Verifying Quantum Advantage Experiments with Multiple Amplitude Tensor Network Contraction.

The quantum supremacy experiment, such as Google Sycamore [F. Arute et al., Nature (London) 574, 505 (2019).NATUAS0028-083610.1038/s41586-019-1666-5], poses a great challenge for classical verification due to the exponentially increasing compute cost. Using a new-generation Sunway supercomputer within 8.5 d, we provide a direct verification by computing 3×10^{6} exact amplitudes for the experimentally generated bitstrings, obtaining a cross-entropy benchmarking fidelity of 0.191% (the estimated value is 0.224%). The leap of simulation capability is built on a multiple-amplitude tensor network contraction algorithm which systematically exploits the "classical advantage" (the inherent "store-and-compute" operation mode of von Neumann machines) of current supercomputers, and a fused tensor network contraction algorithm which drastically increases the compute efficiency on heterogeneous architectures. Our method has a far-reaching impact in solving quantum many-body problems, statistical problems, as well as combinatorial optimization problems.

Gaussian Boson Sampling with Pseudo-Photon-Number-Resolving Detectors and Quantum Computational Advantage.

We report new Gaussian boson sampling experiments with pseudo-photon-number-resolving detection, which register up to 255 photon-click events. We consider partial photon distinguishability and develop a more complete model for the characterization of the noisy Gaussian boson sampling. In the quantum computational advantage regime, we use Bayesian tests and correlation function analysis to validate the samples against all current classical spoofing mockups. Estimating with the best classical algorithms to date, generating a single ideal sample from the same distribution on the supercomputer Frontier would take ∼600 yr using exact methods, whereas our quantum computer, Jiǔzhang 3.0, takes only 1.27 µs to produce a sample. Generating the hardest sample from the experiment using an exact algorithm would take Frontier∼3.1×10^{10} yr.

Large-Scale Simulation of Full Three-Dimensional Flow and Combustion of an Aero-Turbofan Engine on Sunway TaihuLight Supercomputer.

Computational fluid dynamics- (CFD-) based component-level numerical simulation technology has been widely used in the design of aeroengines. However, due to the strong coupling effects between components, the numerical simulation of the whole engine considering the full three-dimensional flow and multi-component chemical reaction is still very difficult at present. Aimed at this problem, an efficient implicit solver, 'sprayDyMFoam' for an unstructured mesh, is developed in this paper based on the Sunway TaihuLight supercomputer. This sprayDyMFoam solver improves the PIMPLE algorithm in the solution of aerodynamic force and adjusts the existing droplet atomization model in the solution of the combustion process so as to meet the matching situation between components and the combustion chamber in the solution process. Meanwhile, the parallel communication mechanism of AMI boundary processing is optimized based on the hardware environment of the Sunway supercomputer. The sprayDyMFoam solver is used to simulate a typical double-rotor turbofan engine: the calculation capacity and efficiency meet the use requirements, and the obtained compressor performance can form a good match with the test. The research proposed in this paper has strong application value in high-confidence computing, complex phenomenon capturing, and time and cost reduction for aeroengine development.

Elastic Nanovaccine Enhances Dendritic Cell-Mediated Tumor Immunotherapy.

Nanovaccine-based immunotherapy (NBI) has the ability to initiate dendritic cell (DC)-mediated tumor-specific immune responses and maintain long-term antitumor immune memory. To date, the mechanism by which the mechanical properties of nanoparticles alter the functions of DCs in NBI remains largely unclear. Here, a soft mesoporous organosilica-based nanovaccine (SMONV) is prepared and the elasticity-dependent effect of the nanovaccine on the underlying DC-mediated immune responses is studied. It is found that the elasticity results in greater internalization of SMONV by DCs, followed by the induction of substantial cytosolic delivery of antigens via endosomal escape, leading to effective DC maturation and antigen cross-presentation. Impressively, elasticity enables SMONV to enhance lymphatic drainage of antigens in vivo, thus stimulating robust humoral and cellular immunity. The results from therapeutic tumor vaccination further reveal that subcutaneously administered SMONV effectively suppresses tumor growth in tumor-bearing mice by evoking antigen-specific CD8+ T-cell immune responses, mitigating regulatory T-cell-mediated immunosuppression, and increasing central memory and effector memory T-cell populations. Furthermore, combinatorial immunization with SMONV and anti-PD-L1 blocking antibodies results in an amplified therapeutic effect on tumor-bearing mice. These findings reveal the elastic effect of the nanovaccine on DC-mediated immune responses, and the prepared SMONV represents a facile and powerful strategy for antitumor immunotherapy.

Microbiota analysis of peri-implant mucositis in patients with periodontitis history.

OBJECTIVES: To investigate the bacterial diversity in peri-implant plaques and the effect of periodontitis history on the occurrence of peri-implant mucositis. MATERIALS AND METHODS: Three groups of subgingival plaques were collected from peri-implant sulci in the first molar area. The three groups included healthy implants in patients without periodontitis (NH implant), healthy implants in patients with periodontitis history (PH implant), and peri-implant mucositis implants in patients with periodontitis history (PM implant). Subgingival plaques in periodontal pockets of contralateral natural first molars were also collected. Bacterial DNA was extracted and the V4 region of the 16S rDNA sequence was amplified and sequenced on an Illumina HiSeq platform. The operational taxonomic units obtained from amplicon sequencing were used to analyze the prevalence and identity of bacteria based on public databases and advanced techniques. RESULTS: Analysis of similarities indicated a significant difference in bacterial structures between the NH implant and PM implant groups. Additionally, a significantly higher relative abundance of the genera Actinomyces and Streptococcus was found in the samples of the NH implant group. The genera Fusobacterium and Prevotella could be considered as potential biomarkers for peri-implant mucositis. Moreover, more gram-negative anaerobic bacteria (Porphyromonas and Prevotella) were detected in the samples from patients with periodontitis history. CONCLUSIONS: The increased accumulation of Fusobacterium and Prevotella is associated with a higher risk of peri-implant mucositis. In addition, patients with periodontal history may be more likely to develop peri-implant mucositis. CLINICAL RELEVANCE: The increase in periodontal pathogens and the decrease in health-associated bacteria in patients with periodontitis history may be more likely to develop peri-implant mucositis. These results provide a bacteriological basis for the prevention and treatment of peri-implant mucositis in patients with periodontitis history.

A particle-filter framework for robust cryo-EM 3D reconstruction.

Single-particle electron cryomicroscopy (cryo-EM) involves estimating a set of parameters for each particle image and reconstructing a 3D density map; robust algorithms with accurate parameter estimation are essential for high resolution and automation. We introduce a particle-filter algorithm for cryo-EM, which provides high-dimensional parameter estimation through a posterior probability density function (PDF) of the parameters given in the model and the experimental image. The framework uses a set of random support points to represent such a PDF and assigns weighting coefficients not only among the parameters of each particle but also among different particles. We implemented the algorithm in a new program named THUNDER, which features self-adaptive parameter adjustment, tolerance to bad particles, and per-particle defocus refinement. We tested the algorithm by using cryo-EM datasets for the cyclic-nucleotide-gated (CNG) channel, the proteasome, ß-galactosidase, and an influenza hemagglutinin (HA) trimer, and observed substantial improvement in resolution.

Phase-Programmable Gaussian Boson Sampling Using Stimulated Squeezed Light.

We report phase-programmable Gaussian boson sampling (GBS) which produces up to 113 photon detection events out of a 144-mode photonic circuit. A new high-brightness and scalable quantum light source is developed, exploring the idea of stimulated emission of squeezed photons, which has simultaneously near-unity purity and efficiency. This GBS is programmable by tuning the phase of the input squeezed states. The obtained samples are efficiently validated by inferring from computationally friendly subsystems, which rules out hypotheses including distinguishable photons and thermal states. We show that our GBS experiment passes a nonclassicality test based on inequality constraints, and we reveal nontrivial genuine high-order correlations in the GBS samples, which are evidence of robustness against possible classical simulation schemes. This photonic quantum computer, Jiuzhang 2.0, yields a Hilbert space dimension up to ∼10^{43}, and a sampling rate ∼10^{24} faster than using brute-force simulation on classical supercomputers.

Quantum-Teleportation-Inspired Algorithm for Sampling Large Random Quantum Circuits.

Quantum teleportation transfers and processes quantum information through quantum entanglement channels. It is one of the most versatile protocols in quantum information science and leads to many remarkable applications, particularly the one-way quantum computing. Here, we show, for the first time, that the concept of teleportation can also be used to facilitate an important classical computing task, sampling random quantum circuits, which is highly relevant to prove the near-term demonstration of quantum computational supremacy. In our method, the classical computation in the physical-qubit state space is converted to simulate teleportation in logical-qubit state space, resulting in a much smaller number of qubits involved in classical computing. We tested this new method on 1D and 2D lattices up to 1000 qubits. This Letter presents a new quantum-inspired classical computing technology and is helpful to design and optimize classically hard quantum sampling experiments.

Discovery of aminocyclohexene analogues as selective and orally bioavailable hNav1.7 inhibitors for analgesia.

hNav1.7 receives a lot of attention owing to its attractive mechanism of action in pain processing pathway. We have previously reported our design of a novel series of tetrahydropyridine analogues towards hNav1.7 selective inhibitors. Herein, we disclose further efforts to the optimization of hit compound (-)-6, which led to the identification of aminocyclohexene analogues (-)-9 and (-)-17 with good potency, high selectivity, and minimal CYP inhibition. Both compounds (-)-9 and (-)-17 demonstrated improved pharmacokinetic profiles in rats, and robust efficacy in rat formalin-induced nociception and spinal nerve ligation (SNL) models.

The discovery of tetrahydropyridine analogs as hNav1.7 selective inhibitors for analgesia.

hNav1.7 small molecular inhibitors have attracted lots of attention by its unique analgesic effect. Herein, we report the design and synthesis of a novel series of tetrahydropyridine analogs as hNav1.7 inhibitors for analgesia. Detail structural-activity relationship (SAR) studies were undertaken towards improving hNav1.7 activity, in vitro ADME, and in vivo PK profiles. These efforts resulted in the identification of compound (-)-15h, a highly potent and selective hNav1.7 inhibitor with good ADME and PK profiles.

Aperiodic dynamical quantum phase transition in multi-band Bloch Hamiltonian and its origin.

We investigate the dynamical quantum phase transition (DQPT) in the multi-band Bloch Hamiltonian of the one-dimensional periodic Kitaev model, focusing on quenches from a Bloch band. By analyzing the dynamical free energy and Pancharatnam geometric phase (PGP), we show that the critical times of DQPTs deviate from periodic spacing due to the multi-band effect, contrasting with results from two-band models. We propose a geometric interpretation to explain this non-uniform spacing. Additionally, we clarify the conditions needed for DQPT occurrence in the multi-band Bloch Hamiltonian, highlighting that a DQPT only arises when the quench from the Bloch states collapses the band gap at the critical point. Moreover, we establish that the dynamical topological order parameter, defined by the winding number of the PGP, is not quantized but still exhibits discontinuous jumps at DQPT critical times due to periodic modulation. Additionally, we extend our analysis to mixed-state DQPT and find its absence at non-zero temperatures.

A Joint Time-Frequency Domain Transformer for multivariate time series forecasting.

In order to enhance the performance of Transformer models for long-term multivariate forecasting while minimizing computational demands, this paper introduces the Joint Time-Frequency Domain Transformer (JTFT). JTFT combines time and frequency domain representations to make predictions. The frequency domain representation efficiently extracts multi-scale dependencies while maintaining sparsity by utilizing a small number of learnable frequencies. Simultaneously, the time domain (TD) representation is derived from a fixed number of the most recent data points, strengthening the modeling of local relationships and mitigating the effects of non-stationarity. Importantly, the length of the representation remains independent of the input sequence length, enabling JTFT to achieve linear computational complexity. Furthermore, a low-rank attention layer is proposed to efficiently capture cross-dimensional dependencies, thus preventing performance degradation resulting from the entanglement of temporal and channel-wise modeling. Experimental results on eight real-world datasets demonstrate that JTFT outperforms state-of-the-art baselines in predictive performance.

A photo-responsive self-healing hydrogel loaded with immunoadjuvants and MoS2 nanosheets for combating post-resection breast cancer recurrence.

Tumor recurrence after surgical resection remains a significant challenge in breast cancer treatment. Immune checkpoint blockade therapy, as a promising alternative therapy, faces limitations in combating tumor recurrence due to the low immune response rate. In this study, we developed an implantable photo-responsive self-healing hydrogel loaded with MoS2 nanosheets and the immunoadjuvant R837 (PVA-MoS2-R837, PMR hydrogel) for in situ generation of tumor-associated antigens at the post-surgical site of the primary tumor, enabling sustained and effective activation of the immune response. This PMR hydrogel exhibited potential for near-infrared (NIR) light response, tissue adhesion, self-healing, and sustained adjuvant release. When implanted at the site after tumor resection, NIR irradiation triggered a photothermal effect, resulting in the ablation of residual cancer cells. The in situ-generated tumor-associated antigens promoted dendritic cell (DC) maturation. In a mouse model, PMR hydrogel-mediated photothermal therapy combined with immune checkpoint blockade effectively inhibited the recurrence of resected tumors, providing new insights for combating post-resection breast cancer recurrence.

Endogenous/Exogenous Nanovaccines Synergistically Enhance Dendritic Cell-Mediated Tumor Immunotherapy.

Traditional dendritic cell (DC)-mediated immunotherapy is usually suppressed by weak immunogenicity in tumors and generally leads to unsatisfactory outcomes. Synergistic exogenous/endogenous immunogenic activation can provide an alternative strategy for evoking a robust immune response by promoting DC activation. Herein, Ti3 C2 MXene-based nanoplatforms (termed MXP) are prepared with high-efficiency near-infrared photothermal conversion and immunocompetent loading capacity to form endogenous/exogenous nanovaccines. Specifically, the immunogenic cell death of tumor cells induced by the photothermal effects of the MXP can generate endogenous danger signals and antigens release to boost vaccination for DC maturation and antigen cross-presentation. In addition, MXP can deliver model antigen ovalbumin (OVA) and agonists (CpG-ODN) as an exogenous nanovaccine (MXP@OC), which further enhances DC activation. Importantly, the synergistic strategy of photothermal therapy and DC-mediated immunotherapy by MXP significantly eradicates tumors and enhances adaptive immunity. Hence, the present work provides a two-pronged strategy for improving immunogenicity and killing tumor cells to achieve a favorable outcome in tumor patients.

An alternative surgical technique for varicoceles: a preliminary experience of the microsurgical spermatic (distal end)-inferior or superficial epigastric vein anastomosis in symptomatic varicoceles associated with perineal pain.

Many therapies are effective in treating varicoceles, including dilation of the pampiniform plexus in males. The most common method of treatment is varicocelectomy. We aimed to assess an alternative technique (microsurgical spermatic [distal end]-superficial or inferior epigastric vein anastomosis) that preserves the normal blood flow pattern for varicocele treatment. We retrospectively analyzed 27 men with varicocele between October 2019 and July 2020. All patients underwent microsurgical spermatic (distal end)-superficial or inferior epigastric vein anastomosis. The prognosis was reviewed retrospectively with an additional survey conducted 3 months after surgery. The mean ± standard deviation of the age was 26.1 ± 7.3 years in patients with microsurgical spermatic (distal end)-superficial or inferior epigastric vein anastomosis. The maximum diameter of the varicocele vein, perineal pain score, sperm density, and forward movement of sperm improved over 3 months after surgery. Microsurgical spermatic (distal end)-superficial or inferior epigastric vein anastomosis is a safe and efficient surgical treatment for varicoceles.

The immunodominant and neutralization linear epitopes for SARS-CoV-2.

Although vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are under development, the antigen epitopes on the virus and their immunogenicity are poorly understood. Here, we simulate the 3D structures and predict the B cell epitopes on the spike (S), envelope (E), membrane (M), and nucleocapsid (N) proteins of SARS-CoV-2 using structure-based approaches and validate epitope immunogenicity by immunizing mice. Almost all 33 predicted epitopes effectively induce antibody production, six of these are immunodominant epitopes in individuals, and 23 are conserved within SARS-CoV-2, SARS-CoV, and bat coronavirus RaTG13. We find that the immunodominant epitopes of individuals with domestic (China) SARS-CoV-2 are different from those of individuals with imported (Europe) SARS-CoV-2, which may be caused by mutations on the S (G614D) and N proteins. Importantly, we find several epitopes on the S protein that elicit neutralizing antibodies against D614 and G614 SARS-CoV-2, which can contribute to vaccine design against coronaviruses.

Icosahedral face-centered cubic Fe nanoparticles: facile synthesis and characterization with aberration-corrected TEM.

Iron nanoparticles are highly desirable for their potential applications in magnetic and catalytic industry. However, their shape-controlled fabrication is still an important challenge. Here we successfully synthesized icosahedral face-centered cubic (fcc) Fe nanoparticles with size of 5-13 nm by a specifically designed thermodynamic governed synthetic route, which is facile but highly efficient and reproducible. With the aberration-corrected transmission electron microscopy (TEM), the unique icosahedral structure's pseudo-2-fold, 3-fold, and pseudo-5-fold axes were directly observed for the first time and verified by computer simulation, which reveals that nanoparticles' orientations have a large impact on HRTEM images at ultrahigh resolution. It is expected that as-synthesized Fe nanoparticles with sharp corners and edges would be beneficial for tailoring chemical and physical properties at the nanoscale.

Stem cell therapies for periodontal tissue regeneration: a network meta-analysis of preclinical studies.

BACKGROUND: Periodontal tissue regeneration (PTR) is the ultimate goal of periodontal therapy. Currently, stem cell therapy is considered a promising strategy for achieving PTR. However, there is still no conclusive comparison that distinguishes clear hierarchies among different kinds of stem cells. METHODS: A systematic review and network meta-analysis (NMA) was performed using MEDLINE (via PubMed), EMBASE, and Web of Science up to February 2020. Preclinical studies assessing five types of stem cells for PTR were included; the five types of stem cells included periodontal ligament-derived stem cells (PDLSCs), bone marrow-derived stem cells (BMSCs), adipose tissue-derived stem cells (ADSCs), dental pulp-derived stem cells (DPSCs), and gingival-derived stem cells (GMSCs). The primary outcomes were three histological indicators with continuous variables: newly formed alveolar bone (NB), newly formed cementum (NC), and newly formed periodontal ligament (NPDL). We performed pairwise meta-analyses using a random-effects model and then performed a random-effects NMA using a multivariate meta-analysis model. RESULTS: Sixty preclinical studies assessing five different stem cell-based therapies were identified. The NMA showed that in terms of NB, PDLSCs (standardized mean difference 1.87, 95% credible interval 1.24 to 2.51), BMSCs (1.88, 1.17 to 2.59), and DPSCs (1.69, 0.64 to 2.75) were statistically more efficacious than cell carriers (CCs). In addition, PDLSCs were superior to GMSCs (1.49, 0.04 to 2.94). For NC, PDLSCs (2.18, 1.48 to 2.87), BMSCs (2.11, 1.28 to 2.94), and ADSCs (1.55, 0.18 to 2.91) were superior to CCs. For NPDL, PDLSCs (1.69, 0.92 to 2.47) and BMSCs (1.41, 0.56 to 2.26) were more efficacious than CCs, and PDLSCs (1.26, 0.11 to 2.42) were superior to GMSCs. The results of treatment hierarchies also demonstrated that the two highest-ranked interventions were PDLSCs and BMSCs. CONCLUSION: PDLSCs and BMSCs were the most effective and well-documented stem cells for PTR among the five kinds of stem cells evaluated in this study, and there was no statistical significance between them. To translate the stem cell therapies for PTR successfully in the clinic, future studies should utilize robust experimental designs and reports.

Mouse Tumor-Bearing Models as Preclinical Study Platforms for Oral Squamous Cell Carcinoma.

Preclinical animal models of oral squamous cell carcinoma (OSCC) have been extensively studied in recent years. Investigating the pathogenesis and potential therapeutic strategies of OSCC is required to further progress in this field, and a suitable research animal model that reflects the intricacies of cancer biology is crucial. Of the animal models established for the study of cancers, mouse tumor-bearing models are among the most popular and widely deployed for their high fertility, low cost, and molecular and physiological similarity to humans, as well as the ease of rearing experimental mice. Currently, the different methods of establishing OSCC mouse models can be divided into three categories: chemical carcinogen-induced, transplanted and genetically engineered mouse models. Each of these methods has unique advantages and limitations, and the appropriate application of these techniques in OSCC research deserves our attention. Therefore, this review comprehensively investigates and summarizes the tumorigenesis mechanisms, characteristics, establishment methods, and current applications of OSCC mouse models in published papers. The objective of this review is to provide foundations and considerations for choosing suitable model establishment methods to study the relevant pathogenesis, early diagnosis, and clinical treatment of OSCC.

Retrospective clinical analysis of risk factors associated with failed short implants.

BACKGROUND: With advanced technology, short implants are more commonly used and have proven to have a relatively reliable curable efficacy. A consensus has not been reached regarding potential risk factors related to the loss of short implants. PURPOSE: This large-sample retrospective study concentrated not only on patient characteristics and medical procedures but also on the features of implants in order to uncover the risk factors associated with short implants. METHODS: Between 2014 and 2017, a total of 7001 implants were inserted at Nanjing Stomatological Hospital, Medical School of Nanjing University. Among the all, 1236 short implants were included after being evaluated according to the inclusion and exclusion criteria. In organizing the detailed information, seven variables including bone grafting procedure, age, gender, diameter of the implant, implant position, surface treatment, and definitive restorations were taken into consideration. The χ2 test, Kaplan-Meier test, logistic regression, and multifactorial Cox regression analysis were employed to explore the risk factors. RESULTS: The cumulative survival rate of short implants was 96.36%, slightly lower than that of the standard implants (98.16%, P < .001). Most of the short implants (84.44%) were lost at the early stage, mainly because of infection. Based on the results, male gender, implants treated by titanium anodizing and single-crown restoration increased the loss rate of short implants. Comparison of the short implants inserted into the maxillary and mandibular posterior area alone showed that the maxillary molar area was a risk factor for prognosis. CONCLUSIONS: Male gender, TA surface treatment, and the presence of a single crown were associated with an increasing rate of short implants loss. Examination of the implant location focused on the posterior area revealed the maxillary posterior area to be a risk factor.