On the choice of ensemble mean for estimating the forced signal in the presence of internal variability

This is the final version of the article. Available from American Meteorological Society via the DOI in this record.In this paper we examine various options for the calculation of the forced signal in climate model simulations, and the impact these choices have on the estimates of internal variability. We find that an ensemble mean of runs from a single climate model [a single model ensemble mean (SMEM)] provides a good estimate of the true forced signal even for models with very few ensemble members. In cases where only a single member is available for a given model, however, the SMEM from other models is in general out-performed by the scaled ensemble mean from all available climate model simulations [the multimodel ensemble mean (MMEM)]. The scaled MMEM may therefore be used as an estimate of the forced signal for observations. The MMEM method, however, leads to increasing errors further into the future, as the different rates of warming in the models causes their trajectories to diverge. We therefore apply the SMEM method to those models with a sufficient number of ensemble members to estimate the change in the amplitude of internal variability under a future forcing scenario. In line with previous results, we find that on average the surface air temperature variability decreases at higher latitudes, particularly over the ocean along the sea ice margins, while variability in precipitation increases on average, particularly at high latitudes. Variability in sea level pressure decreases on average in the Southern Hemisphere, while in the Northern Hemisphere there are regional differences.This work was supported by the Australian Research Council (ARC) through grants to L. M. F. (DE170100367) and to M. H. E. through the ARC Centre of Excellence in Climate System Science (CE110001028). J. B. K. is supported by the Natural Environment Research Council (Grant NE/N005783/1). B. A. S. was supported by the U.S. National Science Foundation (EAR-1447048)

Variation in antibiotic treatment for diabetic patients with serious foot infections: A retrospective observational study

<p>Abstract</p> <p>Background</p> <p>Diabetic foot infections are common, serious, and diverse. There is uncertainty about optimal antibiotic treatment, and probably substantial variation in practice. Our aim was to document whether this is the case: A finding that would raise questions about the comparative cost-effectiveness of different regimens and also open the possibility of examining costs and outcomes to determine which should be preferred.</p> <p>Methods</p> <p>We used the Veterans Health Administration (VA) Diabetes Epidemiology Cohorts (DEpiC) database to conduct a retrospective observational study of hospitalized patients with diabetic foot infections. DEpiC contains computerized VA and Medicare patient-level data for VA patients with diabetes since 1998, including demographics, ICD-9-CM diagnostic codes, antibiotics prescribed, and VA facility. We identified all patients with ICD-9-CM codes for cellulitis/abscess of the foot and then sub-grouped them according to whether they had cellulitis/abscess plus codes for gangrene, osteomyelitis, skin ulcer, or none of these. For each facility, we determined: 1) The proportion of patients treated with an antibiotic and the initial route of administration; 2) The first antibiotic regimen prescribed for each patient, defined as treatment with the same antibiotic, or combination of antibiotics, for at least 5 continuous days; and 3) The antibacterial spectrum of the first regimen.</p> <p>Results</p> <p>We identified 3,792 patients with cellulitis/abscess of the foot either alone (16.4%), or with ulcer (32.6%), osteomyelitis (19.0%) or gangrene (32.0%). Antibiotics were prescribed for 98.9%. At least 5 continuous days of treatment with an unchanged regimen of one or more antibiotics was prescribed for 59.3%. The means and (ranges) across facilities of the three most common regimens were: 16.4%, (22.8%); 15.7%, (36.1%); and 10.8%, (50.5%). The range of variation across facilities proved substantially greater than that across the different categories of foot infection. We found similar variation in the spectrum of the antibiotic regimen.</p> <p>Conclusions</p> <p>The large variations in regimen appear to reflect differences in facility practice styles rather than case mix. It is unlikely that all regimens are equally cost-effective. Our methods make possible evaluation of many regimens across many facilities, and can be applied in further studies to determine which antibiotic regimens should be preferred.</p

Conducting High-Value Secondary Dataset Analysis: An Introductory Guide and Resources

Secondary analyses of large datasets provide a mechanism for researchers to address high impact questions that would otherwise be prohibitively expensive and time-consuming to study. This paper presents a guide to assist investigators interested in conducting secondary data analysis, including advice on the process of successful secondary data analysis as well as a brief summary of high-value datasets and online resources for researchers, including the SGIM dataset compendium (www.sgim.org/go/datasets). The same basic research principles that apply to primary data analysis apply to secondary data analysis, including the development of a clear and clinically relevant research question, study sample, appropriate measures, and a thoughtful analytic approach. A real-world case description illustrates key steps: (1) define your research topic and question; (2) select a dataset; (3) get to know your dataset; and (4) structure your analysis and presentation of findings in a way that is clinically meaningful. Secondary dataset analysis is a well-established methodology. Secondary analysis is particularly valuable for junior investigators, who have limited time and resources to demonstrate expertise and productivity

Mesenchymal stromal-cell transplants induce oligodendrocyte progenitor migration and remyelination in a chronic demyelination model.

Demyelinating disorders such as leukodystrophies and multiple sclerosis are neurodegenerative diseases characterized by the progressive loss of myelin that may lead toward a chronic demyelination of the brain¿s white matter, impairing normal axonal conduction velocity and ultimately causing neurodegeneration. Current treatments modifying the pathological mechanisms are capable of ameliorating the disease; however, frequently, these therapies are not sufficient to repress the progressive demyelination into a chronic condition and permanent loss of function. To this end, we analyzed the effect that bone marrowderived mesenchymal stromal cell (BM-MSC) grafts exert in a chronically demyelinated mouse brain. As a result, oligodendrocyte progenitors were recruited surrounding the graft due to the expression of various trophic signals by the grafted MSCs. Although there was no significant reaction in the non-grafted side, in the grafted regions oligodendrocyte progenitors were detected. These progenitors were derived from the nearby tissue as well as from the neurogenic niches, including the subependymal zone and dentate gyrus. Once near the graft site, the cells matured to myelinating oligodendrocytes. Finally, electrophysiological studies demonstrated that axonal conduction velocity was significantly increased in the grafted side of the fimbria. In conclusion, we demonstrate here that in chronic demyelinated white matter, BM-MSC transplantation activates oligodendrocyte progenitors and induces remyelination in the tissue surrounding the stem cell graft

Making sense of the early-2000s warming slowdown

It has been claimed that the early-2000s global warming slowdown or hiatus, characterized by a reduced rate of global surface warming, has been overstated, lacks sound scientific basis, or is unsupported by observations. The evidence presented here contradicts these claims

Tocotrienols are good adjuvants for developing cancer vaccines

<p>Abstract</p> <p>Background</p> <p>Dendritic cells (DCs) have the potential for cancer immunotherapy due to their ability to process and present antigens to T-cells and also in stimulating immune responses. However, DC-based vaccines have only exhibited minimal effectiveness against established tumours in mice and humans. The use of appropriate adjuvant enhances the efficacy of DC based cancer vaccines in treating tumours.</p> <p>Methods</p> <p>In this study we have used tocotrienol-rich fraction (TRF), a non-toxic natural compound, as an adjuvant to enhance the effectiveness of DC vaccines in treating mouse mammary cancers. In the mouse model, six-week-old female BALB/c mice were injected subcutaneously with DC and supplemented with oral TRF daily (DC+TRF) and DC pulsed with tumour lysate from 4T1 cells (DC+TL). Experimental mice were also injected with DC pulsed with tumour lysate and supplemented daily with oral TRF (DC+TL+TRF) while two groups of animal which were supplemented daily with carrier oil (control) and with TRF (TRF). After three times vaccination, mice were inoculated with 4T1 cells in the mammary breast pad to induce tumour.</p> <p>Results</p> <p>Our study showed that TRF in combination with DC pulsed with tumour lysate (DC+TL+TRF) injected subcutaneously significantly inhibited the growth of 4T1 mammary tumour cells as compared to control group. Analysis of cytokines production from murine splenocytes showed significant increased productions of IFN-γ and IL-12 in experimental mice (DC+TL+TRF) compared to control, mice injected with DC without TRF, mice injected with DC pulsed with tumour lysate and mice supplemented with TRF alone. Higher numbers of cytotoxic T cells (CD8) and natural killer cells (NK) were observed in the peripheral blood of TRF adjuvanted DC pulsed tumour lysate mice.</p> <p>Conclusion</p> <p>Our study show that TRF has the potential to be an adjuvant to augment DC based immunotherapy.</p

Internal and external forcing of multidecadal Atlantic climate variability over the past 1,200 years

The North Atlantic experiences climate variability on multidecadal scales, which is sometimes referred to as Atlantic multidecadal variability. However, the relative contributions of external forcing such as changes in solar irradiance or volcanic activity and internal dynamics to these variations are unclear. Here we provide evidence for persistent summer Atlantic multidecadal variability from AD 800 to 2010 using a network of annually resolved terrestrial proxy records from the circum-North Atlantic region. We find that large volcanic eruptions and solar irradiance minima induce cool phases of Atlantic multidecadal variability and collectively explain about 30% of the variance in the reconstruction on timescales greater than 30 years. We are then able to isolate the internally generated component of Atlantic multidecadal variability, which we define as the Atlantic multidecadal oscillation. We find that the Atlantic multidecadal oscillation is the largest contributor to Atlantic multidecadal variability over the past 1,200 years. We also identify coherence between the Atlantic multidecadal oscillation and Northern Hemisphere temperature variations, leading us to conclude that the apparent link between Atlantic multidecadal variability and regional to hemispheric climate does not arise solely from a common response to external drivers, and may instead reflect dynamic processes

Induction of tumour-specific CD8+ cytotoxic T lymphocytes by tumour lysate-pulsed autologous dendritic cells in patients with uterine serous papillary cancer

Uterine serous papillary carcinoma is a highly aggressive variant of endometrial cancer histologically similar to high grade ovarian cancer. Unlike ovarian cancer, however, it is a chemoresistant disease from onset, with responses to combined cisplatinum-based chemotherapy in the order of 20% and an extremely poor prognosis. In this study, we demonstrate that tumour lysate-pulsed autologous dendritic cells can elicit a specific CD8+ cytotoxic T lymphocyte response against autologous tumour target cells in three patients with uterine serous papillary cancer. CTL from patients 1 and 2 expressed strong cytolytic activity against autologous tumour cells, did not lyse autologous lymphoblasts or autologous EBV-transformed cell lines, and were variably cytotoxic against the NK-sensitive cell line K-562. Patient 3 CD8+ T cells expressed a modest but reproducible cytotoxicity against autologous tumour cells only at the time of the first priming. Further priming attempts with PBL collected from patient 3 after tumour progression in the lumboaortic lymph nodes were unsuccesful. Cytotoxicity against autologous tumour cells could be significantly inhibited by anti-HLA class I (W6/32) and anti-LFA-1 MAbs. Highly cytotoxic CD8+ T cells from patients 1 and 2 showed a heterogeneous CD56 expression while CD56 was not expressed by non-cytotoxic CD8+ T cells from patient 3. Using two colour flow cytometric analysis of intracellular cytokine expression at the single cell level, a striking dominance of IFN-γ expressors was detectable in CTL populations of patients 1 and 2 while in patient 3 a dominant population of CD8+ T cells expressing IL-4 and IL-10 was consistently detected. Taken together, these data demonstrate that tumour lysate-pulsed DC can be an effective tool in inducing uterine serous papillary cancer-specific CD8+ CTL able to kill autologous tumour cells in vitro. However, high levels of tumour specific tolerance in some patients may impose a significant barrier to therapeutic vaccination. These results may have important implications for the treatment in the adjuvant setting of uterine serous papillary cancer patients with active or adoptive immunotherapy