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Extracellular vesicles (EVs) secreted by human‐induced pluripotent stem cells (hiPSCs) have great potential as cell‐free therapies in various diseases, including prevention of blood–brain barrier senescence and stroke. However, there are still challenges in pre‐clinical and clinical use of hiPSC‐EVs due to the need for large‐scale production of a large quantity. Vertical‐Wheel bioreactors (VWBRs) have design features that allow the biomanufacturing of hiPSC‐EVs using a scalable aggregate or microcarrier‐based culture system under low shear stress. EV secretion by undifferentiated hiPSCs expanded as 3‐D aggregates and on Synthemax II microcarriers in VWBRs were investigated. Additionally, two types of EV collection media, mTeSR and HBM, were compared. The hiPSCs were characterized by metabolite and transcriptome analysis as well as EV biogenesis markers. Protein and microRNA cargo were analysed by proteomics and microRNA‐seq, respectively. Thein vitrofunctional assays of microglia stimulation and proliferation were conducted. HiPSCs expanded as 3‐D aggregates and on microcarriers had comparable cell number, while microcarrier culture had higher glucose consumption, higher glycolysis and lower autophagy gene expression based on mRNA‐seq. The microcarrier cultures had at least 17–23 fold higher EV secretion, and EV collection in mTeSR had 2.7–3.7 fold higher yield than HBM medium. Microcarrier culture with mTeSR EV collection had a smaller EV size than other groups, and the cargo was enriched with proteins (proteomics) and miRNAs (microRNA‐seq) reducing apoptosis and promoting cell proliferation (e.g. Wnt‐related pathways). hiPSC‐EVs demonstrated the ability of stimulating proliferation and M2 polarization of microgliain vitro. HiPSC expansion on microcarriers produces much higher yields of EVs than hiPSC aggregates in VWBRs. EV collection in mTeSR increases yield compared to HBM. The biomanufactured EVs from microcarrier culture in mTeSR have exosomal characteristics and are functional in microglia stimulation, which paves the ways for future in vivo anti‐aging study.

 

We conduct a systematic search for quasars with periodic variations from the archival photometric data of the Zwicky Transient Facility by cross-matching with the quasar catalogues of the Sloan Digital Sky Survey and Véron-Cetty and Véron. We first select out 184 primitive periodic candidates using the generalized Lomb–Scargle periodogram and autocorrelation function and then estimate their statistical significance of periodicity based on two red-noise models, i.e. damped random walk (DRW) and single power-law (SPL) models. As such, we finally identify 106 (DRW) and 86 (SPL) candidates with the most significant periodic variations out of 143 700 quasars. We further compare DRW and SPL models using Bayes factors, which indicate a relative preference of the SPL model for our primitive sample. We thus adopt the candidates identified with SPL as the final sample and summarize its basic properties. We extend the light curves of the selected candidates by supplying other archival survey data to verify their periodicity. However, only three candidates (with 6–8 cycles of periods) meet the selection criteria. This result clearly implies that, instead of being strictly periodic, the variability must be quasi-periodic or caused by stochastic red-noise. This exerts a challenge to the existing search approaches and calls for developing new effective methods.

 

Mapping of spatial hotspots, i.e., regions with significantly higher rates of generating cases of certain events (e.g., disease or crime cases), is an important task in diverse societal domains, including public health, public safety, transportation, agriculture, environmental science, and so on. Clustering techniques required by these domains differ from traditional clustering methods due to the high economic and social costs of spurious results (e.g., false alarms of crime clusters). As a result, statistical rigor is needed explicitly to control the rate of spurious detections. To address this challenge, techniques for statistically-robust clustering (e.g., scan statistics) have been extensively studied by the data mining and statistics communities. In this survey, we present an up-to-date and detailed review of the models and algorithms developed by this field. We first present a general taxonomy for statistically-robust clustering, covering key steps of data and statistical modeling, region enumeration and maximization, and significance testing. We further discuss different paradigms and methods within each of the key steps. Finally, we highlight research gaps and potential future directions, which may serve as a stepping stone in generating new ideas and thoughts in this growing field and beyond. 

Abstract Extracellular matrix (ECM) in the human tissue contains vesicles, which are defined as matrix‐bound nanovesicles (MBVs). MBVs serve as one of the functional components in ECM, recapitulating part of the regulatory roles and in vivo microenvironment. In this study, extracellular vesicles from culture supernatants (SuEVs) and MBVs are isolated from the conditioned medium or ECM, respectively, of 3D human mesenchymal stem cells. Nanoparticle tracking analysis shows that MBVs are smaller than SuEVs (100–150 nm). Transmission electron microscopy captures the typical cup shape morphology for both SuEVs and MBVs. Western blot reveals that MBVs have low detection of some SuEV markers such as syntenin‐1. miRNA analysis of MBVs shows that 3D microenvironment enhances the expression of miRNAs such as miR‐19a and miR‐21. In vitro functional analysis shows that MBVs can facilitate human pluripotent stem cell‐derived forebrain organoid recovery after starvation and promote high passage fibroblast proliferation. In macrophage polarization, 2D MBVs tend to suppress the pro‐inflammatory cytokine IL‐12 β , while 3D MBVs tend to enhance the anti‐inflammatory cytokine IL‐10. This study has the significance in advancing the understanding of the bio‐interface of nanovesicles with human tissue and the design of cell‐free therapy for treating neurological disorders such as ischemic stroke. 

Polymer-derived ceramics (PDCs) which are fabricated through pyrolysis of preceramic polymers have attracted increasing attention due to their versatility in structure architecture design and property tailoring. Shaping at the polymer state using 3D printing allows the final ceramic products to exhibit arbitrary shapes and complex architectures that are otherwise impossible to achieve through traditional processing routes. The polymer-to-ceramic phase transition also provides additional space for mechanical property tailoring. A multiscale computational model is developed to explore the phase transition mechanisms and their correlations with processing parameters and failure response. Calculations in this work concern PMHS/DVB preceramic polymers. Molecular dynamics (MD) simulations are carried out first to track the atomic structure evolution at different temperatures. Continuum-scale ceramic phase formation is calculated on the basis of the competition between gas generation and gas diffusion. The effect of processing parameters on mechanical properties of pyrolyzed PMHS/DVB is systematically studied. Conclusions from this study can provide direct guidance for fabricating PDC composites with tailored mechanical properties.