Human Transplant Kidneys on Normothermic Machine Perfusion Display Endocrine Activity

Background. Normothermic machine perfusion (NMP) is an alternative to hypothermic machine perfusion (HMP) for donor kidney preservation before transplantation. Contrary to HMP, NMP allows for functional assessment of donor kidneys because normothermic conditions allow for metabolic activity. The kidneys are key producers of hormones. Yet, it remains unknown whether donor kidneys during NMP display endocrine functions. Methods. Fifteen donor kidneys were subjected to HMP followed by 2 h of NMP before transplantation. NMP perfusate was collected at 3 time points (0, 1, 2 h) for the measurements of prorenin/renin, erythropoietin (EPO), and vitamin D, and urine samples were collected at 1 h and 2 h for urodilatin measurement. Fifteen HMP perfusate samples were collected for the same measurements. Results. Kidneys on NMP secreted significantly more prorenin, renin, EPO, and active vitamin D than during HMP. EPO and vitamin D secretion remained stable during 2 h of NMP, whereas the prorenin release rate increased and renin release rate decreased after 1 h. Donation after brain death kidneys secreted more vitamin D and less EPO during NMP than donation after circulatory death kidneys. Twelve donor kidneys produced urine during NMP and released detectable levels of urodilatin. Kidneys exhibited a large variation in hormone release rates. No significant differences were found in hormone release capacity between delayed graft function (DGF) and non-DGF kidneys, and no significant correlations were found between hormone release rates and the duration of DGF or 1-mo posttransplant serum creatinine levels. Conclusions. Human transplant kidneys display endocrine activity during NMP. To explore whether correlations exist between hormone release rates and posttransplant kidney function, large numbers of kidneys are required.</p

MicroRNA-93 Regulates Hypoxia-Induced Autophagy by Targeting ULK1

The expression of the core autophagy kinase, Unc51-like kinase 1 (ULK1), is regulated transcriptionally and translationally by starvation-induced autophagy. However, how ULK1 is regulated during hypoxia is not well understood. Previously, we showed that ULK1 expression is induced by hypoxia stress. Here, we report a new ULK1-modulating microRNA, miR-93; its transcription is negatively correlated with the translation of ULK1 under hypoxic condition. miR-93 targets ULK1 and reduces its protein levels under hypoxia condition. miR-93 also inhibits hypoxia-induced autophagy by preventing LC3-I to LC3-II transition and P62 degradation; these processes are reversed by the overexpression of an endogenous miR-93 inhibitor. Re-expression of ULK1 without miR-93 response elements restores the hypoxia-induced autophagy which is inhibited by miR-93. Finally, we detected the effects of miR-93 on cell viability and apoptosis in noncancer cell lines and cancer cells. We found that miR-93 sustains the viability of MEFs (mouse embryonic fibroblasts) and inhibits its apoptosis under hypoxia. Thus, we conclude that miR-93 is involved in hypoxia-induced autophagy by regulating ULK1. Our results provide a new angle to understand the complicated regulation of the key autophagy kinase ULK1 during different stress conditions

Human kidney organoids produce functional renin

Renin production by the kidney is of vital importance for salt, volume, and blood pressure homeostasis. The lack of human models hampers investigation into the regulation of renin and its relevance for kidney physiology. To develop such a model, we used human induced pluripotent stem cell–derived kidney organoids to study the role of renin and the renin-angiotensin system in the kidney. Extensive characterization of the kidney organoids revealed kidney-specific cell populations consisting of podocytes, proximal and distal tubular cells, stromal cells and endothelial cells. We examined the presence of various components of the renin-angiotensin system such as angiotensin II receptors, angiotensinogen, and angiotensin-converting enzymes 1 and 2. We identified by single-cell sequencing, immunohistochemistry, and functional assays that cyclic AMP stimulation induces a subset of pericytes to increase the synthesis and secretion of enzymatically active renin. Renin production by the organoids was responsive to regulation by parathyroid hormone. Subcutaneously implanted kidney organoids in immunodeficient IL2Ry-/-Rag2-/- mice were successfully vascularized, maintained tubular and glomerular structures, and retained capacity to produce renin two months after implantation. Thus, our results demonstrate that kidney organoids express renin and provide insights into the endocrine potential of human kidney organoids, which is important for regenerative medicine in the context of the endocrine system

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Security and Privacy of Collaborative Spectrum Sensing in Cognitive Radio Networks

International audienceCollaborative spectrum sensing is regarded as a promising approach to significantly improve the performance of spectrum sensing in cognitive radio networks. However, due to the open nature of wireless communications and the increasingly available software defined radio platforms, collaborative spectrum sensing also poses many new research challenges, especially in the aspect of security and privacy. In this article, we first identify the potential security threats toward collaborative spectrum sensing in CRNs. Then we review the existing proposals related to secure collaborative spectrum sensing. Furthermore, we identify several new location privacy related attacks in collaborative sensing, which are expected to compromise secondary users¿ location privacy by correlating their sensing reports and their physical location. To thwart these attacks, we propose a novel privacy preserving framework in collaborative spectrum sensing to prevent location privacy leaking. We design and implement a real-world testbed to evaluate the system performance. The attack experiment results show that if there is no any security guarantee, the attackers could successfully compromise a secondary user¿s location privacy at a success rate of more than 90 percent. We also show that the proposed privacy preserving framework could significantly improve the location privacy of secondary users with a minimal effect on the performance of collaborative sensing

Green forage and fattening duration differentially modulate cecal microbiome of Wanxi white geese.

Gut microbial ecology is responsible for fatty acid metabolism in ruminants. The cecal microbiota composition of geese and their adaptation to fiber inclusion and feeding timeswere investigated in this study. A total of 116 Wanxi white geese were randomly selected at 70 days old. Eight geese were subjected to cecal sampling at 70 d of age, and the remaining 108 geese were divided into four groups with three replicates each (9 geese in each replicate). The geese in the four groups were fed 0, 15, 30, and 45% green forage (relative to dry matter), respectively. Three birds from each replicate were selected for cecal sampling at 80, 90, and 100 days old. All samples were subjected to 16S rRNA gene sequencing using the Illumina Ion Personal Genome Machine platform. Bacterial abundance was analyzed using two-way ANOVA analysis, and the relationship between the relative abundance of bacteria (phylum level) and fatty acids was analyzed using acanonical correspondence analysis. Cecal microbiota in geese were mainly composed of Bacteroidetes (68.46%), Firmicutes (20.04%), and Proteobacteria (7.89%). Dietary treatments had no significant effect on the α-diversity indices of the cecal bacterial community (P > 0.05), but a numerical increase occurred with increased fattening duration and green forage inclusion. The Selenomonadales order (P = 0.024), Negativicutes class (P = 0.026), and Megamonas (P = 0.012) and Oscillospira (P = 0.042) genera were affected by green forageinclusion level, and microflora abundance was mainly influenced by the fattening duration. Bacteria phyla were mostly set along the line of linolenic acid and oleic acid. Finally, Bacteroidales might be an intestinal promoter that improves unsaturated fatty acid synthesis in geese

Adaptive Industrial Control System Attack Sample Expansion Algorithm Based on Generative Adversarial Network

The scarcity of attack samples is the bottleneck problem of anomaly detection of underlying business data in the industrial control system. Predecessors have done a lot of research on temporal data generation, but most of them are not suitable for industrial control attack sample generation. The change patterns of the characteristics of the underlying business data attack samples can be divided into three types: oscillation type, step type, and pulse type. This paper proposes an adaptive industrial control attack sample expansion algorithm based on GAN, which expands the three types of features in different ways. The basic network structure of data expansion adopts GAN. According to the characteristics of oscillation type changes, momentum is selected as the optimizer. Aiming at the characteristics of step type changes, the Adam optimization method is improved. For pulse type features, attack samples are generated according to the location and length of the pulse. Compared with previous time-series data generation methods, this method is more targeted for each feature and has higher similarities