Abstract: Disclosed are methods of preparing an isolated population of dendritic cells, isolated populations of dendritic cells prepared by the methods, and pharmaceutical compositions comprising the isolated population of dendritic cells. Also disclosed are methods of treating or preventing cancer using the isolated population of dendritic cells or pharmaceutical compositions.

Abstract: Systems including an elliptical machine and a processing device. The processing device may be configured to receive, before or while a user operates the elliptical machine, one or more messages pertaining to the user or a use of the elliptical machine by the user. The processing device may be also configured to determine whether the one or more messages were received by the processing device. In response to determining that the one or more messages were not received by the processing device, the processing device may be configured to determine, via one or more machine learning models, one or more actions to perform. The one or more actions may include at least one of initiating a telecommunications transmission, stopping operation of the elliptical machine, and modifying one or more parameters associated with the operation of the elliptical machine.

Abstract: Systems including an elliptical machine and a processing device. The processing device may be configured to receive, before or while a user operates the elliptical machine, one or more messages pertaining to the user or a use of the elliptical machine by the user. The processing device may be also configured to determine whether the one or more messages were received by the processing device. In response to determining that the one or more messages were not received by the processing device, the processing device may be configured to determine, via one or more machine learning models, one or more actions to perform. The one or more actions may include at least one of initiating a telecommunications transmission, stopping operation of the elliptical machine, and modifying one or more parameters associated with the operation of the elliptical machine.

Abstract: Systems including an elliptical machine and a processing device. The processing device may be configured to receive, before or while a user operates the elliptical machine, one or more messages pertaining to the user or a use of the elliptical machine by the user. The processing device may be also configured to determine whether the one or more messages were received by the processing device. In response to determining that the one or more messages were not received by the processing device, the processing device may be configured to determine, via one or more machine learning models, one or more actions to perform. The one or more actions may include at least one of initiating a telecommunications transmission, stopping operation of the elliptical machine, and modifying one or more parameters associated with the operation of the elliptical machine.

Abstract: Disclosed are methods of isolating paired T cell receptor (TCR) alpha and beta chain sequences, or an antigen-binding portion thereof. Also disclosed are methods of automatically identifying the TCR alpha and beta chain V segment sequences and CDR3 sequences of a TCR having antigenic specificity for a mutated amino acid sequence encoded by a cancer-specific mutation. Methods of preparing a population of cells that express paired TCR alpha and beta chain sequences, or an antigen-binding portion thereof, are also disclosed. Isolated pairs of TCR alpha and beta chain sequences and isolated populations of cells prepared by the methods are also disclosed.

Abstract: A computer-implemented system includes one or more processing devices configured to receive attribute data associated with a user, generate, based on at least one of a first bariatric procedure to be performed on the user and a second bariatric procedure already performed on the user, a selected set of the attribute data, determine, based on the selected set of the attribute data, at least one of a first probability of being eligible for the first bariatric procedure to be performed on the user and a second probability of improving a bariatric condition of the user subsequent to the second bariatric procedure being performed on the user, and generate, based on the at least one of the first probability and the second probability, a treatment plan that includes one or more exercises directed to modifying the at least one of the first probability and the second probability, and a treatment apparatus configured for implementation of the treatment plan.

Abstract: A computer-implemented system includes one or more processing devices configured to receive attribute data associated with a user, generate, based on a cardio-oncologic condition of the user, a selected set of the attribute data, determine, based on the selected set of the attribute data, a first probability of improving a cardio-oncologic condition of the user subsequent to at least one of a cardio-oncologic procedure and a cardio-oncologic treatment being performed on the user, and generate, based on the first probability, a treatment plan that includes one or more exercises directed to modifying the first probability, and a treatment apparatus configured for implementation of the treatment plan.

Abstract: A computer-implemented method is disclosed. The method includes receiving, at a computing device, a first treatment plan designed to treat an invasive surgical-related health issue of a user. The first treatment plan comprises at least two exercise sessions that, based on the invasive surgical-related health issue, enable the user to perform an exercise at different exertion levels. Next, while the user uses the electromechanical machine to perform the first treatment plan, receiving, at the computing device, data from sensors configured to measure the data associated with the invasive surgical-related health issue and transmitting the data. One or more machine learning models are used to generate a second treatment plan. The second treatment plan modifies at least one exertion level, and the modification is based on a standardized measure comprising perceived exertion, the data, and the invasive surgical-related health issue. The method additionally includes receiving the second treatment plan.

Abstract: A computer-implemented system includes a processing device configured to receive a plurality of user and blood vessel characteristics associated with a user, generate a selected set of user and blood vessel characteristics, determine, based on the selected set of the user and blood vessel characteristics, a probability that angiogenesis will occur, and generate, based on the probability and the selected set of the user and blood vessel characteristics, a treatment plan that includes one or more exercises directed to modifying the probability that angiogenesis will occur, and a treatment apparatus configured to implement the treatment plan while the treatment apparatus is being manipulated by the user.

Abstract: A computer-implemented system includes one or more processing devices configured to receive user information associated with a user, generate a selected set of the user information, determine, based on the selected set of the user information, at least one of a first probability of surviving one or more procedures and a second probability indicating an improvement, resulting from the one or more procedures, in quality-of-life metrics for the user, generate, based on the at least one of the first probability and the second probability and on the selected set of the user information, one or more recommendations of whether the user should undergo the one or more procedures, and generate, based on the one or more recommendations, a treatment plan that includes one or more exercises directed to modifying the at least one of the first probability and the second probability.

Abstract: The embodiments set forth a technique implemented by a computing device. The technique includes the steps of (1) receiving one or more characteristics associated with a user, wherein the one or more characteristics comprise personal information, performance information, measurement information, cohort information, familial information, comorbidity information, healthcare professional information, or some combination thereof; (2) determining, based on the one or more characteristics, one or more conditions of the user, wherein the one or more conditions pertain to cardiac health, pulmonary health, bariatric health, oncologic health, cardio-oncologic health, or some combination thereof; (3) based on the one or more conditions, identifying, using one or more trained machine learning models, one or more subgroups to present via the display, wherein the one or more subgroups represent different partitions of the one or more characteristics; and (4) presenting, via the display, the one or more subgroups.

Abstract: Disclosed is an isolated or purified T cell receptor (TCR) having antigenic specificity for mutated human p53. Related polypeptides and proteins, as well as related nucleic acids, recombinant expression vectors, host cells, populations of cells, and pharmaceutical compositions are also provided. Also disclosed are methods of detecting the presence of cancer in a mammal and methods of treating or preventing cancer in a mammal.

Abstract: The invention provides methods of increasing the efficacy of a T cell therapy in a patient in need thereof. The invention includes methods of identifying a patient who would respond well to a T cell therapy or conditioning a patient prior to a T cell therapy so that the patient responds well to a T cell therapy. The conditioning involves administering one or more preconditioning agents prior to a T cell therapy and identifying biomarker cytokines prior to administering a T cell therapy.

Abstract: Genetically modified compositions, such as non-viral vectors and T cells, for treating cancer are disclosed. Also disclosed are the methods of making and using the genetically modified compositions in treating cancer.

Abstract: Computer-implemented systems, computer-implemented methods, and tangible, non-transitory computer-readable media for detecting abnormal heart rhythms of a user performing treatment plan with an electromechanical machine. The system includes, in one embodiment, an electromechanical machine, one or more sensors, and one or more processing devices. The electromechanical machine is configured to be manipulated by a user while the user is performing a treatment plan. The one or more sensors are configured to determine one or more measurements associated with the user. The one or more processing devices are configured to receive, from the one or more sensors while the user performs the treatment plan, the one or more measurements associated with the user. The one or more processing devices also configured to determine, using one or more machine learning models, a probability that the one or more measurements indicate that the user satisfies a threshold for a condition associated with an abnormal heart rhythm.

Abstract: Disclosed are methods of preparing an isolated population of human papillomavirus (HPV)-specific T cells comprise dividing an HPV-positive tumor sample into multiple fragments; separately culturing the multiple fragments; obtaining T cells from the cultured multiple fragments; testing the T cells for specific autologous HPV-positive tumor recognition; selecting the T cells that exhibit specific autologous HPV-positive tumor recognition; and expanding the number of selected T cells to produce a population of HPV-specific T cells for adoptive cell therapy. Related methods of treating or preventing cancer using the T cells are also disclosed.

Abstract: A computer-implemented system may include an electromechanical machine configured to be manipulated by a user while the user performs a treatment plan, an interface comprising a display configured to present information associated with the treatment plan, and a processing device configured to receive, from one or more data sources, information associated with the user, wherein the information comprises one or more risk factors associated with a cardiac condition or a cardiac outcome, generate, using one or more trained machine learning models, the treatment plan for the user, wherein the treatment plan is generated based on the information associated with the user, and the treatment plan comprises one or more exercises associated with managing the one or more risk factors in order to reduce a probability of a cardiac intervention for the user, and transmit the treatment plan to cause the electromechanical machine to implement the one or more exercises.