Characterization of a reproducible model of fracture healing in mice using an open femoral osteotomy

Purpose: The classic fracture model, described by Bonnarens and Einhorn in 1984, enlists a blunt guillotine to generate a closed fracture in a pre-stabilized rodent femur. However, in less experienced hands, this technique yields considerable variability in fracture pattern and requires highly-specialized equipment. This study describes a reproducible and low-cost model of mouse fracture healing using an open femoral osteotomy. Methods: Femur fractures were produced in skeletally mature male and female mice using an open femoral osteotomy after intramedullary stabilization. Mice were recovered for up to 28 days prior to analysis with microradiographs, histomorphometry, a novel μCT methodology, and biomechanical torsion testing at weekly intervals. Results: Eight mice were excluded due to complications (8/193, 4.1%), including unacceptable fracture pattern (2/193, 1.0%). Microradiographs showed progression of the fracture site to mineralized callus by 14 days and remodelling 28 days after surgery. Histomorphometry from 14 to 28 days revealed decreased cartilage area and maintained bone area. μCT analysis demonstrated a reduction in mineral surface from 14 to 28 days, stable mineral volume, decreased strut number, and increased strut thickness. Torsion testing at 21 days showed that fractured femurs had 61% of the ultimate torque, 63% of the stiffness, and similar twist to failure when compared to unfractured contralateral femurs. Conclusions: The fracture model described herein, an open femoral osteotomy, demonstrated healing comparable to that reported using closed techniques. This simple model could be used in future research with improved reliability and reduced costs compared to the current options

A cell cycle model for somitogenesis: mathematical formulation and numerical simulation

After many years of research, the mechanisms that generate a periodic pattern of repeated elements (somites) along the length of the embryonic body axis is still one of the major unresolved problems in developmental biology. Here we present a mathematical formulation of the cell cycle model for somitogenesis proposed in Development105 (1989), 119–130. Somite precursor cells in the node are asynchronous, and therefore, as a population, generate continuously pre-somite cells which enter the segmental plate. The model makes the hypothesis that there exists a time window within the cell cycle, making up one-seventh of the cycle, which gates the pre-somite cells so that they make somites discretely, seven per cycle. We show that the model can indeed account for the spatiotemporal patterning of somite formation during normal development as well as the periodic abnormalities produced by heat shock treatment. We also relate the model to recent molecular data on the process of somite formation

Parting with illusions in evolutionary ethics

I offer a critical analysis of a view that has become a dominant aspect of recent thought on the relationship between evolution and morality, and propose an alternative. An ingredient in Michael Ruse's 'error theory' (Ruse 1995) is that belief in moral (prescriptive, universal, and nonsubjective) guidelines arose in humans because such belief results in the performance of adaptive cooperative behaviors. This statement relies on two particular connections: between ostensible and intentional types of altruism, and between intentional altruism and morality. The latter connection is problematic because it makes morality redundant, its role having already been fulfilled by the psychological dispositions that constitute intentional altruism. Both behavioral ecology and moral psychology support this criticism, and neither human behavioral flexibility nor the self-regard / other-regard distinction can provide a defense of the error theory. I conclude that morality did not evolve to curb rampant selfishness; instead, the evolutionarily recent 'universal law' aspect of morality may function to update behavioral strategies which were adaptive in the paleolithic environment of our ancestors (to which our psychological dispositions are best adapted), by means of norms more appropriate to our novel social environment.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42482/1/10539_2004_Article_5102509.pd

Genome-Wide Association Study in BRCA1 Mutation Carriers Identifies Novel Loci Associated with Breast and Ovarian Cancer Risk

BRCA1-associated breast and ovarian cancer risks can be modified by common genetic variants. To identify further cancer risk-modifying loci, we performed a multi-stage GWAS of 11,705 BRCA1 carriers (of whom 5,920 were diagnosed with breast and 1,839 were diagnosed with ovarian cancer), with a further replication in an additional sample of 2,646 BRCA1 carriers. We identified a novel breast cancer risk modifier locus at 1q32 for BRCA1 carriers (rs2290854, P = 2.7×10-8, HR = 1.14, 95% CI: 1.09-1.20). In addition, we identified two novel ovarian cancer risk modifier loci: 17q21.31 (rs17631303, P = 1.4×10-8, HR = 1.27, 95% CI: 1.17-1.38) and 4q32.3 (rs4691139, P = 3.4×10-8, HR = 1.20, 95% CI: 1.17-1.38). The 4q32.3 locus was not associated with ovarian cancer risk in the general population or BRCA2 carriers, suggesting a BRCA1-specific associat

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease