958 research outputs found

    Comparing three-dimensional and two-dimensional deep-learning, radiomics, and fusion models for predicting occult lymph node metastasis in laryngeal squamous cell carcinoma based on CT imaging: a multicentre, retrospective, diagnostic studyResearch in context

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    Summary: Background: The occult lymph node metastasis (LNM) of laryngeal squamous cell carcinoma (LSCC) affects the treatment and prognosis of patients. This study aimed to comprehensively compare the performance of the three-dimensional and two-dimensional deep learning models, radiomics model, and the fusion models for predicting occult LNM in LSCC. Methods: In this retrospective diagnostic study, a total of 553 patients with clinical N0 stage LSCC, who underwent surgical treatment without distant metastasis and multiple primary cancers, were consecutively enrolled from four Chinese medical centres between January 01, 2016 and December 30, 2020. The participant data were manually retrieved from medical records, imaging databases, and pathology reports. The study cohort was divided into a training set (n = 300), an internal test set (n = 89), and two external test sets (n = 120 and 44, respectively). The three-dimensional deep learning (3D DL), two-dimensional deep learning (2D DL), and radiomics model were developed using CT images of the primary tumor. The clinical model was constructed based on clinical and radiological features. Two fusion strategies were utilized to develop the fusion model: the feature-based DLRad_FB model and the decision-based DLRad_DB model. The discriminative ability and correlation of 3D DL, 2D DL and radiomics features were analysed comprehensively. The performances of the predictive models were evaluated based on the pathological diagnosis. Findings: The 3D DL features had superior discriminative ability and lower internal redundancy compared to 2D DL and radiomics features. The DLRad_DB model achieved the highest AUC (0.89–0.90) among all the study sets, significantly outperforming the clinical model (AUC = 0.73–0.78, P = 0.0001–0.042, Delong test). Compared to the DLRad_DB model, the AUC values for the DLRad_FB, 3D DL, 2D DL, and radiomics models were 0.82–0.84 (P = 0.025–0.46), 0.86–0.89 (P = 0.75–0.97), 0.83–0.86 (P = 0.029–0.66), and 0.79–0.82 (P = 0.0072–0.10), respectively in the study sets. Additionally, the DLRad_DB model exhibited the best sensitivity (82–88%) and specificity (79–85%) in the test sets. Interpretation: The decision-based fusion model DLRad_DB, which combines 3D DL, 2D DL, radiomics, and clinical data, can be utilized to predict occult LNM in LSCC. This has the potential to minimize unnecessary lymph node dissection and prophylactic radiotherapy in patients with cN0 disease. Funding: National Natural Science Foundation of China, Natural Science Foundation of Shandong Province

    Continuous cropping of potato changed the metabolic pathway of root exudates to drive rhizosphere microflora

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    For potato production, continuous cropping (CC) could lead to autotoxicity buildup and microflora imbalance in the field soil, which may result in failure of crops and reduction in yield. In this study, non-targeted metabolomics (via liquid chromatography with tandem mass spectrometry (LC–MS/MS)) combined with metagenomic profiling (via high-throughput amplicon sequencing) were used to evaluate correlations between metabolomics of potato root exudates and communities of bacteria and fungi around potato plants to illustrate the impacts of CC. Potato plants were grown in soil collected from fields with various CC years (0, 1, 4, and 7 years). Metabolomic analysis showed that the contents and types of potential autotoxins in potato root exudates increased significantly in CC4 and CC7 plants (i.e., grown in soils with 4 and 7 years of CC). The differentially expressed metabolites were mainly produced via alpha-linolenic acid metabolism in plant groups CC0 and CC1 (i.e., no CC or 1 year CC). The metabolomics of the groups CC4 and CC7 became dominated by styrene degradation, biosynthesis of siderophore group non-ribosomal peptides, phenylpropanoid biosynthesis, and biosynthesis of various plant secondary metabolites. Continuous cropping beyond 4 years significantly changed the bacterial and fungal communities in the soil around the potato crops, with significant reduction of beneficial bacteria and accumulation of harmful fungi. Correlations between DEMs and microflora biomarkers were established with strong significances. These results suggested that continuous cropping of potato crops changed their metabolism as reflected in the plant root exudates and drove rhizosphere microflora to directions less favorable to plant growth, and it needs to be well managed to assure potato yield.This article is published as Xing, Yanhong, Pingliang Zhang, Wenming Zhang, Chenxu Yu, and Zhuzhu Luo. "Continuous cropping of potato changed the metabolic pathway of root exudates to drive rhizosphere microflora." Frontiers in Microbiology 14: 1318586. doi: https://doi.org/10.3389/fmicb.2023.1318586. © 2024 Xing, Zhang, Zhang, Yu and Luo. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY)

    Low-frequency vibration absorption of magnetic quasi-zero-stiffness structures with lever mechanism

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    Dynamic vibration absorbers (DVAs) are widely employed in diverse engineering systems for their capacity to mitigate structural vibrations. However, traditional absorbers exhibit sensitivity to natural frequencies and present challenges in tuning within the low-frequency range. This study introduces a lever mechanism to enhance the low-frequency vibration absorption performance of magnetic quasi-zero-stiffness structures, resulting in a lever-type DVA (L-DVA). We elucidate the design philosophy behind the proposed L-DVA. An analytical model is derived based on the Lagrange equation and the frequency-response relationship is determined using the harmonic balance method. We conduct numerical and experimental analyses to assess the impact of the lever ratio, mass ratio, frequency ratio, nonlinear stiffness coefficient ratio, and damping ratio on vibration absorption performance. Furthermore, we fabricate a prototype of the L-DVA with an adjustable magnetic quasi-zero-stiffness structure, and the experimental results align with simulation outcomes. The result shows that this study is the ease of customization in the vibration absorption capabilities of magnetic quasi-zero-stiffness structures, achieved by adjusting the lever ratio. An increase in the lever ratio and tip mass effectively shifts the anti-resonant peak to a lower frequency. The decrease in the frequency ratio leads to a reduction in the anti-resonant frequency. This study validates the efficacy and feasibility of utilizing the L-DVA for low-frequency vibration absorption

    Combinatorial Drug Screening Based on Massive 3D Tumor Cultures Using Micropatterned Array Chips

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    The establishment and application of a generalizable three-dimensional (3D) tumor device for high-throughput screening plays an important role in drug discovery and cancer therapeutics. In this study, we introduce a facile microplatform for considerable 3D tumor generation and combinatorial drug screening evaluation. High fidelity of chip fabrication was achieved depending on the simple and well-improved microcontact printing. We demonstrated the high stability and repeatability of the established tumor-on-a-chip system for controllable and massive production of 3D tumors with high size uniformity. Importantly, we accomplished the screening-like chemotherapy investigation involving individual and combinatorial drugs and validated the high accessibility and applicability of the system in 3D tumor-based manipulation and analysis on a large scale. This achievement in tumor-on-a-chip has potential applications in plenty of biomedical fields such as tumor biology, pharmacology, and tissue microengineering. It offers an insight into the development of the popularized microplatform with easy-to-fabricate and easy-to-operate properties for cancer exploration and therapy

    Integrated Path Tracking Controller of Underground Articulated Vehicle Based on Nonlinear Model Predictive Control

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    This paper proposes an integrated path tracking controller for articulated vehicles. A nonlinear model-predictive control (NMPC)-based reference state tracker is designed as an upper-level controller to solve the vehicle’s longitudinal velocity and steering rate. A terminal cost is introduced into the NMPC to improve the controller’s stability. A lower-level controller is developed to translate upper-level solutions into vehicle actuators’ signals, including steering and driving controllers. The steering controller translates the steering rate into the linear velocity of the cylinder to calculate the required fluid volume and ultimately into the rotation speed of the steering motor. The neural network method is applied in the driving controller to ensure accuracy under different loadings. In order to investigate the effects of the path tracking controller, an articulated dump truck is adapted for the field tests by adding the steering-by-wire system and driving-by-wire system, respectively. Experimental verifications of the lower-level controller are performed. The results show that the controller can accurately satisfy the demand. Finally, the tracking performance of the integrated path tracking controller is analyzed experimentally under different reference velocities. The results indicate that tracking accuracy can be guaranteed

    On the stability of critical points of the Hardy-Littlewood-Sobolev inequality

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    This paper is concerned with the quantitative stability of critical points of the Hardy-Littlewood-Sobolev inequality. Namely, we give quantitative estimates for the Choquard equation: Δu=(Iμu2μ)u2μ1  in  RN,-\Delta u=(I_{\mu}\ast|u|^{2_\mu^*}) u^{2_\mu^*-1}\ \ \text{in}\ \ \R^N, where u>0, N3, μ(0,N)u>0,\ N\geq 3,\ \mu\in(0,N), IμI_{\mu} is the Riesz potential and 2μ2NμN22_\mu^* \coloneqq \frac{2N-\mu}{N-2} is the upper Hardy-Littlewood-Sobolev critical exponent. The Struwe's decomposition (see M. Struwe: Math Z.,1984) showed that the equation Δu+uN+2N2=0\Delta u + u^{\frac{N+2}{N-2 }}=0 has phenomenon of ``stable up to bubbling'', that is, if u0u\geq0 and Δu+uN+2N2(D1,2)1\|\Delta u+u^{\frac{N+2}{N-2}}\|_{(\mathcal{D}^{1,2})^{-1}} approaches zero, then d(u)d(u) goes to zero, where d(u)d(u) denotes the D1,2(RN)\mathcal{D}^{1,2}(\R^N)-distance between uu and the set of all sums of Talenti bubbles. Ciraolo, F{}igalli and Maggi (Int. Math. Res. Not.,2017) obtained the f{}irst quantitative version of Struwe's decomposition with single bubble in all dimensions N3N\geq 3, i.e, d(u)CΔu+uN+2N2L2NN+2.\displaystyle d(u)\leq C\|\Delta u+u^{\frac{N+2}{N-2}}\|_{L^{\frac{2N}{N+2}}}. For multiple bubbles, F{}igalli and Glaudo (Arch. Rational Mech. Anal., 2020) obtained quantitative estimates depending on the dimension, namely d(u)CΔu+uN+2N2(D1,2)1, where 3N5, d(u)\leq C\|\Delta u+u^{\frac{N+2}{N-2}}\|_{(\mathcal{D}^{1,2})^{-1}}, \hbox{ where } 3\leq N\leq 5, which is invalid as N6.N\geq 6. \vskip0.1in \quad In this paper, we prove the quantitative estimate of the Hardy-Littlewood-Sobolev inequality, we get d(u)\leq C\|\Delta u +(I_{\mu}\ast|u|^{2_\mu^*})|u|^{2_\mu^*-2}u\|_{(\mathcal{D}^{1,2})^{-1}}, \hbox{ when } N=3 \hbox{ and } 5/2< \mu<3.$

    Artificial multi-enzyme cascades and whole-cell transformation for bioconversion of C1 compounds: Advances, challenge and perspectives

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    Artificial multi-enzyme cascades bear great potential for bioconversion of C1 compounds to value-added chemicals. Over the past decade, massive efforts have been devoted to constructing multi-enzyme cascades to produce glycolic acid, rare functional sugars and even starch from C1 compounds. However, in contrast to traditional fermentation utilizing C1 compounds with the expectation of competitive economic performance in future industrialization, multi-enzyme cascades systems in the proof-of-concept phase are facing the challenges of upscaling. Here, we offered an overview of the recent advances in the construction of in vitro multi-enzyme cascades and whole-cell transformation using C1 compounds as substrate. In addition, the existing challenges and possible solutions were also discussed aiming to combine the strengths of in vitro and in vivo multi-enzyme cascades systems for upscaling

    Development of a recombinase-aided amplification combined with a lateral flow dipstick assay for rapid detection of H7 subtype avian influenza virus

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    Avian influenza viruses (AIV) pose a significant persistent threat to the public health and safety. It is estimated that there have been over 100 outbreaks caused by various H7 subtypes of avian influenza viruses (AIV-H7) worldwide, resulting in over 33 million deaths of poultry. In this study, we developed a recombinase-aided amplification combined with a lateral flow dipstick assay for the detection of hemagglutinin (HA) genes to provide technical support for rapid clinical detection of AIV-H7. The results showed that the assay can complete the reaction within 30 min at a temperature of 39°C. Specificity tests demonstrated that there was no cross-reactivity with other common poultry pathogens, including Newcastle disease virus (NDV) and infections bronchitis virus (IBV). The detection limit of this assay was 1 × 101 copies/μL, while RT-qPCR method was 1 × 101 copies/μL, and RT-PCR was 1 × 102 copies/μL. The κ value of the RT-RAA-LFD and RT-PCR assay in 132 avian clinical samples was 0.9169 (p &lt; 0.001). These results indicated that the developed RT-RAA-LFD assay had good specificity, sensitivity, stability and repeatability and may be used for rapid detection of AIV-H7 in clinical diagnosis
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