Notes

On the correction regarding determined vibrational wavelengths for the connection between the particular counterions : α,ω-diamine dihydrochlorides.
The elastic modulus and Poisson's ratio for the skull were the most important parameters, followed by the hyperelastic constants for the brain, scalp and suture. It is recommended that future research prioritises increasing experimental datasets of skull elastic modulus, especially at higher loading rates, followed by obtaining data for the skull Poisson's ratio. The results from this sensitivity analysis can ensure that future experimental work makes the best use of scarce tissues.A major concern in personalised models of heart mechanics is the unknown zero-pressure domain, a prerequisite for accurately predicting cardiac biomechanics. As the reference configuration cannot be captured by clinical data, studies often employ in-vivo frames which are unlikely to correspond to unloaded geometries. Alternatively, zero-pressure domain is approximated through inverse methodologies, which, however, entail assumptions pertaining to boundary conditions and material parameters. Both approaches are likely to introduce biases in estimated biomechanical properties; nevertheless, quantification of these effects is unattainable without ground-truth data. In this work, we assess the unloaded state influence on model-derived biomechanics, by employing an in-silico modelling framework relying on experimental data on porcine hearts. In-vivo images are used for model personalisation, while in-situ experiments provide a reliable approximation of the reference domain, creating a unique opportunity for a validation study. Personalised whole-cycle cardiac models are developed which employ different reference domains (image-derived, inversely estimated) and are compared against ground-truth model outcomes. Simulations are conducted with varying boundary conditions, to investigate the effect of data-derived constraints on model accuracy. Attention is given to modelling the influence of the ribcage on the epicardium, due to its close proximity to the heart in the porcine anatomy. Our results find merit in both approaches for dealing with the unknown reference domain, but also demonstrate differences in estimated biomechanical quantities such as material parameters, strains and stresses. Notably, they highlight the importance of a boundary condition accounting for the constraining influence of the ribcage, in forward and inverse biomechanical models.Critical-sized bone defects are critical healing conditions that, if left untreated, often lead to non-unions. To reduce the risk, critical-sized bone defects are often treated with recombinant human BMP-2. Although enhanced bone tissue formation is observed when BMP-2 is administered locally to the defect, spatial and temporal distribution of callus tissue often differs from that found during regular bone healing or in defects treated differently. How this altered tissue patterning due to BMP-2 treatment is linked to mechano-biological principles at the cellular scale remains largely unknown. In this study, the mechano-biological regulation of BMP-2-treated critical-sized bone defect healing was investigated using a multiphysics multiscale in silico approach. Finite element and agent-based modeling techniques were combined to simulate healing within a critical-sized bone defect (5 mm) in a rat femur. Computer model predictions were compared to in vivo microCT data outcome of bone tissue patterning at 2, 4, and 6 weeks postoperation. Thioflavine S In vivo, BMP-2 treatment led to complete healing through periosteal bone bridging already after 2 weeks postoperation. Computer model simulations showed that the BMP-2 specific tissue patterning can be explained by the migration of mesenchymal stromal cells to regions with a specific concentration of BMP-2 (chemotaxis). This study shows how computational modeling can help us to further understand the mechanisms behind treatment effects on compromised healing conditions as well as to optimize future treatment strategies.
Although bone metastasis beyond the vertebrae and pelvis has been a key factor in prognostic models of metastatic hormone-sensitive prostate cancer (mHSPC), the clinical significance of it is still unclear. The present study evaluated the prognostic impact of the volume of bone metastasis beyond the vertebrae and pelvis on the outcomes of mHSPC and created an ideal risk classification based on it.

We retrospectively reviewed 197 patients with mHSPC who were treated with combined androgen blockade as the initial treatment between June 2003 and October 2019. We calculated the bone scan index (BSI), including the BSI beyond the vertebrae and pelvis (bBSI), using BONENAVI, and investigated the association between the BSI and the overall survival (OS) of mHSPC.

According to the CHAARTED criteria, 91 and 106 patients were classified into the low- and high-volume groups, respectively. Of the 79 patients who did not have visceral metastasis in the high-volume group, those with a bBSI ≤ 0.27 (n = 16) showed a favorable OS, as did those in the low-volume group. The modified CHAARTED high-volume group (presence of visceral metastases or 4 bone lesions with a bBSI > 0.27) showed a significantly shorter OS than others, with a hazard ratio (HR) of 4.69 (p < 0.001), which was higher than that observed with the original CHAARTED criteria (HR = 4.33).

Our data suggested that considering the volume of bone metastasis beyond the vertebrae and pelvis may help to improve the accuracy of risk classification. Further large-scale prospective studies are needed to validate our findings.
Our data suggested that considering the volume of bone metastasis beyond the vertebrae and pelvis may help to improve the accuracy of risk classification. Further large-scale prospective studies are needed to validate our findings.In this article we attend to recent critiques of psychometric applications of life history (LH) theory to variance among humans and develop theory to advance the study of latent LH constructs. We then reanalyze data (n = 4,244) previously examined by Richardson et al. (Evolutionary Psychology, 15(1), 2017, https//doi.org/10.1177/1474704916666840 to determine whether (a) previously reported evidence of multidimensionality is robust to the modeling approach employed and (b) the structure of LH indicators is invariant by sex. Findings provide further evidence that a single LH dimension is implausible and that researchers should cease interpreting K-factor scores as empirical proxies for LH speed. In contrast to the original study, we detected a small inverse correlation between mating competition and Super-K that is consistent with a trade-off. Tests of measurement invariance across the sexes revealed evidence of metric invariance (i.e., equivalence of factor loadings), consistent with the theory that K is a proximate cause of its indicators; however, evidence of partial scalar invariance suggests use of scores likely introduces bias when the sexes are compared.
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