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In recent years, the application of deep learning models to protein-ligand docking and affinity prediction, both vital for structure-based drug design, has garnered increasing interest. However, many of these models overlook the intricate modeling of interactions between ligand and protein atoms in the complex, consequently limiting their capacity for generalization and interpretability. In this work, we propose Interformer, a unified model built upon the Graph-Transformer architecture. The proposed model is designed to capture non-covalent interactions utilizing an interaction-aware mixture density network. Additionally, we introduce a negative sampling strategy, facilitating an effective correction of interaction distribution for affinity prediction. Experimental results on widely used and our in-house datasets demonstrate the effectiveness and universality of the proposed approach. Extensive analyses confirm our claim that our approach improves performance by accurately modeling specific protein-ligand interactions. Encouragingly, our approach advances docking tasks state-of-the-art (SOTA) performance. Interformer, a generative deep learning model, enhances protein-ligand docking accuracy and generalizability by capturing essential non-covalent interactions. It demonstrates its practical value in real-world drug design by reasonably ranking ligand affinity through a contrastive learning strategy.

To study the mechanical properties of different types of rocks under impact loading, static mechanical parameter tests and split-Hopkinson pressure bar (SHPB) dynamic impact experiments were conducted on five typical rock specimens. The mechanical properties and failure modes of different rock specimens under the same static and dynamic loading were investigated. The differences between numerical simulation results and laboratory test results under different constitutive models in LS-DYNA were also compared and analyzed. The results show that with the increase of SHPB impact pressure (0.5–0.8 MPa), the stress peak values of granite, marble, and limestone also increase, while gypsum and reef limestone follow no particular trend. At the same time, both HJC and RHT constitutive models can simulate the laboratory impact test results of granite, marble, and limestone, however, the gypsum and reef limestone are not modelled by the HJC constitutive model, while the RHT constitutive model can describe the deformation-damage-failure process of rock specimens with different strengths. Therefore, the RHT model can better reflect the real deformation and failure of rocks.

Due to the extensive application of antibiotics in medical and farming practices, the continued diversification and development of antimicrobial resistance (AMR) has attracted serious public concern. With the emergence of AMR and the failure to treat bacterial infections, it has led to an increased interest in searching for novel antibacterial substances such as natural antimicrobial substances, including microbial volatile compounds (MVCs), plant-derived compounds, and antimicrobial peptides. However, increasing observations have revealed that AMR is associated not only with the use of antibacterial substances but also with tolerance to heavy metals existing in nature and being used in agriculture practice. Additionally, bacteria respond to environmental stresses, e.g., nutrients, oxidative stress, envelope stress, by employing various adaptive strategies that contribute to the development of AMR and the survival of bacteria. Therefore, we need to elucidate thoroughly the factors and conditions affecting AMR to take comprehensive measures to control the development of AMR.

Background Stress hyperglycemia ratio (SHR) has been associated with adverse clinical outcomes in hospitalized patients with acute coronary syndromes (ACS). However, its role in long-term prognosis remains controversial. This study aims to investigate the correlation between SHR and post-discharge all-cause mortality in coronary heart disease (CHD) patients. Methods A retrospective cohort analysis was conducted on a comprehensive dataset encompassing 5,273 coronary heart disease (CHD) patients from The First Affiliated Hospital of Shantou University Medical College, spanning from January 2020 to April 2024. The study introduced a novel parameter, Stress hyperglycemia ratio (SHR), calculated using the formula: SHR = . Cox regression analysis, smooth curve fitting techniques, and subgroup analyses were employed to evaluate associations. Results During a maximum follow-up of 1,649 days, 8.1% of patients experienced all-cause mortality. After multivariable adjustments, a U-shaped association emerged between SHR and mortality risk (HR = 1.35, 95%CI= (1.03 ~ 1.77), P  = 0.031). Both low and high SHR levels were linked to increased mortality. Conclusions SHR demonstrates a U-shaped association with post-discharge all-cause mortality in CHD patients, highlighting the need for glycemic management within an optimal range.

Public unrest about the use of antimicrobial agents in farming practice is the leading cause of increasing and the emergences of Multi-drug Resistant Bacteria that have placed pressure on the agri-food industry to act. The usage of antimicrobials in food and agriculture have direct or indirect effects on the development of Antimicrobial resistance (AMR) by bacteria associated with animals and plants which may enter the food chain through consumption of meat, fish, vegetables or some other food sources. In addition to antimicrobials, recent reports have shown that AMR is associated with tolerance to heavy metals existing naturally or used in agri-food production. Besides, biocides including disinfectants, antiseptics and preservatives which are widely used in farms and slaughter houses may also contribute in the development of AMR. Though the direct transmission of AMR from food-animals and related environment to human is still vague and debatable, the risk should not be neglected. Therefore, combined global efforts are necessary for the proper use of antimicrobials, heavy metals and biocides in agri-food production to control the development of AMR. These collective measures will preserve the effectiveness of existing antimicrobials for future generations.

The peak particle velocity (PPV) is an important indicator for predicting blasting excavation disturbances. However, the PPV distribution in the deep underground space is significantly different from that on the outdoor ground. Therefore, it is difficult to predict the underground PPV by Sadovsky’s vibration formula. The PPV sidewall distribution characteristics were studied during site blasting in an underground cavern in the Taohuazui mine in China, and a similar numerical model was used to verify the site test data. We derived a PPV prediction formula for the underground cavern sidewall surrounding rock using a mechanical analysis model of a simply supported plate and beam in combination with dimensional analysis. The model considered derived boundary constraints, comparison with site measured data, the value predicted by Sadovsky’s vibration formula, and numerical simulation results. The results showed that the PPV distribution on the middle 1/3 section of the underground cavern sidewall showed a “platform” or “bulge” different from the curve from Sadovsky’s vibration formula. The PPV amplification coefficient in this section was distributed in a drum shape. The PPV prediction formula for the middle section of the sidewall derived in this paper was highly consistent with the data measured on-site and the numerical simulation results. The mechanical analysis model with a simply supported plate and beam included an underground cavern sidewall length–height ratio of 5 and effectively supplemented the PPV prediction formula for the middle section of the traditional underground cavern sidewall.

Oil–water annular flow is an efficient method of heavy oil transportation for energy-saving. To deeply study the influencing factors of the energy savings of oil–water annular flow, this paper compares the interface fluctuation and energy-saving situation of oil–water annular flow under different pipe structures (such as straight pipe, sudden-contraction pipe, and elbow pipe), flow parameters, and fluid properties. In the straight pipe, the flow parameters can impact the oil–water annular flow pattern and the energy savings, and the interface fluctuation is consistent with the energy savings. The stable oil–water core annular flow has slight interface fluctuation and significant energy savings. At the same time, the influences of pipe structure and fluid properties on energy saving are also analyzed. In the sudden-contraction pipe, the oil–water interface fluctuates, largely due to the sharp changes in flow cross-section, which leads to reduced energy savings. In the elbow, the oil–water interface fluctuates greatly due to the influence of centrifugal force caused by flow direction variation, and also leads to a decline in energy savings. The effects of oil property or annulus liquid property on the interface fluctuates, and the energy savings are analyzed; reducing surface tension is an effective measure to provide an energy-saving effect. These results can provide a reference for the design of heavy-oil-transportation pipelines, the analysis of interface fluctuation, and the energy-saving evaluation of oil–water annular flow.

Up to 80% of the human genome produces “dark matter” RNAs, most of which are noncapped RNAs (napRNAs) that frequently act as noncoding RNAs (ncRNAs) to modulate gene expression. Here, by developing a method, NAP-seq, to globally profile the full-length sequences of napRNAs with various terminal modifications at single-nucleotide resolution, we reveal diverse classes of structured ncRNAs. We discover stably expressed linear intron RNAs (sliRNAs), a class of snoRNA-intron RNAs (snotrons), a class of RNAs embedded in miRNA spacers (misRNAs) and thousands of previously uncharacterized structured napRNAs in humans and mice. These napRNAs undergo dynamic changes in response to various stimuli and differentiation stages. Importantly, we show that a structured napRNA regulates myoblast differentiation and a napRNA DINAP interacts with dyskerin pseudouridine synthase 1 (DKC1) to promote cell proliferation by maintaining DKC1 protein stability. Our approach establishes a paradigm for discovering various classes of ncRNAs with regulatory functions. The genome-wide prevalence, mechanism and function of noncapped RNAs (napRNAs) are currently poorly understood. Here, the authors develop a method called NAP-seq, to globally profile the full-length sequences of napRNAs, revealing several classes of structured noncoding RNAs.

Radioresistance imposes a great challenge in reducing tumor recurrence and improving the clinical prognosis of individuals having oral squamous cell carcinoma (OSCC). OSCC harbors a subpopulation of CD44(+) cells that exhibit cancer stem-like cell (CSC) characteristics are involved in malignant tumor phenotype and radioresistance. Nevertheless, the underlying molecular mechanisms in CD44( + )-OSCC remain unclear. The current investigation demonstrated that methyltransferase-like 3 (METTL3) is highly expressed in CD44(+) cells and promotes CSCs phenotype. Using RNA-sequencing analysis, we further showed that Spalt-like transcription factor 4 (SALL4) is involved in the maintenance of CSCs properties. Furthermore, the overexpression of SALL4 in CD44( + )-OSCC cells caused radioresistance in vitro and in vivo. In contrast, silencing SALL4 sensitized OSCC cells to radiation therapy (RT). Mechanistically, we illustrated that SALL4 is a direct downstream transcriptional regulation target of METTL3, the transcription activation of SALL4 promotes the nuclear transport of β-catenin and the expression of downstream target genes after radiation therapy, there by activates the Wnt/β-catenin pathway, effectively enhancing the CSCs phenotype and causing radioresistance. Herein, this study indicates that the METTL3/SALL4 axis promotes the CSCs phenotype and resistance to radiation in OSCC via the Wnt/β-catenin signaling pathway, and provides a potential therapeutic target to eliminate radioresistant OSCC.