Osteocalcin binds to a GPRC6A Venus fly trap allosteric site to positively modulate GPRC6A signaling.

GPRC6A, a member of the Family C G-protein coupled receptors, regulates energy metabolism and sex hormone production and is activated by diverse ligands, including cations, L-amino acids, the osteocalcin (Ocn) peptide and the steroid hormone testosterone. We sought a structural framework for the ability of multiple distinct classes of ligands to active GPRC6A. We created a structural model of GPRC6A using Alphafold2. Using this model we explored a putative orthosteric ligand binding site in the bilobed Venus fly trap (VFT) domain of GPRC6A and two positive allosteric modulator (PAM) sites, one in the VFT and the other in the 7 transmembrane (7TM) domain. We provide evidence that Ocn peptides act as a PAM for GPRC6A by binding to a site in the VFT that is distinct from the orthosteric site for calcium and L-amino acids. In agreement with this prediction, alternatively spliced GPRC6A isoforms 2 and 3, which lack regions of the VFT, and mutations in the computationally predicted Ocn binding site, K352E and H355P, prevent Ocn activation of GPRC6A. These observations explain how dissimilar ligands activate GPRC6A and set the stage to develop novel molecules to activate and inhibit this previously poorly understood receptor.

GPRC6A is a Potential Therapeutic Target for Metformin Regulation of Glucose Homeostasis in Mice.

Understanding the mechanism of metformin actions in treating type 2 diabetes is limited by an incomplete knowledge of the specific protein targets mediating its metabolic effects. Metformin has structural similarities to L-Arginine (2-amino-5-guanidinopentanoic acid), which is a ligand for GPRC6A, a Family C G-protein coupled receptor that regulates energy metabolism. Ligand activation of GPRC6A results in lowering of blood glucose and other metabolic changes resembling the therapeutic effect of metformin. In the current study, we tested if metformin activates GPRC6A. We used Alphafold2 to develop a structural model for L-Arginine (L-Arg) binding to the extracellu-lar bilobed venus flytrap domain (VFT) of GPRC6A. We found that metformin docked to the site in the VFT that overlaps the binding site for L-Arg. Metformin resulted in a dose-dependent stimulation of GPRC6A activity in HEK-293 cells transfected with full-length wild-type GPRC6A but not in untransfected control cells. In addition, metformin failed to activate an alternatively spliced GPRC6A isoform lacking the putative binding site in the VFT. More specifically, mutation of the predicted metformin key binding residues Glu170 and Asp303 in the GPRC6A VFT resulted in loss of metformin receptor activation in vitro. The in vivo role of GPRC6A in mediating the effects of metformin was tested in Gprc6a-/- mice. Administration of therapeutic doses of metformin lowered blood glucose levels following a glucose tolerance test in wild-type but not Gprc6a-/- mice. Finally, we EN300, created by adding a carboxymethyl group from L-Arg to the biguanide backbone of metformin. EN300 showed dose-dependent stimulation of GPRC6A activity in vitro with greater potency than L-Arginine, but less than metformin. Thus, we suggest that GPRC6A is a potential molecular target for metformin which may be used to understand the therapeutic actions of metformin and develop novel small molecules to treat T2D.

Reduced voluntary wheel running behaviour in Kiss1r knockout mice.

Kisspeptin and its receptor, Kiss1r, are novel players in the central balance of energy intake and expenditure. Recent evidence also indicates that kisspeptin signalling is important in thermoregulation and generation of the circadian rhythm. We used global Kiss1r knockout mice (Kiss1r KO), which are hypogonadal and develop obesity, to determine the impact of kisspeptin on circadian related behaviour. Voluntary wheel running was examined in Kiss1r KO and wild-type (WT) mice, using gonad intact and gonadectomised (GDX) mice to account for the effects of kisspeptin on gonadal sex steroids. Intact male and female Kiss1r KO mice covered only 10% and 30% of the distance travelled each day by their respective WT controls. In all mice, most of the running activity occurred during the dark phase. GDX WT mice ran significantly less during dark periods than the intact WT. GDX Kiss1r KO male mice ran significantly less than the GDX WT male mice, but the decrease was attenuated compared to intact mice. There was no difference between the female GDX Kiss1r KO and GDX WT. In contrast to the obese phenotype that develops in Kiss1r KO mice, body mass at the end of the study was significantly lower in the GDX Kiss1r KO than it was in the GDX WT mice. The difference in wheel running activity was not associated with any histological change in WAT, BAT, or muscle diameter. No difference in immunohistochemistry expression was seen in lateral hypothalamic orexin neurons or dopamine neurons in the ventral tegmental area / substantia nigra. We observed increased Iba1 expression (activation of microglia) in the arcuate nucleus of male Kiss1r KO mice. Overall, the circadian locomotor activity in male Kiss1r KO mice appears dependant on kisspeptin signalling and the obese phenotype does not develop in Kiss1r KO mice when they engage in voluntary activity.

A Transient Iron Carbide Generated by Cyaphide Cleavage.

Despite their potential relevance as molecular models for industrial and biological catalysis, well-defined mononuclear iron carbide complexes are unknown, in part due to the limited number of appropriate C1 synthons. Here, we show the ability of the cyaphide anion (C≡P-) to serve as a C1 source. The high spin (S = 2) cyaphide complex PhB(tBuIm)3Fe-C≡P (PhB(tBuIm)3- = phenyl(tris(3-tert-butylimidazol-2-ylidene)borate) is readily accessed using the new cyaphide transfer reagent [Mg(DippNacNac)(CP)]2 (DippNacNac = CH{C(CH3)N(Dipp)}2 and Dipp = 2,6-di(iso-propyl)phenyl). Phosphorus atom abstraction is effected by the three-coordinate Mo(III) complex Mo(NtBuAr)3 (Ar = 3,5-Me2C6H3), which produces the known phosphide (tBuArN)3Mo≡P along with a transient iron carbide complex PhB(tBuIm)3Fe≡C. Electronic structure calculations reveal that PhB(tBuIm)3Fe≡C adopts a doublet ground state with nonzero spin density on the carbide ligand. While isolation of this complex is thwarted by rapid dimerization to afford the corresponding diiron ethynediyl complex, the carbide can be intercepted by styrene to provide an iron alkylidene.

TCR-H: explainable machine learning prediction of T-cell receptor epitope binding on unseen datasets.

Artificial-intelligence and machine-learning (AI/ML) approaches to predicting T-cell receptor (TCR)-epitope specificity achieve high performance metrics on test datasets which include sequences that are also part of the training set but fail to generalize to test sets consisting of epitopes and TCRs that are absent from the training set, i.e., are 'unseen' during training of the ML model. We present TCR-H, a supervised classification Support Vector Machines model using physicochemical features trained on the largest dataset available to date using only experimentally validated non-binders as negative datapoints. TCR-H exhibits an area under the curve of the receiver-operator characteristic (AUC of ROC) of 0.87 for epitope 'hard splitting' (i.e., on test sets with all epitopes unseen during ML training), 0.92 for TCR hard splitting and 0.89 for 'strict splitting' in which neither the epitopes nor the TCRs in the test set are seen in the training data. Furthermore, we employ the SHAP (Shapley additive explanations) eXplainable AI (XAI) method for post hoc interrogation to interpret the models trained with different hard splits, shedding light on the key physiochemical features driving model predictions. TCR-H thus represents a significant step towards general applicability and explainability of epitope:TCR specificity prediction.

Agar lot-specific inhibition in the plating efficiency of yeast spores and cells.

The fission yeast Schizosaccharomyces pombe and the budding yeast Saccharomyces cerevisiae are highly diverged (530 mya), single-celled, model eukaryotic organisms. Scientists employ mating, meiosis, and the plating of ascospores and cells to generate strains with novel genotypes and to discover biological processes. Our three laboratories encountered independently sudden-onset, major impediments to such research. Spore suspensions and vegetative cells no longer plated effectively on minimal media. By systematically analyzing multiple different media components from multiple different suppliers, we identified the source of the problem. Specific lots of agar were toxic. We report that this sporadic toxicity affects independently the agar stocks of multiple vendors, has occurred repeatedly over at least three decades, and extends to species in highly diverged taxa. Interestingly, the inhibitory effects displayed variable penetrance and were attenuated on rich media. Consequently, quality control checks that use only rich media can provide false assurances on the quality of the agar. Lastly, we describe likely sources of the toxicity and we provide specific guidance for quality control measures that should be applied by all vendors as preconditions for their sale of agar.

Molecular-level design of alternative media for energy-saving pilot-scale fibrillation of nanocellulose.

The outstanding mechanical properties, light weight, and biodegradability of cellulose nanofibrils (CNFs) make them promising components of renewable and sustainable next-generation reinforced composite biomaterials and bioplastics. Manufacturing CNFs at a pilot scale requires disc-refining fibrillation of dilute cellulose fibers in aqueous pulp suspensions to shear the fibers apart into their nanodimensional forms, which is, however, an energy-intensive process. Here, we used atomistic molecular dynamics (MD) simulation to examine media that might facilitate the reduction of interactions between cellulose fibers, thereby reducing energy consumption in fibrillation. The most suitable medium found by the simulations was an aqueous solution with 0.007:0.012 wt.% NaOH:urea, and indeed this was found in pilot-scale experiments to reduce the fibrillation energy by ~21% on average relative to water alone. The NaOH:urea-mediated CNFs have similar crystallinity, morphology, and mechanical strength to those formed in water. The NaOH and urea act synergistically on CNFs to aid fibrillation but at different length scales. NaOH deprotonates hydroxyl groups leading to mesoscale electrostatic repulsion between fibrils, whereas urea forms hydrogen bonds with protonated hydroxyl groups thus disrupting interfibril hydrogen bonds. This suggests a general mechanism in which an aqueous medium that contains a strong base and a small organic molecule acting as a hydrogen-bond acceptor and/or donor may be effectively employed in materials processes where dispersion of deprotonable polymers is required. The study demonstrates how atomic-detail computer simulation can be integrated with pilot-scale experiments in the rational design of materials processes for the circular bioeconomy.

Management change following transthoracic echocardiogram in the intensive care unit.

Introduction/Purpose: The optimal utilisation of echocardiography in intensive care units (ICU) is not yet known; however, its use is becoming more frequent. Management change from transthoracic echocardiography (TTE) in ICU is quoted to be from 3% to 50%. Methods: A retrospective review of clinical practice was performed over a 2-month period in a tertiary adult ICU, to explore the utilisation of formal TTEs and the findings of these. The rate of management change and critical findings were investigated, along with the indication for TTE and the patient cohort. Results: Sixty-three TTEs were performed in 54 patients. A change in management occurred in 25.4% (16/63) of TTEs, with critical findings being found in 47.6% (30/63) of all TTEs. The most common indications for formal TTEs were incompletely differentiated or further evaluation of shock, and post arrest cardiac function. Discussion: Almost half of the TTEs performed had critical findings, with common critical findings being severe LV dysfunction, severe RV dysfunction and regional wall motion abnormalities. Despite critical findings being seen frequently, there was only management change in 25%, suggesting that several of the critical findings were already suspected, clinically confirmed or had anticipatory management prior to TTE. Conclusion: Critical findings are common in critically ill patients. However, not all critical findings will lead to a change in management. Formal TTEs in the ICU should be focussed to the clinical question being asked and a screening intensivist performed bedside TTE may be appropriate in certain situations to decrease workload of cardiology department.

Enter MnIV-NHC: A Dark Photooxidant with a Long-Lived Charge-Transfer Excited State.

Detailed photophysical investigation of a Mn(IV)-carbene complex has revealed that excitation into its lowest-energy absorption band (∼500 nm) results in the formation of an energetic ligand-to-metal charge-transfer (LMCT) state with a lifetime of 15 ns. To the best of our knowledge, this is the longest lifetime reported for charge-transfer states of first-row-based transition metal complexes in solution, barring those based on Cu, with a d10 configuration. A so-called superoxidant, Mn(IV)-carbene exhibits an excited state potential typically only harnessed via excited states of reactive organic radical species. Furthermore, the long-lived excited state in this case is found to be a dark doublet, with its transition to the quartet ground state being spin-forbidden, a contrast to most first-row literature examples, and a possible cause of the long lifetime. Showcasing excited state properties which in some cases exceed those of complexes based on precious metals, these findings not only advance the library of earth-abundant photosensitizers but also shed general insight into the photophysics of d3 and related Mn complexes.

Emerging Patterns of Foot and Ankle Injuries in Pickleball Players: A Short Report.

BACKGROUND: Pickleball's surging popularity has driven an increase in injuries presenting to medical providers. This study seeks to describe the epidemiology of pickleball foot and ankle injuries including patient demographics, diagnoses, and mechanism of injury. METHODS: A retrospective review from our institutional database identified patients treated in the foot and ankle clinic whose medical records included the search terms "pickleball" and "pickle ball." Only injuries sustained while playing pickleball were included. Patient demographics, diagnosis, mechanism of injury, and treatment were collected. Injury incidence and descriptive analyses were calculated. RESULTS: A total of 198 patients with pickleball foot and ankle injuries were identified. The incidence of injuries increased 6.5-fold from 2019 to 2023. The mean age of patients was 58.3 years (SD = 12.2). Most patients were male (58.6%) and reported a traumatic injury (77.8%). The most common diagnosis was Achilles tendon rupture (39.4%). The most common mechanisms of injury were running or lunging forward (30.9%), planting the foot (16.5%), and inverting the foot and ankle (15.5%). Most injuries were treated nonoperatively (71.2%); however, 62.8% of Achilles tendon ruptures were treated surgically. CONCLUSION: The incidence of pickleball foot and ankle injuries increased dramatically from 2015 to 2023. Injuries occurred more frequently in older, male patients, with Achilles tendon rupture being the most common diagnosis.

Efficiency of Foot and Ankle Surgeries Completed on the Preoperative Stretcher vs Operating Room Table: A Randomized Controlled Trial.

Background: Extremity surgeons frequently operate on the preoperative stretcher rather than the operating room (OR) table. This study sought to identify differences between stretcher-based (SB) and OR table-based (TB) procedures with regard to time efficiency and OR team member preferences. Methods: We conducted a prospective randomized controlled trial comparing the efficiency of SB vs OR TB foot and ankle procedures. Fifty-two patients undergoing a hardware removal, isolated gastrocnemius recession, soft tissue procedure, or foreign body removal at our day surgery unit were included. Start time and exit time were recorded. "Start time" was the number of minutes between the patient entering the OR and first incision. "Exit time" was the number of minutes between the procedure ending and the patient exiting the OR. Surveys were disseminated to OR staff who participated in the included cases. Results: The total measured time in the OR was an average 6 minutes shorter in the Stretcher group compared to the OR Table group (10 minutes vs 16 minutes, P < .001). SB procedures were associated with a significantly shorter start time (median difference = 4 minutes, P = .001), but not exit time (median difference = 1 minute, P = .058). No difference was found in actual surgical time. Thirty (96.8%) OR team members perceived SB procedures as enhancing OR efficiency, and 30 (96.8%) respondents considered SB procedures to be equal or superior to OR TB procedures in terms of patient safety. All would recommend or strongly recommend SB procedures. Conclusion: We found SB foot and ankle procedures to require less room time than OR TB procedures. Particularly for high-volume specialties, an average 6 minutes saved per case may meaningfully improve overall OR efficiency. Most OR team members believed that SB surgery improves OR efficiency and is the safer option for OR team members. Level of Evidence: Level II, randomized controlled trial, survey.

Inclusion of genital, sexual, and gender diversity in human reproductive teaching: impact on student experience and recommendations for tertiary educators.

Western societal norms have long been constrained by binary and exclusionary perspectives on matters such as infertility, contraception, sexual health, sexuality, and gender. These viewpoints have shaped research and knowledge frameworks for decades and led to an inaccurate and incomplete reproductive biology curriculum. To combat these deficiencies in reproductive systems-related education, our teaching team undertook a gradual transformation of unit content from 2018 to 2023, aiming to better reflect real diversity in human reproductive biology. This initiative involved intentional modifications, including clear use of pronoun self-identification by staff. We addressed the historical lack of representation of genital variation and helped students interrogate oversimplified reproductive biology binaries. A novel assignment was also introduced, prompting students to apply reproductive physiology knowledge to propose innovative assisted reproductive technology solutions for diverse demographics. The collective impact of these innovations had a positive effect on student learning. With improved lecture content and inclusive language, the proportion of inclusive group assignment topics chosen by students more than doubled in 2021. By 2022, coinciding with assessment topic changes, the percentage of inclusive assignments topics surpassed 50%. Further development of laboratory activities on intersex genital variation and genital modification raised further understanding of genital, sexual, gender, and cultural diversity. While implementing these changes posed challenges, pushing both staff and students out of their comfort zones at times, collaboration with relevant organizations and individuals with lived experience of queer identity proved integral. Ultimately, these relatively simple adjustments had a substantial impact on student experiences and appreciation for diversity.NEW & NOTEWORTHY We outline the teaching innovations that we have implemented to improve inclusion of diversity in reproductive biology and physiology contexts. This includes improved representation of genital, sexual, and gender diversity considerations in the curriculum. There is a critical need for these innovations as how we teach fundamentally shapes the understanding of our future medical and health professionals and researchers and thus influences the quality of future medical care and research.

Structure-Based Identification of Novel Histone Deacetylase 4 (HDAC4) Inhibitors.

Histone deacetylases (HDACs) are important cancer drug targets. Existing FDA-approved drugs target the catalytic pocket of HDACs, which is conserved across subfamilies (classes) of HDAC. However, engineering specificity is an important goal. Herein, we use molecular modeling approaches to identify and target potential novel pockets specific to Class IIA HDAC-HDAC4 at the interface between HDAC4 and the transcriptional corepressor component protein NCoR. These pockets were screened using an ensemble docking approach combined with consensus scoring to identify compounds with a different binding mechanism than the currently known HDAC modulators. Binding was compared in experimental assays between HDAC4 and HDAC3, which belong to a different family of HDACs. HDAC4 was significantly inhibited by compound 88402 but not HDAC3. Two other compounds (67436 and 134199) had IC50 values in the low micromolar range for both HDACs, which is comparable to the known inhibitor of HDAC4, SAHA (Vorinostat). However, both of these compounds were significantly weaker inhibitors of HDAC3 than SAHA and thus more selective, albeit to a limited extent. Five compounds exhibited activity on human breast carcinoma and/or urothelial carcinoma cell lines. The present result suggests potential mechanistic and chemical approaches for developing selective HDAC4 modulators.

On the Use and Construction of Wi-Fi Fingerprint Databases for Large-Scale Multi-Building and Multi-Floor Indoor Localization: A Case Study of the UJIIndoorLoc Database.

Large-scale multi-building and multi-floor indoor localization has recently been the focus of intense research in indoor localization based on Wi-Fi fingerprinting. Although significant progress has been made in developing indoor localization algorithms, few studies are dedicated to the critical issues of using existing and constructing new Wi-Fi fingerprint databases, especially for large-scale multi-building and multi-floor indoor localization. In this paper, we first identify the challenges in using and constructing Wi-Fi fingerprint databases for large-scale multi-building and multi-floor indoor localization and then provide our recommendations for those challenges based on a case study of the UJIIndoorLoc database, which is the most popular publicly available Wi-Fi fingerprint multi-building and multi-floor database. Through the case study, we investigate its statistical characteristics with a focus on the three aspects of (1) the properties of detected wireless access points, (2) the number, distribution and quality of labels, and (3) the composition of the database records. We then identify potential issues and ways to address them using the UJIIndoorLoc database. Based on the results from the case study, we not only provide valuable insights on the use of existing databases but also give important directions for the design and construction of new databases for large-scale multi-building and multi-floor indoor localization in the future.

Deep Learning and Neural Architecture Search for Optimizing Binary Neural Network Image Super Resolution.

The evolution of super-resolution (SR) technology has seen significant advancements through the adoption of deep learning methods. However, the deployment of such models by resource-constrained devices necessitates models that not only perform efficiently, but also conserve computational resources. Binary neural networks (BNNs) offer a promising solution by minimizing the data precision to binary levels, thus reducing the computational complexity and memory requirements. However, for BNNs, an effective architecture is essential due to their inherent limitations in representing information. Designing such architectures traditionally requires extensive computational resources and time. With the advancement in neural architecture search (NAS), differentiable NAS has emerged as an attractive solution for efficiently crafting network structures. In this paper, we introduce a novel and efficient binary network search method tailored for image super-resolution tasks. We adapt the search space specifically for super resolution to ensure it is optimally suited for the requirements of such tasks. Furthermore, we incorporate Libra Parameter Binarization (Libra-PB) to maximize information retention during forward propagation. Our experimental results demonstrate that the network structures generated by our method require only a third of the parameters, compared to conventional methods, and yet deliver comparable performance.

Coronary and Cerebrovascular Events and Exacerbation of Existing Conditions After Laboratory-Confirmed Influenza Infection Among US Veterans: A Self-Controlled Case Series Study.

BACKGROUND: Influenza may contribute to coronary/cerebrovascular events and exacerbate underlying conditions. METHODS: We used self-controlled case series (SCCS) design to analyze data from US Veterans ≥18 years with coronary/cerebrovascular or exacerbation event +/-1 year of lab-confirmed influenza (LCI) during 2010-2018. We estimated the incidence ratio (IR) (95% CI) of the event for risk interval (Days 1-7 post-LCI) versus control interval (all other times +/-1 year of LCI) with fixed-effects conditional Poisson regression. We included biomarker data for mediation analysis. RESULTS: We identified 3439 episodes with coronary/cerebrovascular-related hospitalizations. IRs (95% CI) for LCI risk versus control interval were STEMI 0.6 (0.1, 4.4), NSTEMI 7.3 (5.8, 9.2), ischemic stroke 4.0 (3.0, 5.4), hemorrhagic stroke 6.2 (3.4, 11.5), and coronary spasm 1.3 (0.5, 3.0). IR significantly increased for NSTEMI and ischemic stroke among those ≥ 65 years. IR for NSTEMI and ischemic stroke dropped 26% and 10%, respectively, when white blood cell (WBC) and platelet count were considered. LCI was significantly associated with exacerbation of preexisting asthma, chronic obstructive pulmonary disease, and congestive heart failure. CONCLUSIONS: We found significant association between LCI and hospitalization for NSTEMI, ischemic stroke, and hemorrhagic stroke, the latter possibly due to unaccounted time-varying confounding in SCCS design.

Trimethylsilyldiazomethane Disassembly at a Three-Fold Symmetric Iron Site.

The reaction of equimolar trimethylsilyldiazomethyllithium (LiTMSD) with high spin (S = 2) PhB(AdIm)3FeCl (PhB(AdIm)3- = tris(3-adamantylimidazol-2-ylidene)phenylborate) affords the corresponding N-nitrilimido complex PhB(AdIm)3Fe-N═N═C(SiMe3). This complex can be converted to the thermodynamically more favorable C-isocyanoamido isomer PhB(AdIm)3Fe-C═N═N(SiMe3) by reaction with an additional equivalent of LiTMSD. While the iron(II) complexes are four-coordinate, the diazomethane is bound side-on in the iron(I) congener PhB(AdIm)3Fe(N,N'-κ2-N2C(H)Si(CH3)3). The latter complex adopts high spin (S = 3/2) ground state and features an unusually weak C-H bond. Photolysis of the iron(II) complexes induces N═N bond cleavage, with the iron(II) cyanide PhB(AdIm)3Fe-C≡N and iron(IV) nitride PhB(AdIm)3Fe≡N complexes being the major products of the reaction. The same products are obtained when the iron(I) complex is photolyzed or treated with a fluoride source. The trimethylsilyldiazomethane-derived ligand disassembly reactions are contrasted with those observed for related tris(carbene)amine complexes.

High-throughput functional mapping of variants in an arrhythmia gene, KCNE1, reveals novel biology.

BACKGROUND: KCNE1 encodes a 129-residue cardiac potassium channel (IKs) subunit. KCNE1 variants are associated with long QT syndrome and atrial fibrillation. However, most variants have insufficient evidence of clinical consequences and thus limited clinical utility. METHODS: In this study, we leveraged the power of variant effect mapping, which couples saturation mutagenesis with high-throughput sequencing, to ascertain the function of thousands of protein-coding KCNE1 variants. RESULTS: We comprehensively assayed KCNE1 variant cell surface expression (2554/2709 possible single-amino-acid variants) and function (2534 variants). Our study identified 470 loss- or partial loss-of-surface expression and 574 loss- or partial loss-of-function variants. Of the 574 loss- or partial loss-of-function variants, 152 (26.5%) had reduced cell surface expression, indicating that most functionally deleterious variants affect channel gating. Nonsense variants at residues 56-104 generally had WT-like trafficking scores but decreased functional scores, indicating that the latter half of the protein is dispensable for protein trafficking but essential for channel function. 22 of the 30 KCNE1 residues (73%) highly intolerant of variation (with > 70% loss-of-function variants) were in predicted close contact with binding partners KCNQ1 or calmodulin. Our functional assay data were consistent with gold standard electrophysiological data (ρ = - 0.64), population and patient cohorts (32/38 presumed benign or pathogenic variants with consistent scores), and computational predictors (ρ = - 0.62). Our data provide moderate-strength evidence for the American College of Medical Genetics/Association of Molecular Pathology functional criteria for benign and pathogenic variants. CONCLUSIONS: Comprehensive variant effect maps of KCNE1 can both provide insight into I Ks channel biology and help reclassify variants of uncertain significance.

Physics-Based Machine Learning Models Predict Carbon Dioxide Solubility in Chemically Reactive Deep Eutectic Solvents.

Carbon dioxide (CO2) is a detrimental greenhouse gas and is the main contributor to global warming. In addressing this environmental challenge, a promising approach emerges through the utilization of deep eutectic solvents (DESs) as an ecofriendly and sustainable medium for effective CO2 capture. Chemically reactive DESs, which form chemical bonds with the CO2, are superior to nonreactive, physically based DESs for CO2 absorption. However, there are no accurate computational models that provide accurate predictions of the CO2 solubility in chemically reactive DESs. Here, we develop machine learning (ML) models to predict the solubility of CO2 in chemically reactive DESs. As training data, we collected 214 data points for the CO2 solubility in 149 different chemically reactive DESs at different temperatures, pressures, and DES molar ratios from published work. The physics-driven input features for the ML models include σ-profile descriptors that quantify the relative probability of a molecular surface segment having a certain screening charge density and were calculated with the first-principle quantum chemical method COSMO-RS. We show here that, although COSMO-RS does not explicitly calculate chemical reaction profiles, the COSMO-RS-derived σ-profile features can be used to predict bond formation. Of the models trained, an artificial neural network (ANN) provides the most accurate CO2 solubility prediction with an average absolute relative deviation of 2.94% on the testing sets. Overall, this work provides ML models that can predict CO2 solubility precisely and thus accelerate the design and application of chemically reactive DESs.