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Abstract Background To evaluate the effect of the single energy metal artifact reduction (SEMAR) algorithm with a multidetector CT (MDCT) for knee tumor prostheses. Methods First, a phantom of knee tumor prosthesis underwent a MDCT scan. The raw data was reconstructed by iterative reconstruction (IR) alone and IR plus SEMAR. The mean value of the CT number and the image noise were measured around the prosthesis at the stem level and articular level. Second, 95 consecutive patients with knee tumor prostheses underwent MDCT scans. The raw data were also reconstructed by the two methods. Periprosthetic structures were selected at the similar two levels. Four radiologists visually graded the image quality on a scale from 0 to 5. Additionally, the readers also assessed the presence of prosthetic complication and tumor recurrence on a same scale. Results In the phantom, when the SEMAR was used, the CT numbers were closer to normal value and the noise of images using soft and sharper kernel were respectively reduced by up to 77.1% and 43.4% at the stem level, and by up to 82.2% and 64.5% at the articular level. The subjective scores increased 1 ~ 3 points and 1 ~ 4 points at the two levels, respectively. Prosthetic complications and tumor recurrence were diagnosed in 66 patients. And the SEMAR increased the diagnostic confidence of prosthetic complications and tumor recurrence (4 ~ 5 vs. 1 ~ 1.5). Conclusions The SEMAR algorithm can significantly reduce the metal artifacts and increase diagnostic confidence of prosthetic complications and tumor recurrence in patients with knee tumor prostheses.

Osteosarcoma is a highly aggressive cancer common in children and adolescents. There is still a lack of effective treatments for metastatic or recurrent osteosarcoma. The role of long non-coding RNAs (lncRNAs) in osteosarcoma has gradually attracted attention. Here, we identified lncRNAs that were abnormally expressed in metastatic osteosarcoma through analyzing the sequencing data of osteosarcoma tissues and selected upregulated lncRNA MELTF-AS1 for detailed study. The qRT-PCR analysis showed that the expression of MELTF-AS1 was increased in osteosarcoma tissues and cells, and the high expression of MELTF-AS1 indicated a poor prognosis of osteosarcoma patients. The high expression of MELTF-AS1 in osteosarcoma was partly due to the transcriptional activation of RREB1. The results of transwell assays, scratch wound healing assays, and the tail vein injection lung metastasis model demonstrated that knocking down MELTF-AS1 inhibited metastasis ability of osteosarcoma cells. Furthermore, the results of RNA pull-down assays, luciferase reporter assays, and RNA immunoprecipitation (RIP) assays revealed that MELTF-AS1 could regulate MMP14 expression through interaction with miR-485-5p. Our study suggested that MELTF-AS1 functioned as a pro-metastasis gene in osteosarcoma by upregulating MMP14 and that it could be a potential therapeutic and diagnostic target for osteosarcoma.

Spinel oxide NiCo2O4 is introduced as an emerging material for photocatalytic oxygen precipitating catalysts. The NiCo2O4 hollow spheres prepared using the template method combine a large specific surface area with high electrical conductivity and exhibit excellent catalytic properties. Building on this significant improvement, our research aims to enhance the photoelectrochemical performance of Mo,W: BVO/NiCo2O4 heterojunctions by integrating hollow NiCo2O4 during BiVO4 fabrication, thereby improving the charge transfer and water oxidation kinetics of Mo,W:BVO/NiCo2O4 photoanodes. Additionally, the deposition of Ag as a middle layer prevents oxidation issues during the PEC process, resulting in the most significant enhancement of photocurrent. Compared to a reversible hydrogen electrode, the obtained photoanodes achieve a photocurrent density of 5.30 mA cm-2 at 1.23 V vs. RHE. Through experimental and theoretical demonstrations, our work provides novel insights into modifying BiVO4 photoanodes using oxygen precipitating catalysts and noble metals to improve their photoelectrochemical performance. [ABSTRACT FROM AUTHOR]

As the core component of the flow-making system, the circulating pump has differences in its internal flow structure under different operating conditions, which affects the flow quality of the environmental simulation test area and the authenticity of marine environmental simulation. To explore the internal flow characteristics and outlet evolution characteristics of the circulating pump, this paper uses the DDES (delayed detached eddy simulation) method for numerical simulation. This paper combines BVF (boundary vorticity flow) diagnosis and the limit streamline method to analyze the evolution characteristics of the unstable flow area on the blade surface; it uses the Q criterion to identify the vortex structure inside the pump and analyze its evolution and development laws. Additionally, a quantitative analysis of the flow state of the circulating pump using flow uniformity indexes is performed. The results show that the surface of impeller blades is uniform under 1.0 QN. At 0.7 QN, the evolution process of the blade suction surface BVF is periodic, with a corresponding period of about 2/9 T (0.02 s). At 1.0 QN, the strength and scale of the separated vortices inside the guide vanes are minimized compared to other flow rates, and the scale and strength of the vortices show a decreasing trend along the outer normal direction. The evolution period of the separation vortex on the pressure surface of the guide vane is about 1/3 T (0.033 s) under 1.1 QN and the evolution period of the suction surface of the guide vane is about 2/3 T (0.067 s) under 0.7 QN. The flow uniformity indexes value downstream of the pump outlet under 1.0 QN are very close to the ideal value; with a corresponding value of Ϛi = 0.023, θ¯ = 89.94°, γ = 0.95, λ = 97.9%, the outflow can be approximately regarded as axial uniform flow. The research results can provide theoretical support for the further optimization design of circulating pumps and lay the foundation for the implementation of real systems.

Extracting roads from remote sensing images is of significant importance for automatic road network updating, urban planning, and construction. However, various factors in complex scenes (e.g., high vegetation coverage occlusions) may lead to fragmentation in the extracted road networks and also affect the robustness of road extraction methods. This study proposes a multi-scale road extraction method with asymmetric generative adversarial learning (MS-AGAN). First, we design an asymmetric GAN with a multi-scale feature encoder to better utilize the context information in high-resolution remote sensing images (HRSIs). Atrous spatial pyramid pooling (ASPP) and feature fusion are integrated into the asymmetric encoder–decoder structure to avoid feature redundancy caused by multi-level cascading operations and enhance the generator network’s ability to extract fine-grained road information at the pixel level. Second, to maintain road connectivity, topologic features are considered in the pixel segmentation process. A linear structural similarity loss (LSSIM) is introduced into the loss function of MS-AGAN, which guides MS-AGAN to generate more accurate segmentation results. Finally, to fairly evaluate the performance of deep models under complex backgrounds, the Bayesian error rate (BER) is introduced into the field of road extraction for the first time. Experiments are conducted via Gaofen-2 (GF-2) high-resolution remote sensing images with high vegetation coverage in the Daxing District of Beijing, China, and the public DeepGlobe dataset. The performance of MS-AGAN is compared with a list of advanced models, including RCFSNet, CoANet, UNet, DeepLabV3+, and DiResNet. The final results show that (1) with respect to road extraction performance, the Recall, F1, and IoU values of MS-AGAN on the Daxing dataset are 2.17%, 0.04%, and 2.63% higher than the baselines. On DeepGlobe, the Recall, F1, and IoU of MS-AGAN improve by 1.12%, 0.42%, and 0.25%, respectively. (2) On road connectivity, the Conn index of MS-AGAN from the Daxing dataset is 46.39%, with an improvement of 0.62% over the baselines, and the Conn index of MS-AGAN on DeepGlobe is 70.08%, holding an improvement of 1.73% over CoANet. The quantitative and qualitative analyses both demonstrate the superiority of MS-AGAN in preserving road connectivity. (3) In particular, the BER of MS-AGAN is 20.86% over the Daxing dataset with a 0.22% decrease compared to the best baselines and 11.77% on DeepGlobe with a 0.85% decrease compared to the best baselines. The proposed MS-AGAN provides an efficient, cost-effective, and reliable method for the dynamic updating of road networks via HRSIs.

In the original publication [...]

We established an experimental apparatus by combining polarized light scattering and angle-resolved light scattering measurement technology to rapidly identify the shape of an individual aerosol particle. The experimental data of scattered light of Oleic acid, rod-shaped Silicon dioxide, and other particles with typical shape characteristics were analyzed statistically. To better study the relationship between the shape of particles and the properties of scattered light, the partial least squares discriminant analysis (PLS-DA) method was used to analyze the scattered light of aerosol samples based on the size screening of particles, and the shape recognition and classification method of the individual aerosol particle was established based on the analysis of the spectral data after nonlinear processing and grouping by particle size with the area under the receiver operating characteristic curve (AUC) as reference. The experimental results show that the proposed classification method has a good discrimination ability for spherical, rod-shaped, and other non-spherical particles, which can provide more information for atmospheric aerosol measurement, and has application value for traceability and exposure hazard assessment of aerosol particles.

Breast cancer is the most prevalent cancer in the world. Currently, the main treatments for breast cancer are radiotherapy, chemotherapy, targeted therapy and surgery. The treatment measures for breast cancer depend on the molecular subtype. Thus, the exploration of the underlying molecular mechanisms and therapeutic targets for breast cancer remains a hotspot in research. In breast cancer, a high level of expression of DNMTs is highly correlated with poor prognosis, that is, the abnormal methylation of tumor suppressor genes usually promotes tumorigenesis and progression. MiRNAs, as non-coding RNAs, have been identified to play key roles in breast cancer. The aberrant methylation of miRNAs could lead to drug resistance during the aforementioned treatment. Therefore, the regulation of miRNA methylation might serve as a therapeutic target in breast cancer. In this paper, we reviewed studies on the regulatory mechanisms of miRNA and DNA methylation in breast cancer from the last decade, focusing on the promoter region of tumor suppressor miRNAs methylated by DNMTs and the highly expressed oncogenic miRNAs inhibited by DNMTs or activating TETs.

Monitoring global greenhouse gas concentration information via satellite remote sensing has become a critical area of research to support the further understanding of global carbon emissions. The Greenhouse-gases Absorption Spectrometer-2 (GAS-2) is being developed as the primary payload of the Fengyun-3H (FY-3H), which will be launched in 2024. Achieving high-precision mesurements of greenhouse gases requires precise spectral calibration. However, currently, there is no method for assessing the detection accuracy of GAS-2 using spectral calibration light sources, and quantitative studies are lacking. In this study, the influence model of calibration light sources on spectral calibration accuracy is established, and the spectral radiance acquired via GAS-2 is simulated using the line-by-line radiative transfer model (LBLRTM). We investigated the impact of different linewidths and wavelength stabilities of the calibration light source on its accuracy in four wavelength bands. This study is the first to examine the effects of the linewidth and wavelength stability of a calibration light source on the spectral radiance acquired via GAS-2. The initial results demonstrate that if the linewidth of the calibration light source is approximately 100 MHz and the wavelength stability is in the order of subpicometers, the radiance error obtained by GAS-2 is less than 10%. Among the four bands, the 2.06 μm (strong-CO2) band is more affected by the calibration light source than the other three bands. In addition, the wavelength stability of the light source has a greater influence on the error than the linewidth of the light source under the same error condition. The research findings can be used to guide and reference the selection of light sources in the laboratory spectral calibration of GAS-2, ultimately contributing to the instrument’s quantitative development level.

Abstract With the widespread use of PD‐1/PD‐L1 monoclonal antibodies (mAbs) in the treatment of multiple malignant tumors, they were also gradually applied to advanced renal cell carcinoma (aRCC). Nowadays, multiple PD‐1/PD‐L1 mAbs, such as nivolumab, avelumab, and pembrolizumab, have achieved considerable efficacy in clinical trials. However, due to the primary, adaptive, and acquired resistance to these mAbs, the efficacy of this immunotherapy is not satisfactory. Theories also vary as to why the difference in efficacy occurs. The alterations of PD‐L1 expression and the interference of cellular immunity may affect the efficacy. These mechanisms demand to be revealed to achieve a sustained and complete objective response in patients with aRCC. Tyrosine kinase inhibitors have been proven to have synergistic mechanisms with PD‐1/PD‐L1 mAb in the treatment of aRCC, and CTLA‐4 mAb has been shown to have a non‐redundant effect with PD‐1/PD‐L1 mAb to enhance efficacy. Although combinations with targeted agents or other checkpoint mAbs have yielded enhanced clinical outcomes in multiple clinical trials nowadays, the potential of PD‐1/PD‐L1 mAbs still has a large development space. More potential mechanisms that affect the efficacy demand to be developed and transformed into the clinical treatment of aRCC to search for possible combination regimens. We elucidate these mechanisms in RCC and present existing combination therapies applied in clinical trials. This may help physicians’ select treatment options for patients with refractory kidney cancer.

Toroidal moments arise from vortex like spin arrangements. These moments can then interact, giving rise to ferri- or ferro-toroidal order, though controlling such order is difficult. Here, the authors demonstrate a ferri-toroidal state in BaCoSiO4, which under an applied magnetic field exhibits multiple toroidal and metamagnetic transitions.

Abstract Ecosystem imbalance is often associated with a feedback mechanism, which a self‐amplifying or ‐dampening process expressed by a pathway of causal processes that come back to its starting point, establishing a cycle. Warming, which is increasing worldwide due to human activities, influences the structure and functioning of ecosystems, has threatened sustainable regional and global development, especially over the mountain regions. This is because, the climatic condition rapidly changes along elevation gradients, which may amplify or mitigate the effects of climate on ecosystems. Based on it, a reference system and standardized techniques are extremely important to understand the ecosystem imbalance. Because of terrestrial oxygen production (TOP), which is the terrestrial biosphere continually absorbs CO2 and releases O2 resulting through vegetation photosynthesis, is closely related to the exchange of energy, carbon and other ecosystem factors between the atmosphere and the land. Therefore, whether TOP significantly increases indicate that accelerate in ecosystem imbalance over the Tibetan Plateau (TP) is largely unknown. To do so, integrated with characteristics and drivers of TOP, we investigated how TOP changes respond to ecosystem imbalance over the TP. These changes are influenced by related to climatic conditions, plant productivity, soil fertility, and microbial stability, which can establish a positive feedback loop that standardized direct effect is 0.99, 0.73, 0.75, and 0.75. Our findings suggest that ecosystem imbalance will accelerate with rapid TOP increase over the TP by ∼2,100. This study confirms the importance of the ecosystem imbalance under global warming in the future.

Abstract Background An unexplained pneumonia occurred in Wuhan, China in December 2019, later identified and named coronavirus disease 2019 (COVID‐19). This study aimed to compare the ultrasonographic features of the lung between patients with COVID‐19 in Wuhan (the primary region) and those in Beijing (the secondary region) and to find the value of applying ultrasound in COVID‐19. Methods A total of 248 COVID‐19 cases were collected, including long‐term residents in Wuhan (138), those who had a short‐term stay in Wuhan (72), and those who had never visited Wuhan (38). Ultrasound examination was performed daily; the highest lung ultrasound score (LUS) was the first comparison point, while the LUS of the fifth day thereafter was the second comparison point. The differences between overall treatment and ultrasonography of left and right lungs among groups were compared. Results The severity decreased significantly after treatment. The scores of the groups with long‐term residence and short‐term stay in Wuhan were higher than those of the group that had never been to Wuhan. Conclusion Ultrasonography is effective for dynamic monitoring of COVID‐19. The ultrasonographic features of patients in the Wuhan area indicated relatively severe disease. Thus, Wuhan was the main affected area of china.

Brain-wide patterns in resting human brains, as either structured functional connectivity (FC) or recurring brain states, have been widely studied in the neuroimaging literature. In particular, resting-state FCs estimated over windowed timeframe neuroimaging data from sub-minutes to minutes using correlation or blind source separation techniques have reported many brain-wide patterns of significant behavioral and disease correlates. The present pilot study utilized a novel whole-head cap-based high-density diffuse optical tomography (DOT) technology, together with data-driven analysis methods, to investigate recurring transient brain-wide patterns in spontaneous fluctuations of hemodynamic signals at the resolution of single timeframes from thirteen healthy adults in resting conditions. Our results report that a small number, i.e., six, of brain-wide coactivation patterns (CAPs) describe major spatiotemporal dynamics of spontaneous hemodynamic signals recorded by DOT. These CAPs represent recurring brain states, showing spatial topographies of hemispheric symmetry, and exhibit highly anticorrelated pairs. Moreover, a structured transition pattern among the six brain states is identified, where two CAPs with anterior-posterior spatial patterns are significantly involved in transitions among all brain states. Our results further elucidate two brain states of global positive and negative patterns, indicating transient neuronal coactivations and co-deactivations, respectively, over the entire cortex. We demonstrate that these two brain states are responsible for the generation of a subset of peaks and troughs in global signals (GS), supporting the recent reports on neuronal relevance of hemodynamic GS. Collectively, our results suggest that transient neuronal events (i.e., CAPs), global brain activity, and brain-wide structured transitions co-exist in humans and these phenomena are closely related, which extend the observations of similar neuronal events recently reported in animal hemodynamic data. Future studies on the quantitative relationship among these transient events and their relationships to windowed FCs along with larger sample size are needed to understand their changes with behaviors and diseased conditions.

Spontaneous neural activity in human as assessed with resting-state functional magnetic resonance imaging (fMRI) exhibits brain-wide coordinated patterns in the frequency of

Osteoarthritis (OA) is a common degenerative joint disease. Effective drugs that can halt or decelerate osteoarthritis progression are still lacking. Omaveloxolone is a semisynthetic oleanane triterpenoid exerting antioxidative and anti-inflammatory effects. The present study aims to determine whether omaveloxolone has a therapeutic effect on OA. Chondrocytes were treated with interleukin (IL)-1β to establish an OA cell model in vitro. Indicators of cell viability, oxidative stress, inflammation, cell apoptosis and extracellular matrix (ECM) degradation were investigated. Proteins related to the Nuclear factor erythroid derived-2-related factor 2 (Nrf2)/antioxidant response element (ARE) and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) signalling pathways were assessed using Western blotting. A destabilized medial meniscus surgery-induced OA rat model was used in vivo. Gait analysis, microcomputed tomography analysis, and histopathological and immunohistochemical analyses were performed to determine the therapeutic effect of omaveloxolone on attenuating osteoarthritis in vivo. The results showed that omaveloxolone exerts antioxidative, anti-inflammatory, antiapoptotic and anti-ECM degradation effects via activation of the Nrf2/ARE signalling pathway and inhibition of the NF-κB signalling pathway in chondrocytes in vitro and attenuates OA progression in vivo, suggesting that omaveloxolone may be a potential therapeutic agent for OA.

Metabolic reprogramming is one of the characteristics of clear cell renal cell carcinoma (ccRCC). Although some treatments associated with the metabolic reprogramming for ccRCC have been identified, remain still lacking. In this study, we identified the differentially expressed genes (DEGs) associated with clinical traits with a total of 965 samples via DEG analysis and weighted correlation network analysis (WGCNA), screened the prognostic metabolism-related genes, and constructed the risk score prognostic models. We took the intersection of DEGs with significant difference coexpression modules and received two groups of intersection genes that were connected with metabolism via functional enrichment analysis. Then we respectively screened prognostic metabolic-related genes from the genes of the two intersection groups and constructed the risk score prognostic models. Compared with the predicted effect of clinical grade and stage for ccRCC patients, finally, we selected the model constructed with genes of ABAT, ALDH6A1, CHDH, EPHX2, ETNK2, and FBP1. The risk scores of the prognostic model were significantly related to overall survival (OS) and could serve as an independent prognostic factor. The Kaplan-Meier analysis and ROC curves revealed that the model efficiently predicts prognosis in the TCGA-KIRC cohort and the validation cohort. Then we investigated the potential underlying mechanism and sensitive drugs between high- and low-risk groups. The six key genes were significantly linked with worse OS and were downregulated in ccRCC, we confirmed the results in clinical samples. These results demonstrated the efficacy and robustness of the risk score prognostic model, based on the characteristics of metabolic reprogramming in ccRCC, and the key genes used in constructing the model also could develop into targets of molecular therapy for ccRCC.

Cuproptosis is a novel form of cell death, correlated with the tricarboxylic acid (TCA) cycle. However, the metabolic features and the benefit of immune checkpoint inhibitor (ICI) therapy based on cuproptosis have not yet been elucidated in Hepatocellular carcinoma (HCC). First, we identified and validated three cuproptosis subtypes based on 10 cuproptosis-related genes (CRGs) in HCC patients. We explored the correlation between three cuproptosis subtypes and metabolism-related pathways. Besides, a comprehensive immune analysis of three cuproptosis subtypes was performed. Then, we calculated the cuproptosis-related gene prognostic index (CRGPI) score for predicting prognosis and validated its predictive capability by Decision curve analysis (DCA). We as well explored the benefit of ICI therapy of different CRGPI subgroups in two anti-PD1/PD-L1 therapy cohorts (IMvigor210 cohort and GSE176307). Finally, we performed the ridge regression algorithm to calculate the IC50 value for drug sensitivity and Gene set enrichment analysis (GSEA) analysis to explore the potential mechanism. We found that cluster A presented a higher expression of FDX1 and was correlated with metabolism, glycolysis, and TCA cycle pathways, compared with the other two clusters. HCC patients with high CRGPI scores had a worse OS probability, and we further found that the CRGPI-high group had high expression of PD1/PDL1, TMB, and better response (PR/CR) to immunotherapy in the IMvigor210 cohort and GSE176307. These findings highlight the importance of CRGPI serving as a potential biomarker for both prognostic and immunotherapy for HCC patients. Generally, our results provide novel insights about cuproptosis into immune therapeutic strategies.

Abstract Background Colorectal cancer (CRC) is a common malignant tumour of the digestive tract that is characterized by high patient morbidity and mortality rates. Claudin-7 (Cldn7), a tight junction protein, was recently reported to function as a candidate tumour suppressor gene in CRC. Our previous study demonstrated that the large intestine of C57/BL6 mice showed intestinal adenomas and abnormal Ki67 expression and distribution in the intestinal crypt when Cldn7 was knocked out. The aim of this study was to further investigate whether Cldn7 deficiency has non-tight junction functions, affects intestinal stemness properties, promotes CRC and to determine the specific mechanism. Methods Cell proliferation assays, migration assays, apoptosis assays, tumour sphere formation assays in vitro, and subcutaneous xenograft models in vivo were used to determine the effects of Cldn7 knockdown on the biological characteristics of CRC stem cells. Western blotting, qPCR and immunofluorescence staining were performed to identify the epithelial-mesenchymal transition and the activation of Wnt/β-catenin pathway in CRC stem cells. Cldn7 inducible conditional gene knockout mice and immunohistochemical staining further verified this hypothesis in vivo. The mechanism and target of Cldn7 were determined by performing a chromatin immunoprecipitation (ChIP) assay and coimmunoprecipitation (CoIP) assay. Results Cldn7 knock down in CRC stem cells promoted cell proliferation, migration, and globular growth in serum-free medium and the ability to form xenograft tumours; cell apoptosis was inhibited, while the cellular epithelial-mesenchymal transition was also observed. These changes in cell characteristics were achieved by activating the Wnt/β-catenin pathway and promoting the expression of downstream target genes after β-catenin entry into the nucleus, as observed in CRC cell lines and Cldn7 gene knockout mouse experiments. Using ChIP and CoIP experiments, we initially found that Cldn7 and Sox9 interacted at the protein level to activate the Wnt/β-catenin pathway. Conclusions Based on our research, Cldn7 deficiency confers stemness properties in CRC through Sox9-mediated Wnt/β-catenin signalling. This result clarifies that Cldn7 plays an inhibitory role in CRC and reveals a possible molecular mechanism, which is conducive to further research on Cldn7 and cancer stem cells.

Abstract Background This study aimed to assess the clinical usefulness of 13N-ammonia and 11C- Methionine (MET) positron emission tomography (PET)/ computed tomography (CT) in the differentiation of residual/recurrent pituitary adenoma (RPA) from the pituitary gland remnant (PGR) after trans-sphenoidal adenomectomy. Methods Between June 2012 and December 2019, a total of 19 patients with a history of trans-sphenoidal adenomectomy before PET/CT scans and histological confirmation of RPA after additional surgery in our hospital were enrolled in this study. Images were interpreted by visual evaluation and semi-quantitative analysis. In semi-quantitative analysis, the maximum standard uptake value (SUVmax) of the target and gray matter was measured and the target uptake/gray matter uptake (T/G) ratio was calculated. Results The T/G ratios of 13N-ammonia were significantly higher in PGR than RPA (1.58 ± 0.69 vs 0.63 ± 1.37, P

Abstract Background The objective of this study was to investigate the survival outcomes of surgical margin width in intrahepatic cholangiocarcinoma (ICC). Methods Between November 2011 and August 2017, patients who underwent hepatectomy for ICC were collected from 13 major hepatopancreatobiliary centers in China. The survival outcomes for patients who underwent wide margin hepatectomy (WMH) were compared with those who underwent narrow margin hepatectomy (NMH) using the 1:1 propensity score matching (PSM). Results Among 478 included patients, 195 (40.8%) underwent WMH whereas 283 (59.2%) underwent NMH. PSM yielded 79 matched patients with similar baseline characteristics. Patients underwent WMH had a significant better OS and DFS compared with those underwent NMH (before PSM: median OS 27 vs 17 months, P

Abstract Alternaria alternata, a causal agent of leaf blights and spots on a wide range of hosts, has a high risk of developing resistance to fungicides. Procymidone, a dicarboximide fungicide (DCF), has been widely used in controlling Alternaria leaf blights in China for decades. However, the resistance of A. alternata against DCFs has rarely been reported from crucifer plants. A total of 198 A. alternata isolates were collected from commercial fields of broccoli and cabbage during 2018–2019, and their sensitivities to procymidone were determined. Biochemical and molecular characteristics were subsequently compared between the high-level procymidone-resistant (ProHR) and procymidone-sensitive (ProS) isolates, and also between ProHR isolates from broccoli and cabbage. Compared with ProS isolates, the mycelial growth rate, sporulation capacity and virulence of most ProHR isolates were reduced; ProHR isolates displayed an increased sensitivity to osmotic stresses and a reduced sensitivity to sodium dodecyl sulfate (SDS); all ProHR isolates showed a reduced sensitivity to hydrogen peroxide (H2O2) except for the isolate B102. Correlation analysis revealed a positive cross-resistance between procymidone and iprodione, or fludioxonil. When treated with 10 μg/mL of procymidone, both mycelial intracellular glycerol accumulations (MIGAs) and relative expression of AaHK1 in ProS isolates were higher than those in ProHR isolates. Sequence alignment of AaHK1 from ten ProHR isolates demonstrated that five of them possessed a single-point mutation (P94A, V612L, E708K or Q924STOP), and four isolates had an insertion or a deletion in their coding regions. No significant difference in biochemical characteristics was observed among ProHR isolates from two different hosts, though mutations in AaHK1 of the cabbage-originated ProHR isolates were distinct from those of the broccoli-originated ProHR isolates.

A cordycipitoid fungus infecting Hepialidae sp. in Nepal was supposed to be identical to Cordyceps liangshanensis, originally described from southwestern China, and thus, transferred to the genus Metacordyceps or Papiliomyces in previous studies. However, our multi-gene (nrSSU-nrLSU-tef-1α-rpb1-rpb2) phylogenetic and morphological studies based on the type specimen and additional collections of C. liangshanensis revealed that the fungus belongs to the genus Ophiocordyceps (Ophiocordycipitaceae). Therefore, a new combination O. liangshanensis was made, and a detailed description of this species was provided.

Abstract Background The pine wood nematode (PWN), Bursaphelenchus xylophilus, is a devastating pathogen of many Pinus species in China. The aim of this study was to understand the interactive molecular mechanism of PWN and its host by comparing differentially expressed genes and candidate effectors from three transcriptomes of B. xylophilus at different infection stages. Results In total, 62, 69 and 46 candidate effectors were identified in three transcriptomes (2.5 h postinfection, 6, 12 and 24 h postinoculation and 6 and 15 d postinfection, respectively). In addition to uncharacterized pioneers, other candidate effectors were involved in the degradation of host tissues, suppression of host defenses, targeting plant signaling pathways, feeding and detoxification, which helped B. xylophilus survive successfully in the host. Seven candidate effectors were identified in both our study and the B. xylophilus transcriptome at 2.5 h postinfection, and one candidate effector was identified in all three transcriptomes. These common candidate effectors were upregulated at infection stages, and one of them suppressed pathogen-associated molecular pattern (PAMP) PsXEG1-triggered cell death in Nicotiana benthamiana. Conclusions The results indicated that B. xylophilus secreted various candidate effectors, and some of them continued to function throughout all infection stages. These various candidate effectors were important to B. xylophilus infection and survival, and they functioned in different ways (such as breaking down host cell walls, suppressing host defenses, promoting feeding efficiency, promoting detoxification and playing virulence functions). The present results provide valuable resources for in-depth research on the pathogenesis of B. xylophilus from the perspective of effectors.

A 1/3 scaled-down mock-up reactor of ACP100 was used to simulate the flow field in the prototype reactor and to carry out the experiment of core inlet flow distribution. In the mock-up reactor, the major flow path of the reactor is linearly scaled except for the core region which is replaced by 57 dummy fuel assemblies. In addition, the experiment measures core inlet flow rates by a specially designed turbine installed in each dummy fuel assembly. In the experiment, both four-loop balanced and unbalanced operating conditions are tested. The experimental results show that the flow in the major flow path of the mock-up reactor has entered the self-modeling zone and the flow field characteristics are the same as the prototype. The core inlet flow rates of different tests show similar distributions, which all meet the hydraulic performance requirements. Moreover, the effect of impeller rotation on the flow field of the core inlet has also been studied. The study indicates that the flow distribution is almost unaffected by the swirl flow.

Recent studies have emphasized the changes in large-scale brain networks related to healthy aging, with the ultimate purpose to aid in differentiating normal neurocognitive aging from neurodegenerative disorders that also arise with age. Emerging evidence from functional Magnetic Resonance Imaging (fMRI) indicates that connectivity patterns within specific brain networks, especially the Default Mode Network (DMN), distinguish those with Alzheimer's disease from healthy individuals. In addition, disruptive alterations in the large-scale brain systems that support high-level cognition are shown to accompany cognitive decline at the behavioral level, which is commonly observed in the aging populations, even in the absence of disease. Although fMRI is useful for assessing functional changes in brain networks, its high costs and limited accessibility discourage studies that need large populations. In this study, we investigated the aging-effect on large-scale networks of the human brain using high-density electroencephalography and electrophysiological source imaging, which is a less costly and more accessible alternative to fMRI. In particular, our study examined a group of healthy subjects in the age range from middle- to older-aged adults, which is an under-studied range in the literature. Employing a high-resolution computation model, our results revealed age associations in the connectivity pattern of DMN in a consistent manner with previous fMRI findings. Particularly, in combination with a standard battery of cognitive tests, our data showed that in the posterior cingulate / precuneus area of DMN higher brain connectivity was associated with lower performance on an episodic memory task. The findings demonstrate the feasibility of using electrophysiological imaging to characterize large-scale brain networks and suggest that changes in network connectivity are associated with normal aging.

Zinc is an essential micronutrient for plant growth and development, and functions as a cofactor for hundreds of transcription factors and enzymes in numerous biological processes. Zinc deficiency is common abiotic stress resulting in yield loss and quality deterioration of crops, but zinc excess causes toxicity for biological systems. In plants, zinc homeostasis is tightly modulated by zinc transporters and binding compounds that uptake/release, transport, localize, and store zinc, as well as their upstream regulators. Lazarus 1 (LAZ1), a member of DUF300 protein family, functions as transmembrane organic solute transporter in vertebrates. However, the function of LAZ1 in plants is still obscure. In the present study, the ZmLAZ1-4 protein was confirmed to bind to zinc ions by bioinformatic prediction and thermal shift assay. Heterologous expression of ZmLAZ1-4 in the zinc-sensitive yeast mutant, Arabidopsis, and maize significantly facilitated the accumulation of Zn2+ in transgenic lines, respectively. The result of subcellular localization exhibited that ZmLAZ1-4 was localized on the plasma and vacuolar membrane, as well as chloroplast. Moreover, the ZmLAZ1-4 gene was negatively co-expressed with ZmBES1/BZR1-11 gene through co-expression and real-time quantitative PCR analysis. The results of yeast one-hybrid and dual-luciferase assay suggested that ZmBES1/BZR1-11 could bind to ZmLAZ1-4 promoter to inhibit its transcription. All results indicated that ZmLAZ1-4 was a novel zinc transporter on plasma and vacuolar membrane, and transported zinc under negative regulation of the ZmBES1/BZR1-11 transcription factor. The study provides insights into further underlying the mechanism of ZmLAZ1-4 regulating zinc homeostasis.

Improving the digital economy and environmental governance efficiency are important methods for current high-quality economic development. Based on the panel data of 11 cities in Zhejiang, on the eastern coast of China, fine particulate matter smaller than a 2.5 μm (PM2.5) environmental efficiency (PMEE) was measured by the undesirable output Slack-Based Measure-Data Envelopment Analysis (SBM-DEA) model. The fixed effect regression model, the divergences in the difference model and other empirical methods were obtained to test the driving mechanism of social-economic factors on the PMEE. The results showed that: (1) the concentration of PM2.5 was continually decreasing, and environmental quality experienced a continuous improvement in Zhejiang province in the observation period, although cities such as Hangzhou, Jiaxing and Shaoxing have relatively severe PM2.5 pollution. (2) The total average value of PMEE in Zhejiang was 0.6430 over the observation period, while there was still a lot of room for improvement when compared to the production frontier. Additionally, PMEE in each city showed a fluctuating growth trend. Cities with a higher PMEE were mainly Zhoushan, Hangzhou and Ningbo. (3) The level of the digital economy had a positive role in promoting the PMEE, which was statistically significant. The level of pollution control and technological innovation also had a significantly positive effect. However, the ratio of the industrial output value to the gross domestic product (GDP) presented a negative effect on the PMEE. In the future, it is suggested that the development of the urban digital economy should be accelerated in an all-around way to improve the efficiency of government pollution control and to improve the technical efficiency of PM2.5 via innovative technological progress.

Diabetic Nephropathy (DN) is a serious complication of type I and II diabetes. It develops from the initial microproteinuria to end-stage renal failure. The main initiator for DN is chronic hyperglycemia. Hyperglycemia (HG) can stimulate the resident and non-resident renal cells to produce humoral mediators and cytokines that can lead to functional and phenotypic changes in renal cells and tissues, interference with cell growth, interacting proteins, advanced glycation end products (AGEs), etc., ultimately resulting in glomerular and tubular damage and the onset of kidney disease. Therefore, poor blood glucose control is a particularly important risk factor for the development of DN. In this paper, the types and mechanisms of DN cell damage are classified and summarized by reviewing the related literature concerning the effect of hyperglycemia on the development of DN. At the cellular level, we summarize the mechanisms and effects of renal damage by hyperglycemia. This is expected to provide therapeutic ideas and inspiration for further studies on the treatment of patients with DN.

Deep learning has achieved great success in remote sensing image change detection (CD). However, most methods focus only on the changed regions of images and cannot accurately identify their detailed semantic categories. In addition, most CD methods using convolutional neural networks (CNN) have difficulty capturing sufficient global information from images. To address the above issues, we propose a novel symmetric multi-task network (SMNet) that integrates global and local information for semantic change detection (SCD) in this paper. Specifically, we employ a hybrid unit consisting of pre-activated residual blocks (PR) and transformation blocks (TB) to construct the (PRTB) backbone, which obtains more abundant semantic features with local and global information from bi-temporal images. To accurately capture fine-grained changes, the multi-content fusion module (MCFM) is introduced, which effectively enhances change features by distinguishing foreground and background information in complex scenes. In the meantime, the multi-task prediction branches are adopted, and the multi-task loss function is used to jointly supervise model training to improve the performance of the network. Extensive experimental results on the challenging SECOND and Landsat-SCD datasets, demonstrate that our SMNet obtains 71.95% and 85.65% at mean Intersection over Union (mIoU), respectively. In addition, the proposed SMNet achieves 20.29% and 51.14% at Separated Kappa coefficient (Sek) on the SECOND and Landsat-SCD datasets, respectively. All of the above proves the effectiveness and superiority of the proposed method.

Milk spectral data on 2118 cows from nine herds located in northern China were used to access the association of days open (DO). Meanwhile, the parity and calving season of dairy cows were also studied to characterize the difference in DO between groups of these two cow-level factors. The result of the linear mixed-effects model revealed that no significant differences were observed between the parity groups. However, a significant difference in DO exists between calving season groups. The interaction between parity and calving season presented that primiparous cows always exhibit lower DO among all calving season groups, and the variation in DO among parity groups was especially clearer in winter. Survival analysis revealed that the difference in DO between calving season groups might be caused by the different P/AI at the first TAI. In addition, the summer group had a higher chance of conception in the subsequent services than other groups, implying that the micro-environment featured by season played a critical role in P/AI. A weak linkage between DO and wavenumbers ranging in the mid-infrared region was detected. In summary, our study revealed that the calving season of dairy cows can be used to optimize the reproduction management. The potential application of mid-infrared spectroscopy in dairy cows needs to be further developed.