Effects of multiple-dose ponesimod, a selective SIP1 receptor modulator, on lymphocyte subsets in healthy humans

This study investigated the effects of ponesimod, a selective SIP1 receptor modulator, on T lymphocyte subsets in 16 healthy subjects. Lymphocyte subset proportions and absolute numbers were determined at baseline and on Day 10, after once-daily administration of ponesimod (10 mg, 20 mg, and 40 mg each consecutively for 3 days) or placebo (ratio 3: 1). The overall change from baseline in lymphocyte count was -1,292 +/- 340x10(6) cells/L and 275 +/- 486x10(6) cells/L in ponesimod- and placebo-treated subjects, respectively. This included a decrease in both T and B lymphocytes following ponesimod treatment. A decrease in naive CD4(+) T cells (CD45RA(+)CCR7(+)) from baseline was observed only after ponesimod treatment (-113 +/- 98x10(6) cells/L, placebo: 0 +/- 18x10(6) cells/L). The number of T-cytotoxic (CD3(+)CD8(+)) and T-helper (CD3(+)CD4(+)) cells was significantly altered following ponesimod treatment compared with placebo. Furthermore, ponesimod treatment resulted in marked decreases in CD4(+) T-central memory (CD45RA(-)CCR7(+)) cells (-437 +/- 164x10(6) cells/L) and CD4(+) T-effector memory (CD45RA(-)CCR7(-)) cells (-131 +/- 57x10(6) cells/L). In addition, ponesimod treatment led to a decrease of -228 +/- 90x10(6) cells/L of gut-homing T cells (CLA(-)integrin beta 7(+)). In contrast, when compared with placebo, CD8(+) T-effector memory and natural killer (NK) cells were not significantly reduced following multiple-dose administration of ponesimod. In summary, ponesimod treatment led to a marked reduction in overall T and B cells. Further investigations revealed that the number of CD4(+) cells was dramatically reduced, whereas CD8(+) and NK cells were less affected, allowing the body to preserve critical viral-clearing functions

The Effects of Lifestyle Modification on Glycemic Levels and Medication Intake: The Rockford CHIP

Introduction: The high prevalence of cardiovascular disease (CVD) in the past 50 years has led to intense research, resulting in many improvements in treatment. At the same time, type 2 diabetes, with its concomitant increase in vascular complications, has become a serious, exploding and costly public health concern . Diabetes now affects 285 million adults worldwide and 344 million with pre-diabetes. Of these, 25.8 million diabetics and 79 million pre-diabetics are found in the United States alone.The current cost of diabetes in the US is likely to exceed the $174 billion estimate, which includes 2/3 for direct medical costs and 1/3 for indirect costs, such as disability, work loss, and premature death, but omits the social cost of intangibles (e.g. pain, suffering, lower quality of life). The diabetes epidemic has been accompanied by a similarly drastic increase in obesity. Although the relationship between the two developments is a matter of debate, both are presumably caused by changes in dietary habits and an increasingly sedentary modern lifestyle . Compelling evidence has shown that lifestyle changes can effectively prevent or delay the occurrence of type 2 diabetes. Because individuals at risk for this disease can usually be identified during the pre-diabetic phase of impaired glucose tolerance, early intervention and lifestyle change offer a logical approach to preventing this disease and its devastating vascular complications. Additionally, community-based lifestyle interventions for high risk groups and for the general population are a cost-effective way of curbing the growing burden of the disease. Solidifying the scientific basis for the prevention, treatment and control of this disease and its implementation on a national level, however, remains a difficult challenge. Moreresearch is needed to provide comprehensive and more effective strategies for weight-loss,especially over time. Therefore, the objectives of this study were to identify diabetics and those at risk (prediabetics) out of the total cohort of 1,517 who selected themselves into an intensive community-based lifestyle intervention program, and to assess its clinical efficacy ineffecting medication status as determined and managed by their personal physicians

Semi-annual report of the Department of Energy, Office of Environmental Management, Quality Assessment Program

This Quality Assessment Program (QAP) is designed to test the quality of the environmental measurements being reported to the Department of Energy by its contractors. Since 1976, real or synthetic environmental samples that have been prepared and thoroughly analyzed at the Environmental Measurements Laboratory (EML) have been distributed at first quarterly and then semi-annually to these contractors. Their results, which are returned to EML within 90 days, are compiled with EML`s results and are reported back to the participating contractors 30 days later. This report presents the results from the analysis of the 48th set of environmental quality assessment samples (QAP XLVIII) that were received on or before June 1, 1998

Space Efficient Algorithms for Breadth-Depth Search

Continuing the recent trend, in this article we design several space-efficient algorithms for two well-known graph search methods. Both these search methods share the same name {\it breadth-depth search} (henceforth {\sf BDS}), although they work entirely in different fashion. The classical implementation for these graph search methods takes $O(m+n)$ time and $O(n \lg n)$ bits of space in the standard word RAM model (with word size being $\Theta(\lg n)$ bits), where $m$ and $n$ denotes the number of edges and vertices of the input graph respectively. Our goal here is to beat the space bound of the classical implementations, and design $o(n \lg n)$ space algorithms for these search methods by paying little to no penalty in the running time. Note that our space bounds (i.e., with $o(n \lg n)$ bits of space) do not even allow us to explicitly store the required information to implement the classical algorithms, yet our algorithms visits and reports all the vertices of the input graph in correct order.Comment: 12 pages, This work will appear in FCT 201

The Role of the Fc Region in CD70-specific Antibody Effects on Cardiac Transplant Survival

Background: The role of the CD70-specific antibody and the mechanisms by which it extends transplant survival are not known. Methods: Fully major histocompatibility complex-mismatched heterotopic heart transplantation (BALB/c to C57BL/6) was performed. Treated mice received intraperitoneal injections of wild-type (WT) CD70-specific antibody (FR70) or IgG1 or IgG2a chimeric antibodies on days 0, 2, 4, and 6 posttransplantation. Results: WT FR70 antibody significantly extended heart transplant survival to 19 days compared with untreated mice (median survival time [MST]=10 days). Graft survival using the nondepleting IgG1 antibody was significantly shorter (MST=14 days), whereas the survival using depleting IgG2a antibody (MST=18) was similar to that using WT FR70. The FR70 and IgG2a antibodies demonstrated a greater efficiency of fixing mouse complement over the IgG1 variant in vitro. CD4 and CD8 T-cell graft infiltration was reduced with treatment; however, this was most pronounced with WT FR70 and IgG2a antibody therapy compared with the IgG1 chimeric variant. Circulating donor-specific IgG alloantibodies were initially reduced with WT FR70 treatment (day 8 posttransplantation) but increased at days 15 and 20 posttransplantation to the level detected in untreated controls. Conclusion: We conclude that WT (FR70) and the IgG2a depleting variant of CD70-specific antibody reduce graft infiltrating CD4 and CD8 T cells, transiently reduce serum alloantibody levels, and extend graft survival. In contrast, the nondepleting IgG1 variant of this antibody showed lower efficacy. These data suggest that a depleting mechanism of action and not merely costimulation blockade plays a substantial role in the therapeutic effects of CD70-specific antibody

Theoretically Efficient Parallel Graph Algorithms Can Be Fast and Scalable

There has been significant recent interest in parallel graph processing due to the need to quickly analyze the large graphs available today. Many graph codes have been designed for distributed memory or external memory. However, today even the largest publicly-available real-world graph (the Hyperlink Web graph with over 3.5 billion vertices and 128 billion edges) can fit in the memory of a single commodity multicore server. Nevertheless, most experimental work in the literature report results on much smaller graphs, and the ones for the Hyperlink graph use distributed or external memory. Therefore, it is natural to ask whether we can efficiently solve a broad class of graph problems on this graph in memory. This paper shows that theoretically-efficient parallel graph algorithms can scale to the largest publicly-available graphs using a single machine with a terabyte of RAM, processing them in minutes. We give implementations of theoretically-efficient parallel algorithms for 20 important graph problems. We also present the optimizations and techniques that we used in our implementations, which were crucial in enabling us to process these large graphs quickly. We show that the running times of our implementations outperform existing state-of-the-art implementations on the largest real-world graphs. For many of the problems that we consider, this is the first time they have been solved on graphs at this scale. We have made the implementations developed in this work publicly-available as the Graph-Based Benchmark Suite (GBBS).Comment: This is the full version of the paper appearing in the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 201

Aliskiren, enalapril, or aliskiren and enalapril in heart failure

BACKGROUND Among patients with chronic heart failure, angiotensin-converting–enzyme (ACE) inhibitors reduce mortality and hospitalization, but the role of a renin inhibitor in such patients is unknown. We compared the ACE inhibitor enalapril with the renin inhibitor aliskiren (to test superiority or at least noninferiority) and with the combination of the two treatments (to test superiority) in patients with heart failure and a reduced ejection fraction. METHODS After a single-blind run-in period, we assigned patients, in a double-blind fashion, to one of three groups: 2336 patients were assigned to receive enalapril at a dose of 5 or 10 mg twice daily, 2340 to receive aliskiren at a dose of 300 mg once daily, and 2340 to receive both treatments (combination therapy). The primary composite outcome was death from cardiovascular causes or hospitalization for heart failure. RESULTS After a median follow-up of 36.6 months, the primary outcome occurred in 770 patients (32.9%) in the combination-therapy group and in 808 (34.6%) in the enalapril group (hazard ratio, 0.93; 95% confidence interval [CI], 0.85 to 1.03). The primary outcome occurred in 791 patients (33.8%) in the aliskiren group (hazard ratio vs. enalapril, 0.99; 95% CI, 0.90 to 1.10); the prespecified test for noninferiority was not met. There was a higher risk of hypotensive symptoms in the combination-therapy group than in the enalapril group (13.8% vs. 11.0%, P=0.005), as well as higher risks of an elevated serum creatinine level (4.1% vs. 2.7%, P=0.009) and an elevated potassium level (17.1% vs. 12.5%, P<0.001). CONCLUSIONS In patients with chronic heart failure, the addition of aliskiren to enalapril led to more adverse events without an increase in benefit. Noninferiority was not shown for aliskiren as compared with enalapri