Photochemically Mediated Nickel-Catalyzed Synthesis of N-(Hetero)aryl Sulfamides.

A general method for the N-arylation of sulfamides with aryl bromides is described. The protocol leverages a dual-catalytic system, with [Ir(ppy)2(dtbbpy)]PF6 as a photosensitizer, NiBr2·glyme as a precatalyst, and 1,8-diazabicyclo(5.4.0)undec-7-ene (DBU) as a base, and proceeds at room temperature under visible light irradiation. Using these tactics, aryl boronic esters and aryl chlorides can be carried through the reaction untouched. The developed reactions efficiently engage simple bromoarenes and primary sulfamides in between 66% and quantitative yields. For more challenging substrates, such as secondary sulfamides, the reaction efficiency is documented. Thereby, these methods complement the known Buchwald-Hartwig coupling methods for N-arylation of sulfamides.

Deep Learning-Based Kinetic Analysis in Paper-Based Analytical Cartridges Integrated with Field-Effect Transistors.

This study explores the fusion of a field-effect transistor (FET), a paper-based analytical cartridge, and the computational power of deep learning (DL) for quantitative biosensing via kinetic analyses. The FET sensors address the low sensitivity challenge observed in paper analytical devices, enabling electrical measurements with kinetic data. The paper-based cartridge eliminates the need for surface chemistry required in FET sensors, ensuring economical operation (cost < $0.15/test). The DL analysis mitigates chronic challenges of FET biosensors such as sample matrix interference, by leveraging kinetic data from target-specific bioreactions. In our proof-of-concept demonstration, our DL-based analyses showcased a coefficient of variation of <6.46% and a decent concentration measurement correlation with an r2 value of >0.976 for cholesterol testing when blindly compared to results obtained from a CLIA-certified clinical laboratory. These integrated technologies have the potential to advance FET-based biosensors, potentially transforming point-of-care diagnostics and at-home testing through enhanced accessibility, ease-of-use, and accuracy.

Insulin Deficiency From Insulin Gene Mutation Leads to Smaller Pancreas.

OBJECTIVE: To determine the mechanism of reduced pancreas size in type 1 diabetes and the significance of islet-derived insulin in pancreatic growth. RESEARCH DESIGN AND METHODS: Using a validated and standardized MRI protocol, we measured pancreas volume and shape in a family with an autosomal-dominant insulin gene mutation that results in insulin deficiency similar in severity to that of type 1 diabetes but without autoimmunity. DNA sequencing confirmed the mutation in all four affected individuals and none of the four control family members. Insulin secretory capacity was determined by measuring postprandial urinary C-peptide. RESULTS: Family members with this form of monogenic diabetes had a markedly smaller pancreas and a severely impaired postprandial C-peptide level than family members without diabetes. CONCLUSIONS: These results suggest that severe insulin deficiency, rather than islet-directed autoimmunity, leads to reduced pancreas size in type 1 diabetes and that insulin is a major trophic factor for the exocrine pancreas.