Publications by authors named "Tianyu Lu"

We present Protpardelle-1c, a collection of protein structure generative models with robust motif scaffolding and support for multi-chain complex generation under hotspot-conditioning. Enabling sidechain-conditioning to a backbone-only model increased Protpardelle-1c's MotifBench score from 4.97 to 28.

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The global spread of hypervirulent (hvKp) poses a serious public health threat. In this study, we conducted genomic epidemiology analysis on 2097 global hvKp isolates, including our 900 isolates sequenced through the Illumina platform (177 of them fully sequenced through PacBio platform), representing the most comprehensive genomic analysis of hvKp to date. Our results identified six dominant clonal groups (CGs), particularly including CG23 and CG258, and 17 major virulence determinant combinations (VDCs) comprising 10 virulence gene profiles (VGPs), four types of virulence plasmids, four ICE variants, Tn, and _island.

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N4-acetylcytidine (ac4C) is an evolutionarily conserved RNA modification catalyzed by the acetyltransferase NAT10. It regulates RNA stability, translation, and post-transcriptional processes. Meanwhile, NAT10 functions as a dual-function enzyme exhibiting both protein acetyltransferase and RNA acetylase activities.

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Unlike preceding MERS-related coronaviruses, the recently identified MjHKU4r-CoV-1 strain can directly infect human cells. Nonetheless, its potential pathogenic attributes and underlying molecular mechanisms remain unclear. We find that MjHKU4r-CoV-1 induces significant inflammation, including interleukin (IL)-6 and tumor necrosis factor alpha (TNF-α), and exhibits pronounced fusogenicity mediated by its spike (S) protein, leading to extensive syncytium formation.

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Recent advances in generative modeling enable efficient sampling of protein structures, but their tendency to optimize for designability imposes a bias toward idealized structures at the expense of loops and other complex structural motifs that are critical for function. We introduce SHAPES (structural and hierarchical assessment of proteins with embedding similarity) to evaluate five state-of-the-art generative models of protein structures. Using structural embeddings across multiple structural hierarchies, ranging from local geometries to global protein architectures, we reveal substantial undersampling of the observed protein structure space by these models.

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While generative AI is transforming the design of proteins, its effectiveness for structure-based design of small molecules remains limited. Current methods, including diffusion models, often produce small molecules with difficult-to-synthesize structures, poor medicinal chemistry properties, and limited target selectivity. To address these limitations, we introduce MedSAGE, a novel generative AI framework that adapts diffusion models specifically for small-molecule design.

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Background: Esophageal cancer is the 11th most common malignancy and the 7th leading cause of cancer-related death globally. Identifying key molecules and underlying mechanisms in the progression of esophageal cancer represents an effective strategy for developing novel therapeutic approaches.

Methods: DDX18 expression in clinical specimens was evaluated by immunohistochemistry and western blot analysis.

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This study proposed a novel perovskite/silicon heterojunction (SHJ) tandem device structure without an interlayer, represented as ITO/NiO/perovskite/SnO/MoO/i-a-Si:H/n-c-Si/i-a-Si:H/n-a-Si:H/Ag, which was investigated by Silvaco TCAD software. The recombination layer in this structure comprises the carrier transport layers of SnO and MoO, where MoO serves dual functions, acting as the emitter for the SHJ bottom cell and as part of the recombination layer in the tandem cell. First, the effects of different recombination layers are analyzed, and the SnO/MoO layer demonstrates the best performance.

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Sarbecoviruses, such as SARS-CoV-2, utilize angiotensin-converting enzyme 2 (ACE2) as the entry receptor; while merbecoviruses, such as MERS-CoV, use dipeptidyl peptidase 4 (DPP4) for viral entry. Recently, several MERS-related coronaviruses, NeoCoV and PDF-2180, were reported to use ACE2, the same receptor as SARS-CoV-2, to enter cells, raising the possibility of potential recombination between SARS-CoV-2 and MERS-related coronaviruses within the co-infected ACE2-expressing cells. However, facing this potential recombination risk, the serum and antibody cross-reactivity against MERS/MERS-related coronaviruses after SARS-CoV-2 vaccination and/or infection is still elusive.

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Objectives: To develop and validate a contrast-enhanced MRI-based intratumoral heterogeneity (ITH) model for predicting lymph node (LN) metastasis in resectable pancreatic ductal adenocarcinoma (PDAC).

Methods: Lesions were encoded into different habitats based on enhancement ratios at arterial, venous, and delayed phases of contrast-enhanced MRI. Habitat models on enhanced ratio mapping and single sequences, radiomic models, and clinical models were developed for evaluating LN metastasis.

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Advances in multi-omics datasets and analytical methods have revolutionized cancer research, offering a comprehensive, pan-cancer perspective. Pan-cancer studies identify shared mechanisms and unique traits across different cancer types, which are reshaping diagnostic and treatment strategies. However, continued innovation is required to refine these approaches and deepen our understanding of cancer biology and medicine.

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Recent advances in generative modeling enable efficient sampling of protein structures, but their tendency to optimize for designability imposes a bias toward idealized structures at the expense of loops and other complex structural motifs critical for function. We introduce SHAPES (Structural and Hierarchical Assessment of Proteins with Embedding Similarity) to evaluate five state-of-the-art generative models of protein structures. Using structural embeddings across multiple structural hierarchies, ranging from local geometries to global protein architectures, we reveal substantial undersampling of the observed protein structure space by these models.

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Functional fibrous membranes with high mechanical properties are intensively developed for different application fields. In this study, to enhance moisture and air permeability without compromising mechanical strength, a facile float-surface modification strategy is employed to fabricate Janus fibrous membranes with distinct hydrophobicity/hydrophilicity using the high-density polyethylene (HDPE) fibrous membranes. By coating one side of the HDPE fibrous membranes with polydopamine (PDA) and a superhydrophilic polyelectrolyte, the obtained Janus HDPE fibrous membranes demonstrate an excellent water transmission rate (577.

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The effect of HMC4 produced by protoplast fusion on silage was studied. The silage formula was composed of heterozygote HMC4 (Group C), parent Lactobacillus (Group A) and a combination of two parents (Group B). The fermentation quality and microbial composition of each batch of silage were evaluated.

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Cancer has become one of the major diseases threatening human health in the twenty-first century due to its incurability. In 2022, new cases of esophageal and gastrointestinal cancers accounted for 17.1% of all newly diagnosed cancer cases worldwide.

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Accumulating evidence indicates that maternal exposure to carbon black nanoparticles (CBNPs) during gestation can induce multiple system abnormalities in offspring, whereas its potential mechanism in respiratory disease is still largely unknown. In order to explore the effect of maternal exposure to CBNPs on offspring's lung and latent pathogenesis, we respectively established in vivo model of pregnant rats exposed to CBNPs and ex vivo model of lung epithelial cells treated with pups' serum of pregnant rats exposed to CBNPs. After maternal exposure to CBNPs, epithelial-mesenchymal transition (EMT) and fibrosis levels increased as a result of DDRGK1-mediated reticulophagy upregulated in offspring's lung.

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Adeno-associated virus (AAV) is a widely used vehicle for gene delivery, lending interest to developing methods for enhancing AAV transduction and transgene expression. Here, we profile the function of several topoisomerase poisons, which are small molecules that stabilize topoisomerase enzymatic intermediates, where topoisomerase enzymes are covalently bound at chromosomal DNA breaks. As previously observed, we found that the topoisomerase poisons camptothecin (CPT), doxorubicin (DOX), and etoposide (ETO) increased AAV transduction in cultured cell models.

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We have developed an ultrasound-assisted remote benzylic C(sp)-H alkylation of -fluorobenzamides with enol silanes; a series of β-aryl substituted propiophenones was generated in good to high yields. This reaction represents a C(sp)-C(sp) coupling and features simplicity, high efficiency, and wide substrate scope in a multiple-step sequential process, which involves N-F homolysis, 1,5-hydrogen atom transfer, benzylic radical addition, oxidation by copper(II) salt, and removal of the trimethylsilyl group. Also, DFT theoretical calculations and Marcus theory were employed to consolidate the proposed reaction mechanism.

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Article Synopsis
  • * The study found that CFAP65 expression was notably higher in colon cancer tissue compared to adjacent healthy tissue, with 61.9% of samples showing high expression.
  • * Low CFAP65 expression was associated with a lower five-year disease-free survival rate, while its expression, along with tumor stage and location, were identified as independent prognostic factors for colon cancer outcomes.
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  • Crohn's disease (CD) and intestinal tuberculosis (ITB) are often confused for each other, but they require different treatments and prognoses, highlighting the need for accurate diagnosis.
  • A study involving 72 tissue samples used advanced techniques like infrared spectroscopy and machine learning to differentiate between CD and ITB.
  • The developed diagnostic model achieved high accuracy (91.84%), specificity (92.59%), and sensitivity (90.90%), suggesting that this method could effectively distinguish between the two diseases at a molecular level.
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  • The study focused on comparing the effectiveness of handcrafted radiomics (HR) features and deep transfer learning (DTL) features in predicting lymph node metastasis in non-small cell lung cancer (NSCLC) using CT scans.
  • The research involved 199 NSCLC patients, with data divided into training and validation groups, and various machine learning models were evaluated for their predictive performance.
  • Results indicated that the logistic regression model utilizing DTL features outperformed the HR features, demonstrating a higher ability to predict lymph node metastasis in NSCLC patients.
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  • The study investigates the genetic and brain features linked to vocal learning in mammals by comparing data from the Egyptian fruit bat and 215 other placental mammals.* -
  • Researchers found that certain proteins evolve more slowly in vocal learners and identified a specific brain region responsible for vocal motor control in the Egyptian fruit bat.* -
  • Using machine learning, they uncovered 50 regulatory elements that are associated with vocal learning, suggesting that losses in these elements played a role in the evolution of vocal learning in mammals.*
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  • 1,4-dioxane is a potentially harmful chemical in water that can be removed using specially engineered carbon aerogels, which are effective adsorbents due to their unique structural properties.
  • The effectiveness of these carbon aerogels depends on specific preparation conditions, with the optimal setup achieving over 95% removal of 1,4-dioxane at a pyrolysis temperature of 800 °C, among other factors.
  • The carbon aerogels demonstrated strong adsorption capabilities even in the presence of other solvents, maintaining their effectiveness through multiple regeneration cycles, highlighting their practical use in cleaning contaminated water.
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  • The study aimed to create and validate a prognostic model that uses clinical lab biomarkers to identify hospitalized patients with the Omicron variant of SARS-CoV-2 who are at high risk for needing ICU care, specifically those with myocardial injury.
  • Researchers enrolled 263 patients with confirmed Omicron infections and divided them into training and validation groups, using specific biomarkers (WBC count, PCT, CRP, and BUN levels) to develop a Cox regression model.
  • The model demonstrated strong predictive capability, with good discrimination and calibration in both cohorts, suggesting it could be a valuable tool for early identification of severe cases needing critical care.
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