Anti-ADC (aa 179-228) polyclonal antibody

This brief presents a 2(nd)-order noise-shaping (NS) successive approximation register (SAR) analog-to-digital converter (ADC) with a lossless integrator for achieving low power and high NS efficiency. It implements the lossless integrator through a ping-pong structure and a low-gain dynamic amplifier with moderate gain variation tolerance. Taking advantage of the lossless integrator, a low resolution SAR ADC is allowed under the same quantization noise budget. Fabricated in a 65-nm CMOS process, the prototype 8-bit NS-SAR ADC consumes 1.24 mW at 1.2 V while operating at 100 MS/s. It achieves a peak signal to noise and distortion ratio (SNDR) of 77 dB over a bandwidth of 3.125 MHz at the oversampling ratio (OSR) of 16, leading to an SNDR-based Schreier figure of merit (FoM) of 171 dB.

Purpose: To investigate mono-exponential, bi-exponential, and stretched-exponential models of diffusion-weighted imaging (DWI) for evaluation of prognosis-related risk factors of endometrial cancer (EC). Method: Sixty-one consecutive patients with EC who preoperatively underwent pelvic MRI with multiple b value DWI between September 2016 and May 2018 were enrolled. The apparent-diffusion-coefficient (ADC), bi-exponential model parameters (D, D* and f) and stretched-exponential model parameters (DDC and alpha) were measured and compared to analyze the following prognosis-related risk factors confirmed by pathology: histological grade, depth of myometrial invasion, cervical stromal infiltration (CSI) and lymphovascular invasion (LVSI). A stepwise multilvariate logistic regression and the receiver operating characteristic (ROC) curves were performed for further statistical analysis. Results: Lower ADC, D, f, and DDC were observed in tumor with high grade compared with a low-grade group, and the largest area under curve (AUC) was obtained when combining f and DDC values. ADC, D, f, DDC, and alpha were significantly different in patients with deep myometrial invasion (DMI) compared to those without DMI; the combination of f, DDC and a showed the highest AUC. Significantly different ADC and f were found between patients' presence and absence CSI; the f values showed the highest diagnostic performance with an AUC of 0.825. Regarding the LVSI, ADC, D*, f, and DDC were significantly lower in tumors with LVSI compared to those without LVSI; the combination of f and DDC showed the largest AUC. Conclusion: Multiple mathematical DWI models are a useful approach for the prediction of prognosis-related risk factors in EC.