Ultrahigh-throughput generation and characterization of cellular aggregates in laser-ablated microwells of poly(dimethylsiloxane)

Aggregates of cells, also known as multicellular aggregates (MCAs), have been used as microscale tissues in the fields of cancer biology, regenerative medicine, and developmental biology for many decades. However, small MCAs (fewer than 100 cells per aggregate) have remained challenging to manufacture in large quantities at high uniformity. Forced aggregation into microwells offers a promising solution for forming consistent aggregates, but commercial sources of microwells are expensive, complicated to manufacture, or lack the surface packing densities that would significantly improve MCA production. To address these concerns, we custom-modified a commercial laser cutter to provide complete control over laser ablation and directly generate microwells in a poly(dimethylsiloxane) (PDMS) substrate. We achieved ultra rapid microwell production speeds (>50000 microwells per h) at high areal packing densities (1800 microwells per cm2) and over large surface areas for cell culture (60 cm2). Variation of the PDMS substrate distance from the laser focal plane during ablation allowed for the generation of microwells with a variety of sizes, contours, and aspect ratios. Casting of high-fidelity microneedle masters in polyurethane allowed for non-ablative microwell reproduction through replica molding. MCAs of human bone marrow derived mesenchymal stem cells (hMSCs), murine 344SQ metastatic adenocarcinoma cells, and human C4-2 prostate cancer cells were generated in our system with high uniformity within 24 hours, and computer vision software aided in the ultra-high-throughput analysis of harvested aggregates. Moreover, MCAs maintained invasive capabilities in 3D migration assays. In particular, 344SQ MCAs demonstrated epithelial lumen formation on Matrigel, and underwent EMT and invasion in the presence of TGF-β. We expect this technique to find broad utility in the generation and cultivation of cancer cell aggregates, primary cell aggregates, and embryoid bodies

COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study

Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≤ 18 years: 69, 48, 23; 85%), older adults (≥ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P < 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men

Open-Source Selective Laser Sintering (OpenSLS) of Nylon and Biocompatible Polycaprolactone

Selective Laser Sintering (SLS) is an additive manufacturing process that uses a laser to fuse powdered starting materials into solid 3D structures. Despite the potential for fabrication of complex, high-resolution structures with SLS using diverse starting materials (including biomaterials), prohibitive costs of commercial SLS systems have hindered the wide adoption of this technology in the scientific community. Here, we developed a low-cost, open-source SLS system (OpenSLS) and demonstrated its capacity to fabricate structures in nylon with sub-millimeter features and overhanging regions. Subsequently, we demonstrated fabrication of polycaprolactone (PCL) into macroporous structures such as a diamond lattice. Widespread interest in using PCL for bone tissue engineering suggests that PCL lattices are relevant model scaffold geometries for engineering bone. SLS of materials with large powder grain size (~500 μm) leads to part surfaces with high roughness, so we further introduced a simple vapor-smoothing technique to reduce the surface roughness of sintered PCL structures which further improves their elastic modulus and yield stress. Vapor-smoothed PCL can also be used for sacrificial templating of perfusable fluidic networks within orthogonal materials such as poly(dimethylsiloxane) silicone. Finally, we demonstrated that human mesenchymal stem cells were able to adhere, survive, and differentiate down an osteogenic lineage on sintered and smoothed PCL surfaces, suggesting that OpenSLS has the potential to produce PCL scaffolds useful for cell studies. OpenSLS provides the scientific community with an accessible platform for the study of laser sintering and the fabrication of complex geometries in diverse materials

Custom Open-source Selective Laser Sintering (OpenSLS) hardware.

<p>a) A simplified depiction of the SLS process illustrates the sintering of powdered materials into 3D parts using a laser. For each new layer, the powder reservoir piston moves up to expose a layer of fresh powder while the build platform lowers within the build volume to leave space for the new powder layer at the top. The distributor pushes the exposed powder from the reservoir to the top of the build area so that the laser can pattern the next layer. b) A schematic rendering of our custom powder handling module. All of the red parts are 3D printed; full designs for these and the laser-cut acrylic walls may be found on the OpenSLS github repository. With the exception of the blue-green wall in the background, the exterior acrylic walls (as well as the exit ducts for excess powder) have been omitted for clarity. c) A photograph of the assembled powder module that was used throughout this study shows the components highlighted in the schematic (b) as well as the remaining acrylic walls and ducting for excess powder. The powder module was readily integrated into a commercial laser cutter with the indicated mounting brackets. d) After mounting the powder module in the laser cutter, we successfully implemented selective laser sintering and fabricated structures such as the illustrated gear. The gear is shown just after sintering and powder removal as well as after cleaning with compressed air (inset).</p

Fluidic networks templated by sacrificial PCL structures.

<p>a) Schematic for a workflow which begins with a sintered PCL structure and yields the corresponding fluidic network as void space in a PDMS slab. The original PCL structure is vapor smoothed before encapsulation in a block of PDMS. The smoothed PCL is dissolved out of the cured PDMS using DCM, leaving a fluidic network that retains the architecture of the original structure. b) The workflow schematized in (a) is demonstrated with a simple ladder geometry. The inlet and outlet allow perfusion and continuous flow through the network. c-e) Sacrificial templating of the reduced diamond lattice model (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0147399#pone.0147399.g003" target="_blank">Fig 3</a>) resulted in the formation of a complex, interconnected fluidic network in PDMS. Perfusion with blue dye (d, scale bar = 1 cm) highlights the interconnectivity of the void space and a virtual cross-section through a μCT scan (e) demonstrates fluidic channels retaining the original structure’s geometry (artifacts are present due to bubbles trapped in PDMS).</p

Survival and osteogenic differentiation of hMSCs on PCL fabricated via OpenSLS.

<p>a,b) Live and dead channels for live/dead staining of hMSCs on vapor-smoothed PCL platforms show a majority live cells and a generally homogeneous distribution of dead cells among live cells. Gamma correction was used to improve visualization of cells. c) Quantification of live and dead hMSCs from three separate PCL platforms showed that 84 ± 7% of adhered cells were alive. d) Gross images of sintered PCL after 32 days show intense staining on platforms seeded with hMSCs incubated in osteogenic media (osteogenic platforms), indicating the presence of calcium deposits characteristic of early osteoblasts. e) Quantification of alizarin red absorbance shows a nearly 15-fold increase in staining on osteogenic platforms compared to those cultured in growth media. f,g) The same intense staining of osteogenic PCL platforms was observed when the PCL was vapor smoothed prior to seeding of hMSCs. Scale bars = 1 cm. * denotes p < 0.01 using Student’s T-test. Plots represent mean ± SD.</p

Build times for 3D models using OpenSLS.

<p>Cube, Cube Dimensional Accuracy Model (1.04 cm³); ASTM Cylinder, ASTM Cylinder with Macropores (0.54 cm³, see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0147399#pone.0147399.s005" target="_blank">S3 Fig</a>); Diamond, Diamond Lattice (0.90 cm³, see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0147399#pone.0147399.g002" target="_blank">Fig 2</a>); Reduced Diamond, Reduced Diamond Lattice Model (0.21 cm³, see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0147399#pone.0147399.g003" target="_blank">Fig 3</a>).</p

Dimensional Accuracy and Precision of OpenSLS.

<p>Note: Measurements are reported as mean ± SD</p