STAR Protocols

At-home sampling can address obstacles to participation in transcriptomics research. We previously developed the homeRNA and homeRNAmax platforms; these custom-designed tubes containing RNA stabilizer interface with a blood tube compatible with upper-arm blood collection devices, allowing for blood collection and RNA stabilization to occur from a participant's home. In this work we introduce homeRNAdrop, an insert for a commercially available blood tube (BD Microtainer) that divides the tube into two compartments: the top compartment holds 200 L blood and the bottom compartment holds ~590 L liquid stabilizer (RNAlater). By combining blood collection and RNA stabilization into the same tube, homeRNAdrop streamlines sample preparation for participants and allows for more compact sample storage for the lab. In a remote pilot study, n=25 participants from across the United States tested the homeRNAdrop kit. The n=23 samples successfully received by the lab show that samples collected using homeRNAdrop are of sufficient RNA quality (all RINs > 6, a common cutoff for analysis) and yield (mean yield=1.44 g) for downstream gene expression analysis. Almost all participants who successfully collected blood using the Tasso Mini device found the homeRNAdrop device easy to use (n=23/24). Overall, this work adds a simplified, user-friendly platform to the growing suite of tools for remote blood RNA stabilization.

Regenerating tissues like the axolotl (Ambystoma mexicanum) limb draw from many cell types, but isolating specific cell populations remains a bottleneck. Standard approaches rely on enzymatic dissociation and fluorescence-activated cell sorting (FACS), which are slow, costly, and require specialized instrumentation. We adapted INTACT (Isolation of Nuclei Tagged in specific Cell Types) to the axolotl, generating a transgenic line (INTACT-olotl) expressing Sun1-sfGFP in limb connective tissue, the population that carries limb positional information, dedifferentiates following injury, and forms the majority of the regenerative blastema. Combining an optimized nuclei isolation protocol with anti-GFP nanobody capture enriched labeled nuclei from ~34.6% of input to 80-89% purity. Relative to dissociation and FACS, this recovers roughly 30-fold more target nuclei in less than half the time and without a cytometer. Bead-bound nuclei are directly applied to combinatorial-barcoding snRNA-seq, eliminating fluorescence-activated nuclei sorting (FANS). Profiling INTACT+ connective tissue during TGF{beta} inhibition revealed a loss of extracellular matrix remodeling with upregulated pro-fibrotic and inflammatory gene programs, resembling an unresolved wound environment. These changes reverse and regeneration resumes upon drug washout, indicating that functional TGF{beta} signaling is required for the transition from wound resolution to blastema formation.

Motivation: Real-time qPCR data are commonly analyzed to obtain a Cq values, which are used to compare the relative abundance of a targeted template. However, improper background subtraction distorts Cq and changing the assigned threshold can alter experimental conclusions. In addition, a Cq values provide no information on the quality of the qPCR for a given sample. Alternatively, global fitting of qPCR data provides agnostic quantification without the use of Cq or thresholds, and the fitting terms provide a useful metric of reaction performance. Current implementations of global fitting are limited to custom in-house programs. Results: qPyCR is comprehensive analysis tool written in Python that performs background signal subtractions, computes a threshold, and reports Cq values in a traditional manner. The program also performs global fitting and reports template abundances along with reaction quality values. The quality values can be used to assign performance standards, which allow researchers to distinguish aberrant reactions from true changes in template abundance. Availability and Implementation: Code and example data are freely available on GitHub (https://github.com/sdmoore-labs/qPyCR) and on Zenodo (https://doi.org/10.5281/zenodo.21115342).

Suspension mass cytometry can measure 50 or more markers per cell and is not impacted by cellular autofluorescence, making it an appealing platform for comprehensive phenotyping of single cells in tissue with high innate fluorescence, such as brain. However, this organ is challenging to reduce to a single cell suspension: it is a deeply interconnected tissue rich in extracellular material and contains a wide variety of cell types including neurons, their supporting glia, and hematopoietic cells from peripheral circulation, any or all of which may have competing requirements for survival through the dissociation process. This study compares approaches for producing single-cell preparations from white and gray matter enriched regions of adult mouse brain, testing simple mechanical dissociation, Accutase, and three gentle enzymes plus DNase: papain, collagenase II, and collagenase plus dispase, all with or without Percoll gradient centrifugation to separate intact cells from debris. Live cells were counted by hemocytometer and Trypan blue exclusion to assess yield and compare across enzyme conditions. Mass cytometry was used to assess cellular composition after representative dissociation, debris removal, and viable cryopreservation. Key proteins measured included beta III-tubulin for neurons, glial fibrillary acidic protein (GFAP) for astrocytes, oligodendrocyte transcription factor (OLIG2) for oligodendrocytes, CD31 for endothelial cells, CD24 for ependymal cells, purinergic receptor P2Y12 (P2RY12) for microglia, and CD45 for leukocytes. Mechanical disaggregation paired with enzymatic dissociation by papain, Collagenase/Disapse, or Collagenase II plus DNase produced approximately 400,000 live cells per 100 grams of tissue. Cell yield was not significantly different between conditions and yields were similar between white and grey matter. Addition of Percoll gradient centrifugation substantially reduced the number of viable cells recovered (average decrease of 88%) and resulted in viable cell numbers that were insufficient for robust analysis of less common cell subsets. In addition to neurons, mass cytometry identified six major populations of non-neuronal cells: oligodendrocytes, astrocytes, endothelial cells, ependymal cells, microglia, and leukocytes. The relative abundance of these six populations was generally unchanged by cryopreservation in both grey matter (r = 0.95), and white matter (r = 0.90), though loss of oligodendrocytes did occur in both tissues. Proliferation, as measured by Ki67 positivity, was non-existent; consistent with this, levels of phosphorylated STAT1 (p-STAT1) and p-STAT3 proteins were low in all cell populations and unchanged by cryopreservation. A modest increase in p-S6(S235/236) after cryopreservation was consistently observed only in microglia. Together, these results establish standardized procedures for generating viable single cell suspensions for cytometry that preserve the cellular diversity of the adult murine brain with minimal perturbation of intracellular signaling cascades.

The field of microglial research has evolved throughout the years. Microglia, the immune cells of the central nervous system, are recognized as highly heterogeneous and dynamic cells, known for modifying their structure and function based on the local context. Investigating microglial density, spatial distribution, and morphological states is important for uncovering their distinct functional states in health and pathology. However, quantifying these features accurately is often a methodological challenge. Fully automated computational approaches often fail to capture subtle biological nuances and complex structural variations. Also, the high diversity of image sets makes it difficult to maintain consistent reliability. In contrast, entirely manual quantification is labor-intensive and prone to observer bias. To bridge this gap, we propose a semi-automated framework using the open-source software CellProfiler. Our workflow is divided into two distinct pipelines designed to combine automation of batch analysis with targeted user oversight, allowing for manual intervention when necessary to ensure maximum accuracy. Both pipelines are capable of recognizing microglial soma and tracing their processes. In the density workflow, it automatically calculates cell density and provides spatial distribution measurements, such as closest-neighbor distance and spacing index. For morphological profiling, it yields extensive structural data, including area, perimeter, convex area, form factor, and various shape descriptors. Furthermore, we demonstrate how researchers can optimize the pipeline settings to accommodate varied image datasets and experimental conditions. We hope this open-source framework can standardize microglial density, distribution, and morphological analysis and reduce systematic bias, providing researchers with a robust tool to better characterize their heterogeneity.

Two-photon calcium imaging enables measurements of neural activity from individual neurons and their subcellular processes in awake animals. Axial brain motion can change measured fluorescence independently of neural activity and move small structures out of the imaging plane, confounding two-photon calcium measurements in behaving animals. We developed two complementary post-acquisition methods, selected according to whether the imaged structure remains detectable across the encountered depth range. When it does, z-stack correction estimates imaging depth from a separately acquired reference z-stack and uses an axial fluorescence profile specific to each neural structure to rescale fluorescence to a common reference depth. When a structure can leave a single imaging plane, volume-based z-registration reconstructs a common-depth movie from repeated acquisitions of closely spaced planes. In awake mice, both methods tracked experimentally imposed axial displacements within the sampled range, with depth-estimation root mean squared errors (RMSEs) below 1 m for z-stack correction and 0.69-1.03 m for volume-based z-registration. Correction changed fluorescence substantially for a subset of somata, with larger effects in axonal boutons. Both methods are implemented in suite2p-in-depth, a Python package that integrates with Suite2p and provides diagnostics for depth estimation, correction quality and data reliability. Together, these methods enable axial-motion artifacts to be assessed and corrected within established Suite2p workflows.

Background: Transcardial perfusion fixation is widely used to preserve rodent brains for histological and ultrastructural analysis, but protocols can vary in the use of pre-fixation washout, fixative formulation, and osmotic additives. Relatively few studies have directly compared how the chemical composition of the perfusate affects tissue preservation. Methods: Male Sprague-Dawley rats underwent transcardial perfusion using a series of aldehyde-based fixative formulations that varied in fixative composition, use of a phosphate buffered saline washout, and the addition of mannitol or polyethylene glycol 35 kDa (PEG35). Perfusion outcomes were assessed using gross brain morphology, semi-quantitative grading of vascular blood clearance, quantitative detection of residual erythrocytes in whole-slide histological images, and light microscopic measures of cellular visualization and morphology. Perfusate osmolality was measured, and selected specimens were examined by electron microscopy. Results: Substantial vascular blood clearance was frequently achieved with fixative-only perfusion, indicating that a pre-fixation washout was not required to achieve high levels of blood clearance under the conditions tested. Routine light microscopy-based measures of cellular visibility and morphology were broadly similar across treatment groups. Adding mannitol and PEG35 to the fixative solution both led to concentration-dependent gross tissue shrinkage, particularly with PEG35, without correspondingly large or consistent changes on light microscopy. A substantial degree of case-to-case variation in perfusion quality was also observed among animals undergoing nominally similar procedures. Conclusions: Substantial variation in perfusate composition produced relatively modest differences in the light microscopy outcomes examined, despite pronounced effects of osmotic additives on gross brain morphology. There were some cases where perfusion with fixative alone led to near-complete blood vessel clearance, and the use of a preceding phosphate buffered saline washout was not associated with higher vascular clearance scores. The degree of case-to-case variability observed within treatment conditions suggests that procedural factors can play an important role on perfusion quality in addition to perfusate composition.

An increasing number of researchers, educators, and at-home growers are turning to hydroponics as an alternative method of food production, diversifying and strengthening the food supply chain. This has led to a substantial increase in the amount of academic work involving hydroponic production of plants for a variety of purposes, including but not limited to a more controlled and customizable environment than conventional production methods, utilizing hydroponics as a method of wastewater treatment, and investigating the vertical production of plants on a much smaller footprint than traditional commercial-scale production. Because so many unique stakeholders are interested in hydroponics for a variety of reasons, academic studies use a wide variety of hydroponic systems with varying levels of technology and automation, making comparisons across studies and systems challenging. A few institutions have sophisticated plant growth and research facilities, like those used by commercial companies, but these systems are often prohibitively expensive, costing upwards of $10,000 USD for a very limited amount of growing space for experimental trials. To enable more researchers, educators, and citizen scientists to conduct experiments and easily compare their results, this study details three pilot-scale hydroponic production systems (Kratky, NFT, and DWC), utilizing entirely off-the-shelf components, for under $5,000 USD each, that are capable of maintaining the desired consistent temperature and relative humidity levels, and have space for 216, 108 (6 irrigation loops), and 64 (16 irrigation bins) plants, respectively. The material lists and prices are provided along with assembly instructions and general guidelines for each hydroponic system. The testing and optimization process of environmental conditions within each growth system is also detailed, with suggested customizations for potential experimental setups. The authors developed these systems during their Masters and Doctoral degree programs, enabling improved hydroponic research at the University of Illinois Urbana-Champaign. They hope that other aspiring hydroponic researchers can benefit from this work in the development and operation of their hydroponic systems, increasing research efficiency and collaboration opportunities in this field of study.

Small RNA (sRNA) sequencing is widely used to study siRNA, miRNA and piRNA pathways and to profile sRNAs derived from viruses, transposons and host transcripts. However, many sRNA workflows rely on command-line mapping and separate software for downstream analysis and visualisation. We present sRNAMap, an HTML5/JavaScript application for mapping and analysing sRNA sequencing data. sRNAMap accepts either raw FASTA/FASTQ reads or pre-aligned BAM files. For raw reads, sRNAMap uses a k-mer-seeded alignment algorithm that runs directly in the browser using parallel Web Workers where supported. It generates strand-specific per-base coverage, 5'- and 3';-end profiles, read-length distributions and nucleotide-bias summaries, with optional library-size normalisation. It also quantifies characteristic read-overlap signatures, including 5';-to-5'; overlaps associated with ping-pong-like processing. Additional modules quantify phased sRNA production, non-templated 3'- and 5'-additions, and sequence diversity. Analyses can be saved and restored as JSON or exported as self-contained HTML reports containing figures and analysis metadata. Benchmarking against Bowtie 2 under approximately matched alignment settings using a representative virus-infected arthropod small-RNA dataset showed highly concordant mapping profiles. Per-position depth showed an R^2 of approximately 0.998, while 5';- and 3';-end counts showed R^2 values of approximately 0.97. sRNAMap is available at https://github.com/rhparry/sRNAMap under the MIT licence.

Mass spectrometry based immunopeptidomics is limited by peptide identification. HLA class I ligands are non-tryptic, frequently carry low charge states and often fragment incompletely, yet nearly all workflows rely on a single activation method, higher-energy collisional dissociation (HCD). Unlike proteomics, where a protein is inferred from several peptides, in immunopeptidomics the peptide is itself the analyte and the candidate therapeutic target, so a ligand that is not identified is a target that is not found. Here we evaluate whether two alternative activation chemistries, ion trap collision-induced dissociation (CID) and infrared multiphoton dissociation (IRMPD), recover ligands that HCD does not. To our knowledge this is the first application of either method to HLA class I immunopeptidomics, made practical by the integrated infrared laser of the Orbitrap Tribrid Apex MultiOmics. Four HLA-typed cell lines were analysed in technical triplicate against the canonical human proteome and a Ribo-seq-derived cryptic ORF database. Because fragment-intensity predictors are trained almost exclusively on HCD spectra, AlphaPeptDeep was fine-tuned separately for each method; fine-tuning and Percolator rescoring increased unique peptide identifications in every cell line and method combination (median +17.1% canonical, +54.5% cryptic), and fine-tuned models transferred across cell lines with a median loss of 0.4%, placing the three methods on a common analytical footing. On that footing the three methods yielded immunopeptidomes of similar size and composition, but each recovered peptides the others missed. HCD produced the most complete fragment-ion ladders and recovered more peptides from the basic-anchor alleles A*11:01 and A*33:03, both members of the A3 supertype. CID and IRMPD recovered a larger share of alleles without a basic C-terminal anchor and, for peptides containing no lysine, arginine or histidine, produced higher search scores and more matched b/y ion current in three of four cell lines. Each method therefore contributed exclusive peptides, and at a fixed budget of three LC-MS/MS runs, one run per method yielded on average more unique peptides than triplicate runs of a single method in all four cell lines (+0.4% to +10.9%). Of 239 novel canonical predicted HLA binders in the two cancer cell lines (HCT116 and MDA-MB-231) absent from the Immune Epitope Database, 55% were detected by only one method; nine derive from cancer-associated antigens. CID and IRMPD can therefore provide sequences that may not be identified by HCD alone, or with better spectral quality for a chemically defined subset of ligands. Their value lies alongside HCD rather than in its place, and realising it will require fragment-intensity models and acquisition schemes built for these chemistries rather than adapted from HCD.

Double-stranded RNAs are inflammatory byproducts of in vitro transcription of single-stranded RNA. Here we investigate removal of dsRNA byproducts using dsRNA affinity chromatography (dsRNA-AC) and two common mRNA molecules: 1) GFP, and 2) high dsRNA wild-type firefly luciferase (fLucWT). For GFP mRNA, dsRNA levels decreased by 2,000-fold, and mRNA recovery was high. In contrast, dsRNA levels decreased only two-fold for fLucWT, and mRNA yields were lower. Biophysical characterization revealed that fLucWT contains polydisperse higher-order structures that interfered with dsRNA-AC. Sedimentation-velocity analytical ultracentrifugation experiments demonstrated the higher-order structures were driven by mRNA concentration. Decreasing fLucWT concentrations increased the effectiveness of dsRNA-AC by reducing polydispersity. dsRNA levels were measured with ELISA, dot-blots, immuno-northern blots, and a cell-based interferon release assay, enabling comparison and cross-validation of these analytical methods. dsRNA-AC is a new chromatography modality, and this study identifies sample polydispersity as a key determinant of efficient dsRNA removal.

Many studies using mouse models of human brain disorders rely on extended recordings of brain electrical activity through electroencephalogram, or EEG. The features that researchers measure in these recordings, such as seizures and epileptiform activity, are deeply influenced by whether the animal is awake, in non-rapid eye movement (NREM) sleep, or in rapid eye movement (REM) sleep. Because total sleep duration varies naturally across animals, rigorous experimental comparisons require classifying the sleep state of every few seconds of a recording. Manual annotation is highly labor-intensive, often requiring hours per subject. While automated scoring tools accelerate this process, they are typically trained exclusively on healthy cohorts and frequently fail when applied to disease models that exhibit atypical or fragmented sleep architecture. Somnus is an open-source Python package designed to automate rodent sleep staging using EEG, muscle activity (EMG), and optional video-tracking data. It includes a robust base model trained on diverse recordings from six independent laboratories, enabling out-of-the-box classification across various equipment setups without requiring prior manual labeling. A central feature of Somnus is its capacity for rapid adaptation to pathological sleep structure. The software provides a graphical interface that directs researchers to the specific epochs where the base model is least certain. Users can manually correct these targeted epochs in a built-in viewer by comparing the model's classification to the raw EEG signal and video, and then use their corrections to fine-tune the model. This workflow empowers researchers to generate accurate custom scorers for complex disease models or novel treatments with just a few minutes of manual correction, bypassing the need to hand-score entire experimental cohorts or develop their own models from scratch.

Transfer RNA (tRNA) is highly modified and difficult to profile using reverse-transcription-based sequencing. Here, we established a direct RNA sequencing (tRNA-DRS) workflow to simultaneously characterize tRNA abundance and modification signals in mouse liver. The workflow included small-RNA enrichment, deacylation, splint-adapter ligation, barcoding, reverse transcription, and nanopore sequencing on PromethION with modification-aware basecalling. From 1,678,666 raw reads, 1,421,279 (84.67%) reads were retained after 20-200 nt length filtering, and 17,094 uniquely mapped reads (MAPQ [≥] 10) were obtained. These reads covered 244 tRNA genes and represented all 23 tRNA isotypes. tRNA abundance was strongly skewed, with Asp, Gly, Ser, and Lys accounting for 56.6% of uniquely mapped reads. Read-body coverage indicated that most uniquely mapped reads spanned substantial portions of tRNA molecules (mean 71.1%, median 75.9%; 83.3% reads covering [≥]50% of the reference). Modification analysis identified 41,013 candidate sites, of which 711 passed stringent filtering (modification fraction [≥]50%, coverage [≥]5), spanning eight modification types and dominated by pseudouridine and m5C. Filtered sites showed position-specific clustering and isotype-dependent patterns. Together, these results support tRNA-DRS as a practical single-assay framework for simultaneous tRNA expression and epitranscriptomic profiling in mammalian tissue.

Public data sharing in immunological and clinical research is essential for transparency, reproducibility, and secondary analysis. However, many datasets in repositories such as ImmPort lack sufficient structured data to enable reuse. ImmPort's Assessments and Lab Tests templates -- which capture critical clinical information -- are often incomplete or omitted due to their complexity and the manual effort required. To address this challenge, an application with a graphical user interface requiring no programming was developed to facilitate population of these templates. The tool streamlines the submission process by reducing time and complexity for data contributors while ensuring template formatting. It integrates ImmPort files, study-specific data files, and a curated data dictionary to automate the mapping of study variables to the required fields within each template. The tool was evaluated on seven ImmPort studies with diverse designs. It successfully generated submission-ready templates that passed ImmPort's internal validation and will be incorporated into the repository. By improving the feasibility and completeness of templates, this approach enhances the quality, findability, and reusability of data within ImmPort.

Optical mapping is a fundamental tool for cardiac electrophysiology research. Processing of these signals can be non-trivial, requiring multiple pre- and post-processing steps to limit interpretation errors. Existing software packages have features siloed across platforms and require users to combine several packages for in-depth analysis. To address this, we developed CADENCE, an open-source MATLAB-based application combining feature breadth (e.g., SVD denoising, conduction velocity, alternans, annotated rotors) and depth (e.g., 15 independent alternans features across both voltage and calcium modalities) in an end-to-end pipeline including data conversion, signal conditioning, feature extraction, and signal analysis. We demonstrate CADENCE's capabilities across datasets spanning four species (rat, rabbit, pig, and human), three tissue preparations (slices, wedge, and whole heart), and three camera configurations (single, dual, and panoramic). CADENCE was validated against three blinded expert observers (15 hearts) and demonstrated agreement comparable to inter-observer variability (SD ratios 1.07/0.95/0.89 for APD80, activation, CaTD80). Dominant frequency was recovered with a median error of 0.03% across 84 of 88 paced recordings with 1:1 capture. CADENCE's code is publicly available and distributed as a compiled standalone application that the end-user can install and run without a MATLAB license to encourage adoption and standardization across laboratories.

Lymphatic endothelial cell (LEC) function is strongly tied to transitions between button- and zipper-like junctions that control fluid flow into vessels. Published methods quantifying junction morphology are limited to single cell analysis or use few quantitative metrics to describe junctions across LEC monolayers. Therefore, a novel 3-step image analysis pipeline was developed to identify new metrics that quantify differences in button- and zipper-like junctions in LECs. The pipeline used Cellpose, CellProfiler, and Fiji to analyze VE-cadherin expression across lymphatic vessels within a 3D microfluidic chip and quantify VE-cadherin radial intensity, number of objects, object size, branchpoints, end-points, and junction thickness. Tumor necrosis factor (TNF)- exposure produced but-ton-like junctions, and unexposed cells were zippered. Radial intensity was heightened at the cell membrane in zipper-like junctions while perinuclear intensity increased for but-ton-like junctions. Increased branchpoints, endpoints, objects per cell, and junction thick-ness were associated with junction buttoning, while increased object size was associated with junction zippering. Principle component analysis results reinforced these trends and identified metric combinations that represented each junctional state. Overall, this semi-automated pipeline quantified differences in VE-cadherin junction morphology across LEC monolayers and generated new quantitative metrics to expand the tools available for studying junction morphology in lymphatic vasculature.

Introduction: The inability to measure renal sympathetic outflow clinically poses a significant problem for patient identification and intraprocedural feedback for renal denervation. Sympathetic vasomotion is a novel physiologic measure of rhythmic vascular control that reflects renal sympathetic nervous system activity, but previous measurements of sympathetic vasomotion relied on 15-minute data recordings, which may be impractical in many clinical settings. We therefore tested whether shorter data segments can provide reliable sympathetic vasomotion assessment to enhance decision making for renal denervation. Methods: Ten swine that had previously undergone unilateral surgical renal denervation underwent four rounds of catheter-based denervation of the contralateral kidney. Sympathetic vasomotion was quantified from the time-varying arterial pressure-resistive renal blood flow transfer function of recordings obtained before and after each round of ablation. Randomly placed 1- to 14-minute data segments were scored and compared with the corresponding 15-minute sympathetic vasomotion scores across 100 passes using correlation, intraclass correlation, error, and Bland-Altman agreement metrics, and by whether they reproduced the denervation decisions made from the full recordings. Results: Agreement with the 15-minute reference score improved steeply with recording length up to approximately four minutes and slowly thereafter, with the point of diminishing returns at four minutes for every group-level measure. Four-minute data segments showed an intraclass correlation coefficient of 0.94, reproduced the group-level statistical results across ablations, and preserved intraprocedural denervation decisions. Bland-Altman analysis revealed that individual-level precision continued to improve with recording length; the proportion of scores falling within a quarter of the average difference between innervated and denervated kidneys at baseline was 65 percent at four minutes and 96 percent at ten minutes. Discussion: Four-minute data segments provide a feasible minimum recording duration when the question is a group comparison or a paired, within-individual decision, such as intraprocedural confirmation that an innervated kidney has shifted toward a denervated state. When a single score must be interpreted on its own, as in preprocedural patient selection, ten-minute recordings provide greater precision. Further studies are needed to prospectively evaluate sympathetic vasomotion in clinical settings and determine whether this technology can support procedural feedback and inform patient selection.

Genome engineering via CRISPR/Cas9 has been widely applied in biological research and developing gene therapies. However, genome editing flexibility is strongly constrained by the position and quality of guide RNAs relative to the intended edit: desired edit sites are frequently positioned far from efficient protospacer adjacent motifs (PAM). SMART (Silently Mutate And Repair Template) technique relaxes this constraint by silently mutating the gap between the Cas9 cut and the edit in the repair donor, preserving the encoded protein while expanding the usable guide-RNA design space. Designing such donors manually requires coordinated reasoning over transcript structure, reading frame, candidate protospacers, codon usage, homology arms and the expected edited allele. Auto-SMART is a web platform that automates this process for CRISPR/Cas9-mediated insertion, deletion, point mutation and sequence replacement in coding exons and in introns. Users choose a genome assembly, search a gene symbol or transcript, select a modification site and select an editing operation. Auto-SMART finds nearby Streptococcus pyogenes Cas9 (SpCas9) guides, ranks them by predicted on-target activity and cut-to-edit geometry, builds repair templates with synonymous substitutions, automatically recodes residual on-target sites to prevent re-cutting and renders interpretable panels for the target locus, donor template and locus after HDR, together with a downloadable report and a Primer3 genotyping handoff. The web application for Auto-SMART is freely available at https://auto-smart.chuanping.org/.

Context: Cytological specimens allow minimally invasive, repeated sampling for diagnosis and molecular testing. However, cytology biobanking protocols have primarily been optimized for morphology, and the effects of preanalytical handling and storage on intracellular proteins remain unclear. Objective: To assess how fixation, staining, storage temperature, and duration affect intracellular protein preservation in cytological specimens and to identify conditions suitable for in situ proximity ligation assay (isPLA). Design: Human cancer cell lines were processed under different preanalytical conditions. Intracellular proteins and protein protein interactions were assessed by isPLA, fluorescence microscopy, and quantitative image analysis. Slides were stored at room temperature or minus 20 Celsius, with or without MayGrunwaldGiemsa (MGG) staining. Results: Storage temperature had the greatest effect on protein signal. Unstained slides stored at minus 20 Celsius retained strong signals for up to 24 months, whereas room temperature storage reduced detectable protein interactions by approximately 95%. MGG staining further reduced signal intensity during prolonged storage. Nevertheless, stained slides remained suitable for isPLA when staining, microscopic evaluation, destaining, and antibody labeling were completed on the same day. Prolonged room temperature storage of stained slides caused loss of antigenicity, increased autofluorescence, and false negative findings. Conclusions: Low temperature storage and standardized preanalytical handling preserve intracellular protein signals in cytological specimens. These conditions support reliable single cell protein profiling of archived samples and their use in biomarker research and translational pathology.

Point-of-care (POC) molecular detection has enabled rapid and accessible testing at or near the site of need, facilitating timely decision-making in clinical, field, and industrial settings. Despite these advancements, molecular detection platforms remain limited in their ability to prepare DNA from complex tissue matrices, restricting their applicability to a narrow range of sample types. To address sample preparation inefficiencies, focused ultrasound extraction (FUSE) has been developed for the rapid release of DNA from robust tissue matrices. FUSE disintegrates target tissue and releases DNA by delivering high pressure ultrasound pulses that generate a cavitation bubble cloud. In prior work, FUSE was performed using large, laboratory-based equipment. Here, a miniaturized FUSE device was designed and tested to enable POC DNA sample preparation. Design constraints were defined based on prior FUSE experiments, and based on these metrics, a 750 kHz cylindrical transducer was fabricated. The pressure output was measured, and high-speed optical imaging demonstrated that the transducer generated sustained cavitation within the defined focal region. The feasibility of DNA extraction from piscine and timber tissues was evaluated, and results show that the device can release DNA with quality suitable for PCR-based detection from both tissue types. These results demonstrate the potential of this device to rapidly extract DNA from complex samples and expand the applicability of molecular detection platforms.