Loss of Endothelial Annexin A1 Aggravates Inflammation-Induched Vascular Aging.

Chronic inflammation is increasingly considered as the most important component of vascular aging, contributing to the progression of age-related cardiovascular diseases. To delay the process of vascular aging, anti-inflammation may be an effective measure. The anti-inflammatory factor annexin A1 (ANXA1) is shown to participate in several age-related diseases; however, its function during vascular aging remains unclear. Here, an ANXA1 knockout (ANXA1-/-) and an endothelial cell-specific ANXA1 deletion mouse (ANXA1△EC) model are used to investigate the role of ANXA1 in vascular aging. ANXA1 depletion exacerbates vascular remodeling and dysfunction while upregulates age- and inflammation-related protein expression. Conversely, Ac2-26 (a mimetic peptide of ANXA1) supplementation reverses this phenomenon. Furthermore, long-term tumor necrosis factor-alpha (TNF-α) induction of human umbilical vein endothelial cells (HUVECs) increases cell senescence. Finally, the senescence-associated secretory phenotype and senescence-related protein expression, rates of senescence-ß-galactosidase positivity, cell cycle arrest, cell migration, and tube formation ability are observed in both ANXA1-knockdown HUVECs and overexpressed ANXA1-TNF-α induced senescent HUVECs. They also explore the impact of formyl peptide receptor 2 (a receptor of ANXA1) in an ANXA1 overexpression inflammatory model. These data provide compelling evidence that age-related inflammation in arteries contributes to senescent endothelial cells that promote vascular aging.

Interband cascade laser based mid-infrared methane sensor system using a novel electrical-domain self-adaptive direct laser absorption spectroscopy (SA-DLAS).

To suppress sensor noise with unknown statistical properties, a novel self-adaptive direct laser absorption spectroscopy (SA-DLAS) technique was proposed by incorporating a recursive, least square (RLS) self-adaptive denoising (SAD) algorithm and a 3291 nm interband cascade laser (ICL) for methane (CH4) detection. Background noise was suppressed by introducing an electrical-domain noise-channel and an expectation-known-based RLS SAD algorithm. Numerical simulations and measurements were carried out to validate the function of the SA-DLAS technique by imposing low-frequency, high-frequency, White-Gaussian and hybrid noise on the ICL scan signal. Sensor calibration, stability test and dynamic response measurement were performed for the SA-DLAS sensor using standard or diluted CH4 samples. With the intrinsic sensor noise considered only, an Allan deviation of ~43.9 ppbv with a ~6 s averaging time was obtained and it was further decreased to 6.3 ppbv with a ~240 s averaging time, through the use of self-adaptive filtering (SAF). The reported SA-DLAS technique shows enhanced sensitivity compared to a DLAS sensor using a traditional sensing architecture and filtering method. Indoor and outdoor atmospheric CH4 measurements were conducted to validate the normal operation of the reported SA-DLAS technique.