Controlled Noise: Evidence of epigenetic regulation of Single-Cell expression variability.

MOTIVATION: Understanding single-cell expression variability (scEV) or gene expression noise among cells of the same type and state is crucial for delineating population-level cellular function. While epigenetic mechanisms are widely implicated in gene expression regulation, a definitive link between chromatin accessibility and scEV remains elusive. Recent advances in single-cell techniques enable the study of single-cell multiomics data that include the simultaneous measurement of scATAC-seq and scRNA-seq within individual cells, presenting an unprecedented opportunity to address this gap. RESULTS: This paper introduces an innovative testing pipeline to investigate the association between chromatin accessibility and scEV. With single-cell multiomics data of scATAC-seq and scRNA-seq, the pipeline hinges on comparing the prediction performance of scATAC-seq data on gene expression levels between highly variable genes (HVGs) and non-highly variable genes (non-HVGs). Applying this pipeline to paired scATAC-seq and scRNA-seq data from human hematopoietic stem and progenitor cells, we observed a significantly superior prediction performance of scATAC-seq data for HVGs compared to non-HVGs. Notably, there was substantial overlap between well-predicted genes and HVGs. The gene pathways enriched from well-predicted genes are highly pertinent to cell type-specific functions. Our findings support the notion that scEV largely stems from cell-to-cell variability in chromatin accessibility, providing compelling evidence for the epigenetic regulation of scEV and offering promising avenues for investigating gene regulation mechanisms at the single-cell level. AVAILABILITY: The source code and data used in this paper can be found at https://github.com/SiweiCui/EpigeneticControlOfSingle-CellExpressionVariability. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Identification of a copper-responsive small molecule inhibitor of uropathogenic Escherichia coli.

Urinary tract infections (UTIs) are a major global health problem and are caused predominantly by uropathogenic Escherichia coli (UPEC). UTIs are a leading cause of prescription antimicrobial use. Incessant increase in antimicrobial resistance in UPEC and other uropathogens poses a serious threat to the current treatment practices. Copper is an effector of nutritional immunity that impedes the growth of pathogens during infection. We hypothesized that copper would augment the toxicity of select small molecules against bacterial pathogens. We conducted a small molecule screening campaign with a library of 51,098 molecules to detect hits that inhibit a UPEC ΔtolC mutant in a copper-dependent manner. A molecule, denoted as E. coli inhibitor or ECIN, was identified as a copper-responsive inhibitor of wild-type UPEC strains. Our gene expression and metal content analysis results demonstrate that ECIN works in concert with copper to exacerbate Cu toxicity in UPEC. ECIN has a broad spectrum of activity against pathogens of medical and veterinary significance including Acinetobacter baumannii, Pseudomonas aeruginosa, and methicillin-resistant Staphylococcus aureus. Subinhibitory levels of ECIN eliminate UPEC biofilm formation. Transcriptome analysis of UPEC treated with ECIN reveals induction of multiple stress response systems. Furthermore, we demonstrate that L-cysteine rescues the growth of UPEC exposed to ECIN. In summary, we report the identification and characterization of a novel copper-responsive small molecule inhibitor of UPEC.IMPORTANCEUrinary tract infection (UTI) is a ubiquitous infectious condition affecting millions of people annually. Uropathogenic Escherichia coli (UPEC) is the predominant etiological agent of UTI. However, UTIs are becoming increasingly difficult to resolve with antimicrobials due to increased antimicrobial resistance in UPEC and other uropathogens. Here, we report the identification and characterization of a novel copper-responsive small molecule inhibitor of UPEC. In addition to E. coli, this small molecule also inhibits pathogens of medical and veterinary significance including Acinetobacter baumannii, Pseudomonas aeruginosa, and methicillin-resistant Staphylococcus aureus.

Ephrin Forward Signaling Controls Interspecies Cell Competition in Pluripotent Stem Cells.

In the animal kingdom, evolutionarily conserved mechanisms known as cell competition eliminate unfit cells during development. Interestingly, cell competition also leads to apoptosis of donor cells upon direct contact with host cells from a different species during interspecies chimera formation. The mechanisms underlying how host animal cells recognize and transmit cell death signals to adjacent xenogeneic human cells remain incompletely understood. In this study, we developed an interspecies cell contact reporter system to dissect the mechanisms underlying competitive interactions between mouse and human pluripotent stem cells (PSCs). Through single-cell RNA-seq analyses, we discovered that Ephrin A ligands in mouse cells play a crucial role in signaling cell death to adjacent human cells that express EPHA receptors during interspecies PSC co-culture. We also demonstrated that blocking the Ephrin A-EPHA receptor interaction pharmacologically, and inhibiting Ephrin forward signaling genetically in the mouse cells, enhances the survival of human PSCs and promotes chimera formation both in vitro and in vivo . Our findings elucidate key mechanisms of interspecies PSC competition during early embryogenesis and open new avenues for generating humanized tissues or organs in animals, potentially revolutionizing regenerative medicine.

Parallel degradome-seq and DMS-MaPseq substantially revise the miRNA biogenesis atlas in Arabidopsis.

MicroRNAs (miRNAs) are produced from highly structured primary transcripts (pri-miRNAs) and regulate numerous biological processes in eukaryotes. Due to the extreme heterogeneity of these structures, the initial processing sites of plant pri-miRNAs and the structural rules that determine their processing have been predicted for many miRNAs but remain elusive for others. Here we used semi-active DCL1 mutants and advanced degradome-sequencing strategies to accurately identify the initial processing sites for 147 of 326 previously annotated Arabidopsis miRNAs and to illustrate their associated pri-miRNA cleavage patterns. Elucidating the in vivo RNA secondary structures of 73 pri-miRNAs revealed that about 95% of them differ from in silico predictions, and that the revised structures offer clearer interpretation of the processing sites and patterns. Finally, DCL1 partners Serrate and HYL1 could synergistically and independently impact processing patterns and in vivo RNA secondary structures of pri-miRNAs. Together, our work sheds light on the precise processing mechanisms of plant pri-miRNAs.

Transcriptomic signature, bioactivity and safety of a non-hepatotoxic analgesic generating AM404 in the midbrain PAG region.

Safe and effective pain management is a critical healthcare and societal need. The potential for acute liver injury from paracetamol (ApAP) overdose; nephrotoxicity and gastrointestinal damage from chronic non-steroidal anti-inflammatory drug (NSAID) use; and opioids' addiction are unresolved challenges. We developed SRP-001, a non-opioid and non-hepatotoxic small molecule that, unlike ApAP, does not produce the hepatotoxic metabolite N-acetyl-p-benzoquinone-imine (NAPQI) and preserves hepatic tight junction integrity at high doses. CD-1 mice exposed to SRP-001 showed no mortality, unlike a 70% mortality observed with increasing equimolar doses of ApAP within 72 h. SRP-001 and ApAP have comparable antinociceptive effects, including the complete Freund's adjuvant-induced inflammatory von Frey model. Both induce analgesia via N-arachidonoylphenolamine (AM404) formation in the midbrain periaqueductal grey (PAG) nociception region, with SRP-001 generating higher amounts of AM404 than ApAP. Single-cell transcriptomics of PAG uncovered that SRP-001 and ApAP also share modulation of pain-related gene expression and cell signaling pathways/networks, including endocannabinoid signaling, genes pertaining to mechanical nociception, and fatty acid amide hydrolase (FAAH). Both regulate the expression of key genes encoding FAAH, 2-arachidonoylglycerol (2-AG), cannabinoid receptor 1 (CNR1), CNR2, transient receptor potential vanilloid type 4 (TRPV4), and voltage-gated Ca2+ channel. Phase 1 trial (NCT05484414) (02/08/2022) demonstrates SRP-001's safety, tolerability, and favorable pharmacokinetics, including a half-life from 4.9 to 9.8 h. Given its non-hepatotoxicity and clinically validated analgesic mechanisms, SRP-001 offers a promising alternative to ApAP, NSAIDs, and opioids for safer pain treatment.

Single-nucleus transcriptomics of epicardial adipose tissue from female pigs reveals effects of exercise training on resident innate and adaptive immune cells.

BACKGROUND: Coronary artery disease (CAD) is a leading cause of death in women. Epicardial adipose tissue (EAT) secretes cytokines to modulate coronary artery function, and the release of fatty acids from EAT serves as a readily available energy source for cardiomyocytes. However, despite having beneficial functions, excessive amounts of EAT can cause the secretion of proinflammatory molecules that increase the instability of atherosclerotic plaques and contribute to CAD progression. Although exercise mitigates CAD, the mechanisms by which exercise impacts EAT are unknown. The Yucatan pig is an excellent translational model for the effects of exercise on cardiac function. Therefore, we sought to determine if chronic aerobic exercise promotes an anti-inflammatory microenvironment in EAT from female Yucatan pigs. METHODS: Sexually mature, female Yucatan pigs (n = 7 total) were assigned to sedentary (Sed, n = 3) or exercise (Ex, n = 4) treatments, and coronary arteries were occluded (O) with an ameroid to mimic CAD or remained non-occluded (N). EAT was collected for bulk (n = 7 total) and single nucleus transcriptomic sequencing (n = 2 total, 1 per exercise treatment). RESULTS: Based on the bulk transcriptomic analysis, exercise upregulated S100 family, G-protein coupled receptor, and CREB signaling in neurons canonical pathways in EAT. The top networks in EAT affected by exercise as measured by bulk RNA sequencing were SRC kinase family, fibroblast growth factor receptor, Jak-Stat, and vascular endothelial growth factor. Single nucleus transcriptomic analysis revealed that exercise increased the interaction between immune, endothelial, and mesenchymal cells in the insulin-like growth factor pathway and between endothelial and other cell types in the platelet endothelial cell adhesion molecule 1 pathway. Sub-clustering revealed nine cell types in EAT, with fibroblast and macrophage populations predominant in O-Ex EAT and T cell populations predominant in N-Ex EAT. Unlike the findings for exercise alone as a treatment, there were not increased interactions between endothelial and mesenchymal cells in O-Ex EAT. Coronary artery occlusion impacted the most genes in T cells and endothelial cells. Genes related to fatty acid metabolism were the most highly upregulated in non-immune cells from O-Ex EAT. Sub-clustering of endothelial cells revealed that N-Ex EAT separated from other treatments. CONCLUSIONS: According to bulk transcriptomics, exercise upregulated pathways and networks related to growth factors and immune cell communication. Based on single nucleus transcriptomics, aerobic exercise increased cell-to-cell interaction amongst immune, mesenchymal, and endothelial cells in female EAT. Yet, exercise was minimally effective at reversing alterations in gene expression in endothelial and mesenchymal cells in EAT surrounding occluded arteries. These findings lay the foundation for future work focused on the impact of exercise on cell types in EAT.

Novel Nuclear Roles for Testis-Specific ACTL7A and ACTL7B Supported by In Vivo Characterizations and AI Facilitated In Silico Mechanistic Modeling with Implications for Epigenetic Regulation in Spermiogenesis.

A mechanistic role for nuclear function of testis-specific actin related proteins (ARPs) is proposed here through contributions of ARP subunit swapping in canonical chromatin regulatory complexes. This is significant to our understanding of both mechanisms controlling regulation of spermiogenesis, and the expanding functional roles of the ARPs in cell biology. Among these roles, actins and ARPs are pivotal not only in cytoskeletal regulation, but also in intranuclear chromatin organization, influencing gene regulation and nucleosome remodeling. This study focuses on two testis-specific ARPs, ACTL7A and ACTL7B, exploring their intranuclear activities and broader implications utilizing combined in vivo, in vitro, and in silico approaches. ACTL7A and ACTL7B, previously associated with structural roles, are hypothesized here to serve in chromatin regulation during germline development. This study confirms the intranuclear presence of ACTL7B in spermatocytes and round spermatids, revealing a potential role in intranuclear processes, and identifies a putative nuclear localization sequence conserved across mammalian ACTL7B, indicating a potentially unique mode of nuclear transport which differs from conventional actin. Ablation of ACTL7B leads to varied transcriptional changes reported here. Additionally, in the absence of ACTL7A or ACTL7B there is a loss of intranuclear localization of HDAC1 and HDAC3, which are known regulators of epigenetic associated acetylation changes that in turn regulate gene expression. Thus, these HDACs are implicated as contributors to the aberrant gene expression observed in the KO mouse testis transcriptomic analysis. Furthermore, this study employed and confirmed the accuracy of in silico models to predict ARP interactions with Helicase-SANT-associated (HSA) domains, uncovering putative roles for testis-specific ARPs in nucleosome remodeling complexes. In these models, ACTL7A and ACTL7B were found capable of binding to INO80 and SWI/SNF nucleosome remodeler family members in a manner akin to nuclear actin and ACTL6A. These models thus implicate germline-specific ARP subunit swapping within chromatin regulatory complexes as a potential regulatory mechanism for chromatin and associated molecular machinery adaptations in nuclear reorganizations required during spermiogenesis. These results hold implications for male fertility and epigenetic programing in the male-germline that warrant significant future investigation. In summary, this study reveals that ACTL7A and ACTL7B play intranuclear gene regulation roles in male gametogenesis, adding to the multifaceted roles identified also spanning structural, acrosomal, and flagellar stability. ACTL7A and ACTL7B unique nuclear transport, impact on HDAC nuclear associations, impact on transcriptional processes, and proposed mechanism for involvement in nucleosome remodeling complexes supported by AI facilitated in silico modeling contribute to a more comprehensive understanding of the indispensable functions of ARPs broadly in cell biology, and specifically in male fertility.

Experimental and analytical pipeline for sub-genomic RNA landscape of coronavirus by Nanopore sequencer.

Coronaviruses (CoVs), including severe acute respiratory syndrome coronavirus 2, can infect a variety of mammalian and avian hosts with significant medical and economic consequences. During the life cycle of CoV, a coordinated series of subgenomic RNAs, including canonical subgenomic messenger RNA and non-canonical defective viral genomes (DVGs), are generated with different biological implications. Studies that adopted the Nanopore sequencer (ONT) to investigate the landscape and dynamics of viral RNA subgenomic transcriptomes applied arbitrary bioinformatics parameters without justification or experimental validation. The current study used bovine coronavirus (BCoV), which can be performed under biosafety level 2 for library construction and experimental validation using traditional colony polymerase chain reaction and Sanger sequencing. Four different ONT protocols, including RNA direct and cDNA direct sequencing with or without exonuclease treatment, were used to generate RNA transcriptomic libraries from BCoV-infected cell lysates. Through rigorously examining the k-mer, gap size, segment size, and bin size, the optimal cutoffs for the bioinformatic pipeline were determined to remove the sequence noise while keeping the informative DVG reads. The sensitivity and specificity of identifying DVG reads using the proposed pipeline can reach 82.6% and 99.6% under the k-mer size cutoff of 15. Exonuclease treatment reduced the abundance of RNA transcripts; however, it was not necessary for future library preparation. Additional recovery of clipped BCoV nucleotide sequences with experimental validation expands the landscape of the CoV discontinuous RNA transcriptome, whose biological function requires future investigation. The results of this study provide the benchmarks for library construction and bioinformatic parameters for studying the discontinuous CoV RNA transcriptome.IMPORTANCEFunctional defective viral genomic RNA, containing all the cis-acting elements required for translation or replication, may play different roles in triggering cell innate immune signaling, interfering with the canonical subgenomic messenger RNA transcription/translation or assisting in establishing persistence infection. This study does not only provide benchmarks for library construction and bioinformatic parameters for studying the discontinuous coronavirus RNA transcriptome but also reveals the complexity of the bovine coronavirus transcriptome, whose functional assays will be critical in future studies.

Intranasally Administered EVs from hiPSC-derived NSCs Alter the Transcriptomic Profile of Activated Microglia and Conserve Brain Function in an Alzheimer's Model.

Antiinflammatory extracellular vesicles (EVs) derived from human induced pluripotent stem cell (hiPSC)-derived neural stem cells (NSCs) hold promise as a disease-modifying biologic for Alzheimer's disease (AD). This study directly addressed this issue by examining the effects of intranasal administrations of hiPSC-NSC-EVs to 3-month-old 5xFAD mice. The EVs were internalized by all microglia, which led to reduced expression of multiple genes associated with disease-associated microglia, inflammasome, and interferon-1 signaling. Furthermore, the effects of hiPSC-NSC-EVs persisted for two months post-treatment in the hippocampus, evident from reduced microglial clusters, inflammasome complexes, and expression of proteins and/or genes linked to the activation of inflammasomes, p38/mitogen-activated protein kinase, and interferon-1 signaling. The amyloid-beta (Aß) plaques, Aß-42, and phosphorylated-tau concentrations were also diminished, leading to better cognitive and mood function in 5xFAD mice. Thus, early intervention with hiPSC-NSC-EVs in AD may help maintain better brain function by restraining the progression of adverse neuroinflammatory signaling cascades.

Single-nucleus transcriptomics of epicardial adipose tissue from females reveals exercise control of innate and adaptive immune cells.

Coronary artery disease (CAD) is a leading cause of death in women. Although exercise mitigates CAD, the mechanisms by which exercise impacts epicardial adipose tissue (EAT) are unknown. We hypothesized that exercise promotes an anti-inflammatory microenvironment in EAT from female pigs. Yucatan pigs (n=7) were assigned to sedentary (Sed) or exercise (Ex) treatments and coronary arteries were occluded (O) with an ameroid to mimic CAD or remained non-occluded (N). EAT was collected for bulk and single nucleus transcriptomic sequencing (snRNA-seq). Exercise upregulated G-protein coupled receptor, S100 family, and FAK pathways and downregulated the coagulation pathway. Exercise increased the interaction between immune, endothelial, and mesenchymal cells in the insulin-like growth factor pathway and between endothelial and other cell types in the platelet endothelial cell adhesion molecule 1 pathway. Sub-clustering revealed nine cell types in EAT with fibroblast and macrophage populations predominant in O-Ex EAT and T cell population predominant in N-Ex EAT. Coronary occlusion impacted the largest number of genes in T and endothelial cells. Genes related to fatty acid metabolism were the most highly upregulated in non-immune cells from O-Ex EAT. Sub-clustering of endothelial cells revealed that N-Ex EAT separated from other treatments. In conclusion, aerobic exercise increased interaction amongst immune and mesenchymal and endothelial cells in female EAT. Exercise was minimally effective at reversing alterations in gene expression in endothelial and mesenchymal cells in EAT surrounding occluded arteries. These findings lay the foundation for future work focused on the impact of exercise on cell types in EAT.

Inflammation in the tumor-adjacent lung as a predictor of clinical outcome in lung adenocarcinoma.

Approximately 30% of early-stage lung adenocarcinoma patients present with disease progression after successful surgical resection. Despite efforts of mapping the genetic landscape, there has been limited success in discovering predictive biomarkers of disease outcomes. Here we performed a systematic multi-omic assessment of 143 tumors and matched tumor-adjacent, histologically-normal lung tissue with long-term patient follow-up. Through histologic, mutational, and transcriptomic profiling of tumor and adjacent-normal tissue, we identified an inflammatory gene signature in tumor-adjacent tissue as the strongest clinical predictor of disease progression. Single-cell transcriptomic analysis demonstrated the progression-associated inflammatory signature was expressed in both immune and non-immune cells, and cell type-specific profiling in monocytes further improved outcome predictions. Additional analyses of tumor-adjacent transcriptomic data from The Cancer Genome Atlas validated the association of the inflammatory signature with worse outcomes across cancers. Collectively, our study suggests that molecular profiling of tumor-adjacent tissue can identify patients at high risk for disease progression.

Interpretable modeling of time-resolved single-cell gene-protein expression with CrossmodalNet.

Cell-surface proteins play a critical role in cell function and are primary targets for therapeutics. CITE-seq is a single-cell technique that enables simultaneous measurement of gene and surface protein expression. It is powerful but costly and technically challenging. Computational methods have been developed to predict surface protein expression using gene expression information such as from single-cell RNA sequencing (scRNA-seq) data. Existing methods however are computationally demanding and lack the interpretability to reveal underlying biological processes. We propose CrossmodalNet, an interpretable machine learning model, to predict surface protein expression from scRNA-seq data. Our model with a customized adaptive loss accurately predicts surface protein abundances. When samples from multiple time points are given, our model encodes temporal information into an easy-to-interpret time embedding to make prediction in a time-point-specific manner, and is able to uncover noise-free causal gene-protein relationships. Using three publicly available time-resolved CITE-seq data sets, we validate the performance of our model by comparing it with benchmarking methods and evaluate its interpretability. Together, we show that our method accurately and interpretably profiles surface protein expression using scRNA-seq data, thereby expanding the capacity of CITE-seq experiments for investigating molecular mechanisms involving surface proteins.

Suppression of FOXO1 attenuates inflamm-aging and improves liver function during aging.

The liver is a key metabolic organ that maintains whole-body nutrient homeostasis. Aging-induced liver function alterations contribute to systemic susceptibility to aging-related diseases. However, the molecular mechanisms of liver aging remain insufficiently understood. In this study, we performed bulk RNA-Seq and single-cell RNA-Seq analyses to investigate the underlying mechanisms of the aging-induced liver function changes. We found that liver inflammation, glucose intolerance, and liver fat deposition were aggravated in old mice. Aging significantly increased pro-inflammation in hepatic macrophages. Furthermore, we found that Kupffer cells (KCs) were the major driver to induce pro-inflammation in hepatic macrophages during aging. In KCs, aging significantly increased pro-inflammatory levels; in monocyte-derived macrophages (MDMs), aging had a limited effect on pro-inflammation but led to a functional quiescence in antigen presentation and phagosome process. In addition, we identified an aging-responsive KC-specific (ARKC) gene set that potentially mediates aging-induced pro-inflammation in KCs. Interestingly, FOXO1 activity was significantly increased in the liver of old mice. FOXO1 inhibition by AS1842856 significantly alleviated glucose intolerance, hepatic steatosis, and systemic inflammation in old mice. FOXO1 inhibition significantly attenuated aging-induced pro-inflammation in KCs partially through downregulation of ARKC genes. However, FOXO1 inhibition had a limited effect on aging-induced functional quiescence in MDMs. These results indicate that aging induces pro-inflammation in liver mainly through targeting KCs and FOXO1 is a key player in aging-induced pro-inflammation in KCs. Thus, FOXO1 could be a potential therapeutic target for the treatment of age-associated chronic diseases.

Empirical networks for localized COVID-19 interventions using WiFi infrastructure at university campuses.

Infectious diseases, like COVID-19, pose serious challenges to university campuses, which typically adopt closure as a non-pharmaceutical intervention to control spread and ensure a gradual return to normalcy. Intervention policies, such as remote instruction (RI) where large classes are offered online, reduce potential contact but also have broad side-effects on campus by hampering the local economy, students' learning outcomes, and community wellbeing. In this paper, we demonstrate that university policymakers can mitigate these tradeoffs by leveraging anonymized data from their WiFi infrastructure to learn community mobility-a methodology we refer to as WiFi mobility models (WiMob). This approach enables policymakers to explore more granular policies like localized closures (LC). WiMob can construct contact networks that capture behavior in various spaces, highlighting new potential transmission pathways and temporal variation in contact behavior. Additionally, WiMob enables us to design LC policies that close super-spreader locations on campus. By simulating disease spread with contact networks from WiMob, we find that LC maintains the same reduction in cumulative infections as RI while showing greater reduction in peak infections and internal transmission. Moreover, LC reduces campus burden by closing fewer locations, forcing fewer students into completely online schedules, and requiring no additional isolation. WiMob can empower universities to conceive and assess a variety of closure policies to prevent future outbreaks.

Transcriptomic signature, bioactivity and safety of a non-hepatoxic analgesic generating AM404 in the mid-brain PAG region.

The safe and effective management of pain is a critical healthcare and societal need. The potential for misuse and addiction associated with opioids, nephrotoxicity, and gastrointestinal damage from chronic non-steroidal anti-inflammatory drug (NSAID) use, as well as acute liver injury from paracetamol (ApAP) overdose, are unresolved challenges. To address them, we developed a non-opioid and non-hepatotoxic small molecule, SRP-001. Compared to ApAP, SRP-001 is not hepatotoxic as it does not produce N-acetyl-p-benzoquinone-imine (NAPQI) and maintains hepatic tight junction integrity at high doses. SRP-001 has comparable analgesia in pain models, including the complete Freund's adjuvant (CFA) inflammatory von Frey. Both induce analgesia via N-arachidonoylphenolamine (AM404) formation in the midbrain periaqueductal grey (PAG) nociception area, with SRP-001 generating higher amounts of AM404 than ApAP. Single-cell transcriptomics of PAG uncovered that SRP-001 and ApAP also share modulation of pain-related gene expression and cell signaling pathways, including the endocannabinoid, mechanical nociception, and fatty acid amide hydrolase (FAAH) pathways. Both regulate the expression of key genes encoding FAAH, 2-AG, CNR1, CNR2, TRPV4, and voltage-gated Ca2+ channel. Interim Phase 1 trial results demonstrate SRP-001's safety, tolerability, and favorable pharmacokinetics (NCT05484414). Given its non-hepatotoxicity and clinically validated analgesic mechanisms, SRP-001 offers a promising alternative to ApAP, NSAIDs, and opioids for safer pain treatment.

Gene knockout inference with variational graph autoencoder learning single-cell gene regulatory networks.

In this paper, we introduce Gene Knockout Inference (GenKI), a virtual knockout (KO) tool for gene function prediction using single-cell RNA sequencing (scRNA-seq) data in the absence of KO samples when only wild-type (WT) samples are available. Without using any information from real KO samples, GenKI is designed to capture shifting patterns in gene regulation caused by the KO perturbation in an unsupervised manner and provide a robust and scalable framework for gene function studies. To achieve this goal, GenKI adapts a variational graph autoencoder (VGAE) model to learn latent representations of genes and interactions between genes from the input WT scRNA-seq data and a derived single-cell gene regulatory network (scGRN). The virtual KO data is then generated by computationally removing all edges of the KO gene-the gene to be knocked out for functional study-from the scGRN. The differences between WT and virtual KO data are discerned by using their corresponding latent parameters derived from the trained VGAE model. Our simulations show that GenKI accurately approximates the perturbation profiles upon gene KO and outperforms the state-of-the-art under a series of evaluation conditions. Using publicly available scRNA-seq data sets, we demonstrate that GenKI recapitulates discoveries of real-animal KO experiments and accurately predicts cell type-specific functions of KO genes. Thus, GenKI provides an in-silico alternative to KO experiments that may partially replace the need for genetically modified animals or other genetically perturbed systems.

scTenifoldXct: A semi-supervised method for predicting cell-cell interactions and mapping cellular communication graphs.

We present scTenifoldXct, a semi-supervised computational tool for detecting ligand-receptor (LR)-mediated cell-cell interactions and mapping cellular communication graphs. Our method is based on manifold alignment, using LR pairs as inter-data correspondences to embed ligand and receptor genes expressed in interacting cells into a unified latent space. Neural networks are employed to minimize the distance between corresponding genes while preserving the structure of gene regression networks. We apply scTenifoldXct to real datasets for testing and demonstrate that our method detects interactions with high consistency compared with other methods. More importantly, scTenifoldXct uncovers weak but biologically relevant interactions overlooked by other methods. We also demonstrate how scTenifoldXct can be used to compare different samples, such as healthy vs. diseased and wild type vs. knockout, to identify differential interactions, thereby revealing functional implications associated with changes in cellular communication status.

Interventions incorporating a multi-disciplinary team approach and a dedicated care team can help reduce preventable hospital readmissions of people with type 2 diabetes mellitus: A scoping review of current literature.

AIMS: This review aimed to identify interventions that hospitals can implement to reduce preventable hospital readmissions of people with type 2 diabetes mellitus (T2DM). METHODS: A scoping review framework was utilised to inform the overall process. The electronic databases Cumulative Index to Nursing and Allied Health Literature (CINAHL), Medline, the University of New England (UNE) library search engine and Google Scholar were utilised to search for relevant literature. RESULTS: The results from this review demonstrate that interventions started at index admission for people diagnosed with T2DM can result in reductions in hospital readmissions. Common strategies which attributed to the success of interventions in reducing hospital readmissions of people with T2DM included a multidisciplinary team approach, a dedicated care team, certified diabetes educator appointments, basic survival skills education and influencing hospital protocol development and implementation. CONCLUSION: This scoping review is an attempt at exploring and synthesising current research on interventions that hospitals can implement to reduce preventable hospital readmissions of people with T2DM.

Hepatocyte Adenosine Kinase Promotes Excessive Fat Deposition and Liver Inflammation.

BACKGROUND & AIMS: Nonalcoholic fatty liver disease is highly associated with obesity and progresses to nonalcoholic steatohepatitis when the liver develops overt inflammatory damage. While removing adenosine in the purine salvage pathway, adenosine kinase (ADK) regulates methylation reactions. We aimed to study whether hepatocyte ADK functions as an obesogenic gene/enzyme to promote excessive fat deposition and liver inflammation. METHODS: Liver sections of human subjects were examined for ADK expression using immunohistochemistry. Mice with hepatocyte-specific ADK disruption or overexpression were examined for hepatic fat deposition and inflammation. Liver lipidomics, hepatocyte RNA sequencing (RNA-seq), and single-cell RNA-seq for liver nonparenchymal cells were performed to analyze ADK regulation of hepatocyte metabolic responses and hepatocyte-nonparenchymal cells crosstalk. RESULTS: Whereas patients with nonalcoholic fatty liver disease had increased hepatic ADK levels, mice with hepatocyte-specific ADK disruption displayed decreased hepatic fat deposition on a chow diet and were protected from diet-induced excessive hepatic fat deposition and inflammation. In contrast, mice with hepatocyte-specific ADK overexpression displayed increased body weight and adiposity and elevated degrees of hepatic steatosis and inflammation compared with control mice. RNA-seq and epigenetic analyses indicated that ADK increased hepatic DNA methylation and decreased hepatic Ppara expression and fatty acid oxidation. Lipidomic and single-cell RNA-seq analyses indicated that ADK-driven hepatocyte factors, due to mitochondrial dysfunction, enhanced macrophage proinflammatory activation in manners involving increased expression of stimulator of interferon genes. CONCLUSIONS: Hepatocyte ADK functions to promote excessive fat deposition and liver inflammation through suppressing hepatocyte fatty acid oxidation and producing hepatocyte-derived proinflammatory mediators. Therefore, hepatocyte ADK is a therapeutic target for managing obesity and nonalcoholic fatty liver disease.

A Unified Bayesian Framework for Bi-overlapping-Clustering Multi-omics Data via Sparse Matrix Factorization.

The advances of modern sequencing techniques have generated an unprecedented amount of multi-omics data which provide great opportunities to quantitatively explore functional genomes from different but complementary perspectives. However, distinct modalities/sequencing technologies generate diverse types of data which greatly complicate statistical modeling because uniquely optimized methods are required for handling each type of data. In this paper, we propose a unified framework for Bayesian nonparametric matrix factorization that infers overlapping bi-clusters for multi-omics data. The proposed method adaptively discretizes different types of observations into common latent states on which cluster structures are built hierarchically. The proposed Bayesian nonparametric method is able to automatically determine the number of clusters. We demonstrate the utility of the proposed method using simulation studies and applications to a single-cell RNA-sequencing dataset, a combination of single-cell RNA-sequencing and single-cell ATAC-sequencing dataset, a bulk RNA-sequencing dataset, and a DNA methylation dataset which reveal several interesting findings that are consistent with biological literature.