Towards Early Prediction of Human iPSC Reprogramming Success

This paper presents advancements in automated early-stage prediction of the success of reprogramming human induced pluripotent stem cells (iPSCs) as a potential source for regenerative cell therapies.The minuscule success rate of iPSC-reprogramming of around $0.01$ to $0.1$ makes it labor-intensive, time-consuming, and exorbitantly expensive to generate a stable iPSC line. Since that requires culturing of millions of cells and intense biological scrutiny of multiple clones to identify a single optimal clone. The ability to reliably predict which cells are likely to establish as an optimal iPSC line at an early stage of pluripotency would therefore be ground-breaking in rendering this a practical and cost-effective approach to personalized medicine. Temporal information about changes in cellular appearance over time is crucial for predicting its future growth outcomes. In order to generate this data, we first performed continuous time-lapse imaging of iPSCs in culture using an ultra-high resolution microscope. We then annotated the locations and identities of cells in late-stage images where reliable manual identification is possible. Next, we propagated these labels backwards in time using a semi-automated tracking system to obtain labels for early stages of growth. Finally, we used this data to train deep neural networks to perform automatic cell segmentation and classification. Our code and data are available at https://github.com/abhineet123/ipsc_prediction.Comment: Accepted for publication at the Journal of Machine Learning for Biomedical Imaging (MELBA) https://melba-journal.org/2023:01

Uremic encephalopathy manifesting with a unique MRI finding (the lentiform fork sign) in an adult male: A case report

Key Clinical Message A novel radiologic sign in patients with renal failure and uremic encephalopathy (UE) with metabolic acidosis has recently been identified as the lentiform fork sign. On magnetic resonance imaging (MRI), the “lentiform fork sign” has been described as bilateral symmetrical hyperintensities in the basal ganglia encircled by a hyperintese rim delineating the lentiform nucleus. Changes in uremic solute retention, aberrant blood–brain barrier transport, disordered vascular reactivity, altered electrolyte and acid–base balance, and altered hormone metabolism are the most likely causes of the condition. A 56‐year‐old male with end‐stage renal disease was brought to the emergency room for a progressive change in mental status and involuntary arm movements over the previous 5 days, which were accompanied by mild dyspnea. A brain MRI was performed, and it revealed hyperintensity on T2/FLAIR in the white matter surrounding the basal ganglia. the patient was treated with dialysis and improved greatly. Intensified hemodialysis and glycemic control are the cornerstones of treating diabetic uremic syndrome (DUS) with likely reversible clinical symptoms and remission of imaging abnormalities