Lambert Colon (bowsand02)
Antigen-specific immunotherapy (ASI) has been proposed as an alternative treatment strategy for type 1 diabetes (T1D). ASI aims to induce a regulatory, rather than stimulatory, immune response in order to reduce, or prevent, autoimmune mediated β-cell destruction, thus preserving endogenous insulin production. The abundance of immunocompetent antigen presenting cells (APCs) within the skin makes this organ an attractive target for immunotherapies. Microneedles (MNs) have been proposed as a suitable drug delivery system to facilitate intradermal delivery of autoantigens in a minimally invasive manner. However, studies to date have employed single peptide autoantigens, which would restrict ASI to patients expressing specific Human Leukocyte Antigen (HLA) molecules, thus stratifying the patient population. This study aims to develop, for the first time, an intradermal MN delivery system to target proinsulin, a large multi-epitope protein capable of inducing tolerance in a heterogenous (in terms of HLA status) po-specific T cells in the local lymph nodes. The development of an innovative coated MN system for highly targeted and reproducible delivery of proinsulin to local immune cells warrants further evaluation to determine translation to a tolerogenic clinical outcome. V.Realization of phototherapy on the big animal modal with orthotopic tumor is of considerable significance in view of its great clinical relevance to the human deep tumor treatment. Herein, near infrared (NIR)-active ZrN nanoparticles were chosen for both of photothermal and photodynamic purposes to achieve the synergetic phototherapy on mice with subcutaneous tumor and even rabbits bearing with orthotopic tumor. Broad and strong photoabsorption, photosensitive ROS generation and photothermal effect of ZrN nanoparticles together made it to be ideal candidate for the effective tumor photoablation. Meanwhile, cell-cargo of macrophage enables targeted delivery of ZrN nanoparticles without influence on its photophysical properties. Resultantly, macrophage loaded ZrN could efficiently mediate synergetic phototherapeutic outcome as proved by complete removal of solid tumor from mice and rabbits. In this work, we also introduced B-mode ultrasonography and contrast-enhanced ultrasound technique for monitoring the evolution process of deep orthotopic tumor on rabbits post-treatment and confirmed the pathological changes of vascular degeneration and liquefaction necrosis post phototherapy. BACKGROUND AND OBJECTIVE Published models predicting health related outcomes rely on clinical, claims and social determinants of health (SDH) data. Addressing the challenge of predicting with only SDH we developed a novel framework termed Stratified Cascade Learning (SCL) and used it for predicting the risk of hospitalization (ROH). MATERIALS AND METHODS The variable set includes 27 SDH and "age" and "sex" for a cohort of diabetic patients. The SCL model uses three sub-models SM1 (whole training set) stratifies training set into "predictable" and "unpredictable" subsets, SM2 (built on whole training set) classifies test set patients into "predictable" and "unpredictable", and SM3 (built on only the "predictable" subset) predicts the ROH for the patients classified as "predictable" by SM2. RESULTS The SCL model does not improve either the AUC or the NPV of the basic classifier, but materially improves accuracy and specificity measures at the expense of lowering sensitivity for the "predictable" subset. Optimization of the risk thresholds of the sub-models does not noticeably change the AUC and NPV but further improves the accuracy and specificity at the expense of further lowering sensitivity. CONCLUSION Since the SLC model yields low sensitivity it fails to predict high risk patients. But it yields high specificity that can be useful when the objective is to eliminate low-risk patients as candidates for further testing or treatment. The use of the SCL is not limited to healthcare, it c
