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The cover shows the postulated neurogenic and direct mechanisms through which serotonin receptors and TRPV4 may induce tissue edema. For more information, see the paper by Retamal et al, this issue, p 851.
Dimethylarginine dimethylamino hydrolase-1 (DDAH-1), as the critical enzyme responsible for asymmetric dimethylarginine (ADMA) degradation, serves as a protective factor for ischemic stroke. DDAH-1 protects ischemia-induced disruption of blood-brain-barrier via regulating ADMA level and preventing tight junction proteins degradation. The supplementation of L-arginine helps restore the function of DDAH-1.
Rett syndrome (RTT) is a rare neurodevelopmental disorder that results in severe multiple disabilities. This study provides evidence that exosomal miR-21-5p from human urine-derived stem cells facilitates early neural formation by regulating the EPha4/TEK axis, and may be a promising therapeutic option for this devastating disease.
M2 microglia-derived EVs inhibit neuronal autophagic activity. Mechanistically, M2 microglia-derived EVs deliver miR-135a-5p into neuronal cells to inhibit TXNIP expression, which further inhibits the activation of NLRP3 inflammasomes, thereby reducing neuronal autophagy and ischemic brain injury. Hence, M2 microglia-derived EVs can serve as novel therapeutic targets for ischemic brain injury.
Serotonin (5-HT) is an important mediator of tissue edema and inflammation. The authors used mouse models and cell-based signaling assays to provide greater understanding of the mechanisms involved. They demonstrate that effects of 5-HT are mediated through the 5-HT2A receptor and involve activation of the mechanosensitive ion channel TRPV4 and neuropeptide release.
Choline attenuates abdominal aortic coarctation-induced cardiac remodeling and cardiac dysfunction, by amelioration of circadian rhythm disruption and attenuation of calcium-handling protein defects. Modulation of vagal activity by choline may have therapeutic potential for cardiac remodeling and heart failure.
The authors show that intraperitoneal injection of tubeimoside I (TBM) alleviates the endothelial dysfunction caused by sepsis. Their results suggest that TBM functions by reducing oxidative stress and apoptosis via SIRT3, an NAD-dependent deacetylase. TBM is therefore a promising new therapeutic agent against sepsis-induced endothelial dysfunction.
This study reports that long non-coding RNA lncRNA SLCO4A1-AS1 regulates the characteristics of colon cancer stem cells. Moreover, SLCO4A1 targets miR-150-3p. LncRNA SLCO4A1-AS1 can be used as ceRNA to adsorb miR-150-3p and thus affect the expression of SLCO4A1. Mechanistically, miR-150-3p can downregulate SLCO4A1, thereby inhibiting migration, invasion, spheroidization and tumor formation of colon cancer stem cells. This study lays a theoretical foundation for in-depth understanding of the pathogenesis of colon cancer and points to new therapeutic targets.
EPHB2 deficiency in prostate cancer cells leads to alterations of the triacylglyceride (TAG) synthesis pathway involved in lipogenesis and lipolysis. These changes initiate de novo cytoplasmic and intranuclear lipid droplets accumulation associated with increased proliferative capacity. Targeting the TAG pathway molecule DGAT1 diminishes the deleterious effects exerted by EPHB2 silencing.
The impact of lowering lipids alone on the pathologic complications of Type 2 diabetes is unknown. Treatment with a novel antisense oligonucleotide directed against ApoC-III lowered triglycerides significantly in the leptin deficient BTBR ob/ob murine model of type 2 diabetes, but did not ameliorate hyperglycemia or improve the nephropathy.
The authors used artificial intelligence to estimate gestational age from scanned whole-slide images of placenta. They developed attention and aggregation deep learning methods because of the large volume of data and tissue heterogeneity. This study provides proof-of-concept in unannotated, unknown images with high accuracy.
The current study reports the assessment of tumor progression in athymic nude mice by Photoacoustic spectroscopy-based machine learning tools. The progressive tumors were classified using multi-class Support Vector Machine (SVM) algorithms with 99.5% accuracy. The serum metabolomic levels during tumor progression complemented photoacoustic spectral features, depicting breast cancer pathophysiology.