Morphometric variation in nearly unstudied populations of the most studied mammal: The non-commensal house mouse (Mus musculus domesticus) in the Near East and Northern Africa

The phenotypic consequences in the house mouse (Mus musculus domesticus) of the transition from an ordinary field-dwelling rodent to a species that is dependent on human populations was studied by investigating the morphometric variation of non-commensal populations of M. m. domesticus from Syria, Jordan, SW Iran, and Libya and comparing them with that of conspecific commensal populations from Eastern Turkey, Greece, and Bulgaria. Commensal populations of M. musculus musculus from the Czech Republic were used as an outgroup. About 849 adult specimens of M. musculus were analysed by multivariate procedures based on standard molar, skull and body measurements. As expected, there was considerable variation among the studied populations and a good correspondence between morphometric and geographic distances. The resulting morphometric tree was consistent with the hypothesis that the original radiation of M. m. domesticus took place somewhere in the Near East. Commensal populations of M. m. domesticus form a single derived branch. Specimens originating from four different sites in eastern Syria showed the greatest similarity to one another and possessed relatively bigger molars than the other studied populations. Commensal populations were characterised by longer tails when compared to non-commensal populations, which suggests an adaptation for living in a more three-dimensionally heterogeneous environment for commensal populations.     

Velocity of Lordosis Angle during Spinal Flexion and Extension

The importance of functional parameters for evaluating the severity of low back pain is gaining clinical recognition, with evidence suggesting that the angular velocity of lordosis is critical for identification of musculoskeletal deficits. However, there is a lack of data regarding the range of functional kinematics (RoKs), particularly which include the changing shape and curvature of the spine. We address this deficit by characterising the angular velocity of lordosis throughout the thoracolumbar spine according to age and gender. The velocity of lumbar back shape changes was measured using Epionics SPINE during maximum flexion and extension activities in 429 asymptomatic volunteers. The difference between maximum positive and negative velocities represented the RoKs. The mean RoKs for flexion decreased with age; 114°/s (20–35 years), 100°/s (36–50 years) and 83°/s (51–75 years). For extension, the corresponding mean RoKs were 73°/s, 57°/s and 47°/s. ANCOVA analyses revealed that age and gender had the largest influence on the RoKs (p<0.05). The Epionics SPINE system allows the rapid assessment of functional kinematics in the lumbar spine. The results of this study now serve as normative data for comparison to patients with spinal pathology or after surgical treatment.     

Drug2ways: Reasoning over causal paths in biological networks for drug discovery

Elucidating the causal mechanisms responsible for disease can reveal potential therapeutic targets for pharmacological intervention and, accordingly, guide drug repositioning and discovery. In essence, the topology of a network can reveal the impact a drug candidate may have on a given biological state, leading the way for enhanced disease characterization and the design of advanced therapies. Network-based approaches, in particular, are highly suited for these purposes as they hold the capacity to identify the molecular mechanisms underlying disease. Here, we present drug2ways, a novel methodology that leverages multimodal causal networks for predicting drug candidates. Drug2ways implements an efficient algorithm which reasons over causal paths in large-scale biological networks to propose drug candidates for a given disease. We validate our approach using clinical trial information and demonstrate how drug2ways can be used for multiple applications to identify: i) single-target drug candidates, ii) candidates with polypharmacological properties that can optimize multiple targets, and iii) candidates for combination therapy. Finally, we make drug2ways available to the scientific community as a Python package that enables conducting these applications on multiple standard network formats.