Signalling by senescent melanocytes hyperactivates hair growth.

Niche signals maintain stem cells in a prolonged quiescence or transiently activate them for proper regeneration1. Altering balanced niche signalling can lead to regenerative disorders. Melanocytic skin nevi in human often display excessive hair growth, suggesting hair stem cell hyperactivity. Here, using genetic mouse models of nevi2,3, we show that dermal clusters of senescent melanocytes drive epithelial hair stem cells to exit quiescence and change their transcriptome and composition, potently enhancing hair renewal. Nevus melanocytes activate a distinct secretome, enriched for signalling factors. Osteopontin, the leading nevus signalling factor, is both necessary and sufficient to induce hair growth. Injection of osteopontin or its genetic overexpression is sufficient to induce robust hair growth in mice, whereas germline and conditional deletions of either osteopontin or CD44, its cognate receptor on epithelial hair cells, rescue enhanced hair growth induced by dermal nevus melanocytes. Osteopontin is overexpressed in human hairy nevi, and it stimulates new growth of human hair follicles. Although broad accumulation of senescent cells, such as upon ageing or genotoxic stress, is detrimental for the regenerative capacity of tissue4, we show that signalling by senescent cell clusters can potently enhance the activity of adjacent intact stem cells and stimulate tissue renewal. This finding identifies senescent cells and their secretome as an attractive therapeutic target in regenerative disorders.

Supraclavicular brown adipocytes originate from Tbx1+ myoprogenitors.

Brown adipose tissue (BAT) dissipates energy as heat, contributing to temperature control, energy expenditure, and systemic homeostasis. In adult humans, BAT mainly exists in supraclavicular areas and its prevalence is associated with cardiometabolic health. However, the developmental origin of supraclavicular BAT remains unknown. Here, using genetic cell marking in mice, we demonstrate that supraclavicular brown adipocytes do not develop from the Pax3+/Myf5+ epaxial dermomyotome that gives rise to interscapular BAT (iBAT). Instead, the Tbx1+ lineage that specifies the pharyngeal mesoderm marks the majority of supraclavicular brown adipocytes. Tbx1Cre-mediated ablation of peroxisome proliferator-activated receptor gamma (PPARγ) or PR/SET Domain 16 (PRDM16), components of the transcriptional complex for brown fat determination, leads to supraclavicular BAT paucity or dysfunction, thus rendering mice more sensitive to cold exposure. Moreover, human deep neck BAT expresses higher levels of the TBX1 gene than subcutaneous neck white adipocytes. Taken together, our observations reveal location-specific developmental origins of BAT depots and call attention to Tbx1+ lineage cells when investigating human relevant supraclavicular BAT.

Accelerated discovery of CO2 electrocatalysts using active machine learning.

The rapid increase in global energy demand and the need to replace carbon dioxide (CO2)-emitting fossil fuels with renewable sources have driven interest in chemical storage of intermittent solar and wind energy1,2. Particularly attractive is the electrochemical reduction of CO2 to chemical feedstocks, which uses both CO2 and renewable energy3-8. Copper has been the predominant electrocatalyst for this reaction when aiming for more valuable multi-carbon products9-16, and process improvements have been particularly notable when targeting ethylene. However, the energy efficiency and productivity (current density) achieved so far still fall below the values required to produce ethylene at cost-competitive prices. Here we describe Cu-Al electrocatalysts, identified using density functional theory calculations in combination with active machine learning, that efficiently reduce CO2 to ethylene with the highest Faradaic efficiency reported so far. This Faradaic efficiency of over 80 per cent (compared to about 66 per cent for pure Cu) is achieved at a current density of 400 milliamperes per square centimetre (at 1.5 volts versus a reversible hydrogen electrode) and a cathodic-side (half-cell) ethylene power conversion efficiency of 55 ± 2 per cent at 150 milliamperes per square centimetre. We perform computational studies that suggest that the Cu-Al alloys provide multiple sites and surface orientations with near-optimal CO binding for both efficient and selective CO2 reduction17. Furthermore, in situ X-ray absorption measurements reveal that Cu and Al enable a favourable Cu coordination environment that enhances C-C dimerization. These findings illustrate the value of computation and machine learning in guiding the experimental exploration of multi-metallic systems that go beyond the limitations of conventional single-metal electrocatalysts.

Are parental condition transfer effects more widespread than is currently appreciated?

It has long been recognized that the environment experienced by parents can influence the traits of offspring (i.e. 'parental effects'). Much research has explored whether mothers respond to predictable shifts in environmental signals by modifying offspring phenotypes to best match future conditions. Many organisms experience conditions that theory predicts should favor the evolution of such 'anticipatory parental effects', but such predictions have received limited empirical support. 'Condition transfer effects' are an alternative to anticipatory effects that occur when the environment experienced by parents during development influences offspring fitness. Condition transfer effects occur when parents that experience high-quality conditions produce offspring that exhibit higher fitness irrespective of the environmental conditions in the offspring generation. Condition transfer effects are not driven by external signals but are instead a byproduct of past environmental quality. They are also likely adaptive but have received far less attention than anticipatory effects. Here, we review the generality of condition transfer effects and show that they are much more widespread than is currently appreciated. Condition transfer effects are observed across taxa and are commonly associated with experimental manipulations of resource conditions experienced by parents. Our Review calls for increased research into condition transfer effects when considering the role of parental effects in ecology and evolution.

Post-radiotherapy stage III/IV non-small cell lung cancer radiomics research: a systematic review and comparison of CLEAR and RQS frameworks.

BACKGROUND: Lung cancer, the second most common cancer, presents persistently dismal prognoses. Radiomics, a promising field, aims to provide novel imaging biomarkers to improve outcomes. However, clinical translation faces reproducibility challenges, despite efforts to address them with quality scoring tools. OBJECTIVE: This study had two objectives: 1) identify radiomics biomarkers in post-radiotherapy stage III/IV nonsmall cell lung cancer (NSCLC) patients, 2) evaluate research quality using the CLEAR (CheckList_for_EvaluAtion_of_Radiomics_research), RQS (Radiomics_Quality_Score) frameworks, and formulate an amalgamated CLEAR-RQS tool to enhance scientific rigor. MATERIALS AND METHODS: A systematic literature review (Jun-Aug 2023, MEDLINE/PubMed/SCOPUS) was conducted concerning stage III/IV NSCLC, radiotherapy, and radiomic features (RF). Extracted data included study design particulars, such as sample size, radiotherapy/CT technique, selected RFs, and endpoints. CLEAR and RQS were merged into a CLEAR-RQS checklist. Three readers appraised articles utilizing CLEAR, RQS, and CLEAR-RQS metrics. RESULTS: Out of 871 articles, 11 met the inclusion/exclusion criteria. The Median cohort size was 91 (range: 10-337) with 9 studies being single-center. No common RF were identified. The merged CLEAR-RQS checklist comprised 61 items. Most unreported items were within CLEAR's "methods" and "open-source," and within RQS's "phantom-calibration," "registry-enrolled prospective-trial-design," and "cost-effective-analysis" sections. No study scored above 50% on RQS. Median CLEAR scores were 55.74% (32.33/58 points), and for RQS, 17.59% (6.3/36 points). CLEAR-RQS article ranking fell between CLEAR and RQS and aligned with CLEAR. CONCLUSION: Radiomics research in post-radiotherapy stage III/IV NSCLC exhibits variability and frequently low-quality reporting. The formulated CLEAR-RQS checklist may facilitate education and holds promise for enhancing radiomics research quality. CLINICAL RELEVANCE STATEMENT: Current radiomics research in the field of stage III/IV postradiotherapy NSCLC is heterogenous, lacking reproducibility, with no identified imaging biomarker. Radiomics research quality assessment tools may enhance scientific rigor and thereby facilitate radiomics translation into clinical practice. KEY POINTS: There is heterogenous and low radiomics research quality in postradiotherapy stage III/IV nonsmall cell lung cancer. Barriers to reproducibility are small cohort size, nonvalidated studies, missing technical parameters, and lack of data, code, and model sharing. CLEAR (CheckList_for_EvaluAtion_of_Radiomics_research), RQS (Radiomics_Quality_Score), and the amalgamated CLEAR-RQS tool are useful frameworks for assessing radiomics research quality and may provide a valuable resource for educational purposes in the field of radiomics.

A TrkB and TrkC partial agonist restores deficits in synaptic function and promotes activity-dependent synaptic and microglial transcriptomic changes in a late-stage Alzheimer's mouse model.

INTRODUCTION: Tropomyosin related kinase B (TrkB) and C (TrkC) receptor signaling promotes synaptic plasticity and interacts with pathways affected by amyloid beta (Aß) toxicity. Upregulating TrkB/C signaling could reduce Alzheimer's disease (AD)-related degenerative signaling, memory loss, and synaptic dysfunction. METHODS: PTX-BD10-2 (BD10-2), a small molecule TrkB/C receptor partial agonist, was orally administered to aged London/Swedish-APP mutant mice (APPL/S) and wild-type controls. Effects on memory and hippocampal long-term potentiation (LTP) were assessed using electrophysiology, behavioral studies, immunoblotting, immunofluorescence staining, and RNA sequencing. RESULTS: In APPL/S mice, BD10-2 treatment improved memory and LTP deficits. This was accompanied by normalized phosphorylation of protein kinase B (Akt), calcium-calmodulin-dependent kinase II (CaMKII), and AMPA-type glutamate receptors containing the subunit GluA1; enhanced activity-dependent recruitment of synaptic proteins; and increased excitatory synapse number. BD10-2 also had potentially favorable effects on LTP-dependent complement pathway and synaptic gene transcription. DISCUSSION: BD10-2 prevented APPL/S/Aß-associated memory and LTP deficits, reduced abnormalities in synapse-related signaling and activity-dependent transcription of synaptic genes, and bolstered transcriptional changes associated with microglial immune response. HIGHLIGHTS: Small molecule modulation of tropomyosin related kinase B (TrkB) and C (TrkC) restores long-term potentiation (LTP) and behavior in an Alzheimer's disease (AD) model. Modulation of TrkB and TrkC regulates synaptic activity-dependent transcription. TrkB and TrkC receptors are candidate targets for translational therapeutics. Electrophysiology combined with transcriptomics elucidates synaptic restoration. LTP identifies neuron and microglia AD-relevant human-mouse co-expression modules.

Heterocyclic Merging of Stereochemically Diverse Chiral Piperazines and Morpholines with Indazoles.

We report a heterocyclic merging approach to construct novel indazolo-piperazines and indazolo-morpholines. Starting from chiral diamines and amino alcohols, novel regiochemically (1,3 and 1,4) and stereochemically diverse (relative and absolute) cohorts of indazolo-piperazines and indazolo-morpholines were obtained within six or seven steps. The key transformations involved are a Smiles rearrangement to generate the indazole core structure and a late-stage Michael addition to build the piperazine and morpholine heterocycles. We further explored additional vector diversity by incorporating substitutions on the indazole aromatic ring, generating a total of 20 unique, enantiomerically pure heterocyclic scaffolds.

Para-conduit diaphragmatic hernia following esophagectomy-the new price of minimally invasive surgery?

Esophageal Cancer is the seventh commonest cancer worldwide with poor overall survival. Significant morbidity related to open esophagectomy has driven practice toward hybrid, totally minimally invasive and robotic procedures. With the increase in minimally invasive approaches, it has been suggested that there might be an increased incidence of subsequent para-conduit diaphragmatic hernia. To assess the incidence, modifiable risk factors and association with operative approach of this emerging complication, we evaluated outcomes following esophagectomy from two Australian Centers. Prospectively collected databases were examined to identify patients who developed versus did not develop a para-conduit hernia. Patient characteristics, disease factors, treatment factors, operative and post-operative factors were compared for these two groups. A total of 24 of 297 patients who underwent esophagectomy were diagnosed with a symptomatic para-conduit diaphragmatic hernia (8.1%). The significant risk factor for hernia was a minimally invasive abdominal approach (70.8% vs. 35.5%; P = 0.004, odds ratio = 12.876, 95% CI 2.214-74.89). Minimally invasive thoracic approaches were not associated with increased risk. Minimally invasive abdominal approaches to esophagectomy doubled the risk of developing a para-conduit diaphragmatic hernia. Effective operative solutions to address this complication are required.

Pre-analytical effects on whole transcriptome and targeted RNA sequencing analysis in cytology: The effects of prolonged time in storage of effusion specimens prior to preservation.

OBJECTIVES: To investigate the pre-analytics of the molecular testing of cytology specimens, we studied the effects of time in refrigerator storage (4°C) of malignant effusions on RNA sequencing (RNAseq) results. METHODS: Ten effusion specimens were stored in a refrigerator (4°C) for different durations (day 0, 1, 4, and 7). All specimens were prepared as cytospins fixed in either Carnoy's solution or 95% ethanol (EtOH) and in an RNA preservative for a fresh frozen (FF) high-quality reference. Whole transcriptome (wt) and targeted (t)RNAseq of two multigene expression signatures were performed. We then compared transcript expression levels (including mutant allele fraction) according to pre-analytical variables using a concordance correlation coefficient (CCC) and a mixed effect model. RESULTS: Sequencing results were mostly stable over increasing time in storage. Cytospins fixed in Carnoy's solution were more concordant with FF samples than cytospins fixed in 95% EtOH at all timepoints. This finding was consistent for both wtRNAseq (averages: day 0 CCC = 0.98 vs 0.91; day 7 CCC = 0.88 vs 0.78) and tRNAseq methods (averages: day 0 CCC = 0.98 vs 0.81; day 7 CCC = 0.98 vs 0.90). Cytospins fixed in Carnoy's solution did not show significant changes in expression over timepoints or between expression signatures, whereas 95% EtOH did. CONCLUSION: RNAseq can be accurately performed on effusion specimens after prolonged refrigerator storage. RNA extracted from scraped cytospin slides fixed in Carnoy's solution was marginally superior to 95% EtOH fixation, but either method had comparable analytic performance to high-quality FF RNA samples.

The Impact of Race and Ethnicity on Use of Minimally Invasive Surgery for Myomas.

STUDY OBJECTIVE: To determine whether minimally invasive surgery (MIS) for uterine myomas is used differentially based on race and ethnicity. DESIGN: Retrospective cohort study. SETTING: Quaternary care academic hospital in the United States. PATIENTS: Patients undergoing hysterectomy or myomectomy for uterine myomas between March 15, 2015, and March 14, 2020 (N = 1311). Cases involving correction of pelvic organ prolapse, malignancy, peripartum hysterectomy, or combined procedures with nongynecologic specialties were excluded. Racial/ethnic composition of the study population was 40.0% non-Hispanic white (white), 27.9% non-Hispanic black (black), 14.0% Hispanic, 13.7% non-Hispanic Asian (Asian), and 4.3% non-Hispanic American Indian/Alaska Native/Pacific Islander/Other. INTERVENTIONS: Hysterectomy, myomectomy. MEASUREMENTS AND MAIN RESULTS: Of the 1311 cases, 35.9% were minimally invasive hysterectomy, 16.4% abdominal hysterectomy, 35.6% minimally invasive myomectomy, and 12.1% abdominal myomectomy. MIS rates were 94.7% among fellowship-trained minimally invasive gynecologic surgery subspecialists, 44.2% among obstetrics and gynecology specialists, and 46.8% among gynecologic oncologists. There were disparities in surgeon type based on race/ethnicity, with 59.8% of white patients having undergone surgery with a minimally invasive gynecologic surgery subspecialist vs 44.0% of black patients and 45.7% of Hispanic patients. Black and Hispanic patients were less likely to undergo MIS overall vs white patients (adjusted odds ratio [aOR] 0.33, 95% confidence interval [CI] 0.22-0.48 and aOR 0.44, 95% CI 0.28-0.72, respectively). Black and Hispanic patients undergoing hysterectomy were less likely than white patients to undergo MIS (aOR 0.33, 95% CI 0.21-0.51 and aOR 0.35, 95% CI 0.20-0.60, respectively). There were no significant differences in rates of MIS based on race/ethnicity for myomectomies nor differences in major or minor complications by race/ethnicity overall. CONCLUSION: At a quaternary care institution, black and Hispanic patients were significantly less likely than white patients to undergo MIS for uterine myomas, particularly for hysterectomy.

A Concise Synthetic Method for Constructing 3-Substituted Piperazine-2-Acetic Acid Esters from 1,2-Diamines.

We report a short synthetic route for synthesizing 2,3-substituted piperazine acetic acid esters. Optically pure amino acids were efficiently converted into 1,2-diamines that could be utilized to deliver the title 2,3-substituted piperazines in five steps with a high enantiomeric purity. The novel route facilitated, for the first time, the synthesis of 3-phenyl substituted-2-piperazine acetic acid esters that were difficult to achieve using other methods; however, in this case, the products underwent racemization.

IL-37-induced activation of glycogen synthase kinase 3ß promotes IL-1R8/Sigirr phosphorylation, internalization, and degradation in lung epithelial cells.

Interleukin (IL)-37 diminishes a variety of inflammatory responses through ligation to its receptor IL-1R8/Sigirr. Sigirr is a Toll like receptor/IL-1R family member. We have shown that Sigirr is not stable in response to IL-37 treatment. IL-37-induced Sigirr degradation is mediated by the ubiquitin-proteasome system, and the process is reversed by a deubiquitinase, USP13. However, the molecular mechanisms by which USP13 regulates Sigirr stability have not been revealed. In this study, we investigate the roles of glycogen synthesis kinase 3ß (GSK3ß) in Sigirr phosphorylation and stability. IL-37 stimulation induced Sigirr phosphorylation and degradation, as well as activation of GSK3ß. Inhibition of GSK3ß attenuated IL-37-induced Sigirr phosphorylation, while exogenous expressed GSK3ß promoted Sigirr phosphorylation at threonine (T)372 residue. Sigirr association with GSK3ß was detected. Amino acid residues 51-101 in GSK3ß were identified as the Sigirr binding domain. These data indicate that GSK3ß mediates IL-37-induced threonine phosphorylation of Sigirr. Further, we investigated the role of GSK3ß-mediated phosphorylation of Sigirr in Sigirr degradation. Inhibition of GSK3ß attenuated IL-37-induced Sigirr degradation, while T372 mutant of Sigirr was resistant to IL-37-mediated degradation. Furthermore, inhibition of Sigirr phosphorylation prevented Sigirr internalization and association with USP13, suggesting GSK3ß promotes Sigirr degradation through disrupting Sigirr association with USP13.

SCF FBXW17 E3 ubiquitin ligase regulates FBXL19 stability and cell migration.

The Skp1-Cul1-F-box protein (SCF) E3 ligase complex is one of the largest ubiquitin E3 ligase families. FBXL19, a F-box protein in SCFFBXL19 E3 ligase complex, regulates a variety of cellular responses including cell migration. We have shown that FBXL19 is not stable and its degradation is mediated by the ubiquitin-proteasome system, while the ubiquitin E3 ligase for FBXL19 ubiquitination and degradation has not been identified. In the study, we discovered that a new ubiquitin E3 ligase, SCFFBXW17 , ubiquitinates and induces FBXL19 degradation. Exogenous FBXW17 targets FBXL19 for its ubiquitination and degradation. Lysine 114 in FBXL19 is a potential ubiquitin acceptor site. Acetylation of FBXL19 attenuated SCFFBXW17 -mediated FBXL19 degradation. SCFFBXL19 E3 ligase reduced Rac1 levels and cell migration, while the effects were attenuated by exogenous FBXW17. Downregulation of FBXW17 attenuated lysophosphatidic acid-induced lamellipodia formation and Rac1 accumulation at migration leading edge. Taken together with our previous studies, FBXL19 is degraded by the ubiquitin-proteasome system and its site-specific ubiquitination is mediated by SCFFBXW17 E3 ligase, which promotes cell migration.

Design and construction of a stereochemically diverse piperazine-based DNA-encoded chemical library.

Here we report the successful construction of a novel, stereochemically diverse DNA-Encoded Chemical Library (DECL) by utilizing 24 enantiomerically pure trifunctional 2, 6- di-substituted piperazines as central cores. We introduce the concept of positional diversity by placing the DNA attachment at either of two possible sites on the piperazine scaffold. Using a wide range of building blocks, a diverse library of 77 million compounds was produced. Cheminformatic analysis demonstrates that this library occupies a wide swath of chemical space, and that the piperazine scaffolds confers different shape diversity compared to the commonly used triazine core.

Computational catalyst discovery: Active classification through myopic multiscale sampling.

The recent boom in computational chemistry has enabled several projects aimed at discovering useful materials or catalysts. We acknowledge and address two recurring issues in the field of computational catalyst discovery. First, calculating macro-scale catalyst properties is not straightforward when using ensembles of atomic-scale calculations [e.g., density functional theory (DFT)]. We attempt to address this issue by creating a multi-scale model that estimates bulk catalyst activity using adsorption energy predictions from both DFT and machine learning models. The second issue is that many catalyst discovery efforts seek to optimize catalyst properties, but optimization is an inherently exploitative objective that is in tension with the explorative nature of early-stage discovery projects. In other words, why invest so much time finding a "best" catalyst when it is likely to fail for some other, unforeseen problem? We address this issue by relaxing the catalyst discovery goal into a classification problem: "What is the set of catalysts that is worth testing experimentally?" Here, we present a catalyst discovery method called myopic multiscale sampling, which combines multiscale modeling with automated selection of DFT calculations. It is an active classification strategy that seeks to classify catalysts as "worth investigating" or "not worth investigating" experimentally. Our results show an ∼7-16 times speedup in catalyst classification relative to random sampling. These results were based on offline simulations of our algorithm on two different datasets: a larger, synthesized dataset and a smaller, real dataset.

Simulation of operating room crisis management - hypotension training for pre-clinical students.

BACKGROUND: Simulation training is an essential criterion for medical staff. The majority of residents are trained in operating room crisis management (ORCM), but only a few pre-clinical anesthesia undergraduate students are trained. Anesthesia methodology and technology were studied by the anesthesia undergraduate students in theory, but they were not able to practically resolve all clinical problems scientifically and reasonably. Consequently, there is a need to apply their competencies and bring together their technology knowledge practically. The crisis management of operating room emergencies was a method of choice applied and used over time. Here, we designed the scenarios for comprehensive crisis management to train anesthesia undergraduate students. We tried to establish or identify the problems which occurred during attempts to implement these scenarios. METHODS: Anesthesia undergraduate students initially examined the basic theory, fundamental practice techniques, and case studies before the simulation training program. Subsequently, they participated in comprehensive ORCM training. Training outcomes were evaluated through different viewpoints: understanding the subject, crisis management, nontechnical skills, and a user experience evaluation. RESULTS: Anesthesia undergraduate students performed significantly better with completion of ORCM, indicated by higher scores in all four tests (P < 0.001), as well as clinical crisis management (P = 0.0016) and nontechnical skills (P = 0.0002). Following the simulation, the students described the experience as helpful in "combining theoretical knowledge with clinical practice", helpful with memorization, and in "promoting understanding of the subject," while "learning clinical logic authentically" and "inspiring learning interests." CONCLUSIONS: This research indicates that ORCM could be implemented as a useful learning tool for pre-clinical anesthesia undergraduate students. The ORCM could be an excellent training method to help improve students' professional competence in crisis management and nontechnical skills, integrating the knowledge and technology of the field of anesthesiology.

Prospective Molecular Profiling of Circulating Tumor Cells from Patients with Melanoma Receiving Combinatorial Immunotherapy.

BACKGROUND: Blood molecular profiling of circulating tumor cells (CTCs) can enable monitoring of patients with metastatic melanoma during checkpoint inhibitor immunotherapy (CII) and in combination with targeted therapies. We developed a microfluidics-based CTC platform to explore CTC profiling utility in CII-treated patients with melanoma using a melanoma messenger RNA (mRNA)/DNA biomarker panel. METHODS: Blood samples (n = 213) were collected prospectively from 75 American Joint Committee on Cancer-staged III/IV melanoma patients during CII treatment and those enriched for CTCs. CTC profiling was performed using 5 known melanoma mRNA biomarkers and BRAF V600E DNA mutation. CTC biomarker status associations with clinical outcomes were assessed. RESULTS: CTCs were detected in 88% of blood samples from patients with melanoma. CTC-derived biomarkers and clinical variables analyzed using classification and regression tree analysis revealed that a combination of lactate dehydrogenase, CTC-mRNA biomarkers, and tumor BRAF-mutation status was indicative of clinical outcomes for patients with stage IV melanoma (n = 52). The panel stratified low-risk and high-risk patients, whereby the latter had poor disease-free (P = 0.03) and overall survival (P = 0.02). Incorporation of a DNA biomarker with mRNA profiling increased overall CTC-detection capability by 57% compared to mRNA profiling only. RNA sequencing of isolated CTCs identified significant catenin beta 1 (CTNNB1) overexpression (P <0.01) compared to nondisease donor blood. CTC-CTNNB1 was associated with progressive disease/stable disease compared to complete-responder patient status (P = 0.02). Serial CTC profiling identified subclinical disease in patients who developed progressive disease during treatment/follow-up. CONCLUSIONS: CTC-derived mRNA/DNA biomarkers have utility for monitoring CII, targeted, and combinatorial therapies in metastatic melanoma patients.

In silico discovery of active, stable, CO-tolerant and cost-effective electrocatalysts for hydrogen evolution and oxidation.

Various databases of density functional theory (DFT) calculations for materials and adsorption properties are currently available. Using the Materials Project and GASpy databases of material stability and binding energies (H* and CO*), respectively, we evaluate multiple aspects of catalysts to discover active, stable, CO-tolerant, and cost-effective hydrogen evolution and oxidation catalysts. Finally, we suggest a few candidate materials for future experimental validations. We highlight that the stability analysis is easily obtainable but provides invaluable information to assess thermodynamic and electrochemical stability, bridging the gap between simulations and experiments. Furthermore, it reduces the number of expensive DFT calculations required to predict catalytic activities of surfaces by filtering out unstable materials.

Correction: Functional Constraint Profiling of a Viral Protein Reveals Discordance of Evolutionary Conservation and Functionality.

[This corrects the article DOI: 10.1371/journal.pgen.1005310.].

Toward Predicting Intermetallics Surface Properties with High-Throughput DFT and Convolutional Neural Networks.

The surface energy of inorganic crystals is important in understanding experimentally relevant surface properties and designing materials for many applications. Predictive methods and data sets exist for surface energies of monometallic crystals. However, predicting these properties for bimetallic or more complicated surfaces is an open challenge. Computing cleavage energy is the first step in calculating surface energy across a large space. Here, we present a workflow to predict cleavage energies ab initio using high-throughput DFT and a machine learning framework. We calculated the cleavage energy of 3033 intermetallic alloys with combinations of 36 elements and 47 space groups. This high-throughput workflow was used to seed a database of cleavage energies. The database was used to train a crystal graph convolutional neural network (CGCNN). The CGCNN model provides an accurate prediction of cleavage energy with a mean absolute test error of 0.0071 eV/Å2. It can also qualitatively reproduce nanoparticle surface distributions (Wulff constructions). Our workflow provides quantitative insights into unexplored chemical space by predicting which surfaces are relatively stable and therefore more realistic. The insights allow us to down-select interesting candidates that we can study with robust theoretical and experimental methods for applications such as catalyst screening and nanomaterials synthesis.