Well-confined polyoxometalate-ionic liquid in silicic framework for environmentally friendly asymmetric di-hydroxylation of olefins

Chiral 1,2-diols with a high yield could be directly prepared from asymmetric di-hydroxylation of olefins via an eco-friendly and enduring catalyst, in which abundant "chiral pools" of polyoxometalate-ionic liquid were target-designed into the silicic framework (POM-ILS) and well stabilized in aqueous media.

Resveratrol-induced gut microbiota reduces obesity in high-fat diet-fed mice

OBJECTIVE

Resveratrol (RSV) is a natural polyphenol with putative anti-obesity effects; however, its mechanisms of action remain unclear due to its low bioavailability. Microbial functions in the physiology result from the microbiota-host coevolution has profoundly affected host metabolism. Here, we sought to determine how beneficial microbiome caused by RSV interventions affects antiobesity.

METHODS

C57BL/6J mice were fed either standard diet (SD) or RSV (300 mg/kg/day) diet for 16 weeks. The composition of the gut microbiota was assessed by analyzing 16S rRNA gene sequences. Then, transplant the RSV-microbiota to high-fat diet (HFD)-fed mice (HFD-RSVT) to explore the function of microbiota. Body weight and food intake were monitored. Markers of lipid metabolism, inflammation, gut microbiota compostion, and intestinal barrier were determined.

RESULTS

Mice treated with RSV shows a remarkable alteration in microbiota composition compared with that of SD-fed mice and is characterized by an enrichment of Bacteroides, Lachnospiraceae_NK4A136_group, Blautia, Lachnoclostridium, Parabacteroides, and Ruminiclostridium_9, collectively referred to as RSV-microbiota. We further explored whether RSV-microbiota has anti-obesity functions. Transplantation of the RSV-microbiota to high-fat diet (HFD)-fed mice (HFD-RSVT) was sufficient to decrease their weight gain and increase their insulin sensitivity. Moreover, RSV-microbiota was able to modulate lipid metabolism, stimulate the development of beige adipocytes in WAT, reduce inflammation and improve intestinal barrier function.

CONCLUSIONS

Our study demonstrates that RSV-induced microbiota plays a key role in controlling obesity development and brings new insights to a potential therapy based on host-microbe interactions.

Risk factors and score for recollapse of the augmented vertebrae after percutaneous vertebroplasty in osteoporotic vertebral compression fractures

Our study demonstrated a high incidence of recollapse of the augmented vertebrae after PVP treatment for OVCFs. A risk score based on all significant factors can predict the rate of recollapse and gain clinical benefits to prevent recollapse in patients at high risk.

BACKGROUND

Recollapse of the augmented vertebrae after percutaneous vertebroplasty (PVP) treatment for osteoporotic vertebral compression fractures (OVCFs) has obtained much attention. However, little is known about risk factors and score for recollapse of the augmented vertebrae.

OBJECTIVE

To determine risk factors and furthermore develop a risk score related to recollapse of the augmented vertebrae after PVP treatment for OVCFs.

METHODS

Patients who were treated with PVP for single OVCFs and met this study's inclusion criteria were retrospectively reviewed. The follow-up period was at least 2 years. Associations of recollapse with co-variates (age, gender, bone mass density [BMD] with a T-score, fracture level, intravertebral cleft [IVC], fracture type, cement volume, cement leakage, leakage into a disc, cement distribution pattern, Non-PMMA-endplate-contact [NPEC], preoperative fracture severity, reduction rate [RR], reduction angle [RA]) were analyzed and a risk score for recollapse was further developed to predict recollapse.

RESULTS

A total of 152 patients were included. Recollapse group was found in 42 (27.6%) patients. Preoperative IVC, solid lump cement distribution pattern, more RR (a cutoff value of 7%) and larger RA (a cutoff value of 3°) was significantly associated with increased risk for recollapse of the augmented vertebrae. A risk score was developed based on the number of risk factors present in each patient. Patients with a score of 4 had an approximately ninefold increased risk of developing recollapse over patients with a score of 0. The receiver operating characteristic curve of the risk score generated an area under the curve of 0.899 (95% CI 0.642-0.836, P = 0.000).

CONCLUSION

A risk score based on preoperative IVC, cement distribution pattern, reduction rate, and reduction angle predicts the rate of recollapse. Additional studies should aim to validate this score and inspect clinical benefits of recollapse prophylaxis in patients at high risk.

Low-Dose Computed Tomography Image Super-Resolution Reconstruction via Random Forests

Aiming at reducing computed tomography (CT) scan radiation while ensuring CT image quality, a new low-dose CT super-resolution reconstruction method based on combining a random forest with coupled dictionary learning is proposed. The random forest classifier finds the optimal solution of the mapping relationship between low-dose CT (LDCT) images and high-dose CT (HDCT) images and then completes CT image reconstruction by coupled dictionary learning. An iterative method is developed to improve robustness, the important coefficients for the tree structure are discussed and the optimal solutions are reported. The proposed method is further compared with a traditional interpolation method. The results show that the proposed algorithm can obtain a higher peak signal-to-noise ratio (PSNR) and structural similarity index measurement (SSIM) and has better ability to reduce noise and artifacts. This method can be applied to many different medical imaging fields in the future and the addition of computer multithreaded computing can reduce time consumption.

Positron emission tomography image reconstruction using feature extraction

PURPOSE

To reduce the cost of positron emission tomography (PET) scanning systems, image reconstruction algorithms for low-sampled data have been extensively studied. However, the current method based on total variation (TV) minimization regularization nested in the maximum likelihood-expectation maximization (MLEM) algorithm cannot distinguish true structures from noise resulting losing some fine features in the images. Thus, this work aims to recover fine features lost in the MLEM-TV algorithm from low-sampled data.

METHOD

A feature refinement (FR) approach previously developed for statistical interior computed tomography (CT) reconstruction is applied to PET imaging to recover fine features in this study. The proposed method starts with a constant initial image and the FR step is performed after each MLEM-TV iteration to extract the desired structural information lost during TV minimization. A feature descriptor is specifically designed to distinguish structure from noise and artifacts. A modified steepest descent method is adopted to minimize the objective function. After evaluating the impacts of different patch sizes on the outcome of the presented method, an optimal patch size of 7×7 is selected in this study to balance structure-detection ability and computational efficiency.

RESULTS

Applying MLEM-TV-FR algorithm to the simulated brain PET imaging using an emission activity phantom, a standard Shepp-Logan phantom, and mouse results in the increased peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) as comparing to using the conventional MLEM-TV algorithm, as well as the substantial reduction of the used sampling numbers, which improves the computational efficiency.

CONCLUSIONS

The presented algorithm can achieve image quality superior to that of the MLEM and MLEM-TV approaches in terms of the preservation of fine structure and the suppression of undesired artifacts and noise, indicating its useful potential for low-sampled data in PET imaging.

Preparation and evaluation of gastro-floating hollow adhesive microspheres of carbomer/ethyl cellulose encapsulating dipyridamole

Gastro-floating hollow adhesive microspheres of Carbomer/ethyl cellulose encapsulating dipyridamole were fabricated and evaluated in vitro and in vivo.

Highly luminescent copper(i) halide complexes chelated with a tetradentate ligand (PNNP): synthesis, structure, photophysical properties and theoretical studies

Strongly emissive copper(i) halide complexes constructed from a new tetradentate chelating ligand and butterfly-shaped Cu₂X₂ cores are presented and systematically investigated.

Effects of Long Form of CAPON Overexpression on Glioma Cell Proliferation are Dependent on AKT/mTOR/P53 Signaling

Background: CAPON has two isoforms in human brain: long form of CAPON (CAPON-L) and short form of CAPON (CAPON-S). Recent studies have indicated the involvement of CAPON in tumor cell growth. We aimed to reveal the role of the two CAPON isoforms in the proliferation of glioma cells in this study. Materials and Methods: Lentivirus-mediated stable cell lines with CAPON-L or CAPON-S overexpression were established in U87 and U251 glioma cells. Cell counting kit-8 and colony formation assays were used to evaluate cell proliferation. Western blot analysis of cell cycle-related proteins and flow cytometry were performed to analyze cell cycle progression. Some important molecules of the AKT/mTOR pathway and P53 were also measured by Western blot analysis. Results: Overexpression of CAPON-L showed a significantly inhibitory role in U251 cells, while it exhibited a promoting role in U87 cells. Consistently, overexpressing CAPON-L impeded the cell cycle progression and down-regulated the expression levels of Cyclin D1, CDK4 and CDK6 in U251 cells, whereas it up-regulated the CDK6 level in U87 cells. The overexpression of CAPON-L significantly decreased the phosphorylation and/or total levels of AKT, mTOR and S6 in U251 cells, while it did not affect these signaling molecules in U87 cells, except for a significant increase in the phosphorylation of AKT at Thr-308 site. Transfecting constitutively active AKT (myr-AKT) partially reversed the decreased phosphorylation of AKT and S6 in the CAPON-L-overexpressing U251 cells. In addition, we found a significant decrease in the wild-type P53 level in the CAPON-L-overexpressing U87 cells. The overexpression of CAPON-S also inhibited cell proliferation, blocked cell cycle progression, and decreased the AKT/mTOR pathway activity in U251 cells. Conclusion: The effects of CAPON-L overexpression on glioma cell proliferation are dependent on the AKT/mTOR/P53 activity. The overexpression of CAPON inhibits U251 cell proliferation through the AKT/mTOR signaling pathway, while overexpressing CAPON-L promoted U87 cell proliferation, possibly through down-regulating the P53 level.

KerNL: Kernel-Based Nonlinear Approach to Parallel MRI Reconstruction

The conventional calibration-based parallel imaging method assumes a linear relationship between the acquired multi-channel k-space data and the unacquired missing data, where the linear coefficients are estimated using some auto-calibration data. In this paper, we first analyze the model errors in the conventional calibration-based methods and demonstrate the nonlinear relationship. Then, a much more general nonlinear framework is proposed for auto-calibrated parallel imaging. In this framework, kernel tricks are employed to represent the general nonlinear relationship between acquired and unacquired k-space data without increasing the computational complexity. Identification of the nonlinear relationship is still performed by solving linear equations. Experimental results demonstrate that the proposed method can achieve reconstruction quality superior to GRAPPA and NL-GRAPPA at high net reduction factors.

Few-view CT image reconstruction using improved total variation regularization

X-ray radiation is harmful to human health. Thus, obtaining a better reconstructed image with few projection view constraints is a major challenge in the computed tomography (CT) field to reduce radiation dose. In this study, we proposed and tested a new algorithm that combines penalized weighted least-squares using total generalized variation (PWLS-TGV) and dictionary learning (DL), named PWLS-TGV-DL to address this challenge. We first presented and tested this new algorithm and evaluated it through both data simulation and physical experiments. We then analyzed experimental data in terms of image qualitative and quantitative measures, such as the structural similarity index (SSIM) and the root mean square error (RMSE). The experiments and data analysis indicated that applying the new algorithm to CT data recovered images more efficiently and yielded better results than the traditional CT image reconstruction approaches.

Practical heterogeneous photoredox/nickel dual catalysis for C-N and C-O coupling reactions

Efficient C-N and C-O coupling reactions of aryl halides with amines and alcohols have been developed by using the strategy of heterogeneous visible light photoredox and nickel dual catalysis. Obviously, the joint use of inexpensive and bench-stable CdS and nickel salts, together with mild reaction conditions, makes these two transformations attractive for the synthetic community. This heterogeneous dual catalysis system also proved to be successful in the ligand-free catalytic hydroxylation of aryl bromide with water as a nucleophile. The practicality of this protocol is further emphasized by the scaled-up reaction and the reusability of heterogeneous photocatalysts.

Iterative image reconstruction for sparse-view CT via total variation regularization and dictionary learning

Recently, low-dose computed tomography (CT) has become highly desirable due to the increasing attention paid to the potential risks of excessive radiation of the regular dose CT. However, ensuring image quality while reducing the radiation dose in the low-dose CT imaging is a major challenge. Compared to classical filtered back-projection (FBP) algorithms, statistical iterative reconstruction (SIR) methods for modeling measurement statistics and imaging geometry can significantly reduce the radiation dose, while maintaining the image quality in a variety of CT applications. To facilitate low-dose CT imaging, we in this study proposed an improved statistical iterative reconstruction scheme based on the penalized weighted least squares (PWLS) standard combined with total variation (TV) minimization and sparse dictionary learning (DL), which is named as a method of PWLS-TV-DL. To evaluate this PWLS-TV-DL method, we performed experiments on digital phantoms and physical phantoms, and analyzed the results in terms of image quality and calculation. The results show that the proposed method is better than the comparison methods, which indicates the potential of applying this PWLS-TV-DL method to reconstruct low-dose CT images.

Zebrafish microRNA miR-210-5p inhibits primitive myelopoiesis by silencing foxj1b and slc3a2a mRNAs downstream of gata4/5/6 transcription factor genes

Zebrafish gata4/5/6 genes encode transcription factors that lie on the apex of the regulatory hierarchy in primitive myelopoiesis. However, little is known about the roles of microRNAs in gata4/5/6-regulated processes. Performing RNA-Seq deep sequencing analysis of the expression changes of microRNAs in gata4/5/6-knockdown embryos, we identified miR-210-5p as a regulator of zebrafish primitive myelopoiesis. Knocking down gata4/5/6 (generating gata5/6 morphants) significantly increased miR-210-5p expression, whereas gata4/5/6 overexpression greatly reduced its expression. Consistent with inhibited primitive myelopoiesis in the gata5/6 morphants, miR-210-5p overexpression repressed primitive myelopoiesis, indicated by reduced numbers of granulocytes and macrophages. Moreover, knocking out miR-210 partially rescued the defective primitive myelopoiesis in zebrafish gata4/5/6-knockdown embryos. Furthermore, we show that the restrictive role of miR-210-5p in zebrafish primitive myelopoiesis is due to impaired differentiation of hemangioblast into myeloid progenitor cells. By comparing the set of genes with reduced expression levels in the gata5/6 morphants to the predicted target genes of miR-210-5p, we found that foxj1b and slc3a2a, encoding a forkhead box transcription factor and a solute carrier family 3 protein, respectively, are two direct downstream targets of miR-210-5p that mediate its inhibitory roles in zebrafish primitive myelopoiesis. In summary, our results reveal that miR-210-5p has an important role in the genetic network controlling zebrafish primitive myelopoiesis.

Degradation of Polyacrylate in the Outdoor Agricultural Soil Measured by FTIR-PAS and LIBS

Recently, polyacrylates (PA) have been applied in coated controlled-release fertilizer (CRF), but the impacts of the soil on the degradation of PA have not been evaluated. In this study, an outdoor agriculture soil buried test was carried out for 12 months to investigate the degradation of PA films. The residual degraded films were taken regularly from the soil and analyzed by SEM, Fourier transform infrared photoacoustic spectroscopy (FTIR-PAS) and laser-induced breakdown spectroscopy (LIBS). The concentration of C⁻H and C=O molecular groups of PA were decreased, and the element concentrations of C, O, K, Si of PA were increased under the degradation process. The surface of PA became rough and the degradation of PA occurred on the surface layer. Principal component analysis (PCA) showed that soil invaded PA. The results indicated that PA were environmentally friendly when applied to CRF. FTIR-PAS and LIBS were advanced in the in-situ surface analysis of the degradation process of the polymer.

Multiregional radiomics profiling from multiparametric MRI: Identifying an imaging predictor of IDH1 mutation status in glioblastoma

Purpose

Isocitrate dehydrogenase 1 (IDH1) has been proven as a prognostic and predictive marker in glioblastoma (GBM) patients. The purpose was to preoperatively predict IDH mutation status in GBM using multiregional radiomics features from multiparametric magnetic resonance imaging (MRI).

Methods

In this retrospective multicenter study, 225 patients were included. A total of 1614 multiregional features were extracted from enhancement area, non‐enhancement area, necrosis, edema, tumor core, and whole tumor in multiparametric MRI. Three multiregional radiomics models were built from tumor core, whole tumor, and all regions using an all‐relevant feature selection and a random forest classification for predicting IDH1. Four single‐region models and a model combining all‐region features with clinical factors (age, sex, and Karnofsky performance status) were also built. All models were built from a training cohort (118 patients) and tested on an independent validation cohort (107 patients).

Results

Among the four single‐region radiomics models, the edema model achieved the best accuracy of 96% and the best F1‐score of 0.75 while the non‐enhancement model achieved the best area under the receiver operating characteristic curve (AUC) of 0.88 in the validation cohort. The overall performance of the tumor‐core model (accuracy 0.96, AUC 0.86 and F1‐score 0.75) and the whole‐tumor model (accuracy 0.96, AUC 0.88 and F1‐score 0.75) was slightly better than the single‐regional models. The 8‐feature all‐region radiomics model achieved an improved overall performance of an accuracy 96%, an AUC 0.90, and an F1‐score 0.78. Among all models, the model combining all‐region imaging features with age achieved the best performance of an accuracy 97%, an AUC 0.96, and an F1‐score 0.84.

Conclusions

The radiomics model built with multiregional features from multiparametric MRI has the potential to preoperatively detect the IDH1 mutation status in GBM patients. The multiregional model built with all‐region features performed better than the single‐region models, while combining age with all‐region features achieved the best performance.

Compressible Supercapacitor with Residual Stress Effect for Sensitive Elastic-Electrochemical Stress Sensor

In this work, we have synthesized graphene aerogels using natural-drying method and fabricated a compressible all-solid-state supercapacitor, which offers outstanding energy density of 23.08 Wh kg^-1 at 240 W kg^-1. We further demonstrate that the device is deformable in squeezed cases with a residual stress effect. Taking advantage of the compressibility and excellent electrochemical performance of the graphene aerogel, we offer a new type of stress sensor called elastic-electrochemical stress sensor. Served as the elastic-electrochemical stress device, the cell demonstrates steady response current toward the external mechanical force by transforming mechanical energy to electrochemical energy. The high-sensitive stress sensor will help us comprehend the interaction principle between electrochemistry and external stress well.

Coumarinolignoids and Taraxerane Triterpenoids from Sapium discolor and Their Inhibitory Potential on Microglial Nitric Oxide Production

Seventeen compounds, including three new pairs of coumarinolignoid enantiomers, (7' S,8' S)-sapiumins A-C (1a-3a) and (7' R,8' R)-sapiumins A-C (1b-3b), six new taraxerane triterpenoids, sapiumic acids A-F (4-9), and five known taraxerane triterpenoids (10-14), were isolated from an ethanol extract prepared from the stems and leaves of Sapium discolor. The structures of 1-9 and their relative configurations were determined by spectroscopic data analysis, and the absolute configurations of the coumarinolignoids 1a/1b-3a/3b and triterpenoids 6-9 were assigned using experimental and calculated ECD data. Compounds 1a/1b-3a/3b are the first coumarinolignoids to be reported from the genus Sapium. Among all the isolates, compounds 1b, 2a/2b, 3a/3b, and 6-9 inhibited nitric oxide production in lipopolysaccharide-stimulated BV-2 microglial cells, with IC₅₀ values of 1.7-15.3 μM.

[Incidence and mortality of bladder cancer in China, 2014]

Objective: To estimate the incidence and mortality of bladder cancer in China based on the cancer registration data in 2014, collected by the National Central Cancer Registry (NCCR). Methods: There were 449 cancer registries submitted bladder cancer new cases and deaths occurred in 2014 to NCCR. After evaluating the data quality, 339 registries' data were finally accepted for analysis. According to the national population data of 2014, the nationwide incidence and mortality of bladder cancer were estimated by stratification in the area (urban or rural), gender, and age. Chinese population census in 2000 and Segi's population were used for age-standardized incidence/mortality rates. Results: All 339 cancer registries covered a total of 288 243 347 populations (144 061 915 in urban and 144 181 432 in rural areas). The percentage of morphologically verified cases and death certificate-only cases were 74.86% and 1.45%, respectively. The mortality to incidence ratio was 0.41. The estimates of new bladder cancer cases were 78 100 in China in 2014, with a crude incidence rate of 5.71/100 000. The age-standardized incidence rates by China standard population (ASR China) and world standard population (ASR world) of bladder cancer were 3.61/100 000 and 3.56/100 000, respectively. Cumulative incidence rate of bladder cancer in China was 0.41%. The crude and ASR China incidence rates in urban areas were 6.88/100 000 and 4.07/100 000, respectively, whereas those were 4.29/100, 000 and 2.96/100 000 in rural areas. The estimates of bladder cancer deaths caused by bladder cancer were about 32 100 in China in 2014, with a crude mortality rate of 2.35/100 000. The ASR China and ASR world mortality rates were both 1.30/100 000 with a cumulative mortality rate (0-74 years old) of 0.12%. The crude and ASR China mortality rates were 2.79/100 000 and 1.41/100 000 in urban areas, respectively, whereas those were 1.81/100 000 and 1.14/100 000 in rural areas. Conclusions: The incidence and mortality pattern of bladder cancer were different in urban and rural areas. The incidence and mortality were higher in urban areas than that in rural areas, and higher for male than for female. We should focus on strengthening the prevention and control of bladder cancer in key population, especially men in urban areas.

Fusion of Unmanned Aerial Vehicle Panchromatic and Hyperspectral Images Combining Joint Skewness-Kurtosis Figures and a Non-Subsampled Contourlet Transform

To obtain fine and potential features, a highly informative fused image created by merging multiple images is usually required. In our study, a novel fusion algorithm called JSKF-NSCT is proposed for fusing panchromatic (PAN) and hyperspectral (HS) images by combining the joint skewness-kurtosis figure (JSKF) and the non-subsampled contourlet transform (NSCT). The JSKF model is used first to derive the three most sensitive bands from the original HS image according to the product of the skewness and the kurtosis coefficients of each band. Afterwards, an intensity-hue-saturation (IHS) transform is used to obtain the luminance component I of the produced false-colour image consisting of the above three bands. Then the NSCT method is used to decompose component I of the false-colour image and the PAN image. The weight-selection rule based on the regional energy is adopted to acquire the low-frequency coefficients and the correlation between the central pixel and its surrounding pixels is used to select the high-frequency coefficients. Finally, the fused image is obtained by applying an IHS inverse transform and an inverse NSCT transform. The unmanned aerial vehicle (UAV) HS and PAN images under low- and high-vegetation coverage of wheat at the flag leaf stage (Stage I) and the grain filling stage (Stage II) are used as the sample data sources. The fusion results are comparatively validated using spatial (entropy, standard deviation, average gradient and mean) and spectral (normalised difference vegetation, NDVI, and leaf area index, LAI) assessments. Additional comparative studies using anomaly detection and pixel clustering also demonstrate that the proposed method outperforms other methods. They show that the algorithm reported herein can better preserve the original spatial and spectral characteristics of the two types of images to be fused and is more stable than IHS, principal components analysis (PCA), non-negative matrix factorization (NMF) and Gram-Schmidt (GS).