Collagen Dysregulation in the Dermis of the Sagg/+ Mouse: A Loose Skin Model

The Sagg/+ mouse is an ethylnitrosourea-derived mutant with a dermal phenotype similar to some of the subtypes of Ehlers-Danlos syndrome (EDS) and cutis laxa. The dermis of the Sagg/+ mouse has less dense and more disorganized collagen fibers compared to controls. The size of extracted Type I dermal collagen was the same as that observed in normal skin; however, more collagen could be extracted from Sagg/ + skin, which also showed decreased collagen content and decreased steady-state levels of α1(I), α2(I), α1(V), and α2(V) procollagen mRNAs. The biomechanical properties of Sagg/+ skin were significantly decreased relative to normal skin. However, there were no significant differences in the quantities of the major collagen cross-links, that is, dehydrohydroxylysinonorleucine and dehydrohistidinohydroxymerodesmosine between Sagg/+ and normal skin. Electron microscopic evaluation of Sagg/+ skin indicated that the mutation interferes with the proper formation of collagen fibrils and the data are consistent with a mutation in Type V collagen leading to haploinsufficiency with the formation of two sub-populations of collagen fibrils, one normal and one with irregular shape and a larger diameter. Further study of this novel mutation will allow the identification of new mechanisms involved in the regulation of normal and pathologic collagen gene expression

Causal role of thalamic interneurons in brain state transitions: a study using a neural mass model implementing synaptic kinetics

Experimental studies on the Lateral Geniculate Nucleus (LGN) of mammals and rodents show that the inhibitory interneurons (IN) receive around 47.1% of their afferents from the retinal spiking neurons, and constitute around 20–25% of the LGN cell population. However, there is a definite gap in knowledge about the role and impact of IN on thalamocortical dynamics in both experimental and model-based research. We use a neural mass computational model of the LGN with three neural populations viz. IN, thalamocortical relay (TCR), thalamic reticular nucleus (TRN), to study the causality of IN on LGN oscillations and state-transitions. The synaptic information transmission in the model is implemented with kinetic modeling, facilitating the linking of low-level cellular attributes with high-level population dynamics. The model is parameterized and tuned to simulate alpha (8–13 Hz) rhythm that is dominant in both Local Field Potential (LFP) of LGN and electroencephalogram (EEG) of visual cortex in an awake resting state with eyes closed. The results show that: First, the response of the TRN is suppressed in the presence of IN in the circuit; disconnecting the IN from the circuit effects a dramatic change in the model output, displaying high amplitude synchronous oscillations within the alpha band in both TCR and TRN. These observations conform to experimental reports implicating the IN as the primary inhibitory modulator of LGN dynamics in a cognitive state, and that reduced cognition is achieved by suppressing the TRN response. Second, the model validates steady state visually evoked potential response in humans corresponding to periodic input stimuli; however, when the IN is disconnected from the circuit, the output power spectra do not reflect the input frequency. This agrees with experimental reports underpinning the role of IN in efficient retino-geniculate information transmission. Third, a smooth transition from alpha to theta band is observed by progressive decrease of neurotransmitter concentrations in the synaptic clefts; however, the transition is abrupt with removal of the IN circuitry in the model. The results imply a role of IN toward maintaining homeostasis in the LGN by suppressing any instability that may arise due to anomalous synaptic attributes

Modelling human choices: MADeM and decision‑making

Research supported by FAPESP 2015/50122-0 and DFG-GRTK 1740/2. RP and AR are also part of the Research, Innovation and Dissemination Center for Neuromathematics FAPESP grant (2013/07699-0). RP is supported by a FAPESP scholarship (2013/25667-8). ACR is partially supported by a CNPq fellowship (grant 306251/2014-0)