Evaluating the performance of machine learning and variable selection methods to identify document paper using infrared spectral data.

Infrared spectroscopy is a valuable tool for forensic examinations because it realizes nondestructive and rapid analysis. Recent advancements in machine learning have facilitated the development of chemometrics, extending to applications in questioned document examination. In this study, support vector machine (SVM), feedforward neural network (FNN), and random forest (RF) models were constructed using the infrared spectral data of document paper samples to identify the manufacturer of document paper products.

Immunosuppressants inhibit hormone-stimulated Mg2+ uptake in mouse distal convoluted tubule cells.

Immunosuppressants such as cyclosporinA and FK506 (tacrolimus) are widely prescribed to treat numerous disorders and to treat organ transplant recipients. However, cyclosporine A and FK506 are both known to produce hypomagnesaemia. The mechanism of this effect is still unclear.