Utility of Tissue Similarity Maps Based on Relative Cerebral Blood Volume for Grading Gliomas as Validated by Histological Results

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Neutrophils Play an Important Role in Protective Immunity against Coxiella burnetii Infection

Coxiella burnetii is an obligate intracellular Gram-negative bacterium that causes the zoonotic disease Q fever. Although Q fever is mainly transmitted by aerosol infection, study of the immune responses in the lung following pulmonary C. burnetii infection is lacking. Neutrophils are considered the first immune cell to migrate into the lung and play an important role in host defense against aerosol infection with microbial pathogens. However, the role of neutrophils in the host defense against C. burnetii infection remains unclear. To determine the role of neutrophils in protective immunity against C. burnetii infection, the RB6-8C5 antibody was used to deplete neutrophils in mice before intranasal infection with C. burnetii. The results indicated that neutrophil-depleted mice developed more severe disease than their wild-type counterparts, suggesting that neutrophils play an important role in host defense against C. burnetii pulmonary infection. We also found that neither CXC chemokine receptor 2 (CXCR2) nor interleukin-17 (IL-17) receptor (IL-17R) deficiency changed the severity of disease following intranasal C. burnetii challenge, suggesting that keratinocyte-derived chemokine and IL-17 may not play essential roles in the response to C. burnetii infection. However, significantly higher C. burnetii genome copy numbers were detected in the lungs of IL-1R^−/− mice at 14 days postinfection. This indicates that IL-1 may be important for the clearance of C. burnetii from the lungs following intranasal infection. Our results also suggest that neutrophils are involved in protecting vaccinated mice from C. burnetii challenge-induced disease. This is the first study to demonstrate an important role for neutrophils in protective immunity against C. burnetii infection.     

Association of Early Kidney Allograft Failure with Preformed IgA Antibodies to β2-Glycoprotein I

In the current immunosuppressive therapy era, vessel thrombosis is the most common cause of early graft loss after renal transplantation. The prevalence of IgA anti–β₂-glycoprotein I antibodies (IgA-aB2GPI-ab) in patients on dialysis is elevated (>30%), and these antibodies correlate with mortality and cardiovascular morbidity. To evaluate the effect of IgA-aB2GPI-ab in patients with transplants, we followed all patients transplanted from 2000 to 2002 in the Hospital 12 de Octubre prospectively for 10 years. Presence of IgA-aB2GPI-ab in pretransplant serum was examined retrospectively. Of 269 patients, 89 patients were positive for IgA-aB2GPI-ab (33%; group 1), and the remaining patients were negative (67%; group 2). Graft loss at 6 months post-transplant was significantly higher in group 1 (10 of 89 versus 3 of 180 patients in group 2; P=0.002). The most frequent cause of graft loss was thrombosis of the vessels, which was observed only in group 1 (8 of 10 versus 0 of 3 patients in group 2; P=0.04). Multivariate analysis showed that the presence of IgA-aB2GPI-ab was an independent risk factor for early graft loss (P=0.04) and delayed graft function (P=0.04). There were no significant differences regarding patient survival between the two groups. Graft survival was similar in both groups after 6 months. In conclusion, patients with pretransplant IgA-aB2GPI-ab have a high risk of early graft loss caused by thrombosis and a high risk of delayed graft function. Therefore, pretransplant IgA-aB2GPI-ab may have a detrimental effect on early clinical outcomes after renal transplantation.     

Esophagectomy with Ileocoloplasty,Last Treatment for a Leak After Laparoscopic Sleeve: “From Less to More”

Obesity Surgery - Laparoscopic sleeve gastrectomy (LSG) is increasingly playing a key role in obesity management. Such operations, however, carry complications sometimes including leaks. The...     

Optimal tracking control for non-zero-sum games of linear discrete-time systems via off-policy reinforcement learning

In this article, a model-free off-policy reinforcement learning algorithm is applied to address the optimal tracking problem based on multiplayer non-zero-sum games for discrete-time linear systems. In contrast to the traditional method and the policy iteration method for solving the optimal tracking problems, the proposed algorithm operates with the system data rather than the knowledge of the system dynamics. For performing the proposed algorithm, an auxiliary augmented system is constructed via assembling the original system and the reference trajectory while a discount factor is introduced into the performance indexes. It is analyzed that the solutions of the proposed algorithm converge to the Nash equilibrium and the result is not influenced by the probing noise. Two simulations are presented to verify the feasibility and effectiveness of the proposed algorithm.