Search

Machine learning methods have been widely used in the investigations of the complex plasmas. In this paper, we demonstrate that the unsupervised convolutional neural network can be applied to obtain the melting line in the two-dimensional complex plasmas based on the Langevin dynamics simulation results. The training samples do not need to be labeled. The resulting melting line coincides with those obtained by the analysis of hexatic order parameter and supervised machine learning method.

Purpose: Oxidative stress and apoptosis contribute to the pathological basis of doxorubicin (DOX)-induced cardiotoxicity. Columbianadin (CBN) is one of the main bioactive constituents isolated from the root of Angelica pubescens. Herein, we intended to explore the potential role and molecular basis of CBN in DOX-induced cardiotoxicity. Methods: C57BL/6 mice were subjected to DOX (15 mg/kg/day, i.p.) to generate DOX-induced cardiotoxicity. CBN (10 mg/kg/day, i.p.) was administered for four week following DOX injection. Results: DOX administered markedly dampened cardiac function, increased cardiac injury, excessive reactive oxygen species (ROS) production, and cardiomyocyte loss. These alterations induced by DOX significantly alleviated by CBN treatment. Mechanistically, our results demonstrated that the CBN exerts cardioprotection role against DOX by up-regulating silent information regulator 1 (Sirt1) and decreasing acetylation of forkhead box O1 (FOXO1). Moreover, Sirt1 inhibition with Ex-527 significantly blunt the beneficial effect of CBN on DOX-induced cardiotoxicity, including cardiac dysfunction, ROS, and apoptosis. Conclusion: Collectively, CBN attenuated oxidative stress and cardiomyocyte apoptosis in DOX-induced cardiotoxicity through maintaining Sirt1/FOXO1 signaling pathway. Our results demonstrated that CBN might be used to treat DOX-related cardiotoxicity.

We study the two-photon scattering processes in a one-dimensional (1D) waveguide coupled to a two- or three-level giant atom, respectively. The accumulated phase shift between the two coupling points can be utilized to alter the scattering processes. We obtain the exact interacting two-photon scattering wavefunction of these two systems following the Lippmann-Schwinger (LS) formalism, from which the analytical expressions of incoherent power spectra and second-order correlations are also derived. The incoherent spectrum, defined by the correlation of the bound state, serves as a useful indication of photon-photon correlation. The second-order correlation function gives a direct measure of photon-photon correlation. For photons scattered by the two-level giant atom, the accumulated phase shift can be used to improve photon-photon correlation, and adjust the evolution of the second-order correlation. In the system of the three-level giant atom, the photon-photon correlation can be substantially increased. Moreover, the photon-photon interactions and correlation distance of scattered photons can be further enhanced by tuning the accumulated phase shift.

Fruit cracking decreases the total production and the commercial value of watermelon. The molecular mechanisms of fruit cracking are unknown. In this study, 164 recombinant inbred lines (RILs) of watermelon, derived from the crossing of the WQ1 (cracking-sensitive) and WQ2 (cracking-tolerant) lines, were sequenced using specific length amplified fragment sequencing (SLAF-seq). A high-density genetic linkage map was constructed with 3,335 markers spanning 1,322.74 cM, at an average 0.40 cM across whole-genome flanking markers. The cracking tolerance capacity (CTC), depth of fruit cracking (DFC), rind thickness (RT), and rind hardness (RH) were measured for quantitative trait locus (QTL) analysis. Of the four traits analyzed, one major QTL with high phenotypic variation (41.04%–61.37%) was detected at 76.613–76.919 cM on chromosome 2, which contained 104 annotated genes. Differential gene expression analysis with RNA sequencing (RNA-seq) data between the two parents identified 4,508 differentially expressed genes (DEGs). Comparison of the genes between the QTL region and the DEGs obtained eight coexisting genes. Quantitative real-time PCR (qRT-PCR) analysis revealed that these genes were significant differentially expressed between the two parents. These results provide new insights into the identification of QTLs or genes and marker-assisted breeding in watermelon.

4D human perception plays an essential role in a myriad of applications, such as home automation and metaverse avatar simulation. However, existing solutions which mainly rely on cameras and wearable devices are either privacy intrusive or inconvenient to use. To address these issues, wireless sensing has emerged as a promising alternative, leveraging LiDAR, mmWave radar, and WiFi signals for device-free human sensing. In this paper, we propose MM-Fi, the first multi-modal non-intrusive 4D human dataset with 27 daily or rehabilitation action categories, to bridge the gap between wireless sensing and high-level human perception tasks. MM-Fi consists of over 320k synchronized frames of five modalities from 40 human subjects. Various annotations are provided to support potential sensing tasks, e.g., human pose estimation and action recognition. Extensive experiments have been conducted to compare the sensing capacity of each or several modalities in terms of multiple tasks. We envision that MM-Fi can contribute to wireless sensing research with respect to action recognition, human pose estimation, multi-modal learning, cross-modal supervision, and interdisciplinary healthcare research., Project page: https://ntu-aiot-lab.github.io/mm-fi

Conformer-based models have become the most dominant end-to-end architecture for speech processing tasks. In this work, we propose a carefully redesigned Conformer with a new down-sampling schema. The proposed model, named Fast Conformer, is 2.8x faster than original Conformer, while preserving state-of-the-art accuracy on Automatic Speech Recognition benchmarks. Also we replace the original Conformer global attention with limited context attention post-training to enable transcription of an hour-long audio. We further improve long-form speech transcription by adding a global token. Fast Conformer combined with a Transformer decoder also outperforms the original Conformer in accuracy and in speed for Speech Translation and Spoken Language Understanding.

Ischemic stroke (IS) is the second leading cause of death and disability in the world. Pyroptosis, a form of programmed cell death initiated by caspases, participates in the occurrence and development of IS. Because it can increase cell membrane permeability, mediate the release of inflammatory factors, and aggravate inflammation, inhibiting this process can significantly reduce the pathological injury of IS. The nucleotide binding oligomerization domain-like receptor family pyrin domain protein 3 (NLRP3) is a multiprotein complex whose activation is the core link of pyroptosis. In recent years, studies have reported that traditional Chinese medicine (TCM) could regulate pyroptosis mediated by NLRP3 inflammasome through multi-channel and multi-target networks and thus exert the effect against IS. This article reviews 107 papers published in recent years in PubMed, Chinese National Knowledge Infrastructure (CNKI), and WanFang Data in recent years. It has found that the activation factors of NLRP3 inflammasome include ROS, mitochondrial dysfunction, K+, Ca2+, lysosome rupture, and trans-Golgi breakdown. TLR4/NF-κB/NLRP3, ROS/TXNIP/NLRP3, AMPK/Nrf2/NLRP3, DRP1/NLRP3, TAK1/JNK/NLRP3 signaling pathways regulate the initiation and assembly of the NLRP3 inflammasome, subsequently induce pyroptosis, affecting the occurrence and development of IS. TCM can affect the above signaling pathways and regulate the pyroptosis mediated by NLRP3 inflammasome, so as to play a protective role against IS, which provides a new entry point for discussing the pathological mechanism of IS and a theoretical basis for developing TCM treasure house.

Cellulose extraction accounts for 70% of the total production cost required for the preparation of micro/nano cellulose. Conventional pretreatment methods cause equipment corrosion and generate non-recyclable waste liquids. Thus the industrial-scale preparation of micro/nano cellulose is limited. To overcome this limitation, herein, a method is proposed, where in a mild alkaline pretreatment is combined with the micro-nano bubble (MNB) treatment, for the extraction of cellulose from bagasse. A delignification rate of >92% was attained, micro/nano cellulose was exposed on the pulp surface owing to the MNB treatment; the 4-h MNB treatment resulted in the complete exposure of micro/nano fibers. The production cost for this process was only 3.19 USD/kg CNFs, about 70.9 times lower than that for TEMPO oxidation. An appropriate MNB treatment time (1 h, 2 h) allowed the retention of moderate micro-fibers, which enhanced the maximum tensile force and tensile strength of micro/nano cellulose paper by about 50%. The results revealed that the proposed method serves as an efficient, green, and sustainable strategy for the large-scale and low-cost production of micro/nano cellulose.

OBJECTIVE: : To analyze the clinical features of hemophagocytic syndrome (HLH) following B cell maturation antigen (BCMA) chimeric antigen receptor (CAR) T cell therapy in patients with relapsed/refractory multiple myeloma. METHODS: : Ninety-nine patients with relapsed/refractory multiple myeloma (including 3 cases of plasma cell leukemia) undergoing BCMA CAR-T cell therapy (monocentric phaseⅠclinical trial, ChiCTR1800017404) in the First Affiliated Hospital, Zhejiang University School of Medicine from July 2018 to December 2021 were enrolled in the study. The baseline features, laboratory findings, treatment, and clinical response of these patients were analyzed. RESULTS: : CAR-T cell associated HLH (carHLH) occurred in 20 patients (20.20%), and the median onset time was 7(0–19) d after cytokine release syndrome (CRS). Patients with carHLH were maily male patients, and manifested as high percentage of abnormal plasma cells, higher incidence of severe CRS (grade 3–4), and robust expansion of CAR-T cells in the peripheral blood (all P0.05]. CONCLUSIONS: The incidence of carHLH is relatively high in BCMA CAR-T cell treated patients, which is closely related to pretreatment tumor cell percentage in bone marrow, expansion of CAR-T cells and the secretion of cytokines. Medication based on tocilizumab and steroids can achieve considerable therapeutic effects in patient with carHLH.

Chimeric antigen receptor (CAR) T cell therapy is an effective treatment for hematological malignancies, which have experienced the development of CD19 CAR-T cells for B lymphoblastic leukemia and lymphoma, B cell maturation antigen (BCMA) CAR-T cells for multiple myeloid, and more recently, the development of CD7 CAR-T cells for T cell malignancies. There are more obstacles for myeloid malignancies compared to other hematological malignancies in this field, thus concerning researches are in more diverse ways. In order to obtain more effective clinical CAR-T cells with lower side effects, scientists have developed multi-target CAR-T cells, universal CAR-T cells, as well as CAR-T cells, CAR-NK cells, CAR-iMac cells derived from induced pluripotent stem cells (iPSC) by genetic engineering. Chinese scientists have made significant contribution to the invention and manufacture of origin CAR-T cells and the establishment of an intact clinical research system. This review introduces the latest progress involving CAR-T cell therapy for hematological malignancies including B lymphoblastic malignancies, T lymphoblastic malignancies and myeloid malignancies, and also discuss the future developments including multi-target, universal and iPSC-derived CAR-related cell therapy.

OBJECTIVE: : To explore the risk factors of acute kidney injury (AKI) during B cell maturation antigen (BCMA) chimeric antigen receptor (CAR) T cell therapy in patients with relapsed/refractory multiple myeloma (MM). METHODS: : The clinical data of 99 patients with relapsed/refractory MM who received BCMA CAR-T cell therapy in the First Affiliated Hospital of Zhejiang University School of Medicine from July 2018 to December 2021 was retrospectively analyzed. Dynamic changes of renal function before and after chemotherapy preconditioning and after CAR-T cell infusion were observed. Logistic regression was used to analyze the independent risk factors associated with the occurrence of AKI. RESULTS: : Among 99 patients, the AKI occurred in 25 cases with an incidence rate of 25.3%, and the median time was 8.0 (5.5,11.0) d. The AKI grade 1, 2 and 3 accounted for 8.0%, 12.0% and 36.0%, respectively. Logistic regression analysis showed that serum creatinine (SCr) after chemotherapy preconditioning ( OR=1.020, P

ObjectivesShanghai witnessed an unprecedented outbreak of COVID-19 and experienced a strict lockdown from March 28, 2022 to May 31, 2022. Most studies to date are on the first lockdown after the outbreak in December 2019. This study aimed to examine the impact of lockdown on delivery and neonatal outcomes among uninfected pregnant women in the new phase of the COVID-19 outbreak.MethodsA retrospective analysis was conducted in the Obstetrics and Gynecology Hospital of Fudan University. Pregnant women without COVID-19 who delivered from March 28, 2022 to May 31, 2022 (lockdown group) and the same period in 2021 (non-lockdown group) were recruited for this study. Logistic regression models and 1 : 1 propensity score matching (PSM) were used to assess the effect of lockdown on delivery outcomes.ResultsA total of 2,962 patients were included in this study, 1,339 of whom were from the lockdown group. Compared with the non-lockdown group, pregnant women giving birth during lockdown had an increased risk of term prelabor rupture of membranes (TPROM) (aOR = 1.253, 95% CI: 1.026–1.530), and decreased risks of postpartum hemorrhage (PPH) (aOR = 0.362, 95% CI: 0.216–0.606) and fetal malformation (aOR = 0.309, 95% CI: 0.164–0.582). The risk of large for gestational age (LGA) (aOR = 0.802, 95% CI: 0.648–0.992) and rate of admission to the neonatal intensive care unit (NICU) (aOR = 0.722, 95% CI: 0.589–0.885) also significantly declined. After 1 : 1 PSM, the impact of lockdown on the risk of TPROM (aOR = 1.501, 95% CI: 1.083–2.080), PPH (aOR = 0.371, 95% CI: 0.211–0.654), fetal malformation (aOR = 0.332, 95% CI: 0.161–0.684), LGA (aOR = 0.749, 95% CI: 0.594–0.945) and rate of admission to the NICU (aOR = 0.700, 95% CI: 0.564–0.869) all remained. There were no other delivery or neonatal outcomes affected by the lockdown after the COVID-19 outbreak.ConclusionThis study indicated a significant increase in the risk of term PROM, significant decreases in the risk of PPH, fetal malformation and LGA, and a marked decline in the rate of admission to the NICU during Shanghai Lockdown.

Additional file 5: Figure S4. GO terms (A-C) and KEGG pathways (D-F) significantly enriched in DEGs in comparisons of ND4_VS_AD4, ND5_VS_AD5, ND6_VS_AD6.

Additional file 2: Table S2 Clinical characteristics of different risk groups in the validation cohort.

We study speech intent classification and slot filling (SICSF) by proposing to use an encoder pretrained on speech recognition (ASR) to initialize an end-to-end (E2E) Conformer-Transformer model, which achieves the new state-of-the-art results on the SLURP dataset, with 90.14% intent accuracy and 82.27% SLURP-F1. We compare our model with encoders pretrained on self-supervised learning (SSL), and show that ASR pretraining is much more effective than SSL for SICSF. To explore parameter efficiency, we freeze the encoder and add Adapter modules, and show that parameter efficiency is only achievable with an ASR-pretrained encoder, while the SSL encoder needs full finetuning to achieve comparable results. In addition, we provide an in-depth comparison on end-to-end models versus cascading models (ASR+NLU), and show that E2E models are better than cascaded models unless an oracle ASR model is provided. Last but not least, our model is the first E2E model that achieves the same performance as cascading models with oracle ASR. Code, checkpoints and configs are available., Comment: INTERSPEECH 2023

Additional file 1: Figure S1. Six different development stages of non-anemone-type and anemone-type chrysanthemums based on the Table 1.

Additional file 1: Fig. S1. Influence of WCO from different canteens on α-humulene production. Fig. S2. Influence of differential genes regulation on α-humulene production (DCW). (A) Overexpression of genes with significantly up-regulated transcript levels. (B) down-regulation of gene with significantly down-regulated transcript levels. The data represent the means ± standard deviations (n = 3). Fig. S3. Rational metabolic engineering to improve α-humulene production (DCW). YALI0_B21780g and YALI0_B21142g were down-regulated. YALI0_E32835g was overexpressed. The data represent the means ± standard deviations (n = 3).

Additional file 12: Figure S8. qRT-PCR analysis of 15 DEGs in three non-anemone-type (082, 086, and PF) and four anemone-type (050, 068, GS, FK) chrysanthemums.

This paper introduces a novel Token-and-Duration Transducer (TDT) architecture for sequence-to-sequence tasks. TDT extends conventional RNN-Transducer architectures by jointly predicting both a token and its duration, i.e. the number of input frames covered by the emitted token. This is achieved by using a joint network with two outputs which are independently normalized to generate distributions over tokens and durations. During inference, TDT models can skip input frames guided by the predicted duration output, which makes them significantly faster than conventional Transducers which process the encoder output frame by frame. TDT models achieve both better accuracy and significantly faster inference than conventional Transducers on different sequence transduction tasks. TDT models for Speech Recognition achieve better accuracy and up to 2.82X faster inference than conventional Transducers. TDT models for Speech Translation achieve an absolute gain of over 1 BLEU on the MUST-C test compared with conventional Transducers, and its inference is 2.27X faster. In Speech Intent Classification and Slot Filling tasks, TDT models improve the intent accuracy by up to over 1% (absolute) over conventional Transducers, while running up to 1.28X faster. Our implementation of the TDT model will be open-sourced with the NeMo (https://github.com/NVIDIA/NeMo) toolkit.

Additional file 4: Figure S1. The expression of seven IRSS genes between normal and tumor.

Additional file 9: Figure S6. Correlation between immune cells and seven genes in TCGA. MAPT and NROB1 have no Significant correlation wirh immune cells in TCGA.

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 \textit{Zuchongzhi} 2.1 superconducting quantum processor. An average of \hhl{$0.8983 \pm 0.0002$} logical fidelity at different logical states with distance-three is achieved, \hhl{taking into account both state preparation and measurement errors.} In particular, \hhl{the magic states $|A^{\pi/4}\rangle_L$, $|H\rangle_L$, and $|T\rangle_L$ are prepared non-destructively with logical fidelities of $0.8771 \pm 0.0009 $, $0.9090 \pm 0.0009 $, and $0.8890 \pm 0.0010$, 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., Comment: In this version, we do not employ readout error mitigation strategies (in the previous version, we use readout transition matrix to mitigate the measurement error) to remove measurement errors because we believe it provides a more predictive assessment of the actual fidelity when generating and consuming magic states for a non-Clifford gate, as consuming the state involves measurement

Additional file 1: Table S1. NOS of the included studies. Table S2. Definition of the primary endpoint. Table S3. Results of the secondary outcomes. Figure S1. The flow chart of the process (*83 from PubMed, 94 from EMbase, 92 from The Cochrane Library and 112 from Web of Science). Figure S2. Results of the secondary outcomes.

Additional file 7: Figure S4. Identification of consensus clusters by prognostic genes.Consensus cluster matrix for k=2 in TCGA dataset.Relative change in area under CDF curve for k=2 to 10 in TCGA dataset.Consensus clustering cumulative distribution functionfor k=2 to 10 in TCGA dataset.Consensus cluster matrix for k=2 in ICGC dataset.Relative change in area under CDF curve for k=2 to 10 in ICGC dataset.Consensus clustering cumulative distribution functionfor k=2 to 10 in ICGC dataset.Contingency table showing the consistency between clustered groups and risk groups in TCGA.Contingency table showing the consistency between clustered groups and risk groups in ICGC.

Additional file 10: Figure S6. The original and full-length gel images of DEGs between NAT and AT disc floret.

Additional file 1: Table S1 Clinical characteristics of different risk groups in the training cohort.

Additional file 14: Figure S10. The stamen of AT and NAT disc floret.

Additional file 1: Supplementary Methods. Supplementary Table S1. Clinical characteristics of patients. Supplementary Figure S1. The overview of patients enrolled in this study and the concurrent gene/pathway alterations. (A) A total of 328 colorectal patients whose treatment-naïve tumor samples harboring BRAF mutations from the database are included in this study. (B) The oncoprint of the most frequently concurrent gene mutations (top panel) and pathway alterations (bottom panel) are shown as legend by BRAF classes. Supplementary Figure S2. Patients with Class 3 BRAF mutations demonstrated longer OS compared to those with Class1/2 BRAF mutations. Patients’ overall survival (OS) data from an additional external cohort were analyzed based on the Kaplan-Meier modeling. NR, not reached.

Additional file 6: Figure S3. The differences in risk scores across clinical features.Age.Gender.Grade.Stage.T stage.N stage.M stage.

Additional file 3: Figure S2. PCA analysis of the 36 samples.

Additional file 2: Table S1. Post-transplant parameters of HLA-matched sibling donorand haploidentical donor.

Additional file 11: Figure S7. RT-PCR analysis of DEGs in two non-anemone-type (082 and 086) and three anemone-type (050, 068, and 153) chrysanthemums using RT-PCR.

Additional file 5: Figure S2. Heat map results of seven IRSS genes expression levels.The expression of seven IRSS genes in the TCGA test set.The expression of seven IRSS genes in the TCGA sum set.The expression of seven IRSS genes in the ICGC validation set.

Additional file 8: Figure S5. Clustering analyses in TCGA and ICGC.PCA results for two groups of patients in TCGA.ggalluvial of two clusters in TCGA displayed the correlation between clusters, risk, and survival status.PCA results for two groups of patients in ICGC.ggalluvial of two clusters in ICGC displayed the correlation between clusters, risk, and survival status.

Additional file 2. Figure S1. Bone marrow smear diagram and representative images of AML subtypes; Figure S2. Distribution of dual-center test dataset in the study; Figure S3. AMLnet diagnostic pipeline; Figure S4. Performance of the AMLnet on image and patient level in the test set; Figure S5. Visualization of AMLnet Gradients in Discriminating AML Subtypes M1, M2a, M2b, and M4; Table S1. Characteristics of patients in the developmental and dual-center test datasets; Table S2. Subtype-wise performance of AMLnet at the image level on the test set

Additional file 1: Figure S1. Probabilities of overall survival in haploidentical donor group regarding antithymocyte globulin type.

Additional file 4: Table S4 Clincial characteristic of the patients treated with or without CCT during LRRT in the validation cohort.

We analyze the stability of the Einstein static universe in scalar-tensor theory of gravity, and find it can be stable against both scalar and tensor perturbations under certain conditions. By assuming the emergent scenario originating from an Einstein static state, followed by an instantaneous transition to an inflationary phase, we study and obtain the analytical approximations of the primordial power spectrum for the emergent scenario. Then, we plot the primordial power spectrum and CMB TT-spectrum of the emergent scenario and the slow expansion scenario. These figures show that both of these spectra for the slow expansion scenario are the same as that for $\Lambda$CDM, and the spectra of the emergent scenario are lower than that for $\Lambda$CDM at large scales.

Supplemental Material for Clinical efficacy of ZelanteDVT™ catheter rheolytic thrombectomy in the single-session treatment of patients with subacute deep venous thrombosis by Da Li, Xiaosong Zhang, Yusheng Wang, Hao Tang, He Huang, Xiaomin Huang, and Honggang Zhang in Phlebology.