Seek Homogeneous Critical Ice Nucleus at Moderate Supercooling

The quantitative investigation and dynamical understanding of homogeneous nucleation remain a topic of intense research in the interdisciplinary subject. From supercooled water, homogeneous ice nucleation will not happen spontaneously until a critical crystallite nucleus (Nc) pre-exists. In this work, we investigate homogeneous ice nucleation with our molecular dynamics software SPONGE. Using metadynamics and two structural-based collective variables, we successfully improve the sampling technic to grow spherical nuclei with various cubicity and sizes in a 23040-water box. First, we perform the first long-term freezing in all-atom simulation, various nuclei freeze out into Isd. Instead of a certain cluster size based on classical nucleation theory, the dynamic behaviors of ice nuclei experience a wide range of intermediate states. We provide a novel critical nucleus diagram to seek the critical nucleus: the main external factor, surface area, contributes to the freezing speed of the ice nucleus; while the key internal factor, the mean tetrahedral order, controls the melting speed instead. The ice nucleation rates of our work are in good agreement with the former simulation data. We provide a brief frame to discuss the structural details of the nucleation decision

Unsupervisedly Prompting AlphaFold2 for Few-Shot Learning of Accurate Folding Landscape and Protein Structure Prediction

Data-driven predictive methods which can efficiently and accurately transform protein sequences into biologically active structures are highly valuable for scientific research and medical development. Determining accurate folding landscape using co-evolutionary information is fundamental to the success of modern protein structure prediction methods. As the state of the art, AlphaFold2 has dramatically raised the accuracy without performing explicit co-evolutionary analysis. Nevertheless, its performance still shows strong dependence on available sequence homologs. Based on the interrogation on the cause of such dependence, we presented EvoGen, a meta generative model, to remedy the underperformance of AlphaFold2 for poor MSA targets. By prompting the model with calibrated or virtually generated homologue sequences, EvoGen helps AlphaFold2 fold accurately in low-data regime and even achieve encouraging performance with single-sequence predictions. Being able to make accurate predictions with few-shot MSA not only generalizes AlphaFold2 better for orphan sequences, but also democratizes its use for high-throughput applications. Besides, EvoGen combined with AlphaFold2 yields a probabilistic structure generation method which could explore alternative conformations of protein sequences, and the task-aware differentiable algorithm for sequence generation will benefit other related tasks including protein design.Comment: version 2.0; 28 pages, 6 figure

Prognostic Implications of Epidermal Growth Factor Receptor and KRAS Gene Mutations and Epidermal Growth Factor Receptor Gene Copy Numbers in Patients with Surgically Resectable Non-small Cell Lung Cancer in Taiwan

IntroductionThe prognostic role of epidermal growth factor receptor (EGFR) mutations in patients with surgically resectable non-small cell lung cancer (NSCLC) without EGFR tyrosine kinase inhibitor treatment has not been well established, because the reports are still few.Materials and MethodsWe analyzed the survival data of 164 patients with surgically resectable (stages I to IIIA) NSCLC of two year groups (1996–1998 and 2002–2004), and compared with EGFR mutations, KRAS mutations, and EGFR gene copy numbers.ResultsComparing the survival of wild-type patients and patients having L858R mutations or exon 19 deletion, the median survival was much longer for patient with EGFR mutations (54.7 months) than wild type (34.9 months). The difference was not statistically significant by univariate analysis (p = 0.1981) but had borderline significance by multivariate analyses (p = 0.0506). In addition, the 3-year survival rates of patients with EGFR mutations were also significantly higher than wild type (p = 0.0232). After exclusion of 18 patients treated by EGFR-tyrosine kinase inhibitor for tumor recurrence, the trends were still the same. Patients with KRAS mutations had shorter median survival (21 months) than wild type (44.4 months). Patients with EGFR polysomy (≧copies) also had longer median survival (56.2 months) than wild type (53.4 months). But the survival differences of these two genetic markers were all not significant statistically.ConclusionIt is intriguing that patients with NSCLC with EGFR mutations had better survival than wild type. Such a tumor biology may confound the survival data in a study without the stratification by EGFR mutation

Global DNA methylation and transcriptional analyses of human ESC-derived cardiomyocytes.

With defined culture protocol, human embryonic stem cells (hESCs) are able to generate cardiomyocytes in vitro, therefore providing a great model for human heart development, and holding great potential for cardiac disease therapies. In this study, we successfully generated a highly pure population of human cardiomyocytes (hCMs) (>95% cTnT(+)) from hESC line, which enabled us to identify and characterize an hCM-specific signature, at both the gene expression and DNA methylation levels. Gene functional association network and gene-disease network analyses of these hCM-enriched genes provide new insights into the mechanisms of hCM transcriptional regulation, and stand as an informative and rich resource for investigating cardiac gene functions and disease mechanisms. Moreover, we show that cardiac-structural genes and cardiac-transcription factors have distinct epigenetic mechanisms to regulate their gene expression, providing a better understanding of how the epigenetic machinery coordinates to regulate gene expression in different cell types

Real-Time Monitoring and Analysis of Zebrafish Electrocardiogram with Anomaly Detection.

Heart disease is the leading cause of mortality in the U.S. with approximately 610,000 people dying every year. Effective therapies for many cardiac diseases are lacking, largely due to an incomplete understanding of their genetic basis and underlying molecular mechanisms. Zebrafish (Danio rerio) are an excellent model system for studying heart disease as they enable a forward genetic approach to tackle this unmet medical need. In recent years, our team has been employing electrocardiogram (ECG) as an efficient tool to study the zebrafish heart along with conventional approaches, such as immunohistochemistry, DNA and protein analyses. We have overcome various challenges in the small size and aquatic environment of zebrafish in order to obtain ECG signals with favorable signal-to-noise ratio (SNR), and high spatial and temporal resolution. In this paper, we highlight our recent efforts in zebrafish ECG acquisition with a cost-effective simplified microelectrode array (MEA) membrane providing multi-channel recording, a novel multi-chamber apparatus for simultaneous screening, and a LabVIEW program to facilitate recording and processing. We also demonstrate the use of machine learning-based programs to recognize specific ECG patterns, yielding promising results with our current limited amount of zebrafish data. Our solutions hold promise to carry out numerous studies of heart diseases, drug screening, stem cell-based therapy validation, and regenerative medicine