Comparative metabolomics reveals serum metabolites changes in goats during different developmental stages.

Goats can provide meat, milk and skins for humans and are livestock with high economic benefits. However, despite their economic significance, the comprehensive analysis of goats' serum metabolic profile and its intricate alterations throughout their developmental journey remains conspicuously absent. To investigate the stage-specificity and dynamic change characteristics of metabolites during the growth and development of goats, this study compared the alterations in serum hormone levels and serum biochemical markers across different developmental stages of female goats (1, 60, 120 and 180 days old; n = 5). Additionally, a serum untargeted LC-MS metabolomics analysis was conducted. A total of 504 DAMs were identified with age. The results indicated that PE, PC, Lyso-PE, Lyso-PC and FAFHA may play important roles in lipid metabolism in goats after birth. Weighted gene co-expression network analysis (WGCNA) identified two metabolite modules (Turquoise and Yellow) and key metabolites within these modules that were significantly associated with phenotypic features. L-carnitine may be a metabolite related to muscle development in goats. The findings of this study demonstrate notable variations in serum metabolites across distinct developmental phases in goats. Lipids and organic acids play important roles in different developmental stages of goats.

Altered resting-state brain functional activities and networks in Crohn's disease: a systematic review.

Background: Crohn's disease (CD) is a non-specific chronic inflammatory disease of the gastrointestinal tract and is a phenotype of inflammatory bowel disease (IBD). The current study sought to compile the resting-state functional differences in the brain between CD patients and healthy controls. Methods: The online databases PubMed, Web of Science Core, and EMBASE were used to find the published neuroimage studies. The search period was from the beginning through December 15, 2023. The predetermined inclusion and exclusion criteria allowed for the identification of the studies. The studies were assembled by two impartial reviewers, who also assessed their quality and bias. Results: This review comprised 16 resting-state fMRI studies in total. The included studies generally had modest levels of bias. According to the research, emotional processing and pain processing were largely linked to increased or decreased brain activity in patients with CD. The DMN, CEN, and limbic systems may have abnormalities in patients with CD, according to research on brain networks. Several brain regions showed functional changes in the active CD group compared to the inactive CD group and the healthy control group, respectively. The abnormalities in brain areas were linked to changes in mood fluctuations (anxiety, melancholy) in patients with CD. Conclusion: Functional neuroimaging helps provide a better understanding of the underlying neuropathological processes in patients with CD. In this review, we summarize as follows: First, these findings indicate alterations in brain function in patients with CD, specifically affecting brain regions associated with pain, emotion, cognition, and visceral sensation; second, disease activity may have an impact on brain functions in patients with CD; and third, psychological factors may be associated with altered brain functions in patients with CD.

Study on the Influence of Label Image Accuracy on the Performance of Concrete Crack Segmentation Network Models.

A high-quality dataset is a basic requirement to ensure the training quality and prediction accuracy of a deep learning network model (DLNM). To explore the influence of label image accuracy on the performance of a concrete crack segmentation network model in a semantic segmentation dataset, this study uses three labelling strategies, namely pixel-level fine labelling, outer contour widening labelling and topological structure widening labelling, respectively, to generate crack label images and construct three sets of crack semantic segmentation datasets with different accuracy. Four semantic segmentation network models (SSNMs), U-Net, High-Resolution Net (HRNet)V2, Pyramid Scene Parsing Network (PSPNet) and DeepLabV3+, were used for learning and training. The results show that the datasets constructed from the crack label images with pix-el-level fine labelling are more conducive to improving the accuracy of the network model for crack image segmentation. The U-Net had the best performance among the four SSNMs. The Mean Intersection over Union (MIoU), Mean Pixel Accuracy (MPA) and Accuracy reached 85.47%, 90.86% and 98.66%, respectively. The average difference between the quantized width of the crack image segmentation obtained by U-Net and the real crack width was 0.734 pixels, the maximum difference was 1.997 pixels, and the minimum difference was 0.141 pixels. Therefore, to improve the segmentation accuracy of crack images, the pixel-level fine labelling strategy and U-Net are the best choices.

Value of the virtual monoenergetic image from dual-layer dual-energy computed tomography enterography in the preoperative assessment of the internal penetrating complication of Crohn's disease.

BACKGROUND: To determine the utility of virtual-monoenergetic imaging (VMI) at low energy levels from contrast-enhanced dual-layer dual-energy (DLDE) computed tomography enterography (CTE) in the preoperative assessment of internal penetrating lesions of Crohn's disease (CD). MATERIALS AND METHODS: Thirty-eight patients with penetrating lesions of CD by surgery undergoing contrast-enhanced DLDE CTE were retrospectively included. Polyenergetic imaging (PEI) and VMIs at low energy levels [40-70 kiloelectron volts (keV)] with 10 keV intervals were reconstructed. The objective parameters of image quality [noise, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR)] and the subjective parameter of image quality [diagnostic performance of lesions (DPL), overall image quality(OIQ)] of PEI and all VMIs at the low energy level were compared to determine the VMI on the optimal energy level. The lesion detection capability between PEI and the optimal VMI was compared. RESULTS: VMI40 was determined to be the optimal VMI among all VMIs at the low energy level for owning the best image quality. No significant difference was found in the detecting capability in penetrating lesions between VMI40 and PEI (p = 1.0), whereas a significant difference was found in the detecting capability in the bowel origin of the penetrating lesions (p = 0.004), the involved organ or structure by the fistula (p = 0.016) and the orifice of the fistula connected to the involved organ or structure ( p = 0.031) between them. CONCLUSIONS: Compared to conventional PEI, VMI40 improves the detection capability in anatomical details of penetrating lesions of CD, helping colorectal surgeons rationalizing preoperative plans of internal penetrating lesions of CD.

Characterization of MicroRNA expression profiles in the ovarian tissue of goats during the sexual maturity period.

BACKGROUND: The ovary is an important reproductive organ in mammals, and its development directly affects the sexual maturity and reproductive capacity of individuals. MicroRNAs (miRNAs) are recognized as regulators of reproductive physiological processes in various animals and have been shown to regulate ovarian development through typical targeting and translational repression. However, little is known about the regulatory role of miRNAs in ovarian tissue development during sexual maturity in goats. To comprehensively profile the different physiological stages of sexual maturation in goats, we performed small-RNA sequencing of ovarian tissue samples collected at four specific time points (1 day after birth (D1), 2 months old (M2), 4 months old (M4), and 6 months old (M6)). In addition, we used ELISAs to measure serum levels of reproductive hormones to study their temporal changes. RESULTS: The results showed that serum levels of gonadotropin-releasing hormone, follicle-stimulating hormone, luteinizing hormone, oestradiol, progesterone, oxytocin, and prolactin were lower in goats at the D1 stage than at the other three developmental stages (P < 0.05). The secretion patterns of these seven hormones show a similar trend, with hormone levels reaching their peaks at 4 months of age. A total of 667 miRNAs were detected in 20 libraries, and 254 differentially expressed miRNAs and 3 groups of miRNA clusters that had unique expression patterns were identified (|log2-fold change|> 1, FDR < 0.05) in the 6 comparison groups. RT‒qPCR was employed to confirm that the expression pattern of the 15 selected miRNAs was consistent with the Illumina sequencing results. Gene ontology analyses revealed significant enrichment of GO terms such as cell proliferation regulation, epithelial cell development, and amino acid transport, as well as important signaling pathways including the MAPK signaling pathway, the PI3K-Akt signaling pathway, and the oestrogen signaling pathway. Further miRNA‒mRNA regulation network analysis revealed that 8 differentially expressed miRNAs (chi-miR-1343, chi-miR-328-3p, chi-miR-877-3p, chi-miR-296-3p, chi-miR-128-5p, chi-miR-331-3p, chi-miR-342-5p and chi-miR-34a) have important regulatory roles in ovarian cell proliferation, hormone secretion and metabolism-related biological processes. CONCLUSIONS: Overall, our study investigated the changes in serum hormone and miRNA levels in the ovaries. These data provide a valuable resource for understanding the molecular regulatory mechanisms of miRNAs in ovarian tissue during the sexual maturity period in goats.

Study on the correlation between bioelectrical impedance analysis index and protein energy consumption in maintenance dialysis patients.

BACKGROUND: Protein-energy wasting (PEW) has been reported to be pretty common in maintenance dialysis patients. However, the existing PEW diagnostic standard is limited in clinical use due to the complexity of it. Bioelectrical impedance analysis (BIA), as a non-invasive nutritional assessment method, can objectively and quantitatively analyze the changes of body tissue components under different nutritional states. We aim to explore the association between PEW and BIA and establish a reliable diagnostic model of PEW. METHODS: We collected cross-sectional data of 609 maintenance dialysis patients at the First Affiliated Hospital, College of Medicine, Zhejiang University. PEW was diagnosed according to International Society of Renal Nutrition and Metabolism (ISRNM) criteria. Among them, 448 consecutive patients were included in the training set for the establishment of a diagnostic nomogram. 161 consecutive patients were included for internal validation. 52 patients from Zhejiang Hospital were included for external validation of the diagnostic model. Correlation analysis of BIA indexes with other nutritional indicators was performed. Logistic regression was used to examine the association of BIA indexes with PEW. 12 diagnostic models of PEW in maintenance dialysis patients were developed and the performance of them in terms of discrimination and calibration was evaluated using C statistics and Hosmer-Lemeshow-type χ2 statistics. After comparing to existing diagnostic models, and performing both internal and external validation, we finally established a simple but reliable PEW diagnostic model which may have great value of clinical application. RESULTS: A total of 609 individuals from First Affiliated Hospital, College of Medicine, Zhejiang University and 52 individuals from Zhejiang Hospital were included. After full adjustment, age, peritoneal dialysis (compared to hemodialysis), subjective global assessment (SGA, compared to non-SGA) and water ratio were independent risk factors, while triglyceride, urea nitrogen, calcium, ferritin, BCM, VFA and phase angle were independent protective factors of PEW. The model incorporated water ratio, VFA, BCM, phase angle and cholesterol revealed best performance. A nomogram was developed according to the results of model performance. The model achieved high C-indexes of 0.843 in the training set, 0.841 and 0.829 in the internal and external validation sets, respectively, and had a well-fitted calibration curve. The net reclassification improvement (NRI) showed 8%, 13%, 2%, 38%, 36% improvement of diagnostic accuracy of our model compared with "PEW score model", "modified PEW score model", "3-index model", "SGA model" and "BIA decision tree model", respectively. CONCLUSIONS: BIA can be used as an auxiliary tool to evaluate PEW risk and may have certain clinical application value.

Research on the Efficiency of Bridge Crack Detection by Coupling Deep Learning Frameworks with Convolutional Neural Networks.

Bridge crack detection based on deep learning is a research area of great interest and difficulty in the field of bridge health detection. This study aimed to investigate the effectiveness of coupling a deep learning framework (DLF) with a convolutional neural network (CNN) for bridge crack detection. A dataset consisting of 2068 bridge crack images was randomly split into training, verification, and testing sets with a ratio of 8:1:1, respectively. Several CNN models, including Faster R-CNN, Single Shot MultiBox Detector (SSD), You Only Look Once (YOLO)-v5(x), U-Net, and Pyramid Scene Parsing Network (PSPNet), were used to conduct experiments using the PyTorch, TensorFlow2, and Keras frameworks. The experimental results show that the Harmonic Mean (F1) values of the detection results of the Faster R-CNN and SSD models under the Keras framework are relatively large (0.76 and 0.67, respectively, in the object detection model). The YOLO-v5(x) model of the TensorFlow2 framework achieved the highest F1 value of 0.67. In semantic segmentation models, the U-Net model achieved the highest detection result accuracy (AC) value of 98.37% under the PyTorch framework. The PSPNet model achieved the highest AC value of 97.86% under the TensorFlow2 framework. These experimental results provide optimal coupling efficiency parameters of a DLF and CNN for bridge crack detection. A more accurate and efficient DLF and CNN model for bridge crack detection has been obtained, which has significant practical application value.

Prediction of extracapsular extension in prostate cancer using the Likert scale combined with clinical and pathological parameters.

Abstract: This study aimed to investigate the independent clinical, pathological, and radiological factors associated with extracapsular extension in radical prostatectomy specimens and to improve the accuracy of predicting extracapsular extension of prostate cancer before surgery. Methods: From August 2018 to June 2023, the clinical and pathological data of 229 patients with confirmed prostate cancer underwent radical prostatectomy from The Second Hospital of Yinzhou. The patients' multiparametric magnetic resonance imaging data were graded using the Likert scale. The chi-square or independent-sample T-test was used to analyze the related factors for an extracapsular extension. Multivariate analysis was used to identify independent factors associated with extracapsular extension in prostate cancer. Additionally, receiver operating characteristic curve analysis was used to calculate the area under the curve and assess the diagnostic performance of our model. The clinical decision curve was used to analyze the clinical net income of Likert scale, biopsy positive rate, biopsy GG, and combined mode. Results: Of the 229 patients, 52 had an extracapsular extension, and 177 did not. Multivariate analysis showed that the Likert scale score, biopsy grade group and biopsy positive rate were independent risk factors for extracapsular extension in prostate cancer. The area under the curves for the Likert scale score, biopsy grade group, and biopsy positive rate were 0.802, 0.762, and 0.796, respectively. Furthermore, there was no significant difference in the diagnostic efficiency for extracapsular extension (P>0.05). However, when these three factors were combined, the diagnostic efficiency was significantly improved, and the area under the curve increased to 0.905 (P<0.05). In the analysis of the decision curve, The clinical net income of the combined model is obviously higher than that of Likert scale, biopsy positive rate, and biopsy GG. Conclusion: The Likert scale, biopsy grade group and biopsy positive rate are independent risk factors for extracapsular extension in prostate cancer, and their combination can significantly improve the diagnostic efficiency for an extracapsular extension.

Double-Layer Electrolyte Boosts Cycling Stability of All-Solid-State Li Metal Batteries.

All-solid-state lithium metal batteries (ASSLMBs), as a candidate for advanced energy storage devices, invite an abundance of interest due to the merits of high specific energy density and eminent safety. Nevertheless, issues of overwhelming lithium dendrite growth and poor interfacial contact still limit the practical application of ASSLMBs. Herein, we designed and fabricated a double-layer composite solid electrolyte (CSE), namely, PVDF-LiTFSI-Li1.3Al0.3Ti1.7(PO4)3/PVDF-LiTFSI-h-BN (denoted as PLLB), for ASSLMBs. The reduction-tolerant PVDF-LiTFSI-h-BN (denoted as PLB) layer of the CSE tightly contacts with the Li metal anode to avoid the reduction of LATP by the electrode and participates in the formation of a stable SEI film using Li3N. Meanwhile, the oxidation-resistance and ion-conductive PVDF-LiTFSI- LATP (denoted as PLA) layer facing the cathode can reduce the interfacial impedance by facilitating ionic migration. With the synergistic effect of PLA and PLB, the Li/Li symmetric cells with sandwich-type electrolytes (PLB/PLA/PLB) can operate for 1500 h with ultralong cycling stability at 0.1 mA cm-2. Additionally, the LiFePO4/Li cell with PLLB maintains satisfactory capacity retention of 88.2% after 250 cycles. This novel double-layer electrolyte offers an effective approach to achieving fully commercialized ASSLMBs.

Identification and Characterization of circRNAs in Non-Lactating Dairy Goat Mammary Glands Reveal Their Regulatory Role in Mammary Cell Involution and Remodeling.

This study conducted transcriptome sequencing of goat-mammary-gland tissue at the late lactation (LL), dry period (DP), and late gestation (LG) stages to reveal the expression characteristics and molecular functions of circRNAs during mammary involution. A total of 11,756 circRNAs were identified in this study, of which 2528 circRNAs were expressed in all three stages. The number of exonic circRNAs was the largest, and the least identified circRNAs were antisense circRNAs. circRNA source gene analysis found that 9282 circRNAs were derived from 3889 genes, and 127 circRNAs' source genes were unknown. Gene Ontology (GO) terms, such as histone modification, regulation of GTPase activity, and establishment or maintenance of cell polarity, were significantly enriched (FDR < 0.05), which indicates the functional diversity of circRNAs' source genes. A total of 218 differentially expressed circRNAs were identified during the non-lactation period. The number of specifically expressed circRNAs was the highest in the DP and the lowest in LL stages. These indicated temporal specificity of circRNA expression in mammary gland tissues at different developmental stages. In addition, this study also constructed circRNA-miRNA-mRNA competitive endogenous RNA (ceRNA) regulatory networks related to mammary development, immunity, substance metabolism, and apoptosis. These findings help understand the regulatory role of circRNAs in mammary cell involution and remodeling.

Blending Aryl Ketone in Covalent Organic Frameworks to Promote Photoinduced Electron Transfer.

Aryl-ketone derivatives have been acknowledged as promising organic photocatalysts for photosynthesis. However, they are limited by their photostability and have been less explored for photoinduced electron transfer (PET) applications. Herein we demonstrate a novel strategy to cover the shortage of aryl-ketone photocatalysts and control the photoreactivity by implanting symmetric aryl ketones into the conjugated covalent organic frameworks (COFs). To prove the concept, three comparative materials with the same topology and varied electronic structures were built, adopting truxenone knot and functionalized terephthalaldehyde linkers. Spectroscopic investigation and excited carrier dynamics analysis disclosed improvements in the photostability and electronic transfer efficiency as well as the structure-performance relationships toward N-aryl tetrahydroisoquinoline oxidation. This system provides a robust rule of thumb for designing new-generation aryl-ketone photocatalysts.

Oxidative Cleavage and Ammoxidation of Unsaturated Hydrocarbons via Heterogeneous Auto-Tandem Catalysis.

The oxidative cleavage and functionalization of unsaturated C-C bonds are important processes for synthesis of carbonyl compounds from hydrocarbon feedstocks, yet there has been no report of direct amidation of unsaturated hydrocarbons via an oxidative cleavage of unsaturated C-C bonds with molecular oxygen as an environmentally benign oxidant. Herein, for the first time, we describe a manganese oxide-catalyzed auto-tandem catalysis strategy that enables direct synthesis of amides from unsaturated hydrocarbons by coupling oxidative cleavage with amidation. With oxygen as an oxidant and ammonia as a nitrogen source, a wide range of structurally diverse mono- and multisubstituted activated and unactivated alkenes or alkynes can smoothly undergo unsaturated C-C bond cleavage to deliver one- or multiple-carbon shorter amides. Moreover, a slight modification of the reaction conditions also allows for the direct synthesis of sterically hindered nitriles from alkenes or alkynes. This protocol features excellent functional group tolerance, a broad substrate scope, flexible late-stage functionalization, facile scalability, and a cost-effective and recyclable catalyst. Detailed characterizations reveal that the high activity and selectivity of the manganese oxides are attributed to the large specific surface area, abundant oxygen vacancies, better reducibility, and moderate acid sites. Mechanistic studies and density functional theory calculations indicate that the reaction proceeds through divergent pathways depending on the structure of substrates.

Application of Low-Dose CT and MRI in the Evaluation of Soft Tissue Injury in Tibial Plateau Fractures.

Objective: To explore the application value of low-dose CT and MRI in the evaluation of soft tissue injury in tibial plateau fractures. Methods: This study included 89 patients with high suspicion of TPF and KI admitted to our hospital from July 2015 to May 2021. After arthroscopy, 81 patients were diagnosed with FTP combined with KI. The Schatzker classification based on X-ray and CT plain scan combined with three-dimensional reconstruction was recorded, and the soft tissue injury was recorded according to the MRI examination of the affected knee joint. Results: With the results of pathological examination and arthroscopic surgery as the gold standard, the results of MRI and pathological examination and arthroscopic examination were in good agreement (Kappa = 0.857, 0.844), and CT was moderately in agreement (Kappa = 0.697, 0.694). In KI examination, CT and MRI had no difference in the evaluation of ligament injury and bone injury (P > 0.05), but MRI had better diagnostic effect on meniscus injury (P < 0.05). Finally, the satisfaction survey showed that patients in the CT group were more satisfied with clinical services (P < 0.05). Conclusion: Both CT and MRI have certain diagnostic value for occult tibial plateau fractures, among which CT examination is more advantageous for trabecular bone fractures, MRI examination is more advantageous for cortical bone fractures, and MRI examination can improve occult tibial plateau fracture inspection accuracy.

BMSC-derived exosomal miR-27a-3p and miR-196b-5p regulate bone remodeling in ovariectomized rats.

Background: In the bone marrow microenvironment of postmenopausal osteoporosis (PMOP), bone marrow mesenchymal stem cell (BMSC)-derived exosomal miRNAs play an important role in bone formation and bone resorption, although the pathogenesis has yet to be clarified. Methods: BMSC-derived exosomes from ovariectomized rats (OVX-Exo) and sham-operated rats (Sham-Exo) were co-cultured with bone marrow-derived macrophages to study their effects on osteoclast differentiation. Next-generation sequencing was utilized to identify the differentially expressed miRNAs (DE-miRNAs) between OVX-Exo and Sham-Exo, while target genes were analyzed using bioinformatics. The regulatory effects of miR-27a-3p and miR-196b-5p on osteogenic differentiation of BMSCs and osteoclast differentiation were verified by gain-of-function and loss-of-function analyses. Results: Osteoclast differentiation was significantly enhanced in the OVX-Exo treatment group compared to the Sham-Exo group. Twenty DE-miRNAs were identified between OVX-Exo and Sham-Exo, among which miR-27a-3p and miR-196b-5p promoted the expressions of osteogenic differentiation markers in BMSCs. In contrast, knockdown of miR-27a-3p and miR-196b-5p increased the expressions of osteoclastic markers in osteoclast. These 20 DE-miRNAs were found to target 11435 mRNAs. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses revealed that these target genes were involved in several biological processes and osteoporosis-related signaling pathways. Conclusion: BMSC-derived exosomal miR-27a-3p and miR-196b-5p may play a positive regulatory role in bone remodeling.

The Status Quo of Criminal Responsibility for Aflatoxin Pollution in China: From the Perspective of Judgment Analysis.

With the development of the economy, the food safety problems caused by aflatoxin have become increasingly prominent. With regard to the control of aflatoxin pollution, the Chinese government has promulgated a series of legal documents on food safety related to aflatoxin pollution, such as the formulation of industry standards for allowable limits of aflatoxin and various penalties for violators. Although these measures have achieved good results to some extent, there are still many legal problems. This study reviews the current situation of aflatoxin pollution control in food in China. The court judgment documents related to aflatoxin pollution from January 1st 2014 to January 1st 2020 are investigated to analyze the accountability status of aflatoxin pollution treatment in China. Furthermore, this study mainly cross verified the above problems by means of the literature survey and an organization interview and proposed solutions on the basis of in-depth analysis of their causes. Finally, some suggestions are put forward to solve the problem of aflatoxin pollution accountability in China.

The role of agricultural green production technologies in improving low-carbon efficiency in China: Necessary but not effective.

The effects of agricultural green production technologies (AGPTs) on agricultural productivity and the environment have received increasing attention. With the panel data of agricultural production of mainland China from 2000 to 2017, this study investigates the role of AGPTs adoption rates in improving low-carbon efficiency by adopting a random-effects panel Tobit model. Results indicate that average adoption rates of AGPTs are less than 20% and unbalanced adoptions vary between the main and non-main grain-producing areas, as well as the northern and southern main grain-producing areas. Furthermore, AGPTs adoption reduces low-carbon efficiency at nationwide and main grain-producing areas. In the northern main grain-producing areas, water-saving irrigation and no-tillage seeding reduce low-carbon efficiency, while mechanized returning straw crushing promotes it. In the southern main grain-producing areas, deep tillage with fertilizer application and no-tillage seeding decrease low-carbon efficiency, while mechanized deep ploughing and scarification increases it. We also find that AGPTs can promote low-carbon efficiency through comprehensive mechanization level and mechanical input density. To improve low-carbon efficiency, we suggest that the improvement and diffusion of applicable AGPTs should be adapted to the local production conditions, and the agricultural machinery service, research and development system should be improved as well.

Succinic anhydride-based chemical modification making laccase@Cu3(PO4)2 hybrid nanoflowers robust in removing bisphenol A in wastewater.

To prepare a robust biocatalyst and enhance the removal of bisphenol A in wastewater, succinic anhydride was reacted with laccase to obtain succinic anhydride-modified laccase (SA-laccase) and then co-crystallized with Cu3(PO4)2 to form SA-laccase@Cu3(PO4)2 hybrid nanoflowers (hNFs). The activity of SA-laccase@Cu3(PO4)2 reached 5.27 U/mg, 1.86-, 2.88- and 2.15-fold those of bare laccase@Cu3(PO4)2, laccase@Ca3(PO4)2 and laccase@epoxy resin, respectively. Compared with free laccase, the obtained hNFs present enhanced activity and tolerance to pH and high temperature in the removal of BPA. Under the optimum conditions of pH 6.0 and 35 °C, BPA removal reached 93.2% using SA-laccase@Cu3(PO4)2 hNFs, which was 1.21-fold of that using free laccase. In addition, the obtained SA-laccase@Cu3(PO4)2 hNFs retained nearly 90% of their initial catalytic activity for BPA removal after 8 consecutive batch cycles. This efficient method for preparing immobilized laccase can also be further developed and improved to acquire green biocatalysts for removing persistent organic pollutants in wastewater.

Diagnostic value of phosphatidylethanolamine binding protein 4 levels in patients receiving nursing interventions for advanced chronic kidney disease.

OBJECTIVE: To explore the diagnostic role of phosphatidylethanolamine binding protein 4 (PEBP4) in patients with chronic kidney disease (CKD) receiving nursing interventions. METHODS: ELISA was used to evaluate serum PEBP4 levels. Receiver-operating characteristic curve analysis was used to assess diagnostic accuracy. Spearman correlation analysis was used to assess the relationships between PEBP4 levels and biochemical indexes. RESULTS: Serum PEBP4 was high in CKD patients compared with healthy individuals. PEBP4 levels were positively correlated with pathological stage in CKD patients. PEBP4 had higher sensitivity for diagnosis of CKD than common indexes including blood urea nitrogen, creatinine and C-reactive protein. Among CKD patients treated with calcium channel blockers, serum PEBP4 levels declined notably and were associated with concentrations of K+, Na+, Cl- and Ca2+. Nursing interventions significantly decreased serum PEBP4 levels. A significant association between serum PEBP4 level and ionic concentration was observed in CKD patients receiving nursing interventions. CONCLUSIONS: This prospective study demonstrated that PEBP4 level might represent an effective diagnostic biomarker in CKD patients. PEBP4 also acted as a valuable care compliance factor for determining the necessity for nursing interventions. Nursing interventions restored ion channel function and subsequently resulted in decreased PEBP4 levels and proteinuria.

Synthesis and Characterization of a Crown-Shaped 36-Molybdate Cluster and Application in Catalyzing Knoevenagel Condensation.

A novel crown-shaped 36-molybdate cluster with organophosphonate-functionalized polyoxomolybdates, (NH4)17Na7H12[Co(H2O)TeMo6O21{N(CH2PO3)3}]6·42H2O, has been successfully synthesized and well-characterized. It owns the highest nuclearity in the family of organophosphonate-based polyoxometalates reported so far. Furthermore, for the first time in the field, we illustrated that polyoxomolybdate could work as an effective heterogeneous catalyst for the Knoevenagel condensation reaction with high TOF (7714 h-1) and good recyclability. Impressively, the catalytic performance of 1 was also tested successfully in a large scale (∼10 g) reaction, where 89% of reaction yield and 3216 of TON were afforded.

36-Nuclearity Organophosphonate-Functionalized Polyoxomolybdates: Synthesis, Characterization and Selective Catalytic Oxidation of Sulfides.

The crown-shaped 36-molybdate cluster organophosphonate-functionalized polyoxomolybdates with the highest nuclearity in organophosphonate-based polyoxometalate chemistry, (NH4 )19 Na7 H10 [Cu(H2 O)TeMo6 O21 {N(CH2 PO3 )3 }]6 ⋅31 H2 O, has been reported for the first time. The synthesized 36-molybdate cluster was characterized by routine techniques and tested as a heterogeneous catalyst for selective oxidation of sulfides with impressive catalytic and selective performances after heat treatment. High efficiency (TON=15333) was achieved in the selective oxidation of sulfides to sulfoxides, caused by the synergic effect between copper and polyoxomolybdates and the generation of the cuprous species during the heat treatment.