scPanel: a tool for automatic identification of sparse gene panels for generalizable patient classification using scRNA-seq datasets.

Single-cell RNA sequencing (scRNA-seq) technologies can generate transcriptomic profiles at a single-cell resolution in large patient cohorts, facilitating discovery of gene and cellular biomarkers for disease. Yet, when the number of biomarker genes is large, the translation to clinical applications is challenging due to prohibitive sequencing costs. Here, we introduce scPanel, a computational framework designed to bridge the gap between biomarker discovery and clinical application by identifying a sparse gene panel for patient classification from the cell population(s) most responsive to perturbations (e.g. diseases/drugs). scPanel incorporates a data-driven way to automatically determine a minimal number of informative biomarker genes. Patient-level classification is achieved by aggregating the prediction probabilities of cells associated with a patient using the area under the curve score. Application of scPanel to scleroderma, colorectal cancer, and COVID-19 datasets resulted in high patient classification accuracy using only a small number of genes (<20), automatically selected from the entire transcriptome. In the COVID-19 case study, we demonstrated cross-dataset generalizability in predicting disease state in an external patient cohort. scPanel outperforms other state-of-the-art gene selection methods for patient classification and can be used to identify parsimonious sets of reliable biomarker candidates for clinical translation.

GATA4 downregulation enhances CCL20-mediated immunosuppression in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is a deadly cancer with a high global mortality rate, and the downregulation of GATA binding protein 4 (GATA4) has been implicated in HCC progression. In this study, we investigated the role of GATA4 in shaping the immune landscape of HCC. METHODS: HCC tumor samples were classified into "low" or "normal/high" based on GATA4 RNA expression relative to adjacent non-tumor liver tissues. The immune landscapes of GATA4-low and GATA4-normal/high tumors were analyzed using cytometry by time-of-flight, bulk/spatial transcriptomic analyses and validated by multiplex immunofluorescence. RESULTS: GATA4-low tumors displayed enrichment in exhausted programmed cell death protein 1+ T cells, immunosuppressive regulatory T cells, myeloid-derived suppressor cells, and macrophages, highlighting the impact of GATA4 downregulation on immunosuppression. Spatial and bulk transcriptomic analyses revealed a negative correlation between GATA4 and C-C Motif Chemokine Ligand 20 (CCL20) expression in HCC. Overexpressing GATA4 confirmed CCL20 as a downstream target, contributing to an immunosuppressive tumor microenvironment, as evidenced by increased regulatory T cells and myeloid-derived suppressor cells in CCL20-high tumors. Lastly, the reduced expression of GATA4 and higher expression of CCL20 were associated with poorer overall survival in patients with HCC, implicating their roles in tumor progression. CONCLUSIONS: Our study reveals that GATA4 downregulation contributes to an immunosuppressive microenvironment, driven by CCL20-mediated enrichment of regulatory T cells and myeloid-derived suppressor cells in HCC. These findings underscore the critical role of GATA4 reduction in promoting immunosuppression and HCC progression.

Transcriptomic imputation of genetic risk variants uncovers novel whole-blood biomarkers of Parkinson's disease.

Blood-based gene expression signatures could potentially be used as biomarkers for PD. However, it is unclear whether genetically-regulated transcriptomic signatures can provide novel gene candidates for use as PD biomarkers. We leveraged on the Genotype-Tissue Expression (GTEx) database to impute whole-blood transcriptomic expression using summary statistics of three large-scale PD GWAS. A random forest classifier was used with the consensus whole-blood imputed gene signature (IGS) to discriminate between cases and controls. Outcome measures included Area under the Curve (AUC) of Receiver Operating Characteristic (ROC) Curve. We demonstrated that the IGS (n = 37 genes) is conserved across PD GWAS studies and brain tissues. IGS discriminated between cases and controls in an independent whole-blood RNA-sequencing study (1176 PD, 254 prodromal, and 860 healthy controls) with mean AUC and accuracy of 64.8% and 69.4% for PD cohort, and 78.8% and 74% for prodromal cohort. PATL2 was the top-performing imputed gene in both PD and prodromal PD cohorts, whose classifier performance varied with biological sex (higher performance for males and females in the PD and prodromal PD, respectively). Single-cell RNA-sequencing studies (scRNA-seq) of healthy humans and PD patients found PATL2 to be enriched in terminal effector CD8+ and cytotoxic CD4+ cells, whose proportions are both increased in PD patients. We demonstrated the utility of GWAS transcriptomic imputation in identifying novel whole-blood transcriptomic signatures which could be leveraged upon for PD biomarker derivation. We identified PATL2 as a potential biomarker in both clinical and prodromic PD.

Systems level identification of a matrisome-associated macrophage polarisation state in multi-organ fibrosis.

Tissue fibrosis affects multiple organs and involves a master-regulatory role of macrophages which respond to an initial inflammatory insult common in all forms of fibrosis. The recently unravelled multi-organ heterogeneity of macrophages in healthy and fibrotic human disease suggests that macrophages expressing osteopontin (SPP1) associate with lung and liver fibrosis. However, the conservation of this SPP1+ macrophage population across different tissues and its specificity to fibrotic diseases with different etiologies remain unclear. Integrating 15 single-cell RNA-sequencing datasets to profile 235,930 tissue macrophages from healthy and fibrotic heart, lung, liver, kidney, skin, and endometrium, we extended the association of SPP1+ macrophages with fibrosis to all these tissues. We also identified a subpopulation expressing matrisome-associated genes (e.g., matrix metalloproteinases and their tissue inhibitors), functionally enriched for ECM remodelling and cell metabolism, representative of a matrisome-associated macrophage (MAM) polarisation state within SPP1+ macrophages. Importantly, the MAM polarisation state follows a differentiation trajectory from SPP1+ macrophages and is associated with a core set of regulon activity. SPP1+ macrophages without the MAM polarisation state (SPP1+MAM-) show a positive association with ageing lung in mice and humans. These results suggest an advanced and conserved polarisation state of SPP1+ macrophages in fibrotic tissues resulting from prolonged inflammatory cues within each tissue microenvironment.

Transient naive reprogramming corrects hiPS cells functionally and epigenetically.

Cells undergo a major epigenome reconfiguration when reprogrammed to human induced pluripotent stem cells (hiPS cells). However, the epigenomes of hiPS cells and human embryonic stem (hES) cells differ significantly, which affects hiPS cell function1-8. These differences include epigenetic memory and aberrations that emerge during reprogramming, for which the mechanisms remain unknown. Here we characterized the persistence and emergence of these epigenetic differences by performing genome-wide DNA methylation profiling throughout primed and naive reprogramming of human somatic cells to hiPS cells. We found that reprogramming-induced epigenetic aberrations emerge midway through primed reprogramming, whereas DNA demethylation begins early in naive reprogramming. Using this knowledge, we developed a transient-naive-treatment (TNT) reprogramming strategy that emulates the embryonic epigenetic reset. We show that the epigenetic memory in hiPS cells is concentrated in cell of origin-dependent repressive chromatin marked by H3K9me3, lamin-B1 and aberrant CpH methylation. TNT reprogramming reconfigures these domains to a hES cell-like state and does not disrupt genomic imprinting. Using an isogenic system, we demonstrate that TNT reprogramming can correct the transposable element overexpression and differential gene expression seen in conventional hiPS cells, and that TNT-reprogrammed hiPS and hES cells show similar differentiation efficiencies. Moreover, TNT reprogramming enhances the differentiation of hiPS cells derived from multiple cell types. Thus, TNT reprogramming corrects epigenetic memory and aberrations, producing hiPS cells that are molecularly and functionally more similar to hES cells than conventional hiPS cells. We foresee TNT reprogramming becoming a new standard for biomedical and therapeutic applications and providing a novel system for studying epigenetic memory.

OVERTURE: A Worldwide, Prospective, Observational Study of Disease Characteristics in Patients With ADPKD.

Introduction: The course of autosomal dominant polycystic kidney disease (ADPKD) varies greatly among affected individuals, necessitating natural history studies to characterize the determinants and effects of disease progression. Therefore, we conducted an observational, longitudinal study (OVERTURE; NCT01430494) of patients with ADPKD. Methods: This prospective study enrolled a large international population (N = 3409) encompassing a broad spectrum of ages (12-78 years), chronic kidney disease (CKD) stages (G1-G5), and Mayo imaging classifications (1A-1E). Outcomes included kidney function, complications, quality of life, health care resource utilization, and work productivity. Results: Most subjects (84.4%) completed ≥12 months of follow-up. Consistent with earlier findings, each additional l/m of height-adjusted total kidney volume (htTKV) on magnetic resonance imaging (MRI) was associated with worse outcomes, including lower estimated glomerular filtration rate (eGFR) (regression coefficient 17.02, 95% confidence interval [CI] 15.94-18.11) and greater likelihood of hypertension (odds ratio [OR] 1.25, 95% CI 1.17-1.34), kidney pain (OR 1.22, 95% CI 1.11-1.33), and hematuria (OR 1.35, 95% CI 1.21-1.51). Greater baseline htTKV was also associated with worse patient-reported health-related quality of life (e.g., ADPKD Impact Scale physical score, regression coefficient 1.02, 95% CI 0.65-1.39), decreased work productivity (e.g., work days missed, regression coefficient 0.55, 95% CI 0.18-0.92), and increased health care resource utilization (e.g., hospitalizations, OR 1.48, 95% CI 1.33-1.64) during follow-up. Conclusion: Although limited by a maximum 3-year duration of follow-up, this observational study characterized the burden of ADPKD in a broad population and indicated the predictive value of kidney volume for outcomes other than kidney function.

Single cell analysis in head and neck cancer reveals potential immune evasion mechanisms during early metastasis.

Profiling tumors at single-cell resolution provides an opportunity to understand complexities underpinning lymph-node metastases in head and neck squamous-cell carcinoma. Single-cell RNAseq (scRNAseq) analysis of cancer-cell trajectories identifies a subpopulation of pre-metastatic cells, driven by actionable pathways including AXL and AURK. Blocking these two proteins blunts tumor invasion in patient-derived cultures. Furthermore, scRNAseq analyses of tumor-infiltrating CD8 + T-lymphocytes show two distinct trajectories to T-cell dysfunction, corroborated by their clonal architecture based on single-cell T-cell receptor sequencing. By determining key modulators of these trajectories, followed by validation using external datasets and functional experiments, we uncover a role for SOX4 in mediating T-cell exhaustion. Finally, interactome analyses between pre-metastatic tumor cells and CD8 + T-lymphocytes uncover a putative role for the Midkine pathway in immune-modulation and this is confirmed by scRNAseq of tumors from humanized mice. Aside from specific findings, this study demonstrates the importance of tumor heterogeneity analyses in identifying key vulnerabilities during early metastasis.

A single-cell atlas identifies pretreatment features of primary imatinib resistance in chronic myeloid leukemia.

Primary resistance to tyrosine kinase inhibitors (TKIs) is a significant barrier to optimal outcomes in chronic myeloid leukemia (CML), but factors contributing to response heterogeneity remain unclear. Using single-cell RNA (scRNA) sequencing, we identified 8 statistically significant features in pretreatment bone marrow, which correlated with either sensitivity (major molecular response or MMR) or extreme resistance to imatinib (eventual blast crisis [BC] transformation). Employing machine-learning, we identified leukemic stem cell (LSC) and natural killer (NK) cell gene expression profiles predicting imatinib response with >80% accuracy, including no false positives for predicting BC. A canonical erythroid-specifying (TAL1/KLF1/GATA1) regulon was a hallmark of LSCs from patients with MMR and was associated with erythroid progenitor [ERP] expansion in vivo (P < .05), and a 2- to 10-fold (6.3-fold in group A vs 1.09-fold in group C) erythroid over myeloid bias in vitro. Notably, ERPs demonstrated exquisite TKI sensitivity compared with myeloid progenitors (P < .001). These LSC features were lost with progressive resistance, and MYC- and IRF1-driven inflammatory regulons were evident in patients who progressed to transformation. Patients with MMR also exhibited a 56-fold expansion (P < .01) of a normally rare subset of hyperfunctional adaptive-like NK cells, which diminished with progressive resistance, whereas patients destined for BC accumulated inhibitory NKG2A+ NK cells favoring NK cell tolerance. Finally, we developed antibody panels to validate our scRNA-seq findings. These panels may be useful for prospective studies of primary resistance, and in assessing the contribution of predetermined vs acquired factors in TKI response heterogeneity.

Deep learning models will shape the future of stem cell research.

Our ability to understand and control stem cell biology is being augmented by developments on two fronts, our ability to collect more data describing cell state and our capability to comprehend these data using deep learning models. Here we consider the impact deep learning will have in the future of stem cell research. We explore the importance of generating data suitable for these methods, the requirement for close collaboration between experimental and computational researchers, and the challenges we face to do this fairly and effectively. Achieving this will ensure that the resulting deep learning models are biologically meaningful and computationally tractable.

A high-resolution map of human RNA translation.

Translated small open reading frames (smORFs) can have important regulatory roles and encode microproteins, yet their genome-wide identification has been challenging. We determined the ribosome locations across six primary human cell types and five tissues and detected 7,767 smORFs with translational profiles matching those of known proteins. The human genome was found to contain highly cell-type- and tissue-specific smORFs and a subset that encodes highly conserved amino acid sequences. Changes in the translational efficiency of upstream-encoded smORFs (uORFs) and the corresponding main ORFs predominantly occur in the same direction. Integration with 456 mass-spectrometry datasets confirms the presence of 603 small peptides at the protein level in humans and provides insights into the subcellular localization of these small proteins. This study provides a comprehensive atlas of high-confidence translated smORFs derived from primary human cells and tissues in order to provide a more complete understanding of the translated human genome.

The conserved helicase ZNFX-1 memorializes silenced RNAs in perinuclear condensates.

RNA-mediated interference (RNAi) is a conserved mechanism that uses small RNAs (sRNAs) to silence gene expression. In the Caenorhabditis elegans germline, transcripts targeted by sRNAs are used as templates for sRNA amplification to propagate silencing into the next generation. Here we show that RNAi leads to heritable changes in the distribution of nascent and mature transcripts that correlate with two parallel sRNA amplification loops. The first loop, dependent on the nuclear Argonaute HRDE-1, targets nascent transcripts and reduces but does not eliminate productive transcription at the locus. The second loop, dependent on the conserved helicase ZNFX-1, targets mature transcripts and concentrates them in perinuclear condensates. ZNFX-1 interacts with sRNA-targeted transcripts that have acquired poly(UG) tails and is required to sustain pUGylation and robust sRNA amplification in the inheriting generation. By maintaining a pool of transcripts for amplification, ZNFX-1 prevents premature extinction of the RNAi response and extends silencing into the next generation.

Pooled Data Analysis of the Long-Term Treatment Effects of Tolvaptan in ADPKD.

Introduction: In 1- and 3-year randomized trials, tolvaptan slowed kidney function decline in subjects with autosomal dominant polycystic kidney disease (ADPKD) at risk of rapid progression. The 3-year trial also evaluated effects on total kidney volume (TKV); slowing of TKV growth was demonstrated. Subjects were followed in open-label extension trials. To characterize longer-term effects of treatment, an analysis was conducted comparing tolvaptan-treated subjects with subjects from standard of care (SOC) ADPKD studies without tolvaptan. Methods: This was a pooled, longitudinal analysis of data from 8 tolvaptan clinical trials and 5 studies without tolvaptan (natural history or SOC) in ADPKD. Data from subjects who participated in multiple studies were linked for longer follow-up. Outcomes were rates of change in estimated glomerular filtration rate (eGFR) and TKV over 5.5 years. To control for heterogeneity in disease characteristics between tolvaptan and SOC treatment groups, analysis populations matched for baseline demographic and disease characteristics were constructed. Results: Matched analysis (n = 1186 in each treatment group) indicated that tolvaptan slowed annualized eGFR decline by 1.01 ml/min per 1.73 m2 (P < 0.001) versus SOC over 5.5 years. An analysis conducted on the full, unmatched data set (tolvaptan: n = 2928; SOC: n = 4189) confirmed significant reduction in annual eGFR decline. Among subjects with TKV data, TKV was significantly reduced at years 1, 3, and 5 for tolvaptan versus SOC in both matched and full data sets. Conclusion: Comparison of a pooled tolvaptan cohort to a pooled control cohort with ADPKD supports longer-term treatment effects of tolvaptan.

Nuage condensates: accelerators or circuit breakers for sRNA silencing pathways?

Nuage are RNA-rich condensates that assemble around the nuclei of developing germ cells. Many proteins required for the biogenesis and function of silencing small RNAs (sRNAs) enrich in nuage, and it is often assumed that nuage is the cellular site where sRNAs are synthesized and encounter target transcripts for silencing. Using C. elegans as a model, we examine the complex multicondensate architecture of nuage and review evidence for compartmentalization of silencing pathways. We consider the possibility that nuage condensates balance the activity of competing sRNA pathways and serve to limit, rather than enhance, sRNA amplification to protect transcripts from dangerous runaway silencing.

Tolvaptan in ADPKD Patients With Very Low Kidney Function.

INTRODUCTION: Tolvaptan slowed estimated glomerular filtration rate (eGFR) decline in subjects with autosomal dominant polycystic kidney disease (ADPKD) in TEMPO 3:4 and REPRISE trials. Tolvaptan effects in subjects with eGFR 15 to 24 ml/min per 1.73 m2 were not investigated. This post hoc analysis retrospectively investigated eGFR decline in REPRISE versus an open-label, phase 3b extension trial (open-label extension [OLE] NCT02251275) in subjects who received placebo in REPRISE and tolvaptan in OLE with eGFR 15 to 24 and 25 to 29 ml/min per 1.73 m2, respectively. METHODS: One data subset comprised subjects with OLE baseline eGFR 15 to 29 ml/min per 1.73 m2 who had received placebo in REPRISE and began tolvaptan in OLE. The second comprised subjects who had received tolvaptan in REPRISE and were matched to REPRISE placebo-treated subjects for REPRISE baseline characteristics. Annualized eGFR slopes in REPRISE versus OLE were compared within the REPRISE placebo (i.e., placebo vs. tolvaptan treatment) and tolvaptan (i.e., 2 periods of tolvaptan treatment) subsets. RESULTS: Mean annualized eGFR slopes (ml/min per 1.73 m2) during tolvaptan treatment in OLE versus placebo treatment in REPRISE were -3.4 versus -5.2 for subjects with OLE baseline eGFR 15 to 29 (difference, 1.7; P < 0.001), -3.6 versus -5.4 with baseline eGFR 15 to 24 (difference, 1.8; P < 0.001), and -3.3 versus -4.9 with baseline eGFR 25 to 29 (difference, 1.6; P < 0.001). In REPRISE tolvaptan subjects who continued tolvaptan in OLE, treatment effect was maintained (no difference between mean annualized eGFR slopes). CONCLUSION: Initiating or maintaining tolvaptan therapy significantly delayed eGFR decline in subjects with baseline eGFR 15 to 24 and 25 to 29 ml/min per 1.73 m2.

The MURAL collection of prostate cancer patient-derived xenografts enables discovery through preclinical models of uro-oncology.

Preclinical testing is a crucial step in evaluating cancer therapeutics. We aimed to establish a significant resource of patient-derived xenografts (PDXs) of prostate cancer for rapid and systematic evaluation of candidate therapies. The PDX collection comprises 59 tumors collected from 30 patients between 2012-2020, coinciding with availability of abiraterone and enzalutamide. The PDXs represent the clinico-pathological and genomic spectrum of prostate cancer, from treatment-naïve primary tumors to castration-resistant metastases. Inter- and intra-tumor heterogeneity in adenocarcinoma and neuroendocrine phenotypes is evident from bulk and single-cell RNA sequencing data. Organoids can be cultured from PDXs, providing further capabilities for preclinical studies. Using a 1 x 1 x 1 design, we rapidly identify tumors with exceptional responses to combination treatments. To govern the distribution of PDXs, we formed the Melbourne Urological Research Alliance (MURAL). This PDX collection is a substantial resource, expanding the capacity to test and prioritize effective treatments for prospective clinical trials in prostate cancer.

Overweight and Obesity and Progression of ADPKD.

BACKGROUND AND OBJECTIVES: On the basis of earlier observations, we evaluated the association between overweight and obesity and rapid progression of autosomal dominant polycystic kidney disease in participants in the Tolvaptan Efficacy and Safety in Management of Autosomal Dominant Polycystic Kidney Disease and Its Outcomes (TEMPO) 3:4 trial. More importantly, we also determined whether efficacy of tolvaptan was attenuated in individuals with baseline overweight or obesity. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: A total of 1312 study participants with relatively early-stage autosomal dominant polycystic kidney disease (mean eGFR 78±22 ml/min per 1.73 m2) who were at high risk of rapid progression were categorized by body mass index (BMI; calculated using nonkidney weight) as normal weight (18.5-24.9 kg/m2; n=670), overweight (25.0-29.9 kg/m2; n=429), or obese (≥30 kg/m2; n=213). Linear and multinomial logistic regression models were used to determine the association of baseline overweight and obesity with change in total kidney volume (TKV) over the 3-year study period. RESULTS: In fully adjusted models, higher BMI was associated with greater annual percent change in TKV (difference of 1.20 [95% confidence interval (95% CI), 0.85 to 1.55] per five-unit higher BMI). Overweight and obesity were associated with higher odds of annual percent change in TKV of ≥7% versus <5% (overweight: odds ratio, 2.04 [95% CI, 1.45 to 2.87]; obese: odds ratio, 4.31 [95% CI, 2.83 to 6.57] versus normal weight). eGFR decline did not differ according to BMI (fully adjusted difference in decline of -0.95 [95% CI, -2.32 to 0.40] ml/min per 1.73 m2 per year per five-unit higher BMI). The three-way interaction (treatment×time×BMI group) was not statistically significant in linear mixed models with an outcome of TKV (log-transformed estimated coefficient comparing the treatment effect for overweight versus normal weight: 0.56% [95% CI, -0.70% to 1.84%] per year; P=0.38; obese versus normal weight: 0.07% [95% CI, -1.47% to 1.63%] per year; P=0.93) or eGFR (estimated coefficient comparing overweight versus normal weight: -0.07 [95% CI, -0.95 to 0.82] ml/min per 1.73 m2 per year; P=0.88; obese versus normal weight: 0.22 [95% CI, -0.93 to 1.36] ml/min per 1.73 m2 per year; P=0.71). CONCLUSIONS: Overweight and particularly obesity are strongly and independently associated with kidney growth, but not eGFR slope, in the TEMPO 3:4 trial, and tolvaptan efficacy is irrespective of BMI categorization. CLINICAL TRIAL REGISTRY NAME AND REGISTRATION NUMBER: Tolvaptan Efficacy and Safety in Management of Autosomal Dominant Polycystic Kidney Disease and Its Outcomes (TEMPO) 3:4, NCT00428948.

Transcriptional signature in microglia associated with Aß plaque phagocytosis.

The role of microglia cells in Alzheimer's disease (AD) is well recognized, however their molecular and functional diversity remain unclear. Here, we isolated amyloid plaque-containing (using labelling with methoxy-XO4, XO4+) and non-containing (XO4-) microglia from an AD mouse model. Transcriptomics analysis identified different transcriptional trajectories in ageing and AD mice. XO4+ microglial transcriptomes demonstrated dysregulated expression of genes associated with late onset AD. We further showed that the transcriptional program associated with XO4+ microglia from mice is present in a subset of human microglia isolated from brains of individuals with AD. XO4- microglia displayed transcriptional signatures associated with accelerated ageing and contained more intracellular post-synaptic material than XO4+ microglia, despite reduced active synaptosome phagocytosis. We identified HIF1α as potentially regulating synaptosome phagocytosis in vitro using primary human microglia, and BV2 mouse microglial cells. Together, these findings provide insight into molecular mechanisms underpinning the functional diversity of microglia in AD.

The Effect of Tolvaptan on BP in Polycystic Kidney Disease: A Post Hoc Analysis of the TEMPO 3:4 Trial.

BACKGROUND: The V2 receptor antagonist tolvaptan is prescribed to patients with autosomal dominant polycystic kidney disease to slow disease progression. Tolvaptan may alter BP via various acute and chronic effects. METHODS: To investigate the magnitude and time course of the effect of tolvaptan use on BP, we conducted a post hoc study of the TEMPO 3:4 trial, which included 1445 patients with autosomal dominant polycystic kidney disease randomized 2:1 to tolvaptan or placebo for 3 years. We evaluated systolic and diastolic BP, mean arterial pressure, hypertension status, and use and dosing of antihypertensive drugs over the course of the trial. RESULTS: At baseline, BP did not differ between study arms. After 3 weeks of tolvaptan use, mean body weight had decreased from 79.7 to 78.8 kg, and mean plasma sodium increased from 140.4 to 142.6 mmol/L (both P<0.001), suggesting a decrease in circulating volume. We observed none of these changes in the placebo arm. Nonetheless, BP remained similar in the study arms. After 3 years of treatment, however, mean systolic BP was significantly lower in participants receiving tolvaptan versus placebo (126 versus 129 mm Hg, respectively; P=0.002), as was mean diastolic BP (81.2 versus 82.6 mm Hg, respectively; P=0.01). These differences leveled off at follow-up 3 weeks after discontinuation of the study medication. Use of antihypertensive drugs remained similar in both study arms during the entire study. CONCLUSIONS: Long-term treatment with tolvaptan gradually lowered BP compared with placebo, which may be attributed to a beneficial effect on disease progression, a continued natriuretic effect, or both. CLINICAL TRIAL REGISTRY NAME AND REGISTRATION NUMBER: TEMPO 3:4, NCT00428948.

ShinyCell: simple and sharable visualization of single-cell gene expression data.

MOTIVATION: As the generation of complex single-cell RNA sequencing datasets becomes more commonplace it is the responsibility of researchers to provide access to these data in a way that can be easily explored and shared. Whilst it is often the case that data is deposited for future bioinformatic analysis many studies do not release their data in a way that is easy to explore by non-computational researchers. RESULTS: In order to help address this we have developed ShinyCell, an R package that converts single-cell RNA sequencing datasets into explorable and shareable interactive interfaces. These interfaces can be easily customized in order to maximize their usability and can be easily uploaded to online platforms to facilitate wider access to published data. AVAILABILITY AND IMPLEMENTATION: ShinyCell is available at https://github.com/SGDDNB/ShinyCell and https://figshare.com/projects/ShinyCell/100439. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Modelling human blastocysts by reprogramming fibroblasts into iBlastoids.

Human pluripotent and trophoblast stem cells have been essential alternatives to blastocysts for understanding early human development1-4. However, these simple culture systems lack the complexity to adequately model the spatiotemporal cellular and molecular dynamics that occur during early embryonic development. Here we describe the reprogramming of fibroblasts into in vitro three-dimensional models of the human blastocyst, termed iBlastoids. Characterization of iBlastoids shows that they model the overall architecture of blastocysts, presenting an inner cell mass-like structure, with epiblast- and primitive endoderm-like cells, a blastocoel-like cavity and a trophectoderm-like outer layer of cells. Single-cell transcriptomics further confirmed the presence of epiblast-, primitive endoderm-, and trophectoderm-like cells. Moreover, iBlastoids can give rise to pluripotent and trophoblast stem cells and are capable of modelling, in vitro, several aspects of the early stage of implantation. In summary, we have developed a scalable and tractable system to model human blastocyst biology; we envision that this will facilitate the study of early human development and the effects of gene mutations and toxins during early embryogenesis, as well as aiding in the development of new therapies associated with in vitro fertilization.