Peripheral Blood Pressure Changes Induced by Dobutamine Do Not Alter BOLD Signals in The Human Brain

In extending the use of functional MRI to neuropharmacology, a primary area of concern is that peripheral blood pressure changes induced by pharmacological agents could independently produce a change in the blood oxygenation level-dependent (BOLD) signal, resulting in difficulties distinguishing or interpreting drug-induced neural activations. In the present study, we utilized intravenous dobutamine, a beta-adrenergic receptor agonist, to increase the mean arterial blood pressure (MABP), while examining the effects of MABP changes on the BOLD signal in cocaine-dependent participants. Dobutamine infusion significantly increased the MABP from 93 ± 8 mm Hg to 106 ± 12 mm Hg (P \u3c 0.0005), but did not produce a significant global BOLD signal. Yet, a few voxels in the anterior cingulate showed BOLD signal changes that paralleled the changes in blood pressure (BP). Our observations support the conclusion that following the infusion of psychoactive agents, brain BOLD signals accurately reflect neuronal activity, even in the face of relatively large peripheral cardiovascular effects that transiently increase systemic BP

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Variability in geochemical weathering indices in loess over the last full glacial cycle at Karamaidan, central Asia (Tajikistan)

This study presents the first quantitative assessment of weathering conditions in the Tajikistan depression throughout the last full glacial cycle. We employed geochemical and magnetic susceptibility analyses to investigate various weathering indices (WIs), with the CPA and FENG indices identified as the most suitable for this region. Our results confirm the formation of a robust pedocomplex, PS2, during the OIS5 interglacial phase, while primary loess deposition occurred during the interstadials. The presence of a weak paleosol, PS1, suggests that OIS3 was not significantly pronounced, and sediment transport and deposition continued during this period. Furthermore, we assessed the effectiveness of various climatic transfer functions, including some recently developed specifically for Chinese loess. These transfer functions have also shown promising applicability to the loess of Central Asia, producing realistic climate trends that are, however, still to be taken with caution. The MAT and mean annual precipitation generated with these functions show for the last interglacial period about 13°C and 665 mm, thus higher temperatures and lower precipitation than the current conditions of 10.8°C and 730 mm. These results indicate a significant increase (c. 15%) in both temperature and precipitation compared to the stadial periods

Variability in geochemical weathering indices in loess over the last full glacial cycle at Karamaidan, central Asia (Tajikistan)

International audienceThis study presents the first quantitative assessment of weathering conditions in the Tajikistan depression throughout the last full glacial cycle. We employed geochemical and magnetic susceptibility analyses to investigate various weathering indices (WIs), with the CPA and FENG indices identified as the most suitable for this region. Our results confirm the formation of a robust pedocomplex, PS2, during the OIS5 interglacial phase, while primary loess deposition occurred during the interstadials. The presence of a weak paleosol, PS1, suggests that OIS3 was not significantly pronounced, and sediment transport and deposition continued during this period. Furthermore, we assessed the effectiveness of various climatic transfer functions, including some recently developed specifically for Chinese loess. These transfer functions have also shown promising applicability to the loess of Central Asia, producing realistic climate trends that are, however, still to be taken with caution. The MAT and mean annual precipitation generated with these functions show for the last interglacial period about 13°C and 665 mm, thus higher temperatures and lower precipitation than the current conditions of 10.8°C and 730 mm. These results indicate a significant increase (c. 15%) in both temperature and precipitation compared to the stadial periods