast, we show that the XX chain, as free fermions on a one-dimensional lattice, fails to thermalize to the Gibbs ensemble, and local information does not scramble in the integrable channel. Our experiments reveal ergodicity and scrambling in the controllable qubit ladder, and open the door to further investigations on the thermodynamics and chaos in quantum many-body systems.

Strong Quantum Computational Advantage Using a Superconducting Quantum Processor.

Scaling up to a large number of qubits with high-precision control is essential in the demonstrations of quantum computational advantage to exponentially outpace the classical hardware and algorithmic improvements. Here, we develop a two-dimensional programmable superconducting quantum processor, Zuchongzhi, which is composed of 66 functional qubits in a tunable coupling architecture. To characterize the performance of the whole system, we perform random quantum circuits sampling for benchmarking, up to a system size of 56 qubits and 20 cycles. The computational cost of the classical simulation of this task is estimated to be 2-3 orders of magnitude higher than the previous work on 53-qubit Sycamore processor [Nature 574, 505 (2019)NATUAS0028-083610.1038/s41586-019-1666-5. We estimate that the sampling task finished by Zuchongzhi in about 1.2 h will take the most powerful supercomputer at least 8 yr. Our work establishes an unambiguous quantum computational advantage that is infeasible for classical computation in a reasonable amount of time. The high-precision and programmable quantum computing platform opens a new door to explore novel many-body phenomena and implement complex quantum algorithms.

Observation of Strong and Weak Thermalization in a Superconducting Quantum Processor.

We experimentally study the ergodic dynamics of a 1D array of 12 superconducting qubits with a transverse field, and identify the regimes of strong and weak thermalization with different initial states. We observe convergence of the local observable to its thermal expectation value in the strong-thermalizaion regime. For weak thermalization, the dynamics of local observable exhibits an oscillation around the thermal value, which can only be attained by the time average. We also demonstrate that the entanglement entropy and concurrence can characterize the regimes of strong and weak thermalization. Our work provides an essential step toward a generic understanding of thermalization in quantum systems.

Quantum walks on a programmable two-dimensional 62-qubit superconducting processor.

Quantum walks are the quantum mechanical analog of classical random walks and an extremely powerful tool in quantum simulations, quantum search algorithms, and even for universal quantum computing. In our work, we have designed and fabricated an 8-by-8 two-dimensional square superconducting qubit array composed of 62 functional qubits. We used this device to demonstrate high-fidelity single- and two-particle quantum walks. Furthermore, with the high programmability of the quantum processor, we implemented a Mach-Zehnder interferometer where the quantum walker coherently traverses in two paths before interfering and exiting. By tuning the disorders on the evolution paths, we observed interference fringes with single and double walkers. Our work is a milestone in the field, bringing future larger-scale quantum applications closer to realization for noisy intermediate-scale quantum processors.

Leptomycin B inhibits the proliferation, migration, and invasion of cultured gastric carcinoma cells.

Chromosome region maintenance 1 (CRM1) plays a critical role in tumorigenesis and progression through modulating nuclear export of several proteins. However, the precise effects of CRM1 inhibitor on gastric carcinoma have not yet been illustrated. Here, we investigated the potential anti-cancer activities of leptomycin B, the most potent CRM1 antagonist, on cultured gastric carcinoma cells. Our findings demonstrate that CRM1 was highly expressed in four gastric carcinoma cell lines. Leptomycin B inhibited the viability of HGC-27 and AGS cells in a dose- and time-dependent pattern. Leptomycin B at the dose of 10 nM or 100 nM suppressed the migration and invasion of HGC-27 and AGS cells. Leptomycin B elevated the expressions of autophagy-related protein LC3-II and autophagy substrate p62. Moreover, leptomycin B enhanced the LC3-positive puncta formation in cells. Our data suggest that leptomycin B may exert an anti-cancer activity possibly through interfering autophagy function in gastric carcinoma cells.

Interplay between apoptosis and autophagy in colorectal cancer.

Autophagy and apoptosis are two pivotal mechanisms in mediating cell survival and death. Cross-talk of autophagy and apoptosis has been documented in the tumorigenesis and progression of cancer, while the interplay between the two pathways in colorectal cancer (CRC) has not yet been comprehensively summarized. In this study, we outlined the basis of apoptosis and autophagy machinery firstly, and then reviewed the recent evidence in cellular settings or animal studies regarding the interplay between them in CRC. In addition, several key factors that modulate the cross-talk between autophagy and apoptosis as well as its significance in clinical practice were discussed. Understanding of the interplay between the cell death mechanisms may benefit the translation of CRC treatment from basic research to clinical use.

The cytoplasmic nuclear shuttling of Beclin 1 in neurons with Alzheimer's disease-like injury.

The abnormal expression of the autophagy-related protein Beclin 1 has been implicated in Alzheimer's disease (AD) brains, whereas the precise involvement of Caspase-mediated Beclin 1 cleavage in AD neurons has not yet been fully clarified. In this study, we investigated the distribution of Beclin 1 fragments in neurons with AD-like injury. Our results demonstrated that Beclin 1 was expressed in neurons but not in astrocytes in both neuron-glia co-cultures and in cortical tissue slices. The full length and C-terminal fragments of human Beclin 1 was mainly expressed in cytoplasm, while the N-terminal fragment of Beclin 1 was predominantly localized in nucleus. Compared to amyloid-ß (Aß)42-1 treatment control, exposure of PC12 cells or cortical neurons to Aß1-42 resulted in cell injury, with the appearance of neuritic shortening, reduced nuclear diameter in PC12 cells, beading formation and fragmentation in cortical neurons. A partial nuclear translocation of Beclin 1 was detected in cells incubated with Aß1-42, which could be inhibited by the administration of pan-Caspase inhibitor or Caspase 3 specific inhibitor. Moreover, Beclin 1 mutation at 146/149 sites was resistant to Aß1-42-induced nuclear translocation. The nuclear translocation of Beclin 1 could also been detected in the brains of 12-month-old APPSwe/PS1dE9 transgenic mice. Our findings suggest that after Caspase 3-mediated Beclin 1 cleavage at 146/149 sites, the N-terminal fragments of Beclin 1 may partially translocate into nuclei in neurons subjected to AD-like injury.

PD-L1 and gastric cancer prognosis: A systematic review and meta-analysis.

The expression of Programmed cell Death Ligand 1 (PD-L1) is observed in many malignant tumors and is associated with poor prognosis including Gastric Cancer (GC). The relationship between PD-L1 expression and prognosis, however, is controversial in GC. This paper purports to use a meta-analysis to investigate the relationship between PD-L1 expression and prognosis in GC. For this study, the following databases were searched for articles published from June 2003 until February 2017: PubMed, EBSCO, Web of Science and Cochrane Library. The baseline information extracted were: authors, year of publication, country where the study was performed, study design, sample size, follow-up time, baseline characteristics of the study population, pathologic data, overall survival (OS). A total of 15 eligible studies covering 3291 patients were selected for a meta-analysis based on specified inclusion and exclusion criteria. The analysis showed that the expression level of PD-L1 was associated with the overall survival in GC (Hazard Ratio, HR = 1.46, 95%CI = 1.08-1.98, P = 0.01, random-effect). In addition to the above, subgroup analysis showed that GC patients with deeper tumor infiltration, positive lymph-node metastasis, positive venous invasion, Epstein-Barr virus infection positive (EBV+), Microsatellite Instability (MSI) are more likely to expression PD-L1. The results of this meta-analysis suggest that GC patients, specifically EBV+ and MSI, may be prime candidates for PD-1 directed therapy. These findings support anti-PD-L1/PD-1 antibodies as a kind of immunotherapy which is promising for GC.