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Clarifying the aesthetic differences between Guangxi folk dance and ASEAN dance can promote the in-depth exchange of dance art and culture between the two. In this paper, the aesthetic characteristics of Guangxi folk dance and ASEAN dance are discussed, and the HRNet network is used as the basis, combined with the sequence multi-scale feature fusion and the PCA action gesture segmentation model for the action gesture estimation. The dataset was constructed according to different kinds of Guangxi folk dance and ASEAN dance, and the aesthetic differences between Guangxi folk dance and ASEAN dance in terms of intrinsic culture and extrinsic performance were analyzed using the dataset. The results show that on the inner culture, Guangxi folk dance is mainly based on traditional culture and folk customs. ASEAN dance is more influenced by religious culture, although it has differences, but the correlation coefficients of emotional expression and national custom are 0.963 and 0.954, respectively. On the outer manifestation, Guangxi folk dance has as many as 11 kinds of action dance forms, while ASEAN dance emphasizes more on The ASEAN dance emphasizes more on the “flat, taut, straight and standing” forms. The aesthetic differences between Guangxi folk dance and ASEAN dance can promote the exchange and integration of dance art and culture between the two and provide a good artistic foundation for the in-depth promotion of the Belt and Road.

Abstract Tumor immunotherapy offers a new paradigm to treat cancer; however, the existing regimens are accompanied by the dilemma of insufficient therapeutic outcomes and off‐target adverse effects. The intestinal immune system contains a bulk of immune cells, which can be important contributors to the maintenance of systemic immune homeostasis. However, manipulating intestinal immunity to achieve systemic anti‐tumor immunity is extremely challenging. Here, an oral immunotherapy strategy is reported using immune‐enhancing fullerenes (IEF) that can reinvigorate anti‐tumor immunity via immune cell‐metabolic reprogramming of intestinal immune cells. Findings show that IEF can remodel anti‐inflammatory macrophages into tumor‐killing macrophages by regulating the energy metabolism pathway from oxidative phosphorylation (OXPHOS) to glycolysis. Consequently, IEF can reprogram the immunosuppressive intestinal immunity and enhance sys temic immunity in vivo, thereby boosting anti‐tumor immunity and converting “cold” tumors into “hot” tumors. Oral immunotherapy strategy, modulating autoimmune cells in the intestine and achieving systemic anti‐tumor immunity, can ensure safe and efficient tumor immunotherapy.

ABSTRACTOral, gut, and tumor microbiota have been implicated as important regulators in the carcinogenesis and progression of gastrointestinal malignancies. However, few studies focused on the existence and association of resident microbes within different body regions. Herein, we aim to reveal the durability of the oral-gut-tumor microbiome and its diagnostic performance in hepatocellular carcinoma (HCC). Our study included two cohorts: a retrospective discovery cohort of 364 HBV-HCC patients and 160 controls with oral or fecal samples, a prospective validation cohort of 91 cases, and 124 controls for matching samples, as well as 48 HBV, and 39 HBV-cirrhosis patients for gut microbial patterns examined by 16S rRNA gene sequencing. With the random forest analysis, 10 oral and 9 gut genera that could distinguish HCC from controls in the retrospective cohort were validated among the prospective matching participants, with area under the curve (AUC) values of 0.7971 and 0.8084, respectively. When influential taxa were merged, the AUC of the consistent classifier increased to 0.9405. The performance continued to improve to 0.9811 when combined with serum levels of alpha-fetoprotein (AFP). Specifically, microbial biomarkers represented by Streptococcus displayed a constantly increasing trend during the disease transition. Furthermore, the presence of several dominant microbiota species was confirmed in hepatic tumor and non-tumor tissues with fluorescence in situ hybridization (FISH) and 5 R 16S rRNA gene sequencing. Overall, our findings based on the oral-gut-tumor microbiota provide a reliable approach for the early detection of HCC.

Abstract. Background:. Although intensively studied in patients with cardiovascular diseases (CVDs), the prognostic value of diastolic blood pressure (DBP) has little been elucidated in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD). This study aimed to reveal the prognostic value of DBP in AECOPD patients. Methods:. Inpatients with AECOPD were prospectively enrolled from 10 medical centers in China between September 2017 and July 2021. DBP was measured on admission. The primary outcome was all-cause in-hospital mortality; invasive mechanical ventilation and intensive care unit (ICU) admission were secondary outcomes. Least absolute shrinkage and selection operator (LASSO) and multivariable Cox regressions were used to identify independent prognostic factors and calculate the hazard ratio (HR) and 95% confidence interval (CI) for adverse outcomes. Results:. Among 13,633 included patients with AECOPD, 197 (1.45%) died during their hospital stay. Multivariable Cox regression analysis showed that low DBP on admission (

Abstract Background Although surgery has been widely applied for SPLC therapy, there is still no uniform treatment approach. Whether SPLC and primary lung cancer have similar prognostic characteristics remains controversial. Herein, based on a systematic review and meta-analysis, we aimed to enucleate the influences of diverse surgical strategies and underlying prognostic factors on the prognosis of patients with both the first primary lung cancer and SPLC underwent surgical resection. Methods A comprehensive and systematic literature search was implemented in three databases (MEDLINE, EMBASE, and Cochrane), and eligible studies were screened following inclusion and exclusion criteria. Meanwhile, we extracted the hazard ratios (HR) together with 95% confidence intervals (CI) for each prognostic factor, either directly or indirectly, from the enrolled literature. Results Eleven studies (published between 2000 and 2022) were included in this study, including 1,131 SPLC patients. The overall survival (OS) exhibited no difference between patients with lobectomy and sublobar resection after SPLC (HR: 0.87, 95%CI: 0.62–1.21, P = 0.41). The patients after completion pneumonectomy had a poor prognosis (HR: 1.85, 95% CI: 1.34–2.55, P 2 cm (HR: 2.44, 95%CI: 1.73–3.44, P 2 cm, solid predominant in CT morphology, lymph node metastasis, and smoking had a poor prognosis. Meanwhile, SPLC has similar prognostic characteristics with single primary lung cancer. However, the study has some limitations and more evidence is warranted to verify the findings.

Abstract Biofilm-related diseases are a group of diseases that tolerate antimicrobial chemotherapies and therefore are refractory to treatment. Periodontitis, a non-device chronic biofilm disease induced by dental plaque, can serve as an excellent in vivo model to study the important effects of host factors on the biofilm microenvironment. Macrophage activity is one of the key factors that modulate the progression of inflammation-driven destruction in periodontitis; therefore it is an important host immunomodulatory factor. In this study, the reduction of microRNA-126 (miR-126) with the recruitment of macrophages in periodontitis was confirmed in clinical samples, and a strategy for targeted delivery of miR-126 to macrophages was explored. Exosomes overexpressing the C-X-C motif chemokine receptor 4 (CXCR4) loaded with miR-126 (CXCR4-miR126-Exo) was successfully constructed, which reduced off-target delivery to macrophages and regulated macrophages toward the anti-inflammatory phenotype. In vivo local injection of CXCR4-miR126-Exo into sites of periodontitis in rats effectively reduced bone resorption and osteoclastogenesis and inhibited the progression of periodontitis. These results provide new insights for designing novel immunomodulatory factor targeted delivery systems to treat periodontitis and other biofilm-related diseases.

A fluorogenic aptamer (FA)-based hybridization chain reaction (HCR) could provide a sensitive and label-free signal amplification method for imaging molecules in living cells. However, existing FA-HCR methods usually face some problems, such as a complicated design and significant background leakage, which greatly limit their application. Herein, we developed an FA-centered HCR (FAC-HCR) method based on a remote toehold-mediated strand displacement reaction. Compared to traditional HCRs mediated by four hairpin probes (HPs) and two HPs, the FAC-HCR displayed significantly decreased background leakage and improved sensitivity. Furthermore, the FAC-HCR was used to test a non-nucleic acid target, apurinic/apyrimidinic endonuclease 1 (APE1), an important BER-involved endonuclease. The fluorescence analysis results confirmed that FAC-HCR can reach a detection limit of 0.1174 U/mL. By using the two HPs for FAC-HCR with polyetherimide-based nanoparticles, the activity of APE1 in living cells can be imaged. In summary, this study could provide a new idea to design an FA-based HCR and improve the performance of HCRs in live cell imaging.

Commercial oxygen-free copper sheets were cold-rolled with reduction rates ranging from 20% to 87% and annealed at 400, 500 and 600 °C. The microstructure and texture evolution during the cold-rolling and annealing processes were studied using optical microscopy (OM), scanning electron microscopy (SEM) and electron back-scattered diffraction (EBSD). The results show that the deformation textures of {123} (S), {112} (Copper) and {110} (Brass) were continuously enhanced with the increase in cold-rolling reduction. The orientations along the α-oriented fiber converged towards Brass, and the orientation density of β fiber obviously increased when the rolling reduction exceeded 60%. The recrystallization texture was significantly affected by the cold-rolling reduction. After 60% cold-rolling reduction, Copper and S texture components gradually decreased, and the {011} recrystallization texture component formed with the increase in annealing temperature. After 87% cold-rolling reduction, a strong Cube texture formed, and other textures were inhibited with the increase in annealing temperature. The strong Brass and S deformation texture was conducive to the formation of a strong Cube annealing texture. The density of the annealing twin boundary decreased with the increase in annealing temperature, and more annealing twin boundaries formed in the oxygen-free copper sheets with the increase in cold-rolling reduction.

In this paper, we propose a global ionospheric total electron content (TEC) maps (GIM) prediction model based on deep learning methods that is both straightforward and practical, meeting the requirements of various applications. The proposed model utilizes an encoder-decoder structure with a Convolution Long Short-Term Memory (ConvLSTM) network and has a spatial resolution of 5° longitude and 2.5° latitude, with a time resolution of 1 h. We utilized the Center for Orbit Determination in Europe (CODE) GIM dataset for 18 years from 2002 to 2019, without requiring any other external input parameters, to train the ConvLSTM models for forecasting GIM 1, 2, and 3 days in advance. Using the CODE GIM data from 1 January 2020 to 31 December 2023 as the test dataset, the performance evaluation results show that the average root mean square errors (RMSE) for 1, 2 and 3 days of forecasts are 2.81 TECU, 3.16 TECU, and 3.41 TECU, respectively. These results show improved performance compared to the IRI-Plas model and CODE’s 1-day forecast product c1pg, and comparable to CODE’s 2-day forecast c2pg. The model’s predictions get worse as the intensity of the storm increases, and the prediction error of the model increases with the lead time.

In response to the need for a space security situation assessment during orbit, the multi-satellite space environmental risk prediction and early warning system is based on the detection results of the space weather payload of the Fengyun 4A and 4B satellites, as well as the prediction results of the National Space Weather Center, for the first time. By comprehensively utilizing some open-source data, it is the first time that we have achieved a 24 h advanced prediction of the space environment high-energy proton, low-energy particle, and high-energy electron risks for the safety of the Fengyun-series high-orbit satellites, and a real-time warning of satellite single-event upset, surface charging, and deep charging risks. The automation system has preliminarily achieved an intelligent space risk assessment for the safety of multiple stationary meteorological satellites, effectively improving the application efficiency of the space environmental data and the products of Fengyun-series satellites. The business status is stable in operation, and the resulting error between the predicted results of various risk indices and the measured data was less than one level. The warning accuracy was better than 90%. This article uses the system for the first time, to use Fengyun satellite data to, accurately and in a timely manner, predict and warn us about the low-energy particles and surface charging high-risk levels of the Fengyun 4A and 4B satellites during the typical space weather event on 21 April 2023, in response to the impact of complex spatial environmental factors on the safety of Fengyun-series high-orbit satellites. The construction and operation of a multi-satellite space environmental risk prediction and early warning system can provide a reference for the safety work of subsequent satellite ground system operations.

A novel indolium-based fluorescent probe for the detection of CN− was developed based on the conjugation of 1, 2, 3, 3-Tetramethyl-3H-indolium iodide and 2-acetyl benzothiophene. The introduction of external CN− caused a nucleophilic attack to the quaternary amine salt structure in the probe and resulted in the departure of iodide ions and the steric rotation of the index salt group, which caused fluorescence quenching. The titration experiments showed that the probe had rapid qualitative and quantitative analysis capabilities for CN−. Moreover, the relevant biocompatibility experiments also demonstrated the potential application value of the probe.

In the original publication [...]

In the face of ongoing water pollution challenges, the intricate interplay between dissolved organic matter and disinfectants like chlorine gives rise to potentially harmful disinfection byproducts (DBPs) during water treatment. The exploration of DBP formation originating from amino acids (AA) is a critical focus of global research. Aromatic DBPs, in particular, have garnered considerable attention due to their markedly higher toxicity compared to their aliphatic counterparts. This work seeks to advance the understanding of DBP formation by investigating chlorination disinfection and kinetics using tyrosine (Tyr), phenylalanine (Phe), and tryptophan (Trp) as precursors. Via rigorous experiments, a total of 15 distinct DBPs with accurate molecular structures were successfully identified. The chlorination of all three AAs yielded highly toxic chlorophenylacetonitriles (CPANs), and the disinfectant dosage and pH value of the reaction system potentially influence chlorination kinetics. Notably, Phe exhibited the highest degradation rate compared to Tyr and Trp, at both the CAA:CHOCl ratio of within 1:2 and a wide pH range (6.0 to 9.0). Additionally, a neutral pH environment triggered the maximal reaction rates of the three AAs, while an acidic condition may reduce their reactivity. Overall, this study aims to augment the DBP database and foster a deeper comprehension of the DBP formation and relevant kinetics underlying the chlorination of aromatic AAs.

As the next generation of in-vehicle intelligent platforms, the augmented reality heads-up display (AR-HUD) has a huge information interaction capacity, can provide drivers with auxiliary driving information, avoid the distractions caused by the lower head during the driving process, and greatly improve driving safety. However, AR-HUD systems still face great challenges in the realization of multi-plane full-color display, and they cannot truly achieve the integration of virtual information and real road conditions. To overcome these problems, many new devices and materials have been applied to AR-HUDs, and many novel systems have been developed. This study first reviews some key metrics of HUDs, investigates the structures of various picture generation units (PGUs), and finally focuses on the development status of AR-HUDs, analyzes the advantages and disadvantages of existing technologies, and points out the future research directions for AR-HUDs.

A wide variety of small-amplitude waves widely exist in the ionosphere and have significant effects on the evolution of equatorial plasma bubbles. In this paper, we simulated equatorial plasma bubbles (EPB) seeded by vertical neutral wind perturbations with wavelengths of 125 km and 250 km, and compared the morphology characteristics of plasma bubble structures with those under random noise perturbations in the background density. The numerical results showed that both vertical winds and random background noise perturbations can contribute to the growth of plasma bubbles, and the perturbations under additional random background noise can promote the growth of the plasma bubble structures faster. Additionally, several processes of the nonlinear behavior of bifurcated EPB structures, including bifurcation, pinching, and small-scale turbulent structures, were successfully obtained. Our simulation captured supersonic flows within the low-density plasma structures characterized by vertical velocities of about 1.5 km/s, which is consistent with experimental studies found in the literature.

Soil erosion reduces soil fertility and land productivity while enhancing desertification, which seriously threatens ecological security, carbon sequestration, and sustainable economic and social development. Therefore, it is fundamental to precisely assess the long-term dynamics of soil erosion and explore its drivers to control the risk of soil erosion. Currently, machine learning-based analyses of the factors driving soil erosion are lacking in the Beiluo River Basin (BRB), China. This paper aimed to investigate the spatiotemporal dynamics of soil erosion by the Chinese soil loss equation coupled with the gully erosion factor, and then reveal its driving factors using the Boosting Regression Tree method (BRT) and estimate the influence of drivers' interactions on soil erosion in the BRB between 1990 and 2017. The findings demonstrated that the expanded Chinese soil loss equation accurately explained the variations in soil erosion in the BRB. The range of average soil erosion rates was 2,852.83–800.35 t km−2 a−1. Steep gully farmland, particularly areas with relatively rough terrain, was more vulnerable to intense erosion. Soil erosion rates for different geomorphologies decreased as follows: hilly–gully areas > gully–plateau areas > alluvial river plains > Rocky Mountains. The major drivers affecting the soil erosion rate were the biomass control factor (B) and slope, followed by slope length (L) and slope steepness (S). B–soil erodibility (1990), B–LS (2000), LS–rainfall erosivity (2010), and slope–rainfall erosivity (2017) interactions had the greatest influence on soil erosion, with interaction intensities of 32.3%, 17.75%, 46.05%, and 35.69%, respectively. The average soil erosion rates according to land classification types decreased as follows: farmland > grassland > forest. The results indicate that water and soil conservation in the study area benefited greatly from implementation of the Grain for Green Program, with forests reducing erosion more effectively than grassland.

BackgroundThe intestinal microbiota is known to play a role in the development of liver disease, there is a limited understanding of the intestinal microbiota associated with chronic schistosomiasis japonica. This study sought to explore the characteristics of the intestinal microbiota in patients with chronic schistosomiasis japonica and identify potential biomarkers that could aid diagnosis.MethodsA total of 40 residents of Qingshan Island in Yueyang (Hunan, China) were enrolled in this cross-sectional study. These individuals were divided into two groups for analysis of the intestinal microbiota: patients with chronic schistosomiasis japonica-induced liver fibrosis group (CSJ group, n = 10) and a healthy control group (HC group, n = 30). Feces were collected from each participant and analyzed by 16S rRNA gene sequencing, which included species composition analysis at the phylum and family levels, α and β diversity analysis, LEfSe, Kyoto Encyclopedia of Genes and Genome (KEGG) and Clusters of Orthologous Groups of proteins (COG) analysis.ResultsOur results indicated that Schistosoma japonicum infection changed the composition and abundance of intestinal microbiota at the phylum and family levels. Compared with the HC group, the α and β diversity results showed that CSJ group had low diversity of species of the intestinal microbiome. LEfSe and relative abundance analysis found that the Prevotella 7, Alloprevotella, and Holdemanella genera were significantly higher in the CSJ group than in the HC group. Meanwhile, the ROC analysis showed that the area under the curve (AUC) of Prevotella 7, Alloprevotella, and Holdemanella genera was 0.779, 0.769, and 0.840, respectively. KEGG and COG analysis showed that the Replication and Repair, and Defense Mechanism pathways correlated strongly with chronic schistosomiasis japonica infection.ConclusionThe current study was the first to explore differences in the intestinal microbiota of patients with chronic schistosomiasis japonica-induced liver fibrosis and healthy people from Qingshan Island, which indicated that Prevotella 7, Alloprevotella, and Holdemanella genera could have a potential value in non-invasive diagnosis of chronic schistosomiasis japonica-induced fibrosis.

ABSTRACT: The purpose of this study is to investigate the characteristics of egg consumption in China and the production of functional eggs, and finally enrich the types of shell egg products. Trial 1 explored the influence of egg quality on Chinese consumers' willingness to purchase eggs through a questionnaire, which investigated 1,317 consumers' preferences for egg appearance, factors influencing egg purchase, and purchase of functional eggs. The results showed that about 65% of respondents ate more than 4 eggs per wk, pink eggs were the most popular in China, about 65% of consumers preferred eggs with an egg weight of 48 to 58 grams. For functional eggs, 75.32% of consumers have never heard of them. Preferences for eggshell color and yolk color varied by geographic region, with darker colors preferred in Northeast China. Based on the survey results of functional eggs consumption in Trial 1, the dwarf layers of China Agricultural University were used in Trial 2 to produce functional eggs. The eggs are small and pink in color, which is in line with the preferences of Chinese consumers. Three hundred dwarf layers were divided into 4 groups, using the linseed oil added, marigold extract added, and yeast selenium added diets to produce normal, n-3 fatty acid-enriched, lutein-enriched and selenium-enriched eggs by feeding for 28 d, determined the eggs’ nutrient content and egg quality. The results showed that the n-3 fatty acid, lutein and selenium contents of the eggs of dwarf layers were significantly increased by changing the diets and did not affect the egg weight, eggshell strength, Haugh units or the proportion of egg parts. The results of this study are helpful to understand the trend of egg consumption preferences in China, and on this basis to produce functional eggs that meet the consumers’ expectations.

Background: SHR8554 is a novel μ-opioid receptor-biased agonist. It has analgesic effects by selectively activating the G protein-coupled pathway. Additionally, it can weakly activate the ß-arrestin-2 pathway, resulting in a limited number of side effects, such as gastrointestinal inhibition. Previous studies have shown that SHR8554 has good analgesic effects, safety and tolerability, but the pharmacokinetic characteristics of SHR8554 in humans have not been reported. This study was designed to investigate the pharmacokinetics and safety of SHR8554 in healthy Chinese male subjects.Methods: A single 1 mg/41.3 μCi intravenous dose of [14C]SHR8554 was administered to six healthy male subjects. Blood, urine and faecal samples were collected at continuous time points to analyse SHR8554 parent drug levels and their metabolites. The total radioactivity in blood, plasma, urine and faeces was detected by using a liquid scintillation counter. The dynamic changes of SHR8554 and its metabolite concentration were by liquid chromatography-tandem mass spectrometry (LC/MS), and then pharmacokinetic analysis. The safety of the drug on the subjects was also observed after a single intravenous injection.Results: The total recovery of radioactivity in urine and faeces was 99.68% ± 0.79% in 216 h, including 76.22% ± 1.12% in urine and 23.46% ± 1.36% in faeces. Seventeen major metabolites in blood, urine and faeces were analysed and identified. The main metabolic pathways of SHR8554 in the human body involve 1) N-dealkylation; 2) O-deethylation; 3) mono-oxidation; 4) glucuronidation, etc. The primary mechanism of SHR8554 clearance in the human body is through urinary excretion, primarily in its parent drug and metabolite forms. The drug has good safety, and no serious adverse effects were observed.Conclusion: SHR8554 showed favourable pharmacokinetic characteristics and safety profiles in this study. SHR8554 is extensively metabolized in human body. The main metabolic pathways include N-dealkylation and O-deethylation, as well as mono-oxidation and glucuronidation. The main excretion route of SHR8554 and its metabolites is through urine.Clinical Trial Registration:http://www.chinadrugtrials.org.cn/, identifier CTR20220450

Low temperature is a limiting factor affecting plant growth and development. Casuarina equisetifolia, a typical tropical and subtropical tree important for the ecological restoration of coastal beaches, is sensitive to cold stress. By comparing cold tolerance between C. equisetifolia and Arabidopsis, we investigated the molecular basis underlying the cold sensitivity of C. equisetifolia. Transcriptomic analysis showed that the number of cold-induced genes in C. equisetifolia was significantly less than that in Arabidopsis, and notably, the response of cold-induced genes was also delayed in C. equisetifolia. Among the cold-induced genes, C-repeat binding factors (CBFs), the major transcription factors in cold acclimation in Arabidopsis, showed a delayed cold-induced expression in C. equisetifolia, despite that C. equisetifolia CBFs could restore the low temperature-sensitive phenotype of Arabidopsis cbfs triple mutants. Interestingly, some key cold-responsive genes (e.g., COR15A and COR15B) targeted by Arabidopsis CBF were absent in the C. equisetifolia genome and many cold-responsive genes in C. equisetifolia lacked the DRE element (i.e., CBF binding cis-element). Moreover, like in C. equisetifolia, many COR genes in other tropical/subtropical plants lacked the DRE element or were directly missing. These two factors could be the underlying reasons for the low-temperature sensitivity of C. equisetifolia and other tropical/subtropical plants.

Using large-scope and high-accuracy global navigation satellite system (GNSS) ionospheric monitoring, this study considered the polar ionosphere anomaly morphology caused by an interplanetary shock event that occurred on September 12, 2014. First, we used the continuous observation data of GNSS stations in the Antarctic region to estimate the carrier TEC epochs variation (dTEC) that reflects ionospheric electron density changes, and the abnormal signals were extracted. Through sequence data analyses of longitudinal chain stations, we found that the influence range of this anomaly lies in the geomagnetic region between 65$^\circ$ and 80 $^\circ$S. Furthermore, latitude chain analyses revealed that with the continuous fluctuation of the solar wind flow pressure, the polar ionospheric geomagnetic 75 $^\circ$S annular observation sequence gives a corresponding continuous fluctuation response with a range of 0.05–0.4 TECU and a westward anomaly trigger position. The average speed was close to the satellite speed during the study period, and it was determined that the anomaly occurred within an altitude region of 150–300 km. The physical mechanism of this anomaly is discussed in this article. Our results show that the GNSS dTEC and multisource data can accurately reflect the regional intensity, influence region, trigger source location, and velocity of the ionosphere anomaly.

Accurate classifications of land use/land cover (LULC) in arid regions are vital for analyzing changes in climate. We propose an ensemble learning approach for improving LULC classification accuracy in Xinjiang, northwest China. First, multisource geographical datasets were applied, and the study area was divided into Northern Xinjiang, Tianshan, and Southern Xinjiang. Second, five machine learning algorithms—k-nearest neighbor, support vector machine (SVM), random forest (RF), artificial neural network (ANN), and C4.5—were chosen to develop different ensemble learning strategies according to the climatic and topographic characteristics of each subregion. Third, stratified random sampling was used to obtain training samples and optimal parameters for each machine learning algorithm. Lastly, each derived approach was applied across Xinjiang, and subregion performance was evaluated. The results showed that the LULC classification accuracy achieved across Xinjiang via the proposed ensemble learning approach was improved by ≥6.85% compared with individual machine learning algorithms. By specific subregion, the accuracies for Northern Xinjiang, Tianshan, and Southern Xinjiang increased by ≥6.70%, 5.87%, and 6.86%, respectively. Moreover, the ensemble learning strategy combining four machine learning algorithms (i.e., SVM, RF, ANN, and C4.5) was superior across Xinjiang and Tianshan; whereas, the three-algorithm (i.e., SVM, RF, and ANN) strategy worked best for the Northern and Southern Xinjiang. The innovation of this study is to develop a novel ensemble learning approach to divide Xinjiang into different subregions, accurately classify land cover, and generate a new land cover product for simulating climate change in Xinjiang.

Short-chain fatty acids (SCFAs) exhibit anticancer activity in cellular and animal models of colon cancer. Acetate, propionate, and butyrate are the three major SCFAs produced from dietary fiber by gut microbiota fermentation and have beneficial effects on human health. Most previous studies on the antitumor mechanisms of SCFAs have focused on specific metabolites or genes involved in antitumor pathways, such as reactive oxygen species (ROS) biosynthesis. In this study, we performed a systematic and unbiased analysis of the effects of acetate, propionate, and butyrate on ROS levels and metabolic and transcriptomic signatures at physiological concentrations in human colorectal adenocarcinoma cells. We observed significantly elevated levels of ROS in the treated cells. Furthermore, significantly regulated signatures were involved in overlapping pathways at metabolic and transcriptomic levels, including ROS response and metabolism, fatty acid transport and metabolism, glucose response and metabolism, mitochondrial transport and respiratory chain complex, one-carbon metabolism, amino acid transport and metabolism, and glutaminolysis, which are directly or indirectly linked to ROS production. Additionally, metabolic and transcriptomic regulation occurred in a SCFAs types-dependent manner, with an increasing degree from acetate to propionate and then to butyrate. This study provides a comprehensive analysis of how SCFAs induce ROS production and modulate metabolic and transcriptomic levels in colon cancer cells, which is vital for understanding the mechanisms of the effects of SCFAs on antitumor activity in colon cancer.

Abstract Thrombocytopenia is the most frequent haematologic disorder in patients with cirrhosis, and it is perceived as a contributory factor for bleeding events. Cirrhosis patients with portal hypertension (PHT) is often accompanied with mild to moderate thrombocytopenia when they treated with transjugular intrahepatic portosystemic shunt (TIPS). To address whether the risk of variceal hemorrhage after TIPS varies with different platelet count in patients with normal platelet count and thrombocytopenia, we conducted the retrospective controlled study to evaluate the association of platelet count with the risk of variceal bleeding after TIPS. 304 patients were selected to the study. Propensity score matching was performed to adjust for potential selection bias. 63 patients from each group could be paired. Cox proportional hazards models were used to evaluate the association between platelet and variceal bleeding after TIPS. Platelet counts of two groups are 185.0 ± 98.7 × 109/L (normal platelet count) and 70.6 ± 39.3 × 109/L (thrombocytopenia) respectively. The bleeding rates of two groups in overall cohort are 10.9% (normal platelet count) and 12.9% (thrombocytopenia). After matched, the bleeding rates of two groups are 11.1% (normal platelet count) and 14.3% (thrombocytopenia) There was no statistically significant difference in bleeding rates between the two groups, either in the whole cohort (P = 0.671) or in the matched cohort (P = 0.593). Platelet count was not associated with bleeding events after TIPS (hazard ratio (HR) 95% confidence interval: 0.986–1.005, P = 0.397 in normal platelet count and 95% confidence interval: 0.968–1.020, P = 0.648 in thrombocytopenia). Thrombocytopenia in patients with cirrhosis was not associated with the risk of variceal bleeding episodes post-TIPS. Thrombocytopenia should not be viewed as an absolute contraindication for TIPS.

Non-specific phospholipase C (NPC) is a plant-specific phospholipid-hydrolyzing enzyme. Here, the authors define the molecular basis of how Arabidopsis NPC works, and provide new mechanistic insights into the members of phospholipase family.

Abstract In the aging process and central nervous system (CNS) diseases, the functions of the meningeal lymphatic vessels (MLVs) are impaired. Alterations in MLVs have been observed in aging-related neurodegenerative diseases, brain tumors, and even cerebrovascular disease. These findings reveal a new perspective on aging and CNS disorders and provide a promising therapeutic target. Additionally, recent neuropathological studies have shown that MLVs exchange soluble components between the cerebrospinal fluid (CSF) and interstitial fluid (ISF) and drain metabolites, cellular debris, misfolded proteins, and immune cells from the CSF into the deep cervical lymph nodes (dCLNs), directly connecting the brain with the peripheral circulation. Impairment and dysfunction of meningeal lymphatics can lead to the accumulation of toxic proteins in the brain, exacerbating the progression of neurological disorders. However, for many CNS diseases, the causal relationship between MLVs and neuropathological changes is not fully clear. Here, after a brief historical retrospection, we review recent discoveries about the hallmarks of MLVs and their roles in the aging and CNS diseases, as well as potential therapeutic targets for the treatment of neurologic diseases.

Irregular defects generated by trauma or surgery in orthopaedics practice were usually difficult to be fitted by the preformed traditional bone graft substitute. Therefore, the injectable hydrogels have attracted an increasing interest for bone repair because of their fittability and mini-invasivity. However, the uncontrollable spreading or mechanical failures during its manipulation remain a problem to be solved. Moreover, in order to achieve vascularized bone regeneration, alternatives of osteogenic and angiogenic growth factors should be adopted to avoid the problem of immunogenicity and high cost.In this study, a novel injectable self-healing hydrogel system (GMO hydrogel) loaded with KP and QK peptides had been developed for enhancing vascularized regeneration of small irregular bone defect. The dynamic imine bonds between gelatin methacryloyl and oxidized dextran provided the GMO hydrogel with self-healing and shear-thinning abilities, which led to an excellent injectability and fittability. By photopolymerization of the enclosed GelMA, GMO hydrogel was further strengthened and thus more suitable for bone regeneration. Besides, the osteogenic peptide KP and angiogenic peptide QK were tethered to GMO hydrogel by Schiff base reaction, leading to desired releasing profiles. In vitro, this composite hydrogel could significantly improve the osteogenic differentiation of BMSCs and angiogenesis ability of HUVECs. In vivo, KP and QK in the GMO hydrogel demonstrated a significant synergistic effect in promoting new bone formation in rat calvaria. Overall, the KP and QK loaded GMO hydrogel was injectable and self-healing, which can be served as an efficient approach for vascularized bone regeneration via a minimally invasive approach.

Graph neural networks are machine learning models that directly access the structural representation of molecules and materials. This Review discusses state-of-the-art architectures and applications of graph neural networks in materials science and chemistry, indicating a possible road-map for their further development.

In this study, we investigate the generation of parametric decay instability, Langmuir turbulence formation, and electron acceleration in ionospheric heating via a two-fluid model using the Fokker–Planck equation and Vlasov–Poisson system simulations. The simulation results of both the magnetofluid model and the kinetic model demonstrate the dynamics of electron acceleration. Further, the results of the Vlasov–Poisson simulations suggest the formation of electron holes in phase space at the same spatial scale as the Langmuir wave, which are shown to be related to electron acceleration. In addition, electron acceleration is enhanced through the extension of the wavenumber spectrum caused by strong Langmuir turbulence, leading to more electron holes in phase space.

Abstract Background Schistosoma japonicum infection is an important public health problem, imposing heavy social and economic burdens in 78 countries worldwide. However, the mechanism of transition from chronic to advanced S. japonicum infection remains largely unknown. Evidences suggested that gut microbiota plays a role in the pathogenesis of S. japonicum infection. However, the composition of the gut microbiota in patients with chronic and advanced S. japonicum infection is not well defined. In this study, we compared the composition of the intestinal flora in patients with chronic and advanced S. japonicum infection. Methods The feces of 24 patients with chronic S. japonicum infection and five patients with advanced S. japonicum infection from the same area were collected according to standard procedures, and 16S rRNA sequencing technology was used to analyze the intestinal microbial composition of the two groups of patients. Results We found that alteration occurs in the gut microbiota between the groups of patients with chronic and advanced S. japonicum infections. Analysis of alpha and beta diversity indicated that the diversity and abundance of intestinal flora in patients with advanced S. japonicum infection were lower than those in patients with chronic S. japonicum infection. Furthermore, Prevotella 9, Subdoligranulum, Ruminococcus torques, Megamonas and Fusicatenibacter seemed to have potential to discriminate different stages of S. japonicum infection and to act as biomarkers for diagnosis. Function prediction analysis revealed that microbiota function in the chronic group was focused on translation and cell growth and death, while that in the advanced group was concentrated on elevating metabolism-related functions. Conclusions Our study demonstrated that alteration in gut microbiota in different stages of S. japonicum infection plays a potential role in the pathogenesis of transition from chronic to advanced S. japonicum infection. However, further validation in the clinic is needed, and the underlying mechanism requires further study.

Schematic presentation of the design of VEGFR targeting peptide conjugate (QR-KLU) and the antineoplastic efficacy of peptide QR-KLU in vitro and in vivo.

The stability of the forming layer shape is a critical factor that impacts the final quality of sample morphology in wire and arc additive manufacturing (WAAM). This paper investigates the forming process and control methods to identify ways to optimize the process and improve the quality of the final product. The study aims to enhance the quality and precision of samples produced by the WAAM process by establishing a morphology control method based on image feedback. The focus is on real-time image acquisition using a CCD and simultaneous extraction of forming process parameter characteristics. Using a central composite experimental design, a prediction model is developed to estimate key process parameters and feature sizes of deposits, including deposition height and width. To further analyze the dynamic characteristics of feature sizes of deposited layers, step response identification is conducted using three process parameters as the system input: forming speed, arc current, and wire feeding speed. The experiments are designed to determine the weight of each process parameter and achieve a high level of response speed and precision. The findings indicate that the feature size of the deposited layer is most sensitive to changes in forming speed, followed by wire feeding speed, while arc current has the least impact on feature size. After verification, the monitoring of the deposition height and width was found to be in good agreement with the prediction model, with an accuracy of over 90%. The results of this study can be used for size measurement and optimization of large aviation aluminum alloy components using WAAM technology and to improve the quality of products produced using these processes.

A new fluorescent sensor for the detection of CN− was developed based on the conjugation of phenothiazine fluorophore and benzofuran unit. By the nucleophilic attacking of CN− to the fluoroacetylamino group in the sensor, the additional reaction of CN− and carbonyl group induced the ICT (intramolecular charge transfer) effect in the molecule and caused the fluorescence quenching sensor. The titration experiments show that the sensor has good sensitivity, selectivity and quick response for CN−. In addition, the fluorescent detection of CN− in the living cell and zebrafish experiments demonstrated the value of the sensor in tracing the CN− in biological systems.

Abstract Background Kidney transplantation is an effective treatment for end-stage renal disease (ESRD). Delayed graft function (DGF) is a common complication after kidney transplantation and exerts substantial effects on graft function and long-term graft survival. Therefore, the construction of an effective model to predict the occurrence of DGF is particularly important. Methods Seventy-one patients receiving their first kidney transplant at the First Affiliated Hospital of Nanchang University from October 2020 to October 2021 were enrolled in the discovery cohort. Based on clinical characteristics and serum markers, a logistic regression model was used to simulate the risk of DGF in the discovery cohort. The DGF prediction model was named the prediction system and was composed of risk factors related to DGF. Thirty-two patients receiving a kidney transplant at the First Affiliated Hospital of Nanchang University from October 2021 to February 2022 were enrolled in the validation cohort. The validation cohort was used to verify the accuracy and reliability of the prediction model. Results Cold ischemia time (CIT), donor history of diabetes mellitus, donor interleukin-2 (IL-2) level and donor terminal creatinine level constitute the prediction system. In the validation test, the area under the receiver operating characteristic curve (AUC) was 0.867 for the prediction system, and good calibration of the model was confirmed in the validation cohort. Conclusions This study constructed a reliable and highly accurate prediction model that provides a practical tool for predicting DGF. Additionally, IL-2 participates in the kidney injury process and may be a potential marker of kidney injury.

Parametric decay instability (PDI) is an important process in ionospheric heating. This paper focuses on the frequency and wavevector matching condition in the initial PDI process, the subsequent cascade stage, and the generation of strong Langmuir turbulence. A more general numerical model is established based on Maxwell equations and plasma dynamic equations by coupling high-frequency electromagnetic waves to low-frequency waves via ponderomotive force. The primary PDI, cascade process, and strong Langmuir turbulence are excited in the simulation. The matching condition in the initial PDI stage and cascade process is verified. The result indicates that the cascade ion acoustic wave may induce or accelerate the formation of cavitons and lead to the wavenumber spectrum being more enhanced at 2kL (where kL is the primary Langmuir wavenumber). The wavenumber spectra develop from discrete to continuous spectra, which is attributed to the caviton collapse and strong Langmuir turbulence.

Abstract Background Targeted puncture of an appropriate portal venous branch during transjugular intrahepatic portosystemic shunt (TIPS) procedure may reduce the risk of postprocedural overt hepatic encephalopathy (HE). This study aimed to describe blood distribution under portography and combined it with puncture site to determine portal flow diversion, and to evaluate its prognostic value in predicting post-TIPS overt HE. Methods In this retrospective analysis of patients with cirrhosis undergoing TIPS, we included 252 patients to describe blood distribution under portography and 243 patients to assess the association between portal flow diversion and post-TIPS overt HE. Results At the first stage, 51 (20.2%) patients were identified as type A (unilateral type with the right portal branch receives blood from splenic vein [SV]), 16 (6.4%) as type B (unilateral type with the right branch receives blood from superior mesenteric vein [SMV]) and 185 (73.4%) as type C (fully mixed type). At the second stage, 40 patients were divided into the SV group, 25 into the SMV group and 178 into the mixed group. Compared with the mixed group, the risk of post-TIPS overt HE was significantly higher in the SMV group (adjusted HR 3.70 [95% CI 2.01–6.80]; p

Abstract Background Liver fibrosis is thought to have a close relationship with lipid profile. The possible association between lipids and liver fibrosis of different etiologies has been widely explored. However, the association between lipids and liver fibrosis in patients infected with Schistosoma japonicum remains unclear. In the present study we undertook a preliminary exploration of the association between lipid profile and liver fibrosis, and developed a new predictive index for liver fibrosis in S. japonicum-infected patients. Methods A total of 1503 patients diagnosed with S. japonicum at Xiangyue Hospital, China were enrolled in this retrospective study. The patients were divided into two groups, i.e., those with and those without liver fibrosis, by two experienced schistosomiasis specialists, according to the results of liver ultrasound examination. Demographic, clinical, and laboratory data were collected. Multivariable logistic models were used to estimate the independent associations between lipid profile and liver fibrosis. Receiver operating characteristic (ROC) curves were used to assess the discriminative ability of the new index in predicting liver fibrosis in patients with schistosomiasis. Results Logistic regression analysis showed that high-density lipoprotein (HDL) [adjusted odds ratio (aOR), 95% confidence interval (CI) 7.334, 5.051–10.649; P

Abstract. Background:. As a non-invasive and effective diagnostic method for small intestinal bacterial overgrowth (SIBO), wild-use of breath test (BT) has demonstrated a high comorbidity rate in patients with diarrhea-predominant irritable bowel syndrome (IBS-D) and SIBO. Patients overlapping with SIBO respond better to rifaximin therapy than those with IBS-D only. Gut microbiota plays a critical role in both of these two diseases. We aimed to determine the microbial difference between IBS-D overlapping with/without SIBO, and to study the underlying mechanism of its sensitivity to rifaximin. Methods:. Patients with IBS-D were categorized as BT-negative (IBSN) and BT-positive (IBSP). Healthy volunteers (BT-negative) were enrolled as healthy control. The patients were clinically evaluated before and after rifaximin treatment (0.4 g bid, 4 weeks). Blood, intestine, and stool samples were collected for cytokine assessment and gut microbial analyses. Results:. Clinical complaints and microbial abundance were significantly higher in IBSP than in IBSN. In contrast, severe systemic inflammation and more active bacterial invasion function that were associated with enrichment of opportunistic pathogens were seen in IBSN. The symptoms of IBSP patients were relieved in different degrees after therapy, but the symptoms of IBSN rarely changed. We also found that the presence of IBSN-enriched genera (Enterobacter and Enterococcus) are unaffected by rifaximin therapy. Conclusions:. IBS-D patients overlapping with SIBO showed noticeably different fecal microbial composition and function compared with IBS-D only. The better response to rifaximin in those comorbid patients might associate with their different gut microbiota, which suggests that BT is necessary before IBS-D diagnosis and use of rifaximin. Registration:. Chinese Clinical Trial Registry, ChiCTR1800017911.

The treatment and healing of infected skin lesions is one of the major challenges in surgery. To solve this problem, collagen I (Col-I) and the antibacterial agent hydroxypropyltrimethyl ammonium chloride chitosan (HACC) were composited into the bacterial cellulose (BC) three-dimensional network structure by a novel membrane–liquid interface (MLI) culture, and a Col-I/HACC/BC (CHBC) multifunctional dressing was designed. The water absorption rate and water vapor transmission rate of the obtained CHBC dressing were 35.78 ± 2.45 g/g and 3084 ± 56 g m−2·day−1, respectively. The water retention of the CHBC dressing was significantly improved compared with the BC caused by the introduced Col-I and HACC. In vitro results indicated that the combined advantages of HACC and Col-I confer on CHBC dressings not only have outstanding antibacterial properties against Staphylococcus aureus (S. aureus) compared with BC and CBC, but also exhibit better cytocompatibility than BC and HBC to promote the proliferation and spread of NIH3T3 cells and HUVECs. Most importantly, the results of in vivo animal tests demonstrated that the CHBC dressings fully promoted wound healing for 8 days and exhibited shorter healing times, especially in the case of wound infection. Excellent skin regeneration effects and higher expression levels of collagen during infection were also shown in the CHBC group. We believe that CHBC composites with favorable multifunctionality have potential applications as wound dressings to treat infected wounds.

Both natural ginsenoside F2 and unnatural ginsenoside 3β,20S-Di-O-Glc-DM were reported to exhibit anti-tumor activity. Traditional approaches for producing them rely on direct extraction from Panax ginseng, enzymatic catalysis or chemical synthesis, all of which result in low yield and high cost. Metabolic engineering of microbes has been recognized as a green and sustainable biotechnology to produce natural and unnatural products. Hence we engineered the complete biosynthetic pathways of F2 and 3β,20S-Di-O-Glc-DM in Saccharomyces cerevisiae via the CRISPR/Cas9 system. The titers of F2 and 3β,20S-Di-O-Glc-DM were increased from 1.2 to 21.0 mg/L and from 82.0 to 346.1 mg/L at shake flask level, respectively, by multistep metabolic engineering strategies. Additionally, pharmacological evaluation showed that both F2 and 3β,20S-Di-O-Glc-DM exhibited anti-pancreatic cancer activity and the activity of 3β,20S-Di-O-Glc-DM was even better. Furthermore, the titer of 3β,20S-Di-O-Glc-DM reached 2.6 g/L by fed-batch fermentation in a 3 L bioreactor. To our knowledge, this is the first report on demonstrating the anti-pancreatic cancer activity of F2 and 3β,20S-Di-O-Glc-DM, and achieving their de novo biosynthesis by the engineered yeasts. Our work presents an alternative approach to produce F2 and 3β,20S-Di-O-Glc-DM from renewable biomass, which lays a foundation for drug research and development.

Introduction: Low back pain (LBP) is a prevalent and complex condition that poses significant medical, social, and economic burdens worldwide. The accurate and timely assessment and diagnosis of LBP, particularly non-specific LBP (NSLBP), are crucial to developing effective interventions and treatments for LBP patients. In this study, we aimed to investigate the potential of combining B-mode ultrasound image features with shear wave elastography (SWE) features to improve the classification of NSLBP patients.Methods: We recruited 52 subjects with NSLBP from the University of Hong Kong-Shenzhen Hospital and collected B-mode ultrasound images and SWE data from multiple sites. The Visual Analogue Scale (VAS) was used as the ground truth to classify NSLBP patients. We extracted and selected features from the data and employed a support vector machine (SVM) model to classify NSLBP patients. The performance of the SVM model was evaluated using five-fold cross-validation and the accuracy, precision, and sensitivity were calculated.Results: We obtained an optimal feature set of 48 features, among which the SWE elasticity feature had the most significant contribution to the classification task. The SVM model achieved an accuracy, precision, and sensitivity of 0.85, 0.89, and 0.86, respectively, which were higher than the previously reported values of MRI.Discussion: In this study, we aimed to investigate the potential of combining B-mode ultrasound image features with shear wave elastography (SWE) features to improve the classification of non-specific low back pain (NSLBP) patients. Our results showed that combining B-mode ultrasound image features with SWE features and employing an SVM model can improve the automatic classification of NSLBP patients. Our findings also suggest that the SWE elasticity feature is a crucial factor in classifying NSLBP patients, and the proposed method can identify the important site and position of the muscle in the NSLBP classification task.

Kidney disease (KD) is a life-threatening disease characterized by high morbidity and mortality in clinical settings, which can be caused by many reasons, and the incidence increases with age. However, supportive therapy and kidney transplantation still have limitations in alleviating KD progression. Recently, mesenchymal stem cells (MSCs) have shown great potential in repairing injury through their multidirectional differentiation and self-renewal ability. Of note, MSCs serve as a safe and effective therapeutic strategy for treating KD in preclinical and clinical trials. Functionally, MSCs ameliorate KD progression by regulating the immune response, renal tubular cell apoptosis, tubular epithelial–mesenchymal transition, oxidative stress, angiogenesis, and so on. In addition, MSCs exhibit remarkable efficacy in both acute kidney injury (AKI) and chronic kidney disease (CKD) through paracrine mechanisms. In this review, we outline the biological characteristics of MSCs, discuss the efficacy and mechanisms of MSCs-based therapy for KD, summarize the completed and ongoing clinical trials, as well as analyze limitations and new strategies, aiming to provide new ideas and approaches for the preclinical experiments and clinical trials of MSCs transplantation for KD.

Reconciling carbon emissions and GDP development is a challenge for most Chinese cities in the sustainable development process. Taking the Yangtze River Delta of China as an example, this study calculated carbon-emission inventories for five typical years and assigned anthropogenic carbon emissions to land-use types. A multi-objective particle swarm algorithm was used to consider three functions of land-use allocation: maximizing GDP, minimizing carbon emissions, and maximizing suitability. Thereafter, the technique for order of preference by similarity to ideal solution (TOPSIS) method was combined to find the optimal solution for carbon emission and economic development trade-offs. It is observed that Jiangsu has the largest carbon emissions in the Yangtze River Delta region; energy consumption is the main source of the carbon emissions, and industrial land is the most carbon intensive region. The land-use allocation obtained by multi-objective optimization with the TOPSIS evaluation method increases GDP and reduces carbon emissions, which is worthy of reference for land planners. Land use optimization from the perspective of balancing carbon emissions and economic development can provide a useful reference for the rational use of land resources and socio-economic sustainable development.

Over the past two decades, biodegradable metals (BMs) have emerged as promising materials to fabricate temporary biomedical devices, with the purpose of avoiding potential side effects of permanent implants. In this review, we first surveyed the current status of BMs in neuroscience, and briefly summarized the representative stents for treating vascular stenosis. Then, inspired by the convincing clinical evidence on the in vivo safety of Mg alloys as cardiovascular stents, we analyzed the possibility of producing biodegradable cerebrovascular Mg alloy stents for treating ischemic stroke. For these novel applications, some key factors should also be considered in designing BM brain stents, including the anatomic features of the cerebral vasculature, hemodynamic influences, neuro-cytocompatibility and selection of alloying elements. This work may provide insights into the future design and fabrication of BM neurological devices, especially for brain stents.

Abstract Background Deep learning methods have great potential to predict tumor characterization, such as histological diagnosis and genetic aberration. The objective of this study was to evaluate and validate the predictive performance of multimodality imaging-derived models using computer-aided diagnostic (CAD) methods for prediction of MDM2 gene amplification to identify well-differentiated liposarcoma (WDLPS) and lipoma. Materials and methods All 127 patients from two institutions were included with 89 patients in one institution for model training and 38 patients in the other institution for external validation between January 2012 and December 2018. For each modality, handcrafted radiomics analysis with manual segmentation was applied to extract 851 features for each modality, and six pretrained convolutional neural networks (CNNs) extracted 512–2048 deep learning features automatically. Extracted imaging-based features were selected via univariate filter selection methods and the recursive feature elimination algorithm, which were then classified by support vector machine for model construction. Integrated with two significant clinical variables, age and LDH level, a clinical-radiological model was constructed for identification WDLPS and lipoma. All differentiation models were evaluated using the area under the receiver operating characteristics curve (AUC) and their 95% confidence interval (CI). Results The multimodality model on deep learning features extracted from ResNet50 algorithm (RN-DL model) performed great differentiation performance with an AUC of 0.995 (95% CI 0.987–1.000) for the training cohort, and an AUC of 0.950 (95% CI 0.886–1.000), accuracy of 92.11%, sensitivity of 95.00% (95% CI 73.06–99.74%), specificity of 88.89% (95% CI 63.93–98.05%) in external validation. The integrated clinical-radiological model represented an AUC of 0.996 (95% CI 0.989–1.000) for the training cohort, and an AUC of 0.942 (95% CI 0.867–1.000), accuracy of 86.84%, sensitivity of 95.00% (95% CI 73.06–99.74%), and specificity of 77.78% (95% CI 51.92–92.63%) in external validation. Conclusions Imaging-based multimodality models represent effective discrimination abilities between WDLPS and lipoma via CAD methods, and might be a practicable approach in assistance of treatment decision.

Abstract Background Embryo implantation in sows is an important event during pregnancy. During this process, blastocysts undergo dramatic morphologic changes, and the endometrium becomes receptive. Studies have shown that developmental changes associated with the crosstalk between peri-implantation embryos and embryo-uterine are driven by various biomolecules secreted by the endometrium and embryos. In sows, changes in the uterus are also reflected in circulating body fluids and urine. Metabolomics reveals the metabolic state of cells, tissues, and organisms. In this study, we collected urine samples from large white sows during the peri-implantation period. The levels of urinary metabolites at different periods were analyzed using ultra-performance liquid chromatography/tandem mass spectrometry (UPLC–MS/MS) analysis techniques. Results A total of 32 samples were collected from 8 sows during the estrus period and at each phase of early pregnancy (9, 12, and 15 days of gestation). A total of 530 metabolites were identified with high confidence in all samples. Compared with samples collected during the estrus phase, 269 differential metabolites were found in samples obtained during early pregnancy. Conclusions The identified metabolites included lipids and lipid-like molecules, organic acids and their derivatives, organic oxygen compounds, organoheterocyclic compounds, benzenoids, among others. Metabolites, such as choline and pregnanediol-3-glucuronide, play important roles in pregnancy in sows and other animals. These results reveal the metabolic changes in urine of sows during early pregnancy phase. The differential urinary metabolites can be used for assessing peri-implantation status in sows. Understanding these metabolic changes may promote the management of pregnant sows through various interventions such as provision of proper nutrition.

The nickel (Ni) was coated onto carbon fibers (CFs) through an electroplating process to enhance the infiltration of aluminum (Al) matrix to fiber. Moreover, these continuous CFs reinforced Al matrix (CF/Al) composites were fabricated via a twin-roll casting method. Here, the effects of rolling speed, pouring temperature and solidification times on the morphologies of CF/Al composites were discussed. The results show that the rolling speed of 4 rad/min provided excellent integrity between reinforcement and matrix. Moreover, solidification times of 60 s offered an effective balance between the heat transfer and infiltration. Furthermore, pouring temperature of 700 °C was advantageous to infiltrate Al matrix into fibers. In addition, the influence of heat-treatment time on coating evolution and property of the materials were discussed through microstructure evolution, phases composition and mechanical property tests. The results confirmed that composites with outstanding mechanical properties were acquired at the temperature of 600 °C for 160 min in a tube furnace. Hence, it is concluded that the twin-roll casting approach has great application prospects in the fabrication of CF/Al composites with high tensile properties.

Abstract Objective The purpose of this study was to explore the efficacy and safety of transarterial chemoembolization (TACE) combined with apatinib and camrelizumab (TACE + AC) for unresectable hepatocellular carcinoma (HCC), and the impact of the timing of the combination on it. Methods In this single-arm retrospective study, consecutive data of patients with unresectable HCC treated to our hospital from March 2017 to September 2021 were collected. These patients were treated with TACE and started on camrelizumab and apatinib within one week of TACE. Camrelizumab 200 mg intravenously once every three weeks and apatinib 250 mg orally once daily. Repeat TACE treatment was available on an on-demand basis. The primary endpoints were overall survival (OS) and progression-free survival (PFS). Secondary endpoints included objective response rate (ORR), disease control rate (DCR), and safety. The univariate and multivariate Cox regression analyses were used to assess the effect of early and late combination on OS and PFS. Results A total of 80 patients were enrolled in this study. The median OS was 22.1 months (95% confidence interval [CI]: 13.8–30.5 months) and the median PFS was 15.7 months (95% CI: 14.7–16.6 months). The ORR was 58.8% (95% CI: 47.2–69.6) and DCR reached 81.2% (95% CI: 71.0–89.1). Multivariable Cox proportional hazard regression analyses showed that TACE late combined with apatinib and camrelizumab provided better OS than early combination (HR = 0.175, 95% CI:0.060–0.509, P = 0.001), as did PFS (HR = 0.422, 95% CI:0.184–0.967, P = 0.041). All treatment-related adverse events were tolerable, and no serious adverse events were observed. Conclusion TACE combined with apatinib plus camrelizumab for patients with unresectable HCC has promising antitumor activity and a manageable safety profile. For unresectable HCC with large tumor burden, late combination provides better OS and PFS compared to early combination.