Wald χ2 Test for Differential Item Functioning Detection with Polytomous Items in Multilevel Data.

Identifying items with differential item functioning (DIF) in an assessment is a crucial step for achieving equitable measurement. One critical issue that has not been fully addressed with existing studies is how DIF items can be detected when data are multilevel. In the present study, we introduced a Lord's Wald χ2 test-based procedure for detecting both uniform and non-uniform DIF with polytomous items in the presence of the ubiquitous multilevel data structure. The proposed approach is a multilevel extension of a two-stage procedure, which identifies anchor items in its first stage and formally evaluates candidate items in the second stage. We applied the Metropolis-Hastings Robbins-Monro (MH-RM) algorithm to estimate multilevel polytomous item response theory (IRT) models and to obtain accurate covariance matrices. To evaluate the performance of the proposed approach, we conducted a preliminary simulation study that considered various conditions to mimic real-world scenarios. The simulation results indicated that the proposed approach has great power for identifying DIF items and well controls the Type I error rate. Limitations and future research directions were also discussed.

Efficacy and safety of gemcitabine plus raltitrexed or S-1 versus standard third-line therapies in metastatic colorectal cancer: a retrospective cohort study.

Background: After the failure of standard first- and second-line treatments, including oxaliplatin, irinotecan, and 5-fluorouracil (5-FU) combined with targeted drugs, the currently recommended third-line regimens for metastatic colorectal cancer (mCRC) include TAS-102, regorafenib, and fruquintinib. However, these regimens have the drawbacks of mediocre efficacy, substantive side effects, and high cost. Therefore, more effective, economical regimens with fewer side effects are needed in clinical practice. In this study, we assessed the efficacy and safety of gemcitabine plus raltitrexed or S-1 as a third- or later-line treatment in comparison to those of standard third-line therapies for patients with mCRC. Methods: Patients with previous failures of at least two lines of standard therapy with oxaliplatin, 5-FU, irinotecan, or capecitabine combined with targeted drugs were included. The participants received standard third-line therapies (including TAS-102, regorafenib, and fruquintinib) or gemcitabine plus raltitrexed or S-1 until disease progression, death, or intolerable toxicity arose. Imaging follow-up was performed every 3 months during their treatment. Progression-free survival (PFS) and overall survival (OS) were recorded. Cox regression analysis was used to investigate the potential predictors of survival. Results: From April 2018 to October 2022, 60 patients with mCRC were enrolled in our study. The numbers of patients in the chemotherapy, fruquintinib, regorafenib, and TAS-102 groups were 13, 15, 17, and 15, respectively; the median OS of the four groups was 7.4, 6.1, 8.3, and 6.7 months (P=0.384), respectively; the median PFS was 4.1, 3.4, 4.4, and 2.3 months (P=0.656), respectively; the overall response rate was 7.69%, 6.67%, 0.00%, and 13.33%, respectively; and the disease control rate was 61.54%, 60.00%, 70.59%, and 60.00%, respectively. Additionally, multivariate analysis revealed that primary lesion located in the rectum was adverse independent prognostic factors for OS. A typical case is presented in this article. Conclusions: The gemcitabine plus raltitrexed or S-1 regimen is a potential regimen with tolerable adverse reactions and low cost for patients with mCRC.

Approaches to Item-Level Data with Cross-Classified Structure: An Illustration with Student Evaluation of Teaching.

Student evaluation of teaching (SET) questionnaires are ubiquitously applied in higher education institutions in North America for both formative and summative purposes. Data collected from SET questionnaires are usually item-level data with cross-classified structure, which are characterized by multivariate categorical outcomes (i.e., multiple Likert-type items in the questionnaires) and cross-classified structure (i.e., non-nested students and instructors). Recently, a new approach, namely the cross-classified IRT model, was proposed for appropriately handling SET data. To inform researchers in higher education, in this article, the cross-classified IRT model, along with three existing approaches applied in SET studies, including the cross-classified random effects model (CCREM), the multilevel item response theory (MLIRT) model, and a two-step integrated strategy, was reviewed. The strengths and weaknesses of each of the four approaches were also discussed. Additionally, the new and existing approaches were compared through an empirical data analysis and a preliminary simulation study. This article concluded by providing general suggestions to researchers for analyzing SET data and discussing limitations and future research directions.

Psychometric exploration of the RAADS-R with autistic adults: Implications for research and clinical practice.

LAY ABSTRACT: Surveys used to screen for autism are being used much more by adults. Adults and clinicians want to be confident that the results from their surveys are accurate. If scores are not accurate, it is not possible to compare the scores of different groups of individuals. There are also concerns that these surveys do not accurately identify autistic individuals. This study explored the accuracy of two commonly used autism screening surveys for adults: the RAADS-R and the RAADS-14. The accuracy of these two screening tools was measured using a sample of 839 adults. Adults in the study were in one of the following categories: (1) diagnosed with autism, (2) adults who considered themselves to be autistic but had not been diagnosed, (3) adults who were unsure whether they were autistic, and (4) adults who did not consider themselves to be autistic and had not been diagnosed. The study found that the RAADS-R and the RAADS-14 are accurate. The study also found that a person's age, gender, autism diagnosis, or whether an individual considered themselves to be autistic did not impact how they understood the survey. Survey accuracy could be improved by changing the number of question responses from four to two. Importantly, individuals with a clinical diagnosis of autism and those who considered themselves to be autistic responded to survey items in a very similar way. Individuals with autism diagnoses and those who were unsure whether they were autistic were more different in their responses. Four specific survey items related to sensory experiences and social interaction identified key differences between autistic and non-autistic adults.

Disruption of H3K36 methylation provokes cellular plasticity to drive aberrant glandular formation and squamous carcinogenesis.

Chromatin organization is essential for maintaining cell-fate trajectories and developmental programs. Here, we find that disruption of H3K36 methylation dramatically impairs normal epithelial differentiation and development, which promotes increased cellular plasticity and enrichment of alternative cell fates. Specifically, we observe a striking increase in the aberrant generation of excessive epithelial glandular tissues, including hypertrophic salivary, sebaceous, and meibomian glands, as well as enhanced squamous tumorigenesis. These phenotypic and gene expression manifestations are associated with loss of H3K36me2 and rewiring of repressive H3K27me3, changes we also observe in human patients with glandular hyperplasia. Collectively, these results have identified a critical role for H3K36 methylation in both in vivo epithelial cell-fate decisions and the prevention of squamous carcinogenesis and suggest that H3K36 methylation modulation may offer new avenues for the treatment of numerous common disorders driven by altered glandular function, which collectively affect large segments of the human population.

A random item effects generalized partial credit model with a multiple imputation-based scoring procedure.

PURPOSE: Random item effects item response theory (IRT) models have received much attention for more than a decade. However, more research is needed on random item effects IRT models for polytomous data. Additionally, to improve the utility of this new class of IRT models, the scoring issue must be addressed. METHODS: We proposed a new random item effects generalized partial credit model (GPCM), which considers both random person and random item and category-specific effects. In addition, we introduced a multiple imputation (MI)-based scoring procedure that applies to various random item effects IRT models. To evaluate the proposed model and scoring procedure, we analyzed data from a Quality of Life (QoL) scale for the Chronically Mentally III and conducted a preliminary simulation study. RESULTS: In the empirical data analysis, we found that patient scores generated based on the proposed model and scoring procedure were almost identical to those obtained through the conventional GPCM and scoring method. However, the standard errors (SEs) associated with the scores were slightly larger when the proposed approach was utilized. In the simulation study, we observed adequate recovery of the model parameters and patient scores. CONCLUSION: The proposed model and MI-based scoring procedure contribute to the literature. The proposed model substantially reduces the number of free parameters in comparison to a conventional GPCM, which can be desired when sample sizes are small, e.g., special populations. In addition, the MI-based scoring procedure addresses the scoring issue and can be easily extended for scoring with other random item effects IRT models.

An Explanatory Multidimensional Random Item Effects Rating Scale Model.

Random item effects item response theory (IRT) models, which treat both person and item effects as random, have received much attention for more than a decade. The random item effects approach has several advantages in many practical settings. The present study introduced an explanatory multidimensional random item effects rating scale model. The proposed model was formulated under a novel parameterization of the nominal response model (NRM), and allows for flexible inclusion of person-related and item-related covariates (e.g., person characteristics and item features) to study their impacts on the person and item latent variables. A new variant of the Metropolis-Hastings Robbins-Monro (MH-RM) algorithm designed for latent variable models with crossed random effects was applied to obtain parameter estimates for the proposed model. A preliminary simulation study was conducted to evaluate the performance of the MH-RM algorithm for estimating the proposed model. Results indicated that the model parameters were well recovered. An empirical data set was analyzed to further illustrate the usage of the proposed model.

Single-cell transcriptomes reveal a molecular link between diabetic kidney and retinal lesions.

The occurrence of diabetic nephropathy (DN) and diabetic retinopathy (DR) are closely associated in patients with diabetes. However, the cellular and molecular linkage of DN and DR has not been elucidated, and further revelations are needed to improve mutual prognostic decisions and management. Here, we generate and integrate single-cell RNA sequencing profiles of kidney and retina to explore the cellular and molecular association of kidney and retina in both physiological and pathological conditions. We find renal mesangial cells and retinal pericytes share molecular features and undergo similar molecular transitions under diabetes. Furthermore, we uncover that chemokine regulation shared by the two cell types is critical for the co-occurrence of DN and DR, and the chemokine score can be used for the prognosis of DN complicated with DR. These findings shed light on the mechanism of the co-occurrence of DN and DR and could improve the prevention and treatments of diabetic microvascular complications.

Integration of spatial and single-cell data across modalities with weakly linked features.

Although single-cell and spatial sequencing methods enable simultaneous measurement of more than one biological modality, no technology can capture all modalities within the same cell. For current data integration methods, the feasibility of cross-modal integration relies on the existence of highly correlated, a priori 'linked' features. We describe matching X-modality via fuzzy smoothed embedding (MaxFuse), a cross-modal data integration method that, through iterative coembedding, data smoothing and cell matching, uses all information in each modality to obtain high-quality integration even when features are weakly linked. MaxFuse is modality-agnostic and demonstrates high robustness and accuracy in the weak linkage scenario, achieving 20~70% relative improvement over existing methods under key evaluation metrics on benchmarking datasets. A prototypical example of weak linkage is the integration of spatial proteomic data with single-cell sequencing data. On two example analyses of this type, MaxFuse enabled the spatial consolidation of proteomic, transcriptomic and epigenomic information at single-cell resolution on the same tissue section.

Mettl3-catalyzed m6A regulates histone modifier and modification expression in self-renewing somatic tissue.

N6-methyladenosine (m6A) is the most abundant modification on messenger RNAs (mRNAs) and is catalyzed by methyltransferase-like protein 3 (Mettl3). To understand the role of m6A in a self-renewing somatic tissue, we deleted Mettl3 in epidermal progenitors in vivo. Mice lacking Mettl3 demonstrate marked features of dysfunctional development and self-renewal, including a loss of hair follicle morphogenesis and impaired cell adhesion and polarity associated with oral ulcerations. We show that Mettl3 promotes the m6A-mediated degradation of mRNAs encoding critical histone modifying enzymes. Depletion of Mettl3 results in the loss of m6A on these mRNAs and increases their expression and associated modifications, resulting in widespread gene expression abnormalities that mirror the gross phenotypic abnormalities. Collectively, these results have identified an additional layer of gene regulation within epithelial tissues, revealing an essential role for m6A in the regulation of chromatin modifiers, and underscoring a critical role for Mettl3-catalyzed m6A in proper epithelial development and self-renewal.

Actual and Desired Masturbation Frequency, Sexual Distress, and Their Correlates.

We investigated the prevalence of problematic masturbation using different criteria. We also investigated if masturbation-related distress was associated with sexual abuse history, family attitudes towards sexuality during childhood, and depression and anxiety symptoms. Here, 12,271 Finnish men and women completed a survey reporting masturbation frequency, desired masturbation frequency, sexual distress, childhood sexual abuse, sex-positive family background, as well as depression and anxiety symptoms. Among both sexes, those whose masturbation frequency did not match with desired frequency experienced more sexual distress. Different conceptualizations of problematic masturbation resulted in different proportions of individuals categorized as having it (i.e., 8.3% of men and 2.7% of women experienced self-perceived problematic masturbation, that is masturbating more than they desired and experiencing sexual distress; 2% of men and 0.6% of women masturbated more frequently than average and meanwhile experienced self-perceived problematic masturbation; 6.3% of men and 2.1% of women masturbated less frequently than average but still experienced self-perceived problematic masturbation). Moreover, among both sexes, self-perceived problematic masturbation was positively associated with childhood sexual abuse, depression, and anxiety, while negatively associated with a sex-positive family background. Our results point to the complexity of defining problematic masturbation. Causes of sexual distress related to masturbation need to be carefully examined case by case to choose an appropriate clinical approach.

Construction and validation of a prognostic model based on autophagy-related genes for hepatocellular carcinoma in the Asian population.

BACKGROUND AND OBJECTIVE: Hepatocellular carcinoma (HCC), which has a complex pathogenesis and poor prognosis, is one of the most common malignancies worldwide. Hepatitis virus B infection is the most common cause of HCC in Asian patients. Autophagy is the process of digestion and degradation, and studies have shown that autophagy-associated effects are closely related to the development of HCC. In this study, we aimed to construct a prognostic model based on autophagy-related genes (ARGs) for the Asian HCC population to provide new ideas for the clinical management of HCC in the Asian population. METHODS: The clinical information and transcriptome data of Asian patients with HCC were downloaded from The Cancer Genome Atlas (TCGA) database, and 206 ARGs were downloaded from the human autophagy database (HADB). We performed differential and Cox regression analyses to construct a risk score model. The accuracy of the model was validated by using the Kaplan-Meier (K-M) survival curve, receiver operating characteristic (ROC) curve, and univariate and multivariate Cox independent prognostic analyses. The results Thirteen ARGs that were significantly associated with prognosis were finally identified by univariate and multivariate Cox regression analyses. The K-M survival curves showed that the survival rate of the low-risk group was significantly higher than that of the high-risk group (p < 0.001), and the multi-indicator ROC curves further demonstrated the predictive ability of the model (AUC = 0.877). CONCLUSION: The risk score model based on ARGs was effective in predicting the prognosis of Asian patients with HCC.

Associations between sexually submissive and dominant behaviors and sexual function in men and women.

The current study investigated the associations between sexually submissive and dominant behaviors and sexual dysfunction in Finnish men and women. We analyzed three population-based data sets from 2006, 2009, and 2021-2022, including 29,821 participants in total. Participants filled out a questionnaire about their sexually submissive and dominant behaviors, Sexual Distress Scale, Checklist for Early Ejaculation Symptoms and International Index of Erectile Function Questionnaire-5 (men), and Female Sexual Function Index (women). Pearson Correlations showed that for both sexes, sexually submissive (men: r = 0.119, p < 0.001; women: r = 0.175, p < 0.001) and dominant (men: r = 0.150, p < 0.001; women: r = 0.147, p < 0.001) behaviors were both associated with more sexual distress. However, for men, sexually submissive (r = -0.126, p < 0.001) and dominant behaviors (r = -0.156, p < 0.001) were associated with less early ejaculation symptoms. Both sexually submissive (r = 0.040, p = 0.026) and dominant behaviors (r = 0.062, p < 0.001) were also associated with better erectile function while sexually dominant behavior alone was associated with better orgasmic function (r = 0.049, p = 0.007), intercourse satisfaction (r = 0.068, p < 0.001), and overall satisfaction (r = 0.042, p = 0.018). For women, both sexually submissive (r = 0.184, p < 0.001) and dominant behaviors (r = 0.173, p < 0.001) were also associated with better overall female sexual function. One possible explanation is that these individuals have a clear idea of what they prefer sexually facilitating arousal. Particularly, sexually submissive behavior may reduce high-level self-awareness and, in this way, contribute to reduced performance anxiety. However, non-normative interests seem to simultaneously result in increased sexual distress probably due to the absence of self-acceptance. Further research about the causal mechanisms between non-normative sexual interest and sexual function is needed.

Simple Bioparticle Filtration Device Based on an Ultralow-Fouling Zwitterionic Polyurethane Membrane for Rapid Large-Volume Separation of Plasma and Viruses from Whole Blood.

Plasma separation from whole blood is oftent required as an essential first step when performing blood tests with a viral assay. However, developing a point-of-care plasma extraction device with a large output and high virus recovery remains a significant obstacle to the success of on-site viral load tests. Here, we report a portable, easy-to-use, cost-efficient, membrane-filtration-based plasma separation device that enables rapid large-volume plasma extraction from whole blood, designed for point-of-care virus assays. The plasma separation is realized by a low-fouling zwitterionic polyurethane-modified cellulose acetate (PCBU-CA) membrane. The zwitterionic coating on the cellulose acetate membrane can decrease surface protein adsorption by 60% and increase plasma permeation by 46% compared with a pristine membrane. The PCBU-CA membrane, with its ultralow-fouling properties, enables rapid plasma separation. The device can yield a total of 1.33 mL plasma from 10 mL whole blood in 10 min. The extracted plasma is cell-free and exhibits a low hemoglobin level. In addition, our device demonstrated a 57.8% T7 phage recovery in the separated plasma. The results of real-time polymerase chain reaction analysis confirmed that the nucleic acid amplification curve of the plasma extracted by our device is comparable to that obtained by centrifugation. With its high plasma yield and good phage recovery, our plasma separation device provides an excellent replacement for traditional plasma separation protocols for point-of-care virus assays and a broad spectrum of clinical tests.

Signal recovery in single cell batch integration.

Data integration to align cells across batches has become a cornerstone of single cell data analysis, critically affecting downstream results. Yet, how much biological signal is erased during integration? Currently, there are no guidelines for when the biological differences between samples are separable from batch effects, and thus, data integration usually involve a lot of guesswork: Cells across batches should be aligned to be "appropriately" mixed, while preserving "main cell type clusters". We show evidence that current paradigms for single cell data integration are unnecessarily aggressive, removing biologically meaningful variation. To remedy this, we present a novel statistical model and computationally scalable algorithm, CellANOVA, to recover biological signal that is lost during single cell data integration. CellANOVA utilizes a "pool-of-controls" design concept, applicable across diverse settings, to separate unwanted variation from biological variation of interest. When applied with existing integration methods, CellANOVA allows the recovery of subtle biological signals and corrects, to a large extent, the data distortion introduced by integration. Further, CellANOVA explicitly estimates cell- and gene-specific batch effect terms which can be used to identify the cell types and pathways exhibiting the largest batch variations, providing clarity as to which biological signals can be recovered. These concepts are illustrated on studies of diverse designs, where the biological signals that are recovered by CellANOVA are shown to be validated by orthogonal assays. In particular, we show that CellANOVA is effective in the challenging case of single-cell and single-nuclei data integration, where the recovered biological signals are replicated in an independent study.

Fibronectin-coated microgroove titanium surface promotes the behaviors of human gingival fibroblasts.

The present study was designed to clarify the activity of human gingival fibroblasts (HGFs) on the fibronectin (FN)-coated silanized microgroove titanium surface. The surface elemental composition of titanium discs was detected using XPS. HGFs' adhesion to the titanium discs was detected by immunofluorescence staining of vinculin. HGFs' number on the titanium discs was detected using the CCK8 assay. HGFs' secretion of type 1 collagen after five days of culturing was detected using ELISA and qPCR. HGFs could proliferate and spread well on the surface. The viability of HGFs in the experimental group was significantly more than in the control group. The HGFs in the experimental group significantly secreted more type 1 collagen than in the control group. Therefore, FN-coated can improve the morphology, viability, and type 1 collagen secretion of HGFs silanized microgroove titanium surface, which might ameliorate the efficacy of implants.

P4-ATPase subunit Cdc50 plays a role in yeast budding and cell wall integrity in Candida glabrata.

BACKGROUND: As highly-conserved types of lipid flippases among fungi, P4-ATPases play a significant role in various cellular processes. Cdc50 acts as the regulatory subunit of flippases, forming heterodimers with Drs2 to translocate aminophospholipids. Cdc50 homologs have been reported to be implicated in protein trafficking, drug susceptibility, and virulence in Saccharomyces cerevisiae, Candida albicans and Cryptococcus neoformans. It is likely that Cdc50 has an extensive influence on fungal cellular processes. The present study aimed to determine the function of Cdc50 in Candida glabrata by constructing a Δcdc50 null mutant and its complemented strain. RESULTS: In Candida glabrata, the loss of Cdc50 led to difficulty in yeast budding, probably caused by actin depolarization. The Δcdc50 mutant also showed hypersensitivity to azoles, caspofungin, and cell wall stressors. Further experiments indicated hyperactivation of the cell wall integrity pathway in the Δcdc50 mutant, which elevated the major cell wall contents. An increase in exposure of ß-(1,3)-glucan and chitin on the cell surface was also observed through flow cytometry. Interestingly, we observed a decrease in the phagocytosis rate when the Δcdc50 mutant was co-incubated with THP-1 macrophages. The Δcdc50 mutant also exhibited weakened virulence in nematode survival tests. CONCLUSION: The results suggested that the lipid flippase subunit Cdc50 is implicated in yeast budding and cell wall integrity in C. glabrata, and thus have a broad influence on drug susceptibility and virulence. This work highlights the importance of lipid flippase, and offers potential targets for new drug research.

Associations between polyunsaturated fatty acid concentrations and Parkinson's disease: A two-sample Mendelian randomization study.

Introduction: Observational studies demonstrated controversial effect of polyunsaturated fatty acids (PUFAs) on Parkinson's disease (PD) with limited causality evidence. Randomized control trials showed possible improvement in PD symptoms with PUFA supplement but had small study population and limited intervention time. Methods: A two-sample Mendelian randomization was designed to evaluate the causal relevance between PUFAs and PD, using genetic variants of PUFAs as instrumental variables and PD data from the largest genome-wide association study as outcome. Inverse variance weighted (IVW) method was applied to obtain the primary outcome. Mendelian randomization Egger regression, weighted median and weighted mode methods were exploited to assist result analyses. Strict Mendelian randomization and multivariable Mendelian randomization (MVMR) were used to estimate direct effects of PUFAs on PD, eliminating pleiotropic effect. Debiased inverse variance weighted estimator was implemented when weak instrument bias was introduced into the analysis. A variety of sensitivity analyses were utilized to assess validity of the results. Results: Our study included 33,674 PD cases and 449,056 controls. Higher plasma level of arachidonic acid (AA) was associated with a 3% increase of PD risk per 1-standard deviation (SD) increase of AA (IVW; Odds ratio (OR)=1.03 [95% confidence interval (CI) 1.01-1.04], P = 2.24E-04). After MVMR (IVW; OR=1.03 [95% CI 1.02-1.04], P =6.15E-08) and deletion of pleiotropic single-nucleotide polymorphisms overlapping with other lipids (IVW; OR=1.03 [95% CI 1.01-1.05], P =5.88E-04), result was still significant. Increased level of eicosapentaenoic acid (EPA) showed possible relevance with increased PD risk after adjustment of pleiotropy (MVMR; OR=1.05 [95% CI 1.01-1.08], P =5.40E-03). Linoleic acid (LA), docosahexaenoic acid (DHA), docosapentaenoic acid (DPA) and alpha-linolenic acid (ALA) were found not causally relevant to PD risk. Various sensitivity analyses verified the validity of our results. In conclusion, our findings from Mendelian randomization suggested that elevated levels of AA and possibly EPA might be linked to a higher risk of PD. No association between PD risk and LA, DHA, DPA, or ALA was found. Discussion: The odds ratio for plasma AA and PD risk was weak. It is important to approach our results with caution in clinical practice and to conduct additional studies on the relationship between PUFAs and PD risk.

Single cell and spatial alternative splicing analysis with long read sequencing.

Long-read sequencing has become a powerful tool for alternative splicing analysis. However, technical and computational challenges have limited our ability to explore alternative splicing at single cell and spatial resolution. The higher sequencing error of long reads, especially high indel rates, have limited the accuracy of cell barcode and unique molecular identifier (UMI) recovery. Read truncation and mapping errors, the latter exacerbated by the higher sequencing error rates, can cause the false detection of spurious new isoforms. Downstream, there is yet no rigorous statistical framework to quantify splicing variation within and between cells/spots. In light of these challenges, we developed Longcell, a statistical framework and computational pipeline for accurate isoform quantification for single cell and spatial spot barcoded long read sequencing data. Longcell performs computationally efficient cell/spot barcode extraction, UMI recovery, and UMI-based truncation- and mapping-error correction. Through a statistical model that accounts for varying read coverage across cells/spots, Longcell rigorously quantifies the level of inter-cell/spot versus intra-cell/ spot diversity in exon-usage and detects changes in splicing distributions between cell populations. Applying Longcell to single cell long-read data from multiple contexts, we found that intra-cell splicing heterogeneity, where multiple isoforms co-exist within the same cell, is ubiquitous for highly expressed genes. On matched single cell and Visium long read sequencing for a tissue of colorectal cancer metastasis to the liver, Longcell found concordant signals between the two data modalities. Finally, on a perturbation experiment for 9 splicing factors, Longcell identified regulatory targets that are validated by targeted sequencing.