Imaging through multimode fibres with physical prior

Imaging through perturbed multimode fibres based on deep learning has been widely researched. However, existing methods mainly use target-speckle pairs in different configurations. It is challenging to reconstruct targets without trained networks. In this paper, we propose a physics-assisted, unsupervised, learning-based fibre imaging scheme. The role of the physical prior is to simplify the mapping relationship between the speckle pattern and the target image, thereby reducing the computational complexity. The unsupervised network learns target features according to the optimized direction provided by the physical prior. Therefore, the reconstruction process of the online learning only requires a few speckle patterns and unpaired targets. The proposed scheme also increases the generalization ability of the learning-based method in perturbed multimode fibres. Our scheme has the potential to extend the application of multimode fibre imaging

Implications of C1q/TNF-related protein superfamily in patients with coronary artery disease.

The C1q complement/TNF-related protein superfamily (CTRPs) displays differential effects on the regulation of metabolic homeostasis, governing cardiovascular function. However, whether and how they may serve as predictor/pro-diagnosis factors for assessing the risks of coronary artery disease (CAD) remains controversial. Therefore, we performed a clinical study to elaborate on the implication of CTRPs (CTRP1, CTRP5, CTRP7, and CTRP15) in CAD. CTRP1 were significantly increased, whereas CTRP7 and CTRP15 levels were decreased in CAD patients compared to the non-CAD group. Significant differences in CTRP1 levels were discovered between the single- and triple-vascular-vessel lesion groups. ROC analysis revealed that CTRP7 and CTRP15 may serve as CAD markers, while CTRP1 may serve as a marker for the single-vessel lesion of CAD. CTRP1 and CTRP5 can serve as markers for the triple-vessel lesion. CTRP1 may serve as an independent risk predictor for triple-vessel lesion, whereas CTRP15 alteration may serve for a single-vessel lesion of CAD. CTRP1 may serve as a novel superior biomarker for diagnosis of severity of vessel-lesion of CAD patients. CTRP7, CTRP15 may serve as more suitable biomarker for the diagnosis of CAD patients, whereas CTRP5 may serve as an independent predictor for CAD. These findings suggest CTRPs may be the superior predictive factors for the vascular lesion of CAD and represent novel therapeutic targets against CAD

Research Progress on Structure, Function and Application of β-1,3-Glucanases

β-1,3-Glucanases are enzymes that specifically hydrolyze β-1,3-glycosidic linkages bonds in β-1,3-glucan to generate a range of oligosaccharides or monosaccharides. β-1,3-Glucanases have important potential applications in functional oligosaccharide preparation, fruit and vegetable preservation, biopharmaceuticals, and plant disease resistance. β-1,3-Glucanases belonging to 12 glycoside hydrolase (GH) families have been identified, including GH16, GH17, GH55, GH64, GH81, GH128 and GH132. β-1,3-Glucanases are widely distributed in bacteria, fungi, plants and insects, which exhibit diverse structures and catalytic functions due to differences in sources and sequence evolution. Structural and functional studies of enzymes are the basis for exploring the catalytic mechanism, enzyme properties, and molecular modification. Therefore, this paper reviews the current state of research on the structure, function and application of β-1, 3-glucanases, in order to provide a reference for the basic research and application of β-1,3-glucanases

Computation offloading in blockchain-enabled MCS systems : A scalable deep reinforcement learning approach

In Mobile Crowdsensing (MCS) systems, cloud service providers (CSPs) pay for and analyze the sensing data collected by mobile devices (MDs) to enhance the Quality-of-Service (QoS). Therefore, it is necessary to guarantee security when CSPs and users conduct transactions. Blockchain can secure transactions between two parties by using the Proof-of-Work (PoW) to confirm transactions and add new blocks to the chain. Nevertheless, the complex PoW seriously hinders applying Blockchain into MCS since MDs are equipped with limited resources. To address these challenges, we first design a new consortium blockchain framework for MCS, aiming to assure high reliability in complex environments, where a novel Credit-based Proof-of-Work (C-PoW) algorithm is developed to relieve the complexity of PoW while keeping the reliability of blockchain. Next, we propose a new scalable Deep Reinforcement learning based Computation Offloading (DRCO) method to handle the computation-intensive tasks of C-PoW. By combining Proximal Policy Optimization (PPO) and Differentiable Neural Computer (DNC), the DRCO can efficiently make the optimal/near-optimal offloading decisions for C-PoW tasks in blockchain-enabled MCS systems. Extensive experiments demonstrate that the DRCO reaches a lower total cost (weighted sum of latency and power consumption) than state-of-the-art methods under various scenarios

Spatial Motion of Arytenoid Cartilage Using Dynamic Computed Tomography Combined with Euler Angles.

OBJECTIVE(#br)To investigate the feasibility of dynamic computed tomography in recording and describing the spatial motion characteristics of the arytenoid cartilage.(#br)METHODS(#br)Dynamic computed tomography recorded the real-time motion trajectory of the arytenoid cartilage during inspiration and phonation. A stationary coordinate system was established with the cricoid cartilage as a reference and a motion coordinate system was established using the movement of the arytenoid cartilage. The Euler angles of the arytenoid cartilage movement were calculated by transformation of the two coordinate systems, and the spatial motion characteristics of the arytenoid cartilage were quantitatively studied.(#br)RESULTS(#br)Displacement of the cricoid cartilage was primarily inferior during inspiration. During phonation, the displacement was mainly superior. When the glottis closed, the superior displacement was about 5-8 mm within 0.56 s. During inspiration, the arytenoid cartilage was displaced superiorly approximately 1-2 mm each 0.56 s. The rotation angle was subtle with slight rotation around the XYZ axis, with a range of 5-10 degrees. During phonation, the displacement of the arytenoid cartilage was mainly inferior (about 4-6 mm), anterior (about 2-4 mm) and medial (about 1-2 mm). The motion of the arytenoid cartilage mainly consisted of medial rolling, and there was an alternating movement of anterior-posterior tilting. The arytenoid cartilage rolled medially (about 20-40 degrees within 0.56 s), accompanied by anterior-posterior tilting (about 15-20 degrees within 0.56 s).(#br)CONCLUSION(#br)Dynamic computed tomography recordings of arytenoid cartilage movement can be combined with Euler transformations as a tool to study the spatial characteristics of laryngeal structures during phonation.(#br)LEVEL OF EVIDENCE(#br)4 Laryngoscope, 2019

Ultrahigh-charge electron beams from laser-irradiated solid surface

Compact acceleration of a tightly collimated relativistic electron beam with high charge from a laser–plasma interaction has many unique applications. However, currently the well-known schemes, including laser wakefield acceleration from gases and vacuum laser acceleration from solids, often produce electron beams either with low charge or with large divergence angles. In this work, we report the generation of highly collimated electron beams with a divergence angle of a few degrees, nonthermal spectra peaked at the megaelectronvolt level, and extremely high charge (∼100 nC) via a powerful subpicosecond laser pulse interacting with a solid target in grazing incidence. Particle-in-cell simulations illustrate a direct laser acceleration scenario, in which the self-filamentation is triggered in a large-scale near–critical-density plasma and electron bunches are accelerated periodically and collimated by the ultraintense electromagnetic field. The energy density of such electron beams in high-Z materials reaches to ∼1012 J/m3, making it a promising tool to drive warm or even hot dense matter states

Validity and applicability of the global leadership initiative on malnutrition criteria in non-dialysis patients with chronic kidney disease

IntroductionThere are no standardized assessment criteria for selecting nutritional risk screening tools or indicators to assess reduced muscle mass (RMM) in the Global Leadership Initiative on Malnutrition (GLIM) criteria. We aimed to compare the consistency of different GLIM criteria with Subjective Global Assessment (SGA) and protein-energy wasting (PEW).MethodsIn this study, nutritional risk screening 2002 first four questions (NRS-2002-4Q), Nutritional Risk Screening 2002 (NRS-2002), Malnutrition Universal Screening Tool (MUST), and Mini-Nutritional Assessment Short-Form (MNA-SF) tools were used as the first step of nutritional risk screening for the GLIM. The RMM is expressed using different metrics. The SGA and PEW were used to diagnose patients and classify them as malnourished and non-malnourished. Kappa (κ) tests were used to compare the concordance between the SGA, PEW, and GLIM of each combination of screening tools.ResultsA total of 157 patients were included. Patients with Chronic kidney disease (CKD) stage 1–3 accounted for a large proportion (79.0%). The prevalence rates of malnutrition diagnosed using the SGA and PEW were 18.5% and 19.7%, respectively. The prevalence of GLIM-diagnosed malnutrition ranges from 5.1% to 37.6%, depending on the different screening methods for nutritional risk and the different indicators denoting RMM. The SGA was moderately consistent with the PEW (κ = 0.423, p < 0.001). The consistency among the GLIM, SGA, and PEW was generally low. Using the NRS-2002-4Q to screen for nutritional risk, GLIM had the best agreement with SGA and PEW when skeletal muscle index (SMI), fat-free mass index (FFMI), and hand grip strength (HGS) indicated a reduction in muscle mass (SGA: κ = 0.464, 95% CI 0.28–0.65; PEW: κ = 0.306, 95% CI 0.12–0.49).ConclusionThe concordance between the GLIM criteria and the SGA and PEW depended on the screening tool used in the GLIM process. The inclusion of RMM in the GLIM framework is important. The addition of HGS could further improve the performance of the GLIM standard compared to the use of body composition measurements

Progress in the study of aging marker criteria in human populations

The use of human aging markers, which are physiological, biochemical and molecular indicators of structural or functional degeneration associated with aging, is the fundamental basis of individualized aging assessments. Identifying methods for selecting markers has become a primary and vital aspect of aging research. However, there is no clear consensus or uniform principle on the criteria for screening aging markers. Therefore, we combine previous research from our center and summarize the criteria for screening aging markers in previous population studies, which are discussed in three aspects: functional perspective, operational implementation perspective and methodological perspective. Finally, an evaluation framework has been established, and the criteria are categorized into three levels based on their importance, which can help assess the extent to which a candidate biomarker may be feasible, valid, and useful for a specific use context