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# Single-Cell Profiling

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  1. Cell Discovery

    Single-cell epigenome library prep drops from a week to a day: droplet microfluidics with nanopore long reads handles about 5,000 cells at once

    Single-cell epigenome sequencing has moved its barcoding step off the plate and into droplets. Long-read single-cell ATAC and CUT&Tag previously ran well by well, needing at least a week of library work for about 5,000 cells at high cost. Now nuclei are co-encapsulated with barcoded beads on a commercial microfluidic chip and read on Nanopore: about 5,000 cells per run, one day of library prep instead of a week, and roughly $0.39 per cell instead of $1.98. In GM12878, 10,000 input nuclei produced 66 Gb, with 82.8% of reads on valid cell barcodes.

  2. medRxiv

    Blood smears stop at 200 cells: a neural cellular automaton scans the whole slide and holds F1 0.79 across centers

    Automated blood and bone marrow smear analysis had been confined to manually selected regions of interest because gigapixel whole-slide scanning is computationally heavy. HemAutomaton uses a neural cellular automaton to locate white blood cells across entire slides without manual region selection, matching Faster R-CNN in-domain detection and reaching a mean cross-domain F1 of 0.79 versus 0.65, with 3.3k trainable parameters against 41.4M. Across three blood cancer cohorts it extracted 108 million single-cell images and performed automated differential counting through few-shot classification with a pretrained hematology foundation model.

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