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Abstract Background APRI and FIB-4 scores are used to exclude clinically significant fibrosis (defined as stage ≥ F2) in patients with chronic viral hepatitis. However, the cut-offs for these scores (generated by Youden indices) vary between different patient cohorts. This study aimed to evaluate whether serum dithiothreitol-oxidizing capacity (DOC), i.e., a surrogate test of quiescin sulfhydryl oxidase-1, which is a matrix remodeling enzyme, could be used to non-invasively identify significant fibrosis in patients with various chronic liver diseases (CLDs). Methods Diagnostic performance of DOC was compared with APRI and FIB-4 for identifying significant fibrosis. ROC curve analyses were undertaken in: a) two chronic hepatitis B (CHB) cohorts, independently established from hospitals in Wenzhou (n = 208) and Hefei (n = 120); b) a MASLD cohort from Wenzhou hospital (n = 122); and c) a cohort with multiple CLD etiologies (except CHB and MASLD; n = 102), which was identified from patients in both hospitals. Cut-offs were calculated using the Youden index. All CLD patients (n = 552) were then stratified by age for ROC curve analyses and cut-off calculations. Results Stratified by CLD etiology or age, ROC curve analyses consistently showed that the DOC test was superior to APRI and FIB-4 for discriminating between clinically significant fibrosis and no fibrosis, when APRI and FIB-4 showed poor/modest diagnostic performance (P 0.05 in 11 cohort comparisons). DOC had a significant advantage over APRI or FIB-4 scores for establishing a uniform cut-off independently of age and CLD etiology (coefficients of variation of DOC, APRI and FIB-4 cut-offs were 1.7%, 22.9% and 47.6% in cohorts stratified by CLD etiology, 2.0%, 26.7% and 29.5% in cohorts stratified by age, respectively). The uniform cut-off was 2.13, yielded from all patients examined. Surprisingly, the uniform cut-off was the same as the DOC upper limit of normal with a specificity of 99%, estimated from 275 healthy control individuals. Hence, the uniform cut-off should possess a high negative predictive value for excluding significant fibrosis in primary care settings. A high DOC cut-off with 97.5% specificity could be used for detecting significant fibrosis (≥ F2) with an acceptable positive predictive value (87.1%). Conclusions This proof-of-concept study suggests that the DOC test may efficiently rule out and rule in significant liver fibrosis, thereby reducing the numbers of unnecessary liver biopsies. Moreover, the DOC test may be helpful for clinicians to exclude significant liver fibrosis in the general population.

Due to the excellent nuclear properties，99mTc has been used in the field of early diagnosis of tumor and nuclear medicine imaging. As the most widely applied radioisotope，it accounts for more than 70% of the market of total radioisotopes used in the nuclear medicine diagnosis. Until now，99mTc in clinical has been prepared by the 99Mo-99mTc generators. To improve the disadvantages of current technologies including unstable supplement of the fission 99Mo for the fission-type 99Mo-99mTc generator and long production time for the gel-type 99Mo-99mTc generator，a new irradiated-type 99Mo-99mTc generator filled with the Ti99Mo has been developed. The effects of the chemical agents，Mo:Ti molar ratio，dry methods on the elution properties of the Ti99Mo-based 99Mo-99mTc generator were investigated. Based on the results of simulation experiments and performance tests，the elution from the irradiated-type 99Mo-99mTc generator was found to be accorded with medical standard. During the seven elution processes，the radionuclidic purity of sodium technetium-99m solution was above 99.92%，the radiochemical purity was higher than 98.8%，the pH value was between 5.0 and 6.0 and the average elution efficiency reached 72.07%，the peak of elute curve was located at 2-4 mL without the phenomenon of trailing，showing the excellent performance. The synthesized preparation has been advanced before the process of irradiation by the reactor，to simplify the operational radioactive procedures，shorten the production time，increase the elution efficiency of the generator and decrease the loss of 99Mo decay.

To explore the protective effects of water extracts from different Ganoderma lucidum (G. lucidum) mycelium on ethanol-induced hepatocyte injury in LO2 cells. The effects of water extracts obtained from different G. lucidum mycelium against ethanol-induced damage to LO2 cells were examined in this research. Cell survival rate, alanine aminotransferase (ALT), aspartate aminotransferase (AST), reactive oxygen species (ROS), superoxide dismutase (SOD), glutathione (GSH) and malondialdehyde (MDA) levels were measured in a liver injury model employing ethanol-induced LO2 cells, to assess the preventive effects of G. lucidum mycelium water extracts against ethanol-induced damage. The results showed that water extracts from the mycelium of all seven strains exhibited varying degrees of protective effects. Among them, the water extract from strains G0119 and G0154 had the best protective effect. Compared with the model group, the intervention of water extracts significantly increased LO2 cell survival (P

Abstract Diabetic retinopathy (DR) is one of the leading causes of adult blindness in the United States. Although studies applying traditional statistical methods have revealed that heavy metals may be essential environmental risk factors for diabetic retinopathy, there is a lack of analyses based on machine learning (ML) methods to adequately explain the complex relationship between heavy metals and DR and the interactions between variables. Based on characteristic variables of participants with and without DR and heavy metal exposure data obtained from the NHANES database (2003–2010), a ML model was developed for effective prediction of DR. The best predictive model for DR was selected from 11 models by receiver operating characteristic curve (ROC) analysis. Further permutation feature importance (PFI) analysis, partial dependence plots (PDP) analysis, and SHapley Additive exPlanations (SHAP) analysis were used to assess the model capability and key influencing factors. A total of 1042 eligible individuals were randomly assigned to two groups for training and testing set of the prediction model. ROC analysis showed that the k-nearest neighbour (KNN) model had the highest prediction performance, achieving close to 100% accuracy in the testing set. Urinary Sb level was identified as the critical heavy metal affecting the predicted risk of DR, with a contribution weight of 1.730632 ± 1.791722, which was much higher than that of other heavy metals and baseline variables. The results of the PDP analysis and the SHAP analysis also indicated that antimony (Sb) had a more significant effect on DR. The interaction between age and Sb was more significant compared to other variables and metal pairs. We found that Sb could serve as a potential predictor of DR and that Sb may influence the development of DR by mediating cellular and systemic senescence. The study revealed that monitoring urinary Sb levels can be useful for early non-invasive screening and intervention in DR development, and also highlighted the important role of constructed ML models in explaining the effects of heavy metal exposure on DR.

Abstract The van der Waals antiferromagnetic topological insulator MnBi2Te4 represents a promising platform for exploring the layer-dependent magnetism and topological states of matter. Recently observed discrepancies between magnetic and transport properties have aroused controversies concerning the topological nature of MnBi2Te4 in the ground state. In this article, we demonstrate that fabrication can induce mismatched even-odd layer dependent magnetotransport in few-layer MnBi2Te4. We perform a comprehensive study of the magnetotransport properties in 6- and 7-septuple-layer MnBi2Te4, and reveal that both even- and odd-number-layer device can show zero Hall plateau phenomena in zero magnetic field. Importantly, a statistical survey of the optical contrast in more than 200 MnBi2Te4 flakes reveals that the zero Hall plateau in odd-number-layer devices arises from the reduction of the effective thickness during the fabrication, a factor that was rarely noticed in previous studies of 2D materials. Our finding not only provides an explanation to the controversies regarding the discrepancy of the even-odd layer dependent magnetotransport in MnBi2Te4, but also highlights the critical issues concerning the fabrication and characterization of 2D material devices.

Air pollution stands as the single largest environmental risk to human health globally, and negative air ions (NAIs) serve as essential indicators for measuring regional air quality. They play a crucial role in alleviating the pressure and risks posed by air pollution. NAIs are notably abundant in forests, where the photosynthesis of vegetation serves as a significant factor influencing their presence. However, a dearth of quantitative research exists regarding the relationship between vegetation photosynthesis and NAIs. Current literature only offers qualitative insights, suggesting that vegetation photosynthesis may foster NAIs production. The mechanisms through which the photosynthetic process influences NAIs and the potential contribution of forest vegetation to NAIs remain unclear, lacking quantitative investigation. In this study, Quercus variabilis, a typical tree species in the warm temperate zone, was chosen as the research subject. We examined the dynamic changes in NAIs and net ecosystem productivity (NEP) from 2019 to 2021. The results demonstrated a strong correlation between NAIs and NEP at the ecosystem scale during the primary vegetation growing season. NEP effectively tracked daily changes in NAIs and exhibited a good fit. Notably, the scatter plots of NAIs and NEP exhibited clear stratification under varying photosynthetically active radiation (PAR) intensities. The correlation between NAIs and NEP was significantly higher under high PAR conditions compared to low PAR conditions, with R2 values of 0.458 and 0.367, respectively. Consequently, NEP emerges as a superior indicator for tracking NAIs variation characteristics at the ecosystem scale compared to PAR. This finding offers a rapid and accurate evaluation method for discerning the spatial and temporal distribution patterns of NAIs within forest ecosystems. Such insights provide a theoretical foundation for further assessing the potential contribution of forest vegetation to NAIs.

Vegetation phenology serves as an important indicator for climate change and plays a crucial role in affecting the terrestrial water, energy, and carbon cycles. The green chromatic coordinate (GCC) obtained from digital repeat photographs has been widely applied in estimating phenology from the perspective of greenness, while the performance of satellite derived GCC is not well understood. We used flux tower GPP from seven deciduous broadleaf forest (DBF) and three grassland (GRA) sites over the Northern Hemisphere. The aim was to compare phenological events with GCC (obtained from digital repeat photographs and satellite remote sensing (GCCMODIS)) and the enhanced vegetation index (EVI). Meanwhile, we also explored the performance of these three indices in simulating GPP utilizing the light use efficiency (LUE) model at the DBF and GRA sites. Phenology retrieved by GCC, GCCMODIS, and EVI was all significantly correlated with GPP-estimated values at all sites (P

Diquat (DQ) is a commonly used bipyridine herbicide known for its toxic properties and adverse effects on individuals. However, the mechanism underlying DQ-induced damage remain elusive. Our research aimed to uncover the regulatory network involved in DQ-induced damage. We analyzed publicly accessible gene expression patterns and performed research using a DQ-induced damage animal model. The GSE153959 dataset from the Gene Expression Omnibus collection and the animal model of DQ-induced kidney injury were used to identify differentially expressed genes (DEGs). Pathways including the regulation of DNA-templated transcription in response to stress, RNA polymerase II transcription regulator complex and transcription coregulatory activity were shown to be enriched in 21 DEGs. We used least absolute shrinkage and selection operator (LASSO) regression analysis to find possible diagnostic biomarkers for DQ-induced damage. Then, we used an HK-2 cell model to confirm these results. Additionally, we confirmed that 3-hydroxy-3-methylglutaryl-CoA synthase 2 (HMGCS2) was the major gene associated with DQ-induced damage using multi-omics screening. The sample validation strongly suggested that HMGCS2 has promise as a diagnostic marker and may provide new targets for therapy in the context of DQ-induced damage.

During a hospital visit, a significant volume of Gastroscopy Diagnostic Text (GDT) data are produced, representing the unstructured gastric medical records of patients undergoing gastroscopy. As such, GDTs play a crucial role in evaluating the patient’s health, shaping treatment plans, and scheduling follow-up visits. However, given the free-text nature of GDTs, which lack a formal structure, physicians often find it challenging to extract meaningful insights from them. Furthermore, while deep learning has made significant strides in the medical domain, to our knowledge, there are not any readily available text-based pre-trained models tailored for GDT classification and analysis. To address this gap, we introduce a Bidirectional Encoder Representations from Transformers (BERT) based three-branch classification network tailored for GDTs. We leverage the robust representation capabilities of the BERT pre-trained model to deeply encode the texts. A unique three-branch decoder structure is employed to pinpoint lesion sites and determine cancer stages. Experimental outcomes validate the efficacy of our approach in GDT classification, with a precision of 0.993 and a recall of 0.784 in the early cancer category. In pinpointing cancer lesion sites, the weighted F1 score achieved was 0.849.

Abstract Background To characterize the current state of emergency medicine (EM) and the requirements for advancing EM clinical practice, education and research in China. Methods An anonymous electronic survey was conducted by Chinese Society of Emergency Medicine during September to October 2021. The survey contained 30 questions divided into 2 sections: the current state of EM development and the requirements for EM growth. Results 722 hospitals were included, of 487 were Level III and 235 were Level II hospitals. We found that after 40 years of development, EM had established a mature disciplinary system and refined sub-specialties including critical care, cardiopulmonary resuscitation, toxicology, disaster and emergency rescue. In Level III hospitals, 70.8% of EDs were standardized training centers for EM residents, but master’s degree program, Doctor Degree program and post-doctoral degree program was approved in only 37.8%, 8.4% and 2.9% of EDs respectively and postgraduate curriculum was available in 1/4 of EDs. Only 8% have national or provincial key laboratories. In addition to advance clinical practice, there was also a high demand to improve teaching and research capacities, mainly focusing on literature review, research design and delivery, paper writing, residency training. Conclusions EM has built a mature discipline system and refined sub-specialties in China. Teaching and research developed parallel with clinical practice. However, there was still a lack of EM master’s and doctoral programs and research capacities need to be improved. More outstanding clinical and academic training should be provided to promote the rapid growth of EM in China.

Abstract The TRIZ theory was used to accurately discover the problems to be solved in the design of roadway surrounding rock control technology. This paper tried to solve the complex issue of surrounding rock control in deep roadways from a new perspective. Based on the functional component analysis and causal axis analysis of the problem’s primary reason, simultaneously, the surrounding rock control technology was optimized through technical contradiction analysis, physical contradiction analysis, and substance and field model analysis. As a result, a fully enclosed wire-shell support technology was proposed. Finally, taking the typical soft rock roadway engineering of Pansan Coal Mine in Huainan Mining Area, Anhui Province, China, as the engineering background, the engineering application and effect evaluation were completed. This paper provides a reference for controlling the instability of deep soft rock roadways in coal mines. A new idea of optimizing roadway support engineering based on TRIZ theory was proposed.

Change detection is a crucial remote sensing (RS) application because it can locate the interesting changed regions and provide corresponding time-series information with multitemporal RS images acquired in the same region. Synthetic aperture radar (SAR), with the advantages of all-day and all-weather conditions, can achieve high-resolution imaging from long operation distances. Moreover, the coherence imaging characteristics of the SAR system cause the attained complex-value images to be more sensitive to ground surface features. Traditional intensity-based change detection methods merely use the intensity difference between multitemporal images; thus, the results only reflect the significant landmark changes, such as seismic disasters and flood disasters. In this article, we use the coherent imaging characteristics of the SAR complex images to detect very subtle changes, such as vehicle tracks and footprints. Specifically, coherent change detection based on amplitude and phase generates a difference image utilizing the repeat-pass repeat-geometry SAR images, while the global attention-based convolutional neural network achieves automatic subtle change track extraction from the difference images. The experimental results based on our measured airborne SAR data demonstrate that our proposed method reduces the sensitivity of the detectable changed region from the meter level to the centimeter level, further providing our method with the ability to detect very subtle changes, such as vehicle tire tracks or footprints by human activities. This subtle change detection capability can be used for the search and rescue of vehicles and personnel lost in the field.

Plant community characteristics and soil properties are critical indicators for evaluating wetland degradation and restoration. In order to investigate how the degradation of inland salt marsh wetlands affects plants and soils as well as the response relationship between plants and soils under different degradation degrees, this paper selected inland salt marsh wetlands with different degradation degrees in the wetland area of western Songnen Plain, and analyzed the characteristics of plant communities, soils and their relationships. The results show that: that the important value of Gramineae plants decreased by about 21% with increasing degradation, while the vital value of Cyperaceae and weeds increased by 10% and 9%, respectively. Plant height decreased significantly, and coverage and density showed a decreasing and then increasing trend. Overall, species diversity shows a trend of increasing and then decreasing, indicating that the structure of plant communities tends to be more straightforward and more complex with increasing degradation. Soil electrical conductivity, total organic carbon (TOC) and total nitrogen (TN) content decreased significantly with the degree of degradation from ND (non degradation) to HD (heavy degradation) by 34.08%, 19.56%, and 35.82%, respectively. Soil C:N increased from 13.13 to 17.97. Soil N:P and C:P decreased from 5.56 to 3.28 and from 71.59 to 54.02, respectively. Soil factors affecting wetland plants were inconsistent at different stages of degradation. Changes in soil nitrogen and phosphorus content were correlated with changes in wetland vegetation community structure. Therefore, exploring how wetland degradation affects plants and soils can provide a scientific basis for wetland degradation assessment and wetland restoration.

Abstract Objectives Development and validation of a computed tomography urography (CTU)‐based machine learning (ML) model for prediction of preoperative pathology grade of upper urinary tract urothelial carcinoma (UTUC). Methods A total of 140 patients with UTUC who underwent CTU examination from January 2017 to August 2023 were retrospectively enrolled. Tumor lesions on the unenhanced, medullary, and excretory periods of CTU were used to extract Features, respectively. Feature selection was screened by the Pearson and Spearman correlation analysis, least absolute shrinkage and selection operator algorithm, random forest (RF), support vector machine (SVM), and eXtreme Gradient Boosting (XGBoost). The logistic regression (LR) was used to screen for independent influencing factors of clinical baseline characteristics. Machine learning models based on different feature datasets were constructed and validated using algorithms such as LR, RF, SVM, and XGBoost. By computing the selected features, a radiomics score was generated, and a diverse feature dataset was constructed. Based on the training set, 16 ML models were created, and their performance was evaluated using the validation set for metrics including sensitivity, specificity, accuracy, area under the receiver operating characteristic curve (AUC), and others. Results The training set consisted of 98 patients (mean age: 64.5 ± 10.5 years; 30 males), whereas the validation set consisted of 42 patients (mean age: 65.3 ± 9.78 years; 17 males). Hydronephrosis was the best independent influence factor (p

What is the impact of environmental management system certification on green innovation performance, and is it a futile endeavor or a profitable one? Grounded in the principles of ecological civilization construction and green development, this study embarks on a comprehensive examination. Initially, it investigates the varying impacts of environmental management system certification on both traditional innovation performance and green innovation performance. Subsequently, it dissects the underlying mechanisms and moderating factors influencing the latter, including an exploration of intermediary effects. The empirical findings of this study are as follows: (i) Environmental management system certification emerges as a catalyst for innovation performance, with the primary impact observed in the realm of green innovation performance. (ii) Social responsibility disclosure is identified as a mediating factor in the relationship between environmental management system certification and green innovation performance. (iii) Larger enterprises, those equipped with robust equity incentives, and those operating in less competitive markets are more prone to benefit from the impact of environmental management system certification on social responsibility disclosure. This, in turn, amplifies the promotion of green innovation performance. However, the moderating effect of property rights on the mediating path remains statistically insignificant. (iv) Environmental management system certification exerts a more pronounced influence on green innovation performance in regions characterized by lower economic development. Moreover, it particularly stimulates exploratory green innovation performance, surpassing its impact on exploitative green innovation performance.

RNA molecules serve a wide range of functions that are closely linked to their structures. The basic structural units of RNA consist of single- and double-stranded regions. In order to carry out advanced functions such as catalysis and ligand binding, certain types of RNAs can adopt higher-order structures. The analysis of RNA structures has progressed alongside advancements in structural biology techniques, but it comes with its own set of challenges and corresponding solutions. In this review, we will discuss recent advances in RNA structure analysis techniques, including structural probing methods, X-ray crystallography, nuclear magnetic resonance, cryo-electron microscopy, and small-angle X-ray scattering. Often, a combination of multiple techniques is employed for the integrated analysis of RNA structures. We also survey important RNA structures that have been recently determined using various techniques.

Abstract The use of exogenous mitochondria to replenish damaged mitochondria has been proposed as a strategy for the treatment of pulmonary fibrosis. However, the success of this strategy is partially restricted by the difficulty of supplying sufficient mitochondria to diseased cells. Herein, we report the generation of high-powered mesenchymal stem cells with promoted mitochondrial biogenesis and facilitated mitochondrial transfer to injured lung cells by the sequential treatment of pioglitazone and iron oxide nanoparticles. This highly efficient mitochondrial transfer is shown to not only restore mitochondrial homeostasis but also reactivate inhibited mitophagy, consequently recovering impaired cellular functions. We perform studies in mouse to show that these high-powered mesenchymal stem cells successfully mitigate fibrotic progression in a progressive fibrosis model, which was further verified in a humanized multicellular lung spheroid model. The present findings provide a potential strategy to overcome the current limitations in mitochondrial replenishment therapy, thereby promoting therapeutic applications for fibrotic intervention.

Abstract Purpose ​Develop and validate a nomogram prediction model for hypertension-diabetes comorbidities based on chronic disease management in the community. Patients and methods The nomogram prediction model was developed in a cohort of 7200 hypertensive patients at a community health service center in Hongshan District, Wuhan City. The data were collected from January 2022 to December 2022 and randomly divided into modeling and validation groups at a 7:3 ratio. The Lasso regression model was used for data dimensionality reduction, feature selection, and clinical test feature construction. Multivariate logistic regression analysis was used to build the prediction model. Results The application of the nomogram in the verification group showed good discrimination, with an AUC of 0.9205 (95% CI: 0.8471–0.9527) and a good calibration effect. Decision curve analysis demonstrated that the predictive model was clinically useful. Conclusion This study presents a nomogram prediction model that incorporates age, waist-height ratio and elevated density lipoprotein cholesterol (HDL-CHOLESTEROL), which can be used to predict the risk of codeveloping diabetes in hypertensive patients.

Abstract Novel viewpoint image synthesis is very challenging, especially from sparse views, due to large changes in viewpoint and occlusion. Existing image-based methods fail to generate reasonable results for invisible regions, while geometry-based methods have difficulties in synthesizing detailed textures. In this paper, we propose STATE, an end-to-end deep neural network, for sparse view synthesis by learning structure and texture representations. Structure is encoded as a hybrid feature field to predict reasonable structures for invisible regions while maintaining original structures for visible regions, and texture is encoded as a deformed feature map to preserve detailed textures. We propose a hierarchical fusion scheme with intra-branch and inter-branch aggregation, in which spatio-view attention allows multi-view fusion at the feature level to adaptively select important information by regressing pixel-wise or voxel-wise confidence maps. By decoding the aggregated features, STATE is able to generate realistic images with reasonable structures and detailed textures. Experimental results demonstrate that our method achieves qualitatively and quantitatively better results than state-of-the-art methods. Our method also enables texture and structure editing applications benefiting from implicit disentanglement of structure and texture. Our code is available at http://cic.tju.edu.cn/faculty/likun/projects/STATE .

Abstract Objectives To build a nomogram prediction model, assess its predictive ability, and perform a survival decision analysis on patients with muscle‐invasive bladder cancer (MIBC) to study risk factors affecting overall survival (OS). Methods A retrospective analysis was performed on the clinical information of 262 patients with MIBC who underwent radical cystectomy (RC) at the Urology Department of the Second Affiliated Hospital of Kunming Medical University between July 2015 and August 2021. The final model variables that were included were chosen using single‐factor stepwise Cox regression, optimal subset regression, and LASSO regression + cross‐validation with the minimum AIC value. The next step was to do a multivariate Cox regression analysis. The establishment of a nomogram model by fitting and the screening out of independent risk factors impacting the survival of patients with MIBC having radical resection. Receiver Activity Characteristic curves, C‐index, and a calibration plot evaluated the prediction accuracy, validity, and clinical benefit of the model. The 1‐, 3‐, and 5‐year survival rates were then computed for each risk factor using a Kaplan–Meier survival analysis. Results 262 eligible patients in total were enrolled. With a median follow‐up of 32 months, the follow‐up period ranged from 2 to 83 months. 171 cases (65.27%) survived while 91 cases (34.73%) perished. Age (HR = 1.06 [1.04; 1.08], p = 0.001), preoperative hydronephrosis (HR = 0.69 [0.46, 1.05], p = 0.087), T stage (HR = 2.06 [1.09, 3.93], p = 0.027), lymphovascular invasion (LVI, HR = 1.73 [1.12, 2.67], p = 0.013), prognostic nutritional index (PNI, HR = 1.70 [1.09, 2.63], p = 0.018), and neutrophil‐to‐lymphocyte ratio (NLR, HR = 0.52 [0.29, 0.93)], p = 0.026) were independent risk factor for the survival of bladder cancer patients. Create a nomogram based on the aforementioned findings, and then draw the 1‐year, 3‐year, and 5‐year OS receiver operating characteristic curves by the nomogram. The AUC values were 0.811 (95% CI [0.752, 0.869]), 0.814 (95% CI [0.755, 0.873]), and 0.787 (95% CI [0.708, 0.865]), respectively, and the calibration plot matched the predicted value well. The 1‐year, 3‐year, and 5‐year decision curve analyses were higher than the ALL line and None line at threshold values of >5%, 5%–70%, and 20%–70% indicating that the model has good clinical applicability. The calibration plot for the Bootstrap 1000‐time resampled validation model was similar to the actual value. Patients with preoperative combination hydronephrosis, higher T‐stage, combined LVI, low PNI, and high NLR had worse survival, according to Kaplan–Meier survival analysis for each variable. Conclusions This study might conclude that PNI and NLR were separate risk factors that affect a patient's OS after RC for MIBC. The prognosis of bladder cancer may be predicted by PNI and NLR, but additional confirmation in randomized controlled trials is required.

Photocatalysis technology is an economical and effective new energy technology which depends on the conversion and storage of light energy through an energy transfer process or charge transfer process. Recently, organic semiconductor photocatalytic materials with the advantages of controllable structure, broad spectral response, designability, and flexibility have received wide attention. In particular, the organic polymeric materials containing poly-perylene diimides (PDI) show significant promise in the realm of photocatalysis due to their impressive catalytic capabilities and wide spectral reactivity. However, a poor charge separation and transportation (CST) process undermines their photocatalytic efficiency in most polymer photocatalysts, as well as in PDI photocatalysts. In this context, we propose a new strategy through regulating the monomer symmetry to construct highly efficient PDI photocatalysts. As proof-of-concept, a series of new PDI-based organic supramolecular photocatalytic materials with full visible spectral response from the perspectives of both the π-π conjugated structure and the symmetry of chain structure are successfully synthesized. Meanwhile, the structural compositions, morphology features, electrical properties, and photocatalytic performances of those obtained PDI photocatalysts were systematically studied. The results shown that the as-prepared PDI-1,5NDA exhibits 1.6-fold and 3.7-fold higher levels of photosynthesis of H2O2 activity than those of PDI-1,4NDA and PDI-PDA, respectively, which could be ascribe to its lower symmetry and large π-conjugate systems greatly enhances the separation of charge carriers.

Smoking is a pathogenic factor for pulmonary hypertension (PH). Our previous study showed that serum miR-21 levels are elevated in smokers. miR-21 is considered as engaged in the PH process; however, its mechanisms remain unclear. In this investigation, we found that in the lung tissue of smoking-induced PH patients, the levels of miR-21 and aging markers (p21 and p16) were upregulated, and the function of pulmonary vascular endothelial cells was also impaired. Exposure of mice to cigarette smoke (CS) for four months caused similar changes in lung tissues and increased pulmonary arterial pressure, which were attenuated by knockout of miR-21. Further, human umbilical vein endothelial cells (HUVECs) exposed to cigarette smoke extract (CSE) revealed upregulation of miR-21 levels, depression of PTEN, activation of PI3K/AKT/mTOR signaling, an increase in senescence indexes, and enhanced dysfunction. Inhibiting miR-21 overexpression reversed the PTEN-mTOR signaling pathway and prevented senescence and dysfunction of HUVECs. In sum, our data indicate that miR-21-mediated endothelial senescence and dysfunction are involved in CS-induced PH through the activation of PI3K/AKT/mTOR signaling, which suggests that selective miR-21 inhibition offers the potential to attenuate PH.

The authors of this Comment are longstanding selenium investigators with a total of 200 or more published articles on selenium; the corresponding author (Margaret P [...]

Monitoring drought stress is crucial for estimating productivity and assessing the health status of forest ecosystems under global climate change. Solar-induced chlorophyll fluorescence (SIF) is mechanistically coupled to photosynthesis and has advantages over greenness-based vegetation indices in detecting drought. In recent years, SIF has commonly been used in monitoring drought stress in crop ecosystems. However, the response of tower-based SIF to drought stress in forest ecosystems remains unclear. In this study, we investigated the potential of tower-based SIF to monitor drought, which was quantified using the plant water stress index (PWSI) in a Chinese cork oak plantation. The results show the negative effect of drought on SIF, and afternoon depression of SIF emission under drought stress was observed. Canopy SIF (F) exhibited a nonlinear relationship with PWSI, while the quantum yield of SIF (ΦF) exhibited a significant linear relationship with PWSI at 687 nm and 760 nm (ΦF687: R2 = 0.90; ΦF760: R2 = 0.85). Incident radiation (PAR) and canopy structure affected the response of SIF to drought stress, with PAR as the main factor causing the nonlinear relationship between F and PWSI. Afternoon depression was described as the afternoon/morning ratio (AMR). AMRF and AMRΦF exhibited a negative linear response to PWSI. AMRF was less affected than F by PAR and canopy structures, and AMRΦF was more physiologically representative than ΦF. Moreover, AMRΦF was sensitive to VPD and REW, and it might be a good indicator of drought. Red SIF was more sensitive to drought than far-red SIF, as the R2 of PWSI with AMRΦF687 (R2 = 0.89) was higher than that with AMRΦF687 (R2 = 0.84). These results highlight the potential of tower-based SIF, especially red SIF, for drought monitoring in a plantation, and consideration of the physiological diurnal variation in SIF under drought stress is crucial for improving the accuracy of drought stress monitoring.

Evapotranspiration is a key link in the water cycle of terrestrial ecosystems, and the partitioning of evapotranspiration is a prerequisite for diagnosing vegetation growth and water use strategies. In this study, we used double-layer eddy covariance (DLEC) measurements within and above the canopy of poplar plantations to divide evapotranspiration into transpiration and evaporation during the growing season. We diagnosed the coupling state of airflows in the canopy vertical layer and found that the daytime coupling state at the half-hourly scale can mask nighttime decoupling. Furthermore, we investigated the daytime and nighttime vertical layer airflow coupling states separately and quantified the effects of coupling states on the DLEC of resolved transpiration. The partitioning results of the DLEC method were taken as the standard after the airflow coupling test. Then, the performance and accuracy of evapotranspiration partitioning for the modified relaxed eddy accumulation (MREA), the conditional eddy covariance (CEC), and the flux variance similarity (FVS) with DLEC were compared. Transpiration calculated from MREA showed the best agreement with DLEC, and the other methods showed different degrees of underestimation (1:1 slope = 0.64–0.83). Evaporation calculated from FVS showed the best agreement with DLEC, while CEC and FVS made an overestimation of more than 26% (1:1 slope = 1.26–1.99), but MREA made an underestimation from 5% to 35% (1:1 slope = 0.65–0.95). The correlation coefficients between DLEC and MREA for transpiration were 0.95–0.97 with RMSEs of 15.52–17.04 W m−2, and those between DLEC and FVS for transpiration were 0.73–0.78 with RMSEs of 10–21.26 W m−2 at the daily half-hourly scale. A detailed comparison of the differences between DLEC and evapotranspiration partitioning methods from high-frequency eddy covariance data under the condition of canopy vertical layer airflow mixing provides knowledge about the consistency of results for evapotranspiration partitioning in poplar plantation forests.

Point cloud registration is an important task in computer vision and robotics which is widely used in 3D reconstruction, target recognition, and other fields. At present, many registration methods based on deep learning have better registration accuracy in complete point cloud registration, but partial registration accuracy is poor. Therefore, a partial point cloud registration network, HALNet, is proposed. Firstly, a feature extraction network consisting mainly of adaptive graph convolution (AGConv), two-dimensional convolution, and convolution block attention (CBAM) is used to learn the features of the initial point cloud. Then the overlapping estimation is used to remove the non-overlapping points of the two point clouds, and the hybrid attention mechanism composed of self-attention and cross-attention is used to fuse the geometric information of the two point clouds. Finally, the rigid transformation is obtained by using the fully connected layer. Five methods with excellent registration performance were selected for comparison. Compared with SCANet, which has the best registration performance among the five methods, the RMSE(R) and MAE(R) of HALNet are reduced by 10.67% and 12.05%. In addition, the results of the ablation experiment verify that the hybrid attention mechanism and fully connected layer are conducive to improving registration performance.

Abstract Background The prognosis prediction of locally advanced rectal cancer (LARC) was important to individualized treatment, we aimed to investigate the performance of ultra-high b-value DWI (UHBV-DWI) in progression risk prediction of LARC and compare with routine DWI. Methods This retrospective study collected patients with rectal cancer from 2016 to 2019. Routine DWI (b = 0, 1000 s/mm2) and UHBV-DWI (b = 0, 1700 ~ 3500 s/mm2) were processed with mono-exponential model to generate ADC and ADCuh, respectively. The performance of the ADCuh was compared with ADC in 3-year progression free survival (PFS) assessment using time-dependent ROC and Kaplan-Meier curve. Prognosis model was constructed with ADCuh, ADC and clinicopathologic factors using multivariate COX proportional hazard regression analysis. The prognosis model was assessed with time-dependent ROC, decision curve analysis (DCA) and calibration curve. Results A total of 112 patients with LARC (TNM-stage II-III) were evaluated. ADCuh performed better than ADC for 3-year PFS assessment (AUC = 0.754 and 0.586, respectively). Multivariate COX analysis showed that ADCuh and ADC were independent factors for 3-year PFS (P

The pressure analysis and flow characteristics during the flight of a high-speed bullet are significant for aerodynamic performance, flight trajectory control, safety and reliability, performance optimization, guidance and navigation. To accurately monitor the pressure variation for a high-speed bullet in the high-altitude flight, a novel local fluid domain method is introduced in current study. This method overcomes the limitations of conventional global fluid domain simulation methods, which often suffer from poor convergence and stability issues. On the basis, the force analysis is conducted and the mathematical model for the theoretical trajectory is established, which is applied to simulate the flight trajectory and construct fluid domain for the high-speed bullet. The findings reveal that monitoring points within the bullet hole are influenced by both cavity flow and the collision of forward airflows during the high-altitude flight. Furthermore, it is observed that the absolute total pressure and reference pressure at these monitoring points within the bullet hole are influenced by altitude variations. Subsequently, the factors affecting the absolute total pressure within the hole are explored, including the hole depth, the hole diameter, the hole position, and the bullet orientation. The results indicate that modifying the bullet structure to incorporate 45° angled hole, as opposed to standard holes, can lead to a 13.6% reduction in absolute total pressure variation. Additionally, mitigating the interaction between the external and internal fluids emerges as a critical factor in reducing absolute total pressure within the hole. This research not only presents a fresh perspective for pressure monitoring within the bullet hole, but also establishes a theoretical foundation for the precise guidance of high-altitude bullets.

Abstract The cosmic‐ray neutron probe (CRNP) is a mesoscale and noninvasive method for measuring soil moisture and has been widely studied and applied. However, studies of its applicability in rocky mountainous areas are still challenging in complex topography and high gravel content. In this study, a field experiment was carried out to assess the applicability of the CRNP for measuring soil moisture in rocky areas of Taihang Mountains of North China. The results showed that the Pearson correlation coefficient and the root mean square error between the soil moisture from CRNP and the drying method are 0.911 and 0.025 m3 m−3, respectively, indicating that the CRNP can estimate the average soil moisture well in the study area. Compared with the capacitive sensor, the CRNP overestimated soil moisture when small rainfall events occurred, which was caused by the interception of canopy and litter. The nonlinear weighting method performed better than the linear weighting method in representing average soil moisture within the CRNP footprint. The high gravel content that contained high lattice water content reduced the penetration depth of CRNP. Biomass reduces the accuracy of the CRNP by affecting the neutron intensity. In summary, CRNP can measure soil moisture accurately in rocky areas of the Taihang Mountains, especially in dry environments with low biomass.

To improve the long-term performance of concrete engineering in high-altitude areas, waste tire rubber was added to a concrete mix, and freeze–thaw and impact tests were conducted. The effects of waste tire rubber with different particle sizes (10, 20, 30 mesh) and freeze–thaw cycles (0, 25, 50, 75, 100, 125) on the dynamic mechanical properties of concrete materials were studied. The stress–strain curves, peak stress, and fracture morphology of the specimens were analyzed. The microstructure changes of the specimens were also analyzed using scanning electron microscopy (SEM). The results showed the following: (1) Both macroscopic and microscopic analysis results showed that the internal damage of rubber concrete specimens was smaller after freeze–thawing, and the integrity was better after impact, maintaining a loose but not scattered state. The addition of waste tire rubber significantly improved the material’s impact resistance to a certain extent. (2) As the impact pressure increased, the strain rate of the specimens increased linearly, and the dynamic peak stress was linearly positively correlated with the strain rate. (3) After 125 freeze–thaw cycles, the peak stress of the specimens with 30-mesh added rubber decreased significantly less than that of ordinary concrete under 0.3, 0.45, and 0.6 MPa impact pressure. The dynamic peak stress was higher than that of specimens with 10-mesh and 20-mesh added rubber, and the addition of 30-mesh rubber significantly improved the frost resistance and impact resistance of concrete materials. This study can provide new ideas for the engineering application of rubber concrete.

Abstract Antigen delivery based on non‐virus‐like particle self‐associating protein nanoscffolds, such as Aquifex aeolicus lumazine synthase (AaLS), is limited due to the immunotoxicity and/or premature clearance of antigen‐scaffold complex resulted from triggering unregulated innate immune responses. Here, using rational immunoinformatics prediction and computational modeling, we screen the T epitope peptides from thermophilic nanoproteins with the same spatial structure as hyperthermophilic icosahedral AaLS, and reassemble them into a novel thermostable self‐assembling nanoscaffold RPT that can specifically activate T cell‐mediated immunity. Tumor model antigen ovalbumin T epitopes and the severe acute respiratory syndrome coronavirus 2 receptor‐binding domain are loaded onto the scaffold surface through the SpyCather/SpyTag system to construct nanovaccines. Compared to AaLS, RPT‐constructed nanovaccines elicit more potent cytotoxic T cell and CD4+ T helper 1 (Th1)‐biased immune responses, and generate less anti‐scaffold antibody. Moreover, RPT significantly upregulate the expression of transcription factors and cytokines related to the differentiation of type‐1 conventional dendritic cells, promoting the cross‐presentation of antigens to CD8+ T cells and Th1 polarization of CD4+ T cells. RPT confers antigens with increased stability against heating, freeze‐thawing, and lyophilization with almost no antigenicity loss. This novel nanoscaffold offers a simple, safe, and robust strategy for boosting T‐cell immunity‐dependent vaccine development.

Electronic Health Records (EHRs) contain unprecedented volumes of data related to health such as diagnosis and treatment information. Based on the technologies of named entity recognition (NER), EHRs mining has become a research focus in health domain. Nevertheless, the complex medical entities are challenging to be recognized, especially in Chinese EHRs. In this paper, a Glyph and Word Boundary-based Named Entity Recognition (GWBNER) method is presented, which takes into account both the Chinese character glyph and word boundary features in Chinese EHRs. Specifically, the character glyphs are utilized to capture the character-level global structural features, and the word boundaries are adopted to extract the word-level local structural features in Chinese. Therefore, the medical entities are fully recognized with rich semantic features from diverse perspectives in Chinese EHR texts. Finally, we conduct extensive experiments to evaluate the novel approach, and the F1 scores of 0.879, 0.998 and 0.962 are achieved on three EHR datasets, respectively. The experimental results demonstrate the optimal performance of the GWBNER method compared with the state-of-the-art models in NER community.

Objective: Defining the regulators of cell metabolism and signaling is essential to design new therapeutic strategies in obesity and NAFLD/NASH. E3 ubiquitin ligases control diverse cellular functions by ubiquitination-mediated regulation of protein targets, and thus their functional aberration is associated with many diseases. The E3 ligase Ube4A has been implicated in human obesity, inflammation, and cancer. However, its in vivo function is unknown, and no animal models are available to study this novel protein. Methods: A whole-body Ube4A knockout (UKO) mouse model was generated, and various metabolic parameters were compared in chow- and high fat diet (HFD)-fed WT and UKO mice, and in their liver, adipose tissue, and serum. Lipidomics and RNA-Seq studies were performed in the liver samples of HFD-fed WT and UKO mice. Proteomic studies were conducted to identify Ube4A's targets in metabolism. Furthermore, a mechanism by which Ube4A regulates metabolism was identified. Results: Although the body weight and composition of young, chow-fed WT and UKO mice are similar, the knockouts exhibit mild hyperinsulinemia and insulin resistance. HFD feeding substantially augments obesity, hyperinsulinemia, and insulin resistance in both sexes of UKO mice. HFD-fed white and brown adipose tissue depots of UKO mice have increased insulin resistance and inflammation and reduced energy metabolism. Moreover, Ube4A deletion exacerbates hepatic steatosis, inflammation, and liver injury in HFD-fed mice with increased lipid uptake and lipogenesis in hepatocytes. Acute insulin treatment resulted in impaired activation of the insulin effector protein kinase Akt in liver and adipose tissue of chow-fed UKO mice. We identified the Akt activator protein APPL1 as a Ube4A interactor. The K63-linked ubiquitination (K63-Ub) of Akt and APPL1, known to facilitate insulin-induced Akt activation, is impaired in UKO mice. Furthermore, Ube4A K63-ubiquitinates Akt in vitro. Conclusion: Ube4A is a novel regulator of obesity, insulin resistance, adipose tissue dysfunction and NAFLD, and preventing its downregulation may ameliorate these diseases.

One remarkable trend in applying synthetic aperture radar technology is the automatic interpretation of Synthetic Aperture Radar (SAR) images. The electromagnetic scattering characteristics have a robust correlation with the target structure, which provides key support for SAR image interpretation. Therefore, elucidating how to extract accurate electromagnetic characteristics and how to use these electromagnetic characteristics to retrieve target characteristics has been widely valued recently. This study discusses the research accomplishments, summarizes the key elements and ideas of electromagnetic characteristic extraction and electromagnetic-characteristic-based target recognition, and details the extension applications of the electromagnetic scattering mechanism in imaging and recognition. Finally, the future research direction of electromagnetic scattering characteristic extraction and application was proposed.

Abstract Objective To compare the clinical efficacy of minimally invasive percutaneous treatment by ligamentotaxis with traditional open reduction and internal fixation in the treatment of Essex-Lopresti joint depression-type displaced intra-articular calcaneal fractures (DIACFs). Methods The medical records of patients with calcaneal fractures admitted to our department from January 2016 to December 2020 were retrospectively analyzed, and patients who met the inclusion criteria were finally included for analysis. Twenty-one patients underwent minimally invasive percutaneous treatment by ligamentotaxis (Group A), while eighteen patients were treated by traditional open reduction and internal fixation through an extended lateral approach (Group B). The preoperative waiting time, operative time, hospital stay, radiologic parameters (calcaneal height, width, length, Böhler angle and Gissane angle), American Foot and Ankle Surgery Association (AOFAS) hindfoot scores, Maryland Foot Score (MFS), visual analogue scale (VAS), and incidence of complications of the included patients were all recorded and analysed. Results Thirty-nine patients with Essex-Lopresti joint depression type DIACFs were finally included. According to the Sanders classification, 22 were type II, 12 were type III and 5 were type IV. The preoperative waiting time and the hospital stay of Group A were 3.7 ± 1.6 d and 7.2 ± 1.7 d, respectively, which were significantly shorter than those of Group B (6.9 ± 2.0 d and 12.4 ± 1.5 d) (P 0.05). No significant differences were shown in the radiological parameters (calcaneal height, width, length, Böhler angle and Gissane angle) or the satisfactory rate of joint surface reduction (SRJSR) of the two groups immediately postoperatively. All patients were followed up for 14 to 56 months [(30.2 ± 10.4) months]. All fractures healed. At the final follow-up, there were no significant differences in the radiological parameters or the SRJSR between the two groups (P > 0.05). No significant differences were shown in the AOFAS scores, MFS or VAS scores between the two groups [(89.5 ± 8.2) vs. (89.4 ± 9.0), P > 0.05; (87.5 ± 8.3) vs. (86.3 ± 8.9), P > 0.05; and (2.1 ± 1.2) vs. (2.2 ± 1.2), P > 0.05]. The excellent and good rates of the AOFAS scores and MFS were 90.5% and 85.7%, respectively, in Group A and 88.9% and 88.9%, respectively, in Group B (P > 0.05). Four patients experienced wound complications, including 1 superficial incision infection, 2 skin necrosis around the incision edge and 1 deep infection in Group B, while there were no wound complications in Group A (P 0.05). Conclusions In the assessment of Essex-Lopresti joint depression type DIACFs, minimally invasive percutaneous treatment by ligamentotaxis has similar clinical outcomes to traditional open reduction and internal fixation through an extended lateral approach. However, the former has the advantages of shorter preoperative waiting time and hospital stay, and lower incidence of incision complications.

Previous work has reported an axion insulator state in a layered topological antiferromagnet MnBi2Te4 evidenced by a zero Hall plateau. Here, in addition to the zero Hall plateau, the authors identify edge states in transport measurements at zero field which challenge the axion insulator interpretation.

In pursuit of stable operation in thermal hydraulic engineering, this paper researches two-phase flow through tube bundles by the lattice Boltzmann method. The single-relaxation-time lattice Boltzmann model and the multicomponent, multiphase pseudo-potential lattice Boltzmann model are adopted. Specifically, the two-phase flow past double-tandem circular cylinders, double-parallel circular cylinders, in-line tube bundles and staggered tube bundles with various spacing ratios is investigated. The vortex variable distribution and vortex shedding law under different working conditions are further compared to obtain the time-averaged drag, oscillating drag and Strouhal number. The variation law of lift coefficient and lift power spectrum with different spacing ratios is revealed. With increasing spacing ratio, the mutual interference between the double-tandem circular cylinders is weakened, the amplitude of the time-averaged drag on the double-parallel circular cylinders is reduced and the lift power spectrum changes from a double-peak distribution to a single-peak structure. The drag and lift of the center column of in-line tube bundles are lower than those on both sides, while the oscillating drag of the odd-row columns of staggered tube bundles is higher than that of even-row columns. These results contribute toward laying a solid foundation for future research on multiphase tube bundle flow issues in nuclear engineering.

Abstract Background Despite the importance of root hydraulics, there is little research on the in situ dynamic responses of embolism formation and embolism repair of roots distributed in different soil depths in response to different water regimes. Results The vessel diameter, hydraulic conductivity, and vulnerability to cavitation were in the order of deep root > shallow root > branch. The midday PLC of shallow root was the highest in the dry season, while the midday PLC of deep root slightly higher than that of branch with no significant difference in the two seasons. The capacity of embolism repair of roots was significantly greater than that of branch both in dry season and wet season. The xylem pressure was in the order of deep roots > shallow root > branch, and it was negative in most of the time for the latter two in the dry season, but positive for both of the roots during the observation period in the wet season. The NSC and starch content in roots were significantly higher than those in branches, especially in the dry season. In contrast, roots had lower content of soluble sugar. Conclusions The relatively stable water condition in soil, especially in the deep layers, is favorable for the development of larger-diameter vessels in root xylem, however it cannot prevent the root from forming embolism. The mechanism of embolism repair may be different in different parts of plants. Deep roots mainly depend on root pressure to refill the embolized vessels, while branches mainly depend on starch hydrolysis to soluble sugars to do the work, with shallow roots shifted between the two mechanisms in different moisture regimes. There is theoretically an obvious trade-off between conducting efficiency and safety over deep roots, shallow roots and branches. But in natural conditions, roots do not necessarily suffer more severe embolism than branches, maybe due to their root pressure-driven embolism repair and relatively good water conditions.

Abstract The atomically thin MnBi2Te4 crystal is a novel magnetic topological insulator, exhibiting exotic quantum physics. Here we report a systematic investigation of ultrafast carrier dynamics and coherent interlayer phonons in few-layer MnBi2Te4 as a function of layer number using time-resolved pump-probe reflectivity spectroscopy. Pronounced coherent phonon oscillations from the interlayer breathing mode are directly observed in the time domain. We find that the coherent oscillation frequency, the photocarrier and coherent phonon decay rates all depend sensitively on the sample thickness. The time-resolved measurements are complemented by ultralow-frequency Raman spectroscopy measurements, which both confirm the interlayer breathing mode and additionally enable observation of the interlayer shear mode. The layer dependence of these modes allows us to extract both the out-of-plane and in-plane interlayer force constants. Our studies not only reveal the interlayer van der Waals coupling strengths, but also shed light on the ultrafast optical properties of this novel two-dimensional material.

The discrete Fourier transform (DFT) is a principal method for power system harmonic analysis. The fundamental frequency of the power system increases or decreases following load changes during normal operation. It is difficult to achieve synchronous sampling and integer period truncation in power harmonic analysis. The resulting spectrum leakage affects the accuracy of the measurement results. For this reason, a windowed interpolation DFT method for power system harmonic analysis to reduce errors was presented in this paper. First, the frequency domain expression of the windowed signal Fourier transform is analyzed. Then, the magnitude of the three discrete spectrum lines near the harmonic frequency point is used to determine the accurate position of the harmonic spectrum. Then, the calculation of the amplitude, frequency, and phase of harmonics is presented. The tripleline interpolation DFT can improve the accuracy of electrical harmonic analysis. Based on the algorithm, the practical rectification formulas were obtained by using the polynomial approximation method. The simulation results show that the fast attenuation of window function sidelobe is the key to reduce the error. The triple-line interpolation DFT based on Hanning, Blackman, Nuttall 3-Term windows has higher calculation accuracy, which can meet the requirements of electrical harmonic analysis.

Background: Prognostic biomarkers in colorectal carcinoma (CRC) have an important role in therapeutic strategy. Studies have shown that high expression of Aquaporin (AQP) is associated with poor prognosis in a variety of human tumors. AQP is involved in the initiation and development of CRC. The present study aimed to investigate the correlation between the expression of AQP1, 3 and 5 and clinicopathological features or prognosis in CRC.Methods: The AQP1, 3 and 5 expressions were analyzed based on the immunohistochemical staining of tissue microarray specimens including 112 patients with CRC between June 2006 and November 2008. The expression score of AQP (Allred_score and H_score) was digitally obtained with Qupath software. Patients were divided into high or low expression subgroups based on the optimal cut-off values. The relationship between expression of AQP and clinicopathological characteristics were evaluated using chi-square test, t-test, or one-way ANOVA, when appropriate. Survival analysis of 5-year progression free survival (PFS) and overall survival (OS) was performed with time-dependent ROC, Kaplan-Meier curves, univariate and multivariate COX analysis.Results: The AQP1, 3 and 5 expressions were associated with regional lymph node metastasis, histological grading, and tumor location in CRC, respectively (p < 0.05). Kaplan-Meier curves showed that patients with high AQP1 expression had worse 5-year PFS than those with low AQP1 expression (Allred_score: 47% vs. 72%, p = 0.015; H_score: 52% vs. 78% p = 0.006), as well as 5-year OS (Allred_score: 51% vs. 75%, p = 0.005; H_score: 56% vs. 80%, p = 0.002). Multivariate Cox regression analysis indicated that AQP1 expression was an independent risk prognostic factor (p = 0.033, HR = 2.274, HR95% CI: 1.069–4.836). There was no significant correlation between the expression of AQP3 and 5 and the prognosis.Conclusion: The AQP1, 3 and 5 expressions correlate with different clinicopathological characteristics and the AQP1 expression may be a potential biomarker of prognosis in CRC.

Pigment content is a critical assessment indicator in the study of plant physiological metabolism, stress resistance, ornamental characteristics, and forest health. Spectral imaging technology is widely used for rapid and non-destructive determination of plant physicochemical parameters. To address the shortcomings of previous models of spectral reflectance prediction of chlorophyll content of needles only from the perspective of traditional algorithms and ignoring physical models, this research integrates variable complexity and refined classification of physical models to validate the increased accuracy of both the conventional partial least squares (PLS) method and the traditional neural network algorithm. The results of the conifer chlorophyll models of Picea koraiensis Nakai with different needle ages based on spectral reflectance and vegetation index parameters showed that the improved nonlinear state transition algorithm-backpropagation (STA-BP) neural network model approach (R2 of 0.73–0.89) and the nonlinear Stacking partial least squares (Stacking-PLS) model approach (R2 of 0. 67–0.85) is slightly more robust than the traditional algorithms nonlinear BP model (R2 of 0.63–0.82) and linear PLS model (R2 of 0.60–0.76). This finding suggests that the nonlinear fitting of chlorophyll content in needles of different needle ages in P. koraiensis Nakai surpasses the traditional linear model fitting methodology. Furthermore, the model fitting of chlorophyll content in conifers of different needle ages outperforms the mixed P. koraiensis Nakai model, suggesting that chlorophyll models using needle refinement classification help to improve model robustness. This study provides data and theoretical support for rapid and non-invasive characterization of physiological and biochemical properties of needles of different needle ages using spectral imaging techniques to predict growth and community structure productivity of forest trees in the coming years.

Acute lung injury (ALI) is one of the most common clinical emergencies with limited effective pharmaceutical treatment in the clinic, especially when it progresses to acute respiratory distress syndrome (ARDS). Currently, mesenchymal stem cells (MSCs) exhibit specific superiority for ALI/ARDS treatment. However, stem cells from different sources may result in controversial effects on similar disease conditions. This study aimed to determine the effects of human amnion-derived mesenchymal stem cells (hAMSCs) on two different ALI mice model. The administered hAMSCs effectively accumulated in the lung tissues in all hAMSC-treated groups. Compared with the model and 1% human serum albumin (HSA) groups, high-dose hAMSCs (1.0 × 106 cells) group significantly alleviated alveolar-capillary permeability, oxidative stress, inflammatory factors level and histopathological damage. In addition, the NF-κB signaling pathway is one of the key pathways activated during lipopolysaccharide (LPS) or paraquat (PQ)-induced lung injury. Our results indicated that hAMSCs (1.0 × 106 cells) obviously inhibited the expression of p-IKKα/β, p-IκBα, and p-p65 in the lung tissue (p < 0.05). The high-dose (HD) hAMSC treatment exerted beneficial therapeutic effects on ALI mice models without detectable adverse reactions. The therapeutic effect of hAMSCs might involve NF-κB signaling pathway inhibition. hAMSC treatment is a potential candidate therapy for ALI.

Due to the increasing rate of economic development and the increasingly serious problem of environmental degradation, environmental information disclosure has become an important basis for promoting carbon peaking and carbon neutrality, and an important way for enterprises to carry out green governance to achieve sustainable development. This study uses empirical research methods to analyze the relationship between environmental information disclosure and corporate sustainable growth in the context of green governance using panel data of Chinese A-share listed companies in Shanghai and Shenzhen from 2012 to 2021. The empirical tests conclude that there is a U-shaped relationship between environmental information disclosure and corporate sustainable growth, which decreases and then increases, and the U-shaped relationship is transmitted through innovation inputs. The U-shaped relationship between environmental information disclosure and corporate sustainable growth is weakened by firm size and enhanced by equity incentives. In addition, further group analysis reveals that the above U-shaped relationship is more significant in non-state enterprises than in state-owned enterprises.

Dry–wet cycling has a significant impact on the mechanical properties of rocks, and a series of problems such as rock collapse can occur in rock masses under long-term dry–wet cycling. Based on this, some mechanical tests were carried out on sandstone under different dry–wet cycles to analyze the evolution law of its physical and mechanical parameters. The results show that the internal connection of the mineral becomes looser, the drying quality of the sample decreases, and the water absorption quality increases gradually under different dry–wet cycles. The peak strength of the sample decreases first and then increases with increasing dry–wet cycles. The change trend of the elastic modulus and deformation modulus with the increase in dry–wet cycles are similar to the peak strength, which is mainly related to the change in the connection between particles. Furthermore, the specimens showed axial tensile failure under uniaxial action. With the increase in dry–wet cycles, the tensile crack on the surface of the specimen increased, and the fracture of the specimen became looser. The specimen exhibited block spalling when the number of dry–wet cycles was eight times.

Larger-leaf yellow tea (LYT) is a characteristic type of Chinese tea produced in Huoshan County, Anhui Province, which is made by mature leaves with stems. According to recent report, LYT showed competitive effects in anti-hyperglycemia in comparison to other teas such as green or black tea. However, the bioactive compounds of LYT are still undiscovered so far. For this purpose, 5 fractions of LYT were prepared by sequential extraction. The in vitro bioassay results indicated that the ethyl acetate fraction of LYT had the strongest inhibitory effects on α-glucosidase and α-amylase. Fluorescence-quenching analysis and protein-binding test revealed that the compounds of ethyl acetate fraction could inhibit α-glucosidase and α-amylase activities through binding to enzymes or other mechanisms. All chromatographic peaks of high-performance liquid chromatography (HPLC) of ethyl acetate fraction were separated and collected. The purified compounds were identified by liquid chromatography-mass spectrometry (LC-MS), and subsequently screened by calculating their inhibition ratio on α-glucosidase at the real concentration in LYT infusion. The results showed that (–)-epigallocatechin gallate, (–)-gallocatechin gallate, caffeine, N-ethyl-2-pyrrolidone-substituted flavan-3-ols were effective inhibitors for α-glucosidase.