Expression Patterns of Non-Coding Spliced Transcripts from Human Endogenous Retrovirus HERV-H Elements in Colon Cancer

BACKGROUND: Up-regulation of the most abundant H family human endogenous retrovirus (HERV-H), especially env-related transcripts, correlates with colon cancer. However, expression pattern of spliced non-coding transcripts of HERV-H is not clear. METHODOLOGY/PRINCIPAL FINDINGS: In this study, expression of HERV-H spliced transcripts in colon cancer was investigated by a RT-PCR strategy using primers targeting the tRNA(His) primer-binding site and the R region in the 3' long terminal repeat (LTR), followed by cloning and sequencing of the amplicons. Sequences were then assigned to individual HERV-H loci by employing private nucleotide differences between loci. Different expression patterns of HERV-H spliced transcripts from distinct active elements were found in colon cancer cell lines HT29, LS 174T, RKO, SW480 and SW620. Furthermore, the expression patterns in SW480 and RKO were significantly changed by demethylation treatment. Interestingly, more HERV-H elements were found to be transcriptionally active in colon tumor tissues than in adjacent normal tissues (14 vs. 7). CONCLUSIONS/SIGNIFICANCE: This is the first research to study the character of expression of non-coding spliced transcripts of HERV-H elements in colon cancer. Expression patterns of HERV-H spliced transcripts differed among colon cancer cell lines and could be affected by genomic DNA methylation levels. More importantly, besides the commonly accepted view of up-regulation of HERV-H expression in colon tumor tissues, we found more active HERV-H loci in colon tumor as compared with adjacent normal tissues

SeisCLIP: A seismology foundation model pre-trained by multi-modal data for multi-purpose seismic feature extraction

Training specific deep learning models for particular tasks is common across various domains within seismology. However, this approach encounters two limitations: inadequate labeled data for certain tasks and limited generalization across regions. To address these challenges, we develop SeisCLIP, a seismology foundation model trained through contrastive learning from multi-modal data. It consists of a transformer encoder for extracting crucial features from time-frequency seismic spectrum and an MLP encoder for integrating the phase and source information of the same event. These encoders are jointly pre-trained on a vast dataset and the spectrum encoder is subsequently fine-tuned on smaller datasets for various downstream tasks. Notably, SeisCLIP's performance surpasses that of baseline methods in event classification, localization, and focal mechanism analysis tasks, employing distinct datasets from different regions. In conclusion, SeisCLIP holds significant potential as a foundational model in the field of seismology, paving the way for innovative directions in foundation-model-based seismology research.Comment: 27 pages, 9 figures, 4 table

In-situ electrical and thermal transport properties of FeySe1-xTex films with ionic liquid gating

We combine in-situ electrical transport and Seebeck coefficient measurements with the ionic liquid gating technique to investigate superconductivity and the normal state of FeySe1-xTex (FST) films. We find that the pristine FST films feature a non-Fermi liquid temperature dependence of the Seebeck coefficient, i.e., S/T ~ AS lnT, and AS is strongly correlated with the superconducting transition temperature (Tc). Ionic liquid gating significantly raises Tc of FST films, for which the Seebeck coefficient displays a novel scaling behavior and retains the logarithmic temperature dependence. Moreover, a quantitative relationship between the slope of T-linear resistivity (A\r{ho}) and Tc for gated films is observed, i.e., (A\r{ho})1/2 ~ Tc, consistent with previous reports on cuprates and FeSe. The scaling behaviors of AS and A\r{ho} point to a spin-fluctuation-associated transport mechanism in gated FeySe1-xTex superconductors.Comment: 12 pages,5 figure

Genome-Wide Association Mapping of Starch Pasting Properties in Maize Using Single-Locus and Multi-Locus Models

Maize starch plays a critical role in food processing and industrial application. The pasting properties, the most important starch characteristics, have enormous influence on fabrication property, flavor characteristics, storage, cooking, and baking. Understanding the genetic basis of starch pasting properties will be beneficial for manipulation of starch properties for a given purpose. Genome-wide association studies (GWAS) are becoming a powerful tool for dissecting the complex traits. Here, we carried out GWAS for seven pasting properties of maize starch with a panel of 230 inbred lines and 145,232 SNPs using one single-locus method, genome-wide efficient mixed model association (GEMMA), and three multi-locus methods, FASTmrEMMA, FarmCPU, and LASSO. We totally identified 60 quantitative trait nucleotides (QTNs) for starch pasting properties with these four GWAS methods. FASTmrEMMA detected the most QTNs (29), followed by FarmCPU (19) and LASSO (12), GEMMA detected the least QTNs (7). Of these QTNs, seven QTNs were identified by more than one method simultaneously. We further investigated locations of these significantly associated QTNs for possible candidate genes. These candidate genes and significant QTNs provide the guidance for further understanding of molecular mechanisms of starch pasting properties. We also compared the statistical powers and Type I errors of the four GWAS methods using Monte Carlo simulations. The results suggest that the multi-locus method is more powerful than the single-locus method and a combination of these multi-locus methods could help improve the detection power of GWAS

Graphene controlled Brewster angle device for ultra broadband terahertz modulation

Terahertz modulators with high tunability of both intensity and phase are essential for effective control of electromagnetic properties. Due to the underlying physics behind existing approaches there is still a lack of broadband devices able to achieve deep modulation. Here, we demonstrate the effect of tunable Brewster angle controlled by graphene, and develop a highly-tunable solid-state graphene/quartz modulator based on this mechanism. The Brewster angle of the device can be tuned by varying the conductivity of the graphene through an electrical gate. In this way, we achieve near perfect intensity modulation with spectrally flat modulation depth of 99.3 to 99.9 percent and phase tunability of up to 140 degree in the frequency range from 0.5 to 1.6 THz. Different from using electromagnetic resonance effects (for example, metamaterials), this principle ensures that our device can operate in ultra-broadband. Thus it is an effective principle for terahertz modulation

Phase diagrams on composition-spread Fey_yTe1−x_{1-x}Sex_x films

Fe$_y$Te$_{1-x}$Se$_x$, an archetypical iron-based high-temperature superconductor with a simple structure but rich physical properties, has attracted lots of attention because the two end compositions, Se content $x = 0$ and 1, exhibit antiferromagnetism and nematicity, respectively, making it an ideal candidate for studying their interactions with superconductivity. However, what is clearly lacking to date is a complete phase diagram of Fe$_y$Te$_{1-x}$Se$_x$ as functions of its chemical compositions since phase separation usually occurs from $x\sim 0.6$ to 0.9 in bulk crystals. Moreover, fine control of its composition is experimentally challenging because both Te and Se are volatile elements. Here we establish a complete phase diagram of Fe$_y$Te$_{1-x}$Se$_x$, achieved by high-throughput film synthesis and characterization techniques. An advanced combinatorial synthesis process enables us to fabricate an epitaxial composition-spread Fe$_y$Te$_{1-x}$Se$_x$ film encompassing the entire Se content $x$ from 0 to 1 on a single piece of CaF$_2$ substrate. The micro-region composition analysis and X-ray diffraction show a successful continuous tuning of chemical compositions and lattice parameters, respectively. The micro-scale pattern technique allows the mapping of electrical transport properties as a function of relative Se content with an unprecedented resolution of 0.0074. Combining with the spin patterns in literature, we build a detailed phase diagram that can unify the electronic and magnetic properties of Fe$_y$Te$_{1-x}$Se$_x$. Our composition-spread Fe$_y$Te$_{1-x}$Se$_x$ films, overcoming the challenges of phase separation and precise control of chemical compositions, provide an ideal platform for studying the relationship between superconductivity and magnetism.Comment: 13 pages,5 figures and Supplementary Material 3 pages,3 figure

Screening Spin Lattice Interaction Using Deep Learning Approach

Atomic simulations hold significant value in clarifying crucial matters such as phase transitions and energy transport in materials science. Their success stems from the presence of potential energy functions capable of accurately depicting the relationship between system energy and lattice changes. In magnetic materials, two atomic scale degrees of freedom come into play: the lattice and the magnetic moment. Nonetheless, precisely portraying the interaction energy and its impact on lattice and spin-driving forces, such as atomic force and magnetic torque, remains a formidable task in the computational domain. Consequently, there is no atomic-scale approach capable of elucidating the evolution of lattice and spin at the same time in magnetic materials. Addressing this knowledge deficit, we present DeepSPIN, a versatile approach that generates high-precision predictive models of energy, atomic forces, and magnetic torque in magnetic systems. This is achieved by integrating first-principles calculations of magnetic excited states with advanced deep learning techniques via active learning. We thoroughly explore the methodology, accuracy, and scalability of our proposed model in this paper. Our technique adeptly connects first-principles computations and atomic-scale simulations of magnetic materials. This synergy presents opportunities to utilize these calculations in devising and tackling theoretical and practical obstacles concerning magnetic materials.Comment: 8 pages, 4 figure