Latent feature extraction with a prior-based self-attention framework for spatial transcriptomics.

Rapid advances in spatial transcriptomics (ST) have revolutionized the interrogation of spatial heterogeneity and increase the demand for comprehensive methods to effectively characterize spatial domains. As a prerequisite for ST data analysis, spatial domain characterization is a crucial step for downstream analyses and biological implications. Here we propose a prior-based self-attention framework for spatial transcriptomics (PAST), a variational graph convolutional autoencoder for ST, which effectively integrates prior information via a Bayesian neural network, captures spatial patterns via a self-attention mechanism, and enables scalable application via a ripple walk sampler strategy. Through comprehensive experiments on data sets generated by different technologies, we show that PAST can effectively characterize spatial domains and facilitate various downstream analyses, including ST visualization, spatial trajectory inference and pseudotime analysis. Also, we highlight the advantages of PAST for multislice joint embedding and automatic annotation of spatial domains in newly sequenced ST data. Compared with existing methods, PAST is the first ST method that integrates reference data to analyze ST data. We anticipate that PAST will open up new avenues for researchers to decipher ST data with customized reference data, which expands the applicability of ST technology.

NeuronMotif: Deciphering cis-regulatory codes by layer-wise demixing of deep neural networks.

Discovering DNA regulatory sequence motifs and their relative positions is vital to understanding the mechanisms of gene expression regulation. Although deep convolutional neural networks (CNNs) have achieved great success in predicting cis-regulatory elements, the discovery of motifs and their combinatorial patterns from these CNN models has remained difficult. We show that the main difficulty is due to the problem of multifaceted neurons which respond to multiple types of sequence patterns. Since existing interpretation methods were mainly designed to visualize the class of sequences that can activate the neuron, the resulting visualization will correspond to a mixture of patterns. Such a mixture is usually difficult to interpret without resolving the mixed patterns. We propose the NeuronMotif algorithm to interpret such neurons. Given any convolutional neuron (CN) in the network, NeuronMotif first generates a large sample of sequences capable of activating the CN, which typically consists of a mixture of patterns. Then, the sequences are "demixed" in a layer-wise manner by backward clustering of the feature maps of the involved convolutional layers. NeuronMotif can output the sequence motifs, and the syntax rules governing their combinations are depicted by position weight matrices organized in tree structures. Compared to existing methods, the motifs found by NeuronMotif have more matches to known motifs in the JASPAR database. The higher-order patterns uncovered for deep CNs are supported by the literature and ATAC-seq footprinting. Overall, NeuronMotif enables the deciphering of cis-regulatory codes from deep CNs and enhances the utility of CNN in genome interpretation.

Impaired end joining induces cardiac atrophy in a Hutchinson-Gilford progeria mouse model.

Patients with Hutchinson-Gilford progeria syndrome (HGPS) present with a number of premature aging phenotypes, including DNA damage accumulation, and many of them die of cardiovascular complications. Although vascular pathologies have been reported, whether HGPS patients exhibit cardiac dysfunction and its underlying mechanism is unclear, rendering limited options for treating HGPS-related cardiomyopathy. In this study, we reported a cardiac atrophy phenotype in the LmnaG609G/G609G mice (hereafter, HGPS mice). Using a GFP-based reporter system, we demonstrated that the efficiency of nonhomologous end joining (NHEJ) declined by 50% in HGPS cardiomyocytes in vivo, due to the attenuated interaction between γH2AX and Progerin, the causative factor of HGPS. As a result, genomic instability in cardiomyocytes led to an increase of CHK2 protein level, promoting the LKB1-AMPKα interaction and AMPKα phosphorylation, which further led to the activation of FOXO3A-mediated transcription of atrophy-related genes. Moreover, inhibiting AMPK enlarged cardiomyocyte sizes both in vitro and in vivo. Most importantly, our proof-of-concept study indicated that isoproterenol treatment significantly reduced AMPKα and FOXO3A phosphorylation in the heart, attenuated the atrophy phenotype, and extended the mean lifespan of HGPS mice by ~21%, implying that targeting cardiac atrophy may be an approach to HGPS treatment.

Cofea: correlation-based feature selection for single-cell chromatin accessibility data.

Single-cell chromatin accessibility sequencing (scCAS) technologies have enabled characterizing the epigenomic heterogeneity of individual cells. However, the identification of features of scCAS data that are relevant to underlying biological processes remains a significant gap. Here, we introduce a novel method Cofea, to fill this gap. Through comprehensive experiments on 5 simulated and 54 real datasets, Cofea demonstrates its superiority in capturing cellular heterogeneity and facilitating downstream analysis. Applying this method to identification of cell type-specific peaks and candidate enhancers, as well as pathway enrichment analysis and partitioned heritability analysis, we illustrate the potential of Cofea to uncover functional biological process.

Deep generative modeling and clustering of single cell Hi-C data.

Deciphering 3D genome conformation is important for understanding gene regulation and cellular function at a spatial level. The recent advances of single cell Hi-C technologies have enabled the profiling of the 3D architecture of DNA within individual cell, which allows us to study the cell-to-cell variability of 3D chromatin organization. Computational approaches are in urgent need to comprehensively analyze the sparse and heterogeneous single cell Hi-C data. Here, we proposed scDEC-Hi-C, a new framework for single cell Hi-C analysis with deep generative neural networks. scDEC-Hi-C outperforms existing methods in terms of single cell Hi-C data clustering and imputation. Moreover, the generative power of scDEC-Hi-C could help unveil the differences of chromatin architecture across cell types. We expect that scDEC-Hi-C could shed light on deepening our understanding of the complex mechanism underlying the formation of chromatin contacts.

Improving artificial intelligence pipeline for liver malignancy diagnosis using ultrasound images and video frames.

Recent developments of deep learning methods have demonstrated their feasibility in liver malignancy diagnosis using ultrasound (US) images. However, most of these methods require manual selection and annotation of US images by radiologists, which limit their practical application. On the other hand, US videos provide more comprehensive morphological information about liver masses and their relationships with surrounding structures than US images, potentially leading to a more accurate diagnosis. Here, we developed a fully automated artificial intelligence (AI) pipeline to imitate the workflow of radiologists for detecting liver masses and diagnosing liver malignancy. In this pipeline, we designed an automated mass-guided strategy that used segmentation information to direct diagnostic models to focus on liver masses, thus increasing diagnostic accuracy. The diagnostic models based on US videos utilized bi-directional convolutional long short-term memory modules with an attention-boosted module to learn and fuse spatiotemporal information from consecutive video frames. Using a large-scale dataset of 50 063 US images and video frames from 11 468 patients, we developed and tested the AI pipeline and investigated its applications. A dataset of annotated US images is available at https://doi.org/10.5281/zenodo.7272660.

scPRAM accurately predicts single-cell gene expression perturbation response based on attention mechanism.

MOTIVATION: With the rapid advancement of single-cell sequencing technology, it becomes gradually possible to delve into the cellular responses to various external perturbations at the gene expression level. However, obtaining perturbed samples in certain scenarios may be considerably challenging, and the substantial costs associated with sequencing also curtail the feasibility of large-scale experimentation. A repertoire of methodologies has been employed for forecasting perturbative responses in single-cell gene expression. However, existing methods primarily focus on the average response of a specific cell type to perturbation, overlooking the single-cell specificity of perturbation responses and a more comprehensive prediction of the entire perturbation response distribution. RESULTS: Here, we present scPRAM, a method for predicting perturbation responses in single-cell gene expression based on attention mechanisms. Leveraging variational autoencoders and optimal transport, scPRAM aligns cell states before and after perturbation, followed by accurate prediction of gene expression responses to perturbations for unseen cell types through attention mechanisms. Experiments on multiple real perturbation datasets involving drug treatments and bacterial infections demonstrate that scPRAM attains heightened accuracy in perturbation prediction across cell types, species, and individuals, surpassing existing methodologies. Furthermore, scPRAM demonstrates outstanding capability in identifying differentially expressed genes under perturbation, capturing heterogeneity in perturbation responses across species, and maintaining stability in the presence of data noise and sample size variations. AVAILABILITY AND IMPLEMENTATION: https://github.com/jiang-q19/scPRAM and https://doi.org/10.5281/zenodo.10935038.

Maize requires Embryo defective27 for embryogenesis and seedling development.

The essential role of plastid translation in embryogenesis has been established in many plants, but a retrograde signal triggered by defective plastid translation machinery that may leads to embryogenesis arrest remains unknown. In this study, we characterized an embryo defective27 (emb27) mutant in maize (Zea mays), and cloning indicates that Emb27 encodes the plastid ribosomal protein S13. The null mutant emb27-1 conditions an emb phenotype with arrested embryogenesis; however, the leaky mutant emb27-2 exhibits normal embryogenesis but an albino seedling-lethal phenotype. The emb27-1/emb27-2 trans-heterozygotes display varying phenotypes from emb to normal seeds but albino seedlings. Analysis of the Emb27 transcription levels in these mutants revealed that the Emb27 expression level in the embryo corresponds with the phenotypic expression of the emb27 mutants. In the W22 genetic background, an Emb27 transcription level higher than 6% of the wild-type level renders normal embryogenesis, whereas lower than that arrests embryogenesis. Mutation of Emb27 reduces the level of plastid 16S rRNA and the accumulation of the plastid-encoded proteins. As a secondary effect, splicing of several plastid introns was impaired in emb27-1 and 2 other plastid translation-defective mutants, emb15 and emb16, suggesting that plastome-encoded factors are required for the splicing of these introns, such as Maturase K (MatK). Our results indicate that EMB27 is essential for plastid protein translation, embryogenesis, and seedling development in maize and reveal an expression threshold of Emb27 for maize embryogenesis.

HiChIPdb: a comprehensive database of HiChIP regulatory interactions.

Elucidating the role of 3D architecture of DNA in gene regulation is crucial for understanding cell differentiation, tissue homeostasis and disease development. Among various chromatin conformation capture methods, HiChIP has received increasing attention for its significant improvement over other methods in profiling of regulatory (e.g. H3K27ac) and structural (e.g. cohesin) interactions. To facilitate the studies of 3D regulatory interactions, we developed a HiChIP interactions database, HiChIPdb (http://health.tsinghua.edu.cn/hichipdb/). The current version of HiChIPdb contains ∼262M annotated HiChIP interactions from 200 high-throughput HiChIP samples across 108 cell types. The functionalities of HiChIPdb include: (i) standardized categorization of HiChIP interactions in a hierarchical structure based on organ, tissue and cell line and (ii) comprehensive annotations of HiChIP interactions with regulatory genes and GWAS Catalog SNPs. To the best of our knowledge, HiChIPdb is the first comprehensive database that utilizes a unified pipeline to map the functional interactions across diverse cell types and tissues in different resolutions. We believe this database has the potential to advance cutting-edge research in regulatory mechanisms in development and disease by removing the barrier in data aggregation, preprocessing, and analysis.

A Phytophthora infestans RXLR effector AVR8 suppresses plant immunity by targeting a desumoylating isopeptidase DeSI2.

The potato's most devastating disease is late blight, which is caused by Phytophthora infestans. Whereas various resistance (R) genes are known, most are typically defeated by this fast-evolving oomycete pathogen. However, the broad-spectrum and durable R8 is a vital gene resource for potato resistance breeding. To support an educated deployment of R8, we embarked on a study on the corresponding avirulence gene Avr8. We overexpressed Avr8 by transient and stable transformation, and found that Avr8 promotes colonization of P. infestans in Nicotiana benthamiana and potato, respectively. A yeast-two-hybrid (Y2H) screen showed that AVR8 interacts with a desumoylating isopeptidase (StDeSI2) of potato. We overexpressed DeSI2 and found that DeSI2 positively regulates resistance to P. infestans, while silencing StDeSI2 downregulated the expression of a set of defense-related genes. By using a specific proteasome inhibitor, we found that AVR8 destabilized StDeSI2 through the 26S proteasome and attenuated early PTI responses. Altogether, these results indicate that AVR8 manipulates desumoylation, which is a new strategy that adds to the plethora of mechanisms that Phytophthora exploits to modulate host immunity, and StDeSI2 provides a new target for durable resistance breeding against P. infestans in potato.

Nucleolin lactylation contributes to intrahepatic cholangiocarcinoma pathogenesis via RNA splicing regulation of MADD.

BACKGROUND & AIMS: Intrahepatic cholangiocarcinoma (iCCA) is a fatal malignancy of the biliary system. The lack of a detailed understanding of oncogenic signaling or global gene expression alterations has impeded clinical iCCA diagnosis and therapy. The role of protein lactylation, a newly unraveled post-translational modification that orchestrates gene expression, remains largely elusive in the pathogenesis of iCCA. METHODS: Proteomics analysis of clinical iCCA specimens and adjacent tissues was performed to screen for proteins aberrantly lactylated in iCCA. Mass spectrometry, macromolecule interaction and cell behavioral studies were employed to identify the specific lactylation sites on the candidate protein(s) and to decipher the downstream mechanisms responsible for iCCA development, which were subsequently validated using a xenograft tumor model and clinical samples. RESULTS: Nucleolin (NCL), the most abundant RNA-binding protein in the nucleolus, was identified as a functional lactylation target that correlates with iCCA occurrence and progression. NCL was lactylated predominantly at lysine 477 by the acyltransferase P300 in response to a hyperactivity of glycolysis, and promoted the proliferation and invasion of iCCA cells. Mechanistically, lactylated NCL bound to the primary transcript of MAP kinase-activating death domain protein (MADD) and led to efficient translation of MADD by circumventing alternative splicing that generates a premature termination codon. NCL lactylation, MADD translation and subsequent ERK activation promoted xenograft tumor growth and were associated with overall survival in patients with iCCA. CONCLUSION: NCL is lactylated to upregulate MADD through an RNA splicing-dependent mechanism, which potentiates iCCA pathogenesis via the MAPK pathway. Our findings reveal a novel link between metabolic reprogramming and canonical tumor-initiating events, and uncover biomarkers that can potentially be used for prognostic evaluation or targeted treatment of iCCA. IMPACT AND IMPLICATIONS: Intrahepatic cholangiocarcinoma (iCCA) is a highly aggressive liver malignancy with largely uncharacterized pathogenetic mechanisms. Herein, we demonstrated that glycolysis promotes P300-catalyzed lactylation of nucleolin, which upregulates MAP kinase-activating death domain protein (MADD) through precise mRNA splicing and activates ERK signaling to drive iCCA development. These findings unravel a novel link between metabolic rewiring and canonical oncogenic pathways, and reveal new biomarkers for prognostic assessment and targeting of clinical iCCA.

Risks of digestive diseases in long COVID: evidence from a population-based cohort study.

BACKGROUND: In the post-pandemic era, a wide range of COVID-19 sequelae is of growing health concern. However, the risks of digestive diseases in long COVID have not been comprehensively understood. To investigate the long-term risk of digestive diseases among COVID patients. METHODS: In this large-scale retrospective cohort study with up to 2.6 years follow-up (median follow-up: 0.7 years), the COVID-19 group (n = 112,311), the contemporary comparison group (n = 359,671) and the historical comparison group (n = 370,979) predated the COVID-19 outbreak were built using UK Biobank database. Each digestive outcome was defined as the diagnosis 30 days or more after the onset of COVID-19 infection or the index date. Hazard ratios (HRs) and corresponding 95% confidence intervals (CI) were computed utilizing the Cox regression models after inverse probability weighting. RESULTS: Compared with the contemporary comparison group, patients with previous COVID-19 infection had higher risks of digestive diseases, including gastrointestinal (GI) dysfunction (HR 1.38 (95% CI 1.26 to 1.51)); peptic ulcer disease (HR 1.23 (1.00 to 1.52)); gastroesophageal reflux disease (GERD) (HR 1.41 (1.30 to 1.53)); gallbladder disease (HR 1.21 (1.06 to 1.38)); severe liver disease (HR 1.35 (1.03 to 1.76)); non-alcoholic liver disease (HR 1.27 (1.09 to 1.47)); and pancreatic disease (HR 1.36 (1.11 to 1.66)). The risks of GERD were increased stepwise with the severity of the acute phase of COVID-19 infection. Even after 1-year follow-up, GERD (HR 1.64 (1.30 to 2.07)) and GI dysfunction (HR 1.35 (1.04 to 1.75)) continued to pose risks to COVID-19 patients. Compared to those with one SARS-CoV-2 infection, reinfected patients were at a higher risk of pancreatic diseases (HR 2.57 (1.23 to 5.38)). The results were consistent when the historical cohort was used as the comparison group. CONCLUSIONS: Our study provides insights into the association between COVID-19 and the long-term risk of digestive system disorders. COVID-19 patients are at a higher risk of developing digestive diseases. The risks exhibited a stepwise escalation with the severity of COVID-19, were noted in cases of reinfection, and persisted even after 1-year follow-up. This highlights the need to understand the varying risks of digestive outcomes in COVID-19 patients over time, particularly those who experienced reinfection, and develop appropriate follow-up strategies.

ASTER: accurately estimating the number of cell types in single-cell chromatin accessibility data.

SUMMARY: Recent innovations in single-cell chromatin accessibility sequencing (scCAS) have revolutionized the characterization of epigenomic heterogeneity. Estimation of the number of cell types is a crucial step for downstream analyses and biological implications. However, efforts to perform estimation specifically for scCAS data are limited. Here, we propose ASTER, an ensemble learning-based tool for accurately estimating the number of cell types in scCAS data. ASTER outperformed baseline methods in systematic evaluation on 27 datasets of various protocols, sizes, numbers of cell types, degrees of cell-type imbalance, cell states and qualities, providing valuable guidance for scCAS data analysis. AVAILABILITY AND IMPLEMENTATION: ASTER along with detailed documentation is freely accessible at https://aster.readthedocs.io/ under the MIT License. It can be seamlessly integrated into existing scCAS analysis workflows. The source code is available at https://github.com/biox-nku/aster. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

simCAS: an embedding-based method for simulating single-cell chromatin accessibility sequencing data.

MOTIVATION: Single-cell chromatin accessibility sequencing (scCAS) technology provides an epigenomic perspective to characterize gene regulatory mechanisms at single-cell resolution. With an increasing number of computational methods proposed for analyzing scCAS data, a powerful simulation framework is desirable for evaluation and validation of these methods. However, existing simulators generate synthetic data by sampling reads from real data or mimicking existing cell states, which is inadequate to provide credible ground-truth labels for method evaluation. RESULTS: We present simCAS, an embedding-based simulator, for generating high-fidelity scCAS data from both cell- and peak-wise embeddings. We demonstrate simCAS outperforms existing simulators in resembling real data and show that simCAS can generate cells of different states with user-defined cell populations and differentiation trajectories. Additionally, simCAS can simulate data from different batches and encode user-specified interactions of chromatin regions in the synthetic data, which provides ground-truth labels more than cell states. We systematically demonstrate that simCAS facilitates the benchmarking of four core tasks in downstream analysis: cell clustering, trajectory inference, data integration, and cis-regulatory interaction inference. We anticipate simCAS will be a reliable and flexible simulator for evaluating the ongoing computational methods applied on scCAS data. AVAILABILITY AND IMPLEMENTATION: simCAS is freely available at https://github.com/Chen-Li-17/simCAS.

Thrombospondin 1 and Reelin act through Vldlr to regulate cardiac growth and repair.

Adult mammalian cardiomyocytes have minimal cell cycle capacity, which leads to poor regeneration after cardiac injury such as myocardial infarction. Many positive regulators of cardiomyocyte cell cycle and cardioprotective signals have been identified, but extracellular signals that suppress cardiomyocyte proliferation are poorly understood. We profiled receptors enriched in postnatal cardiomyocytes, and found that very-low-density-lipoprotein receptor (Vldlr) inhibits neonatal cardiomyocyte cell cycle. Paradoxically, Reelin, the well-known Vldlr ligand, expressed in cardiac Schwann cells and lymphatic endothelial cells, promotes neonatal cardiomyocyte proliferation. Thrombospondin1 (TSP-1), another ligand of Vldlr highly expressed in adult heart, was then found to inhibit cardiomyocyte proliferation through Vldlr, and may contribute to Vldlr's overall repression on proliferation. Mechanistically, Rac1 and subsequent Yap phosphorylation and nucleus translocation mediate the regulation of the cardiomyocyte cell cycle by TSP-1/Reelin-Vldlr signaling. Importantly, Reln mutant neonatal mice displayed impaired cardiomyocyte proliferation and cardiac regeneration after apical resection, while cardiac-specific Thbs1 deletion and cardiomyocyte-specific Vldlr deletion promote cardiomyocyte proliferation and are cardioprotective after myocardial infarction. Our results identified a novel role of Vldlr in consolidating extracellular signals to regulate cardiomyocyte cell cycle activity and survival, and the overall suppressive TSP-1-Vldlr signal may contribute to the poor cardiac repair capacity of adult mammals.

Adverse clinical outcomes and immunosuppressive microenvironment of RHO-GTPase activation pattern in hepatocellular carcinoma.

BACKGROUND: Emerging evidence suggests that Rho GTPases play a crucial role in tumorigenesis and metastasis, but their involvement in the tumor microenvironment (TME) and prognosis of hepatocellular carcinoma (HCC) is not well understood. METHODS: We aim to develop a tumor prognosis prediction system called the Rho GTPases-related gene score (RGPRG score) using Rho GTPase signaling genes and further bioinformatic analyses. RESULTS: Our work found that HCC patients with a high RGPRG score had significantly worse survival and increased immunosuppressive cell fractions compared to those with a low RGPRG score. Single-cell cohort analysis revealed an immune-active TME in patients with a low RGPRG score, with strengthened communication from T/NK cells to other cells through MIF signaling networks. Targeting these alterations in TME, the patients with high RGPRG score have worse immunotherapeutic outcomes and decreased survival time in the immunotherapy cohort. Moreover, the RGPRG score was found to be correlated with survival in 27 other cancers. In vitro experiments confirmed that knockdown of the key Rho GTPase-signaling biomarker SFN significantly inhibited HCC cell proliferation, invasion, and migration. CONCLUSIONS: This study provides new insight into the TME features and clinical use of Rho GTPase gene pattern at the bulk-seq and single-cell level, which may contribute to guiding personalized treatment and improving clinical outcome in HCC.

Modification of the electrokinetic motion of microalgae through light illumination for viability assessment.

The viability detection of microalgae with the electrokinetic (EK) technique shows vast applications in the biology and maritime industry. However, due to the slight variations in the EK properties between alive and dead microalgae cells, the accuracy and practicability of this technique is limited. In this paper, the light illumination pretreatment was conducted to modify the EK velocity of microalgae for enhancing the EK difference. The effects of the illumination time and light color on the EK velocities of Chlorella vulgaris and Isochrysis galbana were systematically measured, and the EK differences between alive and dead cells were calculated and compared. The results indicate that under light illumination, the photosynthesis of the alive cells leads to the amplification of the zeta potential, leading toward increase in the EK difference along with the illumination time. By using light with different color spectra to treat the microalgae, it was found that the EK difference changes with the light color according to the following order: white light > red light > blue light > green light. The difference in EK potential with exposure to white light treatment surpasses over 10-fold in comparison to those without such treatment. The light pretreatment technique, as illustrated in this study, offers an advantageous strategy to enhance the EK difference between living and dead cells, proving beneficial in the field of microalgae biotechnology.

Venetoclax plus dose-adjusted R-EPOCH (VR-DA-EPOCH) or G-EPOCH bridging to subsequent cellular therapy for the patients with transformed lymphoma a single center clinical experience.

Indolent lymphoma, including chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) and follicular lymphoma (FL), can undergo histological transformation into an aggressive subtype, typically diffuse large B-cell lymphoma (DLBCL). The prognosis of transformed lymphoma is poor. In this study, we reported the efficacy and toxicity of a combination of venetoclax, dose-adjusted rituximab or obinutuzumab, etoposide, prednisone, vincristine, doxorubicin, and cyclophosphamide (VR-DA-EPOCH or VG-DA-EPOCH) in 11 patients with biopsy-proven histology transformation into DLBCL, including 8 patients with RT and 3 with transformed FL (tFL). The study was conducted between October 2019 and March 2023 at our single center. The median age of participants at enrolment was 53 years. Six patients (85.7%, 6/7) achieved complete remission (CR) at the end of treatment. The best overall response rate (ORR) and CR rate were both 72.7%, respectively. Two patients received autologous hemopoietic stem cell transplant (ASCT) while two patients received ASCT concurrently with CAR-T therapy for consolidation. With a median follow-up of 13.5 (range, 2.4-29.8) months after enrollment, the median event-free survival, progression-free survival, and overall survival were 9.4, 11.5, and 17.5 months, respectively. Hematologic toxicities of grade ≥3 consisted of neutropenia (90.9%, 10/11), thrombocytopenia (63.6%, 7/11), and febrile neutropenia (54.5%, 6/11). In conclusion, VR-DA-EPOCH or VG-DA-EPOCH was a promising strategy to achieve an early remission, bridging to cellular therapy within this population.

A low testosterone level impairs erectile function by increasing endocan expression in rat penile corpus cavernosum.

BACKGROUND: The mechanism by which a state of low testosterone leads to erectile dysfunction (ED) has not been determined. Endocan is a novel marker of endothelial function. However, whether endocan is involved in the regulation of erectile function under low testosterone levels remains unclear. AIM: In this study we sought to determine whether a low-testosterone state inhibits erectile function by regulating endocan expression in the endothelial cells of the rat penile corpus cavernosum. METHODS: Thirty-six male Sprague-Dawley rats aged 8 weeks were randomly assigned to 6 groups (n = 6 per group) as follows: (1) control, (2) castration, (3) castration + testosterone treatment (treated with 3 mg/kg testosterone propionate per 2 days), (4) control + transfection (4 weeks after castration, injected with lentiviral vector (1 × 108 transduction units/mL, 10 µL), (5) castration + transfection, or (6) castration + empty transfection. One week after the injection, we measured the maximal intracavernous pressure/mean arterial pressure (ICPmax/MAP), serum testosterone and nitric oxide (NO) levels, and the expression of endocan, phospho-endothelial NO synthase (p-eNOS), eNOS, phospho-protein kinase B (p-AKT), and AKT in the rat penile corpus cavernosum. OUTCOMES: Under a low-androgen state, the expression of endocan in the rat penile corpus cavernosum was significantly increased, which inhibited the AKT/eNOS/NO signaling pathway and resulted in ED. RESULTS: In the castration group, the expression of endocan in the rat penile corpus cavernosum was significantly higher than that in the control group (P < .05). Additionally, the levels of p-AKT/AKT, p-eNOS/eNOS, and NO in the rat penile corpus cavernosum and ICPmax/MAP were significantly lower in the castration group than in the control group (P < .05). In the castration + transfection group compared with the castration group there was a significant decrease in the expression of endocan (P < .05) and an increase in the ratios of p-AKT/AKT, p-eNOS/eNOS, and ICPmax/MAP (P < .05) in the rat penile corpus cavernosum. CLINICAL IMPLICATIONS: Downregulating the expression of endocan in the penile corpus cavernosum may be a feasible approach for treating ED caused by hypoandrogenism. STRENGTHS AND LIMITATIONS: The results of this study indicte that endocan may affect NO levels and erectile function through multiple signaling pathways, but further experiments are needed to clarify the relationship between endocan and androgens. CONCLUSION: A low-testosterone state inhibits the AKT/eNOS/NO signaling pathway by increasing the expression of endocan in the rat penile corpus cavernosum and impairing erectile function in rats. Decreasing the expression of endocan in the penile corpus cavernosum can improve erectile function in rats with low testosterone levels.

Mode of cell death in the penile cavernous tissue of type 1 diabetes mellitus rats.

BACKGROUND: Diabetes mellitus commonly causes endothelial cell and smooth muscle cell death in penile cavernous tissue. AIM: The study sought to study the mode of cell death in the penile cavernous tissue in type 1 diabetic rats. METHODS: A total of 36 Sprague Dawley rats 10 weeks of age were randomly divided into 2 groups: a normoglycemic group and type 1 diabetic group (intraperitoneal injection of Streptozotocin (STZ), 60 mg/kg). We randomly selected 6 rats from each group for tests at the end of 11, 14, and 18 weeks of age, respectively. All rats were able to eat and drink freely. The ratio of maximum intracavernous pressure to mean arterial pressure, concentration of serum testosterone, level of nitric oxide in the penile cavernosum, and expression of active caspase-1 (pyroptosis) and active caspase-3 (apoptosis) were determined. OUTCOMES: At the end of weeks 4 and 8 of type 1 diabetes, the proportions of endothelial cells and smooth muscle cells undergoing apoptosis and pyroptosis in penile cavernous tissue are different. RESULTS: The ratio of maximum intracavernous pressure to mean arterial pressure and nitric oxide levels were significantly lower in the 4- and 8-week diabetic groups than in the normoglycemic group (P < .01). Penile endothelial cell pyroptosis (5.67 ± 0.81%), smooth muscle cell apoptosis (23.72 ± 0.48%), total cell pyroptosis (9.67 ± 0.73%), and total apoptosis (10.52 ± 1.45%) were significantly greater in the 4-week diabetic group than in the normoglycemic group (P < .01). The proportion of endothelial cell pyroptosis (24.4 ± 3.69%), endothelial cell apoptosis (22.13 ± 2.43%), total cell pyroptosis (14.75 ± 0.93%), and total apoptosis (14.82 ± 1.08%) in the penile tissues of the 8-week diabetic group were significantly greater than those in the normoglycemic group (P < .01).The 8-week survival proportions of diabetic endothelial cells (38.86 ± 8.85%) and smooth muscle cells (44.46 ± 2.94%) was significantly lower than the 4-week survival proportions of endothelial cells (93.17 ± 8.07%) and smooth muscle cells (75.12 ± 4.76%) (P < .05). CLINICAL TRANSLATION: Inhibition of cell death by different methods at different stages may be the key to the treatment of type 1 diabetes-induced erectile dysfunction. STRENGTHS AND LIMITATIONS: The effect of type 1 diabetes on other types of cell death in penile cavernous tissue needs further study. CONCLUSION: The mode of death of endothelial cells in the cavernous tissue of the penis in the early stage in diabetic rats is dominated by pyroptosis, and the death of smooth muscle cells is dominated by apoptosis. Endothelial cell and smooth muscle cell death are not consistent at different stages of diabetes progression.