Generative Adversarial Networks Accurately Reconstruct Pan-Cancer Histology from Pathologic, Genomic, and Radiographic Latent Features.

Artificial intelligence models have been increasingly used in the analysis of tumor histology to perform tasks ranging from routine classification to identification of novel molecular features. These approaches distill cancer histologic images into high-level features which are used in predictions, but understanding the biologic meaning of such features remains challenging. We present and validate a custom generative adversarial network - HistoXGAN - capable of reconstructing representative histology using feature vectors produced by common feature extractors. We evaluate HistoXGAN across 29 cancer subtypes and demonstrate that reconstructed images retain information regarding tumor grade, histologic subtype, and gene expression patterns. We leverage HistoXGAN to illustrate the underlying histologic features for deep learning models for actionable mutations, identify model reliance on histologic batch effect in predictions, and demonstrate accurate reconstruction of tumor histology from radiographic imaging for a 'virtual biopsy'.

METTL3 is aberrantly expressed in endometriosis and suppresses proliferation, invasion, and migration of endometrial stromal cells.

Endometriosis (EM) is one of the leading gynecological disorders, and associated with excessive functioning of endometrial stromal cells (ESCs). The current study was conducted to determine the expression and role of methyltransferase-like 3 (METTL3) in the proliferation, invasion, and migration of ESCs in EM. The documented expression levels of METTL3, microRNA (miR)-21-5p, and WNT inhibitory factor 1 (WIF1) in eutopic (Eut) and ectopic (Ect) endometrial tissues and ESCs were determined by a combination of real-time quantitative polymerase chain reaction and Western blot assay. After transfection with pcDNA3.1-METTL3, miR-21-5p mimic, and WIF1 small interfering RNA, cell counting kit-8, colony formation, and Transwell assays were performed in the Ect ESCs (Ect-ESCs). Subsequently, the binding of miR-21-5p to METTL3 was analyzed, along with quantification of the N6-methyladenosine (m6A) level, the enrichments of METTL3 and m6A on WIF1, and the mRNA stability of WIF1. In our findings, METTL3 was downregulated in the EM tissues and cells. METTL3 overexpression intrinsically reduced the proliferation, invasion, and migration of Ect-ESCs. miR-21-5p inhibited the METTL3 expression while METTL3 enhanced the mRNA stability and expression of WIF1 via m6A modification. Additionally, a negative correlation of METTL3 was identified with miR-21-5p along with a positive correlation with the WIF1 mRNA in EM tissues. The miR-21-5p overexpression or WIF1 downregulation enhanced the proliferation, invasion, and migration of Ect-ESCs. Collectively, miR-21-5p inhibited the METTL3-mediated m6A modification and mRNA stability of WIF1, thereby facilitating the proliferation, invasion, and migration of Ect-ESCs.

Development of luminescent nanoswitch for sensing of alkaline phosphatase in human serum based onAl3+-PPi interaction and Cu NCs with AIE properties.

As an important biomarker, alkaline phosphatase (ALP) is one of the most commonly assayed enzymes in clinical practice. Here a novel turn-on fluorescent nanoswitch for ALP assay was suggested. The nanoswitch was easily constructed via two high-affinity ligands between GSH and Al3+ and PPi and Al3+ based on the difference in the affinity. The primary fluorescence of as-prepared GSH capped Cu nanoclusters (NCs) turned on first upon the Al3+ addition due to the Al3+ induced aggregation induced emission (AIE) enhancement based on the high affinity of GSH and Al3+. The presence of PPi then made Al3+ desorb from the surface of GSH capped Cu NCs due to the higher affinity of PPi and Al3+. As a result, the fluorescence of the Cu NCs was quenched. ALP could hydrolyze PPi into phosphate, destroying the PPi-Al3+ complex and releasing Al3+. Thus, the Al3+ binds to GSH again and the fluorescence was restored. The nanoswitch was demonstrated to be sensitive and selective for ALP assay and was successfully used for the ALP assay in the human serum.

Ultrasensitive detection of trypsin activity and inhibitor screening based on the electron transfer between phosphorescence copper nanocluster and cytochrome c.

Trypsin, as one of important proteases, is specific for catalyzing the hydrolysis of peptide and ester bonds containing lysine and arginine residues at the C-terminus. The level of trypsin in biological fluids can serve as a reliable and specific diagnostic biomarker for pancreatic function and its pathological changes. Herein, we demonstrate the application of phosphorescent Cu NCs for trypsin detection for the first time depending on the electron transfer between Cu NCs and cyt c. Cyt c and Cu NCs were selected as the quencher and the fluorophore, respectively. Cu NCs could bind to the positively charged cyt c through electrostatic and hydrophobic interactions, and the phosphorescence of Cu NCs was efficiently quenched by the metal-containing heme of cyt c. In the presence of trypsin, cyt c was digested, thus phosphorescence of Cu NCs remained. Therefore, a new and continuous phosphorescence assay for the detection of trypsin activity and its inhibitor screening was established. The plot of relative fluorescence versus trypsin concentration obtains a good linear detection range from 0 to 20 ng/mL (R2 = 0.9657), and a detection limit of 2 ng/mL, which is much lower than 20 ng/mL of the sensor in buffer solution because of urine amplifying the phosphorescence signal of Cu NCs based on the FRET strategy. This assay still has been successfully applied to trypsin inhibitor screening, demonstrating its potential application in drug discovery.