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Abstract Melanoma is one of the most prevalent skin cancers, with high metastatic rates and poor prognosis. Understanding its molecular pathogenesis is crucial for improving its diagnosis and treatment. Integrated analysis of multi-omics data from 207 treatment-naïve melanomas (primary-cutaneous-melanomas (CM, n = 28), primary-acral-melanomas (AM, n = 81), primary-mucosal-melanomas (MM, n = 28), metastatic-melanomas (n = 27), and nevi (n = 43)) provides insights into melanoma biology. Multivariate analysis reveals that PRKDC amplification is a prognostic molecule for melanomas. Further proteogenomic analysis combined with functional experiments reveals that the cis-effect of PRKDC amplification may lead to tumor proliferation through the activation of DNA repair and folate metabolism pathways. Proteome-based stratification of primary melanomas defines three prognosis-related subtypes, namely, the ECM subtype, angiogenesis subtype (with a high metastasis rate), and cell proliferation subtype, which provides an essential framework for the utilization of specific targeted therapies for particular melanoma subtypes. The immune classification identifies three immune subtypes. Further analysis combined with an independent anti-PD-1 treatment cohort reveals that upregulation of the MAPK7-NFKB signaling pathway may facilitate T-cell recruitment and increase the sensitivity of patients to immunotherapy. In contrast, PRKDC may reduce the sensitivity of melanoma patients to immunotherapy by promoting DNA repair in melanoma cells. These results emphasize the clinical value of multi-omics data and have the potential to improve the understanding of melanoma treatment.

To address the challenges of multiple design variables, long evaluation times, and poor global search capability of traditional surrogate-assisted algorithms that rely on the complete substitution of accurate function evaluations in the turbine aerodynamic optimization process, a pre-screening surrogate-assisted elitist preservation genetic algorithm (pre-SAEGA) optimizer is proposed. Pre-screening strategy in the pre-SAEGA can screen samples instead of directly estimating them, thereby reducing expensive evaluations in each generation. The directly manipulated free-form deformation (DFFD) method is applied to parameterized multi-stage axial turbines, and multi-degree-of-freedom flexible control is realized. Combining the pre-SAEGA with the DFFD method, a data-driven multi-stage axial turbine optimization platform is established. A two-stage axial turbine is the research object, and 44 design variables are selected for the combined optimization design of flow path and blade rows. The results show that the isentropic efficiency and flow rate improve by 1.33 % and 1.81 % respectively, and the pressure ratio decreases by 0.47 % at the turbine design point. The presented optimization platform not only improves the aerodynamic optimization effect but also significantly reduces the number of design variables and real evaluation samples, making it suitable for solving multi-stage turbine optimization problems with multiple degrees of freedom.

Medicago ruthenica is a promising leguminous forage crop due to its lack of saponins, which prevents bloat in livestock from excessive consumption. Legume/grass mixed cropping is an effective forage planting method widely used in agricultural and pastoral regions. However, there is a lack of research on using legume-grass mixed cropping to establish perennial, high-yield, and high-quality cultivated grasslands in the Longxi Loess Plateau. This study conducted a legume/grass intercropping experiment in the Longxi Loess Plateau region of northwestern China, using Medicago ruthenica and Bromus inermis. Experimental plots were established in 2021, with field sampling and laboratory analysis starting in 2022 and 2023, respectively. The research aimed to investigate the effects of intercropping Medicago ruthenica with Bromus inermis on forage yield and quality, and to determine the optimal intercropping ratios. The experiment tested various intercropping ratios of Medicago ruthenica and Bromus inermis in the fall (2:8, 3:7, 4:6, 5:5, 6:4, 7:3, 8:2), with sole crops of each species serving as controls. Results showed that, in the second and third years of mixed cropping, the forage yield under mixed cropping treatments was significantly higher than that of Medicago ruthenica and Bromus inermis monoculture, with increases of 40.89–70.88% and 13.97–38.22% in the second year, and 131.91–199.13% and 44.06–85.82% in the third year. When the legume proportion in the mixed cropping system was around 30%, competition between the two forages reached equilibrium, demonstrating the benefits of mixed cropping. The crude protein and ether extract content of mixed forage were significantly higher than those of monoculture, while the neutral detergent fiber and acid detergent fiber contents were significantly lower, indicating a higher feeding value for the mixed forage. The legume proportion was a key factor influencing the yield of mixed forage. In conclusion, a mixed planting ratio of Medicago ruthenica and Bromus inermis at 3:7 resulted in higher yield and nutritional quality, making it an optimal ratio for establishing cultivated forage fields in the Longxi Loess Plateau.

Abstract Soft tissue sarcoma is a broad family of mesenchymal malignancies exhibiting remarkable histological diversity. We portray the proteomic landscape of 272 soft tissue sarcomas representing 12 major subtypes. Hierarchical classification finds the similarity of proteomic features between angiosarcoma and epithelial sarcoma, and elevated expression of SHC1 in AS and ES is correlated with poor prognosis. Moreover, proteomic clustering classifies patients of soft tissue sarcoma into 3 proteomic clusters with diverse driven pathways and clinical outcomes. In the proteomic cluster featured with the high cell proliferation rate, APEX1 and NPM1 are found to promote cell proliferation and drive the progression of cancer cells. The classification based on immune signatures defines three immune subtypes with distinctive tumor microenvironments. Further analysis illustrates the potential association between immune evasion markers (PD-L1 and CD80) and tumor metastasis in soft tissue sarcoma. Overall, this analysis uncovers sarcoma-type-specific changes in proteins, providing insights about relationships of soft tissue sarcoma.

Abstract MOx (M = Zn, Cu, Mn, Fe, Ce) nanoparticles (NPs) embedded in porous C with uniform diameter and dispersion were synthesized, with potential application as S-absorbents to protect catalysts from S-poisoning in catalytic hydrothermal gasification (cHTG) of biomass. S-absorption performance of MOx/C was evaluated by reacting the materials with diethyl disulfide at HTG conditions (450 °C, 30 MPa, 15 min). Their S-absorption capacity followed the order CuOx/C > CeOx/C ≈ ZnO/C > MnOx/C > FeOx/C. S was absorbed in the first four through the formation of Cu1.8S, Ce2S3, ZnS, and MnS, respectively, with a capacity of 0.17, 0.12, 0.11, and 0.09 molS molM −1. The structure of MOx/C (M = Zn, Cu, Mn) evolved significantly during S-absorption reaction, with the formation of larger agglomerates and separation of MOx particles from porous C. The formation of ZnS NPs and their aggregation in place of hexagonal ZnO crystals indicate a dissolution/precipitation mechanism. Note that aggregated ZnS NPs barely sinter under these conditions. Cu(0) showed a preferential sulfidation over Cu2O, the sulfidation of the latter seemingly following the same mechanism as for ZnO. In contrast, FeOx/C and CeOx/C showed remarkable structural stability with their NPs well-dispersed within the C matrix after reaction. MOx dissolution in water (from liquid to supercritical state) was modeled and a correlation between solubility and particle growth was found, comforting the hypothesis of the importance of an Ostwald ripening mechanism. CeOx/C with high structural stability and promising S-absorption capacity was suggested as a promising bulk absorbent for sulfides in cHTG of biomass.

Abstract Time–frequency ridge not only exhibits the variable process of non-stationary signal with time changing but also provides the information of signal synchronous or non-synchronous components for subsequent detection research. Consequently, the key is to decrease the error between real and estimated ridge in the time–frequency domain for accurate detection. In this article, an adaptive weighted smooth model is presented as a post-processing tool to refine the time–frequency ridge which is based on the coarse estimated time–frequency ridge using newly emerging time–frequency methods. Firstly, the coarse ridge is estimated by using multi-synchrosqueezing transform for vibration signal under variable speed conditions. Secondly, an adaptive weighted method is applied to enhance the large time–frequency energy value location of the estimated ridge. Then, the reasonable smooth regularization parameter associated with the vibration signal is constructed. Thirdly, the majorization–minimization method is developed for solving the adaptive weighted smooth model. Finally, the refined time–frequency characteristic is obtained by utilizing the stop criterion of the optimization model. Simulation and experimental signals are given to validate the performance of the proposed method by average absolute errors. Compared with other methods, the proposed method has the highest performance in refinement accuracy.

The proteogenomic landscape of diffuse gliomas remains to be explored. Here, the authors perform proteogenomic characterisation of diffuse gliomas, investigate the functional role of genomic alterations and suggest three proteomic subgroups.

Using the piezoelectric (PZT) effect, energy-harvesting has become possible for phononic crystal (PnC). Low-frequency vibration energy harvesting is more of a challenge, which can be solved by local resonance phononic crystals (LRPnCs). A novel three-dimensional (3D) energy harvesting LRPnC is proposed and further analyzed using the finite element method (FEM) software COMSOL. The 3D LRPnC with spiral unit-cell structures is constructed with a low initial frequency and wide band gaps (BGs). According to the large vibration deformation of the elastic beam near the scatterer, a PZT sheet is mounted in the surface of that beam, to harvest the energy of elastic waves using the PZT effect. To further improve the energy-harvesting performance, a 5 × 5 super-cell is numerically constructed. Numerical simulations show that the present 3D super-cell PnC structure can make full use of the advantages of the large vibration deformation and the PZT effect, i.e., the BGs with a frequency range from 28.47 Hz to 194.21 Hz with a bandwidth of 142.7 Hz, and the maximum voltage output is about 29.3 V under effective sound pressure with a peak power of 11.5 µW. The present super-cell phononic crystal structure provides better support for low-frequency vibration energy harvesting, when designing PnCs, than that of the traditional Prague type.

The intercooling recuperated cycle (ICR) is commonly employed in marine gas turbines to enhance thermal efficiency. However, the addition of an intercooler may lead to the increased dimension and structural complexity of marine ICR gas turbines. To address this issue, we propose an improved configuration of the intermediate pressure compressor – an axial-centrifugal combined compressor (ACC) with high inlet hub-tip ratio and high flow rate. The aerodynamic performance of the ACC at multi-operating points is optimized via an improved free-form deformation method for the parametric modeling of the flow paths and blades of turbomachinery. The result indicates that the number of stages decreases from 6 to 3 and the axial length is reduced by 38.3% after modification. The adiabatic efficiency of the optimized ACC at the design and low-speed operating points is improved by 1.18% and 6.48% respectively. Additionally, the ACC redesigned scheme can reduce the axial length, maximize the flow path space utilization, enhance the stage load capacity, and significantly improve the low-speed performance. This provides a reference for developing advanced marine ICR gas turbines with high power and low fuel consumption.

Clear cell renal cell carcinoma is an aggressive form of renal cancer, with differences in genomic mutations reported between Western and Eastern populations. In this study, the authors have compiled proteogenomic analysis of Chinese ccRCC to reveal genomic alterations and dysregulation of immune and metabolic responses.

Summary: The eye is a complex organ consisting of multiple compartments with unique and specialized properties, and small disturbances in one eye region can result in impaired vision and blindness. Although there have been advancements in ocular research, the hierarchical molecular network in region-wide resolution, indicating the division of labor and crosstalk among different eye regions, is not yet comprehensively illuminated. Here, we present an atlas of region-resolved proteome and lipidome of mouse eye. Multiphoton microscopy-guided laser microdissection combined with in-depth label-free proteomics identifies 13,536 proteins across various mouse eye regions. Further integrative analysis of spectral imaging, label-free proteome, and imaging mass spectrometry of the lipidome and phosphoproteome reveals distinctive molecular features, including proteins and lipids of various anatomical mouse eye regions. These deposited datasets and our open proteome server integrating all information provide a valuable resource for future functional and mechanistic studies of mouse eye and ocular disease.

This paper investigates the clocking effect in subsonic compressor element stages and the influence of design parameters on the flow mechanism. We focus on the relationship between the wake-induced separation loss and wake mixing loss and the unsteady mechanism in the wake flow process without considering the transition through several steady and unsteady numerical simulations aimed at a series of subsonic compressor element stages. The simulation results indicate that the performance difference at various indexing positions depends on the relationship between wake mixing loss and wake-induced separation loss for different compressor designs and operating conditions. Furthermore, the pressure transport caused by the negative jet of the Stator 0 wake in Rotor 1 creates a local acceleration region called SFAF, and a decrease in its absolute flow angle reduces the Stator 1 separation. Sufficient rim work of the rotor at highly loaded operating conditions is the basis for generating an effective SFAF. Furthermore, the fore-loading blade of Rotor 1 significantly reduces suction surface pressure drop, and a small angle between the stagger angles of Stator 0 and Rotor 1 increases the unsteady rotor load caused by the upstream wake to the total rotor load, both of which enhance SFAF.

Intelligent fault diagnosis of roller bearings is facing two important problems, one is that train and test datasets have the same distribution, and the other is the installation positions of accelerometer sensors are limited in industrial environments, and the collected signals are often polluted by background noise. In the recent years, the discrepancy between train and test datasets is decreased by introducing the idea of transfer learning to solve the first issue. In addition, the non-contact sensors will replace the contact sensors. In this paper, a domain adaption residual neural network (DA-ResNet) model using maximum mean discrepancy (MMD) and a residual connection is constructed for cross-domain diagnosis of roller bearings based on acoustic and vibration data. MMD is used to minimize the distribution discrepancy between the source and target domains, thereby improving the transferability of the learned features. Acoustic and vibration signals from three directions are simultaneously sampled to provide more complete bearing information. Two experimental cases are conducted to test the ideas presented. The first is to verify the necessity of multi-source data, and the second is to demonstrate that transfer operation can improve recognition accuracy in fault diagnosis.

Comparing with the massive efforts in developing innovative catalyst materials system and technologies, structural design of cells has attracted less attention on the road toward high‐performance electrochemical CO2 reduction reaction (eCO2RR). Herein, a hybrid gas diffusion electrode‐based reaction cell is proposed using highly porous carbon paper (CP) and graphene aerogels (GAs), which is expected to offer directional diffusion of gas molecules onto the catalyst bed, to sustain a high performance in CO2 conversion. The above‐mentioned hypothesis is supported by the experimental and simulation results, which show that the CP + GA combined configuration increases the Faraday efficiency (FE) from ≈60% to over 94% toward carbon monoxide (CO) and formate production compared with a CP only cell with Cu2O as the catalyst. It also suppresses the undesirable side reaction–hydrogen evolution over 65 times than the conventional H‐type cell (H‐cell). By combining with advanced catalysts with high selectivity, a 100% FE of the cell with a high current density can be realized. The described strategy sheds an extra light on future development of eCO2RR with a structural design of cell‐enabled high CO2 conversion.

The compressor global geometric model including the endwall and the blade is parameterized based on a directly manipulated free-form deformation (DFFD) approach. A meridional flow streamline curvature method for solving inverse and forward problems is applied to the reverse design and performance analysis of the compressor. Combined with an improved Powell search algorithm and the multi-island genetic algorithm, a platform for the fast aerodynamic optimal design of the multistage axial compressor is established. The integrated automatic design and performance optimization of a nine-stage axial compressor in a gas turbine are performed. Meanwhile, the inlet transition section, strut and outlet expansion section of the compressor are retrofitted and optimized considering the connection with the front and rear of the test section. The result indicates that the platform can automatically and effectively realize the process of the fast design, analysis and optimization for the multistage axial compressor. Finally, the total pressure ratio and adiabatic efficiency at the design point and the surge margin at the design rotate speed are 5.057, 88.16% and 17.25%, which are 0.377%, 1.043% and 1.173% relatively higher than those before the 3D DFFD optimization respectively.

This paper presents an optimization scheme to better design phononic crystals. A locally resonant phononic crystal (LRPC) structure called square spiral with circle inside is employed to verify the performance of the present scheme. Four geometric parameters, i.e., the side length of square scatterer, the length of each elastic beam, the thickness of elastic beams, and the radii of inner circles, are considered to obtain the corresponding influences on band gaps (BGs) using finite element method (FEM). According to the significant influences of the late two key parameters, a 2-factor (the radii of inner circles, and the thickness of elastic beams) and 7-level experiment is designed to obtain optimal BGs with better low-frequency broadband properties. By 29 times calculations using FEM for the different combination of levels, three relationships between the 2-factor and the first BG's starting frequency, the first BG's bandwidth, and the second BG's bandwidth, are obtained and severed as inputs to the software of response surface methodology (RSM). The closed-form expressions of the three relationships are finally obtained to construct optimization models and result in the optimal band gaps (BGs) between 190-300Hz and 500-600Hz. It is expected that the present optimization scheme can be extended to material design of phononic/photonic structures in a reasonable way.

The complicated flow conditions and massive design parameters bring two main difficulties to the aerodynamic optimization of axial compressors: expensive evaluations and numerous optimization variables. To address these challenges, this paper establishes a novel fast aerodynamic optimization platform for axial compressors, consisting of a radial basic function (RBF)-based blade parameterization method, a data-driven differential evolution optimizer, and a computational fluid dynamic (CFD) solver. As a versatile interpolation method, RBF is used as the shape parameterization and deformation technique to reduce optimization variables. Aiming to acquire competitive solutions in limited steps, a data-driven evolution optimizer is developed, named the pre-screen surrogate model assistant differential evolution (pre-SADE) optimizer. Different from most surrogate model-assisted evolutionary algorithms, surrogate models in pre-SADE are used to screen the samples, rather than directly estimate them, in each generation to reduce expensive evaluations. The polynomial regression model, Kriging model, and RBF model are integrated in the surrogate model to improve the accuracy. To further save optimization time, the optimizer also integrates parallel task management programs. The aerodynamic optimization of a transonic rotor (NASA Rotor 37) is performed as the validation of the platform. A differential evolution (DE) optimizer and another surrogate model-assisted algorithm, committee-based active learning for surrogate model assisted particle swarm optimization (CAL-SAPSO), are introduced for the comparison runs. After optimization, the adiabatic efficiency, total pressure ratio, and surge margin are, respectively, increased by 1.47%, 1.0%, and 0.79% compared to the initial rotor. In the same limited steps, pre-SADE gets a 0.57% and 0.51% higher rotor adiabatic efficiency than DE and CAL-SAPSO, respectively. With the help of parallel techniques, pre-SADE and DE save half the optimization time compared to CAL-SAPSO. The results verify the effectiveness and the rapidity of the fast aerodynamic optimization platform.

This paper investigates the effect of rotor-stator spacing and operating conditions on compressor performance and the rotor-stator interaction mechanism. We focus on the interaction between the rotor wake and the stator’s flow field through several unsteady numerical simulations aiming at a transonic compressor stage in the equal radius flow path with two-axial spacing at three operating conditions. The simulation results indicate that the time-averaged efficiency almost declined by 0.6 points due to mixing loss in the spacing ranging from close to far at nominal and low load operating conditions. The deep upstream wake leads to corner separation at high load conditions due to close spacing, imposing a fluctuating efficiency at the frequency where the stator wake near the shroud oscillates, as found by the dominant frequency screening method. Under all conditions, the wake transport can reduce the static pressure on the pressure surface and weaken the hub leakage flow afterward.

BACKGROUND: The EZSCAN test was recently developed to screen for early dysglycemia through an assessment of sudomotor function. Given the associations of dysglycemia and autonomic dysfunction with the development of arterial stiffness, EZSCAN may also detect early arterial stiffness. The aim of this study was to investigate the association of EZSCAN with arterial stiffness across blood glucose levels. METHODOLOGY AND PRINCIPAL FINDINGS: A total of 5532 participants without diabetes or established cardiovascular disease were evaluated with EZSCAN. Their central systolic blood pressure (cSBP), brachial-ankle pulse wave velocity (baPWV), and ankle-brachial index (ABI) were also measured. Multivariate linear regression analyses were used to assess the association between the EZSCAN value and the cSBP, baPWV, and ABI measurements in all of the participants, with additional subgroup analysis that separated participants into a normal glucose tolerance (NGT) group and an impaired glucose regulation (IGR) group. The frequency of the IGRs increased with quartiles of the EZSCAN value (P for trend

The investigation of charm physics plays an important role in checking the Standard Model’s description of strong and weak interactions, validating its predictions for particle physics, and exploring new physics beyond the Standard Model. Using a large dataset from e+e− annihilation, BESIII has conducted comprehensive and extensive studies in the areas of hadronic, leptonic and semileptonic decays. This proceeding presents an overview of the recent researches and discoveries by BESIII on decays of charmed baryons, charmed mesons and charmonium states, highlighting their significance in advancing the understanding of new physics, experimental determination of physical parameters and improvement of measurement precision. [ABSTRACT FROM AUTHOR]