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\"In this book, Kevin M. Cherry compares the views of Aristotle and Plato about the practice, study, and above all, the purpose of politics\"-- Provided by publisher.

Background Computational modeling of cardiovascular flow is a growing and useful field, but such simulations usually require the researcher to guess the flow’s inlet and outlet conditions since they are difficult and expensive to measure. It is critical to determine the amount of uncertainty introduced by these assumptions in order to evaluate the degree to which cardiovascular flow simulations are accurate. Our work begins to address this question by examining the sensitivity of flow to several different assumed velocity inlet and outlet conditions in a patient-specific aorta model. Methods We examined the differences between plug flow, parabolic flow, linear shear flows, skewed cubic flow profiles, and Womersley flow at the inlet. Only the shape of the inlet velocity profile was varied—all other parameters were identical among these simulations. Secondary flow in the form of a counter-rotating pair of vortices was also added to parabolic axial flow to study its effect on the solution. In addition, we examined the differences between two-element Windkessel, three element Windkessel and the outflow boundary conditions. In these simulations, only the outlet boundary condition was varied. Results The results show axial and in-plane velocities are considerably different close to the inlet for the cases with different inlet velocity profile shapes. However, the solutions are qualitatively similar beyond 1.75 D , where D is the inlet diameter. This trend is also observed in other quantities such as pressure and wall shear stress. Normalized root-mean-square deviation, a measure of axial velocity magnitude differences between the different cases, generally decreases along the streamwise coordinate. The linear shear inlet velocity boundary condition and plug velocity boundary condition solution exhibit the highest time-averaged wall shear stress, approximately 8 % higher than the parabolic inlet velocity boundary condition. Upstream of 1 D from the inlet, adding secondary flow has a significant impact on temporal wall shear stress distributions. This is especially observable during diastole, when integrated wall shear stress magnitude varies about 26 % between simulations with and without secondary flow. The results from the outlet boundary condition study show the Windkessel models differ from the outflow boundary condition by as much as 18 % in terms of time-averaged wall shear stress. Furthermore, normalized root-mean-square deviation of axial velocity magnitude, a measure of deviation between Windkessel and the outflow boundary condition, increases along the streamwise coordinate indicating larger variations near outlets. Conclusion It was found that the selection of inlet velocity conditions significantly affects only the flow region close to the inlet of the aorta. Beyond two diameters distal to the inlet, differences in flow solution are small. Although additional studies must be performed to verify this result, the data suggest that it is important to use patient-specific inlet conditions primarily if the researcher is concerned with the details of the flow very close to the inlet. Similarly, the selection of outlet conditions significantly affects the flow in the vicinity of the outlets. Upstream of five diameters proximal to the outlet, deviations between the outlet boundary conditions examined are insignificant. Although the inlet and outlet conditions only affect the flow significantly in their respective neighborhoods, our study indicates that outlet conditions influence a larger percentage of the solution domain.

PurposeWe conducted a feasibility study to investigate the use of ketogenic diets (KDs) as an adjuvant therapy for patients with glioblastoma (GBM), investigating (i) trial feasibility; (ii) potential impacts of the trial on patients’ quality of life and health; (iii) patients’ perspectives of their decision-making when invited to participate in the trial and (iv) recommending improvements to optimize future phase III trials.MethodsA single-center, prospective, randomized, pilot study (KEATING), with an embedded qualitative design. Twelve newly diagnosed patients with GBM were randomized 1:1 to modified ketogenic diet (MKD) or medium chain triglyceride ketogenic diet (MCTKD). Primary outcome was retention at three months. Semi-structured interviews were conducted with a purposive sample of patients and caregivers (n = 15). Descriptive statistics were used for quantitative outcomes and qualitative data were analyzed thematically aided by NVivo.ResultsKEATING achieved recruitment targets, but the recruitment rate was low (28.6%). Retention was poor; only four of 12 patients completed the three-month diet (MCTKD n = 3; MKD n = 1). Participants’ decisions were intuitive and emotional; caregivers supported diet implementation and influenced the patients’ decision to participate. Those who declined made a deliberative and considered decision factoring diet burden and quality of life. A three-month diet was undesirable to patients who declined and withdrew.ConclusionRecruitment to a KD trial for patients with GBM is possible. A six-week intervention period is proposed for a phase III trial. The role of caregivers should not be underestimated. Future trials should optimize and adequately support the decision-making of patients.

Numerical integration of mathematical models of heart cell electrophysiology provides an important computational tool for studying cardiac arrhythmias, but the abundance of available models complicates selecting an appropriate model. We study the behavior of two recently published models of human ventricular action potentials, the Grandi-Pasqualini-Bers (GPB) and the O'Hara-Virág-Varró-Rudy (OVVR) models, and compare the results with four previously published models and with available experimental and clinical data. We find the shapes and durations of action potentials and calcium transients differ between the GPB and OVVR models, as do the magnitudes and rate-dependent properties of transmembrane currents and the calcium transient. Differences also occur in the steady-state and S1-S2 action potential duration and conduction velocity restitution curves, including a maximum conduction velocity for the OVVR model roughly half that of the GPB model and well below clinical values. Between single cells and tissue, both models exhibit differences in properties, including maximum upstroke velocity, action potential amplitude, and minimum diastolic interval. Compared to experimental data, action potential durations for the GPB and OVVR models agree fairly well (although OVVR epicardial action potentials are shorter), but maximum slopes of steady-state restitution curves are smaller. Although studies show alternans in normal hearts, it occurs only in the OVVR model, and only for a narrow range of cycle lengths. We find initiated spiral waves do not progress to sustained breakup for either model. The dominant spiral wave period of the GPB model falls within clinically relevant values for ventricular tachycardia (VT), but for the OVVR model, the dominant period is longer than periods associated with VT. Our results should facilitate choosing a model to match properties of interest in human cardiac tissue and to replicate arrhythmia behavior more closely. Furthermore, by indicating areas where existing models disagree, our findings suggest avenues for further experimental work.

Copy-number analysis to detect disease-causing losses and gains across the genome is recommended for the evaluation of individuals with neurodevelopmental disorders and/or multiple congenital anomalies, as well as for fetuses with ultrasound abnormalities. In the decade that this analysis has been in widespread clinical use, tremendous strides have been made in understanding the effects of copy-number variants (CNVs) in both affected individuals and the general population. However, continued broad implementation of array and next-generation sequencing–based technologies will expand the types of CNVs encountered in the clinical setting, as well as our understanding of their impact on human health. This Article was originally published without the accompanying supplementary file “All evaluated CNVs”. This file is now available in the HTML version of the Article; the PDF was correct from the time of publication. A Correction to this paper has been published: https://doi.org/10.1038/s41436-021-01150-9 To assist clinical laboratories in the classification and reporting of CNVs, irrespective of the technology used to identify them, the American College of Medical Genetics and Genomics has developed the following professional standards in collaboration with the National Institutes of Health (NIH)–funded Clinical Genome Resource (ClinGen) project. This update introduces a quantitative, evidence-based scoring framework; encourages the implementation of the five-tier classification system widely used in sequence variant classification; and recommends “uncoupling” the evidence-based classification of a variant from its potential implications for a particular individual. These professional standards will guide the evaluation of constitutional CNVs and encourage consistency and transparency across clinical laboratories.

From bacteria following simple chemical gradients 1 to the brain distinguishing complex odour information 2 , the ability to recognize molecular patterns is essential for biological organisms. This type of information-processing function has been implemented using DNA-based neural networks 3 , but has been limited to the recognition of a set of no more than four patterns, each composed of four distinct DNA molecules. Winner-take-all computation 4 has been suggested 5 , 6 as a potential strategy for enhancing the capability of DNA-based neural networks. Compared to the linear-threshold circuits 7 and Hopfield networks 8 used previously 3 , winner-take-all circuits are computationally more powerful 4 , allow simpler molecular implementation and are not constrained by the number of patterns and their complexity, so both a large number of simple patterns and a small number of complex patterns can be recognized. Here we report a systematic implementation of winner-take-all neural networks based on DNA-strand-displacement 9 , 10 reactions. We use a previously developed seesaw DNA gate motif 3 , 11 , 12 , extended to include a simple and robust component that facilitates the cooperative hybridization 13 that is involved in the process of selecting a ‘winner’. We show that with this extended seesaw motif DNA-based neural networks can classify patterns into up to nine categories. Each of these patterns consists of 20 distinct DNA molecules chosen from the set of 100 that represents the 100 bits in 10 × 10 patterns, with the 20 DNA molecules selected tracing one of the handwritten digits ‘1’ to ‘9’. The network successfully classified test patterns with up to 30 of the 100 bits flipped relative to the digit patterns ‘remembered’ during training, suggesting that molecular circuits can robustly accomplish the sophisticated task of classifying highly complex and noisy information on the basis of similarity to a memory. DNA-strand-displacement reactions are used to implement a neural network that can distinguish complex and noisy molecular patterns from a set of nine possibilities—an improvement on previous demonstrations that distinguished only four simple patterns.

The emergence of pose estimation algorithms represents a potential paradigm shift in the study and assessment of human movement. Human pose estimation algorithms leverage advances in computer vision to track human movement automatically from simple videos recorded using common household devices with relatively low-cost cameras (e.g., smartphones, tablets, laptop computers). In our view, these technologies offer clear and exciting potential to make measurement of human movement substantially more accessible; for example, a clinician could perform a quantitative motor assessment directly in a patient’s home, a researcher without access to expensive motion capture equipment could analyze movement kinematics using a smartphone video, and a coach could evaluate player performance with video recordings directly from the field. In this review, we combine expertise and perspectives from physical therapy, speech-language pathology, movement science, and engineering to provide insight into applications of pose estimation in human health and performance. We focus specifically on applications in areas of human development, performance optimization, injury prevention, and motor assessment of persons with neurologic damage or disease. We review relevant literature, share interdisciplinary viewpoints on future applications of these technologies to improve human health and performance, and discuss perceived limitations.

Chordomas are malignant neoplasms that typically arise in the axial spine and primarily affect adults. When chordomas arise in pediatric patients they are more likely to display unusual histological features and aggressive behavior. We noted the absence of SMARCB1/INI1 expression by immunohistochemistry in an index case of poorly differentiated chordoma of the sacrum, leading us to further examine SMARCB1/INI1 expression as well as that of brachyury, a highly specific marker of notochordal differentiation, in 3 additional poorly differentiated chordomas of the clivus, 10 typical chordomas, and 8 atypical teratoid/rhabdoid tumors (AT/RTs). All 4 poorly differentiated chordomas and all AT/RTs lacked nuclear expression of SMARCB1/INI1, while the 10 typical chordomas maintained strong nuclear SMARCB1/INI1 immunoreactivity. All 10 typical and 4 poorly differentiated chordomas expressed brachyury; all 8 AT/RTs were brachyury immunonegative. Cytogenetic evaluation utilizing FISH probes near the SMARCB1/INI1 locus on chromosome 22q was also performed in all of the poorly differentiated chordomas in this series. Three of the four poorly differentiated chordomas had evidence for deletion of this region by FISH. Analysis of the SMARCB1/INI1 gene sequence was performed using formalin-fixed paraffin-embedded tissue in all cases and no point mutations were observed. In summary, all poorly differentiated chordomas in this series showed the absence of SMARCB1/INI1 expression, and were reliably distinguished from AT/RTs, clinically by their characteristic primary sites of origin and pathologically by strong nuclear brachyury expression. Our findings reveal a likely role for SMARCB1/INI1 in a subset of chordomas with aggressive features.

A number of patient-reported outcomes (PROs) predict increased mortality after primary cancer treatment. Studies, though, are sometimes affected by methodological limitations. They often use control variables that poorly predict life expectancy, examine only one or two PROs thus not controlling potential confounding by unmeasured PROs, and observe PROs at only a single point in time. To predict all-cause mortality, this study used control variables affording good estimates of life expectancy, conducted multivariate analyses of multiple PROs to identify independent predictors, and monitored PROs two years after diagnosis. We recruited a consecutive sample of 824 patients with uveal melanoma between April 2008 and December 2014. PROs were variables shown to predict mortality in previous studies; anxiety, depression, visual and ocular symptoms, visual function impairment, worry about cancer recurrence, and physical, emotional, social and functional quality of life (QoL), measured 6, 12 and 24 months after diagnosis. We conducted Cox regression analyses with a census date of December 2018. Covariates were age, gender, marital and employment status, self-reported co-morbidities, tumor diameter and thickness, treatment modality and chromosome 3 mutation status, the latter a genetic mutation strongly associated with mortality. Single predictor analyses (with covariates), showed 6-month depression and poorer functional QoL predicting mortality, as did 6–12 month increases in anxiety and 6–12 month decreases in physical and functional QoL. Multivariate analyses using all PROs showed independent prediction by 6-month depression and decreasing QoL over 6–12 months and 12–24 months. Elevated depression scores six months post-diagnosis constituted an increased mortality risk. Early intervention for depressive symptoms may reduce mortality.

Ectopic expression of transcription factors can reprogram somatic cells to a pluripotent state. However, most of the studies used skin fibroblasts as the starting population for reprogramming, which usually take weeks for expansion from a single biopsy. We show here that induced pluripotent stem (iPS) cells can be generated from adult human adipose stem cells (hASCs) freshly isolated from patients. Furthermore, iPS cells can be readily derived from adult hASCs in a feeder-free condition, thereby eliminating potential variability caused by using feeder cells. hASCs can be safely and readily isolated from adult humans in large quantities without extended time for expansion, are easy to maintain in culture, and therefore represent an ideal autologous source of cells for generating individual-specific iPS cells.