Size-resolved aerosol emission factors and new particle formation/growth activity occurring in Mexico City during the MILAGRO 2006 Campaign

Measurements of the aerosol size distribution from 11 nm to 2.5 microns were made in Mexico City in March 2006, during the MILAGRO (Megacity Initiative: Local and Global Research Observations) field campaign. Observations at the urban supersite, referred to as T0, could often be characterized by morning conditions with high particle mass concentrations, low mixing heights, and highly correlated particle number and CO<sub>2</sub> concentrations, indicative that particle number is controlled by primary emissions. Average size-resolved and total number- and volume-based emission factors for combustion sources impacting T0 have been determined using a comparison of peak sizes in particle number and CO<sub>2</sub> concentration. Peaks are determined by subtracting the measured concentration from a calculated baseline concentration time series. The number emission and volume emission factors for particles from 11 nm to 494 nm are 1.56 × 10<sup>15</sup> particles, and 9.48 × 10<sup>11</sup> cubic microns per kg of carbon, respectively. The uncertainty of the number emission factor is approximately plus or minus 50 %. The mode of the number emission factor was between 25 and 32 nm, while the mode of the volume factor was between 0.25 and 0.32 microns. These emission factors are reported as log normal model parameters and are compared with multiple emission factors from the literature. In Mexico City in the afternoon, the CO<sub>2</sub> concentration drops during ventilation of the polluted layer, and the coupling between CO<sub>2</sub> and particle number breaks down, especially during new particle formation events when particle number is no longer controlled by primary emissions. Using measurements of particle number and CO<sub>2</sub> taken aboard the NASA DC-8, the determined primary emission factor was applied to the Mexico City Metropolitan Area (MCMA) plume to quantify the degree of secondary particle formation in the plume; the primary emission factor accounts for less than 50 % of the total particle number and the surplus particle count is not correlated with photochemical age. Primary particle volume and number in the size range 0.1–2 μm are similarly too low to explain the observed volume distribution. Contrary to the case for number, the apparent secondary volume increases with photochemical age. The size distribution of the apparent increase, with a mode at ~250 nm, is reported

How to Train a Cell–Cutting-Edge Molecular Tools

In biological systems, the formation of molecular complexes is the currency for all cellular processes. Traditionally, functional experimentation was targeted to single molecular players in order to understand its effects in a cell or animal phenotype. In the last few years, we have been experiencing rapid progress in the development of ground-breaking molecular biology tools that affect the metabolic, structural, morphological, and (epi) genetic instructions of cells by chemical, optical (optogenetic) and mechanical inputs. Such precise dissection of cellular processes is not only essential for a better understanding of biological systems, but will also allow us to better diagnose and fix common dysfunctions. Here, we present several of these emerging and innovative techniques by providing the reader with elegant examples on how these tools have been implemented in cells, and, in some cases, organisms, to unravel molecular processes in minute detail. We also discuss their advantages and disadvantages with particular focus on their translation to multicellular organisms for in vivo spatiotemporal regulation. We envision that further developments of these tools will not only help solve the processes of life, but will give rise to novel clinical and industrial applications

Single Molecule Conformational Memory Extraction: P5ab RNA Hairpin

Extracting kinetic models from single molecule data is an important route to mechanistic insight in biophysics, chemistry, and biology. Data collected from force spectroscopy can probe discrete hops of a single molecule between different conformational states. Model extraction from such data is a challenging inverse problem because single molecule data are noisy and rich in structure. Standard modeling methods normally assume (i) a prespecified number of discrete states and (ii) that transitions between states are Markovian. The data set is then fit to this predetermined model to find a handful of rates describing the transitions between states. We show that it is unnecessary to assume either (i) or (ii) and focus our analysis on the zipping/unzipping transitions of an RNA hairpin. The key is in starting with a very broad class of non-Markov models in order to let the data guide us toward the best model from this very broad class. Our method suggests that there exists a folding intermediate for the P5ab RNA hairpin whose zipping/unzipping is monitored by force spectroscopy experiments. This intermediate would not have been resolved if a Markov model had been assumed from the onset. We compare the merits of our method with those of others

Age-dependent impact of two exercise training regimens on genomic and metabolic remodeling in skeletal muscle and liver of male mice

Skeletal muscle adapts to different exercise training modalities with age; however, the impact of both variables at the systemic and tissue levels is not fully understood. Here, adult and old C57BL/6 male mice were assigned to one of three groups: sedentary, daily high-intensity intermittent training (HIIT), or moderate intensity continuous training (MICT) for 4 weeks, compatible with the older group’s exercise capacity. Improvements in body composition, fasting blood glucose, and muscle strength were mostly observed in the MICT old group, while effects of HIIT training in adult and old animals was less clear. Skeletal muscle exhibited structural and functional adaptations to exercise training, as revealed by electron microscopy, OXPHOS assays, respirometry, and muscle protein biomarkers. Transcriptomics analysis of gastrocnemius muscle combined with liver and serum metabolomics unveiled an age-dependent metabolic remodeling in response to exercise training. These results support a tailored exercise prescription approach aimed at improving health and ameliorating age-associated loss of muscle strength and function in the elderly.This work was supported by funding from the Intramural Research Program of the National Institute on Aging/NIH. Work in JMV laboratory was supported by the Spanish Ministerio de Economía y Competitividad (MINECO) grant BFU2015-64630-R, Ministerio de Ciencia, Innovación y Universidades (MICIU) grant RTI2018-100695-B-I00, Spanish Junta de Andalucía grants P18-RT-4264, 1263735-R and BIO-276, the FEDER Funding Program from the European Union, and Universidad de Córdoba. MCR was supported by a FPU fellowship from the Spanish Ministerio de Educación, Cultura y Deporte (reference FPU14/06308). SRL held a FPI predoctoral contract funded by MINECO (reference BES-2016-078229).Peer reviewe