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Abstract Wheat stripe rust is a fungal disease caused by Puccinia striiformis f. sp. tritici. The outbreak of wheat stripe rust will have a great impact on wheat production in Xinjiang, China. In order to identify resistance to wheat stripe rust and the distribution of resistance genes in 82 wheat cultivars (41 spring wheat and 41 winter wheat), wheat seedling resistance was evaluated using CYR32, CYR33 and CYR34, and wheat adult plant stage resistance was identified using a combination of 3 races. Six molecular markers were used to identify Yr29, Yr39, Yr46, Yr69 and YrTr1 in 82 wheat cultivars. The results showed that 3 of 82 wheat cultivars (Xinchun No.14, Xinchun No.22, and Xindong No.22) were immune to stripe rust at the adult plant stage. Xinchun No.29, Xinchun No.32, Xindong No.5 and Xindong No.29 were resistant at all stage. The highest detection rates were for Yr69 and YrTr1, at 78.05% and 76.83%. However, the detection rates for Yr39 and Yr46 were only 0 and 2.44%, respectively. The Xindong No.22 were detected with the most resistance genes, which included 4 Yr genes. Furthermore, Xindong No.22 were immune to the disease at adult plant stage. The results confirmed the resistance gene distribution of the wheat cultivars in Xinjiang were heterogeneously, and the number of Yr genes was significantly and positively correlated with wheat cultivars resistant to stripe rust.

Abstract In the Kitaev honeycomb model, spins coupled by strongly-frustrated anisotropic interactions do not order at low temperature but instead form a quantum spin liquid with spin fractionalisation into Majorana fermions and static fluxes. The realization of such a model in crystalline materials could lead to major breakthroughs in understanding entangled quantum states, however achieving this in practice is a very challenging task. The recently synthesized honeycomb material RuI3 shows no long-range magnetic order down to the lowest probed temperatures and has been theoretically proposed as a quantum spin liquid candidate material on the verge of an insulator to metal transition. Here we report a comprehensive study of the magnetic anisotropy in un-twinned single crystals via torque magnetometry and detect clear signatures of strongly anisotropic and frustrated magnetic interactions. We attribute the development of sawtooth and six-fold torque signal to strongly anisotropic, bond-dependent magnetic interactions by comparing to theoretical calculations. As a function of magnetic field strength at low temperatures, torque shows an unusual non-parabolic dependence suggestive of a proximity to a field-induced transition. Thus, RuI3, without signatures of long-range magnetic order, displays key hallmarks of an exciting candidate for extended Kitaev magnetism with enhanced quantum fluctuations.

Summary: This article aims to develop and validate a pathological prognostic model for predicting prognosis in patients with isocitrate dehydrogenase (IDH)-mutant gliomas and reveal the biological underpinning of the prognostic pathological features. The pathomic model was constructed based on whole slide images (WSIs) from a training set (N = 486) and evaluated on internal validation set (N = 209), HPPH validation set (N = 54), and TCGA validation set (N = 352). Biological implications of PathScore and individual pathomic features were identified by pathogenomics set (N = 100). The WSI-based pathological signature was an independent prognostic factor. Incorporating the pathological features into a clinical model resulted in a pathological-clinical model that predicted survival better than either the pathological model or clinical model alone. Ten categories of pathways (metabolism, proliferation, immunity, DNA damage response, disease, migrate, protein modification, synapse, transcription and translation, and complex cellular functions) were significantly correlated with the WSI-based pathological features.

Although immobilization-free and label-free electrochemical DNA (E-DNA) biosensors have engaged tremendous interest due to their superior properties, such as easy operation, time-saving and cost-saving, most of them are fabricated in homogeneous modes and usually produce high background current. In the present work, we proposed a new immobilization-free and label-free heterogeneous E-DNA assay based on a dual-blocker-aided multibranched hybridization chain reaction (HCR) for one-pot nucleic acid detection with zero background. The target nucleic acid triggers the HCR involving cascaded hybridization between two metastable hairpins, resulting in the generation of HCR products with multibranched arms, which can be captured onto the electrode via π-π stacking interactions between multibranched arms and reduced graphene oxide (rGO). Prior to the incubation process with an electrode, two blockers are designed to prohibit the nonspecific absorption of unreacted hairpin probes. Thus, an immobilization-free and label-free heterogeneous electrochemical assay for one-pot nucleic acid detection with zero background is readily realized. This strategy also presents additional merits of simplicity and cheap cost, since probe immobilization, signal tag labeling, and multiple incubation processes are avoided. Therefore, the as-proposed effective and versatile biosensor has great potential to be applied in nucleic acid-related practical biosensing.

Abstract Objectives To propose a surface reconstruction algorithm based on a differential manifold (a space with local Euclidean space properties), which can be used for processing of clinical images and for modeling of the atlantoaxial joint. To describe the ideal anatomy of the lateral atlantoaxial articular surface by measuring the anatomical data. Methods Computed tomography data of 80 healthy subjects who underwent cervical spine examinations at our institution were collected between October 2019 and June 2022, including 46 males and 34 females, aged 37.8 ± 5.1 years (28–59 years). A differential manifold surface reconstruction algorithm was used to generate the model based on DICOM data derived by Vision PACS system. The lateral mass articular surface was measured and compared in terms of its sagittal diameter, transverse diameter, articular surface area, articular curvature and joint space height. Results There was no statistically significant difference between left and right sides of the measured data in normal adults (P > 0.05). The atlantoaxial articular surface sagittal diameter length was (15.83 ± 1.85) and (16.22 ± 1.57) mm on average, respectively. The transverse diameter length of the articular surface was (16.29 ± 2.16) and (16.49 ± 1.84) mm. The lateral articular surface area was (166.53 ± 7.69) and (174.48 ± 6.73) mm2 and the curvature was (164.03 ± 5.27) and (153.23 ± 9.03)°, respectively. The joint space height was 3.05 ± 0.11mm, respectively. There is an irregular articular space in the lateral mass of atlantoaxial, and both upper and lower surfaces of the articular space are concave. A sagittal plane view shows that the inferior articular surface of the atlas is mainly concave above; however, the superior articular surface of the axis is mainly convex above. In the coronal plane, the inferior articular surface of the atlas is mostly concave above, with most concave vertices located in the medial region, and the superior articular surface of the axis is mainly concave below, with most convex vertices located centrally and laterally. Conclusion A differential manifold algorithm can effectively process atlantoaxial imaging data, fit and control mesh topology, and reconstruct curved surfaces to meet clinical measurement applications with high accuracy and efficiency; the articular surface of the lateral mass of atlantoaxial mass in normal adults has relatively constant sagittal diameter, transverse diameter and area. The distance difference between joint spaces is small, but the shape difference of articular surfaces differs greatly.

Due to the high background fluoride content in part of China's Inner Mongolia, Shaanxi, Shanxi and other high-fluorine regions, the concentrated brine with high concentrations of fluoride ions was produced after membrane treatment of coking industry wastewater using coal as raw material. Crystallization and salt separation of brine salt is a necessary method to achieve "zero emission", but the excessive fluoride concentration can have adverse effects on the treatment of concentrated brine. In order to reduce the corrosion of evaporator caused by high concentration of fluoride ions in concentrated brine and its impact on the purity of salt separation, this paper took concentrated brine from a coking enterprise in Hebei, discussed the effects of co-existing ions SO4 2−, NO3 − and Cl− on defluorination agents based on the water quality characteristics of concentrated brine and the defluorination agent developed by our research group. Meanwhile, SEM and EDS were used to characterize the defluorination agents and treated flocs, and the mechanism of defluorination was analyzed. The defluorination effect of one stage treatment process with CaCl2, PAC and defluorination agent was compared. The combined process of CaCl2 and defluorination agent applied in the actual concentrated brine was designed and optimized, then analyzed the economic costs of different treatment schemes. The results showed that the influence order of the three co-existing ions on the effect of defluorination agent was SO4 2−>NO3 −>Cl−. SEM and EDS analysis indicated that F element was uniformly distributed in the floc and could be efficiently removed through the surface adsorption, surface complexation, and surface hydroxyl exchange mechanism. One stage treatment process with defluorination agent was better than the effect of CaCl2 or PAC, when the dosage of defluorination agent was 8 g/L, the removal rate reaches 92.3%. The combined process of CaCl2 and defluorination agent could reduce the concentration of fluoride ions from 238.27 mg/L to less than 10 mg/L. The combination cost of CaCl2 dosage of 6 g/L and fluoride removal agent dosage of 2 g/L was the lowest, which was 14.03 yuan per ton of coking concentrated brine. The two-stage defluorination process with CaCl2+defluorination agent can economically and efficiently remove high concentration fluoride ions from coking concentrated brine which can provide a technical reference for zero discharge of wastewater in the coking industry.

Abstract Background We aimed to develop machine learning models for prediction of molecular subgroups (low-risk group and intermediate/high-risk group) and molecular marker (KIAA1549-BRAF fusion) of pediatric low-grade gliomas (PLGGs) based on radiomic features extracted from multiparametric MRI. Methods 61 patients with PLGGs were included in this retrospective study, which were divided into a training set and an internal validation set at a ratio of 2:1 based on the molecular subgroups or the molecular marker. The patients were classified into low-risk and intermediate/high-risk groups, BRAF fusion positive and negative groups, respectively. We extracted 5929 radiomic features from multiparametric MRI. Thereafter, we removed redundant features, trained random forest models on the training set for predicting the molecular subgroups or the molecular marker, and validated their performance on the internal validation set. The performance of the prediction model was verified by 3-fold cross-validation. Results We constructed the classification model differentiating low-risk PLGGs from intermediate/high-risk PLGGs using 4 relevant features, with an AUC of 0.833 and an accuracy of 76.2% in the internal validation set. In the prediction model for predicting KIAA1549-BRAF fusion using 4 relevant features, an AUC of 0.818 and an accuracy of 81.0% were achieved in the internal validation set. Conclusions The current study demonstrates that MRI radiomics is able to predict molecular subgroups of PLGGs and KIAA1549-BRAF fusion with satisfying sensitivity. Trial registration This study was retrospectively registered at clinicaltrials.gov (NCT04217018).

Over the past few decades, ultrahigh-performance concrete (UHPC) has been widely studied and applied because of its outstanding mechanical properties, such as its high strength and notable durability. However, because of its high cost and easy shrinkage cracking during early pouring in mass concrete construction, to reduce the cost of UHPC and reduce the cracks caused by early pouring, volcanic stone was used as a new type of UHPC coarse aggregate, while metakaolin (MK) was added to the system at the same time, and then two parameters, namely the volcanic rock particle size group and the MK dispersion ratio, were set. Scanning electron microscopy (SEM), X-ray diffraction (XRD) and thermogravimetric (TG) microanalysis methods were used to reveal the influence of changes in the material microstructure, phase composition, material composition and crystallinity of the mineral composition on the compressive properties of the UHPC cubes. The results show that the mechanical “lock-in effect” of the structure formed by the volcanic rock holes and mortar can effectively improve the shear resistance of the UHPC–volcanic rock interface, and the compressive strength of the UHPC cubes increases with the volcanic stone’s particle size. When the MK dispersion ratio is less than 4%, the cube compressive strength of the UHPC and the contents of CaCO3 crystals, C-S-H gel and travertine in the UHPC increase with an increasing MK dispersion ratio. At an age of 28 days, compared with the addition of 1% MK, the addition of 4% MK increases the production of C-S-H gel and travertine in the UHPC matrix by 24.82%. When the MK dispersion ratio is 4%, the crystallinity values of the C-S-H gel, travertine and limestone in the UHPC are greater. Adding MK at a 4% dispersion ratio can promote the crystallization of limestone into a large amount of calcite, which can increase the strength of UHPC. On the one hand, the addition of volcanic coarse aggregate results in the retention of more free water and bound water; on the other hand, it also makes it difficult to crystallize CaCO3. The combined action of MK at a 4% dispersion ratio and volcanic rock significantly inhibits CaCO3 crystallization.

Metal-oxide-based gas sensors are extensively utilized across various domains due to their cost-effectiveness, facile fabrication, and compatibility with microelectronic technologies. The copper (Cu)-based multifunctional polymer-enhanced sensor (CuMPES) represents a notably tailored design for non-invasive environmental monitoring, particularly for detecting diverse gases with a low concentration. In this investigation, the Cu-CuO/PEDOT nanocomposite was synthesized via a straightforward chemical oxidation and vapor-phase polymerization. Comprehensive characterizations employing X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), X-ray diffraction (XRD), and micro Raman elucidated the composition, morphology, and crystal structure of this nanocomposite. Gas-sensing assessments of this CuMPES based on Cu-CuO/PEDOT revealed that the response current of the microneedle-type CuMPES surpassed that of the pure Cu microsensor by nearly threefold. The electrical conductivity and surface reactivity are enhanced by poly (3,4-ethylenedioxythiophene) (PEDOT) polymerized on the CuO-coated surface, resulting in an enhanced sensor performance with an ultra-fast response/recovery of 0.3/0.5 s.

The BeiDou Navigation Satellite System (BDS) has developed rapidly, and the combination of BDS Phase II (BDS-2) and BDS Phase III (BDS-3) has attracted wide attention. It is found that there are code ISBs between BDS-2 and BDS-3, which may have a certain impact on the BDS-2 and BDS-3 combined positioning. This paper focuses on the performance of BDS-2/BDS-3 combined B1I single-frequency pseudorange positioning and investigates the positioning performance with and without code ISBs correction for different types of receivers, include geodetic GNSS receivers and low-cost receivers. The results show the following: (1) For geodetic GNSS receivers, the code ISBs of each receiver is about −0.3 m to −0.8 m, and the position deviation is reduced by 7% after correcting code ISBs. The code ISBs in the baseline with homogeneous receivers has a little influence on the positioning result, which can be ignored. The code ISBs in the baseline with heterogeneous receivers is about −0.5 m, and the position deviation is reduced by 4% after correcting code ISBs. (2) The code ISBs in the low-cost receivers are significantly larger than those in the geodetic GNSS receivers, and the impact on the positioning performance of the low-cost receivers is significantly greater than that on the geodetic GNSS receivers. After correcting the code ISBs, the position deviation of low-cost receivers can be reduced by around 12% for both undifferenced and differenced modes. (3) For low-cost receivers, correcting the code ISBs can increase the number of epochs successfully solved, which effectively improves the low-cost navigation and positioning performance. (4) The carrier-phase-smoothing method can effectively reduce the distribution dispersion of code ISBs and make the estimation of ISBs more accurate. The STD values of estimated code ISBs in geodetic GNSS receivers are reduced by about 40% after carrier-phase smoothing, while the corresponding values are reduced by about 7% in low-cost receivers due to their poor carrier-phase observation quality.

In the field of biomechanics, customizing complex strain fields according to specific requirements poses an important challenge for bioreactor technology, primarily due to the intricate coupling and nonlinear actuation of actuator arrays, which complicates the precise control of strain fields. This paper introduces a bioreactor designed with a 9 × 9 array of independently controllable dielectric elastomer actuators (DEAs), addressing this challenge. We employ image regression-based machine learning for both replicating target strain fields through inverse control and rapidly predicting feasible strain fields generated by the bioreactor in response to control inputs via forward control. To generate training data, a finite element analysis (FEA) simulation model was developed. In the FEA, the device was prestretched, followed by the random assignment of voltages to each pixel, yielding 10,000 distinct output strain field images for the training set. For inverse control, a multilayer perceptron (MLP) is utilized to predict control inputs from images, whereas, for forward control, MLP maps control inputs to low-resolution images, which are then upscaled to high-resolution outputs through a super-resolution generative adversarial network (SRGAN). Demonstrations include inputting biomechanically significant strain fields, where the method successfully replicated the intended fields. Additionally, by using various tumor–stroma interfaces as inputs, the bioreactor demonstrated its ability to customize strain fields accordingly, showcasing its potential as an advanced testbed for tumor biomechanics research.

This study aimed to introduce a novel technique for producing straw fiber cement-based composites from wheat and corn straws. The research analyses the engineering characteristics, including compressive and flexural strengths, water absorption capacity, dry density, porosity, and thermal properties of the wheat and corn straw fiber cementitious composite (WCSFCC) mixtures. The hydration performance and compactness of WCSFCC mixes were described using XRD, SEM, and EDS analyses. The results show that the dosage of NaOH solution is the optimal approach for enhancing the surface of straw fibers and facilitating their effective integration with the cement matrix. The straw powder incineration method leads the straw ash particles to have a specific surface area 9.6 times higher than straw powder. The findings indicated that WCSFCC mixes with untreated straw powder had an optimal compressive strength ranging from 2.85 MPa to 3.79 MPa and corresponding thermal conductivity between 0.147 and 0.162 W/(m·K). Adopting the straw ash increased the compressive strength considerably. The analysis of WCSFCC mechanical properties and thermal conductivity with physical properties reveals a strong correlation between the mechanical properties and dry density, as well as thermal conductivity and dry density. However, the increasing porosity and water absorption capacity have compromised the mechanical properties and thermal conductivity of WCSFCC. The findings of this research may enhance the overall use of wheat and corn straw fibers. The manufacturing process of WCSFCC is simple, conducive to widespread use, and ecologically friendly.

Highlights Optimizing the current collectors with rGO and the addition of CNT in PPy, and the structural pulverization is prevented significantly. Areal capacitances of 65.9 to 70 mF cm−2 are achieved for PPy-CNT@rGO microsupercapacitors (MSCs) with 79% capacitance retention after 10,000 cycles. The MSC-derived capacitive micro-strain sensor is capable of biosignals detection. The micro strain sensor is capable of detecting wide levels of applied strain with short response/recovery time and excellent reliability.

In this paper, we combine the U-net-based phase picking method (PhaseNet) with Graphics Processing Unit-Based Match and Locate technology (GPU-M&L) and a deep-learning-based seismic signal de-noising method (DeepDenoiser) as a workflow for automatically extracting micro-seismic information from continuous raw seismic data. PhaseNet is first used to detect missed seismic phases by scanning through the 5-year continuous waveform data recorded at five broad-band stations in Hainan province. Then Rapid Earthquake Association and Location method (REAL), VELEST program (1-D inversion of velocities and hypocenter locating) and HypoDD (a double-difference locating method) are applied to associate seismic phases with events and to locate, respectively. This initially established catalogue can be served as the template for the following match-filter work. We choose events with a high signal-to-noise ratio (SNR) as templates and apply GPU-M&L to detect more small earthquakes which are difficult to pick by routine methods due to the low SNR. Then, a deep learning-based noise reduction technique named DeepDenoiser is applied to extract seismic signal from noise to provide a better picking of arrival time and then to improve the relocation effects. Finally, we use HypoDD to relocate these events with P- and S- wave arrival times picked by PhaseNet. Compared with the five events listed in the China Earthquake Networks Center routine catalogue, in this study, we detect and locate 977 earthquakes by following the above procedure. Our relocation results illustrate quite a complex distribution pattern of events due to the complicated fault system in the northeastern part of Hainan Province.

TGF-β can function to increase Treg cell function and reduce anti-tumour immunity. Here the authors show that UDCA is a potential mediator that can reduce TGF-β activity and promote anti-tumour immune responses in mice and can be additive to other checkpoint inhibitors.

BackgroundCoronavirus disease 2019 (COVID-19) and inflammatory bowel disease (IBD) are both caused by a disordered immune response and have direct and profound impacts on health care services. In this study, we implemented transcriptomic and single-cell analysis to detect common molecular and cellular intersections between COVID-19 and IBD that help understand the linkage of COVID-19 to the IBD patients.MethodsFour RNA-sequencing datasets (GSE147507, GSE126124, GSE9686 and GSE36807) from Gene Expression Omnibus (GEO) database are extracted to detect mutual differentially expressed genes (DEGs) for IBD patients with the infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to find shared pathways, candidate drugs, hub genes and regulatory networks. Two single-cell RNA sequencing (scRNA-eq) datasets (GSE150728, PRJCA003980) are used to analyze the immune characteristics of hub genes and the proportion of immune cell types, so as to find common immune responses between COVID-19 and IBD.ResultsA total of 121 common DEGs were identified among four RNA-seq datasets, and were all involved in the functional enrichment analysis related to inflammation and immune response. Transcription factors-DEGs interactions, miRNAs-DEGs coregulatory networks, and protein-drug interactions were identified based on these datasets. Protein-protein interactions (PPIs) was built and 59 hub genes were identified. Moreover, scRNA-seq of peripheral blood monocyte cells (PBMCs) from COVID-19 patients revealed a significant increase in the proportion of CD14+ monocytes, in which 38 of 59 hub genes were highly enriched. These genes, encoding inflammatory cytokines, were also highly expressed in inflammatory macrophages (IMacrophage) of intestinal tissues of IBD patients.ConclusionsWe conclude that COVID-19 may promote the progression of IBD through cytokine storms. The candidate drugs and DEGs-regulated networks may suggest effective therapeutic methods for both COVID-19 and IBD.