Mesenchymal stem cells-derived exosomes (MSC-exos) have attracted great interest as a cell-free therapy for acute kidney injury (AKI). However, the in vivo biodistribution of MSC-exos in ischemic AKI has not been established. The potential of MSC-exos in promoting tubular repair and the underlying mechanisms remain largely unknown. Methods: Transmission electron microscopy, nanoparticle tracking analysis, and western blotting were used to characterize the properties of human umbilical cord mesenchymal stem cells (hucMSCs) derived exosomes. The biodistribution of MSC-exos in murine ischemia/reperfusion (I/R) induced AKI was imaged by the IVIS spectrum imaging system. The therapeutic efficacy of MSC-exos was investigated in renal I/R injury. The cell cycle arrest, proliferation and apoptosis of tubular epithelial cells (TECs) were evaluated in vivo and in HK-2 cells. The exosomal miRNAs of MSC-exos were profiled by high-throughput miRNA sequencing. One of the most enriched miRNA in MSC-exos was knockdown by transfecting miRNA inhibitor to hucMSCs. Then we investigated whether this candidate miRNA was involved in MSC-exos-mediated tubular repair. Results: Ex vivo imaging showed that MSC-exos was efficiently homing to the ischemic kidney and predominantly accumulated in proximal tubules by virtue of the VLA-4 and LFA-1 on MSC-exos surface. MSC-exos alleviated murine ischemic AKI and decreased the renal tubules injury in a dose-dependent manner. Furthermore, MSC-exos significantly attenuated the cell cycle arrest and apoptosis of TECs both in vivo and in vitro . Mechanistically, miR-125b-5p, which was highly enriched in MSC-exos, repressed the protein expression of p53 in TECs, leading to not only the up-regulation of CDK1 and Cyclin B1 to rescue G2/M arrest, but also the modulation of Bcl-2 and Bax to inhibit TEC apoptosis. Finally, inhibiting miR-125b-5p could mitigate the protective effects of MSC-exos in I/R mice. Conclusion: MSC-exos exhibit preferential tropism to injured kidney and localize to proximal tubules in ischemic AKI. We demonstrate that MSC-exos ameliorate ischemic AKI and promote tubular repair by targeting the cell cycle arrest and apoptosis of TECs through miR-125b-5p/p53 pathway. This study provides a novel insight into the role of MSC-exos in renal tubule repair and highlights the potential of MSC-exos as a promising therapeutic strategy for AKI.
Consider an energy harvesting (EH) sensor that continuously monitors a system and sends time-stamped status update to a destination. The sensor harvests energy from nature and uses it to power its updating operations. The destination keeps track of the system status through the successfully received updates. With the recently introduced information freshness metric "Age of Information" (AoI), our objective is to design optimal online status updating policy to minimize the long-term average AoI at the destination, subject to the energy causality constraint at the sensor. Due to the noisy channel between the sensor and the destination, each transmitted update may be erased with a fixed probability, and the AoI at the destination will be reset to zero only when an update is successfully received. We first consider status updating without feedback available to the sensor and show that the Best-effort Uniform updating (BU) policy is optimal in a broadly defined class of online policies. We then investigate status updating with perfect feedback to the sensor and prove similar optimality of the Best-effort Uniform updating with Retransmission (BUR) policy. In order to prove the optimality of the proposed policies, for each case, we first identify a lower bound on the long-term average AoI among a broad class of online policies, and then construct a sequence of virtual policies to approach the lower bound asymptotically. Since those virtual policies are sub-optimal to the original policy, the original policy is thus optimal.
Background: Acute kidney injury (AKI) is a significant public health problem with high morbidity and mortality. Unfortunately, no definitive treatment is currently available for AKI. RNA interference (RNAi) provides a new and potent method for gene therapy to tackle this dilemma. Methods We engineered red blood cell-derived extracellular vesicles (REVs) with targeting peptides and therapeutic siRNAs to treat experimental AKI in a mouse model following renal ischemia/reperfusion (I/R) injury and unilateral ureteral obstruction (UUO). Phage display identified peptides that bind to the kidney injury molecule-1 (Kim-1). RNA-sequencing (RNA-seq) characterized the transcriptome of ischemic kidney to explore potential therapeutic targets. Results REVs targeted with Kim-1-binding LTH peptide (REVLTH) efficiently homed to and accumulated at the injured tubules in kidney following I/R injury. We identified transcription factors P65 and Snai1 that drive inflammation and fibrosis as potential therapeutic targets. Taking advantage of the established REVLTH, siRNAs targeting P65 and Snai1 were efficiently delivered to ischemic kidney and consequently blocked the expression of P-p65 and Snai1 in tubules. Moreover, dual suppression of P65 and Snai1 significantly improved I/R- and UUO-induced kidney injury by alleviating tubulointerstitial inflammation and fibrosis, and potently abrogated the transition to chronic kidney disease. Conclusions A red blood cell-derived extracellular vesicle platform targeted Kim-1 in acutely injured mouse kidney and delivered siRNAs for transcription factors P65 and Snai1, alleviating inflammation and fibrosis in the tubules.
Consider an energy harvesting sensor continuously monitors a system and sends time-stamped status update to a destination. The destination keeps track of the system status through the received updates. Under the energy causality constraint at the sensor, our objective is to design an optimal online status updating policy to minimize the long-term average Age of Information (AoI) at the destination. We focus on the scenario where the the channel between the source and the destination is noisy, and each transmitted update may fail independently with a constant probability. We assume there is no channel state information or transmission feedback available to the sensor. We prove that within a broadly defined class of online policies, the best-effort uniform updating policy, which was shown to be optimal when the channel is perfect, is still optimal in the presence of update failures. Our proof relies on tools from Martingale processes, and the construction of a sequence of virtual policies.
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