Lactylation prediction models based on protein sequence and structural feature fusion.

Lysine lactylation (Kla) is a newly discovered posttranslational modification that is involved in important life activities, such as glycolysis-related cell function, macrophage polarization and nervous system regulation, and has received widespread attention due to the Warburg effect in tumor cells. In this work, we first design a natural language processing method to automatically extract the 3D structural features of Kla sites, avoiding potential biases caused by manually designed structural features. Then, we establish two Kla prediction frameworks, Attention-based feature fusion Kla model (ABFF-Kla) and EBFF-Kla, to integrate the sequence features and the structure features based on the attention layer and embedding layer, respectively. The results indicate that ABFF-Kla and Embedding-based feature fusion Kla model (EBFF-Kla), which fuse features from protein sequences and spatial structures, have better predictive performance than that of models that use only sequence features. Our work provides an approach for the automatic extraction of protein structural features, as well as a flexible framework for Kla prediction. The source code and the training data of the ABFF-Kla and the EBFF-Kla are publicly deposited at: https://github.com/ispotato/Lactylation_model.

GTE: a graph learning framework for prediction of T-cell receptors and epitopes binding specificity.

The interaction between T-cell receptors (TCRs) and peptides (epitopes) presented by major histocompatibility complex molecules (MHC) is fundamental to the immune response. Accurate prediction of TCR-epitope interactions is crucial for advancing the understanding of various diseases and their prevention and treatment. Existing methods primarily rely on sequence-based approaches, overlooking the inherent topology structure of TCR-epitope interaction networks. In this study, we present $GTE$, a novel heterogeneous Graph neural network model based on inductive learning to capture the topological structure between TCRs and Epitopes. Furthermore, we address the challenge of constructing negative samples within the graph by proposing a dynamic edge update strategy, enhancing model learning with the nonbinding TCR-epitope pairs. Additionally, to overcome data imbalance, we adapt the Deep AUC Maximization strategy to the graph domain. Extensive experiments are conducted on four public datasets to demonstrate the superiority of exploring underlying topological structures in predicting TCR-epitope interactions, illustrating the benefits of delving into complex molecular networks. The implementation code and data are available at https://github.com/uta-smile/GTE.

HLAIImaster: a deep learning method with adaptive domain knowledge predicts HLA II neoepitope immunogenic responses.

While significant strides have been made in predicting neoepitopes that trigger autologous CD4+ T cell responses, accurately identifying the antigen presentation by human leukocyte antigen (HLA) class II molecules remains a challenge. This identification is critical for developing vaccines and cancer immunotherapies. Current prediction methods are limited, primarily due to a lack of high-quality training epitope datasets and algorithmic constraints. To predict the exogenous HLA class II-restricted peptides across most of the human population, we utilized the mass spectrometry data to profile >223 000 eluted ligands over HLA-DR, -DQ, and -DP alleles. Here, by integrating these data with peptide processing and gene expression, we introduce HLAIImaster, an attention-based deep learning framework with adaptive domain knowledge for predicting neoepitope immunogenicity. Leveraging diverse biological characteristics and our enhanced deep learning framework, HLAIImaster is significantly improved against existing tools in terms of positive predictive value across various neoantigen studies. Robust domain knowledge learning accurately identifies neoepitope immunogenicity, bridging the gap between neoantigen biology and the clinical setting and paving the way for future neoantigen-based therapies to provide greater clinical benefit. In summary, we present a comprehensive exploitation of the immunogenic neoepitope repertoire of cancers, facilitating the effective development of "just-in-time" personalized vaccines.

TransGEM: a molecule generation model based on Transformer with gene expression data.

MOTIVATION: It is difficult to generate new molecules with desirable bioactivity through ligand-based de novo drug design, and receptor-based de novo drug design is constrained by disease target information availability. The combination of artificial intelligence and phenotype-based de novo drug design can generate new bioactive molecules, independent from disease target information. Gene expression profiles can be used to characterize biological phenotypes. The Transformer model can be utilized to capture the associations between gene expression profiles and molecular structures due to its remarkable ability in processing contextual information. RESULTS: We propose TransGEM (Transformer-based model from gene expression to molecules), which is a phenotype-based de novo drug design model. A specialized gene expression encoder is used to embed gene expression difference values between diseased cell lines and their corresponding normal tissue cells into TransGEM model. The results demonstrate that the TransGEM model can generate molecules with desirable evaluation metrics and property distributions. Case studies illustrate that TransGEM model can generate structurally novel molecules with good binding affinity to disease target proteins. The majority of genes with high attention scores obtained from TransGEM model are associated with the onset of the disease, indicating the potential of these genes as disease targets. Therefore, this study provides a new paradigm for de novo drug design, and it will promote phenotype-based drug discovery. AVAILABILITY AND IMPLEMENTATION: The code is available at https://github.com/hzauzqy/TransGEM.

Damage-Tolerant Wood Layers for Corrosion Protection of Metal Structures.

Mechanically strong and damage-tolerant corrosion protection layers are of great technological importance. However, corrosion protection layers with high modulus (>1.5 GPa) and tensile strength (>100 MPa) are rare. Here, we report that a 130 µm thick densified wood veneer with a Young's modulus of 34.49 GPa and tensile strength of 693 MPa exhibits both low diffusivity for metal ions and the ability of self-recovery from mechanical damage. Densified wood veneer is employed as an intermediate layer to render a mechanically strong corrosion protection structure, referred to as "wood corrosion protection structure", or WCPS. The corrosion rate of low-carbon steel protected by WCPS is reduced by 2 orders of magnitude than state-of-the-art corrosion protection layers during a salt spray test. The introduction of engineered wood veneer as a thin and mechanically strong material points to new directions of sustainable corrosion protection design.

tRF-29-79 regulates lung adenocarcinoma progression through mediating glutamine transporter SLC1A5.

In recent decades, considerable evidence has emerged indicating the involvement of tRNA-derived fragments (tRFs) in cancer progression through various mechanisms. However, the biological effects and mechanisms of tRFs in lung adenocarcinoma (LUAD) remain unclear. In this study, we screen out tRF-29-79, a 5'-tRF derived from tRNAGlyGCC, through profiling the tRF expressions in three pairs of LUAD tissues. We show that tRF-29-79 is downregulated in LUAD and downregulation of tRF-29-79 is associated with poorer prognosis. In vivo and in vitro assay reveal that tRF-29-79 inhibits proliferation, migration and invasion of LUAD cells. Mechanistically, we discovered that tRF-29-79 interacts with the RNA-binding protein PTBP1 and facilitates the transportation of PTBP1 from nucleus to cytoplasm, which regulates alternative splicing in the 3' untranslated region (UTR) of SLC1A5 pre-mRNA. Given that SLC1A5 is a core transporter of glutamine, we proved that tRF-29-79 mediate glutamine metabolism of LUAD through affecting the stability of SLC1A5 mRNA, thus exerts its anticancer function. In summary, our findings uncover the novel mechanism that tRF-29-79 participates in glutamine metabolism through interacting with PTBP1 and regulating alternative splicing in the 3' UTR of SLC1A5 pre-mRNA.

Global patterns and drivers of plant-soil microbe interactions.

Plant-soil feedback (PSF) is an important mechanism determining plant community dynamics and structure. Understanding the geographic patterns and drivers of PSF is essential for understanding the mechanisms underlying geographic plant diversity patterns. We compiled a large dataset containing 5969 observations of PSF from 202 studies to demonstrate the global patterns and drivers of PSF for woody and non-woody species. Overall, PSF was negative on average and was influenced by plant attributes and environmental settings. Woody species PSFs did not vary with latitude, but non-woody PSFs were more negative at higher latitudes. PSF was consistently more positive with increasing aridity for both woody and non-woody species, likely due to increased mutualistic microbes relative to soil-borne pathogens. These findings were consistent between field and greenhouse experiments, suggesting that PSF variation can be driven by soil legacies from climates. Our findings call for caution to use PSF as an explanation of the latitudinal diversity gradient and highlight that aridity can influence plant community dynamics and structure across broad scales through mediating plant-soil microbe interactions.

Making Full Use of TMSCF3: Deoxygenative Trifluoromethylation/Silylation of Amides.

As one of the most powerful trifluoromethylation reagents, (trifluoromethyl)trimethylsilane (TMSCF3) has been widely used for the synthesis of fluorine-containing molecules. However, to the best of our knowledge, the simultaneous incorporation of both TMS- and CF3- groups of this reagent onto the same carbon of the products has not been realized. Herein, we report an unprecedented SmI2/Sm promoted deoxygenative difunctionalization of amides with TMSCF3, in which both silyl and trifluoromethyl groups are incorporated into the final product, yielding α-silyl-α-trifluoromethyl amines with high efficiency. Notably, the silyl group could be further transformed into other functional groups, providing a new method for the synthesis of α-quaternary α-CF3-amines.

Triple-Phosphorescent Gold Nanoclusters Enabled by Isomerization of Terminal Thiouracils in the Surface Motifs.

Metal nanoclusters (NCs) hold great promise for expressing multipeak emission based on their well-defined total structure with diverse luminescent centers. Herein, we report the surface motif-dictated triple phosphorescence of Au NCs with dynamic color turning. The deprotonation-triggered isomerization of terminal thiouracils can evolve into a mutual transformation among their hierarchical motifs, thus serving a multipeak-emission expression with good tailoring. More importantly, the underlying electron transfer is thoroughly identified by excluding the radiative and nonradiative energy transfer, where electrons flow from the first phosphorescent state to the last two ones. The findings shed light on finely tailing motifs at the molecular level to motivate studies on customizable luminescence characteristics of metal NCs.

Effects of super-enhancers in cancer metastasis: mechanisms and therapeutic targets.

Metastasis remains the principal cause of cancer-related lethality despite advancements in cancer treatment. Dysfunctional epigenetic alterations are crucial in the metastatic cascade. Among these, super-enhancers (SEs), emerging as new epigenetic regulators, consist of large clusters of regulatory elements that drive the high-level expression of genes essential for the oncogenic process, upon which cancer cells develop a profound dependency. These SE-driven oncogenes play an important role in regulating various facets of metastasis, including the promotion of tumor proliferation in primary and distal metastatic organs, facilitating cellular migration and invasion into the vasculature, triggering epithelial-mesenchymal transition, enhancing cancer stem cell-like properties, circumventing immune detection, and adapting to the heterogeneity of metastatic niches. This heavy reliance on SE-mediated transcription delineates a vulnerable target for therapeutic intervention in cancer cells. In this article, we review current insights into the characteristics, identification methodologies, formation, and activation mechanisms of SEs. We also elaborate the oncogenic roles and regulatory functions of SEs in the context of cancer metastasis. Ultimately, we discuss the potential of SEs as novel therapeutic targets and their implications in clinical oncology, offering insights into future directions for innovative cancer treatment strategies.

Concurrent nimotuzumab and intensity-modulated radiotherapy for elderly patients with locally advanced nasopharyngeal carcinoma.

Because of the common physical condition, reduced organ function, and comorbidities, elderly patients with nasopharyngeal carcinoma (NPC) are often underrepresented in clinical trials. The optimal treatment of elderly patients with locally advanced NPC remains unclear. The purpose of this study was to evaluate the efficacy of concurrent nimotuzumab combined with intensity-modulated radiotherapy (IMRT) in elderly patients with locally advanced NPC. We conducted a single-arm, phase II trial for elderly patients with stage III-IVA NPC (according to UICC-American Joint Committee on Cancer TNM classification, 8th edition). All patients received concurrent nimotuzumab (200 mg/week, 1 week prior to IMRT) combined with IMRT. The primary end-point was complete response (CR) rate. The secondary end-points were survival, safety, and geriatric assessment. Between March 13, 2017 and November 12, 2018, 30 patients were enrolled. In total, 20 (66.7%) patients achieved CR, and objective response was observed in 30 (100.0%) patients 1 month after radiotherapy. The median follow-up time was 56.05 months (25th-75th percentile, 53.45-64.56 months). The 5-year locoregional relapse-free survival, distant metastasis-free survival, cancer-specific survival, disease-free survival, and overall survival were 89.4%, 86.4%, 85.9%, 76.5%, and 78.8%, respectively. Grade 3 mucositis occurred in 10 (33%) patients and grade 3 pneumonia in 3 (10%) patients. Concurrent nimotuzumab combined with IMRT is effective and well-tolerated for elderly patients with locally advanced NPC.

Dual-Track Multifunctional Bimetallic Metal-Organic Frameworks for Antibiotic Enrichment and Detection.

The improper use and overuse of antibiotics have led to significant burdens and detrimental effects on the environment, food supply, and human health. Herein, a magnetic solid-phase extraction program and an optical immunosensor based on bimetallic Ce/Zr-UiO 66 for the detection of antibiotics are developed. A magnetic Fe3O4@SiO2@Ce/Zr-UiO 66 metal-organic framework (MOF) is prepared to extract and enrich chloramphenicol from fish, wastewater, and urine samples, and a horseradish peroxidase (HRP)-Ce/Zr-UiO 66@bovine serum protein-chloramphenicol probe is used for the sensitive detection of chloramphenicol based on the dual-effect catalysis of Ce and HRP. In this manner, the application of Ce/Zr-UiO 66 in integrating sample pretreatment and antibiotic detection is systematically investigated and the associated mechanisms are explored. It is concluded that Ce/Zr-UiO 66 is a versatile dual-track material exhibiting high enrichment efficiency (6.37 mg g-1) and high sensitivity (limit of detection of 51.3 pg mL-1) for chloramphenicol detection and serving as a multifunctional MOF for safeguarding public health and hygiene.

Aerogels based on Bacterial Nanocellulose and their Applications.

Microbial cellulose stands out for its exceptional characteristics in the form of biofilms formed by highly interlocked fibrils, namely, bacterial nanocellulose (BNC). Concurrently, bio-based aerogels are finding uses in innovative materials owing to their lightweight, high surface area, physical, mechanical, and thermal properties. In particular, bio-based aerogels based on BNC offer significant opportunities as alternatives to synthetic or mineral counterparts. BNC aerogels are proposed for diverse applications, ranging from sensors to medical devices, as well as thermal and electroactive systems. Due to the fibrous nanostructure of BNC and the micro-porosity of BNC aerogels, these materials enable the creation of tailored and specialized designs. Herein, a comprehensive review of BNC-based aerogels, their attributes, hierarchical, and multiscale features are provided. Their potential across various disciplines is highlighted, emphasizing their biocompatibility and suitability for physical and chemical modification. BNC aerogels are shown as feasible options to advance material science and foster sustainable solutions through biotechnology.

Equilibrium Moisture Mediated Esterification Reaction to Achieve Over 100% Lignocellulosic Nanofibrils Yield.

Lignocellulosic nanofibrils (LCNFs) isolation is recognized as an efficient strategy for maximizing biomass utilization. Nevertheless, achieving a 100% yield presents a formidable challenge. Here, an esterification strategy mediated by the equilibrium moisture in biomass is proposed for LCNFs preparation without the use of catalysts, resulting in a yield exceeding 100%. Different from anhydrous chemical thermomechanical pulp (CTMP0%), the presence of moisture (moisture content of 7 wt%, denoted as CTMP7%) introduces a notably distinct process for the pretreatment of CTMP, comprising the initial disintegration and the post-esterification steps. The maleic acid, generated through maleic anhydride (MA) hydrolysis, degrades the recalcitrant lignin-carbohydrate complex (LCC) structures, resulting in esterified CTMP7% (E-CTMP7%). The highly grafted esters compensate for the mass loss resulting from the partial removal of hydrolyzed lignin and hemicellulose, ensuring a high yield. Following microfluidization, favorable LCNF7% with a high yield (114.4 ± 3.0%) and a high charge content (1.74 ± 0.09 mmol g-1) can be easily produced, surpassing most previous records for LCNFs. Additionally, LCNF7% presented highly processability for filaments, films, and 3D honeycomb structures preparation. These findings provide valuable insights and guidance for achieving a high yield in the isolation of LCNFs from biomass through the mediation of equilibrium moisture.

"Multi-in-One" Yolk-Shell Structured Nanoplatform Inducing Pyroptosis and Antitumor Immune Response Through Cascade Reactions.

Pyroptosis, a new mode of regulatory cell death, holds a promising prospect in tumor therapy. The occurrence of pyroptosis can trigger the release of damage-associated molecular patterns (DAMPs) and activate the antitumor immune response. Moreover, enhancing intracellular reactive oxygen species (ROS) generation can effectively induce pyroptosis. Herein, an integrated nanoplatform (hCZAG) based on zeolitic imidazolate framework-8 (ZIF-8) with Cu2+ and Zn2+ as active nodes and glucose oxidase (GOx) loading is constructed to evoke pyroptosis. GOx can effectively elevate intracellular hydrogen peroxide (H2O2) levels to regulate the unfavorable tumor microenvironment (TME). Cu2+ can be reduced to Cu+ by endogenous overexpressed GSH and both Cu2+ and Cu+ can exert Fenton-like activity to promote ROS generation and amplify oxidative stress. In addition, the accumulation of Cu2+ leads to the aggregation of lipoylated dihydrolipoamide S-acetyltransferase (DLAT), thus resulting in cuproptosis. Notably, the outburst of ROS induced by hCZAG activates Caspase-1 proteins, leads to the cleavage of gasdermin D (GSDMD), and induces pyroptosis. Pyroptosis further elicits an adaptive immune response, leading to immunogenic cell death (ICD). This study provides effective strategies for triggering pyroptosis-mediated immunotherapy and achieving improved therapeutic effects.

Spatial risk of Haemaphysalis longicornis borne Dabieshan tick virus (DBTV) in China.

The uncertainty and unknowability of emerging infectious diseases have caused many major public health and security incidents in recent years. As a new tick-borne disease, Dabieshan tick virus (DBTV) necessitate systematic epidemiological and spatial distribution analysis. In this study, tick samples from Liaoning Province were collected and used to evaluate distribution of DBTV in ticks. Outbreak points of DBTV and the records of the vector Haemaphysalis longicornis in China were collected and used to establish a prediction model using niche model combined with environmental factors. We found that H. longicornis and DBTV were widely distributed in Liaoning Province. The risk analysis results showed that the DBTV in the eastern provinces of China has a high risk, and the risk is greatly influenced by elevation, land cover, and meteorological factors. The risk geographical area predicted by the model is significantly larger than the detected positive areas, indicating that the etiological survey is seriously insufficient. This study provided molecular and important epidemiological evidence for etiological ecology of DBTV. The predicted high-risk areas indicated the insufficient monitoring and risk evaluation and the necessity of future monitoring and control work.

Influence of arterial transit time delays on the differentiation between tumor progression and pseudoprogression in glioblastoma by arterial spin labeling magnetic resonance imaging.

Arterial spin labeling (ASL) and dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) have shown potential for differentiating tumor progression from pseudoprogression. For pseudocontinuous ASL with a single postlabeling delay, the presence of delayed arterial transit times (ATTs) could affect the evaluation of ASL-MRI perfusion data. In this study, the influence of ATT artifacts on the perfusion assessment and differentiation between tumor progression and pseudoprogression were studied. This study comprised 66 adult patients (mean age 60 ± 13 years; 40 males) with a histologically confirmed glioblastoma who received postoperative radio (chemo)therapy. ASL-MRI and DSC-MRI scans were acquired at 3 months postradiotherapy as part of the standard clinical routine. These scans were visually scored regarding (i) the severity of ATT artifacts (%) on the ASL-MRI scans only, scored by two neuroradiologists; (ii) perfusion of the enhancing tumor lesion; and (iii) radiological evaluation of tumor progression versus pseudoprogression by one neuroradiologist. The final outcome was based on combined clinical and radiological follow-up until 9 months postradiotherapy. ATT artifacts were identified in all patients based on the mean scores of two raters. A significant difference between the radiological evaluation of ASL-MRI and DSC-MRI was observed only for ASL images with moderate ATT severity (30%-65%). The perfusion assessment showed ASL-MRI tending more towards hyperperfusion than DSC-MRI in the case of moderate ATT artifacts. In addition, there was a significant difference between the prediction of tumor progression with ASL-MRI and the final outcome in the case of severe ATT artifacts (McNemar test, p = 0.041). Despite using ASL imaging parameters close to the recommended settings, ATT artifacts frequently occur in patients with treated brain tumors. Those artifacts could hinder the radiological evaluation of ASL-MRI data and the detection of true disease progression, potentially affecting treatment decisions for patients with glioblastoma.

Sensitivity enhancement of an all-solid FPE sensor via a programmable Vernier effect.

All-solid, open-cavity fiber optic Fabry-Perot etalon (FPE) sensors possess a wide static pressure detection range, yet their low sensitivity significantly restricts their application. This study proposes a programmable Vernier effect to improve the gas pressure sensitivity of FPE sensors substantially. By effectively modulating the emission spectrum of a widely tunable laser using a variable optical attenuator (VOA), the emission spectrum at different modulation lengths is expected to produce an optical beating in conjunction with the transmission spectrum of the FPE sensor, thereby realizing the Vernier effect. Experimental results indicate that by utilizing the proposed programmable Vernier effect, the pressure sensitivity of the FPE sensor has increased to -612.21 pm/kPa, demonstrating an amplification in sensitivity of approximately -153 times, consistent with the theoretical results. Owing to the programmable Vernier effect, which flexibly enhances the sensitivity of the FPE sensor, this sensor demonstrates considerable potential for gas pressure monitoring under various extreme conditions.

Proportion of confluent B-Lines predicts respiratory support in term infants shortly after birth.

OBJECTIVE: To develop and evaluate the predictive value of a simplified lung ultrasound (LUS) method for forecasting respiratory support in term infants. METHODS: This observational, prospective, diagnostic accuracy study was conducted in a tertiary academic hospital between June and December 2023. A total of 361 neonates underwent LUS examination within 1 h of birth. The proportion of each LUS sign was utilized to predict their respiratory outcomes and compared with the LUS score model. After identifying the best predictive LUS sign, simplified models were created based on different scan regions. The optimal simplified model was selected by comparing its accuracy with both the full model and the LUS score model. RESULTS: After three days of follow-up, 91 infants required respiratory support, while 270 remained healthy. The proportion of confluent B-lines demonstrated high predictive accuracy for respiratory support, with an area under the curve (AUC) of 89.1% (95% confidence interval [CI]: 84.5-93.7%). The optimal simplified model involved scanning the R/L 1-4 region, yielding an AUC of 87.5% (95% CI: 82.6-92.3%). Both the full model and the optimal simplified model exhibited higher predictive accuracy compared to the LUS score model. The optimal cut-off value for the simplified model was determined to be 15.9%, with a sensitivity of 76.9% and specificity of 91.9%. CONCLUSIONS: The proportion of confluent B-lines in LUS can effectively predict the need for respiratory support in term infants shortly after birth and offers greater reliability than the LUS score model.

Anthraquinodimethane-Based Molecular Switches Tethered by Four-Arm Star-like Polymers.

Molecular switches that reversibly change their structures and physical properties are important for applications such as sensing and information processing at molecular scales. In order to avoid the intermolecular aggregation that is often detrimental to the stimuli-responses of molecular switches, previous studies of molecular switches have been often conducted in dilute solutions which are difficult for applications in solid-state devices. Here we report molecular design and synthesis that integrates anthraquinodimethane as molecular switching units into polymers with amenable processibility in solid states. Optical and electron spin resonance characterizations indicate that the four-arm polymers of poly(ϵ-caprolactone) or poly(D,L-lactide) tethered from anthraquinodimethane slow down the dynamics of the conformational switching between the folded and the twisted conformations, enhance the photoluminescence in solid states and impart materials with a small energy gap from singlet ground state to thermally accessible triplet state.