[Screening of Characteristic Pollutants and Risk Pollutants in Different Media in the Yangtze River Basin Using Comprehensive Evaluation and Risk Quotient Methods].

A variety of pollutants have frequently been detected in the Yangtze River Basin with the rapid economic development, the population increase, and the acceleration of urbanization, which threaten the aquatic ecosystem and human health. A multi-criteria comprehensive evaluation method was developed to identify the characteristic pollutants, and the risk quotient method was used to derive the risk pollutants in water and sediment samples in this article. A total of 155 pollutants from 11 categories were detected in the Yangtze River Basin according to the literature research. Then, the K-means method was used to analyze the cluster of pollutant comprehensive scores. All pollutants were graded based on their scores and recorded as Ⅰ-Ⅵ according to the number of cases in each cluster. A total of 43 pollutants with high scores of Ⅰ and Ⅱ were listed as the characteristic pollutants, which included 11 polycyclic aromatic hydrocarbons, 11 organochlorine pesticides, 10 polychlorinated biphenyls, eight dioxins, two heavy metals, and one phthalate ester. The top five median concentrations of contaminants in water and sediment samples were heavy metals, polycyclic aromatic hydrocarbons, phthalates esters, bisphenols, and pharmaceuticals and personal care products. According to the principle of risk maximization, the risk entropy value （RQ） was calculated based on the highest pollutant concentration. A total of 38 risky pollutants were screened in the water samples （RQ ≥ 0.1）. There were eight high-risk pollutants with RQ ≥ 1, which included benzo[a,h]-anthracene, anthracene, benzo[a]anthracene, pyrene, methoxychlor, aldrin, 2,4'-dichlorodiphenyl, and cadmium. There were 15 high-risk contaminants in the sediment, which included benzo[b]fluoranthene, anthracene, acenaphthene, fluoranthene, cadmium, lead, chromium, arsenic, selenium, dibutyl phthalate, dimethyl phthalate, diisobutyl phthalate, norfloxacin, perfluorobutyric acid, and bisphenol A. The risk pollutants contained emerging pollutants, which included ten pollutants in water samples and nine pollutants in sediments. Antibiotic pollutants accounted for the largest proportion of these emerging pollutants. The information provided in this article may be useful for the relevant departments to monitor the pollutants and propose management programs for the Yangtze River Basin. Additionally, it is of great significance for the ecological environmental protection and management of the Yangtze River Basin.

Super-resolution reconstruction improves multishell diffusion: using radiomics to predict adult-type diffuse glioma IDH and grade.

Objectives: Multishell diffusion scanning is limited by low spatial resolution. We sought to improve the resolution of multishell diffusion images through deep learning-based super-resolution reconstruction (SR) and subsequently develop and validate a prediction model for adult-type diffuse glioma, isocitrate dehydrogenase status and grade 2/3 tumors. Materials and methods: A simple diffusion model (DTI) and three advanced diffusion models (DKI, MAP, and NODDI) were constructed based on multishell diffusion scanning. Migration was performed with a generative adversarial network based on deep residual channel attention networks, after which images with 2x and 4x resolution improvements were generated. Radiomic features were used as inputs, and diagnostic models were subsequently constructed via multiple pipelines. Results: This prospective study included 90 instances (median age, 54.5 years; 39 men) diagnosed with adult-type diffuse glioma. Images with both 2x- and 4x-improved resolution were visually superior to the original images, and the 2x-improved images allowed better predictions than did the 4x-improved images (P<.001). A comparison of the areas under the curve among the multiple pipeline-constructed models revealed that the advanced diffusion models did not have greater diagnostic performance than the simple diffusion model (P>.05). The NODDI model constructed with 2x-improved images had the best performance in predicting isocitrate dehydrogenase status (AUC_validation=0.877; Brier score=0.132). The MAP model constructed with the original images performed best in classifying grade 2 and grade 3 tumors (AUC_validation=0.806; Brier score=0.168). Conclusion: SR improves the resolution of multishell diffusion images and has different advantages in achieving different goals and creating different target diffusion models.

MARCH5 promotes hepatocellular carcinoma progression by inducing p53 ubiquitination degradation.

BACKGROUND: Human MARCH5 is a mitochondria-localized E3 ubiquitin-protein ligase that is essential for the regulation of mitochondrial dynamics. A large body of evidence suggests that imbalances in mitochondrial dynamics are strongly associated with cancer. However, the expression, biological function and prognostic significance of MARCH5 in hepatocellular carcinoma (HCC) have not been determined. MATERIALS AND METHODS: The mRNA and protein expression of MARCH5 in HCC cell lines and tumor tissues was assessed by real-time quantitative PCR, Western blot analysis and immunohistochemistry. The clinical prognostic significance of MARCH5 was evaluated in 135 HCC patients. Knockdown or overexpression of MARCH5 in HCC cells was determined by in vitro cell proliferation, migration and invasion assays, and in vivo tumor growth and metastasis assays. In addition, the intrinsic mechanisms by which MARCH5 regulates HCC cell growth and metastasis were explored. RESULTS: MARCH5 was significantly overexpressed in HCC cells and was closely associated with patients' poor postoperative prognosis. In vivo and in vitro experiments revealed that MARCH5 significantly promoted the increase and invasive and migratory ability of hepatocellular carcinoma cells, which was mainly due to the promotion of autophagy by MARCH5. Mechanistic studies revealed that MARCH5 promoted autophagy through ubiquitination degradation of p53 leading to malignant progression of hepatocellular carcinoma. CONCLUSION: Our findings suggest that MARCH5 plays a critical oncogenic role in HCC cells, which provides experimental evidence for the use of MARCH5 as a potential target for HCC therapy.

Metabolomics reveals early pregnancy biomarkers in sows: a non-invasive diagnostic approach.

In an effort to enhance reproductive management and reduce non-productive periods in swine breeding, this study presents a novel, non-invasive metabolomics approach for the identification of early pregnancy biomarkers in sows. Utilizing an untargeted metabolomics approach with mass spectrometry analysis, we examined saliva samples from pregnant (n = 6) and non-pregnant control sows (n = 6, artificially inseminated with non-viable sperm). Our analysis revealed 286 differentially expressed metabolites, with 152 being up-regulated and 134 down-regulated in the pregnant group. Among these, three metabolites, namely Hyodeoxycholic acid, 2'-deoxyguanosine, and Thymidine, emerged as potential early pregnancy biomarkers. These biomarkers were further evaluated using targeted LC-MS/MS quantification and qualification, accompanied by ROC curve analysis. The study confirmed Hyodeoxycholic acid and 2'-deoxyguanosine as promising biomarkers for early pregnancy detection, offering potential for future implementation in swine production environments. This research establishes a robust theoretical foundation for the development of innovative molecular diagnostic techniques and explores new avenues for molecular genetic breeding and non-invasive diagnostics, ultimately enhancing fertility and productivity in sow herds.

Detection of ion cyclotron emission by using an ion cyclotron range of frequency antennas-based diagnostic system in experimental advanced superconducting tokamak.

In the experimental advanced superconducting tokamak (EAST), a novel ion cyclotron range of frequency (ICRF) antenna-based diagnostic system is designed to measure ion cyclotron emission (ICE) driven by high-energy ions. The diagnostic system includes ICRF antenna straps, a three-tune impedance matching system, a coaxial switching system, a direct current block, and a data acquisition and storage system. Using the coaxial switching system, the ICRF antenna can be switched from the heating mode to the coupling mode between two discharges. In the 2023 EAST experiment campaign, core ICE was observed using the ICRF antenna-based diagnostic system during neutron beam injection heating, and the obtained results agreed well with the signal detected by the previous high-frequency B-dot probe-based diagnostic system.

Introducing terminal alkyne groups at the reducing end of cellulose nanocrystals by aldimine condensation for further click reaction.

In recent years, click reactions with cellulose nanocrystals (CNC) participation have gradually become a research hotspot. Carboxylamine condensation is the most used method to introduce terminal alkyne groups at the reducing end of CNC as reaction sites for click reactions. However, hydroxyl groups on CNC surface would be slightly oxidized during the carboxyamine condensation process, inducing the potential positions of introduced alkynes would be not only at the reducing end but also on CNC surface. Here, aldimine condensation was proposed to introduce terminal alkyne groups just at the reducing end of CNC, and a systematic comparison analysis was conducted with carboxylamine condensation. Firstly, the selectivity and extent of alkynylation were characterized by XPS and EA. Secondly, the end aldehyde content in these CNC samples was measured by the BCA method, which quantitatively explained the grafting efficiency of aldimine condensation and further verified its feasibility. Thirdly, the clickability of the modified CNC samples was confirmed through XPS analysis of the products after a pre-designed click reaction. In sum, aldimine condensation was proven to be a simple and effective strategy for introducing terminal alkyne groups at the reducing end of CNC, which could be used as reaction sites for further click reactions.

Structural changes in corticospinal tract profiling via multishell diffusion models and their relation to overall survival in glioblastoma.

PURPOSE: Advanced MR fiber tracking imaging reflects fiber bundle invasion by glioblastoma, particularly of the corticospinal tract (CST), which is more susceptible as the largest downstream fiber tracts. We aimed to investigate whether CST features can predict the overall survival of glioblastoma. METHODS: In this prospective secondary analysis, 40 participants (mean age, 58 years; 16 male) pathologically diagnosed with glioblastoma were enrolled. Diffusion spectrum MRI was used for CST reconstruction. Fifty morphological and diffusion indicators (DTI, DKI, NODDI, MAP and Q-space) were used to characterize the CST. Optimal parameters capturing fiber bundle damage were obtained through various grouping methods. Eventually, the correlation with overall survival was determined by the hazard ratios (HRs) from various Cox proportional hazard model combinations. RESULTS: Only intracellular volume fraction (ICVF) and non-Gaussianity (NG) values on the affected tumor level were significant in all four groups or stratified comparisons (all P < .05). During the median follow-up 698 days, only the ICVF on the affected tumor level was independently associated with overall survival, even after adjusting for all classic prognostic factors (HR [95 % CI]: 0.611 [0.403, 0.927], P = .021). Moreover, stratification by the ICVF on the affected tumor level successfully predicted risk (P < .01) and improved the C-index of the multivariate model (from 0.695 to 0.736). CONCLUSIONS: This study demonstrates a relationship between NODDI-derived CST features, ICVF on the affected tumor level, and overall survival in glioblastoma. Independent of classical prognostic factors for glioblastoma, a lower ICVF on the affected tumor level might predict a lower overall survival.

Heterogeneity matching and IDH prediction in adult-type diffuse gliomas: a DKI-based habitat analysis.

Objective: To explain adult-type diffuse gliomas heterogeneity through diffusion kurtosis imaging-based habitat characteristics and develop and validate a comprehensive model for predicting isocitrate dehydrogenase (IDH) status. Materials and methods: In this prospective secondary analysis, 103 participants (mean age, 52 years; range, 21-77; 54 [52%] male) pathologically diagnosed with adult-type diffuse gliomas were enrolled between June 2018 and February 2022. The Otsu method was used to generate habitat maps with mean diffusivity (MD) and mean kurtosis (MK) for a total of 4 subhabitats containing 16 habitat features. Habitat heatmaps were created based on the Pearson correlation coefficient. The Habitat imAging aNd clinicraD INtegrated prEdiction SyStem (HANDINESS) was created by combining clinical features, conventional MRI morphological features, and habitat image features. ROC, calibration curve, and decision curve analyses were used to select the optimal model after 32 pipelines for model training and validation. Results: In the restricted diffusion and high-density subhabitat, MK was highly correlated with MD (R2 = 0.999), volume (0.608) and percentage of volume (0.663), and this region had the highest MK value (P<.001). The unrestricted diffusion and low-density subhabitat had the highest MD value (P<.001). When MK was less than the Otsu threshold, there was still a difference between restricted diffusion and low-density and unrestricted diffusion and low-density subhabitats (P<.01). The HANDINESS enabled more accurate prediction of the IDH status in the training (AUC=0.951 [0.902-0.987]) and internal validation cohorts (0.938 [0.881-0.949]). AUC values for single-modality models and independent factors ranged from 0.593 to 0.916. Calibration and decision curve analyses showed that the HANDINESS demonstrated a high level of clinical applicability and predictive consistency. Conclusion: Diffusion kurtosis imaging-based habitat analysis provides additional important information on microscopic tumor spatial heterogeneity. The HANDINESS has higher diagnostic performance and robustness than single-modality models.

Effect of Ursodeoxycholic Acid on Preventing SARS-CoV-2 Infection in Patients With Liver Transplantation: a multicenter retrospective cohort study.

BACKGROUND: Immunosuppressed recipients of liver transplantation (LT) are more likely to develop coronavirus disease 2019 (COVID-19) and may have an increased risk of developing worse outcomes. AIM: To assess the effect of ursodeoxycholic acid (UDCA) on preventing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in LT recipients. DESIGN: Adult patients (aged ≥ 18 years) who underwent LT between January 1st, 2015, and December 31st, 2022, were included and categorized into two groups according to their use of UDCA. METHODS: The prevalence and severity of COVID-19 among transplantation patients between the UDCA and non-UDCA groups were estimated and compared. RESULTS: Among the 897 LT patients who met the inclusion criteria, infection rate of SARS-CoV-2 was 78.4%, and the rate of severe illness was 5.1% from January 2022 to January 2023 in China. In the multivariate analysis, only UDCA treatment (P = 0.006) was found to be a protective factor against SARS-CoV-2 infection. After propensity score matching, the SARS-CoV-2 infection rate in the UDCA group was lower than that in the non-UDCA group (74.1% vs. 84.6%, P = 0.002). This rate was further reduced to 62.1% (P = 0.002) when the oral administration dose was greater than 15 mg/kg/d. There was no difference in the rates of severe COVID-19 illness, ICU admission, or ventilation rate or length of hospital stay with or without UDCA treatment (all P > 0.05). CONCLUSIONS: The use of UDCA in LT patients significantly reduced the SARS-CoV-2 infection rate and showed a dose-dependent protective effect.

AARS2 as a novel biomarker for prognosis and its molecular characterization in pan-cancer.

INTRODUCTION: The mitochondrial alanyl-tRNA synthetase 2 (AARS2) as one of aminoacyl-tRNA synthases (ARSs) performs amino acid transportation and involves protein synthesis. However, its role in cancer remains largely unexplored. METHODS: In this study, more than 10,000 samples were enrolled to explore genomic alterations, biological function, prognosis, and clinical treatment based on AARS2 across pan-cancer. The molecular characterization of AARS2 was confirmed in hepatocellular carcinoma (HCC) using proteomics analysis, quantitative real-time PCR, western blotting, immunohistochemical staining, and cell experiments. RESULTS: For genomic landscape, the AARS2 was dramatically upregulated in multiple cancers, which might be mainly caused by copy number alteration rather than mutation and methylation. The abnormal expression of AARS2 was prominently associated with activity of cancer pathways and performed oncogenic roles in most cancers. Systematic experiments in vitro substantiated the elevated expression of AARS2, and the deficiency of it inhibited cell proliferation and cell migration in HCC. Meanwhile, our findings suggested that AARS2 could serve as a novel promising and stable biomarker for assessing prognosis and immunotherapy. Moreover, a variety of therapeutic drugs and targeted pathways were proposed for cancer treatment, which might enhance clinical efficacy. CONCLUSION: The AARS2 could serve as a new oncogenic gene that promotes cell proliferation and migration in HCC. The comprehensive investigations increased the understanding of AARS2 across human cancers and generated beginning insights of AARS2 in genomic landscape, molecular biological function, prognosis, and clinical treatment.

Model incorporating multiple diffusion MRI features: development and validation of a radiomics-based model to predict adult-type diffuse gliomas grade.

OBJECTIVES: To develop and validate a radiomics-based model (ADGGIP) for predicting adult-type diffuse gliomas (ADG) grade by combining multiple diffusion modalities and clinical and imaging morphologic features. METHODS: In this prospective study, we recruited 103 participants diagnosed with ADG and collected their preoperative conventional MRI and multiple diffusion imaging (diffusion tensor imaging, diffusion kurtosis imaging, neurite orientation dispersion and density imaging, and mean apparent propagator diffusion-MRI) data in our hospital, as well as clinical information. Radiomic features of the diffusion images and clinical information and morphological data from the radiological reports were extracted, and multiple pipelines were used to construct the optimal model. Model validation was performed through a time-independent validation cohort. ROC curves were used to evaluate model performance. The clinical benefit was determined by decision curve analysis. RESULTS: From June 2018 to May 2021, 72 participants were recruited for the training cohort. Between June 2021 and February 2022, 31 participants were enrolled in the prospective validation cohort. In the training cohort (AUC 0.958), internal validation cohort (0.942), and prospective validation cohort (0.880), ADGGIP had good accuracy in predicting ADG grade. ADGGIP was also significantly better than the single-modality prediction model (AUC 0.860) and clinical imaging morphology model (0.841) (all p < .01) in the prospective validation cohort. When the threshold probability was greater than 5%, ADGGIP provided the greatest net benefit. CONCLUSION: ADGGIP, which is based on advanced diffusion modalities, can predict the grade of ADG with high accuracy and robustness and can help improve clinical decision-making. CLINICAL RELEVANCE STATEMENT: Integrated multi-modal predictive modeling is beneficial for early detection and treatment planning of adult-type diffuse gliomas, as well as for investigating the genuine clinical significance of biomarkers. KEY POINTS: • Integrated model exhibits the highest performance and stability. • When the threshold is greater than 5%, the integrated model has the greatest net benefit. • The advanced diffusion models do not demonstrate better performance than the simple technology.

Product from sessile droplet evaporation of PNIPAM/water system above LCST: A block or micro/nano-particles?

PNIPAM as a stimuli-responsive polymer has generated extreme interests due to its versatile applications. However, there is no research report on whether PNIPAM micro/nano-particles can be extracted from its suspension after phase separation. In the present work, LCST-type phase separation in self-synthesized PNIPAM/water system was investigated in depth by dividing the DLS testing process into four stages. In addition to quenching duration, temperature rise process, quenching temperature and PNIPAM concentration all have a great influence on particle size of the suspension. Meanwhile, the steady-state rheology and dynamic viscoelasticity results show that PNIPAM micro/nano-particles in the suspension are "soft" that can deform. Finally, FE-SEM was used to observe the morphology of dehydrated PNIPAM extracted by sessile droplet evaporation under different conditions. The results indicate that these "soft" particles are easier to fuse together, do not have sufficient mechanical strength to maintain their spherical morphology after dehydration. But the above fusion can be suppressed by adjusting evaporation conditions to acquire smaller PNIPAM particles which have sufficient mechanical properties to keep their basic particle morphology. Further, by changing evaporation pressure to positive or negative pressure, dehydrated PNIPAM micro/nano-particles with excellent uniformity and separation can be obtained. This work will provide guidance for extracting micro/nano-particles from polymer/diluent systems with LCST.

Evaluation of diffuse glioma grade and proliferation activity by different diffusion-weighted-imaging models including diffusion kurtosis imaging (DKI) and mean apparent propagator (MAP) MRI.

PURPOSE: To evaluate two advanced diffusion models, diffusion kurtosis imaging and the newly proposed mean apparent propagation factor-magnetic resonance imaging, in the grading of gliomas and the assessing of their proliferative activity. METHODS: Fifty-nine patients with clinically diagnosed and pathologically proven gliomas were enrolled in this retrospective study. All patients underwent DKI and MAP-MRI scans. Manually outline the ROI of the tumour parenchyma. After delineation, the imaging parameters were extracted using only the data from within the ROI including mean diffusion kurtosis (MK), return-to-origin probability (RTOP), Q-space inverse variance (QIV) and non-Gaussian index (NG), and the differences in each parameter in the classification of glioma were compared. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of these parameters. RESULTS: MK, NG, RTOP and QIV were significantly different amongst the different grades of glioma. MK, NG and RTOP had excellent diagnostic value in differentiating high-grade from low-grade glioma, with largest areas under the curve (AUCs; 0.929, 0.933 and 0.819, respectively; P < 0.01). MK and NG had the largest AUCs (0.912 and 0.904) when differentiating grade II tumours from III tumours (P < 0.01) and large AUCs (0.791 and 0.786) when differentiating grade III from grade IV tumours. Correlation analysis of tumour proliferation activity showed that MK, NG and QIV were strongly correlated with the Ki-67 LI (P < 0.001). CONCLUSION: MK, RTOP and NG can effectively represent the microstructure of these altered tumours. Multimodal diffusion-weighted imaging is valuable for the preoperative evaluation of glioma grade and tumour proliferative activity.

Applying MAP-MRI to Identify the WHO Grade and Main Genetic Features of Adult-type Diffuse Gliomas: A Comparison of Three Diffusion-weighted MRI Models.

RATIONALE AND OBJECTIVES: Currently, there is no noninvasive method to effectively judge the genotype of diffuse gliomas. We explored the association between mean apparent propagator-MRI (MAP-MRI) and WHO grade 2/3, IDH 1/2 mutations, and chromosome 1p/19q combined deletion genotypes in adult-type diffuse gliomas and compared it with the diagnostic efficiency of diffusion tensor imaging (DTI) and diffusional kurtosis imaging (DKI). MATERIALS AND METHODS: We prospectively recruited 67 participantshistopathologically diagnosed with adult-type diffuse gliomas. Routine MRI, DKI, and DSI were performed before surgery. The extreme and average partial diffusion indexes of solid tumors were measured. A comprehensive assessment of statistically significant diffusion parameters was performed after Bonferroni correction, including ROC curves, correct classification percentage (CCP), integrated discrimination improvement (IDI), net reclassification improvement (NRI), and k-fold cross validation. RESULTS: For differentiating WHO grade 2/3, q-space inverse variance (QIV), mean kurtosis (MK), non-Gaussianity (NG), and return to the origin probability (RTOP) were different (p' < .05), with the mean QIV exhibiting the best diagnostic efficacy and stability (AUC = 0.973, CCP = 0.906). We observed significant differences in mean diffusivity (MD), mean square displacement, QIV, MK, and RTOP between the IDH wild-type and IDH mutant groups (p' < .001) (AUC, 0.806-0.978) and MAP-MRI showed a higher IDI than DTI and DKI (0.094-0.435, NRI > 0, respectively). For the chromosome 1p/19q combined deletion, the minimum QIV was different between the overall (p' < .05) and no significant differences  in MD and MK was observed. CONCLUSION: MAP-MRI effectively predicts the WHO grade 2/3, IDH 1/2 mutations, and chromosome 1p/19q combined deletion in adult-type diffuse gliomas, and it may perform better than DTI and DKT.

Diagnostic performance of mono-exponential DWI versus diffusion kurtosis imaging in breast lesions: A meta-analysis.

BACKGROUND: This meta-analysis aimed to explore the diagnostic value of diffusion kurtosis imaging (DKI) compared to mono-exponential diffusion weighted imaging (DWI) in the diagnosis of breast cancer. METHODS: A systematic electronic literature search (up to September 2020) was conducted for published English-language studies comparing the diagnostic values of DKI and DWI for the detection of breast cancer. The data of mean kurtosis (MK), mean diffusivity (MD), and apparent diffusion coefficient (ADC) were extracted to construct 2 × 2 contingency tables. The pooled sensitivities, specificities, and areas under the receiver operating characteristic curve (AUCs) were compared between DKI and DWI in the diagnosis of breast cancer. RESULTS: Eight studies were finally included, with a total of 771 patients in the same population. Pooled sensitivities were 82.0% [95% confidence interval (95% CI), 78.2-85.3%] for ADC, 87.3% (95% CI, 83.9-90.1%) for MK, and 83.9% (95% CI, 80.2-87.1%) for MD. Pooled specificities were 81.1% (95% CI, 76.7-84.9%) for ADC, 85.1% (95% CI, 81.1-88.5%) for MK, and 83.2% (95% CI, 79.0-86.8%) for MD. According to the summary receiver operator characteristic curve analyses, the AUCwas 0.901 for ADC, 0.930 for MK, and 0.918 for MD (ADC vs MK, P = .353; ADC vs MD, P = .611). No notable publication bias was found, while significant heterogeneity was observed. CONCLUSIONS: Although DKI is feasible for identifying breast cancer, MD and MK offer similar diagnostic performance to ADC values. Thus, we recommend that DKI should not be included in the routine evaluation of breast lesions now.

A Dual-Responsive Magnetoactive and Electro-Ionic Soft Actuator Derived from a Nickel-Based Metal-Organic Framework.

There is growing demand for multiresponsive soft actuators for the realization of natural, safe, and complex motions in robotic interactions. In particular, soft actuators simultaneously stimulated by electrical and magnetic fields are always under development owing to their simple controllability and reliability during operation. Herein, magnetically and electrically driven dual-responsive soft actuators (MESAs) derived from novel nickel-based metal-organic frameworks (Ni-MOFs-700C), are reported. Nanoscale Ni-MOFs-700C has excellent electrochemical and magnetic properties that allow it to be used as a multifunctional material under both magnetoactive and electro-ionic actuations. The dual-responsive MESA exhibits a bending displacement of 30 mm and an ultrafast rising time of 1.5 s under a very low input voltage of 1 V and also exerts a bending deflection of 12.5 mm at 50 mT under a high excitation frequency of 5 Hz. By utilizing a dual-responsive MESA, the hovering motion of a hummingbird robot is demonstrated under magnetic and electrical stimuli.

Interaction analysis of FADS2 gene variants with chronic hepatitis B infection in Chinese patients.

The risk of chronic hepatitis B (CHB) infection is often affected by polyunsaturated fatty acids (PUFAs) metabolism which is strongly influenced by single nucleotide polymorphisms (SNPs) within the PUFA metabolic pathway. Given this, we designed this study to determine the relationship between specific polymorphisms within fatty acid desaturase 2 (FADS2), a key enzyme in PUFA metabolism, and CHB infection. We completed this evaluation using a case-control study comprising 230 CHB patients and 234 unrelated healthy controls in which the genetic relationships between three previously identified SNPs, isolated via mass spectrometry, and CHB infection. Our data revealed that none of these three SNPs (rs174568, rs174601, and rs2727270) were significantly associated with susceptibility to CHB infection when compared to healthy controls. However, when we stratified our cohort by sex, male subjects with the TC genotype for FADS2 exhibited a decreased risk for CHB infection (OR = 0.62, 95%CI = 0.39-0.96; OR = 0.64, 95%CI = 0.41-1.00; OR = 0.57, 95%CI = 0.36-0.90). Furthermore, age stratification revealed that both the T allele and the TC genotypes for each of the three target SNPs were less common in Chinese CHB cases in people younger than 50 years old. Correlation analysis also revealed that there was no statistically significant relationship between these three SNPs and HBV-DNA replication or hepatitis B surface antigen (HBsAg) levels. Thus, our data suggests that rs174568, rs174601, and rs2727270 may affect the CHB outcomes in various age or sex subgroups, suggesting that they may be useful predictive or diagnostic biomarkers of CHB infection in some populations.

ACADL Functions as a Tumor Suppressor in Hepatocellular Carcinoma Metastasis by Inhibiting Matrix Metalloproteinase 14.

High aggressiveness is the main reason for the poor prognosis of hepatocellular carcinoma (HCC) patients. However, its molecular mechanisms still remain largely unexplored. ACADL, a mitochondrial enzyme that facilitates the primary regulated step in mitochondrial fatty acid oxidation, plays a role in HCC growth inhibition. However, the function of ACADL in tumor metastasis is not well elucidated. We found that the reduced expression of ACADL is closely associated with the loss of tumor encapsulation, extrahepatic metastasis, and poor prognosis in HCC patients. Upregulation of ACADL significantly inhibited HCC migration and invasion ability. Whereas knockdown of ACADL markedly enhanced cell invasive capability. Expression of matrix metalloproteinase-14 (MMP14) was negatively associated with the content of ACADL in HCC specimens. MMP14-positive patients with a low expression of ACADL showed worse outcome. Treatment with MMP14 agonist reversed the inhibitory effect of ACADL on HCC metastasis. In addition, ACADL negatively regulated MMP14 expression by inhibiting the STAT3 signaling pathway, as the sustained activation of STAT3 effectively restored the level of MMP14 in ACADL-overexpressed cells. Collectively, these findings disclose that ACADL represses HCC metastasis via STAT3-MMP14 pathway. This study may propose a promising strategy for the precise treatment of metastatic HCC patients.

Prognostic and Clinicopathological Correlations of Pretreatment Prognostic Nutritional Index in Renal Cell Carcinoma: A Meta-Analysis.

INTRODUCTION: Prognostic nutritional index (PNI) was indicted as a potential prognostic biomarker for cancer. However, the conclusion remains uncertain for renal cell carcinoma (RCC). This study was to confirm the association of PNI with prognosis and clinicopathological features in RCCs. METHODS: The PubMed, EMBASE, Cochrane Library, CNKI, and Wan Fang databases were searched to retrieve eligible studies. Hazard ratios (HRs) and 95% confidence intervals (CIs) were pooled to assess the strength of the association. RESULTS: Fifteen studies were included. The results showed a low pretreatment PNI level was significantly associated with poor overall survival (HR = 1.67, 95% CI: 1.45-1.92), progression-free survival (HR = 1.72, 95% CI: 1.23-2.42), cancer-specific survival (HR = 1.17, 95% CI: 1.09-1.26), disease-free survival (HR = 1.28, 95% CI: 1.09-1.26), and recurrence-free survival (HR = 2.14, 95% CI: 1.38-3.31). This prognostic role of PNI was almost not changed by subgroup analysis based on study design, HR source, RCC type, sample size, cutoff, follow-up, treatment, and country. Furthermore, low PNI was correlated with old age, large tumor size and high T stage, Fuhrman grade, lymph node, and distant metastases. CONCLUSION: Pretreatment PNI might be a promising indicator to beforehand predict the progression and prognosis for RCC patients.

Optimization of the image contrast for the developing fetal brain using 3D radial VIBE sequence in 3 T magnetic resonance imaging.

BACKGROUND: Faster and motion robust magnetic resonance imaging (MRI) sequences are desirable in fetal brain MRI. T1-weighted images are essential for evaluating fetal brain development. We optimized the radial volumetric interpolated breath-hold examination (VIBE) sequence for qualitative T1-weighted images of the fetal brain with improved image contrast and reduced motion sensitivity. MATERIALS AND METHODS: This was an institutional review board-approved prospective study. Thirty-five pregnant subjects underwent fetal brain scan at 3 Tesla MRI. T1-weighted images were acquired using a 3D radial VIBE sequence with flip angles of 6º, 9º, 12º, and 15º. T1-weighted images of Cartesian VIBE sequence were acquired in three of the subjects. Qualitative assessments including image quality and motion artifact severity were evaluated. The image contrast ratio between gray and white matter were measured. Interobserver reliability and intraobserver repeatability were assessed using intraclass correlation coefficient (ICC). RESULTS: Interobserver reliability and intraobserver repeatability universally revealed almost perfect agreement (ICC > 0.800). Significant differences in image quality were detected in basal ganglia (P = 0.023), central sulcus (P = 0.028), myelination (P = 0.007) and gray matter (P = 0.023) among radial VIBE with flip angles 6º, 9º, 12º, 15º. Image quality at the 9º flip angle in radial VIBE was generally better than flip angle of 15º. Radial VIBE sequence with 9º flip angle of gray matter was significantly different by gestational age (GA) before and after 28 weeks (P = 0.036). Quantified image contrast was significantly different among different flip angles, consistent with qualitative analysis of image quality. CONCLUSIONS: Three-dimensional radial VIBE with 9º flip angle provides optimal, stable T1-weighted images of the fetal brain. Fetal brain structure and development can be evaluated using high-quality images obtained using this angle. However, different scanners will achieve different TRs and so the FA should be re-optimized each time a new protocol is employed.