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Stem cells undergo drastic morphological alterations during differentiation. While extensive studies have been performed to examine the cytoskeletal remodeling, there is a growing interest to determine the morphological, structural and functional changes of the nucleus. The current study is therefore aimed at quantifying the extent of remodeling of the nuclear morphology of human mesenchymal stem cells during biochemically-induced adipogenic differentiation. Results show the size of nuclei decreased exponentially over time as the lipid accumulation is up-regulated. Increases in the lipid accumulation appear to lag the nuclear reorganization, suggesting the nuclear deformation is a prerequisite to adipocyte maturation. Furthermore, the lamin A/C expression was increased and redistributed to the nuclear periphery along with a subsequent increase in the nuclear aspect ratio. To further assess the role of the nucleus, a nuclear morphology with a high aspect ratio was achieved using microcontact-printed substrate. The cells with an elongated nuclear shape did not efficiently undergo adipogenesis, suggesting the cellular and nuclear processes associated with stem cell differentiation at the early stage of adipogenesis cause a change in the nuclear morphology and cannot be abrogated by the morphological cues. In addition, a novel computational biomechanical model was generated to simulate the nuclear shape change during differentiation and predict the forces acting upon the nucleus. This effort led to the development of computational scaling approach to simulate the experimentally observed adipogenic differentiation processes over 15 days in less than 1.5 hours.

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We conducted wavelet coherence analysis to quantify/image the cerebral neurovascular coupling at infra-slow frequencies during four different awake-to-sleep vigilance states using whole-head, simultaneous EEG and functional Near Infrared Spectroscopy measurements from 15 healthy human brains.

Biomolecular simulations are computationally expensive. Simulating time histories larger than seconds remain elusive even with the help of supercomputers. Biological phenomena are multiscale in nature. The dynamics range from atomistic to microscale. Herein a recently developed scaling approach, based on the method of multiple scales, is used to accomplish a long term simulation of a subcellular system. The first key advantage of this approach is the drastic reduction in computational time. This approach is illustrated using a mesenchymal stem cell as it undergoes adipogenic differentiation, a process that takes 15 days, which was simulated in less than 1.5 hours on a typical desktop computer. The second key advantage of the high-speed simulation is that it facilitates the study of mechanical properties, such as nucleus membrane stiffness, that are difficult to measure experimentally with certainty.