Current single-cell RNA-sequencing approaches have limitations that stem from the microfluidic devices or fluid handling steps required for sample processing. We develop a method that does not require specialized microfluidic devices, expertise or hardware. Our approach is based on particle-templated emulsification, which allows single-cell encapsulation and barcoding of cDNA in uniform droplet emulsions with only a vortexer. Particle-templated instant partition sequencing (PIP-seq) accommodates a wide range of emulsification formats, including microwell plates and large-volume conical tubes, enabling thousands of samples or millions of cells to be processed in minutes. We demonstrate that PIP-seq produces high-purity transcriptomes in mouse–human mixing studies, is compatible with multiomics measurements and can accurately characterize cell types in human breast tissue compared to a commercial microfluidic platform. Single-cell transcriptional profiling of mixed phenotype acute leukemia using PIP-seq reveals the emergence of heterogeneity within chemotherapy-resistant cell subsets that were hidden by standard immunophenotyping. PIP-seq is a simple, flexible and scalable next-generation workflow that extends single-cell sequencing to new applications.
Background: Social media platforms have changed the way medical information is disseminated. Transgender patients may utilize social media to learn about gender-affirming surgery (GAS). Although videos on social media are readily accessible, their content is not verified or peer-reviewed. Therefore, this study aimed to evaluate the quality and reliability of YouTube and TikTok videos related to GAS. Methods: YouTube and TikTok were queried for gender-affirming top surgery, metoidioplasty, phalloplasty, breast augmentation, and vaginoplasty. Quality of video content was analyzed by the DISCERN scale. Quality scores were compared among the type of GAS, account user, and content category. Results: There were 275 YouTube videos and 55 TikTok videos. Most videos focused on masculinizing top surgery (P < 0.001). Overall, videos on masculinizing GAS had higher quality and reliability than videos on feminizing GAS (P < 0.001). Chest surgery videos were of higher quality than those on genital surgery (P ≤ 0.001). Videos on masculinizing top surgery had the highest quality, whereas vaginoplasty had the lowest quality and reliability (P < 0.001). Videos produced by health care professionals and academic institutions had the greatest quality and reliability, respectively (P < 0.0001), whereas videos produced by patients were the least reliable (P < 0.0001). Conclusions: Videos on GAS ranged from poor to good quality and reliability. Health care professionals, especially plastic surgeons, should create high-quality videos on social media to educate transgender patients. There should also be greater efforts in disseminating existing high-quality videos on social media. Resources posted on social media platforms can reach a wide audience through accessible means.
Single-cell RNA sequencing is now a standard method used to reveal the molecular details of cellular heterogeneity, but current approaches have limitations on speed, scale, and ease of use that stem from the complex microfluidic devices or fluid handling steps required for sample processing. We therefore developed a method that does not require specialized microfluidic devices, expertise, or hardware. Our approach is based on pre-templated instant partitions (PIPs) that allow single cell encapsulation and barcoding of cDNA in uniform droplet emulsions with only a vortexer. PIP-seq accommodates a wide range of emulsification formats, including microwell plates and large-volume conical tubes, enabling thousands of samples or millions of cells to be processed in minutes. We demonstrate that PIP-seq produces high-purity transcriptomes in mouse-human mixing studies, is compatible with multi-omics measurements, and can accurately characterize cell types in human breast tissue when compared to a commercial microfluidic platform. Single-cell transcriptional profiling of mixed phenotype acute leukemia using PIP-seq revealed the emergence of heterogeneity within chemotherapy resistant cell subsets that was hidden by standard immunophenotyping. PIP-seq is a simple, flexible, and scalable next generation workflow that extends single-cell sequencing to new applications, including screening, diagnostics, and disease monitoring.
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