Abstract: A method for in vitro activation and/or expansion of immune cells is provided, including the steps of: a) providing magnetic particles having multi-protrusive surface modified with at least one type of immuno-inducing substance, in which each magnetic particle includes a copolymer core, a polymer layer, a magnetic substance layer, and a silicon-based layer from the inside to the outside; b) providing a cell solution including at least one type of immune cell in the cell solution; and c) bringing the magnetic particles in contact with the cell solution, in which the at least one type of immuno-inducing substance on the surface of the magnetic particle activates and/or expands the at least one type of immune cell in the cell solution.

Abstract: This application relates generally to automated systems and associated methods for identifying hematological abnormalities. An automated system can include at least one processor that, in operation, is configured to: receive, from a flow cytometer, a flow cytometry data matrix characterizing a tube that is associated with a sample; convert the flow cytometry data matrix into a high dimensional vector; produce a single sample high dimensional vector including a concatenation of multiple high dimensional vectors associated with the sample, wherein the multiple high dimensional vectors comprise the tube high dimensional vector; assemble a training data set including multiple sample high dimensional vectors; receive, from a datastore, outcome information including respective labels associated with each of the multiple sample high dimensional vectors; and train a classifier based on the training data set and the outcome information.

Abstract: This application relates generally to a computer implemented method comprising: receiving a medical record data from a patient, wherein said record comprising a static attribute and a time dependent progression attribute; processing the time dependent progression attributes of medical record data using a trained neural network to into time-series representation, and converting the static attributes into static variables; combining the time-series representation and static variables to multiple vectors; providing a prognosis outcome by a trained classifier using said multiple vectors; wherein the neural network is trained by steps of (a) assembling a training data set comprising a retrospective collection of patients' medical record data wherein said record data comprising collected number of static attributes, time dependent progression attributes and patients' mortality and relapse outcomes; (b) processing the time dependent progression attributes of the training data set using a neural network to convert th

Abstract: This application relates generally to automated systems and methods to identify hematological abnormalities.

Abstract: A method for in vitro activation and/or expansion of immune cells is provided, including the steps of: a) providing magnetic particles having multi-protrusive surface modified with at least one type of immuno-inducing substance, in which each magnetic particle includes a copolymer core, a polymer layer, a magnetic substance layer, and a silicon-based layer from the inside to the outside; b) providing a cell solution including at least one type of immune cell in the cell solution; and c) bringing the magnetic particles in contact with the cell solution, in which the at least one type of immuno-inducing substance on the surface of the magnetic particle activates and/or expands the at least one type of immune cell in the cell solution.