PBX/Knotted 1 homeobox-2 (PKNOX2) is a novel regulator of myocardial fibrosis.

Much effort has been made to uncover the cellular heterogeneities of human hearts by single-nucleus RNA sequencing. However, the cardiac transcriptional regulation networks have not been systematically described because of the limitations in detecting transcription factors. In this study, we optimized a pipeline for isolating nuclei and conducting single-nucleus RNA sequencing targeted to detect a higher number of cell signal genes and an optimal number of transcription factors. With this unbiased protocol, we characterized the cellular composition of healthy human hearts and investigated the transcriptional regulation networks involved in determining the cellular identities and functions of the main cardiac cell subtypes. Particularly in fibroblasts, a novel regulator, PKNOX2, was identified as being associated with physiological fibroblast activation in healthy hearts. To validate the roles of these transcription factors in maintaining homeostasis, we used single-nucleus RNA-sequencing analysis of transplanted failing hearts focusing on fibroblast remodelling. The trajectory analysis suggested that PKNOX2 was abnormally decreased from fibroblast activation to pathological myofibroblast formation. Both gain- and loss-of-function in vitro experiments demonstrated the inhibitory role of PKNOX2 in pathological fibrosis remodelling. Moreover, fibroblast-specific overexpression and knockout of PKNOX2 in a heart failure mouse model induced by transverse aortic constriction surgery significantly improved and aggravated myocardial fibrosis, respectively. In summary, this study established a high-quality pipeline for single-nucleus RNA-sequencing analysis of heart muscle. With this optimized protocol, we described the transcriptional regulation networks of the main cardiac cell subtypes and identified PKNOX2 as a novel regulator in suppressing fibrosis and a potential therapeutic target for future translational studies.

Novel Risk Prediction Model to Determine Adverse Heart Failure Outcomes in Arrhythmogenic Right Ventricular Cardiomyopathy.

Background Patients with arrhythmogenic right ventricular cardiomyopathy are at risk for life-threatening ventricular tachyarrhythmias, but progressive heart failure (HF) may occur in later stages of disease. This study aimed to characterize potential risk predictors and develop a model for individualized assessment of adverse HF outcomes in arrhythmogenic right ventricular cardiomyopathy. Methods and Results Longitudinal and observational cohorts with 290 patients with arrhythmogenic right ventricular cardiomyopathy from the Fuwai Hospital in Beijing, China, and 99 patients from the University Heart Center in Zurich, Switzerland, with follow-up data were studied. The primary end point of the study was heart transplantation or death attributable to HF. The model was developed by Cox regression analysis for predicting risk and was internally validated. During 4.92±3.03 years of follow-up, 48 patients reached the primary end point. The determinants of the risk prediction model were left ventricular ejection fraction, serum creatinine levels, moderate-to-severe tricuspid regurgitation, and atrial fibrillation. Implantable cardioverter-defibrillators did not reduce the occurrence of adverse HF outcomes. Conclusions A novel risk prediction model for arrhythmogenic right ventricular cardiomyopathy has been developed using 2 large and well-established cohorts, incorporating common clinical parameters such as left ventricular ejection fraction, serum creatinine levels, tricuspid regurgitation, and atrial fibrillation, which can identify patients who are at risk for terminal HF events, and may guide physicians to assess individualized HF risk and to optimize management strategies.

Clinical Efficacy of Endoscopic Submucosal Dissection for the Treatment of Duodenal Lesions in Terms of Operative Technique and Management of Complications.

Background and Aims: Duodenal endoscopic submucosal dissection (ESD) has been considered to be the most challenging because of its high incidence of complications, which has hindered the development of duodenal ESD. The aim of this study is to discuss operation tips for duodenal ESD and to assess the efficacy and safety of duodenal ESD. Patients and Methods: Eighty-two patients who underwent ESD in the digestive endoscope center for superficial duodenal epithelial tumors (SDETs) from January 2017 to June 2021 were studied. Patients were divided into three groups according to the occurrence of complications, and the clinical characteristics and surgical efficacy of each group were compared. Results: SDETs in 82 patients were completely removed by ESD, with a 97.5% R0 resection rate. The average size of resected lesions was 23.8 ± 6.5 mm. There were significant differences in lesion size and operation time between the normal and intraprocedural complication groups (P < .05). Similarly, between the normal and delayed complication groups, significant differences were noted in lesion location, size, operation time, occupied circumference, and postoperative hospitalization duration (P < .05). Conclusion: Duodenal ESD is prone to complications that increase the complexity of the procedure. By improving the necessary technique and skills, duodenal ESD remains safe and effective.

Single-cell transcriptomic identified HIF1A as a target for attenuating acute rejection after heart transplantation.

Acute rejection (AR) is an important contributor to graft failure, which remains a leading cause of death after heart transplantation (HTX). The regulation of immune metabolism has become a new hotspot in the development of immunosuppressive drugs. In this study, Increased glucose metabolism of cardiac macrophages was found in patients with AR. To find new therapeutic targets of immune metabolism regulation for AR, CD45+ immune cells extracted from murine isografts, allografts, and untransplanted donor hearts were explored by single-cell RNA sequencing. Total 20 immune cell subtypes were identified among 46,040 cells. The function of immune cells in AR were illustrated simultaneously. Cardiac resident macrophages were substantially replaced by monocytes and proinflammatory macrophages during AR. Monocytes/macrophages in AR allograft were more active in antigen presentation and inflammatory recruitment ability, and glycolysis. Based on transcription factor regulation analysis, we found that the increase of glycolysis in monocytes/macrophages was mainly regulated by HIF1A. Inhibition of HIF1A could alleviate inflammatory cells infiltration in AR. To find out the effect of HIF1A on AR, CD45+ immune cells extracted from allografts after HIF1A inhibitor treatment were explored by single-cell RNA sequencing. HIF1A inhibitor could reduce the antigen presenting ability and pro-inflammatory ability of macrophages, and reduce the infiltration of Cd4+ and Cd8a+ T cells in AR. The expression of Hif1α in AR monocytes/macrophages was regulated by pyruvate kinase 2. Higher expression of HIF1A in macrophages was also detected in human hearts with AR. These indicated HIF1A may serve as a potential target for attenuating AR.

SpaGCN: Integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network.

Recent advances in spatially resolved transcriptomics (SRT) technologies have enabled comprehensive characterization of gene expression patterns in the context of tissue microenvironment. To elucidate spatial gene expression variation, we present SpaGCN, a graph convolutional network approach that integrates gene expression, spatial location and histology in SRT data analysis. Through graph convolution, SpaGCN aggregates gene expression of each spot from its neighboring spots, which enables the identification of spatial domains with coherent expression and histology. The subsequent domain guided differential expression (DE) analysis then detects genes with enriched expression patterns in the identified domains. Analyzing seven SRT datasets using SpaGCN, we show it can detect genes with much more enriched spatial expression patterns than competing methods. Furthermore, genes detected by SpaGCN are transferrable and can be utilized to study spatial variation of gene expression in other datasets. SpaGCN is computationally fast, platform independent, making it a desirable tool for diverse SRT studies.

Plasma testosterone and arrhythmic events in male patients with arrhythmogenic right ventricular cardiomyopathy.

AIMS: Arrhythmogenic right ventricular cardiomyopathy (ARVC) is associated with life-threatening ventricular arrhythmia and progressive ventricular dysfunction. Previous studies suggested that sex hormones play an important role in the onset and prognosis of ARVC. This study aimed to investigate the role of testosterone in predicting major adverse cardiac events in the Chinese ARVC cohort. METHODS AND RESULTS: Ninety-nine ARVC patients (median age, 40 years; 70.7% male) and 96 healthy controls (median age, 41 years; 62.5% male) were enrolled. The circulating levels of testosterone were measured by enzyme-linked immunosorbent assays (ELISA). The median follow-up time of all ARVC male patients was 17 months (interquartile range/IQR 9-29). Cox proportional hazards regression was used to analyse the effect of plasma testosterone and other well-described risk factors on malignant arrhythmic events in male ARVC patients. The male ARVC patients had significantly elevated levels of total testosterone [TT, 6.390 (4.438-8.768) ng/mL vs. 3.617 (2.073-4.479) ng/mL, P < 0.0001, data shown as the median with IQR], bioavailable testosterone [BT, 4.11 (1.990-6.545) ng/mL vs. 1.32 (0.7965-2.0350) ng/mL, P < 0.0001, median with IQR], and free testosterone [FT, 0.2055 (0.1000-0.4073) ng/mL vs. 0.0768 (0.0405-0.1105) ng/mL, P < 0.0001, median with IQR] than healthy male volunteer, whereas no differences were observed among female counterparts. There was no significant correlation between the baseline clinical characteristics and testosterone levels in male ARVC patients (Spearman's correlation test, P > 0.05). During the follow-up, the levels of testosterone were higher in male patients who experienced malignant arrhythmic events (N = 22) than in those who did not (N = 25) [TT, 9.034 (7.222-15.370) ng/mL vs. 4.633 (3.363-6.375) ng/mL, P < 0.001; BT, 7.485 (2.070-9.163) ng/mL vs. 3.300 (1.685-4.690) ng/mL, P < 0.05; FT, 0.453 (0.221-0.758) ng/mL vs. 0.161 (0.075-0.337) ng/mL P < 0.05, data expressed as median (IQR) and adjusted by Dunn's multiple comparisons test], whereas such distinction was not observed among patients with significant structural progression events (N = 16). Through multivariable adjustments, the Cox regression analysis showed the level of plasma total testosterone (HR = 1.325, 95% confidence interval = 1.171-1.498, P < 0.001) was an independent predictor for malignant arrhythmic events. CONCLUSIONS: The levels of plasma testosterone in ARVC male patients are higher than those in healthy males. Testosterone level, without relation to the baseline cardiac function and future significant structural progression events, is a strong predictor of future adverse arrhythmic events in male patients with ARVC. Therefore, our results suggest that testosterone may be a useful biomarker in arrhythmic risk prediction in the ARVC.

Deep learning enables accurate clustering with batch effect removal in single-cell RNA-seq analysis.

Single-cell RNA sequencing (scRNA-seq) can characterize cell types and states through unsupervised clustering, but the ever increasing number of cells and batch effect impose computational challenges. We present DESC, an unsupervised deep embedding algorithm that clusters scRNA-seq data by iteratively optimizing a clustering objective function. Through iterative self-learning, DESC gradually removes batch effects, as long as technical differences across batches are smaller than true biological variations. As a soft clustering algorithm, cluster assignment probabilities from DESC are biologically interpretable and can reveal both discrete and pseudotemporal structure of cells. Comprehensive evaluations show that DESC offers a proper balance of clustering accuracy and stability, has a small footprint on memory, does not explicitly require batch information for batch effect removal, and can utilize GPU when available. As the scale of single-cell studies continues to grow, we believe DESC will offer a valuable tool for biomedical researchers to disentangle complex cellular heterogeneity.

The Fgfr2(S252W/+) mutation in mice retards mandible formation and reduces bone mass as in human Apert syndrome.

Apert syndrome is a common craniosynostosis caused by gain-of-function missense mutations of fibroblast growth factor receptor 2 (FGFR2). Mice with the FGFR2 S252W mutation can elucidate the mechanism by which the human Apert syndrome phenotypes arise. However, many studies have focused on mutant skull and long bone malformation, only few studies have focused on mandible changes. Bone formation and micro-architecture between 28- and 56-day-old mutant mice and controls were compared to investigate the changes in the mandibular micro-architecture caused by the Fgfr2(S252W/+) mutation to provide a basis for exploring the pathogenesis and therapeutic measures of human Apert syndrome. Fgfr2(S252W/+) mutant mice were established, and their general characteristics, including weight, naso-anal length, and calcium and phosphate content in serum and bone were tested. Calcein labeling, tartrate-resistant acid phosphatase staining and toluidine blue staining were used to detect osteoblast and osteoclast activities. H&E staining and micro-CT detection were used to test micro-architecture changes. The changes in mineral apposition rate and micro-architecture of the Fgfr2(S252W/+) mice were statistically significant; however, the magnitude of the micro-architecture became less with age. The Fgfr2(S252W/+) mutation may retard mandibular bone formation, decreased bone volume, and compromised skeletal architecture by regulating both osteoblastogenesis and osteoclastogenesis.

[Comparative study of root canal morphology of mandibular first premolar by micro-CT and radio visio graphy].

OBJECTIVE: To compare the consistency of root canal configuration types of mandibular first premolar by using micro-CT and radio visio graphy (RVG). METHODS: One hundred extracted mandibular first premolars with complete dental root and apex which received no endodontic treatment were randomly selected. Each tooth was radiographed with RVG through a buccolingual and mesiodistal direction, and then scanned with micro-CT and reconstructed. The classifications of the root canal types according to Vertucci's type with the two methods were compared. RESULTS: The canal patterns were classified as type I (67%), type III (3%), type V (18%), type VII (2%), additional type (10%) with micro-CT and canal patterns as type I (71%), type III (2%), type V (23%), type VII (1%), additional type (3%) with RVG. 63% of teeth showed one canal in both micro-CT and RVG. Only 25% of teeth were diagnosed as complex canal by the same canal type in both micro-CT and RVG. The Kappa value between micro-CT and RVG was 0.541 which suggested that the two kinds of methods had intermediate consistency. 82.8% of the premolars with root groove had two or more than two canals. CONCLUSION: Although RVG can basically reflect the root canal system type of the mandibular first premolars in vitro, it offers poor accuracy images to complex root canals. Micro-CT three-dimensional images could clearly and precisely display the root canal system morphology of the mandibular first pre-molars in vitro.