Kinetic Modeling of Saccharomyces cerevisiae Central Carbon Metabolism: Achievements, Limitations, and Opportunities

Central carbon metabolism comprises the metabolic pathways in the cell that process nutrients into energy, building blocks and byproducts. To unravel the regulation of this network upon glucose perturbation, several metabolic models have been developed for the microorganism Saccharomyces cerevisiae. These dynamic representations have focused on glycolysis and answered multiple research questions, but no commonly applicable model has been presented. This review systematically evaluates the literature to describe the current advances, limitations, and opportunities. Different kinetic models have unraveled key kinetic glycolytic mechanisms. Nevertheless, some uncertainties regarding model topology and parameter values still limit the application to specific cases. Progressive improvements in experimental measurement technologies as well as advances in computational tools create new opportunities to further extend the model scale. Notably, models need to be made more complex to consider the multiple layers of glycolytic regulation and external physiological variables regulating the bioprocess, opening new possibilities for extrapolation and validation. Finally, the onset of new data representative of individual cells will cause these models to evolve from depicting an average cell in an industrial fermenter, to characterizing the heterogeneity of the population, opening new and unseen possibilities for industrial fermentation improvement.

Mental health changes and the willingness to take risks

Utilizing the longitudinal SOEP data representative of the German population, we find that mental health shocks significantly decrease the willingness to take risks. We also find that mental health improvements increase the willingness to take risks significantly. Our findings are relevant for better understanding the economic decision making of the large number of individuals with mental health issues.

Recommendations on Diversity Data in the Social Sector

Administrative records, surveys, and censuses are all important resources for understanding the extent and nature of existing inequities and biases. When individuals, households, and peoples (pueblos) are properly identified based on their ethnicity, race, disability status, sexual orientation, migration status, gender identity, or other characteristics, gaps in socioeconomic indicators across these groups can be quantified. This enables policymakers to focus efforts and resources towards the most disadvantaged and promote equity. The lack of disaggregated data representative of diverse groups limits our understanding of their living conditions and economic opportunities. It also poses a significant challenge. This guide supports individuals interested in collecting or analyzing data on indigenous peoples, African descendants, people with disabilities, and LGBTQ populations by providing conceptual and empirical tools for specialists.

Recommendations on Diversity Data in the Social Sector

Administrative records, surveys, and censuses are all important resources for understanding the extent and nature of existing inequities and biases. When individuals, households, and peoples (pueblos) are properly identified based on their ethnicity, race, disability status, sexual orientation, migration status, gender identity, or other characteristics, gaps in socioeconomic indicators across these groups can be quantified. This enables policymakers to focus efforts and resources towards the most disadvantaged and promote equity. The lack of disaggregated data representative of diverse groups limits our understanding of their living conditions and economic opportunities. It also poses a significant challenge. This guide supports individuals interested in collecting or analyzing data on indigenous peoples, African descendants, people with disabilities, and LGBTQ populations by providing conceptual and empirical tools for specialists.

Neoclassical toroidal viscosity torque prediction via deep learning

GPECnet is a densely connected neural network that has been trained on GPEC data, to predict the plasma stability, neoclassical toroidal viscosity (NTV) torque, and optimized 3D coil current distributions for desired NTV torque profiles. Using NTV torque, driven by non-axisymmetric field perturbations in a tokamak, can be vital in optimizing pedestal performance by controlling the rotation profile in both the core, to ensure tearing stability, and the edge, to avoid edge localized modes (ELMs). The Generalized Perturbed Equilibrium Code (GPEC) software package can be used to calculate the plasma stability to 3D perturbations and the NTV torque profile generated by applied 3D magnetic fields. These calculations, however, involve complex integrations over space and energy distributions, which takes time to compute. Initially, GPECnet has been trained solely on data representative of the quiescent H-mode (QH) scenario, in which neutral beams are often balanced and toroidal rotation is low across the plasma profile. This work provides the foundation for active control of the rotation shear using a combination of beams and 3D fields for robust and high performance QH mode operation.

CD4 response of QuantiFERON-TB Gold Plus for positive consistency of latent tuberculosis infection in patients on dialysis

A significantly negative reversion in the QuantiFERON-TB Gold In-tube (QFT-GIT) test is reported in patients on dialysis, which makes the results unreliable. The CD4 and CD8 responses of the QFT-Gold plus (QFT-Plus) may have better positive consistency, but this needs to be investigated. We enrolled dialysis patients with baseline positive QFT-GIT0 results and conducted two rounds of follow-up paired QFT-GIT1&2 and QFT-Plus1&2 tests at an interval of 6 months. The positive consistency, concordance, and discordance of the QFT results were analyzed. A total of 236 patients on dialysis were screened, and 73 participants with positive QFT-GIT0 results were enrolled. The baseline QFT-GIT0 response was higher in the 1st QFT-Plus1(+) group than in the QFT-Plus1(−) group, but insignificantly different between the 1st QFT-GIT1(+) and QFT-GIT1(−) groups. The two assays had good correlation when concurrently tested. Fifty-three subjects completed a second round of the QFT-GIT2 and QFT-Plus2. Persistent positivity was higher with the QFT-Plus2 (81.8%) than with the QFT-GIT2 (58.8%, p = 0.040). The QFT-GIT1 and QFT-Plus1 CD4 responses were higher in patients with persistent positivity than in those with negative reversion, whereas the difference of the QFT-Plus TB1 and TB2 data, representative of the CD8 response, were similar between positive persistence and negative reversion. In conclusion, the QFT-Plus provides more reliable positive consistency than does the QFT-GIT. The CD4 interferon-γ response might play a role in maintaining positivity of LTBI.

Columnar Vertical Profile (CVP) Methodology for Validating Polarimetric Radar Retrievals in Ice Using In Situ Aircraft Measurements

A novel way to process polarimetric radar data collected via plan position indicator (PPI) scans and display those data in a time–height format is introduced. The columnar vertical profile (CVP) methodology uses radar data collected via multiple elevation scans, limited to data within a set region in range and azimuth relative to the radar, to create vertical profiles of polarimetric radar data representative of that limited region in space. This technique is compared to others existing in the literature, and various applications are discussed. Polarimetric ice microphysical retrievals are performed on CVPs created within the stratiform rain region of two mesoscale convective systems sampled during two field campaigns, where CVPs follow the track of research aircraft. Aircraft in situ data are collocated to microphysical retrieval data, and the accuracy of these retrievals is tested against other retrieval techniques in the literature.