An integrated single-nucleus and spatial transcriptomics atlas reveals the molecular landscape of the human hippocampus.

The hippocampus contains many unique cell types, which serve the structure's specialized functions, including learning, memory and cognition. These cells have distinct spatial topography, morphology, physiology, and connectivity, highlighting the need for transcriptome-wide profiling strategies that retain cytoarchitectural organization. Here, we generated spatially-resolved transcriptomics (SRT) and single-nucleus RNA-sequencing (snRNA-seq) data from adjacent tissue sections of the anterior human hippocampus across ten adult neurotypical donors. We defined molecular profiles for hippocampal cell types and spatial domains. Using non-negative matrix factorization and transfer learning, we integrated these data to define gene expression patterns within the snRNA-seq data and infer the expression of these patterns in the SRT data. With this approach, we leveraged existing rodent datasets that feature information on circuit connectivity and neural activity induction to make predictions about axonal projection targets and likelihood of ensemble recruitment in spatially-defined cellular populations of the human hippocampus. Finally, we integrated genome-wide association studies with transcriptomic data to identify enrichment of genetic components for neurodevelopmental, neuropsychiatric, and neurodegenerative disorders across cell types, spatial domains, and gene expression patterns of the human hippocampus. To make this comprehensive molecular atlas accessible to the scientific community, both raw and processed data are freely available, including through interactive web applications.

lute: estimating the cell composition of heterogeneous tissue with varying cell sizes using gene expression.

Relative cell type fraction estimates in bulk RNA-sequencing data are important to control for cell composition differences across heterogenous tissue samples. Current computational tools estimate relative RNA abundances rather than cell type proportions in tissues with varying cell sizes, leading to biased estimates. We present lute, a computational tool to accurately deconvolute cell types with varying sizes. Our software wraps existing deconvolution algorithms in a standardized framework. Using simulated and real datasets, we demonstrate how lute adjusts for differences in cell sizes to improve the accuracy of cell composition. Software is available from https://bioconductor.org/packages/lute.

Benchmark of cellular deconvolution methods using a multi-assay reference dataset from postmortem human prefrontal cortex.

Background: Cellular deconvolution of bulk RNA-sequencing (RNA-seq) data using single cell or nuclei RNA-seq (sc/snRNA-seq) reference data is an important strategy for estimating cell type composition in heterogeneous tissues, such as human brain. Computational methods for deconvolution have been developed and benchmarked against simulated data, pseudobulked sc/snRNA-seq data, or immunohistochemistry reference data. A major limitation in developing improved deconvolution algorithms has been the lack of integrated datasets with orthogonal measurements of gene expression and estimates of cell type proportions on the same tissue sample. Deconvolution algorithm performance has not yet been evaluated across different RNA extraction methods (cytosolic, nuclear, or whole cell RNA), different library preparation types (mRNA enrichment vs. ribosomal RNA depletion), or with matched single cell reference datasets. Results: A rich multi-assay dataset was generated in postmortem human dorsolateral prefrontal cortex (DLPFC) from 22 tissue blocks. Assays included spatially-resolved transcriptomics, snRNA-seq, bulk RNA-seq (across six library/extraction RNA-seq combinations), and RNAScope/Immunofluorescence (RNAScope/IF) for six broad cell types. The Mean Ratio method, implemented in the DeconvoBuddies R package, was developed for selecting cell type marker genes. Six computational deconvolution algorithms were evaluated in DLPFC and predicted cell type proportions were compared to orthogonal RNAScope/IF measurements. Conclusions: Bisque and hspe were the most accurate methods, were robust to differences in RNA library types and extractions. This multi-assay dataset showed that cell size differences, marker genes differentially quantified across RNA libraries, and cell composition variability in reference snRNA-seq impact the accuracy of current deconvolution methods.

The gene expression landscape of the human locus coeruleus revealed by single-nucleus and spatially-resolved transcriptomics.

Norepinephrine (NE) neurons in the locus coeruleus (LC) make long-range projections throughout the central nervous system, playing critical roles in arousal and mood, as well as various components of cognition including attention, learning, and memory. The LC-NE system is also implicated in multiple neurological and neuropsychiatric disorders. Importantly, LC-NE neurons are highly sensitive to degeneration in both Alzheimer's and Parkinson's disease. Despite the clinical importance of the brain region and the prominent role of LC-NE neurons in a variety of brain and behavioral functions, a detailed molecular characterization of the LC is lacking. Here, we used a combination of spatially-resolved transcriptomics and single-nucleus RNA-sequencing to characterize the molecular landscape of the LC region and the transcriptomic profile of LC-NE neurons in the human brain. We provide a freely accessible resource of these data in web-accessible and downloadable formats.

Challenges and opportunities to computationally deconvolve heterogeneous tissue with varying cell sizes using single-cell RNA-sequencing datasets.

Deconvolution of cell mixtures in "bulk" transcriptomic samples from homogenate human tissue is important for understanding disease pathologies. However, several experimental and computational challenges impede transcriptomics-based deconvolution approaches using single-cell/nucleus RNA-seq reference atlases. Cells from the brain and blood have substantially different sizes, total mRNA, and transcriptional activities, and existing approaches may quantify total mRNA instead of cell type proportions. Further, standards are lacking for the use of cell reference atlases and integrative analyses of single-cell and spatial transcriptomics data. We discuss how to approach these key challenges with orthogonal "gold standard" datasets for evaluating deconvolution methods.

MicroRNA-mediated attenuation of branched-chain amino acid catabolism promotes ferroptosis in chronic kidney disease.

Chronic kidney disease can develop from kidney injury incident to chemotherapy with cisplatin, which complicates the prognosis of cancer patients. MicroRNAs regulate gene expression by pairing with specific sets of messenger RNAs. Therefore, elucidating direct physical interactions between microRNAs and their target messenger RNAs can help decipher crucial biological processes associated with cisplatin-induced kidney injury. Through intermolecular ligation and transcriptome-wide sequencing, we here identify direct pairs of microRNAs and their target messenger RNAs in the kidney of male mice injured by cisplatin. We find that a group of cisplatin-induced microRNAs can target select messenger RNAs that affect the mitochondrial metabolic pathways in the injured kidney. Specifically, a cisplatin-induced microRNA, miR-429-3p, suppresses the pathway that catabolizes branched-chain amino acids in the proximal tubule, leading to cell death dependent on lipid peroxidation, called ferroptosis. Identification of miRNA-429-3p-mediated ferroptosis stimulation suggests therapeutic potential for modulating the branched-chain amino acid pathway in ameliorating cisplatin-induced kidney injury.

Autophagy activates EGR1 via MAPK/ERK to induce FGF2 in renal tubular cells for fibroblast activation and fibrosis during maladaptive kidney repair.

Macroautophagy/autophagy contributes to maladaptive kidney repair by inducing pro-fibrotic factors such as FGF2 (fibroblast growth factor 2), but the underlying mechanism remains elusive. Here, we show that EGR1 (early growth response 1) was induced in injured proximal tubules after ischemic acute kidney injury (AKI) and this induction was suppressed by autophagy deficiency in inducible, renal tubule-specific atg7 (autophagy related 7) knockout (iRT-atg7 KO) mice. In cultured proximal tubular cells, TGFB1 (transforming growth factor beta 1) induced EGR1 and this induction was also autophagy dependent. Egr1 knockdown in tubular cells reduced FGF2 expression during TGFB1 treatment, leading to less FGF2 secretion and decreased paracrine effects on fibroblasts. ChIP assay detected an increased binding of EGR1 to the Fgf2 gene promoter in TGFB1-treated tubular cells. Both Fgf2 and Egr1 transcription was inhibited by FGF2 neutralizing antibody, suggesting a positive feedback for EGR1-mediated FGF2 autoregulation. This feedback was confirmed using fgf2-deficient tubular cells and fgf2-deficient mice. Upstream of EGR1, autophagy deficiency in mice suppressed MAPK/ERK (mitogen-activated protein kinase) activation in post-ischemic renal tubules. This inhibition correlated with SQSTM1/p62 (sequestosome 1) aggregation and its sequestration of MAPK/ERK. SQSTM1/p62 interacted with MAPK/ERK and blocked its activation during TGFB1 treatment in autophagy-deficient tubular cells. Inhibition of MAPK/ERK suppressed EGR1 and FGF2 expression in maladaptive tubules, leading to the amelioration of renal fibrosis and improvement of renal function. These results suggest that autophagy activates MAPK/ERK in renal tubular cells, which induces EGR1 to transactivate FGF2. FGF2 is then secreted into the interstitium to stimulate fibroblasts for fibrogenesis.Abbreviation: 3-MA: 3-methyladenine; ACTA2/α-SMA: actin alpha 2, smooth muscle, aorta; ACTB/ß-actin: actin, beta; AKI: acute kidney injury; aa: amino acid; ATG/Atg: autophagy related; BUN: blood urea nitrogen; ChIP: chromatin immunoprecipitation; CKD: chronic kidney disease; CM: conditioned medium; COL1A1: collagen, type I, alpha 1; COL4A1: collagen, type IV, alpha 1; CQ: chloroquine; DBA: dolichos biflorus agglutinin; EGR1: early growth response 1; ELK1: ELK1, member of ETS oncogene family; FGF2: fibroblast growth factor 2; FN1: fibronectin 1; GAPDH: glyceraldehyde-3-phosphate dehydrogenase; HAVCR1/KIM-1: hepatitis A virus cellular receptor 1; IP: immunoprecipitation; LIR: LC3-interacting region; MAP1LC3B/LC3B: microtubule-associated protein 1 light chain 3 beta; MAP2K/MEK: mitogen-activated protein kinase kinase; MAPK: mitogen-activated protein kinase; NFKB: nuclear factor kappa B; PB1: Phox and Bem1; PFT: pifithrin α; PPIB/cyclophilin B: peptidylprolyl isomerase B; RT-qPCR: real time-quantitative PCR; SQSTM1/p62: sequestosome 1; TGFB1/TGF-ß1: transforming growth factor beta 1; VIM: vimentin.

Data-driven identification of total RNA expression genes for estimation of RNA abundance in heterogeneous cell types highlighted in brain tissue.

We define and identify a new class of control genes for next-generation sequencing called total RNA expression genes (TREGs), which correlate with total RNA abundance in cell types of different sizes and transcriptional activity. We provide a data-driven method to identify TREGs from single-cell RNA sequencing data, allowing the estimation of total amount of RNA when restricted to quantifying a limited number of genes. We demonstrate our method in postmortem human brain using multiplex single-molecule fluorescent in situ hybridization and compare candidate TREGs against classic housekeeping genes. We identify AKT3 as a top TREG across five brain regions.

Analysis of the Outcomes of Immediate Recurrent Laryngeal Nerve Reconstruction During Thyroid Surgery for Prevention of Vocal Fold Paralysis.

BACKGROUND: Recurrent laryngeal nerve (RLN) injury and the resulting paralysis is the most common and known complication of thyroid surgery. Several surgical techniques, such as medialization thyroplasty with or without arytenoid adduction and injection laryngoplasty, have been developed to treat RLN injury, but these procedures have specific limitations and complications. In this study, we present the outcomes for our patients who underwent immediate RLN reconstruction during thyroid surgery by analyzing both subjective and objective outcomes. METHODS: A retrospective study was conducted for patients who underwent total or subtotal thyroidectomy between May 2012 and March 2020. Among them, patients who underwent immediate RLN reconstruction due to unilateral RLN injury were followed for at least 12 months. The voice perceptual evaluation, acoustic analysis, voice range profile, and Voice Handicap Index (VHI) scores were obtained preoperatively, 1 month, 6 months, and 12 months after surgery. RESULTS: Among the 11 patients, 6 patients (54.5%) underwent direct anastomosis, and 5 patients (45.5%) underwent nerve grafts using ansa cervicalis and great auricular nerve. The grade and breathiness in the GRBAS (grade, roughness, breathiness, asthenia, and strain) scale and jitter item showed significant improvement at 12 months postoperatively, and although not statistically significant, the rest of the items also tended to improve. The total, functional, and physical scores on VHI improved significantly at 12 months postoperatively. Moreover, when comparing the voice analysis of the direct anastomosis group and the nerve graft group, there was no significant difference between the groups in objective and subjective results. CONCLUSION: Immediate RLN reconstruction demonstrated significant voice improvement postoperatively, and reconstructing the nerve immediately and combining follow-up treatment in the event of RLN injury will greatly help patients improve their long-term voice outcomes.

Challenges and opportunities to computationally deconvolve heterogeneous tissue with varying cell sizes using single cell RNA-sequencing datasets.

Deconvolution of cell mixtures in "bulk" transcriptomic samples from homogenate human tissue is important for understanding the pathologies of diseases. However, several experimental and computational challenges remain in developing and implementing transcriptomics-based deconvolution approaches, especially those using a single cell/nuclei RNA-seq reference atlas, which are becoming rapidly available across many tissues. Notably, deconvolution algorithms are frequently developed using samples from tissues with similar cell sizes. However, brain tissue or immune cell populations have cell types with substantially different cell sizes, total mRNA expression, and transcriptional activity. When existing deconvolution approaches are applied to these tissues, these systematic differences in cell sizes and transcriptomic activity confound accurate cell proportion estimates and instead may quantify total mRNA content. Furthermore, there is a lack of standard reference atlases and computational approaches to facilitate integrative analyses, including not only bulk and single cell/nuclei RNA-seq data, but also new data modalities from spatial -omic or imaging approaches. New multi-assay datasets need to be collected with orthogonal data types generated from the same tissue block and the same individual, to serve as a "gold standard" for evaluating new and existing deconvolution methods. Below, we discuss these key challenges and how they can be addressed with the acquisition of new datasets and approaches to analysis.

Assessing the preventive effect of immediate lymphatic reconstruction on the upper extremity lymphedema.

Background: An immediate lymphatic reconstruction (ILR) combining axillary reverse lymphatic mapping (ARLM) and lymphovenous anastomosis (LVA) has been gradually in the spotlight as a novel surgical technique to prevent lymphedema. In this study, we investigate the preventive effect of ILR for the risk of upper extremity lymphedema. We will compare the incidence of postoperative lymphedema between the ILR treatment group and the no-try or failure group during the same period with analysis of the effects of different variables. Methods: In this retrospective cohort study, we analyzed 213 patients who had undergone mastectomy for node-positive unilateral breast cancer in our institution between November 1, 2019 and February 28, 2021. To assess the effect of preventive ILR, we divided the patients into a treatment group (n=30) and a control group (n=183). Univariate and multivariate Cox proportional hazards regression models were used to evaluate the association between ILR and lymphedema occurrence. Results: Of the 30 patients who were attempted, we successfully performed ILRs in 26 patients (86.7%). During a mean follow-up of 14 months, one patient (3.8%) was confirmed to have upper extremity lymphedema in the treatment group, whereas 14 out of 183 patients (7.7%) were diagnosed in the control group. In multivariate analysis, ILR success showed a borderline significant decrease in risk of lymphedema [hazard ratio (HR) =0.174; 95% confidence interval (CI): 0.022-1.374; P=0.097]. Conclusions: Our results suggested that ILR may be a promising surgical treatment to prevent postoperative lymphedema. There is a need for larger studies with longer follow-up to confirm the findings obtained in our study.

Integrated single cell and unsupervised spatial transcriptomic analysis defines molecular anatomy of the human dorsolateral prefrontal cortex.

Generation of a molecular neuroanatomical map of the human prefrontal cortex reveals novel spatial domains and cell-cell interactions relevant for psychiatric disease. The molecular organization of the human neocortex has been historically studied in the context of its histological layers. However, emerging spatial transcriptomic technologies have enabled unbiased identification of transcriptionally-defined spatial domains that move beyond classic cytoarchitecture. Here we used the Visium spatial gene expression platform to generate a data-driven molecular neuroanatomical atlas across the anterior-posterior axis of the human dorsolateral prefrontal cortex (DLPFC). Integration with paired single nucleus RNA-sequencing data revealed distinct cell type compositions and cell-cell interactions across spatial domains. Using PsychENCODE and publicly available data, we map the enrichment of cell types and genes associated with neuropsychiatric disorders to discrete spatial domains. Finally, we provide resources for the scientific community to explore these integrated spatial and single cell datasets at research.libd.org/spatialDLPFC/.

SUFI: an automated approach to spectral unmixing of fluorescent multiplex images captured in mouse and post-mortem human brain tissues.

BACKGROUND: Multispectral fluorescence imaging coupled with linear unmixing is a form of image data collection and analysis that allows for measuring multiple molecular signals in a single biological sample. Multiple fluorescent dyes, each measuring a unique molecule, are simultaneously measured and subsequently "unmixed" to provide a read-out for each molecular signal. This strategy allows for measuring highly multiplexed signals in a single data capture session, such as multiple proteins or RNAs in tissue slices or cultured cells, but can often result in mixed signals and bleed-through problems across dyes. Existing spectral unmixing algorithms are not optimized for challenging biological specimens such as post-mortem human brain tissue, and often require manual intervention to extract spectral signatures. We therefore developed an intuitive, automated, and flexible package called SUFI: spectral unmixing of fluorescent images. RESULTS: This package unmixes multispectral fluorescence images by automating the extraction of spectral signatures using vertex component analysis, and then performs one of three unmixing algorithms derived from remote sensing. We evaluate these remote sensing algorithms' performances on four unique biological datasets and compare the results to unmixing results obtained using ZEN Black software (Zeiss). We lastly integrate our unmixing pipeline into the computational tool dotdotdot, which is used to quantify individual RNA transcripts at single cell resolution in intact tissues and perform differential expression analysis, and thereby provide an end-to-end solution for multispectral fluorescence image analysis and quantification. CONCLUSIONS: In summary, we provide a robust, automated pipeline to assist biologists with improved spectral unmixing of multispectral fluorescence images.

Ascorbate peroxidase-mediated in situ labelling of proteins in secreted exosomes.

The extracellular vesicle exosome mediates intercellular communication by transporting macromolecules such as proteins and ribonucleic acids (RNAs). Determining cargo contents with high accuracy will help decipher the biological processes that exosomes mediate in various contexts. Existing methods for probing exosome cargo molecules rely on a prior exosome isolation procedure. Here we report an in situ labelling approach for exosome cargo identification, which bypasses the exosome isolation steps. In this methodology, a variant of the engineered ascorbate peroxidase APEX, fused to an exosome cargo protein such as CD63, is expressed specifically in exosome-generating vesicles in live cells or in secreted exosomes in the conditioned medium, to induce biotinylation of the proteins in the vicinity of the APEX variant for a short period of time. Mass spectrometry analysis of the proteins biotinylated by this approach in exosomes secreted by kidney proximal tubule-derived cells reveals that oxidative stress can cause ribosomal proteins to accumulate in an exosome subpopulation that contains the CD63-fused APEX variant.

Extracellular Vesicles That Herald the Scarcity of Oxygen.

The natural, membrane-bound nanoscale particles, called extracellular vesicles (EVs) have emerged as an effective, versatile vehicle to transport desired drugs specifically to injury sites. Heralding the presence of the scarcity of oxygen, EVs produced from the cells upregulating the expression of the critical transcriptional regulator of hypoxia, HIF-1, can induce a response in ischemia-reperfusion-damaged cells to ameliorate renal tubular injury and inflammation.

Upregulation of the serine palmitoyltransferase subunit SPTLC2 by endoplasmic reticulum stress inhibits the hepatic insulin response.

Endoplasmic reticulum (ER) stress is induced by various conditions, such as inflammation and the presence of excess nutrients. Abnormal accumulation of unfolded proteins leads to the activation of a collective signaling cascade, termed the unfolded protein response (UPR). ER stress is reported to perturb hepatic insulin response metabolism while promoting insulin resistance. Here, we report that ER stress regulates the de novo biosynthesis of sphingolipids via the activation of serine palmitoyltransferase (SPT), a rate-limiting enzyme involved in the de novo biosynthesis of ceramides. We found that the expression levels of Sptlc1 and Sptlc2, the major SPT subunits, were upregulated and that the cellular concentrations of ceramide and dihydroceramide were elevated by acute ER stress inducers in primary hepatocytes and HepG2 cells. Sptlc2 was upregulated and ceramide levels were elevated by tunicamycin in the livers of C57BL/6J wild-type mice. Analysis of the Sptlc2 promoter demonstrated that the transcriptional activation of Sptlc2 was mediated by the spliced form of X-box binding protein 1 (sXBP1). Liver-specific Sptlc2 transgenic mice exhibited increased ceramide levels in the liver and elevated fasting glucose levels. The insulin response was reduced by the inhibition of the phosphorylation of insulin receptor ß (IRß). Collectively, these results demonstrate that ER stress induces activation of the de novo biosynthesis of ceramide and contributes to the progression of hepatic insulin resistance via the reduced phosphorylation of IRß in hepatocytes.

Differential release of extracellular vesicle tRNA from oxidative stressed renal cells and ischemic kidneys.

While urine-based liquid biopsy has expanded to the analyses of extracellular nucleic acids, the potential of transfer RNA (tRNA) encapsulated within extracellular vesicles has not been explored as a new class of urine biomarkers for kidney injury. Using rat kidney and mouse tubular cell injury models, we tested if extracellular vesicle-loaded tRNA and their m1A (N1-methyladenosine) modification reflect oxidative stress of kidney injury and determined the mechanism of tRNA packaging into extracellular vesicles. We determined a set of extracellular vesicle-loaded, isoaccepting tRNAs differentially released after ischemia-reperfusion injury and oxidative stress. Next, we found that m1A modification of extracellular vesicle tRNAs, despite an increase of the methylated tRNAs in intracellular vesicles, showed little or no change under oxidative stress. Mechanistically, oxidative stress decreases tRNA loading into intracellular vesicles while the tRNA-loaded vesicles are accumulated due to decreased release of the vesicles from the cell surface. Furthermore, Maf1-mediated transcriptional repression of the tRNAs decreases the cargo availability for extracellular vesicle release in response to oxidative stress. Taken together, our data support that release of extracellular vesicle tRNAs reflects oxidative stress of kidney tubules which might be useful to detect ischemic kidney injury and could lead to rebalance protein translation under oxidative stress.

TRIP12 ubiquitination of glucocerebrosidase contributes to neurodegeneration in Parkinson's disease.

Impairment in glucocerebrosidase (GCase) is strongly associated with the development of Parkinson's disease (PD), yet the regulators responsible for its impairment remain elusive. In this paper, we identify the E3 ligase Thyroid Hormone Receptor Interacting Protein 12 (TRIP12) as a key regulator of GCase. TRIP12 interacts with and ubiquitinates GCase at lysine 293 to control its degradation via ubiquitin proteasomal degradation. Ubiquitinated GCase by TRIP12 leads to its functional impairment through premature degradation and subsequent accumulation of α-synuclein. TRIP12 overexpression causes mitochondrial dysfunction, which is ameliorated by GCase overexpression. Further, conditional TRIP12 knockout in vitro and knockdown in vivo promotes the expression of GCase, which blocks α-synuclein preformed fibrils (α-syn PFFs)-provoked dopaminergic neurodegeneration. Moreover, TRIP12 accumulates in human PD brain and α-synuclein-based mouse models. The identification of TRIP12 as a regulator of GCase provides a new perspective on the molecular mechanisms underlying dysfunctional GCase-driven neurodegeneration in PD.

Phosphorylation of slit diaphragm proteins NEPHRIN and NEPH1 upon binding of HGF promotes podocyte repair.

Phosphorylation (activation) and dephosphorylation (deactivation) of the slit diaphragm proteins NEPHRIN and NEPH1 are critical for maintaining the kidney epithelial podocyte actin cytoskeleton and, therefore, proper glomerular filtration. However, the mechanisms underlying these events remain largely unknown. Here we show that NEPHRIN and NEPH1 are novel receptor proteins for hepatocyte growth factor (HGF) and can be phosphorylated independently of the mesenchymal epithelial transition receptor in a ligand-dependent fashion through engagement of their extracellular domains by HGF. Furthermore, we demonstrate SH2 domain-containing protein tyrosine phosphatase-2-dependent dephosphorylation of these proteins. To establish HGF as a ligand, purified baculovirus-expressed NEPHRIN and NEPH1 recombinant proteins were used in surface plasma resonance binding experiments. We report high-affinity interactions of NEPHRIN and NEPH1 with HGF, although NEPHRIN binding was 20-fold higher than that of NEPH1. In addition, using molecular modeling we constructed peptides that were used to map specific HGF-binding regions in the extracellular domains of NEPHRIN and NEPH1. Finally, using an in vitro model of cultured podocytes and an ex vivo model of Drosophila nephrocytes, as well as chemically induced injury models, we demonstrated that HGF-induced phosphorylation of NEPHRIN and NEPH1 is centrally involved in podocyte repair. Taken together, this is the first study demonstrating a receptor-based function for NEPHRIN and NEPH1. This has important biological and clinical implications for the repair of injured podocytes and the maintenance of podocyte integrity.

Extracellular Vesicles in Acute Kidney Injury and Clinical Applications.

Acute kidney injury (AKI)--the sudden loss of kidney function due to tissue damage and subsequent progression to chronic kidney disease--has high morbidity and mortality rates and is a serious worldwide clinical problem. Current AKI diagnosis, which relies on measuring serum creatinine levels and urine output, cannot sensitively and promptly report on the state of damage. To address the shortcomings of these traditional diagnosis tools, several molecular biomarkers have been developed to facilitate the identification and ensuing monitoring of AKI. Nanosized membrane-bound extracellular vesicles (EVs) in body fluids have emerged as excellent sources for discovering such biomarkers. Besides this diagnostic purpose, EVs are also being extensively exploited to deliver therapeutic macromolecules to damaged kidney cells to ameliorate AKI. Consequently, many successful AKI biomarker findings and therapeutic applications based on EVs have been made. Here, we review our understanding of how EVs can help with the early identification and accurate monitoring of AKI and be used therapeutically. We will further discuss where current EV-based AKI diagnosis and therapeutic applications fall short and where future innovations could lead us.