Avian tail ontogeny, pygostyle formation, and interpretation of juvenile Mesozoic specimens

The avian tail played a critical role in the evolutionary transition from long- to short-tailed birds, yet its ontogeny in extant birds has largely been ignored. This deficit has hampered efforts to effectively identify intermediate species during the Mesozoic transition to short tails. Here we show that fusion of distal vertebrae into the pygostyle structure does not occur in extant birds until near skeletal maturity, and mineralization of vertebral processes also occurs long after hatching. Evidence for post-hatching pygostyle formation is also demonstrated in two Cretaceous specimens, a juvenile enantiornithine and a subadult basal ornithuromorph. These findings call for reinterpretations of Zhongornis haoae, a Cretaceous bird hypothesized to be an intermediate in the long- to short-tailed bird transition, and of the recently discovered coelurosaur tail embedded in amber. Zhongornis, as a juvenile, may not yet have formed a pygostyle, and the amber-embedded tail specimen is reinterpreted as possibly avian. Analyses of relative pygostyle lengths in extant and Cretaceous birds suggests the number of vertebrae incorporated into the pygostyle has varied considerably, further complicating the interpretation of potential transitional species. In addition, this analysis of avian tail development reveals the generation and loss of intervertebral discs in the pygostyle, vertebral bodies derived from different kinds of cartilage, and alternative modes of caudal vertebral process morphogenesis in birds. These findings demonstrate that avian tail ontogeny is a crucial parameter specifically for the interpretation of Mesozoic specimens, and generally for insights into vertebrae formation

Spatial assessments in texture analysis: what the radiologist needs to know

To date, studies investigating radiomics-based predictive models have tended to err on the side of data-driven or exploratory analysis of many thousands of extracted features. In particular, spatial assessments of texture have proven to be especially adept at assessing for features of intratumoral heterogeneity in oncologic imaging, which likewise may correspond with tumor biology and behavior. These spatial assessments can be generally classified as spatial filters, which detect areas of rapid change within the grayscale in order to enhance edges and/or textures within an image, or neighborhood-based methods, which quantify gray-level differences of neighboring pixels/voxels within a set distance. Given the high dimensionality of radiomics datasets, data dimensionality reduction methods have been proposed in an attempt to optimize model performance in machine learning studies; however, it should be noted that these approaches should only be applied to training data in order to avoid information leakage and model overfitting. While area under the curve of the receiver operating characteristic is perhaps the most commonly reported assessment of model performance, it is prone to overestimation when output classifications are unbalanced. In such cases, confusion matrices may be additionally reported, whereby diagnostic cut points for model predicted probability may hold more clinical significance to clinical colleagues with respect to related forms of diagnostic testing

Truncating Mutation in the Autophagy Gene \u3cem\u3eUVRAG\u3c/em\u3e Confers Oncogenic Properties and Chemosensitivity in Colorectal Cancers

Autophagy-related factors are implicated in metabolic adaptation and cancer metastasis. However, the role of autophagy factors in cancer progression and their effect in treatment response remain largely elusive. Recent studies have shown that UVRAG, a key autophagic tumour suppressor, is mutated in common human cancers. Here we demonstrate that the cancer-related UVRAG frameshift (FS), which does not result in a null mutation, is expressed as a truncated UVRAGFS in colorectal cancer (CRC) with microsatellite instability (MSI), and promotes tumorigenesis. UVRAGFS abrogates the normal functions of UVRAG, including autophagy, in a dominant-negative manner. Furthermore, expression of UVRAGFS can trigger CRC metastatic spread through Rac1 activation and epithelial-to-mesenchymal transition, independently of autophagy. Interestingly, UVRAGFS expression renders cells more sensitive to standard chemotherapy regimen due to a DNA repair defect. These results identify UVRAG as a new MSI target gene and provide a mechanism for UVRAG participation in CRC pathogenesis and treatment response

A cross-sectional study to test equivalence of low- versus intermediate-flip angle dynamic susceptibility contrast MRI measures of relative cerebral blood volume in patients with high-grade gliomas at 1.5 Tesla field strength

Introduction1.5 Tesla (1.5T) remain a significant field strength for brain imaging worldwide. Recent computer simulations and clinical studies at 3T MRI have suggested that dynamic susceptibility contrast (DSC) MRI using a 30° flip angle (“low-FA”) with model-based leakage correction and no gadolinium-based contrast agent (GBCA) preload provides equivalent relative cerebral blood volume (rCBV) measurements to the reference-standard acquisition using a single-dose GBCA preload with a 60° flip angle (“intermediate-FA”) and model-based leakage correction. However, it remains unclear whether this holds true at 1.5T. The purpose of this study was to test this at 1.5T in human high-grade glioma (HGG) patients.MethodsThis was a single-institution cross-sectional study of patients who had undergone 1.5T MRI for HGG. DSC-MRI consisted of gradient-echo echo-planar imaging (GRE-EPI) with a low-FA without preload (30°/P-); this then subsequently served as a preload for the standard intermediate-FA acquisition (60°/P+). Both normalized (nrCBV) and standardized relative cerebral blood volumes (srCBV) were calculated using model-based leakage correction (C+) with IBNeuro™ software. Whole-enhancing lesion mean and median nrCBV and srCBV from the low- and intermediate-FA methods were compared using the Pearson’s, Spearman’s and intraclass correlation coefficients (ICC).ResultsTwenty-three HGG patients composing a total of 31 scans were analyzed. The Pearson and Spearman correlations and ICCs between the 30°/P-/C+ and 60°/P+/C+ acquisitions demonstrated high correlations for both mean and median nrCBV and srCBV.ConclusionOur study provides preliminary evidence that for HGG patients at 1.5T MRI, a low FA, no preload DSC-MRI acquisition can be an appealing alternative to the reference standard higher FA acquisition that utilizes a preload

Quantitative Computed-Tomography Based Bone-Strength Indicators for the Identification of Low Bone-Strength Individuals in a Clinical Environment

The aim of the current study was to develop quantitative computed-tomography (QCT)-based bone-strength indicators that highly correlate with finite-element (FE)-based strength. We perform a combined numerical-experimental study, comparing FE-predicted surface strains with strain gauge measurements, to validate the FE models of 36 long bones (humerus, radius, femur and tibia) under three-point bending and torsion. The FE models were constructed from trans-axial volumetric CT scans, and the segmented bone images were corrected for partial-volume effects. The material properties (Young\u27s modulus for cortex, density-modulus relationship for trabecular bone and Poisson\u27s ratio) were calibrated by minimizing the error between experiments and simulations among all bones. The resultant R2 values of the measured strains versus load under three-point bending and torsion were 0.96-0.99 and 0.61-0.99, respectively, for all bones in our data set. The errors of the calculated FE strains in comparison to those measured using strain gauges in the mechanical tests ranged from -6% to 7% under bending and from -37% to 19% under torsion. The observation of comparatively low errors and high correlations between the FE-predicted strains and the experimental strains, across the various types of bones and loading conditions (bending and torsion), validates our approach to bone segmentation and our choice of material properties. Based on the analysis of the various FE models of the long bones, the location of the CT slice on the bone that showed the highest propensity to fracture was identified for four loading conditions (compression, three-point bending, cantilever bending and torsion). The identified CT slice was then used to derive novel and improved bone-strength indicators. We evaluated the performance of area-weighted (AW), density-weighted (DW) and modulus-weighted (MW) rigidity measures as well as popular strength indicators like section modulus and stress-strain index. We have also developed a novel strength metric, the centroid deviation, which takes into consideration the spatial distribution of the centroids. Here, we observed that the MW polar moment of inertia and the MW moment of inertia were the two top-performers (average r \u3c 0.87) for all bones and loading conditions. The MW centroid deviations correlated highly with the load to fracture for all bones under compression (r \u3c0.83), except for the humerus (r = 0.67). To test the power of the bone-strength indicators, a receiver operating characteristic (ROC) analysis of the MW rigidity measures that showed the two highest correlations in the femur under compression and three-point bending was performed. QCT scans of a subset of 10 white and 10 black males, who were subjects of a larger study, which reported ethnic differences in bone strength, were used. Results from this small pilot study indicated that the MW section modulus and the MW stress-strain index are the two top performing indicators (area under the ROC curve \u3c 0.79). Consistently DW or MW rigidity measures produced a statistically significant improvement in capturing bone strength compared to AW rigidity measures. The improvement in MW over DW rigidity measures was small yet statistically significant