Crosstalk between RNA Pol II C-Terminal Domain Acetylation and Phosphorylation via RPRD Proteins.

Post-translational modifications of the RNA polymerase II C-terminal domain (CTD) coordinate the transcription cycle. Crosstalk between different modifications is poorly understood. Here, we show how acetylation of lysine residues at position 7 of characteristic heptad repeats (K7ac)-only found in higher eukaryotes-regulates phosphorylation of serines at position 5 (S5p), a conserved mark of polymerases initiating transcription. We identified the regulator of pre-mRNA-domain-containing (RPRD) proteins as reader proteins of K7ac. K7ac enhanced CTD peptide binding to the CTD-interacting domain (CID) of RPRD1A and RPRD1B proteins in isothermal calorimetry and molecular modeling experiments. Deacetylase inhibitors increased K7ac- and decreased S5-phosphorylated polymerases, consistent with acetylation-dependent S5 dephosphorylation by an RPRD-associated S5 phosphatase. Consistent with this model, RPRD1B knockdown increased S5p but enhanced K7ac, indicating that RPRD proteins recruit K7 deacetylases, including HDAC1. We also report autoregulatory crosstalk between K7ac and S5p via RPRD proteins and their interactions with acetyl- and phospho-eraser proteins.

BCR::ABL1 Kinase N-lobe Mutants Confer Moderate to High Degrees of Resistance to Asciminib.

Secondary kinase domain mutations in BCR::ABL1 represent the most common cause of resistance to tyrosine kinase inhibitor (TKI) therapy in chronic myeloid leukemia patients. The first five approved BCR::ABL1 TKIs target the ATP-binding pocket. Mutations confer resistance to these ATP-competitive TKIs and those approved for other malignancies by decreasing TKI affinity and/or increasing ATP affinity. Asciminib, the first highly active allosteric TKI approved for any malignancy, targets an allosteric regulatory pocket in the BCR::ABL1 kinase C-lobe. As a non-ATP-competitive inhibitor, the activity of asciminib is predicted to be impervious to increases in ATP affinity. Here we report several known mutations that confer resistance to ATP-competitive TKIs in the BCR::ABL1 kinase N-lobe that are distant from the asciminib binding pocket yet unexpectedly confer in vitro resistance to asciminib. Among these is BCR::ABL1 M244V, which confers clinical resistance even to escalated asciminib doses. We demonstrate that BCR::ABL1 M244V does not impair asciminib binding, thereby invoking a novel mechanism of resistance. Molecular dynamics simulations of the M244V substitution implicate stabilization of an active kinase conformation through impact on the -C helix as a mechanism of resistance. These N-lobe mutations may compromise the clinical activity of ongoing combination studies of asciminib with ATP-competitive TKIs.

POMSimulator: An open-source tool for predicting the aqueous speciation and self-assembly mechanisms of polyoxometalates.

Elucidating the speciation (in terms of concentration versus pH) and understanding the formation mechanisms of polyoxometalates remains a significant challenge, both in experimental and computational domains. POMSimulator is a new methodology that tackles this problem from a purely computational perspective. The methodology uses results from quantum mechanics based methods to automatically set up the chemical reaction network, and to build speciation models. As a result, it becomes possible to predict speciation and phase diagrams, as well as to derive new insights into the formation mechanisms of large molecular clusters. In this work we present the main features of the first open-source version of the software. Since the first report [Chem. Sci. 2020, 11, 8448-8456], POMSimulator has undergone several improvements to keep up with the growing challenges that were tackled. After four years of research, we recognize that the source code is sufficiently stable to share a polished and user-friendly version. The Python code, manual, examples, and install instructions can be found at https://github.com/petrusen/pomsimulator.

Multi-Time-Scale Simulation of Complex Reactive Mixtures: How Do Polyoxometalates Form?

Understanding the dynamics of reactive mixtures still challenges both experiments and theory. A relevant example can be found in the chemistry of molecular metal-oxide nanoclusters, also known as polyoxometalates. The high number of species potentially involved, the interconnectivity of the reaction network, and the precise control of the pH and concentrations needed in the synthesis of such species make the theoretical/computational treatment of such processes cumbersome. This work addresses this issue relying on a unique combination of recently developed computational methods that tackle the construction, kinetic simulation, and analysis of complex chemical reaction networks. By using the Bell-Evans-Polanyi approximation for estimating activation energies, and an accurate and robust linear scaling for correcting the computed pKa values, we report herein multi-time-scale kinetic simulations for the self-assembly processes of polyoxotungstates that comprise 22 orders of magnitude, from tens of femtoseconds to months of reaction time. This very large time span was required to reproduce very fast processes such as the acid/base equilibria (at 10-12 s), relatively slow reactions such as the formation of key clusters such as the metatungstate (at 103 s), and the very slow assembly of the decatungstate (at 106 s). Analysis of the kinetic data and of the reaction network topology shed light onto the details of the main reaction mechanisms, which explains the origin of kinetic and thermodynamic control followed by the reaction. Simulations at alkaline pH fully reproduce experimental evidence since clusters do not form under those conditions.

Chitin Nanofibrils from Fungi for Hierarchical Gel Polymer Electrolytes for Transient Zinc-Ion Batteries with Stable Zn Electrodeposition.

Rechargeable batteries play an integral role toward carbon neutrality. Environmentally sustainable batteries should consider the trade-offs between material renewability, processability, thermo-mechanical and electrochemical performance, as well as transiency. To address this dilemma, we follow circular economy principles to fabricate fungal chitin nanofibril (ChNF) gel polymer electrolytes (GPEs) for zinc-ion batteries. These biocolloids are physically entangled into hierarchical hydrogels with specific surface areas of 49.5 m2 ·g-1 . Ionic conductivities of 54.1 mS·cm-1 and a Zn2+ transference number of 0.468 are reached, outperforming conventional non-renewable/non-biodegradable glass microfibre separator-liquid electrolyte pairs. Enabled by its mechanically elastic properties and large water uptake, a stable Zn electrodeposition in symmetric Zn|Zn configuration with a lifespan above 600 h at 9.5 mA·cm-2 is obtained. At 100 mA·g-1 , the discharge capacity of Zn/α-MnO2 full cells increases above 500 cycles when replacing glass microfiber separators with ChNF GPEs, while the rate performance remains comparable to glass microfiber separators. To make the battery completely transient, the metallic current collectors are replaced by biodegradable polyester/carbon black composites undergoing degradation in water at 70 °C. This work demonstrates the applicability of bio-based materials to fabricate green and electrochemically competitive batteries with potential applications in sustainable portable electronics, or biomedicine.

Performance Analysis of a Repetition Cat Code Architecture: Computing 256-bit Elliptic Curve Logarithm in 9 Hours with 126 133 Cat Qubits.

Cat qubits provide appealing building blocks for quantum computing. They exhibit a tunable noise bias yielding an exponential suppression of bit flips with the average photon number and a protection against the remaining phase errors can be ensured by a simple repetition code. We here quantify the cost of a repetition code and provide valuable guidance for the choice of a large scale architecture using cat qubits by realizing a performance analysis based on the computation of discrete logarithms on an elliptic curve with Shor's algorithm. By focusing on a 2D grid of cat qubits with neighboring connectivity, we propose to implement 2-qubit gates via lattice surgery and Toffoli gates with off-line fault-tolerant preparation of magic states through projective measurements and subsequent gate teleportations. All-to-all connectivity between logical qubits is ensured by routing qubits. Assuming a ratio between single- and two-photon losses of 10^{-5} and a cycle time of 500 ns, we show concretely that such an architecture can compute a 256-bit elliptic curve logarithm in 9 h with 126 133 cat qubits and on average 19 photons by cat state. We give the details of the realization of Shor's algorithm so that the proposed performance analysis can be easily reused to guide the choice of architecture for others platforms.

The N-Terminal Region of the BcWCL1 Photoreceptor Is Necessary for Self-Dimerization and Transcriptional Activation upon Light Stimulation in Yeast.

The BcWCL1 protein is a blue-light photoreceptor from the fungus Botrytis cinerea. This protein has a central role in B. cinerea circadian regulation and is an ortholog to WC-1 from Neurospora crassa. The BcWCL1 and WC-1 proteins have similar protein domains, including a LOV (Light Oxygen Voltage) domain for light sensing, two PAS (Per Arnt Sim) domains for protein-protein interaction, and a DNA binding domain from the GATA family. Recently, the blue-light response of BcWCL1 was demonstrated in a version without PAS domains (BcWCL1PAS∆). Here, we demonstrated that BcWCL1PAS∆ is capable of self-dimerization through its N-terminal region upon blue-light stimulation. Interestingly, we observed that BcWCL1PAS∆ enables transcriptional activation as a single component in yeast. By using chimeric transcription factors and the luciferase reporter gene, we assessed the transcriptional activity of different fragments of the N-terminal and C-terminal regions of BcWCL1PAS∆, identifying a functional transcriptional activation domain (AD) in the N-terminal region that belongs to the 9aaTAD family. Finally, we determined that the transcriptional activation levels of BcWCL1PAS∆ AD are comparable to those obtained with commonly used ADs in eukaryotic cells (Gal4 and p65). In conclusion, the BcWCL1PAS∆ protein self-dimerized and activated transcription in a blue-light-dependent fashion, opening future applications of this photoreceptor in yeast optogenetics.

Cysteine Oxidation in Proteins: Structure, Biophysics, and Simulation.

Cysteine side chains can exist in distinct oxidation states depending on the pH and redox potential of the environment, and cysteine oxidation plays important yet complex regulatory roles. Compared with the effects of post-translational modifications such as phosphorylation, the effects of oxidation of cysteine to sulfenic, sulfinic, and sulfonic acid on protein structure and function remain relatively poorly characterized. We present an analysis of the role of cysteine reactivity as a regulatory factor in proteins, emphasizing the interplay between electrostatics and redox potential as key determinants of the resulting oxidation state. A review of current computational approaches suggests underdeveloped areas of research for studying cysteine reactivity through molecular simulations.

Elucidating Sulfide Activation Mode in Metal-Catalyzed Sulfoxidation Reactivity.

Interest in the catalytic activation of peroxides, together with the requirement of stereoselectivity for the production of enantiopure sulfoxides, has made sulfoxidation the ideal playground for theoretical and experimental physical organic chemists investigating oxidation reactivity. Efforts have been dedicated for elucidating the catalytic pathway regarding these species and for dissecting out the dominant factors influencing the yield and stereochemistry. In this article, Ti(IV) and Hf(IV) aminotriphenolate complexes have been prepared and investigated as catalysts in the presence of peroxides in sulfide oxidation. Experimental results have been combined with theoretical calculations obtaining detailed mechanistic information on oxygen transfer processes. The study revealed that steric issues are mainly responsible for the formation of intermediates in the oxidation pathway. In particular, we could highlight the occurrence of a blended situation where the steric effects of sulfides, ligands, and oxidants influence the formation of different intermediates and reaction pathways.

Reopening higher education buildings in post-epidemic COVID-19 scenario: monitoring and assessment of indoor environmental quality after implementing ventilation protocols in Spain and Portugal.

Post-epidemic protocols have been implemented in public buildings to keep indoor environments safe. However, indoor environmental conditions are affected by this decision, which also affect the occupants of buildings. This fact has major implications in educational buildings, where the satisfaction and learning performance of students may also be affected. This study investigates the impact of post-epidemic protocols on indoor environmental conditions in higher education buildings of one Portuguese and one Spanish university. A sensor monitoring campaign combined with a simultaneous questionnaire was conducted during the reopening of the educational buildings. Results showed that although renewal air protocols were effective and the mean CO2 concentration levels remained low (742 ppm and 519 ppm in Portugal and Spain universities, respectively), students were dissatisfied with the current indoor environmental conditions. Significant differences were also found between the responses of Portuguese and Spanish students. Indeed, Spanish students showed warmer preferences (thermal neutrality = 23.3℃) than Portuguese students (thermal neutrality = 20.7℃). In terms of involved indoor factors, the obtained data showed significant correlations (p < 0.001) between acoustic factors and overall satisfaction in the Portuguese students (ρ = 0.540) and between thermal factors and overall satisfaction in the Spanish students (ρ = 0.522). Therefore, indoor environmental conditions should be improved by keeping spaces safe while minimizing the impact of post-epidemic protocols on student learning performance.

Modelling and visualization for the analysis and comprehension of the acoustic performance of buildings through the implementation of a building information modelling-based methodology.

Technical and technological advances have revolutionised the architecture, engineering, and construction industries in recent decades. Building information modelling (BIM) methodology has become essential in the process of information management and the development of building projects. This study aims to analyse the potential advantages of the implementation of BIM-based models for the acquisition of theoretical and procedural knowledge about building acoustics. This procedure was implemented as part of a problem-solving exercise in Science, Technology, Engineering, and Mathematics (STEM) university degrees. For this purpose, three-dimensional (3D) BIM models were generated to assess the contribution of their implementation in the process of visualization, comprehension, and analysis of the acoustic behaviour of buildings. The participants' experiences and satisfaction with the BIM models were measured through a questionnaire. The results showed a high level of satisfaction among the participants and good potential for the application of 3D models based on BIM methodology for the acquisition of knowledge and practical skills in building acoustics. These results highlight the potential of BIM models to provide information for understanding the procedure followed during data collection in the experimental analysis and to facilitate the understanding of system behavior.

Rationalizing the Mechanism of Peroxyformate Decomposition: Computational Insights To Understand Solvent Influence.

The heterolytic decomposition of tert-butyl peroxyformate to tert-butanol and carbon dioxide, catalyzed by pyridine, is a long-known example of a reaction whose kinetics are strongly affected by solvent polarity. From DFT and ab initio methods together with the SMD implicit solvation model, an extension on the formerly accepted mechanism is proposed. This novel proposal involves the formation of a carbonic acid ester intermediate and its further decomposition, through an unreported pyridine-mediated stepwise route. Computed barriers for this mechanism at DLPNO/CCSD(T)-def2-TZVP are in excellent agreement with experimental kinetic data across different solvents. Furthermore, the strong relationships between activation energies, geometric parameters in the transition state and the characteristics of the different solvents are also analyzed in depth.

Hospital length of stay for COVID-19 patients: Data-driven methods for forward planning.

BACKGROUND: Predicting hospital length of stay (LoS) for patients with COVID-19 infection is essential to ensure that adequate bed capacity can be provided without unnecessarily restricting care for patients with other conditions. Here, we demonstrate the utility of three complementary methods for predicting LoS using UK national- and hospital-level data. METHOD: On a national scale, relevant patients were identified from the COVID-19 Hospitalisation in England Surveillance System (CHESS) reports. An Accelerated Failure Time (AFT) survival model and a truncation corrected method (TC), both with underlying Weibull distributions, were fitted to the data to estimate LoS from hospital admission date to an outcome (death or discharge) and from hospital admission date to Intensive Care Unit (ICU) admission date. In a second approach we fit a multi-state (MS) survival model to data directly from the Manchester University NHS Foundation Trust (MFT). We develop a planning tool that uses LoS estimates from these models to predict bed occupancy. RESULTS: All methods produced similar overall estimates of LoS for overall hospital stay, given a patient is not admitted to ICU (8.4, 9.1 and 8.0 days for AFT, TC and MS, respectively). Estimates differ more significantly between the local and national level when considering ICU. National estimates for ICU LoS from AFT and TC were 12.4 and 13.4 days, whereas in local data the MS method produced estimates of 18.9 days. CONCLUSIONS: Given the complexity and partiality of different data sources and the rapidly evolving nature of the COVID-19 pandemic, it is most appropriate to use multiple analysis methods on multiple datasets. The AFT method accounts for censored cases, but does not allow for simultaneous consideration of different outcomes. The TC method does not include censored cases, instead correcting for truncation in the data, but does consider these different outcomes. The MS method can model complex pathways to different outcomes whilst accounting for censoring, but cannot handle non-random case missingness. Overall, we conclude that data-driven modelling approaches of LoS using these methods is useful in epidemic planning and management, and should be considered for widespread adoption throughout healthcare systems internationally where similar data resources exist.

Monitoring and Assessment of Indoor Environmental Conditions after the Implementation of COVID-19-Based Ventilation Strategies in an Educational Building in Southern Spain.

Since students and teachers spend much of their time in educational buildings, it is critical to provide good levels of indoor environmental quality (IEQ). The current COVID-19 pandemic has shown that maintaining a good indoor air quality level is an effective measure to control the transmission of the SARS-CoV-2 virus. This study used sensors to monitor key IEQ factors and assess several natural ventilation scenarios in a classroom of the University of Granada. Subsequently, the IEQ factors (temperature, relative humidity, CO2 concentration, acoustic environment, and air velocity) were evaluated for the selected ventilation scenarios in the occupied classroom, and the field monitoring was carried out in two different assessment periods, winter and summer. The obtained results show that the CO2 concentration levels were well below the recommended limits. However, the maintenance of the recommended thermal and acoustic IEQ factors was significantly affected by the natural ventilation strategies (temperature and relative humidity values were very close to the outside values, and the background sound pressure level was over 35 dBA during the entire assessment). The proper measurements and careful selection of the appropriate ventilation scenarios become of utmost importance to ensure that the ventilation rates required by the health authorities are achieved.

Analysis of Impact of Natural Ventilation Strategies in Ventilation Rates and Indoor Environmental Acoustics Using Sensor Measurement Data in Educational Buildings.

Indoor environmental conditions can significantly affect occupants' health and comfort. These conditions are especially important in educational buildings, where students, teachers and staff spend long periods of the day and are vulnerable to these factors. Recently, indoor air quality has been a focus of attention to ensure that disease transmission in these spaces is minimised. In order to increase the knowledge in this field, experimental tests have been carried out to characterise the impact of natural ventilation strategies on indoor air quality and the acoustic environment. This study has evaluated three ventilation scenarios in four different classrooms in buildings of the University of Granada, considering different window and door opening configurations. Ventilation rates were estimated using the CO2 Decay Method, and background noise recordings were made in each classroom for acoustic tests. Results show that specific natural ventilation strategies have a relevant impact that is worth considering on the background noise in indoor spaces. In this sense ventilation rates provided by the different configurations varied between 3.7 and 39.8 air changes per hour (ACH) and the acoustic tests show a background noise ranging from 43 to 54 dBA in these scenarios. Consequently, managers and teachers should take into account not only the ACH, but also other collateral impacts on the indoor environmental conditions such as the thermal comfort or the acoustic environment.

Exploring protein myristoylation in Toxoplasma gondii.

Toxoplasma gondii is an important human and veterinary pathogen and the causative agent of toxoplasmosis, a potentially severe disease especially in immunocompromised or congenitally infected humans. Current therapeutic compounds are not well-tolerated, present increasing resistance, limited efficacy and require long periods of treatment. On this context, searching for new therapeutic targets is crucial to drug discovery. In this sense, recent works suggest that N-myristoyltransferase (NMT), the enzyme responsible for protein myristoylation that is essential in some parasites, could be the target of new anti-parasitic compounds. However, up to date there is no information on NMT and the extent of this modification in T. gondii. In this work, we decided to explore T. gondii genome in search of elements related with the N-myristoylation process. By a bioinformatics approach it was possible to identify a putative T. gondii NMT (TgNMT). This enzyme that is homologous to other parasitic NMTs, presents activity in vitro, is expressed in both intra- and extracellular parasites and interacts with predicted TgNMT substrates. Additionally, NMT activity seems to be important for the lytic cycle of Toxoplasma gondii. In parallel, an in silico myristoylome predicts 157 proteins to be affected by this modification. Myristoylated proteins would be affecting several metabolic functions with some of them being critical for the life cycle of this parasite. Together, these data indicate that TgNMT could be an interesting target of intervention for the treatment of toxoplasmosis.

The CHILD Intervention for Living Drug-free Comprehensive Assessment of Risk, Resilience, and Experience (CHILD CARRE) Measure: Initial Findings.

This paper summarizes the development and evaluation of an assessment instrument for children ages 7-12. The CHILD CARRE measure is a semi-structured interview with 7 domains. Children from the USA and Argentina (N=134) completed baseline and follow-up assessments. Substance use occurred at an average age of 8. Almost 33% of the children were taking medications for medical issues, more than 50% of them said that medical problem gets in the way of doing things they like to to do and almost 64% of the children stated that they would like to feel better. On average, children completed third grade in school, 56% of them knew how to read and 26% of the children started making money at age 8. Most children (74%) saw someone drunk or high and 23% of children reported alcohol or psychoactive substance use. Among these children using substances, such substance use occurred at an average age of 8, and in the past 30 days they used these substances an average for 5 days. The rating of level of risk on the part of the interviewer placed these children in the "risky" to "very risky" categories. Most children reported seeing their family members smoking (83%) or using alcohol (67%), and 49% reported seeing their family members high on drugs. Few children (10%) had conflicts with the law, while 46% of their family members had legal problems. Some children (30%) reported having serious problems getting along with family members, neighbors, or friends. These results suggest that this measure can serve as the first comprehensive measure to assess multiple life domains for young children at risk for or using psychoactive substances.

Impact of Recruitment on Static and Dynamic Lung Strain in Acute Respiratory Distress Syndrome.

BACKGROUND: Lung strain, defined as the ratio between end-inspiratory volume and functional residual capacity, is a marker of the mechanical load during ventilation. However, changes in lung volumes in response to pressures may occur in injured lungs and modify strain values. The objective of this study was to clarify the role of recruitment in strain measurements. METHODS: Six oleic acid-injured pigs were ventilated at positive end-expiratory pressure (PEEP) 0 and 10 cm H2O before and after a recruitment maneuver (PEEP = 20 cm H2O). Lung volumes were measured by helium dilution and inductance plethysmography. In addition, six patients with moderate-to-severe acute respiratory distress syndrome were ventilated with three strategies (peak inspiratory pressure/PEEP: 20/8, 32/8, and 32/20 cm H2O). Lung volumes were measured in computed tomography slices acquired at end-expiration and end-inspiration. From both series, recruited volume and lung strain (total, dynamic, and static) were computed. RESULTS: In the animal model, recruitment caused a significant decrease in dynamic strain (from [mean ± SD] 0.4 ± 0.12 to 0.25 ± 0.07, P < 0.01), while increasing the static component. In patients, total strain remained constant for the three ventilatory settings (0.35 ± 0.1, 0.37 ± 0.11, and 0.32 ± 0.1, respectively). Increases in tidal volume had no significant effects. Increasing PEEP constantly decreased dynamic strain (0.35 ± 0.1, 0.32 ± 0.1, and 0.04+0.03, P < 0.05) and increased static strain (0, 0.06 ± 0.06, and 0.28 ± 0.11, P < 0.05). The changes in dynamic and total strain among patients were correlated to the amount of recruited volume. An analysis restricted to the changes in normally aerated lung yielded similar results. CONCLUSION: Recruitment causes a shift from dynamic to static strain in early acute respiratory distress syndrome.

Social choice functions: A tool for ranking variables involved in action plans against road noise.

Traffic noise is gaining importance in planning and operation of roads in developing countries, and particularly in Europe and Latin America. Many variables with different degrees of importance influence the perception of noise from roads. Thus, the problem of prioritizing road stretches for action against such noise is an important issue in environmental noise management. For example, it can be addressed using multicriteria methods. However, these methodologies require criteria or suitable variables to be ranked according to their relative importance. In the present study, for this ranking, a list of nine variables involved in the decision-making process (called "road stretch priority variables") was presented in the form of questionnaires to high-level experts from Andalusia, southern Spain. These experts ranked the variables by relevance. Using the same data, seven social choice functions (Plurality, Raynaud, Kemeny-Young, Copeland, Simpson, Schulze, and Borda) were used in order to rank the variables. The results indicate that the most important variables were those that take into account the parameters of greatest exposure for the citizens, followed by variables related to the intensity of the problem analyzed. The results show that a combination of the use of social choice functions on aggregated information from expert panels can provide a consensus for ranking priority variables related to road stretches.

Quantitative Structure-Antifungal Activity Relationships for cinnamate derivatives.

Quantitative Structure-Activity Relationships (QSAR) are established with the aim of analyzing the fungicidal activities of a set of 27 active cinnamate derivatives. The exploration of more than a thousand of constitutional, topological, geometrical and electronic molecular descriptors, which are calculated with Dragon software, leads to predictions of the growth inhibition on Pythium sp and Corticium rolfsii fungi species, in close agreement to the experimental values extracted from the literature. A set containing 21 new structurally related cinnamate compounds is prepared. The developed QSAR models are applied to predict the unknown fungicidal activity of this set, showing that cinnamates like 38, 28 and 42 are expected to be highly active for Pythium sp, while this is also predicted for 28 and 34 in C. rolfsii.