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Further, depletion of CD8 T cells in tumor bearing mice abolished the GDF15 induced protection from tumor growth. Infusion of GDF15 into mice bearing orthotopic TRAMP tumor, substantially reduced tumor growth that was further reduced by concurrent PD1 antibody administration. check details GDF15 overexpression or recombinant protein protects from TRAMP tumor growth by modulating CD8 T cell mediated antitumor immunity and augments the positive effects of anti-PD1 blockers.Cerebral cavernous malformations (CCMs) are vascular lesions predominantly developing in the central nervous system (CNS), with no effective treatments other than surgery. Loss-of-function mutation in CCM1/krev interaction trapped 1 (KRIT1), CCM2, or CCM3/programmed cell death 10 (PDCD10) causes lesions that are characterized by abnormal vascular integrity. Vascular endothelial cadherin (VE-cadherin), a major regulator of endothelial cell (EC) junctional integrity is strongly disorganized in ECs lining the CCM lesions. We report here that microRNA-27a (miR-27a), a negative regulator of VE-cadherin, is elevated in ECs isolated from mouse brains developing early CCM lesions and in cultured ECs with CCM1 or CCM2 depletion. Furthermore, we show miR-27a acts downstream of kruppel-like factor (KLF)2 and KLF4, two known key transcription factors involved in CCM lesion development. Using CD5-2 (a target site blocker [TSB]) to prevent the miR-27a/VE-cadherin mRNA interaction, we present a potential therapy to increase VE-cadherin expression and thus rescue the abnormal vascular integrity. In CCM1- or CCM2-depleted ECs, CD5-2 reduces monolayer permeability, and in Ccm1 heterozygous mice, it restores dermal vessel barrier function. In a neonatal mouse model of CCM disease, CD5-2 normalizes vasculature and reduces vascular leakage in the lesions, inhibits the development of large lesions, and significantly reduces the size of established lesions in the hindbrain. Furthermore, CD5-2 limits the accumulation of inflammatory cells in the lesion area. Our work has established that VE-cadherin is a potential therapeutic target for normalization of the vasculature and highlights that targeting miR-27a/VE-cadherin interaction by CD5-2 is a potential novel therapy for the devastating disease, CCM.A framework of social inclusion can promote equity and aid in preventing and addressing the abuse of older adults. Our objective was to build a social inclusion framework for a comprehensive hospital-based elder abuse intervention being developed. Potential components of such a framework, namely, health determinants and guiding principles, were extracted from a systematic scoping review of existing responses (e.g., interventions, protocols) to elder abuse and collated. These were subsequently rated for their importance to the elder abuse intervention by a panel of violence experts and further evaluated by a panel of elder abuse experts. The final social inclusion framework comprised 12 health determinants each representing factors underpinning susceptibility for abuse in aging populations history of trauma/abuse, communication needs, disability, health status, mental capacity, social support, culture, language, sexuality, religion, gender identity, and socioeconomic status. The framework also comprised 19 guiding principles each encompassing considerations for equitable engagement with older adults (e.g., All older adults have the right to self-determination, All older adults have the right to be safe, All older adults are assumed competent unless determined otherwise). Integrating this social inclusion framework into the design and delivery of an elder abuse intervention could empower older adults, while at the same time ensuring that practices and policies are tailored to meet their unique and varying needs.Background and aims The disease-related knowledge levels in patients with inflammatory bowel disease (IBD) are important because it could affect the self-management ability and adaptive coping strategies. We set out to determine whether higher levels of disease-related knowledge reduce medical acceleration. Methods We evaluated the levels of disease-related knowledge in all patients at the time of enrollment for SNUBH IBD cohort using the validated IBD-KNOW questionnaire. Clinical data were prospectively collected and the factors related to step-up therapy were analyzed. Step-up therapy was defined as the new use of corticosteroids, immunomodulators, or biologics after the enrollment. Results Between April 2017 and January 2019, 298 patients were enrolled (mean age, 39.8 years; males, 69.5%); 193 patients (64.8%) had ulcerative colitis and 105 (35.2%) had Crohn's disease. The mean disease duration was 35.8 months. During the mean follow-up of 14.7 months, 90 patients (30.2%) underwent step-up therapy and 208 (69.8%) underwent continuous therapy. The prevalence of continuous therapy increased with increasing IBD-KNOW scores (p for trend = 0.019). Cox proportional hazards analysis revealed that high IBD-KNOW scores (≥ 16) (hazards ratio [HR] 0.498, 95% confidence interval [CI] 0.276-0.897, p = 0.020) was negatively associated with the step-up therapy. Conclusions Higher disease-related knowledge could reduce the requirement of step-up therapy in IBD. The IBD-KNOW score was independently predictive of step-up therapy.[This corrects the article DOI 10.1371/journal.pone.0223464.].Neural networks are widely used in automatic credit scoring systems with high accuracy and outstanding efficiency. However, in the absence of prior knowledge, it is difficult to determine the set of hyper-parameters, which makes its application limited in practice. This paper presents a novel framework of credit-scoring model based on neural networks trained by the optimal swarm intelligence (SI) algorithm. This framework incorporates three procedures. Step 1, pre-processing, including imputation, normalization, and re-ordering of the samples. Step 2, training, where SI algorithms optimize hyper-parameters of back-propagation artificial neural networks (BP-ANN) with the area under curve (AUC) as the evaluation function. Step 3, test, applying the optimized model in Step 2 to predict new samples. The results show that the framework proposed in this paper searches the hyper-parameter space efficiently and finds the optimal set of hyper parameters with appropriate time complexity, which enhances the fitting and generalization ability of BP-ANN.