Developing a safe and effective vaccine will be the principal way of controlling the COVID-19 pandemic. However, current COVID-19 vaccination trials are not adequately representing a diverse participant population in terms of age, ethnicity and comorbidities. Achieving the representative recruitment targets that are adequately powered to the study remains one of the greatest challenges in clinical trial management. To ensure accuracy and generalisability of the safety and efficacy conclusions generated by clinical trials, it is crucial to recruit patient cohorts as representative as possible of the future target population. Missing these targets can lead to reduced validity of the study results and can often slow down drug development leading to costly delays.

One of the main drivers within the field of bottom-up synthetic biology is to develop artificial chemical machines, perhaps even living systems, that have programmable functionality. Numerous toolkits exist to generate giant unilamellar vesicle-based artificial cells. However, methods able to quantitatively measure their molecular constituents upon formation is an underdeveloped area. We report an artificial cell quality control (AC/QC) protocol using a microfluidic-based single-molecule approach, enabling the absolute quantification of encapsulated biomolecules. While the measured average encapsulation efficiency was 11.4 ± 6.8%, the AC/QC method allowed us to determine encapsulation efficiencies per vesicle, which varied significantly from 2.4 to 41%. We show that it is possible to achieve a desired concentration of biomolecule within each vesicle by commensurate compensation of its concentration in the seed emulsion. However, the variability in encapsulation efficiency suggests caution is necessary when using such vesicles as simplified biological models or standards.

Heterotrimeric G-proteins are ubiquitously expressed in several cancers, and they transduce signals from activated G-protein coupled receptors. These proteins have numerous biological functions, and they are becoming interesting target molecules in cancer therapy. Previously, we have shown that heterotrimeric G-protein subunit alphai2 (Gαi2) has an essential role in the migration and invasion of prostate cancer cells. Using a structure-based approach, we have synthesized optimized small molecule inhibitors that are able to prevent specifically the activation of the Gαi2 subunit, keeping the protein in its inactive GDP-bound state. We observed that two of the compounds (13 and 14) at 10 μΜ significantly inhibited the migratory behavior of the PC3 and DU145 prostate cancer cell lines. Additionally, compound 14 at 10 μΜ blocked the activation of Gαi2 in oxytocin-stimulated prostate cancer PC3 cells, and inhibited the migratory capability of DU145 cells overexpressing the constitutively active form of Gαi2, under basal and EGF-stimulated conditions. We also observed that the knockdown or inhibition of Gαi2 negatively regulated migration of renal and ovarian cancer cell lines. Our results suggest that small molecule inhibitors of Gαi2 have potential as leads for discovering novel anti-metastatic agents for attenuating the capability of cancer cells to spread and invade to distant sites.

Information from the retina is carried along the visual pathway with accuracy and spatial conservation as a result of topographically mapped axonal connections. The optic tectum in the midbrain is the primary region to which retinal ganglion cells project their axons in the chick. The two primary axes of the retina project independently onto the tectum using different sets of guidance cues to give rise to the retinotectal map. Specificity of the map is determined by attractive or repulsive interactions between molecular tags that are distributed in gradients in the retina and the tectum. Despite several studies, knowledge of the retinotectal guidance molecules is far from being complete. We screened for all molecules that are expressed differentially along the anterior-posterior and medial-lateral axes of the chick tectum using microarray based transcriptional profiling and identified several novel candidate retinotectal guidance molecules. Two such genes, encoding Wnt5a and Raldh2, the synthesizing enzymes for retinoic acid, were further analyzed for their function as putative regulators of retinotectal map formation. Wnt5a and retinoic acid were found to exhibit differential effects on the growth of axons from retinal explants derived from different quadrants of the retina. This screen also yielded a large number of genes expressed in a lamina-specific manner in the tectum, which may have other roles in tectal development. J. Comp. Neurol. 525:459-477, 2017. © 2016 Wiley Periodicals, Inc.

Serial section electron microscopy (ssEM), a technique where volumes of tissue can be anatomically reconstructed by imaging consecutive tissue slices, has proven to be a powerful tool for the investigation of brain anatomy. Between the process of cutting the slices, or "sections," and imaging them, however, handling 10°-106 delicate sections remains a bottleneck in ssEM, especially for batches in the "mesoscale" regime, i.e., 102-103 sections. We present a tissue section handling device that transports and positions sections, accurately and repeatability, for automated, robotic section pick-up and placement onto an imaging substrate. The device interfaces with a conventional ultramicrotomy diamond knife, accomplishing in-line, exact-constraint trapping of sections with 100-μm repeatability. An associated mathematical model includes capillary-based and Stokes-based forces, accurately describing observed behavior and fundamentally extends the modeling of water-air interface forces. Using the device, we demonstrate and describe the limits of reliable handling of hundreds of slices onto a variety of electron and light microscopy substrates without significant defects (n = 8 datasets composed of 126 serial sections in an automated fashion with an average loss rate and throughput of 0.50% and 63 s/section, respectively. In total, this work represents an automated mesoscale serial sectioning system for scalable 3D-EM connectomics.

Serial section transmission electron microscopy (ssTEM) is the most promising tool for investigating the three-dimensional anatomy of the brain with nanometer resolution. Yet as the field progresses to larger volumes of brain tissue, new methods for high-yield, low-cost, and high-throughput serial sectioning are required. Here, we introduce LASSO (Loop-based Automated Serial Sectioning Operation), in which serial sections are processed in "batches." Batches are quantized groups of individual sections that, in LASSO, are cut with a diamond knife, picked up from an attached waterboat, and placed onto microfabricated TEM substrates using rapid, accurate, and repeatable robotic tools. Additionally, we introduce mathematical models for ssTEM with respect to yield, throughput, and cost to access ssTEM scalability. To validate the method experimentally, we processed 729 serial sections of human brain tissue (~40 nm x 1 mm x 1 mm). Section yield was 727/729 (99.7%). Sections were placed accurately and repeatably (x-direction: -20 ± 110 μm (1 s.d.), y-direction: 60 ± 150 μm (1 s.d.)) with a mean cycle time of 43 s ± 12 s (1 s.d.). High-magnification (2.5 nm/px) TEM imaging was conducted to measure the image quality. We report no significant distortion, information loss, or substrate-derived artifacts in the TEM images. Quantitatively, the edge spread function across vesicle edges and image contrast were comparable, suggesting that LASSO does not negatively affect image quality. In total, LASSO compares favorably with traditional serial sectioning methods with respect to throughput, yield, and cost for large-scale experiments, and represents a flexible, scalable, and accessible technology platform to enable the next generation of neuroanatomical studies.

The type 2 iodothyronine deiodinase (D2) converts the pro-hormone thyroxine into T3 within target tissues. D2 is essential for a full thermogenic response of brown adipose tissue (BAT), and mice with a disrupted Dio2 gene (D2KO) have an impaired response to cold. BAT is also activated by overfeeding.

A key challenge towards a successful COVID-19 vaccine uptake is vaccine hesitancy. We examine and provide novel insights on the key drivers and barriers towards COVID-19 vaccine uptake.

This study aims to determine differences in the on- and off-tumor microbiota between patients with right- and left-sided colorectal cancer. Microbiome profiling of tumor and tumor-adjacent biopsies from patients with right-sided (n = 17) and left-sided (n = 7) colorectal adenocarcinoma was performed using 16S ribosomal RNA sequencing. Off-tumor alpha and beta diversity were significantly different between right- and left-sided colorectal cancer patients. However, no differences in on-tumor diversity were observed between tumor locations. Comparing the off-tumor microbiota showed the right colon to be enriched with species of the Lachnoclostridium, Selenomonas, and Ruminococcus genera. Whereas the left colon is enriched with Epsilonbacteraeota phylum, Campylobacteria class, and Pasteurellales and Campylobacterales orders, in contrast, the on-tumor microbiota showed relatively fewer differences in bacterial taxonomy between tumor sites, with left tumors being enriched with Methylophilaceae and Vadin BE97 families and Alloprevotella, Intestinibacter, Romboutsia, and Ruminococcus 2 genera. Patients with left-sided colorectal cancer had large taxonomic differences between their paired on- and off-tumor microbiota, while patients with right-sided colorectal cancer showed relatively fewer taxonomic differences. Collectively, this suggests that the right and left colon show distinctive bacterial populations; however, the presence of a colonic tumor leads to a more consistent microbiota between locations.