Regardless of exact or non-exact matching, adjusted ULR is generally biased unless the functional form of the matched factors is modelled correctly. The validity of adjusted ULR is vulnerable to model specification error. CLR should remain the primary analytic approach.
  UroVysion cases with one to three abnormal cells that do not meet the threshold for positivity may be better classified as "indeterminate." The aim of this study is to determine the incidence and clinical significance of these indeterminate UroVysion results.
 
  The UroVysion fluorescence in situ hybridization (FISH) results over a 4-year period in our institution were retrospectively analyzed. Follow-up of the initial UroVysion cases, including urine cytology or bladder biopsy performed within 12 months of the initial diagnosis of the result, was obtained from pathology reports.
 
  A significant fraction (178 of 1,907, 9.3%) of the UroVysion cases had indeterminate results. Overall, the subsequent malignancy rate of the group with indeterminate UroVysion results (14 of 59, 23.7%) was higher than the group with normal results (48 of 319, 15.0%), although the difference was not significant (P = .124). For patients without a history of urinary tract neoplasm, the subsequent malignancy rate in the group with indeterminate results (7 of 18, 38.9%) was significantly higher than the group with normal results (16 of 103, 15.5%) (P = .044).
 
  Our results support that indeterminate UroVysion FISH result may warrant closer clinical follow-up in patients without a history of urinary tract neoplasm. We suggest reporting these cases as "aneusomy of undetermined significance."
 Our results support that indeterminate UroVysion FISH result may warrant closer clinical follow-up in patients without a history of urinary tract neoplasm. We suggest reporting these cases as "aneusomy of undetermined significance."The protein-protein interactions (PPIs) between human and viruses mediate viral infection and host immunity processes. Therefore, the study of human-virus PPIs can help us understand the principles of human-virus relationships and can thus guide the development of highly effective drugs to break the transmission of viral infectious diseases. Recent years have witnessed the rapid accumulation of experimentally identified human-virus PPI data, which provides an unprecedented opportunity for bioinformatics studies revolving around human-virus PPIs.  https://www.selleckchem.com/products/rvx-208.html  In this article, we provide a comprehensive overview of computational studies on human-virus PPIs, especially focusing on the method development for human-virus PPI predictions. We briefly introduce the experimental detection methods and existing database resources of human-virus PPIs, and then discuss the research progress in the development of computational prediction methods. In particular, we elaborate the machine learning-based prediction methods and highlight the need to embrace state-of-the-art deep-learning algorithms and new feature engineering techniques (e.g. the protein embedding technique derived from natural language processing). To further advance the understanding in this research topic, we also outline the practical applications of the human-virus interactome in fundamental biological discovery and new antiviral therapy development.
  Branch biomass and other attributes are important for estimating the carbon budget of forest stands and characterizing crown structure. As destructive measuring is time-consuming and labour-intensive, terrestrial laser scanning (TLS) as a solution has been used to estimate branch biomass quickly and non-destructively. However, branch information extraction from TLS data alone is challenging due to occlusion and other defects, especially for estimating individual branch attributes in coniferous trees.
 
  This study presents a method, entitled TSMtls, to estimate individual branch biomass non-destructively and accurately by combining tree structure models and TLS data. The TSMtls constructs the stem taper curve from TLS data, then uses tree structure models to determine the number, basal area and biomass of individual branches in the whorl-level. We estimated the tree structural model parameters from 122 destructively measured Scots pine (Pinus sylvestris) trees and tested the method on 6 Scots pine trees that were first TLS scanned and later destructively measured. Additionally, we estimated the branch biomass using other TLS-based approaches for comparison.
 
  Tree-level branch biomass estimates derived from TSMtls showed the best agreement with the destructive measurements (coefficient of variation of root mean square error [CV-RMSE]= 9.66% and concordance correlation coefficient [CCC]= 0.99), outperforming the other TLS-based approaches (12.97%-57.45% CV-RMSE and 0.43-0.98 CCC). Whorl-level individual branch attributes estimates produced from TSMtls showed more accurate results than those produced from TLS data directly.
 
  The results showed that the TSMtls method proposed in this study holds promise for extending to more species and larger areas.
 The results showed that the TSMtls method proposed in this study holds promise for extending to more species and larger areas.
  Many children worldwide do not eat recommended amounts of vegetables. Disliking vegetables is a key factor associated with low intake.
 
  This umbrella review synthesized systematic reviews to determine the effectiveness of sensory and behavioral strategies to facilitate liking of vegetables (primary outcome) in young children up to 5 y of age, as key predictors of vegetable intake (secondary outcome).
 
  Nine databases were searched up to May 2019 (updated in September 2020). Two reviewers independently conducted study screening and selection, data extraction, and assessment of methodological quality using AMSTAR 2 (AMeaSurement Tool to Assess systematic Reviews). Eleven reviews (n=1 rated strong quality, n=4 moderate quality, n=6 low/critically low quality) examining 85 primary studies met the review criteria systematic reviews and meta-analyses of primary studies (any quantitative design) that examined sensory or behavioral strategies on vegetable liking or intake (outcomes reported separately for children ≤5 y).