Publications by authors named "M A Shulman"

Unlabelled: The Alzheimer's disease (AD) research community continues to make great strides in expanding approaches for early detection and treatment of the disease, including recent advances in our understanding of fundamental AD pathophysiology beyond the classical targets: beta-amyloid and tau. Recent clinical trial readouts implicate a variety of non-amyloid/non-tau (NANT) approaches that show promise in slowing cognitive decline for people with AD. The Alzheimer's Association Research Roundtable (AARR) meeting held on December 13-14, 2022, reviewed the current state of NANT targets on underlying AD pathophysiology and their contribution to cognitive decline, the current data on a diverse range of NANT biomarkers and therapeutic targets, and the integration of NANT concepts in clinical trial designs.

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We present here a passive and label-free droplet microfluidic platform to sort cells stepwise by lactate and proton secretion from glycolysis. A technology developed in our lab, Sorting by Interfacial Tension (SIFT), sorts droplets containing single cells into two populations based on pH by using interfacial tension. Cellular glycolysis lowers the pH of droplets through proton secretion, enabling passive selection based on interfacial tension and hence single-cell glycolysis.

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Life histories of oviparous species dictate high metabolic investment in the process of gonadal development leading to ovulation. In vertebrates, these two distinct processes are controlled by the gonadotropins follicle-stimulating hormone (FSH) and luteinizing hormone (LH), respectively. While it was suggested that a common secretagogue, gonadotropin-releasing hormone (GnRH), oversees both functions, the generation of loss-of-function fish challenged this view.

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The rapid adoption of single-cell technologies has created an opportunity to build single-cell 'atlases' integrating diverse datasets across many laboratories. Such atlases can serve as a reference for analyzing and interpreting current and future data. However, it has become apparent that atlasing approaches differ, and the impact of these differences are often unclear.

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Targeted spatial transcriptomic methods capture the topology of cell types and states in tissues at single-cell and subcellular resolution by measuring the expression of a predefined set of genes. The selection of an optimal set of probed genes is crucial for capturing the spatial signals present in a tissue. This requires selecting the most informative, yet minimal, set of genes to profile (gene set selection) for which it is possible to build probes (probe design).

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