Abstract: Included in the present disclosure is a system, including an electronic document. In some examples, the electronic document includes a work of authorship. According to some examples, the electronic document includes a topic of the work. The electronic document can include a topic tag configured to identify the topic. In some examples, the system includes a tag generator configured to identify a portion of the work of authorship related to the topic tag using a large language model.

Abstract: Methods of treating a subject suffering from an autoimmune disease, disorder, or condition with an alternative to anti-TNF therapy.

Abstract: A field-replaceable unit is reversibly secured in place using two captive fasteners. Each fastener includes a telescoping knob that rotates 180 degrees in a first direction to engage a latch mechanism and rotates 180 degrees in the opposite direction to disengage the latch mechanism. The knob automatically extends when the latch mechanism is disengaged. The knob alternately extends and retracts in response to being successively pressed when the latch mechanism is engaged. The knob has two cutaways formed along outside edges to facilitate a two-finger grip for knob rotation and pulling the unit out of another module. A circular groove centered on an axis of rotation of the knob has a contrasting coloration and provides a visual and tactile indication of know location. A nub indicates rotational position of the knob.

Abstract: Presented herein are systems and methods for developing classifiers useful for predicting response to particular treatments. For example, in some embodiments, the present disclosure provides a method of treating subjects suffering from an autoimmune disorder, the method comprising administering an alternative to anti-TNF therapy to subjects who have been determined to be non-responsive via a classifier established to distinguish between responsive and non-responsive prior subjects in a cohort who have received the anti-TNF therapy.

Abstract: Presented herein are systems and methods for developing classifiers useful for predicting response to particular treatments. For example, in some embodiments, the present disclosure provides a method of treating subjects suffering from an autoimmune disorder, the method comprising administering an alternative to anti-TNF therapy to subjects who have been determined to be non-responsive via a classifier established to distinguish between responsive and non-responsive prior subjects in a cohort who have received the anti-TNF therapy.

Abstract: Methods and systems for administering therapy to subjects who have been determined to not display a gene expression response signature established to distinguish between responsive and non-responsive prior subjects who have received anti-TNF therapy.

Abstract: Presented herein are systems and methods for developing classifiers useful for predicting response to particular treatments. For example, in some embodiments, the present disclosure provides a method of treating subjects suffering from an autoimmune disorder, the method comprising administering an alternative to anti-TNF therapy to subjects who have been determined to be non-responsive via a classifier established to distinguish between responsive and non-responsive prior subjects in a cohort who have received the anti-TNF therapy.

Abstract: Presented herein are systems and methods for developing classifiers useful for predicting response to particular treatments. For example, in some embodiments, the present disclosure provides a method of treating subjects suffering from an autoimmune disorder, the method comprising a step of: administering an anti-TNF therapy to subjects who have been determined to be responsive via a classifier established to distinguish between responsive and non-responsive prior subjects in a cohort who have received the anti-TNF therapy.

Abstract: Presented herein are systems and methods for developing classifiers useful for predicting response to particular treatments. For example, in some embodiments, the present disclosure provides a method of treating subjects suffering from an autoimmune disorder, the method comprising a step of: administering an anti-TNF therapy to subjects who have been determined to be responsive via a classifier established to distinguish between responsive and non-responsive prior subjects in a cohort who have received the anti-TNF therapy.

Abstract: Methods and systems for administering anti-TNF therapy to subjects who have been determined to display a gene expression response signature established to distinguish between responsive and non-responsive prior subjects who have received the anti-TNF therapy.

Abstract: Methods and systems for administering anti-TNF therapy to subjects who have been determined to display a gene expression response signature established to distinguish between responsive and non-responsive prior subjects who have received the anti-TNF therapy.

Abstract: Presented herein are systems and methods for developing classifiers useful for predicting response to particular treatments. For example, in some embodiments, the present disclosure provides a method of treating subjects suffering from an autoimmune disorder, the method comprising a step of: administering an anti-TNF therapy to subjects who have been determined to be responsive via a classifier established to distinguish between responsive and non-responsive prior subjects in a cohort who have received the anti-TNF therapy.

Abstract: Presented herein are systems and methods for developing classifiers useful for predicting response to particular treatments. For example, in some embodiments, the present disclosure provides a method of treating subjects suffering from an autoimmune disorder, the method comprising a step of: administering an anti-TNF therapy to subjects who have been determined to be responsive via a classifier established to distinguish between responsive and non-responsive prior subjects in a cohort who have received the anti-TNF therapy.

Abstract: Methods and systems for administering anti-TNF therapy to subjects who have been determined to display a gene expression response signature established to distinguish between responsive and non-responsive prior subjects who have received the anti-TNF therapy.

Abstract: A nucleotide sequence, specifically a CTG triplet repeat, is shown to be expanded in individuals affected with myotonic dystrophy and can be identified in a sample obtained from an individual. Individuals in whom the CTG triplet repeat is present in normal copy number are likely to be minimally affected and individuals in whom the CTG triplet repeat occurs in abnormally high copy number are likely to be more severely affected.

Abstract: A method by which a nucleotide sequence, specifically a CTG triplet repeat, shown to be expanded in individuals affected with myotonic dystrophy can be identified in a sample obtained from an individual. The present method can be used to identify individuals in whom the CTG triplet repeat is present in normal copy number and individuals in whom the CTG triplet repeat occurs in abnormally high copy number, as well as to further identify individuals likely to be minimally affected and individuals likely to be more severely affected.