Understanding large scale sequencing datasets through changes to protein folding

The expansion of high-quality, low-cost sequencing has created an enormous opportunity to understand how genetic variants alter cellular behaviour in disease. The high diversity of mutations observed has however drawn a spotlight onto the need for predictive modelling of mutational effects on phenotype from variants of uncertain significance. This is particularly important in the clinic due to the potential value in guiding clinical diagnosis and patient treatment. Recent computational modelling has highlighted the importance of mutation induced protein misfolding as a common mechanism for loss of protein or domain function, aided by developments in methods that make large computational screens tractable. Here we review recent applications of this approach to different genes, and how they have enabled and supported subsequent studies. We further discuss developments in the approach and the role for the approach in light of increasingly high throughput experimental approaches.

Regulating bulb dormancy release and flowering in lily through chemical modulation of intercellular communication

Lily is a bulbous plant with an endogenous dormancy trait. Fine-tuning bulb dormancy release is still a challenge in the development of bulb storage technology. In this study, we identified three regulators of symplastic transport, 2,3-Butanedione oxime (BDM), N-Ethyl maleimide (NEM), and 2-Deoxy-D-glucose (DDG), that also regulate bulb dormancy release. We demonstrated that BDM and DDG inhibited callose synthesis between cells and promoted symplastic transport and soluble sugars in the shoot apical meristem (SAM), eventually accelerating bulb dormancy release and flowering in lilies. Conversely, NEM had the opposite effect. These three regulators can be flexibly applied to either accelerate or delay lily bulb dormancy release.

Quantitative comparison of data-driven gating and external hardware gating for 18F-FDG PET-MRI in patients with esophageal tumors

Background

Respiratory motion during PET imaging reduces image quality. Data-driven gating (DDG) based on principal component analysis (PCA) can be used to identify respiratory signals. The use of DDG, without need for external devices, would greatly increase the feasibility of using respiratory gating in a routine clinical setting. The objective of this study was to evaluate data-driven gating in relation to external hardware gating and regular static image acquisition on PET-MRI data with respect to SUV_max and lesion volumes.

Methods

Sixteen patients with esophageal or gastroesophageal cancer (Siewert I and II) underwent a 6-min PET scan on a Signa PET-MRI system (GE Healthcare) 1.5–2 h after injection of 4 MBq/kg ¹⁸F-FDG. External hardware gating was done using a respiratory bellow device, and DDG was performed using MotionFree (GE Healthcare). The DDG raw data files and the external hardware-gating raw files were created on a Matlab-based toolbox from the whole 6-min scan LIST-file. For comparison, two 3-min static raw files were created for each patient. Images were reconstructed using TF-OSEM with resolution recovery with 2 iterations, 28 subsets, and 3-mm post filter. SUV_max and lesion volume were measured in all visible lesions, and noise level was measured in the liver. Paired t-test, linear regression, Pearson correlation, and Bland-Altman analysis were used to investigate difference, correlation, and agreement between the methods.

Results

A total number of 30 lesions were included in the study. No significant differences between DDG and external hardware-gating SUV_max or lesion volumes were found, but the noise level was significantly reduced in the DDG images. Both DDG and external hardware gating demonstrated significantly higher SUV_max (9.4% for DDG, 10.3% for external hardware gating) and smaller lesion volume (− 5.4% for DDG, − 6.6% for external gating) in comparison with non-gated static images.

Conclusions

Data-driven gating with MotionFree for PET-MRI performed similar to external device gating for esophageal lesions with respect to SUV_max and lesion volume. Both gating methods significantly increased the SUV_max and reduced the lesion volume in comparison with non-gated static acquisition. DDG resulted in reduced image noise compared to external device gating and static images.

Establishment and assessment of a novel cleaner production process of corn grain fuel ethanol

An integrated corn ethanol-methane fermentation system was proposed to solve the problem of stillage handling, where thin stillage was treated by anaerobic digestion and then reused to make mash for the following ethanol fermentation. This system was evaluated at laboratory and pilot scale. Anaerobic digestion of thin stillage ran steadily with total chemical oxygen demand removal efficiency of 98% at laboratory scale and 97% at pilot scale. Ethanol production was not influenced by recycling anaerobic digestion effluent at laboratory and pilot scale. Compared with dried distillers' grains with solubles produced in conventional process, dried distillers' grains in the proposed system exhibited higher quality because of increased protein concentration and decreased salts concentration. Energetic assessment indicated that application of this novel process enhanced the net energy balance ratio from 1.26 (conventional process) to 1.76. In conclusion, the proposed system possessed technical advantage over the conventional process for corn fuel ethanol production.