Despite the availabilty of imaging-based and mass-spectrometry-based methods for spatial proteomics, a key challenge remains connecting images with single-cell-resolution protein abundance measurements. Here, we introduce Deep Visual Proteomics (DVP), which combines artificial-intelligence-driven image analysis of cellular phenotypes with automated single-cell or single-nucleus laser microdissection and ultra-high-sensitivity mass spectrometry. DVP links protein abundance to complex cellular or subcellular phenotypes while preserving spatial context. By individually excising nuclei from cell culture, we classified distinct cell states with proteomic profiles defined by known and uncharacterized proteins. In an archived primary melanoma tissue, DVP identified spatially resolved proteome changes as normal melanocytes transition to fully invasive melanoma, revealing pathways that change in a spatial manner as cancer progresses, such as mRNA splicing dysregulation in metastatic vertical growth that coincides with reduced interferon signaling and antigen presentation. The ability of DVP to retain precise spatial proteomic information in the tissue context has implications for the molecular profiling of clinical samples.

Highlights d Robust method automatically adapting to various unseen experimental scenarios d Deep learning solution for accurate nucleus segmentation without user interaction d Accelerates, improves quality, and reduces complexity of bioimage analysis tasks

Uremic cardiomyopathy is characterized by diastolic dysfunction (DD), left ventricular hypertrophy (LVH), and fibrosis. Angiotensin-II plays a major role in the development of uremic cardiomyopathy via nitro-oxidative and inflammatory mechanisms. In heart failure, the beta-3 adrenergic receptor (β3-AR) is up-regulated and coupled to endothelial nitric oxide synthase (eNOS)-mediated pathways, exerting antiremodeling effects. We aimed to compare the antiremodeling effects of the angiotensin-II receptor blocker losartan and the β3-AR agonist mirabegron in uremic cardiomyopathy. Chronic kidney disease (CKD) was induced by 5/6th nephrectomy in male Wistar rats. Five weeks later, rats were randomized into four groups: (1) sham-operated, (2) CKD, (3) losartan-treated (10 mg/kg/day) CKD, and (4) mirabegron-treated (10 mg/kg/day) CKD groups. At week 13, echocardiographic, histologic, laboratory, qRT-PCR, and Western blot measurements proved the development of uremic cardiomyopathy with DD, LVH, fibrosis, inflammation, and reduced eNOS levels, which were significantly ameliorated by losartan. However, mirabegron showed a tendency to decrease DD and fibrosis; but eNOS expression remained reduced. In uremic cardiomyopathy, β3-AR, sarcoplasmic reticulum ATPase (SERCA), and phospholamban levels did not change irrespective of treatments. Mirabegron reduced the angiotensin-II receptor 1 expression in uremic cardiomyopathy that might explain its mild antiremodeling effects despite the unchanged expression of the β3-AR.

A real-time method for fetal heart rate (FHR) monitoring based on signal processing of the fetal heart sounds is presented. The acoustic method, which utilizes an adaptive time pattern analysis to select and analyze those heartbeats that can be recorded without artefact, is guided by a number of rules involving an introduced confidence factor on the timing prediction. The algorithm was implemented in a low-power portable electronic instrument to enable long-term fetal surveillance. A large number of clinical tests have shown the very good performance of the phonocardiographic method in comparison with FHR curves simultaneously recorded with ultrasound cardiotocography. Indeed, approximately 90% of the time, the acoustic FHR curve remained inside a +/- 3 beats/min tolerance limit of the reference ultrasound method. The confidence was typically CF > 0.85. The acoustic method exceeded a +/- 5 beats/min limit relative to the ultrasound method approximately 5% of the time. Finally, no relevant FHR data was measured approximately 5% of the time.