Search

Background There is a requirement for a personalized strategy to make MRI more accessible to men with suspicion of clinically significant prostate cancer (CSPC). Purpose To evaluate an optimized (Op)-MRI compared with biparametric (Bp)-MRI and multiparametric (Mp)-MRI for the diagnosis of CSPC. Study type Two-center, retrospective. Subjects A total of 346 patients from center 1 and 292 patients from center 2. Field strength/sequence 3.0T scanners, T2 -weighted imaging (T2 WI), diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) imaging. Assessment Four radiologists interpreted the Bp-MRI (T2 WI and DWI) and Mp-MRI (T2 WI, DWI, and DCE) independently according to the Prostate Imaging Reporting and Data System (PI-RADS). For Op-MRI, two radiologists used an adjusted decision rule on Bp-MRI-assessed PI-RADS 3 lesions by determining early enhancement of DCE. Pathologies at biopsy and/or prostatectomy specimens were used as standard references. Statistical tests Performance was assessed using receiver operating characteristic (ROC) curves. Kappa statistics were used to assess interobserver variability. Results Interreader agreement was excellent for all three MRI assessments (all κ values >0.80). Op-MRI had comparable sensitivity (senior/junior: 90.9% [261/287] / 91.6% [263/287]) and higher specificity (78.1% [274/351] /74.4% [261/351]) compared with Mp-MRI (sensitivity: 92.3% [265/287] / 93.7% [269/287]; specificity: 67.8% [238/351] / 68.1% [239/351]) and Bp-MRI (sensitivity: 91.6% [263/287] / 93.4% [268/287]; specificity: 71.2% [250/351] / 70.1% [246/351]) for the diagnosis of CSPC. Compared to Mp-MRI, Op-MRI spared biopsy in 80.7% (515/638) of DCE scans with similar performance accuracy. Compared to Bp-MRI, Op-MRI downgraded 25.2% (31/123) of lesions at a cost of missing 6.5% (3/46) of malignancies, and upgraded 45.5% (56/123) of lesions with a positive predictive value of 62.5% (35/56) in 123 equivocal findings. Data conclusion The Op-MRI, using an adjusted PI-RADS decision rule, did not compromise diagnostic accuracy with sparing biopsy in 80.7% of DCE scans compared to Mp-MRI, and outperformed Bp-MRI by regrading PI-RADS lesions. Level of evidence 4 TECHNICAL EFFICACY STAGE: 2.

Cannabinoid receptor 2 (CB2) has been implicated as an important clinical regulator of inflammation and malignant osteolysis. Here, we observed that CB2 expression was markedly higher in the collagen-induced arthritis (CIA) mice synovium and bone tissues than in the noninflamed synovium and bone tissues. The CB2 selective agonist (JWH133) but not antagonist (SR144528) suppressed CIA in mice without toxic effects, as demonstrated by the decreased synovial hyperplasia, inflammatory responses, cartilage damage, and periarticular and systemic bone destruction. JWH133 treatment decreased the infiltration of pro-inflammatory M1-like macrophages and repolarized macrophages from the M1 to M2 phenotype. Similarly, activation of CB2 increased the expression of anti-inflammatory cytokine interleukin (IL)-10 and reduced the expression of pro-inflammatory cytokines, including tumor necrosis factor-α (TNF-α), IL-1β, and IL-6. In addition, JWH133 treatment attenuated osteoclast formation and osteoclastic bone resorption, and reduced the expression of receptor activators of the nuclear factor-κB (NF-κB) ligand (RANKL), matrix metallopeptidase-9 (MMP-9), tartrate-resistant acid phosphatase (TRAP), cathepsin K (CTSK), and nuclear factor of activated T-cells 1 (NFAT-1) in CIA mice and osteoclast precursors, which were obviously blocked by pretreatment with SR144528. Mechanistically, JWH133 inhibited RANKL-induced NF-κB activation in the osteoclast precursors. We found that JWH133 ameliorates pathologic bone destruction in CIA mice via the inhibition of osteoclastogenesis and modulation of inflammatory responses, thereby highlighting its potential as a treatment for human rheumatoid arthritis. © 2018 American Society for Bone and Mineral Research.

Small cell lung cancer (SCLC) needs to be classified from poorly differentiated lung adenocarcinoma (PDLAC) for appropriate treatment of lung cancer patients. Currently, the classification is achieved by experienced clinicians, radiologists and pathologists based on subjective and qualitative analysis of imaging, cytological and immunohistochemical (IHC) features. Label-free classification of lung cancer cell lines is developed here by using two-dimensional (2D) light scattering static cytometric technique. Measurements of scattered light at forward scattering (FSC) and side scattering (SSC) by using conventional cytometry show that SCLC cells are overlapped with PDLAC cells. However, our 2D light scattering static cytometer reveals remarkable differences between the 2D light scattering patterns of SCLC cell lines (H209 and H69) and PDLAC cell line (SK-LU-1). By adopting support vector machine (SVM) classifier with leave-one-out cross-validation (LOO-CV), SCLC and PDLAC cells are automatically classified with an accuracy of 99.87%. Our label-free 2D light scattering static cytometer may serve as a new, accurate, and easy-to-use method for the automatic classification of SCLC and PDLAC cells. © 2018 International Society for Advancement of Cytometry.

The time-invariant gain-limit-constrained inverse Q-filter can control the numerical instability of the inverse Q-filter, but it often suppresses the high frequencies at later times and reduces the seismic resolution. To improve the seismic resolution and obtain high-quality seismic data, we propose a self-adaptive approach to optimize the Q value for the inverse Q-filter amplitude compensation. The optimized Q value is self-adaptive to the cutoff frequency of the effective frequency band for the seismic data, the gain limit of the inverse Q-filter amplitude compensation, the inverse Q-filter amplitude compensation function, and the medium quality factor. In the processing of the inverse Q-filter amplitude compensation, the optimized Q value, corresponding gain limit, and amplitude compensation function are used simultaneously; then, the energy in the effective frequency band for the seismic data can be recovered, and the seismic resolution can be enhanced at all times. Furthermore, the small gain limit or time-variant bandpass filter after the inverse Q-filter amplitude compensation is considered to control the signal-to-noise ratio, and the time-variant bandpass filter is based on the cutoff frequency of the effective frequency band for the seismic data. Synthetic and real data examples demonstrate that the self-adaptive approach for Q value optimization is efficient, and the inverse Q-filter amplitude compensation with the optimized Q value produces high-resolution and low-noise seismic data.

Pyrolysis and steam gasification experiments of coal char with and without K2CO3 were performed using a thermogravimetric analyzer to investigate the effect of catalyst loading method on gasification reactivity at different temperatures (650–800 °C), and an additional redox cycle experiment of catalyzed char-steam gasification was conducted in a fixed-bed reactor. The results showed that, at low temperature, the solution impregnation method had a larger effect on the gasification reactivity than the physical blending method; at temperatures above 700 °C, the differences of two methods diminished due to the high mobility of potassium. In catalytic pyrolysis, the release of CO and CO2 indicated that K2CO3 reacted with carbon. The redox cycle experiments suggest that the potassium reacted with carbon to produce intermediates of the form K2O2C, K2OC, and K2C. The K2C intermediate may help to explain the release of more H2 during the initial period of catalytic coal char–steam gasification.

Land-use patterns affect the quantity and quality of soil nutrients as well as microbial biomass and respiration in soil. However, few studies have been done to assess the influence of land-use on soil and microbial characteristics of the alpine region on the northeastern Tibetan plateau. In order to understand the effect of land-use management, we examined the chemical properties and microbial biomass of soils under three land-use types including natural grassland, crop-field (50 + y of biennial cropping and fallow) and abandoned old-field (10 y) in the area. The results showed that the losses of soil organic carbon (SOC) and total nitrogen (TN) were about 45 and 43 per cent, respectively, due to cultivation for more than 50 y comparing with natural grassland. Because of the abandonment of cultivation for about a decade, SOC and TN were increased by 27 and 23 per cent, respectively, in comparison with the crop field. Microbial carbon (ranging from 357·5 to 761·6 mg kg−1 soil) in the old-field was intermediate between the crop field and grassland. Microbial nitrogen (ranging from 29·9 to 106·7 mg kg−1 soil) and respiration (ranging from 60·4 to 96·4 mg CO2-C g−1 Cmic d−1) were not significantly lower in the old-field than those in the grassland. Thus it could be concluded that cultivation decreased the organic matter and microbial biomass in soils, while the adoption of abandonment has achieved some targets of grassland restoration in the alpine region of Gansu Province on the northeastern Tibetan plateau. Copyright © 2010 John Wiley & Sons, Ltd.

BACKGROUND: The incidence of dilated cardiomyopathy (DCM) has increased in recent years, and many studies have sought to further improve the general understanding of this condition. Previous studies have demonstrated that some single nucleotide polymorphisms (SNPs) associated with systemic lupus erythematosus also affect susceptibility to DCM, suggesting that immune‐related diseases may share similar genetic susceptibility. Recent large‐scale and genome‐wide association studies have identified NCR3,NOTCH4,CYP1A2,ITGA1,OPRM1,ST8SIA2, and LINC00704 as genetic risk factors associated with cardiac manifestations of neonatal lupus. Here, we aimed to determine whether these SNPs conferred susceptibility to DCM in the Chinese Han population. METHODS: We investigated the relationship between these polymorphisms and DCM risk in 273 patients with DCM and 548 healthy controls. Genotyping was performed using MassArray iPLEX system. RESULTS: Logistic regression analysis indicated that the T allele of rs3134942 in NOTCH4 gene increased the risk of DCM by 61% compared with the G allele (P (a) = 6.57 × 10(−3)). The SNP rs3134942 was also significantly associated with increased DCM risk in the additive (P (a) = 6.57 × 10(−3)) and dominant models (P (a) = 1.01 × 10(−2)). Additionally, rs2472299 in CYP1A2 gene showed suggestive association with reduced risk of DCM in the dominant model (P (a) = 4.24 × 10(−2)) and was correlated with smoking status in patients with DCM (P (a) = 1.56 × 10(−2)). CONCLUSIONS: Our findings suggested that rs3134942 in NOTCH4 may be involved in DCM risk. Further, studies in larger and ethnically diverse populations are required to confirm the results reported in this study.