Potential to reduce methane production of using cultivated seaweeds supplementation to reshape the community structure of rumen microorganisms.

Methane is a short-lived greenhouse gas but has a far greater warming effect than carbon dioxide. At the same time, the livestock sector serves as a large contributor to global emissions of anthropogenic methane. Herein, this work aimed to use cultivated seaweed supplementation to reduce methane emissions and investigate the potential influencing mechanism. To evaluate the feasibility, two cultivated seaweeds, Laminaria japonica Aresch, and Porphyra tenera, along with the enzymatic hydrolysates derived from L. japonica, underwent in vitro trials, and they were both added into corn silage feed (CSF) with different concentrations (1%, 5%, and 10% of CSF) for methane reduction evaluation. The results indicated that >75% and 50% reductions in methane production were observed for the seaweeds and seaweed enzymatic hydrolysates in 9- and 30-day, respectively. Combined high-throughput sequencing and multivariate analysis revealed that supplementation with seaweed and seaweed enzymatic hydrolysates had a notable impact on the prokaryotic community structure. Mantel tests further revealed that significant correlations between the prokaryotic community and methane accumulation (P < 0.05), implying the prokaryotic community plays a role in reducing methane emissions within the rumen. Correspondingly, the networks within the prokaryotic community unveiled the crucial role of propionate/butyrate-producing bacteria in regulating methane emissions through microbial interactions. The predicted function of the prokaryotic community exhibited a significant reduction in the presence of the narB gene in seaweed-supplemented treatments. This reduction may facilitate an increased rate of electron flow toward the nitrate reduction pathway while decreasing the conversion of H2 to methane. These results indicated the supplementation of cultivated seaweeds and the enzymatic hydrolysates has the potential to reshape the community structure of rumen microbial communities, and this alteration appears to be a key factor contributing to their methane production-reduction capability.

A single 8-hydroxyquinoline-appended bile acid fluorescent probe obtained by click chemistry for solvent-dependent and distinguishable sensing of zinc(II) and cadmium(II).

Construction of fluorescent probes for zinc ion (Zn2+ ) and cadmium ion (Cd2+ ) is significant for the safety of humans. However, the discriminating recognition of Zn2+ and Cd2+ by a single probe remains challenging owing to their similar properties. Herein, a novel deoxycholic acid derivative containing 8-hydroxyquinoline fluorophore has been facilely synthesized through click chemistry to form a clamp-like probe. Using its perfect bonding cavity from 1,2,3-triazole and quinoline, this molecule showed favorable solvent-dependent fluorescent responses and distinguished Zn2+ and Cd2+ in different solvents. In ethanol aqueous solution, it displayed good selectivity and ratiometric fluorescence to Zn2+ with 30 nm spectroscopic red-shifts. In acetonitrile aqueous solution, it exhibited good selectivity and ratiometric fluorescence to Cd2+ with 18 nm spectroscopic red-shifts. Moreover, the unique microstructural features of the probe in assembly were used to reflect its recognition processes. Due to its merits of low detection limit and instant response time, the probe was utilized for sensing Zn2+ and Cd2+ in water, beer and urine with high accuracy. Meanwhile, this probe served as a handy tool and was employed to obtain inexpensive test strips for the prompt and semiqualitative analysis of Zn2+ and Cd2+ with the naked eye.

Post-GWAS multiomic functional investigation of the TNIP1 locus in Alzheimer's disease highlights a potential role for GPX3.

INTRODUCTION: Recent genome-wide association studies (GWAS) have reported a genetic association with Alzheimer's disease (AD) at the TNIP1/GPX3 locus, but the mechanism is unclear. METHODS: We used cerebrospinal fluid (CSF) proteomics data to test (n = 137) and replicate (n = 446) the association of glutathione peroxidase 3 (GPX3) with CSF biomarkers (including amyloid and tau) and the GWAS-implicated variants (rs34294852 and rs871269). RESULTS: CSF GPX3 levels decreased with amyloid and tau positivity (analysis of variance P = 1.5 × 10-5) and higher CSF phosphorylated tau (p-tau) levels (P = 9.28 × 10-7). The rs34294852 minor allele was associated with decreased GPX3 (P = 0.041). The replication cohort found associations of GPX3 with amyloid and tau positivity (P = 2.56 × 10-6) and CSF p-tau levels (P = 4.38 × 10-9). DISCUSSION: These results suggest variants in the TNIP1 locus may affect the oxidative stress response in AD via altered GPX3 levels. HIGHLIGHTS: Cerebrospinal fluid (CSF) glutathione peroxidase 3 (GPX3) levels decreased with amyloid and tau positivity and higher CSF phosphorylated tau. The minor allele of rs34294852 was associated with lower CSF GPX3. levels when also controlling for amyloid and tau category. GPX3 transcript levels in the prefrontal cortex were lower in Alzheimer's disease than controls. rs34294852 is an expression quantitative trait locus for GPX3 in blood, neutrophils, and microglia.

Chronic kidney disease promotes cerebral microhemorrhage formation.

BACKGROUND: Chronic kidney disease (CKD) is increasingly recognized as a stroke risk factor, but its exact relationship with cerebrovascular disease is not well-understood. We investigated the development of cerebral small vessel disease using in vivo and in vitro models of CKD. METHODS: CKD was produced in aged C57BL/6J mice using an adenine-induced tubulointerstitial nephritis model. We analyzed brain histology using Prussian blue staining to examine formation of cerebral microhemorrhage (CMH), the hemorrhagic component of small vessel disease and the neuropathological substrate of MRI-demonstrable cerebral microbleeds. In cell culture studies, we examined effects of serum from healthy or CKD patients and gut-derived uremic toxins on brain microvascular endothelial barrier. RESULTS: CKD was induced in aged C57BL/6J mice with significant increases in both serum creatinine and cystatin C levels (p < 0.0001) without elevation of systolic or diastolic blood pressure. CMH was significantly increased and positively correlated with serum creatinine level (Spearman r = 0.37, p < 0.01). Moreover, CKD significantly increased Iba-1-positive immunoreactivity by 51% (p < 0.001), induced a phenotypic switch from resting to activated microglia, and enhanced fibrinogen extravasation across the blood-brain barrier (BBB) by 34% (p < 0.05). On analysis stratified by sex, the increase in CMH number was more pronounced in male mice and this correlated with greater creatinine elevation in male compared with female mice. Microglial depletion with PLX3397 diet significantly decreased CMH formation in CKD mice without affecting serum creatinine levels. Incubation of CKD serum significantly reduced transendothelial electrical resistance (TEER) (p < 0.01) and increased sodium fluorescein permeability (p < 0.05) across the endothelial monolayer. Uremic toxins (i.e., indoxyl sulfate, p-cresyl sulfate, and trimethylamine-N-oxide) in combination with urea and lipopolysaccharide induced a marked drop in TEER compared with the control group (p < 0.0001). CONCLUSIONS: CKD promotes the development of CMH in aged mice independent of blood pressure but directly proportional to the degree of renal impairment. These effects of CKD are likely mediated in part by microglia and are associated with BBB impairment. The latter is likely related to gut-derived bacteria-dependent toxins classically associated with CKD. Overall, these findings demonstrate an important role of CKD in the development of cerebral small vessel disease.

The Big (Genetic) Sort? A Research Note on Migration Patterns and Their Genetic Imprint in the United Kingdom.

This research note reinvestigates Abdellaoui et al.'s (2019) findings that genetically selective migration may lead to persistent and accumulating socioeconomic and health inequalities between types (coal mining or non-coal mining) of places in the United Kingdom. Their migration measure classified migrants who moved to the same type of place (coal mining to coal mining or non-coal mining to non-coal mining) into "stay" categories, preventing them from distinguishing migrants from nonmigrants. We reinvestigate the question of genetically selective migration by examining migration patterns between places rather than place types and find genetic selectivity in whether people migrate and where. For example, we find evidence of positive selection: people with genetic variants correlated with better education moved from non-coal mining to coal mining places with our measure of migration. Such findings were obscured in earlier work that could not distinguish nonmigrants from migrants.

Understanding Internal Migration: A Research Note Providing an Assessment of Migration Selection With Genetic Data.

Migration is selective, resulting in inequalities between migrants and nonmigrants. However, investigating migration selection is empirically challenging because combined pre- and post-migration data are rarely available. We propose an alternative approach to assessing internal migration selection by integrating genetic data, enabling an investigation of migration selection with cross-sectional data collected post-migration. Using data from the UK Biobank, we utilized standard tools from statistical genetics to conduct a genome-wide association study (GWAS) for migration distance. We then calculated genetic correlations to compare GWAS results for migration with those for other characteristics. Given that individual genetics are determined at conception, these analyses allow a unique exploration of the association between pre-migration characteristics and migration. Results are generally consistent with the healthy migrant literature: genetics correlated with longer migration distance are associated with higher socioeconomic status and better health. We also extended the analysis to 53 traits and found novel correlations between migration and several physical health, mental health, personality, and sociodemographic traits.

The antitumor activity and pharmacokinetics research of PPD-Arg (Tos) using ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry.

In this study, a new compound PPD-Arg (Tos) (PAT), an arginine derivative of 20(s)-PPD, was synthesized via Fmoc-Arg (Tos)-OH and 20(s)-PPD. The pharmacokinetic properties in rats, in vitro cytotoxicity, and cell apoptosis rates of protopanaxadiol (PPD) and PAT were determined. A sensitive bioanalytical method for pharmacokinetics using ultra-performance liquid chromatography coupled with time-of-flight mass spectrometry was developed and validated. The result showed that the Tmax and t1/2 of PAT were significantly enhanced, indicating a long-lasting effect in vivo. Compared to the PPD group, the PAT group showed higher bioavailability. PAT also exhibited higher antitumor efficacy than PPD against three cancer cells, especially the strongest inhibitory activity against Huh-7, even more potent than the positive control of paclitaxel. Therefore, the apoptosis assay based on annexin V/propidium iodide-combined staining against Huh-7 further demonstrated that PAT could induce apoptosis of Huh-7 cells. Better pharmacokinetic properties and antitumor efficacy of the arginine derivative of 20(s)-PPD were important. These findings could provide references for further clinical research on amino acid derivatives of PPD as antitumor agents.

An Enzymatic Strategy for the Selective Methylation of High-Value-Added Tetrahydroprotoberberine Alkaloids.

Tetrahydroprotoberberines (THPBs) are plant-specific alkaloids with significant medicinal value. They are present in trace amounts in plants and are difficult to chemically synthesize due to stereoselectivity and an unfavorable environment. In this study, a selective methylation strategy was developed for the biocatalysis of seven high-value-added THPB compounds using 4'-O-methyltransferase (Cj4'OMT), norcoclaurine 6-O-methyltransferase (Cj6OMT), and (S)-scoulerine 9-O-methyltransferase (SiSOMT and PsSOMT) in engineered E. coli. The methyltransferases Cj4'OMT, Cj6OMT, PsSOMT, and SiSOMT were expressed heterologously in E. coli. Compound 1 (10-methoxy-2,3,9-tetrahydroxyberbine) was synthesized using the recombinant E. coli strain Cj4'OMT and the substrate 2,3,9,10-tetrahydroxyberbine. Compound 2 (9-methoxy-2,3,10-tetrahydroxyberbine) was produced in the recombinant Escherichia coli (E. coli) strain PsSOMT, and compounds 2 and 3 (discretamine) were produced in the recombinant E. coli strain SiSOMT. Compounds 4 (9,10-methoxy-2,3-tetrahydroxyberbine) and 5 (corypalmine) were obtained by co-culturing the recombinant strains Cj4'OMT and SiSOMT with substrate. Compounds 6 (scoulerine) and 7 (isoscoulerine) were produced by co-culturing the substrate with the recombinant strains Cj4'OMT and Cj6OMT. To increase the yield of novel compound 2, the flask culture conditions of the engineered SiSOMT strain were optimized, resulting in the production of 165.74 mg/L of this compound. This study thus presents an enzymatic approach to the synthesis of high-value-added THPBs with minimum environmental wastage.

Identification of metabolites in plasma related to different biological activities of Panax ginseng and American ginseng.

RATIONALE: Panax ginseng (PG) and American ginseng (AMG) are both medicinal plants of the Panax genus in the Acanthopanax family. Although PG and AMG have similar components of ginsenosides, there are many differences of their bioactivities. In this study, the biochemical mechanisms of different bioactivities of PG and AMG were explored by researching the differential metabolites in plasma after administration of each of PG and AMG. METHODS: In order to explore the material basis of differential bioactivities, two groups of mice were administrated orally with PG and AMG, and the method of metabolomics was used to identify the differential metabolites in plasma. Then network pharmacology was used based on the differential metabolites. Afterward, the metabolite-target-pathway network of PG and AMG was constructed; thus the pathways related to different bioactivities were analyzed. RESULTS: Through principal component analysis and orthogonal projections to latent structures discriminant analysis, there were 10 differential metabolites identified in the PG group and 8 differential metabolites identified in the AMG group. Based on network pharmacology, the differential metabolites were classified and related to differential bioactivities of PG and AMG. In the PG group, there were 6 metabolites related to aphrodisiac effect and exciting the nervous system, and 5 metabolites associated with raised blood pressure. In the AMG group, 5 metabolites were classified as having the effect of inhibiting the nervous system, and 6 metabolites were related to antihypertensive effect. CONCLUSIONS: This study explored the material basis of the differential biological activities between PG and AMG, which is significant for the research of PG and AMG use and to promote human health.

Biodegradation of Terrigenous Organic Matter in a Stratified Large-Volume Water Column: Implications of the Removal of Terrigenous Organic Matter in the Coastal Ocean.

Large amounts of terrigenous organic matter (TOM) are delivered to the ocean every year. However, removal processes of TOM in the ocean are still poorly constrained. Here, we report results from a 339-day dark incubation experiment with a unique system holding a vertically stratified freshwater-seawater column. The quality and quantity of dissolved organic matter (DOM), RNA-based size-fraction microbial communities, and environmental factors were high-frequency-monitored. Microbial processes impacted TOM composition, including an increased DOM photobleaching rate with incubation time. The mixed layer had changed the bacterial community structure, diversity, and higher oxygen consumption rate. A two-end member modeling analysis suggested that estimated nutrient concentrations and prokaryotic abundance were lower, and total dissolved organic carbon was higher than that of the measured values. These results imply that DOM biodegradation was stimulated during freshwater-seawater mixing. In the bottom layer, fluorescent DOM components increased with the incubation time and were significantly positively related to highly unsaturated, oxygenated, and presumably aromatic compound molecular formulas. These results suggest that surfaced-derived TOM sinking leads to increased DOM transformation and likely results in carbon storage in the bottom water. Overall, these results suggest that microbial transforming TOM plays more important biogeochemical roles in estuaries and coastal oceans than what we know before.

YIPF6 controls sorting of FGF21 into COPII vesicles and promotes obesity.

Fibroblast growth factor 21 (FGF21) is an endocrine hormone that regulates glucose, lipid, and energy homeostasis. While gene expression of FGF21 is regulated by the nuclear hormone receptor peroxisome proliferator-activated receptor alpha in the fasted state, little is known about the regulation of trafficking and secretion of FGF21. We show that mice with a mutation in the Yip1 domain family, member 6 gene (Klein-Zschocher [KLZ]; Yipf6KLZ/Y ) on a high-fat diet (HFD) have higher plasma levels of FGF21 than mice that do not carry this mutation (controls) and hepatocytes from Yipf6KLZ/Y mice secrete more FGF21 than hepatocytes from wild-type mice. Consequently, Yipf6KLZ/Y mice are resistant to HFD-induced features of the metabolic syndrome and have increased lipolysis, energy expenditure, and thermogenesis, with an increase in core body temperature. Yipf6KLZ/Y mice with hepatocyte-specific deletion of FGF21 were no longer protected from diet-induced obesity. We show that YIPF6 binds FGF21 in the endoplasmic reticulum to limit its secretion and specifies packaging of FGF21 into coat protein complex II (COPII) vesicles during development of obesity in mice. Levels of YIPF6 protein in human liver correlate with hepatic steatosis and correlate inversely with levels of FGF21 in serum from patients with nonalcoholic fatty liver disease (NAFLD). YIPF6 is therefore a newly identified regulator of FGF21 secretion during development of obesity and could be a target for treatment of obesity and NAFLD.

Identification of ginsenoside metabolites in plasma related to different bioactivities of Panax notoginseng and Panax ginseng.

Although the chemical components of Panax notoginseng (PN) and Panax ginseng (PG) are similar, their bioactivities are different. In this study, the differential bioactivities of PN and PG were used as the research object. First, the different metabolites in the plasma after oral administration of PN and PG were analyzed using a UPLC-Q/TOF-MS-based metabolomics approach. Afterward, the metabolite-target- pathway network of PN and PG was constructed, and thus the pathways related to different bioactivities were analyzed. As a result, 7 different metabolites were identified in PN group, and 10 different metabolites were identified in the PG group. In the PN group, the metabolite N1 was related to hemostasis, N1 and N3 were related to inhibiting the nerve center, antihypertensive, and abirritation. The metabolites N1, N3, N4, N5, and N6 were related to liver protection. The results showed that the metabolites G1, G2, G3, G5, and G6 in PG group were related to heart protection, and G1, G2, G6, and G9 were related to increased blood pressure. There were 13 signaling pathways related to different biological activities of PN (8 pathways) and PG (5 pathways). These pathways further clarified the mechanism of action that caused the different bioactivities between PN and PG. In summary, metabolomics combined with network pharmacology could be helpful to clarify the material basis of different bioactivities between PN and PG, promoting the research on PN and PG.

Dynamic Changes of Asymmetric Cortical Veins Relate to Neurologic Prognosis in Acute Ischemic Stroke.

Background Cerebral oxygenation is closely related to neural function in acute ischemic stroke (AIS) and can be measured noninvasively from asymmetrically prominent cortical veins (APCVs) using quantitative susceptibility mapping (QSM). Purpose To quantify venous oxygen saturation (SvO2) using brain MRI with QSM in patients with AIS, to analyze its change at 2-week follow-up, and to assess the influence of SvO2 in clinical prognosis. Materials and Methods Between 2016 and 2020, consecutive patients with AIS who underwent brain MRI within 24 hours from symptom onset and 2 weeks after treatment were retrospectively enrolled. The SvO2 of APCVs was quantified using QSM. The independent sample t test was used to compare the SvO2 between patients with and patients without APCVs. The paired sample t test was used to assess the dynamic change in SvO2. Pearson and Spearman correlation analysis was used to explore the relationship among dynamic change in SvO2 and hypoperfusion, National Institutes of Health Stroke Scale (NIHSS) score change, and 90-day modified Rankin Scale (mRS) score. The independent sample t test was used to compare the dynamic change in SvO2 between different clinical prognoses and outcome subgroups. Results APCVs were detected in 39 of 73 patients (mean age, 70 years ± 10 [standard deviation]; 49 men) at admission and disappeared in 35 patients at 2-week follow-up MRI. The mean SvO2 increased from 35.0% ± 5.8 to 64.5% ± 10.0 (P < .001) in 39 patients. For the 35 patients with APCVs that disappeared, the dynamic change in SvO2 negatively correlated with change in NIHSS score (r = -0.37, R2 = 0.19, P = .03) and 90-day mRS score (r = -0.54, R2 = 0.27, P = .001), and the dynamic change in SvO2 in the subgroup with good 90-day outcomes (n = 19) was greater than that in the subgroup with poor 90-day outcomes (n = 16) (mean, 34.5% ± 5.8 vs 29.7% ± 6.3; 95% CI: 0.6, 8.9; P = .03). Conclusion Improved oxygen saturation of asymmetric cortical veins detected using brain MRI with quantitative susceptibility mapping corresponded with better acute ischemic stroke outcomes for patients with asymmetrically prominent cortical veins that disappeared at 2-week follow-up MRI. © RSNA, 2021 Online supplemental material is available for this article.

Magnetic Resonance Imaging-Based Radiomics Nomogram for Prediction of the Histopathological Grade of Soft Tissue Sarcomas: A Two-Center Study.

BACKGROUND: Preoperative prediction of soft tissue sarcoma (STS) grade is important for treatment decisions. Therefore, formulation an STS grade model is strongly needed. PURPOSE: To develop and test an magnetic resonance imaging (MRI)-based radiomics nomogram for predicting the grade of STS (low-grade vs. high grade). STUDY TYPE: Retrospective POPULATION: One hundred and eighty patients with STS confirmed by pathologic results at two independent institutions were enrolled (training set, N = 109; external validation set, N = 71). FIELD STRENGTH/SEQUENCE: Unenhanced T1-weighted (T1WI) and fat-suppressed T2-weighted images (FS-T2WI) were acquired at 1.5 T and 3.0 T. ASSESSMENT: Clinical-MRI characteristics included age, gender, tumor-node-metastasis (TNM) stage, American Joint Committee on Cancer (AJCC) stage, progression-free survival (PFS), and MRI morphological features (ie, margin). Radiomics feature extraction were performed on T1WI and FS-T2WI images by minimum redundancy maximum relevance (MRMR) method and least absolute shrinkage and selection operator (LASSO) algorithm. The selected features constructed three radiomics signatures models (RS-T1， RS-FST2, and RS-Combined). Univariate and multivariate logistic regression analysis were applied for screening significant risk factors. Radiomics nomogram was constructed by incorporating the radiomics signature and risk factors. STATISTICAL TESTS: Clinical-MRI characteristics were performed by a univariate analysis. Model performances (discrimination, calibration, and clinical usefulness) were validated in the external validation set. The RS-T1 model, RS-FST2 model, and RS-Combined model had an area under curves (AUCs) of 0.645, 0.641, and 0.829, respectively, in the external validation set. The radiomics nomogram, incorporating significant risk factors and the RS-Combined model had AUCs of 0.916 (95%CI, 0.866-0.966, training set) and 0.879 (95%CI, 0.791-0.967, external validation set), and demonstrated good calibration and good clinical utility. DATA CONCLUSION: The proposed noninvasive MRI-based radiomics models showed good performance in differentiating low-grade from high-grade STSs. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 2.

Nomogram to Assess the Risk of Central Cervical Lymph Node Metastasis in Patients With Clinical N0 Papillary Thyroid Carcinoma.

OBJECTIVE: To develop and validate an individualized risk prediction model for the need for central cervical lymph node dissection in patients with clinical N0 papillary thyroid carcinoma (PTC) diagnosed using ultrasound. METHODS: Upon retrospective review, derivation and internal validation cohorts comprised 1585 consecutive patients with PTC treated from January 2017 to December 2019 at hospital A. The external validation cohort consisted of 406 consecutive patients treated at hospital B from January 2016 to June 2020. Independent risk factors for central cervical lymph node metastasis (CLNM) were determined through univariable and multivariable logistic regression analysis. An individualized risk prediction model was constructed and illustrated as a nomogram, which was internally and externally validated. RESULTS: The following risk factors of CLNM were established: a solitary primary thyroid nodule's diameter, shape, calcification, and capsular abutment-to-lesion perimeter ratio. The areas under the receiver operating characteristic curves of the risk prediction model for the internal and external validation cohorts were 0.921 and 0.923, respectively. The calibration curve showed good agreement between the nomogram-estimated probability of CLNM and the actual CLNM rates in the 3 cohorts. The decision curve analysis confirmed the clinical usefulness of the nomogram. CONCLUSION: This study developed and validated a model for predicting the risk of CLNM in individual patients with clinical N0 PTC, which should be an efficient tool for guiding clinical treatment.

Artificial exosomes for translational nanomedicine.

Exosomes are lipid bilayer membrane vesicles and are emerging as competent nanocarriers for drug delivery. The clinical translation of exosomes faces many challenges such as massive production, standard isolation, drug loading, stability and quality control. In recent years, artificial exosomes are emerging based on nanobiotechnology to overcome the limitations of natural exosomes. Major types of artificial exosomes include 'nanovesicles (NVs)', 'exosome-mimetic (EM)' and 'hybrid exosomes (HEs)', which are obtained by top-down, bottom-up and biohybrid strategies, respectively. Artificial exosomes are powerful alternatives to natural exosomes for drug delivery. Here, we outline recent advances in artificial exosomes through nanobiotechnology and discuss their strengths, limitations and future perspectives. The development of artificial exosomes holds great values for translational nanomedicine.

Radiomics and Machine Learning With Multiparametric Preoperative MRI May Accurately Predict the Histopathological Grades of Soft Tissue Sarcomas.

BACKGROUND: Preoperative prediction of the grade of soft tissue sarcomas (STSs) is important because of its effect on treatment planning. PURPOSE: To assess the value of radiomics features in distinguishing histological grades of STSs. STUDY TYPE: Retrospective. POPULATION: In all, 113 patients with pathology-confirmed low-grade (grade I), intermediate-grade (grade II), or high-grade (grade III) soft tissue sarcoma were collected. FIELD STRENGTH/SEQUENCE: The 3.0T axial T1 -weighted imaging (T1 WI) with 550 msec repetition time (TR); 18 msec echo time (TE), 312 × 312 matrix, fat-suppressed fast spin-echo T2 WI with 4291 msec TR, 85 msec TE, 312 × 312 matrix. ASSESSMENT: Multiple machine-learning methods were trained to establish classification models for predicting STS grades. Eighty STS patients (18 low-grade [grade I]; 62 high-grade [grades II-III]) were enrolled in the primary set and we tested the model with a validation set with 33 patients (7 low-grade, 26 high-grade). STATISTICAL TESTS: 1) Student's t-tests were applied for continuous variables and the χ2 test were applied for categorical variables between low-grade STS and high-grade STS groups. 2) For feature subset selection, either no subset selection or recursive feature elimination was performed. This technology was combined with random forest and support vector machine-learning methods. Finally, to overcome the disparity in the frequencies of the STS grades, each machine-learning model was trained i) without subsampling, ii) with the synthetic minority oversampling technique, and iii) with random oversampling examples, for a total of 12 combinations of machine-learning algorithms that were assessed, trained, and tested in the validation cohort. RESULTS: The best classification model for the prediction of STS grade was a combination of features selected by recursive feature elimination and random forest classification algorithms with a synthetic minority oversampling technique, which had an area under the curve of 0.9615 (95% confidence interval 0.8944-1.0) in the validation set. DATA CONCLUSION: Radiomics feature-based machine-learning methods are useful for distinguishing STS grades. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:791-797.

Radiomics nomogram for differentiating between benign and malignant soft-tissue masses of the extremities.

BACKGROUND: Preoperative differentiation between malignant and benign tumors is important for treatment decisions. PURPOSE/HYPOTHESIS: To investigate/validate a radiomics nomogram for preoperative differentiation between malignant and benign masses. STUDY TYPE: Retrospective. POPULATION: Imaging data of 91 patients. FIELD STRENGTH/SEQUENCE: T1 -weighted images (570 msec repetition time [TR]; 17.9 msec echo time [TE], 200-400 mm field of view [FOV], 208-512 × 208-512 matrix), fat-suppressed fast-spin-echo (FSE) T2 -weighted images (T2 WIs) (4331 msec TR; 87.9 msec TE, 200-400 mm FOV, 312 × 312 matrix), slice thickness 4 mm, and slice spacing 1 mm. ASSESSMENT: Fat-suppressed FSE T2 WIs were selected for extraction of features. Radiomics features were extracted from fat-suppressed T2 WIs. A radiomics signature was generated from the training dataset using least absolute shrinkage and selection operator algorithms. Independent risk factors were identified by multivariate logistic regression analysis and a radiomics nomogram was constructed. Nomogram capability was evaluated in the training dataset and validated in the validation dataset. Performance of the nomogram, radiomics signature, and clinical model were compared. STATISTICAL TESTS: 1) Independent t-test or Mann-Whitney U-test: for continuous variables. Fisher's exact test or χ2 test: comparing categorical variables between two groups. Univariate analysis: evaluating associations between clinical/morphological characteristics and malignancy. 2) Least absolute shrinkage and selection operator (LASSO)-logistic regression model: selection of malignancy features. 3) Significant clinical/morphological characteristics and radiomics signature were input variables for multiple logistic regression analysis. Area under the curve (AUC): evaluation of ability of the nomogram to identify malignancy. Hosmer-Lemeshow test and decision curve: evaluation and validation of nomogram results. RESULTS: The radiomics nomogram was able to differentiate malignancy from benignity in the training and validation datasets with an AUC of 0.94. The nomogram outperformed both the radiomics signature and clinical model alone. DATA CONCLUSION: This radiomics nomogram is a noninvasive, low-cost preoperative prediction method combining the radiomics signature and clinical model. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:155-163.

Preoperative MRI-Based Radiomic Machine-Learning Nomogram May Accurately Distinguish Between Benign and Malignant Soft-Tissue Lesions: A Two-Center Study.

BACKGROUND: Preoperative differentiation between malignant and benign soft-tissue masses is important for treatment decisions. PURPOSE/HYPOTHESIS: To construct/validate a radiomics-based machine method for differentiation between malignant and benign soft-tissue masses. STUDY TYPE: Retrospective. POPULATION: In all, 206 cases. FIELD STRENGTH/SEQUENCE: The T1 sequence was acquired with the following range of parameters: relaxation time / echo time (TR/TE), 352-550/2.75-19 msec. The T2 sequence was acquired with the following parameters: TR/TE, 700-6370/40-120 msec. The data were divided into a 3.0T training cohort, a 1.5T MR validation cohort, and a 3.0T external validationcohort. ASSESSMENT: Twelve machine-learning methods were trained to establish classification models to predict the likelihood of malignancy of each lesion. The data of 206 cases were separated into a training set (n = 69) and two validation sets (n = 64, 73, respectively). STATISTICAL TESTS: 1) Demographic characteristics: a one-way analysis of variance (ANOVA) test was performed for continuous variables as appropriate. The χ2 test or Fisher's exact test was performed for comparing categorical variables as appropriate. 2) The performance of four feature selection methods (least absolute shrinkage and selection operator [LASSO], Boruta, Recursive feature elimination [RFE, and minimum redundancy maximum relevance [mRMR]) and three classifiers (support vector machine [SVM], generalized linear models [GLM], and random forest [RF]) were compared for selecting the likelihood of malignancy of each lesion. The performance of the radiomics model was assessed using area under the receiver-operating characteristic curve (AUC) and accuracy (ACC) values. RESULTS: The LASSO feature method + RF classifier achieved the highest AUC of 0.86 and 0.82 in the two validation cohorts. The nomogram achieved AUCs of 0.96 and 0.88, respectively, in the two validation sets, which was higher than that of the radiomic algorithm in the two validation sets and clinical model of the validation 1 set (0.92, 0.88 respectively). The accuracy, sensitivity, and specificity of the radiomics nomogram were 90.5%, 100%, and 80.6%, respectively, for validation set 1; and 80.8%, 75.8%, and 85.0% for validation set 2. DATA CONCLUSION: A machine-learning nomogram based on radiomics was accurate for distinguishing between malignant and benign soft-tissue masses. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2 J. Magn. Reson. Imaging 2020;52:873-882.

Suppression of peripheral NGF attenuates neuropathic pain induced by chronic constriction injury through the TAK1-MAPK/NF-κB signaling pathways.

BACKGROUND: Anti-nerve growth factor (NGF) monoclonal antibodies (anti-NGF mAbs) have been reported to significantly attenuate pain, but the mechanism involved has not been fully elucidated, and the serious adverse events associated with mAbs seriously limit their clinical use. This study further investigated the mechanism by which peripheral NGF is involved in neuropathic pain and found safe, natural compounds that target NGF to attenuate neuropathic pain. METHODS: Nociception was assessed by the Von Frey hair and Hargreaves' methods. Western-blotting, qPCR and immunofluorescence were used to detect the cell signaling pathway. RAW264.7 macrophages and RSC96 Schwann cells were cultured for in vitro evaluation. RESULTS: Intraplantar administration of anti-NGF mAbs suppressed the expression of phosphorylated transforming growth factor-ß-activated kinase 1 (TAK1) in the dorsal root ganglion (DRG) and sciatic nerve. Intraplantar administration of a TAK1 inhibitor attenuated CCI-induced neuropathic pain and suppressed the expression of phosphorylated mitogen-activated protein kinases (MAPKs) in the DRG and sciatic nerve. Perisciatic nerve administration of levo-corydalmine (l-CDL) on the operated side obviously attenuated CCI-induced neuropathic pain and suppressed the expression of mNGF and proNGF. In addition, l-CDL-induced antinociception was reversed by intraplantar administration of NGF. Further results indicated that l-CDL-induced suppression of phosphorylated TAK1, MAPKs, and p65 and expression of the proinflammatory cytokines TNF-α and IL-1ß in the DRG and sciatic nerve were all abolished by NGF. In addition, in vitro experiments indicated that l-CDL suppressed the secretion of NGF and proNGF in RAW264.7 macrophages and RSC96 Schwann cells, which was abolished by AP-1 and CREB agonists, respectively. CONCLUSIONS: This study showed NGF inhibition suppressed TAK1 in the periphery to attenuate CCI-induced neuropathic pain through inhibition of downstream MAPK and p65 signaling. The natural compound l-CDL inhibited NGF secretion by macrophages and Schwann cells and downstream TAK1-MAPK/NF-κB signaling in the periphery to attenuate CCI-induced neuropathic pain. Video abstract Proposed mechanisms underlying the effect of l-CDL in periphery of CCI rats. In CCI rats, macropahages and Schwann cells could secret NGF to act on the receptors in the periphery to activate TAK1-MAPK/NF-κB axis and promote the release of proinflammatory cytokines, including TNF-α and IL-1ß to promote neuropathic pain. l-CDL decreased the secretion of NGF through inhibiting AP-1 and CREB respectively in RAW264.7 and RSC96 Schwann cells to attenuate CCI-induced neuropathic pain by inhibiting the TAK1-p38 MAPK/NF-κB signaling pathway.