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Abstract The aim of this study was to establish and validate the precision of a novel radiomics approach that integrates 18Fluorine-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)-computed tomography (CT) scan data with clinical information to improve the prognostication of survival rates in patients diagnosed with stage III Non-Small Cell Lung Cancer (NSCLC) who are not candidates for surgery. We evaluated pretreatment 18F-FDG PET-CT scans from 156 individuals diagnosed with stage III inoperable NSCLC at Shandong Cancer Hospital. These individuals were divided into two groups: a training set comprising 110 patients and an internal validation set consisting of 46 patients. By employing random forest classifier and cox proportional hazards model , we identified and utilized relevant features to create predictive models and a nomogram. The effectiveness of these models was assessed through the use of the receiver operating characteristics(ROC) curves, Kaplan–Meier (KM) curves, and the application of the nomogram. Our findings showed that the combined model, which integrates both clinical and radiomic data, outperformed those based solely on clinical or radiomic features in predicting 3-year overall survival(OS). Furthermore, calibration plots revealed a high level of agreement between predicted and actual survival times. The research successfully established a predictive radiomics model that integrates 18F-FDG PET/CT imaging with clinical indicators to enhance survival predictions for patients with stage III inoperable NSCLC.

Abstract An acidic gas is an important basic chemical raw material used for synthesizing fertilizers, insecticides, explosives, dyes, and salts. Alternatively, inorganic acidic gases that leak into the air have harmful effects on the human health, infrastructure, and cultural relics. Therefore, the demand for inorganic acidic gas sensors for air quality monitoring and management has continuously increased, enabling the development of various sensing technologies. Among them, fiber-optic sensors are promising for acidic gas detection because of their excellent in-situ measurement, resistance to corrosion, anti-electromagnetic interference, long service life, and smart structure. In particular, fiber-optic sensors have proven to be very useful for the in-situ detection and distributed monitoring of multiple gas parameters. However, the sensitivity, selectivity, repeatability, and limits of detection of these sensors can be improved to achieve acceptable performance levels for practical applications. In this review, we introduce fiber-optic sensors based on structured optical fibers and fiber gratings for detecting H2S, SO2, NO2, CO2, and N2O. The structures of the sensing regions, gas-sensitive materials, and measurement principles of these sensors are presented. The sensitivity, selectivity, limit of detection, and response time of the sensors are summarized. Finally, the future of fiber-optic sensors for the detection of inorganic acidic gases is discussed.

Abstract Policymakers and managers have increasingly adopted green bonds as a direct financing tool to address environmental degradation and climate change in emerging economies; however, the increasing green washing sentiments in the green bond market raise questions on whether green bonds can nudge polluting businesses to achieve green transformation. Therefore, this study joins the controversial debate by investigating the impact of green bond issuance on corporate environmental responsibilities and the potential impact mechanisms and economic consequences. Using the data of Chinese listed enterprises from 2011 to 2020 and the staggered issuance of green bonds as plausibly exogenous shocks, we determine that the enterprises in the experimental group that issued green bonds increased their environmental performance compared to their counterparts. Furthermore, this positive link is maintains after a series of robustness tests. Moreover, we identify that green bond issuance plausibly enhances environmental responsibility engagements through two governance channels, namely, internal management and external supervision. This beneficial effect appears more pronounced for subsamples of firms in low-polluting industries, without environmental subsidies and with higher managerial abilities. Furthermore, economic consequences indicate that the issuance of green bonds primarily motivates speculative shareholder benefits, as evidenced by short-term increases in stock yields but with limited impact on the short-run financial performance. Overall, these findings offer new evidence supporting that green financing tools could play a helpful hand toward environmental sustainability.

Arecoline, the principal active alkaloid in the areca nut, is known for its ability to induce euphoric sensations. Since ancient times, arecoline has garnered attention for its therapeutic potential in addressing psychiatric disorders and alleviating gastrointestinal ailments. However, in 2020, the International Agency for Research on Cancer has classified arecoline as 'probably carcinogenic to humans' (Group 2B carcinogen), supported by compelling mechanistic evidence. The mechanism of action of arecoline has been extensively studied, but the results of these studies are scattered and lack systematic integration and generalization. In this paper, we have systematically summarized the mechanism of arecoline within the oral cavity, central nervous system, cardiovascular system, and digestion system, in terms of both health functions and toxic effects. In addition, we found some concentration-effect relationship between arecoline in the central nervous system and digestive system, i.e., low doses are beneficial and high doses are harmful. By summarizing the mechanisms of arecoline, this review is poised to provide in-depth and valuable insights into the clinical practice and targeted therapy of arecoline in the future.

Abstract Background The existing staging system cannot meet the needs of accurate survival prediction. Accurate survival prediction for locally advanced cervical cancer (LACC) patients who have undergone concurrent radiochemotherapy (CCRT) can improve their treatment management. Thus, this present study aimed to develop and validate radiomics models based on pretreatment 18Fluorine-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)-computed tomography (CT) images to accurately predict the prognosis in patients. Methods The data from 190 consecutive patients with LACC who underwent pretreatment 18F-FDG PET-CT and CCRT at two cancer hospitals were retrospectively analyzed; 176 patients from the same hospital were randomly divided into training (n = 117) and internal validation (n = 50) cohorts. Clinical features were selected from the training cohort using univariate and multivariate Cox proportional hazards models; radiomic features were extracted from PET and CT images and filtered using least absolute shrinkage and selection operator and Cox proportional hazard regression. Three prediction models and a nomogram were then constructed using the previously selected clinical, CT and PET radiomics features. The external validation cohort that was used to validate the models included 23 patients with LACC from another cancer hospital. The predictive performance of the constructed models was evaluated using receiver operator characteristic curves, Kaplan Meier curves, and a nomogram. Results In total, one clinical, one PET radiomics, and three CT radiomics features were significantly associated with progression-free survival in the training cohort. Across all three cohorts, the combined model displayed better efficacy and clinical utility than any of these parameters alone in predicting 3-year progression-free survival (area under curve: 0.661, 0.718, and 0.775; C-index: 0.698, 0.724, and 0.705, respectively) and 5-year progression-free survival (area under curve: 0.661, 0.711, and 0.767; C-index, 0.698, 0.722, and 0.676, respectively). On subsequent construction of a nomogram, the calibration curve demonstrated good agreement between actually observed and nomogram-predicted values. Conclusions In this study, a clinico-radiomics prediction model was developed and successfully validated using an independent external validation cohort. The nomogram incorporating radiomics and clinical features could be a useful clinical tool for the early and accurate assessment of long-term prognosis in patients with LACC patients who undergo concurrent chemoradiotherapy.

Abstract Liver fibrosis is a reparative response to injury that arises from various etiologies, characterized by activation of hepatic stellate cells (HSCs). Periostin, a secreted matricellular protein, has been reported to participate in tissue development and regeneration. However, its involvement in liver fibrosis remains unknown. This study investigated the roles and mechanisms of Periostin in phenotypic transition of HSCs and relevant abnormal cellular crosstalk during liver fibrosis. The fate of hepatic stellate cells (HSCs) during liver fibrogenesis was investigated using single-cell and bulk RNA sequencing profiles, which revealed a significant proliferation of activated HSCs (aHSCs) in fibrotic livers of both humans and mice. αSMA-TK mice were used to demonstrate that depletion of proliferative aHSCs attenuates liver fibrosis induced by carbon tetrachloride and 3,5-diethoxycarbonyl-1,4-dihydrocollidine. Through integrating data from single-cell and bulk sequencing, Periostin was identified as a distinctive hallmark of proliferative aHSC subpopulation. Elevated levels of Periostin were detected in fibrotic livers of both humans and mice, primarily within aHSCs. However, hepatic Periostin levels were decreased along with depletion of proliferative aHSCs. Deficiency of Periostin led to reduced liver fibrosis and suppressed hepatocyte epithelial-mesenchymal transition (EMT). Periostin-overexpressing HSCs, exhibiting a proliferative aHSC phenotype, release bone morphogenetic protein-1 (Bmp-1), which activates EGFR signaling, inducing hepatocyte EMT and contributing to liver fibrosis. In conclusion, Periostin in aHSCs drives their acquisition of a proliferative phenotype and the release of Bmp-1. Proliferative aHSC subpopulation-derived Bmp-1 induces hepatocyte EMT via EGFR signaling, promoting liver fibrogenesis. Bmp-1 and Periostin should be potential therapeutic targets for liver fibrosis.

Due to the complex natures of dietary food components, it is difficult to elucidate how the compounds affect host health. Dietary food often selectively presents its mechanism of action on different cell types, and participates in the modulation of targeted cells and their microenvironments within organs. However, the limitations of traditional in vitro assays or in vivo animal experiments cannot comprehensively examine cellular heterogeneity and the tissue-biased influences. Single-cell RNA sequencing (scRNA-seq) has emerged as an indispensable methodology to decompose tissues into different cell types for the demonstration of transcriptional profiles of individual cells. ScRNA-seq applications has been summarized on three typical organs (brain, liver, kidney), and two representative immune- and tumor related health problems. The ever-increasing role of scRNA-seq in dietary food research with further improvement can provide sub-cellular information and the coupling between other cellular modalities. In this review, we propose utilizing scRNA-seq to more effectively capture the subtle and complex effects of food chemicals, and how they may lead to health problems at single-cell resolution. This novel technique will be valuable to elucidate the underlying mechanism of both the health benefits of food nutrients and the detrimental consequences food toxicants at the cellular level.

The green transformation of energy consumption is beneficial for promoting green development in China. This study constructed a green energy consumption evaluation index system and measured the green energy consumption levels in 30 provinces of China from 2000 to 2019 using the fuzzy comprehensive evaluation method. This study further employed the spatial Durbin model to examine influencing factors and spillover effects of green energy consumption. The results showed that, temporally, China’s green energy consumption levels had a fluctuating upward trend. While, spatially, the overall levels of green energy consumption in China showed apparent characteristics of “high in the west and low in the east”. In terms of influencing factors, environmental regulations played an important role in promoting green energy consumption in the region, while economic development, opening up, and industrial structure had considerably inhibiting effects. Additionally, economic development, opening up, and industrial structure of neighboring regions showed marked positive spillover effects, while urbanization level and technological innovation showed substantial negative spillover effects. The regional heterogeneity test results showed that environmental regulation and industrial structure rationalization were the important factors for promoting green energy consumption in the eastern region, environmental regulation played an important driving role in the central region, and opening to the outside world and technological innovation helped improve the level of green energy consumption in the western region.

Abstract Background Gestational diabetes mellitus (GDM) affects the metabolism of both the mother and fetus during and after pregnancy. Genetic factors are important in the pathogenesis of GDM, and associations vary by ethnicity. However, related studies about the relationship between the susceptibility genes and glucose traits remain limited in China. This study aimed to identify genes associated with GDM susceptibility in Chinese Han women and validate those findings using clinical data during pregnancy and postpartum period. Methods A genome-wide association study (GWAS) of 398 Chinese Han women (199 each with and without GDM) was conducted and associations between single nucleotide polymorphisms (SNPs) and glucose metabolism were identified by searching public databases. Relationships between filtered differential SNPs and glucose metabolism were verified using clinical data during pregnancy. The GDM group were followed up postpartum to evaluate the progression of glucose metabolism. Results We identified five novel SNPs with genome-wide significant associations with GDM: rs62069863 in TRPV3 gene and rs2232016 in PRMT6 gene were positive correlated with 1 h plasma glucose (1hPG) and 2 h plasma glucose (2hPG), rs1112718 in HHEX/EXOC6 gene and rs10460009 in LPIN2 gene were positive associated with fasting plasma glucose, 1hPG and 2hPG, rs927316 in GLIS3 gene was negative correlated with 2hPG. Of the 166 GDM women followed up postpartum, rs62069863 in TRPV3 gene was positively associated with fasting insulin, homoeostasis model assessment of insulin resistance. Conclusions The variants of rs62069863 in TRPV3 gene, rs2232016 in PRMT6 gene, rs1112718 in HHEX/EXOC6 gene, rs927316 in GLIS3 gene, and rs10460009 in LPIN2 gene were newly-identified susceptibility loci for GDM in the Chinese Han population. TRPV3 was associated with worse insulin resistance postpartum. Trial registration This study was registered in the Chinese Clinical Trial Registry. Trial registration number: ChiCTR2100043762. Date of first registration: 28/02/2021.

This Letter presents, for the first time, direct constraints on the black hole–halo mass relation using weak gravitational-lensing measurements. We construct type I and type II active galactic nucleus (AGN) samples from the Sloan Digital Sky Survey, with a mean redshift of 0.4 (0.1) for type I (type II) AGNs. This sample is cross correlated with weak-lensing shear from the Ultraviolet Near Infrared Optical Northern Survey. We compute the excess surface mass density of the halos associated with 36,181 AGNs from 94,308,561 lensed galaxies and fit the halo mass in bins of black hole mass. We find that more massive AGNs reside in more massive halos. The relation between halo mass and black hole mass is well described by a power law of slope 0.6 for both type I and type II samples, in agreement with models that link black hole growth to baryon feedback. We see no dependence on AGN type or redshift in the black hole–halo mass relation below a black hole mass of 10 ^8.5 M _⊙ . Above that mass, we find more massive halos for the low- z type II sample compared to the high- z type I sample, but this difference may be interpreted as systematic error in the black hole mass measurements. Our results are consistent with previous measurements for non-AGN galaxies. At a fixed black hole mass, our weak-lensing halo masses are consistent with galaxy rotation curves but significantly lower than galaxy-clustering measurements. Finally, our results are broadly consistent with state-of-the-art hydrodynamical cosmological simulations, providing a new constraint for black hole masses in simulations.

Noninvasive differentiation between the squamous cell carcinoma (SCC) and adenocarcinoma (ADC) subtypes of non-small cell lung cancer (NSCLC) could benefit patients who are unsuitable for invasive diagnostic procedures. Therefore, this study evaluates the predictive performance of a PET/CT-based radiomics model. It aims to distinguish between the histological subtypes of lung adenocarcinoma and squamous cell carcinoma, employing four different machine learning techniques. A total of 255 Non-Small Cell Lung Cancer (NSCLC) patients were retrospectively analyzed and randomly divided into the training (n = 177) and validation (n = 78) sets, respectively. Radiomics features were extracted, and the Least Absolute Shrinkage and Selection Operator (LASSO) method was employed for feature selection. Subsequently, models were constructed using four distinct machine learning techniques, with the top-performing algorithm determined by evaluating metrics such as accuracy, sensitivity, specificity, and the area under the curve (AUC). The efficacy of the various models was appraised and compared using the DeLong test. A nomogram was developed based on the model with the best predictive efficiency and clinical utility, and it was validated using calibration curves. Results indicated that the logistic regression classifier had better predictive power in the validation cohort of the radiomic model. The combined model (AUC 0.870) exhibited superior predictive power compared to the clinical model (AUC 0.848) and the radiomics model (AUC 0.774). In this study, we discovered that the combined model, refined by the logistic regression classifier, exhibited the most effective performance in classifying the histological subtypes of NSCLC.

Abstract MOFs have considerable adsorption capacity due to their huge specific surface area. They have the characteristics of photocatalysts for their organic ligands can absorb photons and produce electrons. In this paper, the photodegradation properties of TiO2 composites loaded with UiO-66 were investigated for the first time for MO. A series of TiO2@UiO-66 composites with different contents of TiO2 were prepared by a solvothermal method. The photocatalytic degradation of methyl orange (MO) was performed using a high-pressure mercury lamp as the UV light source. The effects of TiO2 loading, catalyst dosage, pH value, and MO concentration were investigated. The results showed that the degradation of MO by TiO2@UiO-66 could reach 97.59% with the addition of only a small amount of TiO2 (5 wt%). TiO2@UiO-66 exhibited significantly enhanced photoelectron transfer capability and inhibited efficient electron–hole recombination compared to pure TiO2 in MO degradation. The composite catalyst indicated good stability and reusability when they were recycled three times, and the photocatalytic reaction efficiencies were 92.54%, 88.76%, and 86.90%. The results provide a new option to design stable, high-efficiency MOF-based photocatalysts.

The present study investigates the chemical composition variances among Pinelliae Rhizoma, a widely used Chinese herbal medicine, and its common adulterants including Typhonium flagelliforme, Arisaema erubescens, and Pinellia pedatisecta. Utilizing the non-targeted metabolomics technique of employing UHPLC-Q-Orbitrap HRMS, this research aims to comprehensively delineate the metabolic profiles of Pinelliae Rhizoma and its adulterants. Multivariate statistical methods including PCA and OPLS-DA are employed for the identification of differential metabolites. Volcano plot analysis is utilized to discern upregulated and downregulated compounds. KEGG pathway analysis is conducted to elucidate the differences in metabolic pathways associated with these compounds, and significant pathway enrichment analysis is performed. A total of 769 compounds are identified through metabolomics analysis, with alkaloids being predominant, followed by lipids and lipid molecules. Significant differential metabolites were screened out based on VIP > 1 and p-value < 0.05 criteria, followed by KEGG enrichment analysis of these differential metabolites. Differential metabolites between Pinelliae Rhizoma and Typhonium flagelliforme, as well as between Pinelliae Rhizoma and Pinellia pedatisecta, are significantly enriched in the biosynthesis of amino acids and protein digestion and absorption pathways. Differential metabolites between Pinelliae Rhizoma and Arisaema erubescens are mainly enriched in tyrosine metabolism and phenylalanine metabolism pathways. These findings aim to provide valuable data support and theoretical references for further research on the pharmacological substances, resource development and utilization, and quality control of Pinelliae Rhizoma.

Sulforaphane (SFN) is an antioxidant. Unsaturated fatty acids are rich in fish oil, and they are indispensable fatty acids for aquatic animals to grow and reproduce. However, fish oil is easily oxidized, which could have adverse effects on aquatic animals. In this study, Litopenaeus vannamei was divided into four groups: fresh fish oil group (control group), oxidized fish oil group (OFO group), OFO plus low-concentration SFN group (OFO + SL group), and OFO plus high-concentration SFN group (OFO + SH group). A 28-day experiment was conducted, and the antioxidant capacity, inflammation, autophagy, and pathological characteristics were investigated to explore whether SFN could protect L. vannamei from oxidative stress induced by OFO. Results showed that OFO significantly increased the contents of MDA in hepatopancreas, muscle and serum, while high concentrations of SFN significantly decreased the MDA compared with the OFO group (P

AimThis study aimed to investigate the effects of intensive psychological intervention care on adverse emotions and post-traumatic stress disorder (PTSD) symptoms in female teenage patients after induced abortion.MethodsThis prospective cohort study included 100 teenage female patients seeking induced abortion who were randomly divided into two groups: the intervention group (n = 50) and the control group (n = 50). The intervention group received intensive psychological intervention care, while the control group received standard routine nursing. The scores of the PTSD checklist for DSM-5 (PCL-5), self-rating depression (SDS), and self-rating anxiety scale (SAS) were compared between the two groups at 1 month and 3 months after the operation.ResultsThe intervention group had lower risk of developing PTSD (24% vs. 44%), depression (10% vs. 32%), and anxiety (0% vs. 12%) symptoms at 1 month after the surgery. However, there were no significant differences observed between the two groups at 3 months after the surgery. Furthermore, the intervention group had significantly lower scores in PCL-5 (27.4 ± 5.4 vs. 31.8 ± 5.7; 20.5 ± 7.1 vs. 25.0 ± 7.5; p

Acoustically actuated magnetoelectric (ME) antennas utilize acoustic wave resonance to complete the process of receiving and transmitting signals, which promotes the development of antenna miniaturization technology. This paper presents a bilayer magnetostrictive/AlN ME laminated antenna. The proposed laminated antenna uses the FeGa/FeGaB bilayer materials as magnetostrictive materials, which combine the advantages of soft magnetic properties of FeGa and the low loss of FeGaB. First, multiphysics modeling and analysis are performed for the proposed ME laminated antenna by finite element method (FEM). The positive/inverse ME effects and the influences of the volume ratio of the FeGa/FeGaB bilayer on the antenna performance are studied. The results show that the output voltage and ME coefficient of the FeGa/FeGaB bilayer magnetostrictive material with a volume ratio of 1:1 are 3.97 times and 195.8% higher than that of the single FeGaB layer, respectively. The eddy current loss is 52.08% lower than that of single-layer FeGa. According to the surface equivalence principle, the far-field radiation process is simulated. The results show that the gain of the ME antenna is 15 dB larger than that of the same-size micro-loop antenna, and the gain of the ME antenna is about −44.9 dB. The improved performance and magnetic tunability of the proposed bilayer magnetostrictive materials make ME antennas excellent candidates for portable devices and implantable medical devices.

Abstract Background Aerobic glycolysis has been recognized as one of the growth-promoting metabolic alterations of cancer cells. Emerging evidence indicates that nuclear factor κB (NF-κB) plays significant roles in metabolic adaptation in normal cells and cancer cells. However, whether and how NF-κB regulates metabolic reprogramming in hepatocellular carcinoma (HCC), specifically hepatitis B virus X protein (HBx)-initiated HCC, has not been determined. Methods A dataset of the HCC cohort from the TCGA database was used to analyse the expression of NF-κB family members. Expression of NF-κBp65 and phosphorylation of NF-κBp65 (p-p65) were detected in liver tissues from HBV-related HCC patients and normal controls. A newly established HBx +/+/NF-κBp65 f/f and HBx +/+ /NF-κBp65 Δhepa spontaneous HCC mouse model was used to investigate the effects of NF-κBp65 on HBx-initiated hepatocarcinogenesis. Whether and how NF-κBp65 is involved in aerobic glycolysis induced by HBx in hepatocellular carcinogenesis were analysed in vitro and in vivo. Results NF-κBp65 was upregulated in HBV-related HCC, and HBx induced NF-κBp65 upregulation and phosphorylation in vivo and in vitro. Hepatocyte-specific NF-κBp65 deficiency remarkably decreased HBx-initiated spontaneous HCC incidence in HBx-TG mice. Mechanistically, HBx induced aerobic glycolysis by activating NF-κBp65/hexokinase 2 (HK2) signalling in spontaneous hepatocarcinogenesis, and overproduced lactate significantly promoted HCC cell pernicious proliferation via the PI3K (phosphatidylinositide 3-kinase)/Akt pathway in hepatocarcinogenesis. Conclusion The data elucidate that NF-κBp65 plays a pivotal role in HBx-initiated spontaneous HCC, which depends on hyperactive NF-κBp65/HK2-mediated aerobic glycolysis to activate PI3K/Akt signalling. Thus, phosphorylation of NF-κBp65 will be a potential therapeutic target for HBV-related HCC.

Chemical-exfoliated borophene and its application in multi-imaging guided photothermal therapy.

Chlorinated paraffins (CPs) are a notoriously known class of compounds that stand amongst the most wide-spread persistent organic pollutants. Therefore, their reliable, repeatable, and reproducible quantitative analysis using well-defined reference standards is of utmost importance. In view of the increasing demand for constitutionally and stereochemically defined CP standards, we have synthesized a stereoisomeric mixture of 3,4,7,8-tetrachlorodecane. One stereoisomer – (3R,4R,7S,8S)-3,4,7,8-tetrachlorodecane was separated from the mixture, and enriched fractions of residual stereoisomers were achieved through crystallisation of the residual mother liquors. The molecular structure of the single isolated stereoisomer was confirmed through single-crystal X-ray crystallographic data. One fraction of 3,4,7,8-tetrachlorodecane stereoisomers was successfully separated on a chiral stationary phase using supercritical fluid chromatography hyphenated to mass spectrometry (column: Chiral ART Amylose-C; mobile phase: CO2/MeOH (96/4 v/v) with 0.1% diethylamine). The reported separation of stereoisomers is unprecedented in CP analysis so far.

The measurement of hemoglobin is a vital index for diagnosing and monitoring diseases in clinical practice. At present, solutions need to be found for the soreness, high risk of infection, and inconvenient operation associated with invasive detection methods. This paper proposes a method for non-invasively detecting hemoglobin levels based on multi-wavelength photoplethysmography (PPG) signals. AFE4490 and TMUX1109 were used to implement the low-cost collection of an eight-LED transmissive PPG signal. We used seven regular LEDs and one broadband LED (Osram SFH4737) as light sources. Additionally, a finger clip integrating multiple sensors was designed and manufactured via 3D printing to simultaneously monitor the LED–sensor distance and the pressure from the tester’s finger during PPG signal acquisition. We used a method to extract features from PPG signals using a sliding-window’s variance and an evaluation metric for PPG signals based on the AdaCost classification. Data were gathered from 56 participants from the Nephrology department, including 16 anemic patients. Pearson correlation analysis was conducted on the collected data to remove any data with a weak correlation. The advantage of using a broadband LED as a light source was also demonstrated. Several non-invasive hemoglobin regression models were created by applying AdaBoost, BPNN, and Random Forest models. The study’s results indicate that the AdaBoost model produced the best performance, with a mean absolute error (MAE) of 2.67 g/L and a correlation coefficient (R2) of 0.91 The study results show that the device we designed and manufactured can achieve effective non-invasive hemoglobin detection and represents a new methodological approach to obtaining measurements that can be applied in a clinical setting.

ObjectiveTo assess the diagnostic value of the Copenhagen index for ovarian malignancy.MethodsPubMed, Web of Science, the Cochrane Library, Embase, CBM, CNKI, and WanFang databases were searched throughout June 2021. Statistical analyses were performed using Stata 12, Meta-DiSc, and RevMan 5.3. The pooled sensitivity, specificity, and diagnostic odds ratio were calculated, the summary receiver operating characteristic curve was drawn, and the area under the curve was calculated.ResultsTen articles, including 11 studies with a total of 5266 patients, were included. The pooled sensitivity, specificity, and diagnostic odds ratio were 0.82 [95% CI (0.80-0.83)], 0.88 [95% CI (0.87-0.89)], and 57.31 [95% CI (32.84-100.02)], respectively. The area under the summary receiver operating characteristics curve and the Q index were 0.9545 and 0.8966, respectively.ConclusionOur systematic review shows that the sensitivity and specificity of the Copenhagen index are high enough for it to be used in a clinical setting to provide accurate ovarian cancer diagnosis without considering menopausal status.

Traditional non-resorbable bone wax has been used in clinical surgery for more than 100 years. However, residual bone wax has been proven to cause numerous complications. In this study, a novel resorbable bone wax was designed to overcome the disadvantages of traditional non-resorbable bone wax. Alkylene oxide copolymers were used as the main component of resorbable bone wax; additionally, β-tricalcium phosphate and starch microspheres were added to enhance bone regeneration and hemostatic ability. This novel resorbable bone wax has a high potential for clinical translation and is expected to be developed as a substitute for traditional bone wax.

As a complication of malignant tumors, brain metastasis (BM) seriously threatens patients’ survival and quality of life. Accurate detection of BM before determining radiation therapy plans is a paramount task. Due to the small size and heterogeneous number of BMs, their manual diagnosis faces enormous challenges. Thus, MRI-based artificial intelligence-assisted BM diagnosis is significant. Most of the existing deep learning (DL) methods for automatic BM detection try to ensure a good trade-off between precision and recall. However, due to the objective factors of the models, higher recall is often accompanied by higher number of false positive results. In real clinical auxiliary diagnosis, radiation oncologists are required to spend much effort to review these false positive results. In order to reduce false positive results while retaining high accuracy, a modified YOLOv5 algorithm is proposed in this paper. First, in order to focus on the important channels of the feature map, we add a convolutional block attention model to the neck structure. Furthermore, an additional prediction head is introduced for detecting small-size BMs. Finally, to distinguish between cerebral vessels and small-size BMs, a Swin transformer block is embedded into the smallest prediction head. With the introduction of the F2-score index to determine the most appropriate confidence threshold, the proposed method achieves a precision of 0.612 and recall of 0.904. Compared with existing methods, our proposed method shows superior performance with fewer false positive results. It is anticipated that the proposed method could reduce the workload of radiation oncologists in real clinical auxiliary diagnosis.

Abstract The future sixth generation (6G) is going to face the significant challenges of massive connections and green communication. Recently, reconfigurable intelligent surfaces (RIS) and non-orthogonal multiple access (NOMA) have been proposed as two key technologies to solve the above problems. Motivated by this fact, we consider a downlink RIS-aided NOMA system, where the source aims to communicate with the two NOMA users via RIS. Considering future network supporting real-time service, we investigate the system performance with the view of effective capacity (EC), which is an important evaluation metric of delay sensitive systems. Specifically, we derive the analytical expressions of the EC of the near and far users. To obtain more useful insights, we deduce the analytical approximation expressions of the EC in the low signal-to-noise-ratio approximation by utilizing Taylor expansion. Moreover, we provide the results of orthogonal multiple access (OMA) for the purpose of comparison. It is found that (1) The number of RIS components and the transmission power of the source have important effects on the performance of the considered system; (2) Compared with OMA, NOMA system has higher EC due to the short transmission time.

Abstract Berberine (BBR) has been explored as a potential anti-liver fibrosis agent, but the underlying mechanisms are unknown. In the current study, we aimed to investigate the molecular mechanisms underlying the effect of BBR against liver fibrogenesis in thioacetamide (TAA) and carbon tetrachloride (CCl4) induced mouse liver fibrosis. In addition to i.p. injection with TAA or CCl4, mice in the treatment group received BBR intragastrically. Concurrently, combined with TAA and BBR treatment, mice in the inhibitor group were injected i.p. with ferrostatin-1 (Fer-1). Hepatic stellate cells (HSCs) were also used in the study. Our results showed that BBR obviously alleviated mouse liver fibrosis and restored mouse liver function; however, the pharmacological effects of BBR against liver fibrosis were significantly diminished by Fer-1 treatment. Mechanically, BBR impaired the autophagy–lysosome pathway (ALP) and increased cell reactive oxygen species (ROS) production in HSCs. ROS accelerated the breakdown of the iron-storage protein ferritin and sped up iron release from ferritin, which resulted in redox-active iron accumulation in HSCs. Lipid peroxidation and glutathione (GSH) depletion triggered by the Fenton reaction promoted ferroptosis and attenuated liver fibrosis. Furthermore, impaired autophagy enhanced BBR-mediated ferritin proteolysis to increase cellular ferrous overload via the ubiquitin–proteasome pathway (UPS) in HSCs and triggered HSC ferroptosis. Collectively, BBR alleviated liver fibrosis by inducing ferrous redox to activate ROS-mediated HSC ferroptosis. Our findings may be exploited clinically to provide a potential novel therapeutic strategy for liver fibrosis.

To explore the influence of different densities of Sinonovacula constricta on the composition of easily degradable organic matter and related functional bacteria, four experimental ecosystems were established: three polyculture systems (PMB1, PMB2, and PMB3) of Portunus trituberculatus and Marsupenaeus japonicus with different stocking densities of S. constricta (11.6, 23.1, and 34.7×104 ind./hm2, respectively) and a polyculture system with only P. trituberculatus and M. japonicus (PM). Among the easily degradable organic components in all aquaculture systems, protein content was the highest (0.74%~0.86%), followed by carbohydrates (0.16%~0.21%) and lipids (0.06%~0.13%). In the high-density (34.7×104 ind./hm2) S. constricta mixed culture system, the contents of carbohydrates, lipids, and proteins in the sediment were significantly lower than those of the other polyculture systems. The number of cellulose-decomposing bacteria in PMB3 was 3.79×106 cfu/g, which was significantly higher than that in the other systems. The number of starch-degrading bacteria and glutin-degrading bacteria was the lowest in PMB3, 1.26×104 cfu/g, and 160.00 cfu/g, respectively. The number of lipid-degrading bacteria in PMB3 was 0.77×104 cfu/g, which was significantly lower than that in the other systems. The easily degradable organics content in sediment was significantly positively correlated with the corresponding functional bacteria. The results showed that mixed culture of S. constricta could reduce the content of easily degradable organics in the sediment of mariculture ponds and change the number of functional bacteria in the sediment and the availability of degradable organic sediments may determine the abundance of corresponding degradable bacteria.

Abstract Nanomaterials' unique structures at the nanometer level determine their incredible functions, and based on this, they can be widely used in the field of nanomedicine. However, nanomaterials do possess disadvantages that cannot be ignored, such as burst release, rapid elimination, and poor bioadhesion. Hydrogels are scaffolds with three‐dimensional structures, and they exhibit good biocompatibility and drug release capacity. Hydrogels are also associated with disadvantages for biomedical applications such as poor anti‐tumor capability, weak bioimaging capability, limited responsiveness, and so on. Incorporating nanomaterials into the 3D hydrogel network through physical or chemical covalent action may be an effective method to avoid their disadvantages. In nanocomposite hydrogel systems, multifunctional nanomaterials often work as the function core, giving the hydrogels a variety of properties (such as photo‐thermal conversion, magnetothermal conversion, conductivity, targeting tumor, etc.). While, hydrogels can effectively improve the retention effect of nanomaterials and make the nanoparticles have good plasticity to adapt to various biomedical applications (such as various biosensors). Nanocomposite hydrogel systems have broad application prospects in biomedicine. In this review, we comprehensively summarize and discuss the most recent advances of nanomaterials composite hydrogels in biomedicine, including drug and cell delivery, cancer treatment, tissue regeneration, biosensing, and bioimaging, and we also briefly discussed the current situation of their commoditization in biomedicine.

Prestressed rebars are usually used to apply vertical prestress to concrete to prevent web cracking. The reduction of working stress will affect the durability of the structure. However, the existing working stress detection methods for prestressed rebars still need to be improved. To monitor the working stress of rebars, a magnetic resonance sensor was introduced to carry out experimental research. The correlation between rebar stress and the sensor’s induced voltage was theoretically analyzed using the magnetoelastic effect and magnetic resonance theory. A working stress monitoring method for prestressed rebars based on magnetic resonance was proposed. Working stress monitoring experiments were carried out for 16 mm, 18 mm, and 20 mm diameter rebars. The results showed that the induced voltage peak-to-peak value and the rebar prestress were nonlinearly correlated under different working conditions. Correlations between the characteristic indicators and the rebar working stress were obtained using nonlinear and linear fit. The cubic polynomial segmented fit outperformed the gradient overall linear fit, with the goodness of fit R2 greater than 0.96. The average relative error values of working stress monitoring were less than 5% under different working conditions. This provides a new method for working stress measurement of vertical prestressed rebars.

A higher dietary diversity score (DDS) and a lower energy-adjusted dietary inflammatory index (E-DII) may be associated with lower risks of type 2 diabetes (T2D) and mortality. This cohort study aimed to investigate the associations of DDS and E-DII with all-cause mortality, incidence of T2D, and mortality of T2D, as well as the joint effects of these two dietary factors. A total of 181,360 participants without all types of diabetes at baseline from the UK Biobank and 42,139 participants from the US NHANES were included. Cox proportional hazards models were used to assess the associations of DDS and E-DII with outcomes. In the UK Biobank data, 8338 deaths, 3416 incident T2D cases, and 353 T2D deaths occurred during a median follow-up of 12.5 years. In the US NHANES data, 6803 all-cause deaths and 248 T2D-specific deaths were recorded during a median follow-up of 9.6 years. We observed that higher DDS and lower E-DII were significantly associated with lower risks of total mortality and incident T2D. Compared with low DDS, the hazard ratios (HRs) and 95% confidence intervals (CIs) of high DDS were 0.69 (0.64, 0.74) for all-cause mortality, 0.79 (0.70, 0.88) for incident T2D in the UK Biobank, and 0.69 (0.61, 0.78) for all-cause mortality in the US NHANES. Compared with participants in tertile 3 of E-DII, those in tertile 1 had a lower risk of overall death [HR 0.86 (95% CI: 0.81, 0.91) in UK Biobank; 0.83 (0.77, 0.88) in US NHANES] and incident T2D [0.86 (0.79, 0.94)] in UK Biobank. No evidence was observed of the interactive effects of DDS and E-DII on either all-cause mortality or the incidence and mortality of T2D. There was no significant association found between any exposure and T2D mortality in this study. In conclusion, our results revealed that higher DDS and lower E-DII were associated with both total mortality and incident T2D in UK and US adults.

Radar emitter identification (REI) aims to extract the fingerprint of an emitter and determine the individual to which it belongs. Although many methods have used deep neural networks (DNNs) for an end-to-end REI, most of them only focus on a single view of signals, such as spectrogram, bi-spectrum, signal waveforms, and so on. When the electromagnetic environment varies, the performance of DNN will be significantly degraded. In this paper, a multi-view adaptive fusion network (MAFN) is proposed by simultaneously exploring the signal waveform and ambiguity function (AF). First, the original waveform and ambiguity function of the radar signals are used separately for feature extraction. Then, a multi-scale feature-level fusion module is constructed for the fusion of multi-view features from waveforms and AF, via the Atrous Spatial Pyramid Pooling (ASPP) structure. Next, the class probability is modeled as Dirichlet distribution to perform adaptive decision-level fusion via evidence theory. Extensive experiments are conducted on two datasets, and the results show that the proposed MAFN can achieve accurate classification of radar emitters and is more robust than its counterparts.

Social recommendation systems can improve recommendation quality in cases of sparse user–item interaction data, which has attracted the industry’s attention. In reality, social recommendation systems mostly mine real user preferences from social networks. However, trust relationships in social networks are complex and it is difficult to extract valuable user preference information, which worsens recommendation performance. To address this problem, this paper proposes a social recommendation algorithm based on multi-graph contrastive learning. To ensure the reliability of user preferences, the algorithm builds multiple enhanced user relationship views of the user’s social network and encodes multi-view high-order relationship learning node representations using graph and hypergraph convolutional networks. Considering the effect of the long-tail phenomenon, graph-augmentation-free self-supervised learning is used as an auxiliary task to contrastively enhance node representations by adding uniform noise to each layer of encoder embeddings. Three open datasets were used to evaluate the algorithm, and it was compared to well-known recommendation systems. The experimental studies demonstrated the superiority of the algorithm.

Abstract Objective: To investigate the expression level and significance of T cell immunoglobulin and mucin-domain containing molecules-3 (Tim-3) and interleukin-7 (IL-7) in CD4+ T lymphocytes in peripheral blood of patients with coronary heart disease (CHD). Methods: 75 patients with CHD treated at our hospital were selected and classified as mild group (25 cases), moderate group (25 cases) and severe group (25 cases), according to the severity of illness. Twenty-five healthy volunteers who underwent a physical examination at our hospital during the same period were selected as the control group. The expression level of Tim-3 in CD4+ T lymphocytes in peripheral blood of patients in four groups was detected by flow cytometry and quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR). The expression level of IL-7 in peripheral blood serum was measured by enzyme-linked immunosorbent assay (ELISA). Correlation analyses of Tim-3 and IL-7, Tim-3 and disease severity and IL-7 and disease severity were performed, respectively. Results: Flow cytometry and qRT-PCR demonstrated that the expression of Tim-3 in CD4+ T lymphocytes in peripheral blood of patients with CHD increased with the aggravation of the disease. ELISA showed that the tendency of IL-7 expression in peripheral blood serum was consistent with the expression of Tim-3, and the expression of Tim-3 had a positive correlation with IL-7. The expression levels of both Tim-3 and IL-7 were positively correlated with the Gensini score. Conclusion: The expression of Tim-3 and IL-7 in peripheral blood of patients with CHD was upregulated and increased with the aggravation of CHD.

Alzheimer’s disease (AD) is a common neurodegenerative disorder with progressive cognitive impairment in the elderly. Beta-amyloid (Aβ) formation and its accumulation in the brain constitute one of the pathological hallmarks of AD. Until now, how to modulate Aβ formation in hippocampal neurons remains a big challenge. Herein, we investigated whether the exosomal transfer of microRNA (miR) relates to amyloid pathology in the recipient neuron cells. We isolated circulating small extracellular vesicles (sEVs) from AD patients and healthy controls, determined the miR-342-5p level in the sEVs by RT-PCR, and evaluated its diagnostic performance in AD. Then, we took advantage of biomolecular assays to estimate the role of miR-342-5p in modulating the amyloid pathway, including amyloid precursor protein (APP), beta-site APP cleaving enzyme 1 (BACE1), and Aβ42. Furthermore, we subjected HT22 cells to the sEVs from the hippocampal tissues of transgenic APP mice (Exo-APP) or C57BL/6 littermates (Exo-CTL), and the Exo-APP enriched with miR-342-5p mimics or the control to assess the effect of the sEVs’ delivery of miR-342-5p on Aβ formation. We observed a lower level of miR-342-5p in the circulating sEVs from AD patients compared with healthy controls. MiR-342-5p participated in Aβ formation by modulating BACE1 expression, specifically binding its 3′-untranslated region (UTR) sequence. Exo-APP distinctly promoted Aβ42 formation in the recipient cells compared to Exo-CTL. Intriguingly, miR-342-5p enrichment in Exo-APP ameliorated amyloid pathology in the recipient cells. Our study indicated that miR-342-5p was dysregulated in human circulating sEVs from AD patients; sEV transfer of miR-342-5p ameliorates Aβ formation by modulating BACE1 expression. These findings highlight the promising potential of exosomal miRNAs in AD clinical therapy.

Rotating backward extrusion (RBE) is one of severe plastic deformation (SPD) methods used to produce cylindrical components with a very large strain by a single pass. In this study, the microstructure and texture evolution in the different regions of Mg-12Gd-4Y-2Zn-0.5Zr (wt.%) alloys via RBE process were investigated by using optical microscopy (OM), X-ray diffraction (XRD), scanning electron microscopy (SEM) and electron back-scatter diffraction (EBSD). The results showed that the cup-shaped sample formed by RBE process exhibited typical gradient microstructure expanding from its inner wall to outer wall along the radial direction (RD). The average grain size of the RBEed sample decreased when the radius decreased from the edge region to the center region along the RD, which was attributed to the different strains and strain rates in the different regions. It also could be observed that the center region showed highest deformation and the edge region exhibited the lowest deformation in the RBEed sample along the RD. In addition, the grain refinement mechanisms of the experimental alloy containing long-period stacking ordered (LPSO) phases after RBE with 100 N were continuous dynamic recrystallization (CDRX), discontinuous dynamic recrystallization (DDRX) and particle stimulated nucleation (PSN).

In this work, TiO2/CdS nanocomposites with co-exposed {101}/[111]-facets (NH4F-TiO2/CdS), {101}/{010} facets (FMA-TiO2/CdS), and {101}/{010}/[111]-facets (HF-TiO2/CdS and Urea-TiO2/CdS) were successfully synthesized through a one-pot solvothermal method by using [Ti4O9]2− colloidal solution containing CdS crystals as the precursor. The crystal structure, morphology, specific surface area, pore size distribution, separation, and recombination of photogenerated electrons/holes of the TiO2/CdS nanocomposites were characterized. The photocatalytic activity and cycling performance of the TiO2/CdS nanocomposites were also investigated. The results showed that as-prepared FMA-TiO2/CdS with co-exposed {101}/{010} facets exhibited the highest photocatalytic activity in the process of photocatalytic degradation of methyl orange (MO), and its degradation efficiency was 88.4%. The rate constants of FMA-TiO2/CdS was 0.0167 min−1, which was 55.7, 4.0, 3.7, 3.5, 3.3, and 1.9 times of No catalyst, CdS, HF-TiO2/CdS, NH4F-TiO2/CdS, CM-TiO2, Urea-TiO2/CdS, respectively. The highest photocatalytic activity of FMA-TiO2/CdS could be attributed to the synergistic effects of the largest surface energy, co-exposed {101}/{010} facets, the lowest photoluminescence intensity, lower charge-transfer resistance, and a higher charge-transfer efficiency.

In this work, we systematically studied the deposition, characterization, and crystal structure modeling of ScAlN thin film. Measurements of the piezoelectric device’s relevant material properties, such as crystal structure, crystallographic orientation, and piezoelectric response, were performed to characterize the Sc0.29Al0.71N thin film grown using pulsed DC magnetron sputtering. Crystal structure modeling of the ScAlN thin film is proposed and validated, and the structure–property relations are discussed. The investigation results indicated that the sputtered thin film using seed layer technique had a good crystalline quality and a clear grain boundary. In addition, the effective piezoelectric coefficient d33 was up to 12.6 pC/N, and there was no wurtzite-to-rocksalt phase transition under high pressure. These good features demonstrated that the sputtered ScAlN is promising for application in high-coupling piezoelectric devices with high-pressure stability.