Polarimetric Compressed Sensing with Hollow, Self-Assembled Diffractive Films.

Sensing light's polarization and wavefront direction enables surface curvature assessment, material identification, shadow differentiation, and improved image quality in turbid environments. Traditional polarization cameras utilize multiple sensor measurements per pixel and polarization-filtering optics, which result in reduced image resolution. We propose a nanophotonic pipeline that enables compressive sensing and reduces the sampling requirements with a low-refractive-index, self-assembled optical encoder.

An appropriate DNA input for bisulfite conversion reveals LINE-1 and Alu hypermethylation in tissues and circulating cell-free DNA from cancers.

The autonomous and active Long-Interspersed Element-1 (LINE-1, L1) and the non-autonomous Alu retrotransposon elements, contributing to 30% of the human genome, are the most abundant repeated sequences. With more than 90% of their sequences being methylated in normal cells, these elements undeniably contribute to the global DNA methylation level and constitute a major part of circulating-cell-free DNA (cfDNA). So far, the hypomethylation status of LINE-1 and Alu in cellular and extracellular DNA has long been considered a prevailing hallmark of ageing-related diseases and cancer.

Hypermethylation at 45S rDNA promoter in cancers.

The ribosomal genes (rDNA genes) encode 47S rRNA which accounts for up to 80% of all cellular RNA. At any given time, no more than 50% of rDNA genes are actively transcribed, and the other half is silent by forming heterochromatin structures through DNA methylation. In cancer cells, upregulation of ribosome biogenesis has been recognized as a hallmark feature, thus, the reduced methylation of rDNA promoter has been thought to support conformational changes of chromatin accessibility and the subsequent increase in rDNA transcription.

Prediction of checkpoint inhibitor immunotherapy efficacy for cancer using routine blood tests and clinical data.

Predicting whether a patient with cancer will benefit from immune checkpoint inhibitors (ICIs) without resorting to advanced genomic or immunologic assays is an important clinical need. To address this, we developed and evaluated SCORPIO, a machine learning system that utilizes routine blood tests (complete blood count and comprehensive metabolic profile) alongside clinical characteristics from 9,745 ICI-treated patients across 21 cancer types. SCORPIO was trained on data from 1,628 patients across 17 cancer types from Memorial Sloan Kettering Cancer Center.

Development and validation of a gonadotropin dose selection model for optimized ovarian stimulation in IVF/ICSI: an individual participant data meta-analysis.

Background: The ovarian response to gonadotropin stimulation varies widely among women, and could impact the probability of live birth as well as treatment risks. Many studies have evaluated the impact of different gonadotropin starting doses, mainly based on predictive variables like ovarian reserve tests (ORT) including anti-Müllerian hormone (AMH), antral follicle count (AFC), and basal follicle-stimulating hormone (bFSH). A Cochrane systematic review revealed that individualizing the gonadotropin starting dose does not affect efficacy in terms of ongoing pregnancy/live birth rates, but may reduce treatment risks such as the development of ovarian hyperstimulation syndrome (OHSS).