Large Scale Comparison of Innate Responses to Viral and Bacterial Pathogens in Mouse and Macaque

Viral and bacterial infections of the lower respiratory tract are major causes of morbidity and mortality worldwide. Alveolar macrophages line the alveolar spaces and are the first cells of the immune system to respond to invading pathogens. To determine the similarities and differences between the responses of mice and macaques to invading pathogens we profiled alveolar macrophages from these species following infection with two viral (PR8 and Fuj/02 influenza A) and two bacterial (Mycobacterium tuberculosis and Francisella tularensis Schu S4) pathogens. Cells were collected at 6 time points following each infection and expression profiles were compared across and between species. Our analyses identified a core set of genes, activated in both species and across all pathogens that were predominantly part of the interferon response pathway. In addition, we identified similarities across species in the way innate immune cells respond to lethal versus non-lethal pathogens. On the other hand we also found several species and pathogen specific response patterns. These results provide new insights into mechanisms by which the innate immune system responds to, and interacts with, invading pathogens

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed by resource-rich organizations and are frequently kept from the public. As a step towards democratizing this powerful technology, we present BLOOM, a 176B-parameter open-access language model designed and built thanks to a collaboration of hundreds of researchers. BLOOM is a decoder-only Transformer language model that was trained on the ROOTS corpus, a dataset comprising hundreds of sources in 46 natural and 13 programming languages (59 in total). We find that BLOOM achieves competitive performance on a wide variety of benchmarks, with stronger results after undergoing multitask prompted finetuning. To facilitate future research and applications using LLMs, we publicly release our models and code under the Responsible AI License

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

Tracking Plasticity: Effects of Long-Term Rehearsal in Expert Dancers Encoding Music to Movement.

Our knowledge of neural plasticity suggests that neural networks show adaptation to environmental and intrinsic change. In particular, studies investigating the neuroplastic changes associated with learning and practicing motor tasks have shown that practicing such tasks results in an increase in neural activation in several specific brain regions. However, studies comparing experts and non-experts suggest that experts employ less neuronal activation than non-experts when performing a familiar motor task. Here, we aimed to determine the long-term changes in neural networks associated with learning a new dance in professional ballet dancers over 34 weeks. Subjects visualized dance movements to music while undergoing fMRI scanning at four time points over 34-weeks. Results demonstrated that initial learning and performance at seven weeks led to increases in activation in cortical regions during visualization compared to the first week. However, at 34 weeks, the cortical networks showed reduced activation compared to week seven. Specifically, motor learning and performance over the 34 weeks showed the typical inverted-U-shaped function of learning. Further, our result demonstrate that learning of a motor sequence of dance movements to music in the real world can be visualized by expert dancers using fMRI and capture highly significant modeled fits of the brain network variance of BOLD signals from early learning to expert level performance

Quadratic fits from the time points of 1, 7 and 34 weeks of BOLD signals across regions.

<p>Quadratic fits from the time points of 1, 7 and 34 weeks of BOLD signals across regions.</p

Auditory activation in music-visualization task.

<p>All figures show the average activity across participants using an RFX GLM, <i>p <</i> 0.05, FDR corrected. <b>a</b>, Auditory activation in the music-visualization task (parasagittal view is of right hemisphere). <b>b</b>, Music-visualization task: Percent of BOLD signal change across the four scans in right superior temporal lobe. <b>c</b>, Music-visualization task: Average BOLD signals of each of the four scans in right superior temporal lobe (taken from the gray period highlighted at the bottom and averaged in 2b). Signal increased from the second to the third scan (<i>p</i> < 0.01, paired <i>t</i>-test). <b>d</b>, Music-visualization task: Percent of BOLD signal change across the four scans in left superior temporal lobe. <b>e</b>, Music-visualization task: Average BOLD signals of each of the four scans in left superior temporal lobe (taken from the gray period highlighted at the bottom of 2d and the averaged points in 2d). Signal increased from the second to the third scan (<i>p</i> < 0.05, paired <i>t</i>-test), and decreased from third to fourth scan (<i>p</i> < 0.05, paired <i>t</i>-test). All error bars represent the s.e.m. Scale bar represents 0.2 percentage BOLD signal change. * signifies <i>p</i> < 0.025 trend and ** signifies <i>p</i> < 0.05 corrected for Bonferroni multiple comparisons.</p

SMA activation in motor task.

<p>All values were extracted using an RFX GLM, <i>p</i> < 0.05, FDR corrected. Motor task: Percent of BOLD signal change across the four scans. All error bars represent the s.e.m. All conventions the same as <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0147731#pone.0147731.g001" target="_blank">Fig 1E</a>.</p

Supplementary motor area (SMA) in music-visualization and motor tasks.

<p>All figures show the average activity across participants. <b>a-c,</b> The overlapping region of interest (light green) was created with the GLM contrasts (music-visualization task > baseline) in orange and (motor task > baseline) in green, using a random effects general linear model (RFX GLM) from the third scan as described in the methods, <i>p</i> < 0.05, FDR corrected. The brain images have been made with a cluster threshold of 88 voxels (k>88). <b>d</b>, Activity in our five control subjects matched for dance experience in the same two tasks as described in the methods above. No overlapping SMA region was found between the tasks in any slices–a representative slice shown here. <b>e,</b> Music-visualization task: percent of BOLD signal change extracted from the SMA (overlapping region) of all dancers at <i>p</i> < 0.05, FDR corrected. <b>f</b>, Music-visualization task: Average BOLD signals of each of the four scans in SMA region (taken from the gray period highlighted at the bottom of 1e and the averaged points in 1e). Signal increased from second to third scan (<i>p</i> < 0.05, paired <i>t</i>-test) and decreased from third to fourth scan (<i>p</i> < 0.05, paired <i>t</i>-test). <b>g</b>, Motor task: Average BOLD signal of the four scans in same SMA voxels. No significant changes were found across the scans in this task. All error bars represent the standard error of the mean (s.e.m.). Scale bar represents 0.2 percentage BOLD signal change. * signifies <i>p</i> < 0.07 trend and ** signifies <i>p</i> < 0.05 corrected for Bonferroni multiple comparisons.</p