Doping induced multiferroicity and quantum anomalous Hall effect in α\alpha-In2_2Se3_3 thin films

In flat-band materials, the strong Coulomb interaction between electrons can lead to exotic physical phenomena. Recently, $\alpha$-In$_2$Se$_3$ thin films were found to possess ferroelectricity and flat bands. In this work, using first-principles calculations, we find that for the monolayer, there is a Weyl point at $\Gamma$ in the flat band, where the inclusion of the spin-orbit coupling opens a gap. Shifting the Fermi level into the spin-orbit gap gives rise to nontrivial band topology, which is preserved for the bilayer regardless of the interlayer polarization couplings. We further calculate the Chern number and edge states for both the monolayer and bilayer, for which the results suggest that they become quantum anomalous Hall insulators under appropriate dopings. Moreover, we find that the doping-induced magnetism for In$_2$Se$_3$ bilayer is strongly dependent on the interlayer polarization coupling. Therefore, doping the flat bands in In$_2$Se$_3$ bilayer can also yield multiferroicity, where the magnetism is electrically tunable as the system transforms between different polarization states. Our study thus reveals that multiferroicity and nontrivial band topology can be unified into one material for designing multifunctional electronic devices.Comment: 6 pages, 4 figure

ContraNovo: A Contrastive Learning Approach to Enhance De Novo Peptide Sequencing

De novo peptide sequencing from mass spectrometry (MS) data is a critical task in proteomics research. Traditional de novo algorithms have encountered a bottleneck in accuracy due to the inherent complexity of proteomics data. While deep learning-based methods have shown progress, they reduce the problem to a translation task, potentially overlooking critical nuances between spectra and peptides. In our research, we present ContraNovo, a pioneering algorithm that leverages contrastive learning to extract the relationship between spectra and peptides and incorporates the mass information into peptide decoding, aiming to address these intricacies more efficiently. Through rigorous evaluations on two benchmark datasets, ContraNovo consistently outshines contemporary state-of-the-art solutions, underscoring its promising potential in enhancing de novo peptide sequencing. The source code is available at https://github.com/BEAM-Labs/ContraNovo.Comment: This paper has been accepted by AAAI 202

Study on self-loosening of bolted joints excited by dynamic axial load

International audienc

Direct Conversion of Fibroblasts to Neurons by Reprogramming PTB-Regulated MicroRNA Circuits

SummaryThe induction of pluripotency or trans-differentiation of one cell type to another can be accomplished with cell-lineage-specific transcription factors. Here, we report that repression of a single RNA binding polypyrimidine-tract-binding (PTB) protein, which occurs during normal brain development via the action of miR-124, is sufficient to induce trans-differentiation of fibroblasts into functional neurons. Besides its traditional role in regulated splicing, we show that PTB has a previously undocumented function in the regulation of microRNA functions, suppressing or enhancing microRNA targeting by competitive binding on target mRNA or altering local RNA secondary structure. A key event during neuronal induction is the relief of PTB-mediated blockage of microRNA action on multiple components of the REST complex, thereby derepressing a large array of neuronal genes, including miR-124 and multiple neuronal-specific transcription factors, in nonneuronal cells. This converts a negative feedback loop to a positive one to elicit cellular reprogramming to the neuronal lineage

A general Temperature-Guided Language model to engineer enhanced Stability and Activity in Proteins

Designing protein mutants with high stability and activity is a critical yet challenging task in protein engineering. Here, we introduce PRIME, an innovative deep learning approach for the zero-shot prediction of both protein stability and enzymatic activity. PRIME leverages temperature-guided language modelling, providing robust and precise predictions without relying on prior experimental mutagenesis data. Tested against 33 protein datasets, PRIME demonstrated superior predictive performance and generalizability compared to current state-of-the-art modelsComment: arXiv admin note: text overlap with arXiv:2304.0378

Case report: Pulmonary artery sarcoma diagnosed through rare brain metastases

We present the case of a 33-year-old male referred across several hospitals because of suspected chronic thromboembolic pulmonary hypertension (CTEPH). Initially admitted in October 2022 for a recurrent, severe cough and diagnosed with CTEPH, he received anticoagulant therapy. However, his symptoms worsened, necessitating a transfer to another facility for thrombolysis treatment. Following an episode of syncope, an MRI scan revealed a metastatic brain tumor. Subsequently, he experienced a third transfer to our hospital, emergency surgery was performed to alleviate cerebral edema and excise a lesion in the left frontal lobe. Postoperative pathology was inconclusive, but a multidisciplinary team meeting, aided by experienced radiologists, eventually confirmed a diagnosis of pulmonary artery sarcoma (PAS) with systemic metastases. This case underscores the necessity of promptly ruling out PAS in patients presenting with significant emboli in the central pulmonary arteries and suggests early referral to specialized centers for suspected cases

Evolution and Comprehensive Analysis of DNaseI Hypersensitive Sites in Regulatory Regions of Primate Brain-Related Genes

How the human brain differs from those of non-human primates is largely unknown and the complex drivers underlying such differences at the genomic level remain unclear. In this study, we selected 243 brain-related genes, based on Gene Ontology, and identified 184,113 DNaseI hypersensitive sites (DHSs) within their regulatory regions. To performed comprehensive evolutionary analyses, we set strict filtering criteria for alignment quality and filtered 39,132 DHSs for inclusion in the investigation and found that 2,397 (~6%) exhibited evidence of accelerated evolution (aceDHSs), which was a much higher proportion that DHSs genome-wide. Target genes predicted to be regulated by brain-aceDHSs were functionally enriched for brain development and exhibited differential expression between human and chimpanzee. Alignments indicated 61 potential human-specific transcription factor binding sites in brain-aceDHSs, including for CTCF, FOXH1, and FOXQ1. Furthermore, based on GWAS, Hi-C, and eQTL data, 16 GWAS SNPs, and 82 eQTL SNPs were in brain-aceDHSs that regulate genes related to brain development or disease. Among these brain-aceDHSs, we confirmed that one enhanced the expression of GPR133, using CRISPR-Cas9 and western blotting. The GPR133 gene is associated with glioblastoma, indicating that SNPs within DHSs could be related to brain disorders. These findings suggest that brain-related gene regulatory regions are under adaptive evolution and contribute to the differential expression profiles among primates, providing new insights into the genetic basis of brain phenotypes or disorders between humans and other primates

Role of Ammonia on the Feedback Between AWC and Inorganic Aerosol Formation During Heavy Pollution in the North China Plain

Atmospheric NH3 plays a vital role not only in the environmental ecosystem but also in atmosphere chemistry. To further understand the effects of NH3 on the formation of haze pollution in Beijing, ambient NH3 and related species were measured and simulated at high resolutions during the wintertime Air Pollution and Human Health-Beijing (APHH-Beijing) campaign in 2016. We found that the total NHx (gaseous NH3+particle NH4 +) was mostly in excess of the SO4 2−-NO3 −-NH4 +-water equilibrium system during our campaign. This NHx excess made medium aerosol acidity, with the median pH value being 3.6 and 4.5 for polluted and nonpolluted conditions, respectively, and enhanced the formation of particle phase nitrate. Our analysis suggests that NH4NO3 is the most important factor driving the increasing of aerosol water content with NO3 − controlling the prior pollution stage and NH4 + the most polluted stage. Increased formation of NH4NO3 under excess NHx, especially during the nighttime, may trigger the decreasing of aerosol deliquescence relative humidity even down to less than 50% and hence lead to hygroscopic growth even under RH conditions lower than 50% and the wet aerosol particles become better medium for rapid heterogeneous reactions. A further increase of RH promotes the positive feedback “aerosol water content-heterogeneous reactions” and ultimately leads to the formation of severe haze. Modeling results by Nested Air Quality Prediction Monitor System (NAQPMS) show the control of 20% NH3 emission may affect 5–11% of particulate matter PM2.5 formation under current emissions conditions in the North China Plain