Stochastic Search and Rescue Method for Day Ahead Economic Emission Load Dispatch Under Wind Uncertainty
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In every omics experiment, genes or their products are identified for which even state of the art tools are unable to assign a function. In the biotechnology chassis organism Pseudomonas putida, these proteins of unknown function make up 14% of the proteome. This missing information can bias analyses since these proteins can carry out functions which impact the engineering of organisms. As a consequence of predicting protein function across all organisms, function prediction tools generally fail to use all of the types of data available for any specific organism, including protein and transcript expression information. Additionally, the release of Alphafold predictions for all Uniprot proteins provides a novel opportunity for leveraging structural information. We constructed a bespoke machine learning model to predict the function of recalcitrant proteins of unknown function in Pseudomonas putida based on these sources of data, which annotated 1079 terms to 213 proteins. Among the predicted functions supplied by the model, we found evidence for a significant overrepresentation of nitrogen metabolism and macromolecule processing proteins. These findings were corroborated by manual analyses of selected proteins which identified, among others, a functionally unannotated operon that likely encodes a branch of the shikimate pathway.
The Earth’s interconnected and dynamical systems operate on a spectrum of time scales from millions of years to fractions of a second. While the evolution of the Earth and its deep interior are beyond the time span of human observations, understanding of many natural phenomena operating on human times scales have benefited from direct scientific observation. Continuous processes and those that are repeated over time shape the environment we live in. Furthermore, as we are faced with unprecedented changes to climate, understanding the deeper patterns and trends in natural systems through time have taken on new importance (Research Data Alliance, 2019). The call to reuse data is driven not only by economics but also by the recognition of their complete uniqueness (observations of natural systems are not repeatable) and scientific value in enhancing current understandings as well as potential new discoveries especially in the era of big data. These data are part of the historical record and our scientific heritage (American Geophysical Union, 2019) not only in explicitly recording earth observations but implicitly recording, and thus providing the evidence that addresses the manner in which science was conducted.
Millions of dollars were routinely spent on nuclear testing, particularly for test series conducted at the Pacific Proving Ground. Following the Castle-Bravo test of March 1, 1954, however, a small crisis involving only a few hundred dollars created a bureaucratic impasse that could not be resolved until Norris Bradbury interceded.
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Westinghouse Savannah River Company, the SRS Management and Operations Contractor at the time, procured six large IP-2 portable tanks capable of transporting liquids in 2003 to support the layup of the F Canyon at SRS. F Canyon was one of two full-scale hardened radiochemical separations facilities built at SRS in the 1950s as part of the initial construction of the Site. F Canyon and H Canyon provided actinide separations capabilities for SRS through the end of the Cold War. Following the end of the Cold War era, the decision was eventually made that only one of these radiochemical separations facilities at SRS would still be needed moving forward. As H Canyon was considered better suited for ongoing SRS missions, F Canyon was placed into a layup state in the first decade of the 21st Century, with F Area deactivation completing in 2006. This process resulted in the creation of excess, radioactively contaminated solutions, which required disposition. These solutions included contaminated organic solutions as well as DU-bearing aqueous solutions. The six portable tanks were procured to support the transportation of these solutions.
Abstract With the recent advances in data science, machine learning has been increasingly applied to convection and cloud parameterizations in global climate models (GCMs). This study extends the work of Han et al. (2020, https://doi.org/10.1029/2020MS002076 ) and uses an ensemble of 32‐layer deep convolutional residual neural networks, referred to as ResCu‐en, to emulate convection and cloud processes simulated by a superparameterized GCM, SPCAM. ResCu‐en predicts GCM grid‐scale temperature and moisture tendencies, and cloud liquid and ice water contents from moist physics processes. The surface rainfall is derived from the column‐integrated moisture tendency. The prediction uncertainty inherent in deep learning algorithms in emulating the moist physics is reduced by ensemble averaging. Results in 1‐year independent offline validation show that ResCu‐en has high prediction accuracy for all output variables, both in the current climate and in a warmer climate with +4K sea surface temperature. The analysis of different neural net configurations shows that the success to generalize in a warmer climate is attributed to convective memory and the 1‐dimensional convolution layers incorporated into ResCu‐en. We further implement a member of ResCu‐en into CAM5 with real world geography and run the neural‐network‐enabled CAM5 (NCAM) for 5 years without encountering any numerical integration instability. The simulation generally captures the global distribution of the mean precipitation, with a better simulation of precipitation intensity and diurnal cycle. However, there are large biases in temperature and moisture in high latitudes. These results highlight the importance of convective memory and demonstrate the potential for machine learning to enhance climate modeling.
Background Individuals with respiratory conditions, such as asthma, are particularly susceptible to adverse health effects associated with higher levels of ambient air pollution and temperature. This study evaluates whether hourly levels of fine particulate matter (PM 2.5 ) and dry bulb globe temperature (DBGT) are associated with the lung function of adult participants with asthma. Methods and findings Global positioning system (GPS) location, respiratory function (measured as forced expiratory volume at 1 second (FEV 1 )), and self-reports of asthma medication usage and symptoms were collected as part of the Exposure, Location, and Lung Function (ELF) study. Hourly ambient PM 2.5 and DBGT exposures were estimated by integrating air quality and temperature public records with time-activity patterns using GPS coordinates for each participant (n = 35). The relationships between acute PM 2.5 , DBGT, rescue bronchodilator use, and lung function collected in one week periods and over two seasons (summer/winter) were analyzed by multivariate regression, using different exposure time frames. In separate models, increasing levels in PM 2.5 , but not DBGT, were associated with rescue bronchodilator use. Conversely DBGT, but not PM 2.5 , had a significant association with FEV 1 . When DBGT and PM 2.5 exposures were placed in the same model, the strongest association between cumulative PM 2.5 exposures and the use of rescue bronchodilator was identified at the 0–24 hours (OR = 1.030; 95% CI = 1.012–1.049; p-value = 0.001) and 0–48 hours (OR = 1.030; 95% CI = 1.013–1.057; p-value = 0.001) prior to lung function measure. Conversely, DBGT exposure at 0 hours (β = 3.257; SE = 0.879; p-value>0.001) and 0–6 hours (β = 2.885; SE = 0.903; p-value = 0.001) hours before a reading were associated with FEV 1 . No significant interactions between DBGT and PM 2.5 were observed for rescue bronchodilator use or FEV 1 . Conclusions Short-term increases in PM 2.5 were associated with increased rescue bronchodilator use, while DBGT was associated with higher lung function (i.e. FEV 1 ). Further studies are needed to continue to elucidate the mechanisms of acute exposure to PM 2.5 and DBGT on lung function in asthmatics.
Phosphorothioate modifications have widespread use in the field of nucleic acids. As substitution of sulfur for oxygen can alter metal coordination preferences, the phosphorothioate metal-rescue experiment is a powerful method for identifying metal coordination sites that influence specific properties in a large RNAs. The A9/G10.1 metal binding site of the hammerhead ribozyme (HHRz) has previously been shown to be functionally important through phosphorothioate rescue experiments. While an A9-S Rp substitution is inhibitory in Mg 2+ , thiophilic Cd 2+ rescues HHRz activity. Mn 2+ is also often used in phosphorothioate metal-rescue studies but does not support activity for the A9-S Rp HHRz. Here, we use EPR, electron spin-echo envelope modulation (ESEEM), and X-ray absorption spectroscopic methods to directly probe the structural consequences of Mn 2+ and Cd 2+ coordination to R p and S p phosphorothioate modifications at the A9/G10.1 site in the truncated hammerhead ribozyme (tHHRz). The results demonstrate that while Cd 2+ does indeed bind to S in the thio-substituted ligand, Mn 2+ coordinates to the non–sulfur oxo group of this phosphorothioate, regardless of isomer. Computational models demonstrate the energetic preference of Mn—O over Mn—S coordination in metal-dimethylthiophosphate models. In the case of the tHHRz, the resulting Mn 2+ coordination preference of oxygen in either R p or S p A9 phosphorothioates differentially tunes catalytic activity, with Mn—O coordination in the A9-S Rp phosphorothioate enzyme being inhibitory.
Abstract Current moist physics parameterization schemes in general circulation models (GCMs) are the main source of biases in simulated precipitation and atmospheric circulation. Recent advances in machine learning make it possible to explore data‐driven approaches to developing parameterization for moist physics processes such as convection and clouds. This study aims to develop a new moist physics parameterization scheme based on deep learning. We use a residual convolutional neural network (ResNet) for this purpose. It is trained with 1‐year simulation from a superparameterized GCM, SPCAM. An independent year of SPCAM simulation is used for evaluation. In the design of the neural network, referred to as ResCu, the moist static energy conservation during moist processes is considered. In addition, the past history of the atmospheric states, convection, and clouds is also considered. The predicted variables from the neural network are GCM grid‐scale heating and drying rates by convection and clouds, and cloud liquid and ice water contents. Precipitation is derived from predicted moisture tendency. In the independent data test, ResCu can accurately reproduce the SPCAM simulation in both time mean and temporal variance. Comparison with other neural networks demonstrates the superior performance of ResNet architecture. ResCu is further tested in a single‐column model for both continental midlatitude warm season convection and tropical monsoonal convection. In both cases, it simulates the timing and intensity of convective events well. In the prognostic test of tropical convection case, the simulated temperature and moisture biases with ResCu are smaller than those using conventional convection and cloud parameterizations.
Abstract Understanding protein structure and function relationships in cellulose synthase (CesA), including divergent isomers, is an important goal. Here, we report results from mutant complementation assays that tested the ability of sequence variants of AtCesA7, a secondary wall CesA of Arabidopsis thaliana , to rescue the collapsed vessels, short stems, and low cellulose content of the irx3‐1 AtCesA7 null mutant. We tested a catalytic null mutation and seven missense or small domain changes in and near the AtCesA7 FTVTSK motif, which lies near the catalytic domain and may, analogously to bacterial CesA, exist within a substrate “gating loop.” A low‐to‐high gradient of rescue occurred, and even inactive AtCesA7 had a small positive effect on stem cellulose content but not stem elongation. Overall, secondary wall cellulose content and stem length were moderately correlated, but the results were consistent with threshold amounts of cellulose supporting particular developmental processes. Vibrational sum frequency generation microscopy allowed tissue‐specific analysis of cellulose content in stem xylem and interfascicular fibers, revealing subtle differences between selected genotypes that correlated with the extent of rescue of the collapsing xylem phenotype. Similar tests on PpCesA5 from the moss Physcomitrium (formerly Physcomitrella ) patens helped us to synergize the AtCesA7 results with prior results on AtCesA1 and PpCesA5. The cumulative results show that the FTVTxK region is important for the function of an angiosperm secondary wall CesA as well as widely divergent primary wall CesAs, while differences in complementation results between isomers may reflect functional differences that can be explored in further work.
Cellulose synthase 5 (CESA5) and CESA6 are known to share substantial functional overlap. In the zinc-finger domain (ZN) of CESA5, there are five amino acid (AA) mismatches when compared to CESA6. These mismatches in CESA5 were replaced with their CESA6 counterparts one by one until all were replaced, generating nine engineered CESA5s. Each N-terminal enhanced yellow fluorescent protein-tagged engineered CESA5 was introduced to prc1-1, a cesa6 null mutant, and resulting mutants were subjected to phenotypic analyses. For this work, we found that five single AA-replaced CESA5 proteins partially rescue the prc1-1 mutant phenotypes to different extents. Multi-AA replaced CESA5s further rescued the mutant phenotypes in an additive manner, culminating in full recovery by CESA5 G43R + S49T+S54P+S80A+Y88F . Investigations in cellulose content, cellulose synthase complex (CSC) motility, and cellulose microfibril organization in the same mutants support the results of the phenotypic analyses. Bimolecular fluorescence complementation assays demonstrated that the level of homodimerization in every engineered CESA5 is substantially higher than CESA5. The mean fluorescence intensity of CSCs carrying each engineered CESA5 fluctuates with the degree to which the prc1-1 mutant phenotypes are rescued by introducing a corresponding engineered CESA5. Taken together, these five AA mismatches in the ZNs of CESA5 and CESA6 cooperatively modulate the functional properties of these CESAs by controlling their homodimerization capacity, which in turn imposes proportional changes on the incorporation of these CESAs into CSCs.
Elongating RNA polymerase II (Pol II) can be paused or arrested by a variety of obstacles. These obstacles include DNA lesions, DNA-binding proteins, and small molecules. Hairpin pyrrole-imidazole (Py-Im) polyamides bind to the minor groove of DNA in a sequence-specific manner and induce strong transcriptional arrest. Remarkably, this Py-Im–induced Pol II transcriptional arrest is persistent and cannot be rescued by transcription factor TFIIS. In contrast, TFIIS can effectively rescue the transcriptional arrest induced by a nucleosome barrier. The structural basis of Py-Im–induced transcriptional arrest and why TFIIS cannot rescue this arrest remain elusive. Here we determined the X-ray crystal structures of four distinct Pol II elongation complexes (Pol II ECs) in complex with hairpin Py-Im polyamides as well as of the hairpin Py-Im polyamides–dsDNA complex. We observed that the Py-Im oligomer directly interacts with RNA Pol II residues, introduces compression of the downstream DNA duplex, prevents Pol II forward translocation, and induces Pol II backtracking. These results, together with biochemical studies, provide structural insight into the molecular mechanism by which Py-Im blocks transcription. Our structural study reveals why TFIIS fails to promote Pol II bypass of Py-Im–induced transcriptional arrest.
Cellulose is synthesized at the plasma membrane by the cellulose synthase complex, a structure that contains three distinct isoforms of the catalytic subunit, cellulose synthase A (CESA). The division into three subunits appears early in land plant evolution and is highly conserved, particularly for the secondary cell wall. However, what if any unique roles each isoform plays in the complex remain unclear. Here, we assessed the contributions of specific isoforms to microfibril synthesis. First, we expressed CESA isoforms of the primary cell wall or the moss Physcomitrium patens in Arabidopsis thaliana backgrounds missing a secondary cell wall CESA. While the primary cell wall isoforms rescued the cesa knockout phenotype with partial isoform specificity, those from the moss rescued with fewer restrictions. Then, we recreated various CESA missense mutations in all three of the secondary cell wall isoforms; while results are consistent with isoform specificity, they are difficult to interpret further without molecular structures. Finally, we show that catalytically inactive CESA isoforms restore growth and cellulose content in the corresponding knockout in an isoform-specific manner; along with partial rescue of the growth and cellulose content of the inflorescence stem, the replacement lines have fiber cells with partially disorganized microfibrils and secondary cell wall cellulose with narrow crystal width. Generally, effects were more pronounced in lines where CESA8 was inactivated compared with inactivating CESA4 or 7, which tended to have similar phenotypes to each other. Here, we account for these results with a model for cellulose synthase structure with the isoforms assigned specific localization within the cellulose synthase complex.
The evolution of plastid genomes (plastomes) in land plants is typically conservative, with extensive structural rearrangements present in only a few groups. Early Southern blot analysis identified two Lobelia species that minimally required deletion of the plastid gene accD and five inversions to account for their plastome arrangement relative to the ancestral organization. Sixty alternative 5-step inversion scenarios could account for the observed arrangement, but only one scenario was consistent with the criterion of ‘common cause’ attributable to a putative rearrangement hot spot at the accD deletion-site. Plastome sequencing demonstrated that this previously hypothesized inversion order is historically accurate. Detailed reconstructions of the ancestral plastome organization before and after each inversion are presented herein. Stem-loop and disruption-rescue models were evaluated for each inversion. One inversion has an obvious stem-loop basis, but the other four inversions were primarily caused by serial insertion of foreign (extra-plastid) DNA bearing large open-reading frames that disrupted plastome organization at the accD deletion-site, and complete plastomes were rescued by seemingly arbitrary ligation or fortuitous recombination at the other inversion endpoint. Transposed copies of DNA segments from elsewhere in the plastome are frequently inserted at inversion junctions, and four junctions are consistent with the stem-loop ligation model.
Aging muscle experiences functional decline in part mediated by impaired mitochondrial ADP sensitivity. Elamipretide (ELAM) rapidly improves physiological and mitochondrial function in aging and binds directly to the mitochondrial ADP transporter ANT. We hypothesized that ELAM improves ADP sensitivity in aging leading to rescued physiological function. We measured the response to ADP stimulation in young and old muscle mitochondria with ELAM treatment, in vivo heart and muscle function, and compared protein abundance, phosphorylation, and S-glutathionylation of ADP/ATP pathway proteins. ELAM treatment increased ADP sensitivity in old muscle mitochondria by increasing uptake of ADP through the ANT and rescued muscle force and heart systolic function. Protein abundance in the ADP/ATP transport and synthesis pathway was unchanged, but ELAM treatment decreased protein s-glutathionylation incuding of ANT. Mitochondrial ADP sensitivity is rapidly modifiable. This research supports the hypothesis that ELAM improves ANT function in aging and links mitochondrial ADP sensitivity to physiological function.
Highlights: • RAN and YBX1 are co-expressed and required for cell proliferation in OSCC cells. • RAN and YBX1 are positively associated with the immune infiltrates of CD4{sup +} Th2 cells. • RAN and YBX1 can promote IL-4 expression. • RAN is a direct target of YBX1. • RAN and YBX1 can serve as potential co-biomarkers for poor prognosis in OSCC. Oral squamous cell carcinoma (OSCC) is one of the most common malignancies in the world, with a high mortality rate. RAN is a member of the Ras GTPase family and is overexpressed in a range of cancers, however, the relationship between RAN and OSCC is rarely reported. In this study, we found that RAN is overexpressed in OSCC tissues. RAN inhibition retarded OSCC cell proliferation and led to apoptosis and cell cycle arrest. Knockdown of RAN inhibited tumor growth in vivo. Strikingly, we found that RAN and oncogene Y-box binding protein-1 (YBX1) are positively associated with the immune infiltrates of CD4{sup +} Th2 cells in multiple types of cancer, and can promote IL-4 expression. IL-4 treatment can partially rescue RAN knockdown-induced cell apoptosis in OSCC cells. Moreover, overexpression of RAN could rescue cell growth inhibition caused by knockdown of YBX1. Furthermore, patients with low expression of both RAN and YBX1 had better overall survival than others. Collectively, these findings indicate that RAN is a target of YBX1. RAN and YBX1 are required for cell proliferation and IL-4 expression. RAN and YBX1 are co-expressed and can serve as potential co-biomarkers for poor prognosis in OSCC.