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Abstract Immunotherapy successfully complements traditional cancer treatment. However, primary and acquired resistance might limit efficacy. Reduced antigen presentation by MHC-I has been identified as potential resistance factor. Here we show that the epigenetic regulator ubiquitin-like with PHD and ring finger domains 1 (UHRF1), exhibits altered expression and aberrant cytosolic localization in cancerous tissues, where it promotes MHC-I ubiquitination and degradation. Cytoplasmic translocation of UHRF1 is induced by its phosphorylation on a specific serine in response to signals provided by factors present in the tumor microenvironment (TME), such as TGF-β, enabling UHRF1 to bind MHC-I. Downregulation of MHC-I results in suppression of the antigen presentation pathway to establish an immune hostile TME. UHRF1 inactivation by genetic deletion synergizes with immune checkpoint blockade (ICB) treatment and induces an anti-tumour memory response by evoking low-affinity T cells. Our study adds to the understanding of UHRF1 in cancer immune evasion and provides a potential target to synergize with immunotherapy and overcome immunotherapeutic resistance.

Current analysis of fragile bronzes mainly relies on the research of two-dimensional aspects such as sample cross-sections and surfaces while typically utilizing optical and electronic microscopy, Raman spectroscopy, and X-ray fluorescence spectroscopy (XRF). As a fast and nondestructive testing method, computer tomography (CT) can be used to characterize and detect the internal structures, corrosion conditions, and corrosion distribution of bronzes. This study used the CT imaging results of fragile bronzes to analyze, locate, and measure corrosion in fragile bronzes quickly and accurately, thus providing strong support for corrosion evaluation and protection research of fragile bronzes. The results verified the value and application prospects of CT technology in the protection of cultural relics.

Soil salinization and water scarcity are main restrictive factors for irrigated agriculture development in arid regions. Knowing dynamics of soil water and salt content is an important antecedent in remediating salinized soils and optimizing irrigation management. Previous studies mostly used remote sensing technologies to individually monitor water or salt content dynamics in agricultural areas. Their ability to asses different levels of crop water and salt management has been less explored. Therefore, how to extract effective diagnostic features from remote sensing images derived spectral information is crucial for accurately estimating soil water and salt content. In this study, Linear spectral unmixing method (LSU) was used to obtain the contribution of soil water and salt to each band spectrum (abundance), and endmember spectra from Sentinel-2 images. Calculating spectral indices and selecting optimal spectal combination were individually based on soil water and salt endmember spectra. The estimation models were constructed using six machine learning algorithms: BP Neural Network (BPNN), Support Vector Regression (SVR), Partial Least Squares Regression (PLSR), Random Forest Regression (RFR), Gradient Boost Regression Tree (GBRT), and eXtreme Gradient Boosting tree (XGBoost). The results showed that the spectral indices calculated from endmember spectra were able to effectively characterize the response of crop spectral properties to soil water and salt, which circumvent spectral ambiguity induced by water-salt mixing. NDRE spectral index was a reliable indicator for estimating water and salt content, with determination coefficients (R2) being 0.55 and 0.57, respectively. Compared to other models, LSU-XGBoost model achieved the best performance. This model properly reflected the process of soil water-salt dynamics in farmland during crop growth period. This study provided new methods and ideas for soil water-salt estimation in dry irrigated agricultural areas, and provided decision support for governance of salinized land and optimal management of irrigation.

The study aimed to explore the associations between water intake and body composition and differences of body composition in different water itake and hydration statuses among young male athletes. A cross-sectional study was conducted among 111 young male athletes in Beijing, China. Total drinking fluids (TDF) and water from food were assessed using a 7-day, 24-h fluid intake record questionnaire and the duplicate portion method, respectively. The osmolality of 24-hour urine and blood samples was tested. Body composition was measured using a bioelectrical impedance analyzer twice at 5-min intervals. Participants were divided into two groups based on the recommendations of total water intake (TWI) and TDF in China, as well as into three groups based on 24-h urine osmolality. Pearson's correlation coefficients were calculated to determine the relationship between water intake and body composition. Chi-square tests and Student's t-tests were used to compare differences. A total of 109 participants completed the study. TDF (r = 0.230, p = 0.016; r = 0.234, p = 0.014; r = 0.242, p = 0.011) and TWI (r = 0.275, p = 0.004; r = 0.243, p = 0.011; r = 0.243, p = 0.011) were positively correlated with total body water (TBW), intracellular water (ICW), and extracellular water (ECW). TBW/body weight (BW) was positively associated with TDF percentage of BW (TDF/BW) (r = 0.267, p = 0.005), water from food percentage of BW (r = 0.217, p = 0.024), and TWI percentage of BW (TWI/BW) (r = 0.316, p = 0.001). Participants who met the TDF recommendation of China had 1.3 kg higher skeletal muscle mass (SMM), 0.9 kg higher ICW, and 0.5% higher TBW/BW than those who did not (all p 0.05). Participants who met the TWI or TDF recommendations had better body composition distribution than their counterparts. Thus, habitual water intake, not hydration status, affects body composition among athletes in free-living conditions.

Understanding soil moisture dynamics is crucial for crop growth. The digital mapping of field soil moisture distribution provides valuable information for agricultural water management. The optical satellite data provides fine scale soil moisture information for a region. However, these data are greatly limited due to cloud contamination and revisit period. Despite the reported beneficial effects of spatiotemporal fusion methods, the accurate estimates of high-resolution soil moisture through spatiotemporal fusion data are still unclear, particularly when using Sentinel-2/3 fusion images. This study introduces a new soil moisture estimation framework integrating spatio-temporal spectral information from Sentinel-2/3 fusion images and machine learning algorithm,and thus provide spatiotemporally continuous soil moisture estimation. The framework includes four fusion methods (ESTARRFM, Fit-FC, FSDAF and STFMF) and four machine learning models (PLSR, SVM, RF and GBRT). The feasibility of the framework was validated in the Hetao Irrigation Area of Inner Mongolia, China. The results showed that the Sentinel-2/3 fused image generated by Fit-FC was visually the closest to the true image, followed by ESTARFM, FSDAF, and STFMF. The spatiotemporal fusion-machine learning estimation framework provided reliable estimation for multi-layer (0 ∼ 20, 20 ∼ 40 and 40 ∼ 60 cm) soil water in the irrigation area. The dense time series of soil water generated by the framework facilitated the detection of irrigation events in the irrigated farmland. Our findings highlighted the effectiveness of Sentinel-2/3 fused images in providing high-resolution continuous daily monitoring of farmland soil water on a large scale. These high spatial–temporal resolution time series are valuable for monitoring crop growth and water resource management, contributing to further expanding the application of satellite remote sensing in precision agriculture.

Objective Hand clumsiness and reduced hand dexterity can signal early signs of degenerative cervical myelopathy (DCM). While the 10-second grip and release (10-s G&R) test is a common clinical tool for evaluating hand function, a more accessible method is warranted. This study explores the use of deep learning-enhanced hand grip and release test (DL-HGRT) for predicting DCM and evaluates its capability to reduce the duration of the 10-s G&R test. Methods The retrospective study included 508 DCM patients and 1,194 control subjects. Propensity score matching (PSM) was utilized to minimize the confounding effects related to age and sex. Videos of the 10-s G&R test were captured using a smartphone application. The 3D-MobileNetV2 was utilized for analysis, generating a series of parameters. Additionally, receiver operating characteristic curves were employed to assess the performance of the 10-s G&R test in predicting DCM and to evaluate the effectiveness of a shortened testing duration. Results Patients with DCM exhibited impairments in most 10-s G&R test parameters. Before PSM, the number of cycles achieved the best diagnostic performance (area under the curve [AUC], 0.85; sensitivity, 80.12%; specificity, 74.29% at 20 cycles), followed by average grip time. Following PSM for age and gender, the AUC remained above 0.80. The average grip time achieved the highest AUC of 0.83 after 6 seconds, plateauing with no significant improvement in extending the duration to 10 seconds, indicating that 6 seconds is an adequate timeframe to efficiently evaluate hand motor dysfunction in DCM based on DL-HGRT. Conclusion DL-HGRT demonstrates potential as a promising supplementary tool for predicting DCM. Notably, a testing duration of 6 seconds appears to be sufficient for accurate assessment, enhancing the test more feasible and practical without compromising diagnostic performance.

Abstract We demonstrate an adaptation of deep learning for label-free imaging of the micro-scale lymphatic vessels and aqueous veins in the eye using optical coherence tomography (OCT). The proposed deep learning-based OCT lymphangiography (DL-OCTL) method was trained, validated and tested, using OCT scans (23 volumetric scans comprising 19,736 B-scans) from 11 fresh ex vivo porcine eyes with the corresponding vessel labels generated by a conventional OCT lymphangiography (OCTL) method based on thresholding with attenuation compensation. Compared to conventional OCTL, the DL-OCTL method demonstrates comparable results for imaging lymphatics and aqueous veins in the eye, with an Intersection over Union value of 0.79 ± 0.071 (mean ± standard deviation). In addition, DL-OCTL mitigates the imaging artifacts in conventional OCTL where the OCT signal modelling was corrupted by the tissue heterogeneity, provides ~ 10 times faster processing based on a rough comparison and does not require OCT-related knowledge for correct implementation as in conventional OCTL. With these favorable features, DL-OCTL promises to improve the practicality of OCTL for label-free imaging of lymphatics and aqueous veins for preclinical and clinical imaging applications.

Aboveground biomass (AGB) is a critical indicator for monitoring the crop growth status and predicting yields. UAV remote sensing technology offers an efficient and non-destructive method for collecting crop information in small-scale agricultural fields. High-resolution hyperspectral images provide abundant spectral-textural information, but whether they can enhance the accuracy of crop biomass estimations remains subject to further investigation. This study evaluates the predictability of winter canola AGB by integrating the narrowband spectra and texture features from UAV hyperspectral images. Specifically, narrowband spectra and vegetation indices were extracted from the hyperspectral images. The Gray Level Co-occurrence Matrix (GLCM) method was employed to compute texture indices. Correlation analysis and autocorrelation analysis were utilized to determine the final spectral feature scheme, texture feature scheme, and spectral-texture feature scheme. Subsequently, machine learning algorithms were applied to develop estimation models for winter canola biomass. The results indicate: (1) For spectra features, narrow-bands at 450~510 nm, 680~738 nm, 910~940 nm wavelength, as well as vegetation indices containing red-edge narrow-bands, showed outstanding performance with correlation coefficients ranging from 0.49 to 0.65; For texture features, narrow-band texture parameters CON, DIS, ENT, ASM, and vegetation index texture parameter COR demonstrated significant performance, with correlation coefficients between 0.65 and 0.72; (2) The Adaboost model using the spectra-texture feature scheme exhibited the best performance in estimating winter canola biomass (R2 = 0.91; RMSE = 1710.79 kg/ha; NRMSE = 19.88%); (3) The combined use of narrowband spectra and texture feature significantly improved the estimation accuracy of winter canola biomass. Compared to the spectra feature scheme, the model’s R2 increased by 11.2%, RMSE decreased by 29%, and NRMSE reduced by 17%. These findings provide a reference for studies on UAV hyperspectral remote sensing monitoring of crop growth status.

Accurate, timely, and continuous soil moisture information is helpful for crop stress diagnosis and irrigation management decision. OPtical TRApezoid Model (OPTRAM) based on optical satellite data has been proven to be an effective method for assessing soil moisture status. However, the applicability of OPTRAM to small-scale field soil moisture assessment remains to be explored. In this study, we propose a strategy for the genetically parameterized OPTRAM and evaluate its applicability on Unmanned Aerial Vehicle (UAV) high-resolution hyspectral data. The results showed that: (1) When OPTRAM was used to genetically parameterized with PROSAIL generated dataset, 46 characteristic narrowband bands (|R|= 0.52–0.78) were determined in the spectral region of near infrared (NIR) (750–850 nm) and SWIR (1060–1080 and 1450–1500 nm); (2) By fine-tuned soil moisture estimation model using transfer learning strategy, the reliable soil moisture estimation was achieved in three crops (R2=0.57–0.64; RMSE=0.008–0.022 m3m−3);(3) Compared to soil moisture estimation model using a single spectral region (NIR or SWIR), the DSWC model that combine NIR and SWIR was more effective for tracking soil moisture; (4) The scale effect was observed when the fine-tuned soil moisture estimation model was applied on the high-resolution UAV images. The model performance was stable in pixel size of 1–7 cm and began to drop at pixel size of 11 cm. The above results advance the application of OPTRAM on small farmland soil moisture assessment and demonstrate the application potential of OPTRAM on narrow-band hyperspectral data. This study provides a new candidate for the use of hyperspectral data to estimate soil moisture, and scientific support for precision agriculture and irrigation scheduling.

Abstract Background The liver is anatomically divided into eight segments based on the distribution of Glisson's triad. However, the molecular mechanisms underlying each segment and its association with hepatocellular carcinoma (HCC) heterogeneity are not well understood. In this study, our objective is to conduct a comprehensive multiomics profiling of the segmentation atlas in order to investigate potential subtypes and therapeutic approaches for HCC. Methods A high throughput liquid chromatography‐tandem mass spectrometer strategy was employed to comprehensively analyse proteome, lipidome and metabolome data, with a focus on segment‐resolved multiomics profiling. To classify HCC subtypes, the obtained data with normal reference profiling were integrated. Additionally, potential therapeutic targets for HCC were identified using immunohistochemistry assays. The effectiveness of these targets were further validated through patient‐derived organoid (PDO) assays. Results A multiomics profiling of 8536 high‐confidence proteins, 1029 polar metabolites and 3381 nonredundant lipids was performed to analyse the segmentation atlas of HCC. The analysis of the data revealed that in normal adjacent tissues, the left lobe was primarily involved in energy metabolism, while the right lobe was associated with small molecule metabolism. Based on the normal reference atlas, HCC patients with segment‐resolved classification were divided into three subtypes. The C1 subtype showed enrichment in ribosome biogenesis, the C2 subtype exhibited an intermediate phenotype, while the C3 subtype was closely associated with neutrophil degranulation. Furthermore, using the PDO assay, exportin 1 (XPO1) and 5‐lipoxygenase (ALOX5) were identified as potential targets for the C1 and C3 subtypes, respectively. Conclusion Our extensive analysis of the segmentation atlas in multiomics profiling defines molecular subtypes of HCC and uncovers potential therapeutic strategies that have the potential to enhance the prognosis of HCC.

The accumulation of soil salt becomes a worldwide widespread phenomenon, being a major threat to global production. As an environmental stress, soil salinity can reduce the vegetation photosynthetic activity. Solar-induced chlorophyll fluorescence (SIF) is an electromagnetic signal actively released by vegetation during photosynthesis. SIF not only can capture lower vegetation photosynthetic activity due to environmental stress promptly, but also is less affected by atmosphere and soil background. However, the ability of SIF observation to detect soil salinity remains unclear. Here, we use standardized solar-induced chlorophyll iluorescence index (SIFI) from SIF observation time series (2000 ∼ 2020) of global OCO-2 based SIF product (GOSIF) to develop soil salinity model. The results show that: SIF observation can identify salt affected soil (EC ≥ 2 ∼ 4 dS m−1) and salinity class a global scale. The SIFI calculated from SIF observation at May ∼ August (hereafter SIFI5-8) is the optimal sensitivity indices for rainfed cropland, herbaceous cover, irrigated cropland, shrubland, grassland. SIFI10-11 is the optimal sensitivity indices for forest and sparse vegetation; (2) By comparison, the ovrerall classification accuracy of predicted salinity class is above 70 %. The order of classification accuracy is rainfed cropland > irrigated cropland > bare area > forest > grassland > shrubland > herbaceous cover > sparse vegetation; (3) During at least three-quarters of the period from 2000 to 2020, the area of salt affected soil (EC ≥ 2 ∼ 4 dS m−1) was 4.9 Mkm2; (4) The annual change rate of global soil salt content is generally between −0.05 and 0.05 dS m−1 yr−1. Soil salinity in South Africa and West Asia increased greatly with an annual change rate of 0.02 ∼ 0.03 dS m−1 yr−1. These results demonstrate the ability of SIF observation to estimate soil salinity, providing a new perspective for explaining and evaluating soil salinity variation.

Blood-contact devices are prone to inflammation, endothelial dysfunction, coagulation, and the uncontrolled release of metal ions during implantation and service. Therefore, it is essential to make these multifunctional. Herein, a superhydrophobic DE@ZnS-ZnO@SA film (composed of dabigatran ester, zinc sulfite, zinc oxide, and stearic acid, respectively) is produced. The prepared film has non-adhesion and antibacterial properties, superior mechanical stability, durability, corrosion resistance, and is self-cleaning and blood-repellent. The results of the hemolysis, cytotoxicity, and other anticoagulant experiments revealed that the film had good blood compatibility, no cytotoxicity, and excellent anticoagulant properties. The film displays anticoagulant properties even after being immersed in Phosphate-Buffered Saline (PBS) for 7 days. Furthermore, the film can spontaneously release H2S gas for 90 h after soaking in an acidic environment (pH = 6) for 90 h. This property improves the acidic microenvironment of the lesion and promotes the proliferation of endothelial cells by using H2S gas. In addition, the film can inhibit the uncontrollable release of Zn2+ ions, avoiding its toxicity even when immersed in an acid environment for 35 days. This time-sequential functionalized surface has the potential to typify the future of blood-contacting scaffolds for long-lasting use.

Drip fertigation (DF) is a widely used technology to increase grain yield with water and fertilizer conservation. However, the mechanism of high grain yield (GY) under DF is still unclear. Here, a four-year field experiment assessed the impacts of four treatments (i.e., conventional irrigation and nitrogen application, CK; drip irrigation with conventional nitrogen fertilization, DI; split-nitrogen fertigation with conventional irrigation, SF; and drip fertigation, DF) on maize phenology, leaf photosynthetic rates, grain filling processes, plant biomass, and GY. The results showed that DF significantly increased maize GY by affecting phenology, grain filling traits, aboveground biomass (BIO) accumulation, and translocation. Specifically, DF significantly increased leaf chlorophyll content, which enhanced leaf photosynthetic rates, and together with an increase of leaf area index, promoted BIO accumulation. As a result, the BIO at the silking stage of DF increased by 29.5%, transported biomass increased by 109.2% (1.2 t ha−1), and the accumulation of BIO after silking increased by 23.1% (1.7 t ha−1) compared with CK. Meanwhile, DF prolonged grain filling days, significantly increased the grain weight of 100 kernels, and promoted GY increase. Compared with CK, the four-year averaged GY and BIO increased by 34.3% and 26.8% under DF; a 29.7%, 46.1%, and 24.2% GY increase and a 30.7%, 39.5%, and 29.9% BIO increase were contributed by irrigation, nitrogen, and coupling effects of irrigation and nitrogen, respectively. These results reveal the high yield mechanism of drip-fertigated maize, and are of important significance for promoting the application of drip fertigation.

The leaf area index (LAI) is a crucial physiological indicator of crop growth. This paper introduces a new spectral index to overcome angle effects in estimating the LAI of crops. This study quantitatively analyzes the relationship between LAI and multi-angle hyperspectral reflectance from the canopy of winter oilseed rape (Brassica napus L.) at various growth stages, nitrogen application levels and coverage methods. The angular stability of 16 traditional vegetation indices (VIs) for monitoring the LAI was tested under nine view zenith angles (VZAs). These multi-angle VIs were input into machine learning models including support vector machine (SVM), eXtreme gradient boosting (XGBoost), and Random Forest (RF) to determine the optimal monitoring strategy. The results indicated that the back-scattering direction outperformed the vertical and forward-scattering direction in terms of monitoring the LAI. In the solar principal plane (SPP), EVI-1 and REP showed angle stability and high accuracy in monitoring the LAI. Nevertheless, this relationship was influenced by experimental conditions and growth stages. Compared with traditional VIs, the observation perspective insensitivity vegetation index (OPIVI) had the highest correlation with the LAI (r = 0.77–0.85). The linear regression model based on single-angle OPIVI was most accurate at −15° (R2 = 0.71). The LAI monitoring achieved using a multi-angle OPIVI-RF model had the higher accuracy, with an R2 of 0.77 and with a root mean square error (RMSE) of 0.38 cm2·cm−2. This study provides valuable insights for selecting VIs that overcome the angle effect in future drone and satellite applications.

Cervical squamous cell carcinoma (CESC) ranks among the primary contributors to global cancer-associated mortality. However, the role mediated by synaptotagmin 7 (SYT7) in CESC remains unclear. Our study employed immunohistochemistry to assess the level of SYT7 expression in the tissue microarray. Furthermore, lentiviral shRNA transduction was utilized to establish SYT7 knockdown cell line models based on HeLa and SiHa cell lines. The functional impacts of silencing SYT7 expression in vitro were evaluated. A subcutaneous xenograft model was employed to examine the tumorigenic potential of cells with or without SYT7. The content of SYT7 in CESC tissues was significantly elevated compared to adjacent normal tissues. Functionally, silencing SYT7 in HeLa and SiHa cells suppressed cell proliferation, colony formation ability, and apoptosis enhancement. Additionally, cells with suppressed SYT7 also exhibited inhibited cell migration and invasion. In vivo experiments demonstrated the loss of tumorigenic ability in SYT7 knockdown cells and suppressed tumor growth. Quantitative PCR PrimeView PathArray and apoptosis antibody array analyses revealed that upon elimination of SYT7, there was a significant upregulation observed in Caspase 8, TNF-R1 (TNF receptor superfamily member 1A), and HSPA5 (heat shock protein family A [Hsp70] member 5), while TGFBI (transforming growth factor beta-induced), RPL31 (ribosomal protein L31), LUM (lumican), HSDL2 (hydroxysteroid dehydrogenase-like 2), ITGB5 (integrin subunit beta 5), and Smad2 (SMAD family member2) were downregulated. Overall, we have demonstrated the tumor-promoting functions of SYT7 in CESC.

Seed vigor encompasses the germination capacity, ability to form seedlings, and potential for production of seeds, and during storage, the deterioration of seed vigor is an inevitable biological process. However, changes in the microflora of the seed surface and seed vigor under different storage conditions have rarely been studied. In this study, the changes in fungal species on the surface and embryo and their effects of the hybrid maize cultivar Zhengdan958 seeds under different storage conditions were studied. The seed vigor was evaluated according to standard germination, MDA content, respiration rate, ATP content and the integrity of the ATP synthase subunits of seed embryos, with the aim of providing a basis for revealing the molecular mechanism of seed deterioration. The results revealed that at 33% relative humidity (RH), the dominant microflora constituent on the seed surface was Fusarium sp. In the seed embryo, the dominant microflora constituent was Aspergillus fumigatus. At 91% RH, the dominant microflora constituent on the seed surface was Aspergillus Jensen. In the seed embryo, the dominant microflora constituent was Penicillium sp. With the increased RH in the storage environment, the seed germination rate decreased by 86.67%. The respiration rate decreased by 0.04 mg·g-1·h-1 after 24 h imbibition. The seed embryo was hardly stained via TTC. The MDA content increased by 0.99 nmol·g-1, and the ATP content decreased by 0.33 μmol·g-1 after 24 h imbibition. The mRNA integrity of ATP synthase α, β, γ and δ subunits, except for ε subunit, in the seed embryo decreased to different degrees. These findings suggest that a change in the microflora is one of the most important factors causing a decrease in or total loss of seed vigor.

ObjectiveTo reveal the relationship between ARHL and ferroptosis and screen ferroptosis-related genes (FRGs) in ARHL.MethodsBioinformatics were used to analyze the hub genes and molecular mechanism of ferroptosis in the aging cochleae. Senescence β-galactosidase staining, iron content detection, and micro malondialdehyde (MDA) assay kits were used to measure β-galactosidase activity, and expression of Fe2+ and MDA, respectively. Fluorescence microscope was used for immunofluorescence assay of hub genes. Western blot was used to verify the expression of hub genes in HEI-OC1 cells, cochlear explants, and cochleae of C57BL/6J mice. Data were expressed as mean ± SD of at least three independent experiments.ResultsThe analysis of bioinformatics confirmed that lactotransferrin (LTF) is the hub gene and CEBPA-miR-130b-LTF network is the molecular mechanism for cochlear ferroptosis. Compared with the control group, the experiments proved that the indicators of ferroptosis, including Fe2+, MDA, and LTF were differentially expressed in aging HEI-OC1 cells, aging cochlear explants, and aging cochleae.ConclusionThese results demonstrate that ferroptosis plays an important role in ARHL, and LTF is a potential therapeutic target for ARHL via regulating cochlear ferroptosis.

Abstract Background Gliomas are highly refractory intracranial cancers characterized by genetic and transcriptional heterogeneity. However, therapeutic options are limited. In the last years, copper‐induced cell death is becoming a prospective treatment strategy for gliomas and other solid tumors, but copper metabolism‐related genes associated with cancer development remain unclear. Methods We first collected gene expression data from The Cancer Genome Atlas (TCGA) to identify significantly differentially expressed copper metabolism‐related genes in gliomas. Using these genes, we performed COX regression and Least Absolute Shrinkage and Selection Operator (LASSO) regression to construct the prognostic model. The prognostic value of the model was further validated by CGGA testing set. Subsequently, functional analyses were carried out, including gene set enrichment analysis (GSEA), immune infiltration analysis, and mutation analysis. Finally, the expression levels of these genes were verified by immunohistochemical analysis. Results The prognostic model consisted of 7 genes: CDK1, LOXL2, LOXL3, NFE2L2, SLC31A1, SUMF1 and FDX1. According to this prognosis model, glioma patients could be split into the high‐risk group or low‐risk group, and the low‐risk group showed significantly better prognostic survival (p

When calculating the CWSI, previous researchers usually used canopy temperature and atmospheric temperature at the same time. However, it takes some time for the canopy temperature (Tc) to respond to atmospheric temperature (Ta), suggesting the time-lag effects between Ta and Tc. In order to investigate time-lag effects between Ta and Tc on the accuracy of the CWSI inversion of photosynthetic parameters in winter wheat, we conducted an experiment. In this study, four moisture treatments were set up: T1 (95% of field water holding capacity), T2 (80% of field water holding capacity), T3 (65% of field water holding capacity), and T4 (50% of field water holding capacity). We quantified the time-lag parameter in winter wheat using time-lag peak-seeking, time-lag cross-correlation, time-lag mutual information, and gray time-lag correlation analysis. Based on the time-lag parameter, we modified the CWSI theoretical and empirical models and assessed the impact of time-lag effects on the accuracy of the CWSI inversion of photosynthesis parameters. Finally, we applied several machine learning algorithms to predict the daily variation in the CWSI after time-lag correction. The results show that: (1) The time-lag parameter calculated using time-lag peak-seeking, time-lag cross-correlation, time-lag mutual information, and gray time-lag correlation analysis are 44–70, 32–44, 42–58, and 76–97 min, respectively. (2) The CWSI empirical model corrected by the time-lag mutual information method has the highest correlation with photosynthetic parameters. (3) GA-SVM has the highest prediction accuracy for the CWSI empirical model corrected by the time-lag mutual information method. Considering time lag effects between Ta and Tc effectively enhanced the correlation between CWSI and photosynthetic parameters, which can provide theoretical support for thermal infrared remote sensing to diagnose crop water stress conditions.

Abstract Succinic acid (SA) is an intermediate product of the tricarboxylic acid cycle (TCA) and is one of the most significant platform chemicals for the production of various derivatives with high added value. Due to the depletion of fossil raw materials and the demand for eco-friendly energy sources, SA biosynthesis from renewable energy sources is gaining attention for its environmental friendliness. This review comprehensively analyzes strategies for the bioconversion of lignocellulose to SA based on the lignocellulose pretreatment processes and cellulose hydrolysis and fermentation principles and highlights the research progress on acid production and SA utilization under different microbial culture conditions. In addition, the fermentation efficiency of different microbial strains for the production of SA and the main challenges were analyzed. The future application directions of SA derivatives were pointed out. It is expected that this research will provide a reference for the optimization of SA production from lignocellulose.

BackgroundSudden sensorineural hearing loss (SSNHL) is a global problem threatening human health. Early and rapid diagnosis contributes to effective treatment. However, there is a lack of effective SSNHL prediction models.MethodsA retrospective study of SSNHL patients from Fujian Geriatric Hospital (the development cohort with 77 participants) was conducted and data from First Hospital of Putian City (the validation cohort with 57 participants) from January 2018 to December 2021 were validated. Basic characteristics and the results of the conventional coagulation test (CCT) and the blood routine test (BRT) were then evaluated. Binary logistic regression was used to develop a prediction model to identify variables significantly associated with SSNHL, which were then included in the nomogram. The discrimination and calibration ability of the nomogram was evaluated by receiver operating characteristic (ROC), calibration plot, and decision curve analysis both in the development and validation cohorts. Delong’s test was used to calculate the difference in ROC curves between the two cohorts.ResultsThrombin time (TT), red blood cell (RBC), and granulocyte–lymphocyte ratio (GLR) were found to be associated with the diagnosis of SSNHL. A prediction nomogram was constructed using these three predictors. The AUC in the development and validation cohorts was 0.871 (95% CI: 0.789–0.953) and 0.759 (95% CI: 0.635–0.883), respectively. Delong’s test showed no significant difference in the ROC curves between the two groups (D = 1.482, p = 0.141).ConclusionIn this study, a multifactor prediction model for SSNHL was established and validated. The factors included in the model could be easily and quickly accessed, which could help physicians make early diagnosis and clinical treatment decisions.

A novel N-doped activated carbon (NAC) derived from shaddock peel was investigated to remove norfloxacin (NFX) from aqueous solution. The Box-Behnken central composite design (BBD) was used to optimize the preparation conditions of NAC. The specific surface area of NAC was 2,481.81 m2 g−1, which was obtained at 1,106 K activation temperature, 2.4 h residence time, and 2.3:1 mass ratio of KOH to hydrochar. Moreover, the equilibrium data were perfectly represented by Langmuir and Koble-Corrigan isotherms, and the adsorption process was precisely described by the pseudo-second-order kinetic model. Besides, the adsorption of NFX on NAC was mainly controlled by π-π electron-donor-acceptor (EDA) interaction, hydrophobic effect, hydrogen-bonding, electrostatic interaction and Lewis acid-base effect. The maximum monolayer adsorption capacity of NFX was 746.29 mg g−1 at 298 K, implying that NAC was a promising adsorbent for the removal of NFX from aqueous solution. HIGHLIGHTS The specific surface area of N-doped activated carbon prepared by hydrothermal carbonization and KOH activation is as high as 2481.81 m2 g−1.; The maximum monolayer adsorption capacity of norfloxacin on NAC-1106 was 746.29 mg g−1 at 298 K.; The adsorption mechanism of NFX on NAC was investigated by XPS, Raman, FTIR and so on.;

In the service process of gears, premature fatigue failure or fracture of gears is often caused by poor surface performance. 20CrNiMo steel is a commonly used material for gears. Laser-shock peening (LSP), carburizing treatment (CT), and hybrid modification of carburizing treatment and laser-shock peening (LSP + CT) were carried out to improve the performance of 20CrNiMo steel. The hardness, residual stress, microstructure, subgrain size, and toughness of the samples were analyzed following various modification methods. It was observed that the properties of the composite-modified gradient structure materials achieved through carburizing and laser-shock peening were superior to those modified using single methods. After the composite treatment of carburizing and laser shocking, the samples exhibited the most significant increase in hardness, up to 916HV0.1, with a surface layer experiencing residual compressive stress as low as −635 MPa. Simultaneously, a gradient microstructure was formed on the surface layer, with 80% of the crystallites being in the nanoscale range. Furthermore, the toughness was notably enhanced. Experimental results confirm the improvement in the properties of 20CrNiMo samples, resulting in the creation of a functionally graded material through the composite treatment of carburizing and laser shocking.

The grinding grooves of material removal machining and the residues of a machining tool on the key component surface cause surface stress concentration. Thus, it is critical to carry out precise measurements on the key component surface to evaluate the stress concentration. Based on white-light interferometry (WLI), we studied the measurement distortion caused by the reflected light from the steep side of the grinding groove being unable to return to the optical system for imaging. A threshold value was set to eliminate the distorted measurement points, and the cubic spline algorithm was used to interpolate the eliminated points for compensation. The compensation result agrees well with the atomic force microscope (AFM) measurement result. However, for residues on the surface, a practical method was established to obtain a microscopic 3D micro-topography point cloud and a super-depth-of-field fusion image simultaneously. Afterward, the semantic segmentation network U-net was adopted to identify the residues in the super-depth-of-field fusion image and achieved a recognition accuracy of 91.06% for residual identification. Residual feature information, including height, position, and size, was obtained by integrating the information from point clouds and super-depth-of-field fusion images. This work can provide foundational data to study surface stress concentration.

Furfural residue (FR), a solid waste, was applied as the precursor to prepare activated carbon by steam activation. The Box-Behnken design (BBD) approach-based response surface methodology (RSM) was utilized to optimize the preparation conditions to evaluate their effects on the performance of activated carbon from furfural residue (FRAC). The optimum preparation conditions of FRAC were found as follows: activation temperature of 922 °C, activation time of 62 min, and the mass ratio of char to H2O of 1:4.5, resulting in 1,501.84 mg/g of iodine adsorption capacity and 1,662.41 m2/g of specific surface area. The FRAC was characterized and then the adsorption performance of bisphenol S (BPS) on FRAC was investigated. Langmuir and Koble-Corrigan isotherm models were well fitted to the experimental data, and the adsorption kinetics process was perfectly described by the pseudo-second-order model. Thermodynamic parameters showed that the adsorption of BPS was a spontaneous exothermic process. Besides, the regeneration efficiency of FRAC was over 97% after five consecutive cycles. The maximum monolayer adsorption capacity of FRAC for BPS was 3.2848 mmol/g at 298 K, indicating that the FRAC was an excellent adsorbent for the removal of BPS from aqueous solutions. HIGHLIGHTS Activated carbon derived from solid waste furfural residue (FRAC) by steam activation displayed high surface area up to 1662.41 m2/g.; Response surface methodology (RSM) based on Box-Behnken Design (BBD) was applied to optimize the preparation conditions of FRAC.; The maximum adsorption capacity of FRAC for Bisphenol S (BPS) was 3.2848 mmol/g at 298 K.;

Dengue virus infection mainly causes dengue hemorrhagic fever (DHF) and/or dengue shock syndrome (DSS). However, ADE (antibody-dependent enhancement) is one of the main pathogenic factors, and its pathogenic mechanism has not been fully elucidated. Recently, with the development of high-throughput sequencing, an increased number of RNAs have been confirmed to play a vital regulatory role in the process of virus infection. However, there is a lack of research on dengue virus infection and ADE. In this study, we used RNA-Seq to detect differentially expressed RNAs (DE RNAs) profiles in mock-infected, DENV-3-infected, and ADE-infected THP-1 cells. Firstly, we found 69 circRNAs, 259 miRNAs, and 18 mRNAs were differentially expressed in THP-1 vs DENV-3. In THP-1 vs ADE, 94 circRNAs, 263 miRNAs, and 111 mRNAs were differentially expressed. In DENV-3 vs ADE, 68 circRNAs, 105 miRNAs, and 94 mRNAs were differentially expressed. Functional enrichment analysis of these DE RNAs mainly focused on immune system, viral infectious diseases, cytokine-cytokine receptor interactions, and NOD/RIG-I-like receptor signaling pathways. In DENV-3 vs ADE, notably, the expression of HBB was up-regulated, which was a Fcγ Receptor-mediated phagocytosis protein. Additionally, we predicted the encoding ability of DE circRNAs, and it was found that a small peptide was encoded by novel_circ_001562 and that its amino acid sequence was consistent with that of DDX60L, which is a class of interferon-stimulated genes. Finally, we constructed the ceRNA regulatory network pathway. Therefore, our study provides a new strategy for further investigation on DENV-host interactions.

Lay summaryPatients with a family history of cancer, especially digestive tract cancer and esophageal cancer, a family history of cancer in the first degree, and more than one relative affected by cancer were associated with favorable survival when compared to those without a family history of cancer.Precis for use in the Table of ContentsA family history of cancer is a favorable independent prognostic factor in ESCC. Patients with a family history of cancer, especially digestive tract cancer and esophageal cancer, a family history of cancer in the first degree, and more than one relative affected by cancer were associated with favorable survival when compared to those without a family history of cancer.BackgroundA family history of cancer (FH) is closely associated with the risk and survival of many cancers. However, the effect of FH on the prognosis of patients with esophageal squamous cell carcinoma (ESCC) remains unclear. We performed a large cohort study in the Chinese population to obtain insight into the prognostic value of FH in patients with operable ESCC.MethodsA total of 1,322 consecutive patients with thoracic ESCC who had undergone esophagectomy between January 1997 and December 2013 were included. The FH group included patients with any degree of FH, while the non-FH group included patients without any degree of FH. In total, 215 patients with FH and 215 without FH were matched using the propensity score matching analysis method to adjust for differences in baseline variables between the two groups. The impact of FH on disease-free survival (DFS) and overall survival (OS) was estimated using the Kaplan–Meier method and Cox’s proportional hazards models.ResultsBefore matching, 280 (21.2%) patients were included in the FH group and 1,042 (78.8%) in the non-FH group. FH was associated with early pathological T stage (p = 0.001), lymph node-negative status (p = 0.022), and early pathological stage (p = 0.006). After matching, FH was an independent prognostic factor for DFS and OS in ESCC patients. Patients with FH had 35% lower risk of disease progression (hazard ratio [HR] = 0.65, 95% CI: 0.51–0.84, p = 0.001) and 34% lower risk of death (HR = 0.66, 95% CI: 0.51–0.86, p = 0.002) than those without FH. Patients with a family history of digestive tract cancer (FH-DC), a family history of esophageal cancer (FH-EC), FH in first-degree relatives (FH-FD), and more than one relative affected by cancer were associated with favorable DFS and OS as compared to those without FH.ConclusionFH is a favorable independent prognostic factor in ESCC. Patients with FH, especially those with FH-DC, FH-EC, FH-FD, and more than one relative affected by cancer, had improved survival.

To improve the water application uniformity for sprinkler irrigation on sloping land, indoor tests were conducted on an artificial slope (slopes of 0, 0.05, 0.10 and 0.15) to evaluate the effects of two riser orientations, vertical (VO) and perpendicular (PO) to the slope, on the uniformity of sprinkler rotation, radius of throw, water distribution of an individual sprinkler and the overlapped water application uniformity (WAU). Compared with the VO, the PO could effectively improve the water distribution on sloping land and minimize the risk of soil erosion. Additionally, the PO was superior in the WAU, and a rectangular arrangement could dramatically enhance the WAU at smaller sprinkler spacing, while larger acceptable sprinkler spacing was accepted in a triangular arrangement. The riser orientation and sprinkler spacing had the most significant effect on the WAU, followed by the slope and sprinkler arrangement, suggesting that the adjustment of riser orientation or sprinkler spacing was helpful in improving the WAU. However, from the aspects of investment cost and installation convenience for irrigation projects, the method of PO was recommended. Therefore, when designing the sprinkler irrigation systems on the slope, choosing PO is the simplest and most effective way to achieve good irrigation uniformity. HIGHLIGHTS Riser perpendicular to the slope can obviously improve the water distribution on sloping land and minimize the risk of soil erosion.; The overlapped water application uniformity is superior for riser perpendicular to the slope than for a vertical riser.; Both the riser orientation and sprinkler spacing have the most significant effects on the overlapped water application uniformity.;

BackgroundEsophageal squamous cell carcinoma (ESCC) is characterized clinically by frequent recurrence, leading to a poor prognosis after radical surgery. The aim of this study was to identify a prognostic nomogram to predict the post-progression survival (PPS) of ESCC patients based on the features of primary tumor and recurrence.MethodsA total of 234 ESCC patients who underwent recurrence after radical surgery were enrolled in this study. The independent prognostic factors screened by the univariate and multivariate Cox regression analysis were subsequently used to construct a nomogram. The predictive performance of the nomogram was evaluated with the concordance index (C-index), decision curve, and the area under the receiver operating characteristic curve (AUC) and validated in two validation cohorts. The Kaplan-Meier curves of different recurrence patterns were analyzed.ResultsThe prognostic nomogram of PPS was established by integrating independent prognostic factors, including age, body mass index, number of lymph node dissection, recurrence pattern, and recurrence treatment. The nomogram demonstrated good performance, with C-index values of 0.756, 0.817, and 0.730 for the training and two validation cohorts. The 1-year AUC values were 0.773, 0.798, and 0.735 and 3-year AUC values were 0.832, 0.871, and 0.791, respectively. Furthermore, we found that patients with bone metastasis displayed the worst PPS compared to other isolated recurrence patterns.ConclusionWe constructed a nomogram to reliably predict PPS, which would be valuable to provide individual managements for ESCC patients after radical surgery.

Abstract Background An unexpected dengue outbreak occurred in Hunan Province in 2018. This was the first dengue outbreak in this area of inland China, and 172 cases were reported. Methods To verify the causative agent of this outbreak and characterise the viral genes, the genes encoding the structural proteins C/prM/E of viruses isolated from local residents were sequenced followed by mutation and phylogenetic analysis. Recombination, selection pressure, potential secondary structure and three-dimensional structure analyses were also performed. Results Phylogenetic analysis revealed that all epidemic strains were of the cosmopolitan DENV-2 genotype and were most closely related to the Zhejiang strain (MH010629, 2017) and then the Malaysia strain (KJ806803, 2013). Compared with the sequence of DENV-2SS, 151 base substitutions were found in the sequences of 89 isolates; these substitutions resulted in 20 non-synonymous mutations, of which 17 mutations existed in all samples (two in the capsid protein, six in the prM/M proteins, and nine in the envelope proteins). Moreover, amino acid substitutions at the 602nd (E322:Q → H) and 670th (E390: N → S) amino acids may have enhanced the virulence of the epidemic strains. One new DNA binding site and five new protein binding sites were observed. Two polynucleotide binding sites and seven protein binding sites were lost in the epidemic strains compared with DENV-2SS. Meanwhile, five changes were found in helical regions. Minor changes were observed in helical transmembrane and disordered regions. The 429th amino acid of the E protein switched from a histamine (positively charged) to an asparagine (neutral) in all 89 isolated strains. No recombination events or positive selection pressure sites were observed. To our knowledge, this study is the first to analyse the genetic characteristics of epidemic strains in the first dengue outbreak in Hunan Province in inland China. Conclusions The causative agent is likely to come from Zhejiang Province, a neighbouring province where dengue fever broke out in 2017. This study may help clarify the intrinsic geographical relatedness of DENV-2 and contribute to further research on pathogenicity and vaccine development.

Enterovirus A71 (EV-A71) inactivated vaccines have been widely inoculated among children in Kunming City after it was approved. However, there was a large-scale outbreak of Enteroviruses (EVs) infection in Kunming, 2018. The epidemiological characteristics of HFMD and EVs were analysed during 2008–2018, which are before and three years after EV-A71 vaccine starting to use. The changes in infection spectrum were also investigated, especially for severe HFMD in 2018. The incidence of EV-A71 decreased dramatically after the EV-A71 vaccine starting use. The proportion of non-CV-A16/EV-A71 EVs positive patients raised to 77.17–85.82%, while, EV-A71 and CV-A16 only accounted for 3.41–7.24% and 6.94–19.42% in 2017 and 2018, respectively. CV-A6 was the most important causative agent in all clinical symptoms (severe HFMD, HFMD, Herpangina and fever), accounting from 42.13% to 62.33%. EV-A71 only account for 0.36–2.05%. In severe HFMD, CV-A6 (62.33%), CV-A10 (11.64%), and CV-A16 (10.96%) were the major causative agent in 2018. EV-A71 inactivated vaccine has a good protective effect against EV-A71 and induced EVs infection spectrum changefully. EV-A71 vaccine has no or insignificant cross-protection effect on CV-A6, CV-A10, and CV-A16. Herein, developing 4-valent combined vaccines is urgently needed.

In recent years, more and more metal or non-metal materials have been used in the treatment of cardiovascular diseases, but the vascular complications after transplantation are still the main factors restricting the clinical application of most grafts, such as acute thrombosis and graft restenosis. Implant materials have been extensively designed and surface optimized by researchers, but it is still too difficult to avoid complications. Natural vascular endodermis has excellent function, anti-coagulant and anti-intimal hyperplasia, and it is also the key to maintaining the homeostasis of normal vascular microenvironment. Therefore, how to promote the adhesion of endothelial cells (ECs) on the surface of cardiovascular materials to achieve endothelialization of the surface is the key to overcoming the complications after implant materialization. At present, the surface endothelialization design of materials based on materials surface science, bioactive molecules, and biological function intervention and feedback has attracted much attention. In this review, we summarize the related research on the surface modification of materials by endothelialization in recent years, and analyze the advantages and challenges of current endothelialization design ideas, explain the relationship between materials, cells, and vascular remodeling in order to find a more ideal endothelialization surface modification strategy for future researchers to meet the requirements of clinical biocompatibility of cardiovascular materials.

Excessive soil salt content (SSC) seriously affects the crop growth and economic benefits in the agricultural production area. Prior research mainly focused on estimating the salinity in the top bare soil rather than in deep soil that is vital to crop growth. For this end, an experiment was carried out in the Hetao Irrigation District, Inner Mongolia, China. In the experiment, the SSC at different depths under vegetation was measured, and the Sentinel-1 radar images were obtained synchronously. The radar backscattering coefficients (VV and VH) were combined to construct multiple indices, whose sensitivity was then analyzed using the best subset selection (BSS). Meanwhile, four most commonly used algorithms, partial least squares regression (PLSR), quantile regression (QR), support vector machine (SVM), and extreme learning machine (ELM), were utilized to construct estimation models of salinity at the depths of 0–10, 10–20, 0–20, 20–40, 0–40, 40–60 and 0–60 cm before and after BSS, respectively. The results showed: (a) radar remote sensing can be used to estimate the salinity in the root zone of vegetation (0-30 cm); (b) after BSS, the correlation coefficients and estimation accuracy of the four monitoring models were all improved significantly; (c) the estimation accuracy of the four regression models was: SVM > QR > ELM > PLSR; and (d) among the seven sampling depths, 10–20 cm was the optimal inversion depth for all the four models, followed by 20–40 and 0–40 cm. Among the four models, SVM was higher in accuracy than the other three at 10–20 cm (RP2 = 0.67, RMSEP = 0.12%). These findings can provide valuable guidance for soil salinity monitoring and agricultural production in the arid or semi-arid areas under vegetation.

Transmembrane and ubiquitin-like domain-containing 1 (Tmub1) inhibits hepatocyte proliferation during liver regeneration, but its role in hepatocellular carcinoma (HCC) has yet to be revealed. In this study, we show that the levels of Tmub1 were significantly lower in HCC tissues and cells than they were in adjacent tissues and normal hepatic cells, and the low levels of Tmub1 indicated a poor prognosis in HCC patients. Xenograft growth assay revealed that Tmub1 represses HCC growth in vivo. In addition, Tmub1 formed a protein complex with apoptosis-associated protein tumor protein 63 (p63), especially with the ΔN isoforms (ΔNp63α, β, and γ). Further loss- and gain-of-function analyses indicated that Tmub1 promotes apoptosis of Hep3B and MHCC-LM3 cells. Tmub1 decreased the protein expression of ΔNp63, and the pro-apoptotic effect of Tmub1 can be reversed by ΔNp63 isoforms (α, β, and γ). Additionally, we report that Tmub1 promotes the ubiquitination and degradation of ΔNp63 proteins. Finally, we confirmed in HCC tissues that Tmub1 is negatively correlated with ΔNp63 and positively correlated with the level of apoptosis. Taken together, Tmub1 suppresses HCC by enhancing the ubiquitination and degradation of ΔNp63 isoforms to induce HCC cell apoptosis. These findings provide a potential strategy for the management of HCC.

Wireless sensor networks (WSNs) is composed of a large number of tiny sensors. These energy-constrained sensors are deployed in a variety of environments to collect data such as temperature, humidity, and light intensity. Therefore, how to suppress the impact of environmental noise on the collection accuracy and extend the lifetime of WSNs is one of the prominent issues. This article proposes an optimized dictionary updating learning-based compressed data collection algorithm (ODUL-CDC) to suppress the impact of environmental noise on the accuracy of WSNs data collection and extend the life cycle of WSNs. The proposed algorithm uses the dictionary learning method to obtain a sparse dictionary by learning from the training data. The collection error caused by environmental noise is positively correlated with the degree of self-coherence of the sparse dictionary. Therefore, the self-coherence penalty term is introduced during the dictionary updating process, which can reduce the over-fitting of the training data in the dictionary learning process. Moreover, the self-coherence penalty term endows the learned sparse dictionary with a low-self-coherence structure. Experimental and simulation results show that, as compared with discrete cosine transform(DCT), K-SVD and IDL learning-based data collection methods, the proposed algorithm exhibits the highest increase in recovery accuracy of 3.2% in the signal-to-noise ratio (SNR) range of 30-50 dB, the sampling ratio range of 25%-40% and the sparsity range from 3 to 30. Furthermore, the energy consumption is significantly less than that of the compared methods, which helps improve the network lifetime.

BackgroundDengue poses a large burden on the public health systems worldwide. severe dengue (SD) could lead to more serious clinical symptoms and even death. This study aimed to identify the cause of SD in a clinical trial during the dengue outbreak in Xishuangbanna in 2019, and could provide new insights into the pathogenic mechanisms of SD.MethodsMosquito-borne viral (DENV, JEV, and CHIKV) infections were identified. The epidemiological factors and clinical symptoms of inpatients in Xishuangbanna were recorded. The IgG and IgM levels in the serum of dengue inpatients were evaluated, and secondary infections were identified. Then, the structural proteins (C/PrM/E) were sequenced and compared with those of the same type of DENV in the same area as before, and their structures were predicted by the SWISS-MODEL (expasy.org). The full-length viral genomes were sequenced and aligned with representative strains by BioEidt or MEGA 5.0.ResultsIn this outbreak, the clinical symptoms were more serious in SD. The proportion of SD inpatients of male and Han nationality was larger than that of dengue fever (DF) inpatients (p < 0.05). DENV-2 infection was the majority in DF, with 45 inpatients. However, DENV-1 infection was the most common SD, with 54 inpatients. There were 3 DENV-3-positive inpatients in the DF group and 6 ZIKV-positive inpatients in the SD group. A secondary infection accounted for 76.47% (78 cases) of SD inpatients, but secondary infections were only in 20% (17 cases) of DF inpatients. In the three-dimensional structure of protein analysis, the C/PrM/E of DENV-1 and DENV-2 showed more stability than previous epidemic strains, while DENV-3 in 2019 showed a looser spatial structure. After a complete genome sequencing and analysis, all six DENV-2 strains belonged to cosmopolitan, five of which clustered into one branch. The GC/AT of the five strains decreased from 2014 to 2018. Compared with DF strains, SD strains had no mutations of commonness.ConclusionsSD may related to secondary heteromorphic dengue in Xishuangbanna in 2019. The coinfection of ZIKV could be another related factor for SD. The currently datas were very limited and only suggestive.

Atherosclerosis, a chronic inflammatory disease of vascular wall, is a progressive pathophysiological process with lipids oxidation/depositing initiation and innate/adaptive immune responses. The coordination of multi systems covering oxidative stress, dysfunctional endothelium, diseased lipid uptake, cell apoptosis, thrombotic and pro-inflammatory responding as well as switched SMCs contributes to plaque growth. In this circumstance, inevitably, targeting these processes is considered to be effective for treating atherosclerosis. Arriving, retention and working of payload candidates mediated by targets in lesion direct ultimate therapeutic outcomes. Accumulating a series of scientific studies and clinical practice in the past decades, lesion homing delivery strategies including stent/balloon/nanoparticle-based transportation worked as the potent promotor to ensure a therapeutic effect. The objective of this review is to achieve a very brief summary about the effective therapeutic methods cooperating specifical targets and positioning-delivery strategies in atherosclerosis for better outcomes.

Objective To evaluate the knowledge, attitudes and practices (KAP) of Chinese elite athletes about fluid replacement and urination. Methods A cross-section study was carried out among Chinese national and national youth teams from March to April 2020, using a pretested questionnaire. The 42-questions questionnaire was designed to assess the KAP regarding fluid replacement and urination. The questionnaire included knowledge of fluid replacement (KFR), attitudes of fluid replacement (AFR), knowledge of urination (KU), and attitudes of urination (AU), which were awarded 20 scoring points. Descriptive statistics, independent samples t-tests, one-way ANOVA, Pearson’s correlation analysis, Multiple linear stepwise regression and Chi-square test were performed. Results A total of 779 valid questionnaires were collected and the effective rate is 98.4%. We finally conducted an assessment of 646 questionnaires of elite athletes. The mean score for KFR, AFR, KU, and AU was 2.8±1.3, 2.3±0.6, 3.0±1.5, and 2.1±0.8, respectively, with higher scores indicating positive hydration knowledge and attitudes. KFR and AFR scores of winter sports athletes were higher than those of summer sports athletes(PConclusions These findings indicate that Chinese elite athletes did not have sufficient KAP on fluid replacement and urination, more marked in the individuals who were summer sport events, the lower athletic grades and in lower training years. It is recommended that education should be provided in the early stages of professional training for athletes.

In response to the shortcomings of magnesium oxychloride cement (MOC), which has excellent with outstanding mechanical properties and favorable bioactivity but poor water resistance, strontium hydrogen phosphate (SrHPO _4 ) was used as a water resistance modifier for MOC in the paper, and the effects of SrHPO _4 on the strength, water resistance, in vitro degradation and bioactivity of MOC were investigated; the results showed that SrHPO _4 could enhance the water resistance of MOC, in which the initial strength of MOC containing 4.0 wt% SrHPO _4 was 92.3 ± 2.5 MPa, and the strength was still 8.2 ± 0.9 MPa after 84 d of immersion in SBF solution; the degradation experiments of the samples in SBF solution showed that the degradation of SrHPO _4 -MOC was controlled, and the low alkaline environment created by the degradation promoted the deposition of hydroxyapatite on the cement surface, it indicated that SrHPO _4 -MOC material had good degradation properties and bioactivity; cell experiments showed that compared with MOC, SrHPO _4 -MOC was noncytotoxic and could promote cell proliferation, which was expected to be a new material for bone repair.

Dengue fever was included in the top 10 global health threats announced by the World Health Organization (WHO) in early 2019. In some southern provinces of China, autochthonous outbreaks have also been reported over the last decade. An unexpected large outbreak of dengue fever was reported in Xishuangbanna, a border area of China, Myanmar, and Laos, in 2019. Among the 226 hospitalized cases, 90 were diagnosed as severe dengue according to the 2009 WHO guidelines. Serotyping and phylogenetic analyses of envelope gene sequences from 246 randomly selected samples showed that three serotypes of dengue virus were co-circulating in this outbreak, which is very rare in this area. Dengue virus serotype 1 (DENV-1, genotype I) and serotype 2 (DENV-2, Cosmopolitan genotype and Asian genotype) were the main pathogenic agents of this outbreak. Dengue virus serotype 3 (DENV-3) epidemic strains were classified as genotype III and formed a close cluster with the Thailand 2015 epidemic strain. The co-circulation may have led to more serious clinical symptoms and a larger scale epidemic. This finding is of great importance in understanding the circulation of DENV and to strengthen the detection and management of dengue fever in border areas.

Purpose: This study aimed to evaluate the utility of a new plan feature (planomics feature) for predicting the results of patient-specific quality assurance using the head and neck (H&N) volumetric modulated arc therapy (VMAT) plan.Methods: One hundred and thirty-one H&N VMAT plans in our institution from 2019 to 2021 were retrospectively collected. Dosimetric verification for all plans was carried out using the portal dosimetry system integrated into the Eclipse treatment planning system based on the electronic portal imaging devices. Gamma passing rates (GPR) were analyzed using three gamma indices of 3%/3 mm, 3%/2 mm, and 2%/2 mm with a 10% dose threshold. Forty-eight conventional features affecting the dose delivery accuracy were used in the study, and 2,476 planomics features were extracted based on the radiotherapy plan file. Three prediction and classification models using conventional features (CF), planomics features (PF), and hybrid features (HF) combining two sets of features were constructed by the gradient boosting regressor (GBR) and Ridge classifier for each GPR of 3%/3 mm, 3%/2 mm, and 2%/2 mm, respectively. The absolute prediction error (APE) and the area under the curve (AUC) were adopted for assessing the performance of prediction and classification models.Results: In the GPR prediction, the average APE of the models using CF, PF, and HF was 1.3 ± 1.2%/3.6 ± 3.0%, 1.7 ± 1.5%/3.8 ± 3.5%, and 1.1 ± 1.0%/4.1 ± 3.1% for 2%/2 mm; 0.7 ± 0.6%/2.0 ± 2.0%, 1.0±1.1%/2.2 ± 1.8%, and 0.6 ± 0.6%/2.2 ± 1.9% for 3%/2 mm; and 0.4 ± 0.3%/1.2 ± 1.2%, 0.4±0.5%/1.3 ± 1.0%, and 0.3±0.3%/1.2 ± 1.1% for 3%/3 mm, respectively. In the regression prediction, three models give a similar modeling performance for predicting the GPR. The classification results were 0.67 ± 0.03/0.66 ± 0.07, 0.77 ± 0.03/0.73 ± 0.06, and 0.78 ± 0.02/0.75 ± 0.04 for 3%/3 mm, respectively. For 3%/2 mm, the AUCs of the training and testing cohorts were 0.64 ± 0.03/0.62 ± 0.07, 0.70 ± 0.03/0.67 ± 0.06, and 0.75 ± 0.03/0.71 ± 0.07, respectively, and for 2%/2 mm, the average AUCs of the training and testing cohorts were 0.72 ± 0.03/0.72 ± 0.06, 0.78 ± 0.04/0.73 ± 0.07, and 0.81 ± 0.03/0.75 ± 0.06, respectively. In the classification, the PF model has a better classification performance than the CF model. Moreover, the HF model provides the best result among the three classifications models.Conclusions: The planomics features can be used for predicting and classifying the GPR results and for improving the model performance after combining the conventional features for the GPR classification.

With the increase in wind turbine power, the size of the blades is significantly increasing to over 100 m. It is becoming more and more important to optimize the design for the internal layout of large-scale offshore composite wind turbine blades to meet the structural safety requirements while improving the blade power generation efficiency and achieving light weight. In this work, the full-scale internal layout of an NREL 5 MW offshore composite wind turbine blade is elaborately designed via the topology optimization method. The aerodynamic wind loads of the blades were first simulated based on the computational fluid dynamics. Afterwards, the variable density topology optimization method was adopted to perform the internal structure design of the blade. Then, the first and second generation multi-web internal layouts of the blade were reversely designed and evaluated in accordance with the stress level, maximum displacement of blade tip and fatigue life. In contrast with the reference blade, the overall weight of the optimized blade was reduced by 9.88% with the requirements of stress and fatigue life, indicating a better power efficiency. Finally, the vibration modal and full life cycle of the designed blade were analyzed. The design conception and new architecture could be useful for the improvement of advanced wind turbines.

Background: Xishuangbanna, a border area of China, Burma and Laos, had its first major DENV-1 outbreak in 2017. This study aims to explore the genetic characterization, potential source and evolution of the viruses in outbreak. Methods: The structural protein C/prM/E genes of viruses isolated from local residents or Burmese travelers were sequenced followed by mutation, phylogenetic, homologous recombination, molecular clock and demographic reconstruction analysis. Results: Phylogenetic analysis revealed that all of the strains were classified as three cluster of DENV-1. Cluster 1, 2 and 3 were most similar to China Guangzhou 2011, China Hubei 2014 and Laos 2008 strain, respectively. Among 236 base mutations, 31 caused nonsynonymous mutations when compared with the DENV-1SS. No homologous recombination signal was discovered. The structural protein of these strains had similar three-dimensional structure. Only site 434 showed differences among five predicted protein binding sites. Molecular clock phylogenetic and demographic reconstruction analysis showed that DENV-1 became highly diversified in 1972 followed by a slightly decreased period until 2017. Conclusions: Dengue isolated strains show diversification between Burma and China. Amino acid substitution (I440T) may lead to weakened virulence of the epidemic strains. DENV-1 became highly diversified in 1972 followed by a slightly decreased period. Keywords: Dengue virus type 1, Xishuangbanna, Molecular characterization, Structural gene

Simile recognition is to find simile sentences and extract the tenor and vehicle from these sentences. Previous works illustrate that tenors and vehicles are typically noun phrases. A word may have different part-of-speech (POS) labels (e.g., adjectives, adverbs, nouns, and verbs) in different sentences. It is important for the simile recognition task to identify a certain POS information for each word in a sentence. However, existing models use the same word embedding to represent a word, which cannot accurately represent the POS information of this word in different sentences. In this paper, we propose a neural network framework explicitly integrating the POS information into simile recognition task, with additional self-attention mechanism to better capture long term dependencies between any two tokens in sentences. The experimental results show that our proposed models significantly outperform previous state-of-the-art methods in the simile recognition task. We also present an analysis showing that the POS information and self-attention mechanism are effective for the simile recognition task.

ObjectivesTo compare the safety, immunogenicity, and immune persistence of hepatitis A (HA) vaccines between HBs-Ag-positive and -negative participants.Method9000 participants were enrolled in the phase IV study of live attenuated HA (HA-L) or inactivated HA (HA-I) vaccines. The HBs-Ag-positive subjects were detected and became an independent observation group. Adverse reactions (ARs), geometric mean concentrations (GMCs) and seroconversion rates (SRs) of the vaccines were analyzed at five time points until three years after vaccination. Results: 120 HBs-Ag-positive subjects were screened out, only 1 participant had grade 1 experienced ARs after HA-L injection. Except the time point of two years, the SRs of HBs-Ag-positive group were 100% for both vaccines. The GMCs were not statistically different between HBs-Ag-positive and -negative groups after the HA-L vaccination. The logarithmically transformed GMCs for HBs-Ag-positive and -negative groups were 3.21 mIU/mL (95% CI, 2.03-4.39 mIU/mL) and 2.95 mIU/mL (95% CI, 2.88-3.02 mIU/mL) 28 days after the HA-L vaccination, respectively.ConclusionsBoth HA-L and HA-I vaccines were safe for HBs-Ag-positive participants and may provide an excellent long-term protection against HAV in this study. The results indicated that people positive or negative for HBs-Ag can receive both HA-L and HA-I vaccines (ClinicalTrials.gov number, NCT02601040).

China is located in the intersection area of two seismic zones. Due to this special geographical location, earthquake disasters occur frequently in China. Earthquake emergency rescue work is one of the key construction works of disaster prevention and mitigation in China. This paper mainly studies the earthquake disaster rescue model based on the complex adaptive system theory and establishes the earthquake disaster rescue model by analyzing the complex adaptive system theory and combining the earthquake rescue process. In this paper, through the task allocation mechanism task, the disaster rescue task is divided into simple task and complex task, and the executive task subject is divided into single task subject and multitask subject. On the basis of considering the shortest emergency rescue time goal and the goal of maximizing the deployment utility of rescue team, the reasonable deployment of a rescue team is realized through a complex adaptive system, that is, the deployment utility of the rescue team is maximized. In this paper, the simulation experiment and comparison of the earthquake disaster rescue model based on the complex adaptive system theory are carried out. The experimental results show that the model used in this paper is better than the other two models in terms of algorithm convergence, rescue number, and overall score; in different scenarios, the relative survival probability of the model in this paper is 58.92%, 67.85%, and 77.46%, and the proportion of the wounded rescued is 66.31%, 76.45%, and 83.06%, which were higher than those of the other two models. The earthquake disaster rescue model based on the complex adaptive system theory proposed in this paper provides an effective theoretical basis and method system for postdisaster emergency rescue decision making and enhances and improves the emergency response ability to deal with large-scale geological disaster events.

Soil salinization is a global problem closely related to the sustainable development of social economy. Compared with frequently-used satellite-borne sensors, unmanned aerial vehicles (UAVs) equipped with multispectral sensors provide an opportunity to monitor soil salinization with on-demand high spatial and temporal resolution. This study aims to quantitatively estimate soil salt content (SSC) using UAV-borne multispectral imagery, and explore the deep mining of multispectral data. For this purpose, a total of 60 soil samples (0–20 cm) were collected from Shahaoqu Irrigation Area in Inner Mongolia, China. Meanwhile, from the UAV sensor we obtained the multispectral data, based on which 22 spectral covariates (6 spectral bands and 16 spectral indices) were constructed. The sensitive spectral covariates were selected by means of gray relational analysis (GRA), successive projections algorithm (SPA) and variable importance in projection (VIP), and from these selected covariates estimation models were built using back propagation neural network (BPNN) regression, support vector regression (SVR) and random forest (RF) regression, respectively. The performance of the models was assessed by coefficient of determination (R2), root mean squared error (RMSE) and ratio of performance to deviation (RPD). The results showed that the estimation accuracy of the models had been improved markedly using three variable selection methods, and VIP outperformed GRA and GRA outperformed SPA. However, the model accuracy with the three machine learning algorithms turned out to be significantly different: RF > SVR > BPNN. All the 12 SSC estimation models could be used to quantitatively estimate SSC (RPD > 1.4) while the VIP-RF model achieved the highest accuracy (Rc2 = 0.835, RP2 = 0.812, RPD = 2.299). The result of this study proved that UAV-borne multispectral sensor is a feasible instrument for SSC estimation, and provided a reference for further similar research.

Background: Stereotactic radiotherapy treats hepatocellular carcinoma (HCC) at different stages effectively and safely. Besides its direct killing of cancer cells, radiotherapy stimulates host immunity against hepatoma. However, the role of myeloid-derived suppressor cells (MDSCs) in on-target and off-target anti-HCC effects induced by hypofractionated irradiation (IR) is unclear.Methods and Materials: Hepa1-6 and H22 allogeneic transplanted tumors on hind limbs of C57BL/6 and Institute of Cancer Research (ICR) mice, respectively, were irradiated with 0, 2.5, 4, 6, or 8 Gy/fraction until the total dose reached 40 Gy. The off-target effect induced by the IR was investigated by subsequently inoculating the same HCC cells subcutaneously on the abdomen. MDSCs in peripheral blood and tumor tissues were measured by flow cytometry or immunofluorescence microscopy analysis. IL-6, regulated on activation normal T cell expressed and secreted (RANTES), and granulocyte colony-stimulating factor (G-CSF) in irradiated mouse plasma and hepatoma cell cultures were measured with ELISA kits. Conditioned media (CM) from irradiated HCC cell cultures on bone marrow cell differentiation and MDSC proliferation were examined by co-culture and flow cytometry.Results: Our study showed that the IR of primarily inoculated HCC on hind limbs created an “in situ tumor vaccine” and triggered the antitumor immunity. The immunity was capable of suppressing the growth of the same type of HCC subcutaneously implanted on the abdomen, accompanied with reduced MDSCs in both blood and tumors. The decreased MDSCs were associated with low plasma levels of IL-6, RANTES, and G-CSF. The cytokines IL-6 and RANTES in the CM were lower in the high single IR dose group than in the control groups, but G-CSF was higher. The CM from high single-dose IR-Hepa1-6 cell culture reduced the differentiation of C57BL/6 mouse bone marrow cells into MDSCs, whereas CM from high single-dose IR-H22 cells reduced the proliferation of MDSCs, which might be due to the decreased p-STAT3 in bone marrow cells.Conclusions: The hypofractionated IR on transplanted tumors at the primary location exerted a strong antitumor effect on the same tumor at a different location (off target). This abscopal effect is most likely through the reduction of MDSCs and decrease of IL-6, RANTES, and G-CSF.