Three dimensional models can be a valuable tool for surgeons as they develop surgical plans and medical fellows as they learn about complex cases. In particular, 3D models can play an important role in the field of cardiology, where complex congenital heart diseases occur. While many 3D printers can provide anatomically correct and detailed models, existing 3D printing materials fail to replicate myocardial tissue properties and can be extremely costly. This protocol aims to develop a process for the creation of patient-specific models of complex congenital heart defects using a low-cost silicone that more closely matches cardiac muscle properties. With improved model fidelity, actual surgical procedural training could occur in advance of the procedure. Successful creation of cardiac models begins with the segmentation of radiologic images to generate a virtual blood pool (blood that fills the chambers of the heart) and myocardial tissue mold. The blood pool and myocardial mold are 3D printed in acrylonitrile butadiene styrene (ABS), a plastic dissolvable in acetone. The mold is assembled around the blood pool, creating a negative space simulating the myocardium. Silicone with a shore hardness of 2A is poured into the negative space and allowed to cure. The myocardial mold is removed, and the remaining silicone/blood pool model is submerged in acetone. The described process results in a physical model in which all cardiac features, including intra-cardiac defects, are represented with more realistic tissue properties and are more closely approximated than a direct 3D printing approach. The successful surgical correction of a model with a ventricular septal defect (VSD) using a GORE-TEX patch (standard surgical intervention for defect) demonstrates the utility of the method.

Teeth are of key importance in life not only for food mastication and speech but also for psychological well-being. Knowledge on human tooth development and biology is scarce. In particular, not much is known about the tooth's epithelial stem cells and their function. We succeeded in developing a novel organoid model starting from human tooth tissue (i.e., dental follicle, isolated from extracted wisdom teeth). The organoids are robustly and long-term expandable and recapitulate the proposed human tooth epithelial stem cell compartment in terms of marker expression as well as functional activity. In particular, the organoids are capable to unfold an ameloblast differentiation process as occurring in vivo during amelogenesis. This unique organoid model will provide a powerful tool to study not only human tooth development but also dental pathology, and may pave the way toward tooth-regenerative therapy. Replacing lost teeth with a biological tooth based on this new organoid model could be an appealing alternative to the current standard implantation of synthetic materials.

Tortricidae (Lepidoptera), commonly known as tortrix or leafroller moths, comprises many agricultural and forestry pests, which cause serious agricultural losses. To understand the biology of such pest moths, fundamental techniques have been in high demand. Here, methods for mass-rearing, observations, and molecular studies are developed using two tea tortrix, Homona magnanima and Adoxophyes honmai (Lepidoptera: Tortricidae). Insects were mass-reared with sliced artificial diet and maintained by inbreeding for over 100 generations by considering their biological characteristics. Insects have various sex dimorphisms; hence it is difficult to distinguish the sex during the developing stages, which have prevented subsequent assays. The present work highlighted that the sex of tortricids larvae could be determined by observing testes or lactic-acetic orcein staining to visualize the female-specific W chromosome. Moreover, using the sex determination methods, the present study enabled nucleic acid extractions from sex determined embryos and application toward high throughput sequencing. These tips are applicable for other pest insects and will facilitate further morphological and genetic studies.

There is a need for practical assays to visualize and quantify the cells' extracellular vesicle (EV) uptake. EV uptake plays a role in intercellular communication in various research fields; cancer biology, neuroscience, and drug delivery. Many EV uptake assays have been reported in the literature; however, there is a lack of practical, detailed experimental methodology. EV uptake can be assessed by fluorescently labeling EVs to detect their location within cells. Distinguishing between internalized EVs in cells and the superficial EVs on cells is difficult, yet critical, to accurately determine the EV uptake. Therefore, an assay that efficiently quantifies EV uptake through three-dimensional (3D) fluorescence confocal microscopy is proposed in this work. Fluorescently labeled EVs were prepared using a nano-filtration-based microfluidic device, visualized by 3D confocal microscopy, and then analyzed through advanced image-processing software. The protocol provides a robust methodology for analyzing EVs on a cellular level and a practical approach for efficient analysis.

Adipose-derived stromal/stem cells (ASCs) are a subpopulation of cells found in the stromal vascular fraction of human subcutaneous adipose tissue recognized as a classical source of mesenchymal stromal/stem cells. Many studies have been published with ASCs for scaffold-based tissue engineering approaches, which mainly explored the behavior of these cells after their seeding on bioactive scaffolds. However, scaffold-free approaches are emerging to engineer tissues in vitro and in vivo, mainly by using spheroids, to overcome the limitations of scaffold-based approaches. Spheroids are 3D microtissues formed by the self-assembly process. They can better mimic the architecture and microenvironment of native tissues, mainly due to the magnification of cell-to-cell and cell-to-extracellular matrix interactions. Recently, spheroids are mainly being explored as disease models, drug screening studies, and building blocks for 3D bioprinting. However, for 3D bioprinting approaches, numerous spheroids, homogeneous in size and shape, are necessary to biofabricate complex tissue and organ models. In addition, when spheroids are produced automatically, there is little chance for microbiological contamination, increasing the reproducibility of the method. The large-scale production of spheroids is considered the first mandatory step for developing a biofabrication line, which continues in the 3D bioprinting process and finishes in the full maturation of the tissue construct in bioreactors. However, the number of studies that explored the large-scale ASC spheroid production are still scarce, together with the number of studies that used ASC spheroids as building blocks for 3D bioprinting. Therefore, this article aims to show the large-scale production of ASC spheroids using a non-adhesive micromolded hydrogel technique spreading ASC spheroids as building blocks for 3D bioprinting approaches.

Phenolic acids are a class of organic compounds that bear both a phenolic group, and a carboxylic group. They are found in grains and concentrate in the bran of cereals or seed coat of legumes. They possess antioxidant properties that have generated much research interest in recent years, about their potential antioxidant protective health functions. This work presents a generalized method for the extraction of free soluble phenolic acids from whole grains and analysis of their antioxidant capacity. Five whole grain samples comprising two cereals (wheat and yellow corn) and three legumes (cowpea bean, kidney bean, and soybean), were used. The grains were milled into flour and their free soluble phenolic acids extracted using aqueous methanol. The compounds were then identified using a high-pressure liquid chromatograph (HPLC). The Folin-Ciocalteu method was used to determine their total phenolic content while their antioxidant capacities were determined using the DPPH radical scavenging capacity, Trolox equivalent antioxidant capacity (TEAC) and oxygen radical absorbance capacity (ORAC) assays. The phenolic acids identified included vanillic, caffeic, p-coumaric and ferulic acids. Vanillic acid was identified only in cowpea while caffeic acid was identified only in kidney bean. p-Coumaric acid was identified in yellow corn, cowpea, and soybean, while ferulic acid was identified in all the samples. Ferulic acid was the predominant phenolic acid identified. The total concentration of phenolic acids in the samples decreased in the following order: soybean > cowpea bean > yellow corn = kidney bean > wheat. The total antioxidant capacity (sum of values of DPPH, TEAC and ORAC assays) decreased as follows: soybean > kidney bean > yellow corn = cowpea bean > wheat. This study concluded that HPLC analysis as well as DPPH, TEAC, and ORAC assays provide useful information about the phenolic acid composition and antioxidant properties of whole grains.

Arthrocentesis of the knee is a procedure in which a needle is inserted into the knee joint, and synovial fluid is aspirated. An arthrocentesis can be diagnostic or therapeutic. Synovial fluid may be removed for testing to determine the nature of the knee effusion. If septic arthritis is suspected, urgent arthrocentesis before initiation of antibiotic treatment is indicated. Moreover, arthrocentesis can also aid in diagnosing crystal-induced arthritis such as gout or pseudogout, or non-inflammatory arthritis such as osteoarthritis. Identifying the cause of the knee effusion can guide treatment. Furthermore, removing fluid from a knee can reduce intraarticular pressure to decrease pain and improve range of motion. There is no absolute contraindication to performing this procedure, but in selecting the needle entry site, an area of skin that is infected should be avoided. Therefore, caution should be exercised when a patient presents with suspected cellulitis over the knee joint to avoid the potential risk of causing iatrogenic septic arthritis. A knee that has undergone arthroplasty should be assessed for arthrocentesis by an orthopedic surgeon. Arthrocentesis of the knee is typically performed with the patient supine. The site for needle insertion is marked, and then the skin is disinfected. After a local anesthetic is administered, a needle is inserted along the pathway that was anesthetized. Synovial fluid is aspirated, and then the needle is withdrawn. Pressure is applied until any bleeding stops. The synovial fluid can be analyzed for infection and inflammation but cannot directly confirm a diagnosis of internal derangement or autoimmune causes of arthritis. In addition to the history and physical examination, laboratory findings and imaging can clarify the etiology of a knee effusion.

Cells can crawl, self-heal, and tune their stiffness due to their remarkably dynamic cytoskeleton. As such, reconstituting networks of cytoskeletal biopolymers may lead to a host of active and adaptable materials. However, engineering such materials with precisely tuned properties requires measuring how the dynamics depend on the network composition and synthesis methods. Quantifying such dynamics is challenged by variations across the time, space, and formulation space of composite networks. The protocol here describes how the Fourier analysis technique, differential dynamic microscopy (DDM), can quantify the dynamics of biopolymer networks and is particularly well suited for studies of cytoskeleton networks. DDM works on time sequences of images acquired using a range of microscopy modalities, including laser-scanning confocal, widefield fluorescence, and brightfield imaging. From such image sequences, one can extract characteristic decorrelation times of density fluctuations across a span of wave vectors. A user-friendly, open-source Python package to perform DDM analysis is also developed. With this package, one can measure the dynamics of labeled cytoskeleton components or of embedded tracer particles, as demonstrated here with data of intermediate filament (vimentin) networks and active actin-microtubule networks. Users with no prior programming or image processing experience will be able to perform DDM using this software package and associated documentation.

The ability to determine the binding affinity of lipids to proteins is an essential part of understanding protein-lipid interactions in membrane trafficking, signal transduction and cytoskeletal remodeling. Classic tools for measuring such interactions include surface plasmon resonance (SPR) and isothermal titration calorimetry (ITC). While powerful tools, these approaches have setbacks. ITC requires large amounts of purified protein as well as lipids, which can be costly and difficult to produce. Furthermore, ITC as well as SPR are very time consuming, which could add significantly to the cost of performing these experiments. One way to bypass these restrictions is to use the relatively new technique of microscale thermophoresis (MST). MST is fast and cost effective using small amounts of sample to obtain a saturation curve for a given binding event. There currently are two types of MST systems available. One type of MST requires labeling with a fluorophore in the blue or red spectrum. The second system relies on the intrinsic fluorescence of aromatic amino acids in the UV range. Both systems detect the movement of molecules in response to localized induction of heat from an infrared laser. Each approach has its advantages and disadvantages. Label-free MST can use untagged native proteins; however, many analytes, including pharmaceuticals, fluoresce in the UV range, which can interfere with determination of accurate KD values. In comparison, labeled MST allows for a greater diversity of measurable pairwise interactions utilizing fluorescently labeled probes attached to ligands with measurable absorbances in the visible range as opposed to UV, limiting the potential for interfering signals from analytes.

The emergence of the recent SARS-CoV-2 global health crisis introduced key challenges for epidemiological research and clinical testing. Characterized by a high rate of transmission and low mortality, the COVID-19 pandemic necessitated accurate and efficient diagnostic testing, particularly in closed populations such as residential universities. Initial availability of nucleic acid testing, like nasopharyngeal swabs, was limited due to supply chain pressure which also delayed reporting of test results. Saliva-based reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) testing has shown to be comparable in sensitivity and specificity to other testing methods, and saliva collection is less physically invasive to participants. Consequently, we developed a multiplex RT-qPCR diagnostic assay for population surveillance of Clemson University and the surrounding community. The assay utilized open-source liquid handling robots and thermocyclers instead of complex clinical automation systems to optimize workflow and system flexibility. Automation of saliva-based RT-qPCR enables rapid and accurate detection of a wide range of viral RNA concentrations for both large- and small-scale testing demands. The average turnaround for the automated system was < 9 h for 95% of samples and < 24 h for 99% of samples. The cost for a single test was $2.80 when all reagents were purchased in bulk quantities.