SummaryHuman pluripotent stem cell (hPSC)-derived endothelial cells and their progenitors may provide the means for vascularization of tissue-engineered constructs and can serve as models to study vascular development and disease. Here, we report a method to efficiently produce endothelial cells from hPSCs via GSK3 inhibition and culture in defined media to direct hPSC differentiation to CD34+CD31+ endothelial progenitors. Exogenous vascular endothelial growth factor (VEGF) treatment was dispensable, and endothelial progenitor differentiation was β-catenin dependent. Furthermore, by clonal analysis, we showed that CD34+CD31+CD117+TIE-2+ endothelial progenitors were multipotent, capable of differentiating into calponin-expressing smooth muscle cells and CD31+CD144+vWF+I-CAM1+ endothelial cells. These endothelial cells were capable of 20 population doublings, formed tube-like structures, imported acetylated low-density lipoprotein, and maintained a dynamic barrier function. This study provides a rapid and efficient method for production of hPSC-derived endothelial progenitors and endothelial cells and identifies WNT/β-catenin signaling as a primary regulator for generating vascular cells from hPSCs.

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Survival and stemness of bone marrow mesenchymal stem cells (BMSCs) in osteonecrotic areas are especially important in the treatment of early steroid-induced osteonecrosis of the femoral head (ONFH). We had previously used BMSCs to repair early steroid-induced ONFH, but the transplanted BMSCs underwent a great deal of stressinduced apoptosis and aging in the oxidative-stress (OS) microenvironment of the femoral-head necrotic area, which limited their efficacy. Our subsequent studies have shown that under OS, massive accumulation of damaged mitochondria in cells is an important factor leading to stress-induced apoptosis and senescence of BMSCs. The main reason for this accumulation is that OS leads to upregulation of protein 53 (P53), which inhibits mitochondrial translocation of Parkin and activation of Parkin's E3 ubiquitin ligase, which decreases the level of mitophagy and leads to failure of cells to effectively remove damaged mitochondria. However, P53 downregulation can effectively reverse this process. Therefore, we upregulated Parkin and downregulated P53 in BMSCs. We found that this significantly enhanced mitophagy in BMSCs, decreased the accumulation of damaged mitochondria in cells, effectively resisted stress-induced BMSCs apoptosis and senescence, and improved the effect of BMSCs transplantation on early steroidinduced ONFH.

Background Retinopathy of prematurity (ROP) is the leading cause of childhood blindness worldwide. Automated ROP detection system is urgent and it appears to be a safe, reliable, and cost-effective complement to human experts. Methods An automated ROP detection system called DeepROP was developed by using Deep Neural Networks (DNNs). ROP detection was divided into ROP identification and grading tasks. Two specific DNN models, i.e., Id-Net and Gr-Net, were designed for identification and grading tasks, respectively. To develop the DNNs, large-scale datasets of retinal fundus images were constructed by labeling the images of ROP screenings by clinical ophthalmologists. Findings On the test dataset, the Id-Net achieved a sensitivity of 96.62%(95%CI, 92.29%–98.89%) and a specificity of 99.32% (95%CI, 96.29%–9.98%) for ROP identification while the Gr-Net attained sensitivity and specificity values of 88.46% (95%CI, 96.29%–99.98%) and 92.31% (95%CI, 81.46%–97.86%), respectively, on the ROP grading task. On another 552 cases, the developed DNNs outperformed some human experts. In a clinical setting, the sensitivity and specificity values of DeepROP for ROP identification were 84.91% (95%CI, 76.65%–91.12%) and 96.90% (95%CI, 95.49%–97.96%), respectively, whereas the corresponding measures for ROP grading were 93.33%(95%CI, 68.05%–99.83%) and 73.63%(95%CI, 68.05%–99.83%), respectively. Interpretation We constructed large-scale ROP datasets with adequate clinical labels and proposed novel DNN models. The DNN models can directly learn ROP features from big data. The developed DeepROP is potential to be an efficient and effective system for automated ROP screening. Fund National Natural Science Foundation of China under Grant 61432012 and U1435213.

Cancer metabolism has emerged as an indispensable part of contemporary cancer research. During the past 10 years, the use of stable isotopic tracers and network analysis have unveiled a number of metabolic pathways activated in cancer cells. Here, we review such pathways along with the particular tracers and labeling observations that led to the discovery of their rewiring in cancer cells. The list of such pathways comprises the reductive metabolism of glutamine, altered glycolysis, serine and glycine metabolism, mutant isocitrate dehydrogenase (IDH) induced reprogramming and the onset of acetate metabolism. Additionally, we demonstrate the critical role of isotopic labeling and network analysis in identifying these pathways. The alterations described in this review do not constitute a complete list, and future research using these powerful tools is likely to discover other cancer-related pathways and new metabolic targets for cancer therapy.

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Cancer cells exhibit enhanced lactate production to satisfy biosynthetic adenosine triphosphate requirements and also supply ribose 5‐phosphate (R5P) and nicotinamide adenine dinucleotide phosphate via the pentose phosphate pathway (PPP). Yet, little is known about the mechanism by which glycolytic flux is diverted to PPP to fulfill the increased demand for anabolic precursors and reducing equivalents. Here we show, using a 13C‐labeling methodology quantifying glycolysis and the PPP metabolism, that hypoxic cancer cells not only increase net glycolytic flux but also activate the exchange fluxes catalyzed by aldolase and transaldolase. The increased carbon exchange in the upward direction promotes the supplementation of R5P through the nonoxidative PPP and essentially controls the anaplerosis of upper glycolytic metabolites consumed for biosynthesis. This cascade of events is regulated by glyceraldehyde 3‐phosphate dehydrogenase which plays a critical role in diverting metabolites for the synthesis of nucleotide precursors and thus acts as a limiting enzyme under hypoxia. © 2018 American Institute of Chemical Engineers AIChE J, 64: 4289–4296, 2018

Human-machine interfaces (HMIs) are widely studied to understand the human biomechanics and/or physiology and the interaction between humans and machines/robots. The conventional rigid or invasive HMIs that record/send information from/to human bodies have significant disadvantages in practice for longterm, portable, and comfortable usages. To better adapt to natural soft skins, soft HMIs have been designed to deform into arbitrary shapes, and their bendable, stretchable, compressible and twistable properties offer a huge potential in future personalized applications. This paper presents a survey on various soft HMIs in terms of design, sensing, stimulation as well as their applications. Specifically, tactile / motion / bio-potential sensors are categorized for recording various data from human bodies, while stimulators are discussed for information feedback and motion activation to human bodies. It is anticipated that soft HMIs will promote the interaction among humans, machines/robots and environment to achieve desired coexisting-cooperativecognitive function in a robot system, named as Tri-Co Robot, for the human-centered applications, such as rehabilitation, medical monitoring and human-robot cooperation.