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Nonlinear optical imaging modalities, such as stimulated Raman scattering (SRS) microscopy, use pulsed-laser excitation with high peak intensity that can perturb the native state of cells. In this study, we used bulk RNA sequencing, quantitative measurement of cell proliferation, and fluorescent measurement of the generation of reactive oxygen species to assess phototoxic effects of near-IR pulsed laser radiation, at different time scales, for laser excitation settings relevant to SRS imaging. We define a range of laser excitation settings for which there was no significant change in mouse Neuro2A cells after laser exposure. This study provides guidance for imaging parameters that minimize photo-induced perturbations in SRS microscopy to ensure accurate interpretation of experiments with time-lapse imaging or with paired measurements of imaging and sequencing on the same cells.

 

Tissue development and disease lead to changes in cellular organization, nuclear morphology, and gene expression, which can be jointly measured by spatial transcriptomic technologies. However, methods for jointly analyzing the different spatial data modalities in 3D are still lacking. We present a computational framework to integrate Spatial Transcriptomic data using over-parameterized graph-based Autoencoders with Chromatin Imaging data (STACI) to identify molecular and functional alterations in tissues. STACI incorporates multiple modalities in a single representation for downstream tasks, enables the prediction of spatial transcriptomic data from nuclear images in unseen tissue sections, and provides built-in batch correction of gene expression and tissue morphology through over-parameterization. We apply STACI to analyze the spatio-temporal progression of Alzheimer’s disease and identify the associated nuclear morphometric and coupled gene expression features. Collectively, we demonstrate the importance of characterizing disease progression by integrating multiple data modalities and its potential for the discovery of disease biomarkers.

 

Conventionally, DNN models are trained once in the cloud and deployed in edge devices such as cars, robots, or unmanned aerial vehicles (UAVs) for real-time inference. However, there are many cases that require the models to adapt to new environments, domains, or users. In order to realize such domain adaption or personalization, the models on devices need to be continuously trained on the device. In this work, we design EF-Train, an efficient DNN training accelerator with a unified channel-level parallelism-based convolution kernel that can achieve end-to-end training on resource-limited low-power edge-level FPGAs. It is challenging to implement on-device training on resource-limited FPGAs due to the low efficiency caused by different memory access patterns among forward and backward propagation and weight update. Therefore, we developed a data reshaping approach with intra-tile continuous memory allocation and weight reuse. An analytical model is established to automatically schedule computation and memory resources to achieve high energy efficiency on edge FPGAs. The experimental results show that our design achieves 46.99 GFLOPS and 6.09 GFLOPS/W in terms of throughput and energy efficiency, respectively. 

Chloroplast genomes have been widely used in studying plant phylogeny and evolution. Several chloroplast genome visualization tools have been developed to display the distribution of genes on the genome. However, these tools do not draw features, such as exons, introns, repetitive elements, and variable sites, disallowing in‐depth examination of the genome structures. Here, we developed and validated a software package called Chloroplast Genome Viewers (CPGView). CPGView can draw three maps showing (i) the distributions of genes, variable sites, and repetitive sequences, including microsatellites, tandem and dispersed repeats; (ii) the structure of the cis‐splicing genes after adjusting the exon‐intron boundary positions using a coordinate scaling algorithm, and (iii) the structure of the trans‐splicing generps12. To test the accuracy of CPGView, we sequenced, assembled, and annotated 31 chloroplast genomes from 31 genera of 22 families. CPGView drew maps correctly for all the 31 chloroplast genomes. Lastly, we used CPGView to examine 5998 publicly released chloroplast genomes from 2513 genera of 553 families. CPGView succeeded in plotting maps for 5882 but failed to plot maps for 116 chloroplast genomes. Further examination showed that the annotations of these 116 genomes had various errors needing manual correction. The test on newly generated data and publicly available data demonstrated the ability of CPGView to identify errors in the annotations of chloroplast genomes. CPGView will become a widely used tool to study the detailed structure of chloroplast genomes. The web version of CPGView can be accessed fromhttp://www.1kmpg.cn/cpgview.

 

Aquaporins are water channel proteins in cell membrane, highly specific for water molecules while restricting the passage of contaminants and small molecules, such as urea and boric acid. Cysteine functional groups were installed on aquaporin Z for covalent attachment to the polymer membrane matrix so that the proteins could be immobilized to the membranes and aligned in the direction of the flow. Depth profiling using x-ray photoelectron spectrometer (XPS) analysis showed the presence of functional groups corresponding to aquaporin Z modified with cysteine (Aqp-SH). Aqp-SH modified membranes showed a higher salt rejection as compared to unmodified membranes. For 2 M NaCl and CaCl2 solutions, the rejection obtained from Aqp-SH membranes was 49.3 ± 7.5% and 59.1 ± 5.1%. On the other hand, the rejections obtained for 2 M NaCl and CaCl2 solutions from unmodified membranes were 0.8 ± 0.4% and 1.3 ± 0.2% respectively. Furthermore, Aqp-SH membranes did not show a significant decrease in salt rejection with increasing feed concentrations, as was observed with other membranes. Through simulation studies, it was determined that there was approximately 24% capping of membrane pores by dispersed aquaporins.