N-acetyltransferase 10 mediates cognitive dysfunction through the acetylation of GABABR1 mRNA in sepsis-associated encephalopathy.

Sepsis-associated encephalopathy (SAE) is a critical neurological complication of sepsis and represents a crucial factor contributing to high mortality and adverse prognosis in septic patients. This study explored the contribution of NAT10-mediated messenger RNA (mRNA) acetylation in cognitive dysfunction associated with SAE, utilizing a cecal ligation and puncture (CLP)-induced SAE mouse model. Our findings demonstrate that CLP significantly upregulates NAT10 expression and mRNA acetylation in the excitatory neurons of the hippocampal dentate gyrus (DG). Notably, neuronal-specific Nat10 knockdown improved cognitive function in septic mice, highlighting its critical role in SAE. Proteomic analysis, RNA immunoprecipitation, and real-time qPCR identified GABABR1 as a key downstream target of NAT10. Nat10 deletion reduced GABABR1 expression, and subsequently weakened inhibitory postsynaptic currents in hippocampal DG neurons. Further analysis revealed that microglia activation and the release of inflammatory mediators lead to the increased NAT10 expression in neurons. Microglia depletion with PLX3397 effectively reduced NAT10 and GABABR1 expression in neurons, and ameliorated cognitive dysfunction induced by SAE. In summary, our findings revealed that after CLP, NAT10 in hippocampal DG neurons promotes GABABR1 expression through mRNA acetylation, leading to cognitive dysfunction.

HighFold: accurately predicting structures of cyclic peptides and complexes with head-to-tail and disulfide bridge constraints.

In recent years, cyclic peptides have emerged as a promising therapeutic modality due to their diverse biological activities. Understanding the structures of these cyclic peptides and their complexes is crucial for unlocking invaluable insights about protein target-cyclic peptide interaction, which can facilitate the development of novel-related drugs. However, conducting experimental observations is time-consuming and expensive. Computer-aided drug design methods are not practical enough in real-world applications. To tackles this challenge, we introduce HighFold, an AlphaFold-derived model in this study. By integrating specific details about the head-to-tail circle and disulfide bridge structures, the HighFold model can accurately predict the structures of cyclic peptides and their complexes. Our model demonstrates superior predictive performance compared to other existing approaches, representing a significant advancement in structure-activity research. The HighFold model is openly accessible at https://github.com/hongliangduan/HighFold.

Author Correction: The Apostasia genome and the evolution of orchids.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

APEX-pHLA: A novel method for accurate prediction of the binding between exogenous short peptides and HLA class I molecules.

Human leukocyte antigen (HLA) molecules play critically significant role within the realm of immunotherapy due to their capacities to recognize and bind exogenous antigens such as peptides, subsequently delivering them to immune cells. Predicting the binding between peptides and HLA molecules (pHLA) can expedite the screening of immunogenic peptides and facilitate vaccine design. However, traditional experimental methods are time-consuming and inefficient. In this study, an efficient method based on deep learning was developed for predicting peptide-HLA binding, which treated peptide sequences as linguistic entities. It combined the architectures of textCNN and BiLSTM to create a deep neural network model called APEX-pHLA. This model operated without limitations related to HLA class I allele variants and peptide segment lengths, enabling efficient encoding of sequence features for both HLA and peptide segments. On the independent test set, the model achieved Accuracy, ROC_AUC, F1, and MCC is 0.9449, 0.9850, 0.9453, and 0.8899, respectively. Similarly, on an external test set, the results were 0.9803, 0.9574, 0.8835, and 0.7863, respectively. These findings outperformed fifteen methods previously reported in the literature. The accurate prediction capability of the APEX-pHLA model in peptide-HLA binding might provide valuable insights for future HLA vaccine design.

MSR1-dependent efferocytosis improved ischemia-reperfusion injury following aged-donor liver transplantation in mice by regulating the pro-resolving polarisation of macrophages.

Compared with young liver donors, aged liver donors are more susceptible to ischemia-reperfusion injury (IRI) following transplantation, which may be related to excessive inflammatory response and macrophage dysfunction, but the specific mechanism is unclear. Macrophage scavenger receptor 1 (MSR1) is a member of the scavenger receptor family, and plays an important regulatory role in inflammation response and macrophage function regulation. But its role in IRI following aged-donor liver transplantation is still unclear. This study demonstrates that MSR1 expression is decreased in macrophages from aged donor livers, inhibiting their efferocytosis and pro-resolving polarisation. Decreased MSR1 is responsible for the more severe IRI suffered by aged donor livers. Overexpression of MSR1 using F4/80-labelled AAV9 improved intrahepatic macrophage efferocytosis and promoted pro-resolving polarisation, ultimately ameliorating IRI following aged-donor liver transplantation. In vitro co-culture experiments further showed that overexpression of MSR1 promoted an increase in calcium concentration, which further activated the PI3K-AKT-GSK3ß pathway, and induced the upregulation of ß-catenin. Overall, MSR1-dependent efferocytosis promoted the pro-resolving polarisation of macrophages through the PI3K-AKT-GSK3ß pathway-induced up-regulating of ß-catenin leading to improved IRI following aged-donor liver transplantation.

Oridonin attenuates liver ischemia-reperfusion injury by suppressing PKM2/NLRP3-mediated macrophage pyroptosis.

BACKGROUND: The NOD-like receptor protein 3 (NLRP3) mediated pyroptosis of macrophages is closely associated with liver ischemia reperfusion injury (IRI). As a covalent inhibitor of NLRP3, Oridonin (Ori), has strong anti-inflammasome effect, but its effect and mechanisms for liver IRI are still unknown. METHODS: Mice and liver macrophages were treated with Ori, respectively. Co-IP and LC-MS/MS analysis of the interaction between PKM2 and NLRP3 in macrophages. Liver damage was detected using H&E staining. Pyroptosis was detected by WB, TEM, and ELISA. RESULTS: Ori ameliorated liver macrophage pyroptosis and liver IRI. Mechanistically, Ori inhibited the interaction between pyruvate kinase M2 isoform (PKM2) and NLRP3 in hypoxia/reoxygenation（H/R）-induced macrophages, while the inhibition of PKM2/NLRP3 reduced liver macrophage pyroptosis and liver IRI. CONCLUSION: Ori exerted protective effects on liver IRI via suppressing PKM2/NLRP3-mediated liver macrophage pyroptosis, which might become a potential therapeutic target in the clinic.

Comprehensive Analysis of Immune Responses to Neoadjuvant Immunotherapy in Resectable Non-small Cell Lung Cancer.

BACKGROUND: Neoadjuvant immunotherapy using immune checkpoint inhibitors (ICIs) has revolutionized the treatment of early stage non-small cell lung cancer (NSCLC). However, little is known about which patients are likely to benefit most from neoadjuvant immunotherapy. In this study, we performed a multiplatform analysis on samples from resectable NSCLC treated with neoadjuvant immunotherapy to explore molecular characteristics related to immune responses. PATIENTS AND METHODS: A total of 17 patients with resectable stage IB-IIIA NSCLC treated with neoadjuvant immunotherapy were included. A multiplex cytokine assay, bulk TCR sequencing in peripheral blood, and multiplexed immunohistochemistry were performed. RESULTS: Low levels of stromal cell-derived factor (SDF)-1alpha at baseline were associated with unfavorable disease-free survival (DFS). Patients with major pathologic response (MPR) showed a decrease in HGF after one cycle of neoadjuvant immunotherapy. An increase in IDO and IP-10 was observed in patients who developed immune-related adverse events (irAEs) after neoadjuvant immunotherapy. There were no correlations between irAEs and MPR or DFS. The MPR group presented a significant decrease in white blood cells and neutrophil count after neoadjuvant immunotherapy. The high peripheral baseline TCR convergence was correlated with MPR and favorable DFS in lung squamous cell carcinoma (LUSC) receiving neoadjuvant immunotherapy. Neoadjuvant immunotherapy led to a significant increase in CD4+, CD8+, and CD8+CD39+ T-cell infiltration in tumor areas. CONCLUSIONS: This study suggests the potential roles of cytokines and TCR convergence for predicting ICIs response in resectable NSCLC and LUSC. CD8+CD39+T cells and CD4+ T cells could be involved in the action of neoadjuvant immunotherapy.

Dual-domain mean-reverting diffusion model-enhanced temporal compressive coherent diffraction imaging.

Temporal compressive coherent diffraction imaging is a lensless imaging technique with the capability to capture fast-moving small objects. However, the accuracy of imaging reconstruction is often hindered by the loss of frequency domain information, a critical factor limiting the quality of the reconstructed images. To improve the quality of these reconstructed images, a method dual-domain mean-reverting diffusion model-enhanced temporal compressive coherent diffraction imaging (DMDTC) has been introduced. DMDTC leverages the mean-reverting diffusion model to acquire prior information in both frequency and spatial domain through sample learning. The frequency domain mean-reverting diffusion model is employed to recover missing information, while hybrid input-output algorithm is carried out to reconstruct the spatial domain image. The spatial domain mean-reverting diffusion model is utilized for denoising and image restoration. DMDTC has demonstrated a significant enhancement in the quality of the reconstructed images. The results indicate that the structural similarity and peak signal-to-noise ratio of images reconstructed by DMDTC surpass those obtained through conventional methods. DMDTC enables high temporal frame rates and high spatial resolution in coherent diffraction imaging.

Lycorine relieves the CCl4-induced liver fibrosis mainly via the JAK2/STAT3 and PI3K/AKT signaling pathways.

Liver fibrosis, a progressive process of fibrous scarring, results from the accumulation of extracellular matrix proteins (ECM). If left untreated, it often progresses to diseases such as cirrhosis and hepatocellular carcinoma. Lycorine, a natural alkaloid derived from medicinal plants, has shown diverse bioactivities by targeting JAK2/STAT3 signaling, but its pharmacological effects and potential molecular mechanisms in liver fibrosis remains largely unexplored. The purpose of this study is to elucidate the pharmacological activity and molecular mechanism of lycorine in anti-hepatic fibrosis. Findings indicate that lycorine significantly inhibited hepatic stellate cells (HSCs) activation by reducing the expression of α-SMA and collagen-1. In vivo, lycorine treatment alleviated carbon tetrachloride (CCl4) -induced mice liver fibrosis, improving liver function, decreasing ECM deposition, and inhibiting fibrosis-related markers' expression. Mechanistically, it was found that lycorine exerts protective activity through the JAK2/STAT3 and PI3K/AKT signaling pathways, as evidenced by transcriptome sequencing technology and small molecule inhibitors. These results underscore lycorine's potential as a therapeutic drug for liver fibrosis.

GSK3179106 ameliorates lipopolysaccharide-induced inflammation and acute lung injury by targeting P38 MAPK.

Acute lung injury (ALI) is a serious acute respiratory disease that can cause alveolar-capillary barrier disruption and pulmonary edema, respiratory failure and multiple organ dysfunction syndrome. However, there is no effective drugs in clinic until now. GSK3179106 has been reported can alleviate intestinal stress syndrome, but the protective effect of GSK3179106 on ALI has not been elucidated. The present study will evaluate the pharmacological activity of GSK3179106 on lipopolysaccharide (LPS)-induced inflammation and lung injury and clarify its underlying mechanism. We found that GSK3179106 significantly attenuated LPS-induced lung injury in vivo, accompanied by inhibited infiltration of inflammatory cells and reduced expression of inflammatory cytokines. Meanwhile, GSK3179106 dose-dependently reduced the LPS-induced IL-6 expression both in protein and gene levels in macrophages. Mechanistically, GSK3179106 could inhibited the phosphorylation of P38 MAPK induced by LPS. Importantly, results showed that there is a direct combination between GSK3179106 and P38 MAPK. Together, our findings not only clarified the anti-inflammatory activity of GSK3179106 but also discovered its new clinical indications. Therefore, compound GSK3179106 may be a potential candidate for the treatment of acute inflammatory diseases.

Predicting Drug-Drug Interactions Involving Rifampicin Using a Semi-mechanistic Hepatic Compartmental Model.

AIMS: To develop a semi-mechanistic hepatic compartmental model to predict the effects of rifampicin, a known inducer of CYP3A4 enzyme, on the metabolism of five drugs, in the hope of informing dose adjustments to avoid potential drug-drug interactions. METHODS: A search was conducted for DDI studies on the interactions between rifampicin and CYP substrates that met specific criteria, including the availability of plasma concentration-time profiles, physical and absorption parameters, pharmacokinetic parameters, and the use of healthy subjects at therapeutic doses. The semi-mechanistic model utilized in this study was improved from its predecessors, incorporating additional parameters such as population data (specifically for Chinese and Caucasians), virtual individuals, gender distribution, age range, dosing time points, and coefficients of variation. RESULTS: Optimal parameters were identified for our semi-mechanistic model by validating it with clinical data, resulting in a maximum difference of approximately 2-fold between simulated and observed values. PK data of healthy subjects were used for most CYP3A4 substrates, except for gilteritinib, which showed no significant difference between patients and healthy subjects. Dose adjustment of gilteritinib co-administered with rifampicin required a 3-fold increase of the initial dose, while other substrates were further tuned to achieve the desired drug exposure. CONCLUSIONS: The pharmacokinetic parameters AUCR and CmaxR of drugs metabolized by CYP3A4, when influenced by Rifampicin, were predicted by the semi-mechanistic model to be approximately twice the empirically observed values, which suggests that the semi-mechanistic model was able to reasonably simulate the effect. The doses of four drugs adjusted via simulation to reduce rifampicin interaction.

Association between non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio and obstructive sleep apnea: a cross-sectional study from NHANES.

BACKGROUND: Obstructive Sleep Apnea (OSA) is a widespread sleep disturbance linked to metabolic and cardiovascular conditions. The Non-High-Density Lipoprotein Cholesterol to High-Density Lipoprotein Cholesterol Ratios (NHHR) has been proposed as being a potential biomarker to gauge cardiovascular risk. However, its relationship with OSA remains unclear. METHODS: This survey investigated the link NHHR to OSA in American citizens aged 20 and older using information collected via the National Health and Nutrition Examination Survey (NHANES) during the years 2017 to 2020. Logistic regression models with multivariable adjustments were employed to assess this relationship. Nonlinear associations were explored using smooth curve fitting, with a two-part linear regression model identifying a threshold effect. Subgroup analyses were conducted to evaluate population-specific differences. RESULTS: The survey encompassed 6763 participants, with an average age of 50.75 ± 17.32. The average NHHR stood at 2.74, accompanied by a standard deviation of 1.34, while the average frequency of OSA was 49.93%. Upon adjusting for covariates, each unit increase in NHHR may be associated with a 9% rise in OSA incidence. (95% confidence intervals 1.04-1.14; P < 0.0001). Notably, a U-shaped curve depicted the NHHR-OSA relationship, with an inflection point at 4.12. Subgroup analyses revealed consistent associations, with educational attainment and diabetes status modifying the NHHR-OSA relationship. CONCLUSION: The study highlights NHHR as a potential tool for OSA prediction, presenting avenues for advanced risk evaluation, tailored interventions, personalized treatment approaches, and preventive healthcare.

Perfluorooctanoic acid (PFOA) induces cardiotoxicity by activating the Keap1/Nrf2 pathway in zebrafish (Danio rerio) embryos.

Perfluorooctanoic acid (PFOA), a perfluoroalkyl compound, is linked to congenital heart diseases, though its underlying mechanisms remain unclear. We hypothesized that PFOA induces cardiac defects through the inhibition of the Keap1/Nrf2 pathway, leading to oxidative damage in cardiomyocytes. In this study, zebrafish embryos exposed to PFOA showed significant cardiac malformations and dysfunction, characterized by excessive reactive oxygen species (ROS), malondialdehyde (MDA) production, decreased superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GSH-Px) activities. Additionally, we observed dysregulation in the expression of key cardiac development genes (vmhc, gata4, nkx2.5, and sox9b). PFOA also reduced the expression of keap1, nrf2, and ho-1. After overexpression of Nrf2, levels of ROS and MDA decreased, while levels of SOD, CAT, and GSH-Px increased. Additionally, cardiomyocyte apoptosis and cardiac malformations were alleviated. These findings have suggested that PFOA induces oxidative stress through Keap1/Nrf2 pathway inhibition, ultimately leading to cardiac defects.

Evaluating the toxicity effects of thiamethoxam and its main metabolite clothianidin to earthworms (Eisenia fetida) from the perspective of endogenous metabolites.

The widespread application of neonicotinoid insecticides (NNIs) has attracted widespread attention to their potential ecotoxicological effects. In this study, we systematically evaluated the toxic effects of thiamethoxam (TMX) and its metabolite clothianidin (CLO) on earthworms (Eisenia fetida). Specifically, the antioxidant system responses and endogenous metabolite metabolism responses in earthworms were analyzed in the temporal dimension after 7, 14, 21 and 28 days of exposure to TMX and CLO. The results found that TMX and CLO could inhibit the growth phenotype of earthworms and cause significant changes in antioxidant system related indicators. More importantly, we found that TMX and CLO could cause significant changes in the metabolic profiles of earthworms through NMR-based metabolomics. From the changes in endogenous metabolites, the toxicity effects of TMX on earthworms gradually increases with prolonged exposure time. Differently, the toxicity effects of CLO on earthworms is significantly higher than that of TMX in the early stages of exposure. Meanwhile, these impacts will not weaken with prolonged exposure time. Furthermore, the results of KEGG enrichment pathway analysis indicated that TMX and CLO could significantly interfere with energy homeostasis, redox homeostasis, osmotic regulation, amino acid metabolism and protein synthesis in earthworms. These findings further deepen our understanding of the ecotoxicological effects of NNIs on soil organism.

Unraveling the role of low-density lipoprotein-related genes in lung adenocarcinoma: Insights into tumor microenvironment and clinical prognosis.

BACKGROUND: The hypothesized link between low-density lipoprotein (LDL) and oncogenesis has garnered significant interest, yet its explicit impact on lung adenocarcinoma (LUAD) remains to be elucidated. This investigation aims to demystify the function of LDL-related genes (LRGs) within LUAD, endeavoring to shed light on the complex interplay between LDL and carcinogenesis. METHODS: Leveraging single-cell transcriptomics, we examined the role of LRGs within the tumor microenvironment (TME). The expression patterns of LRGs across diverse cellular phenotypes were delineated using an array of computational methodologies, including AUCell, UCell, singscore, ssGSEA, and AddModuleScore. CellChat facilitated the exploration of distinct cellular interactions within LDL_low and LDL_high groups. The findmarker utility, coupled with Pearson correlation analysis, facilitated the identification of pivotal genes correlated with LDL indices. An integrative approach to transcriptomic data analysis was adopted, utilizing a machine learning framework to devise an LDL-associated signature (LAS). This enabled the delineation of genomic disparities, pathway enrichments, immune cell dynamics, and pharmacological sensitivities between LAS stratifications. RESULTS: Enhanced cellular crosstalk was observed in the LDL_high group, with the CoxBoost+Ridge algorithm achieving the apex c-index for LAS formulation. Benchmarking against 144 extant LUAD models underscored the superior prognostic acuity of LAS. Elevated LAS indices were synonymous with adverse outcomes, diminished immune surveillance, and an upsurge in pathways conducive to neoplastic proliferation. Notably, a pronounced susceptibility to paclitaxel and gemcitabine was discerned within the high-LAS cohort, delineating prospective therapeutic corridors. CONCLUSION: This study elucidates the significance of LRGs within the TME and introduces an LAS for prognostication in LUAD patients. Our findings accentuate putative therapeutic targets and elucidate the clinical ramifications of LAS deployment.

CCDN-DETR: A Detection Transformer Based on Constrained Contrast Denoising for Multi-Class Synthetic Aperture Radar Object Detection.

The effectiveness of the SAR object detection technique based on Convolutional Neural Networks (CNNs) has been widely proven, and it is increasingly used in the recognition of ship targets. Recently, efforts have been made to integrate transformer structures into SAR detectors to achieve improved target localization. However, existing methods rarely design the transformer itself as a detector, failing to fully leverage the long-range modeling advantages of self-attention. Furthermore, there has been limited research into multi-class SAR target detection. To address these limitations, this study proposes a SAR detector named CCDN-DETR, which builds upon the framework of the detection transformer (DETR). To adapt to the multiscale characteristics of SAR data, cross-scale encoders were introduced to facilitate comprehensive information modeling and fusion across different scales. Simultaneously, we optimized the query selection scheme for the input decoder layers, employing IOU loss to assist in initializing object queries more effectively. Additionally, we introduced constrained contrastive denoising training at the decoder layers to enhance the model's convergence speed and improve the detection of different categories of SAR targets. In the benchmark evaluation on a joint dataset composed of SSDD, HRSID, and SAR-AIRcraft datasets, CCDN-DETR achieves a mean Average Precision (mAP) of 91.9%. Furthermore, it demonstrates significant competitiveness with 83.7% mAP on the multi-class MSAR dataset compared to CNN-based models.

Quantifying Atomically Dispersed Catalysts Using Deep Learning Assisted Microscopy.

The catalytic performance of atomically dispersed catalysts (ADCs) is greatly influenced by their atomic configurations, such as atom-atom distances, clustering of atoms into dimers and trimers, and their distributions. Scanning transmission electron microscopy (STEM) is a powerful technique for imaging ADCs at the atomic scale; however, most STEM analyses of ADCs thus far have relied on human labeling, making it difficult to analyze large data sets. Here, we introduce a convolutional neural network (CNN)-based algorithm capable of quantifying the spatial arrangement of different adatom configurations. The algorithm was tested on different ADCs with varying support crystallinity and homogeneity. Results show that our algorithm can accurately identify atom positions and effectively analyze large data sets. This work provides a robust method to overcome a major bottleneck in STEM analysis for ADC catalyst research. We highlight the potential of this method to serve as an on-the-fly analysis tool for catalysts in future in situ microscopy experiments.

[Research progress on the relationship between TRAF6 and neurodegenerative diseases].

Given the increasing trend of aging population in the world, neurodegenerative diseases (NDDs), a common type of diseases that mostly occur in the elderly, have attracted much more attention. It has been shown that tumor necrosis factor receptor-associated factor 6 (TRAF6) is involved in the regulation of neuroinflammation, an important pathological feature of NDDs, and affects the occurrence and development of NDDs. Most importantly, the regulatory effect of TRAF6 is related to its ubiquitination. Therefore, in the present paper, the molecular structure, biological function, and ubiquitination mechanism of TRAF6, and its relationship with some common NDDs, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, and amyotrophic lateral sclerosis, were analyzed and summarized. The possible molecular mechanisms by which TRAF6 regulates the occurrence of NDDs were also elucidated, providing a theoretical basis for exploring the etiology and treatment of NDDs.

Nomilin Reversed Cardiotoxicity Caused by Co-exposure to Zearalenone and Deoxynivalenol via the Keap1/Nrf2 Signaling Pathway in Zebrafish.

The contamination of food and feed by mycotoxins, particularly zearalenone (ZEA) and deoxynivalenol (DON), is a global issue. Prenatal exposure to ZEA and DON can result in congenital cardiac malformations in fetuses. Addressing the prevention and mitigation of embryonic cardiotoxicity caused by these toxins is crucial. Citrus limonoid nomilin (NOM) is an extract known for its pathological properties in various diseases. This study investigated the potential mechanism of NOM in mitigating cardiotoxicity caused by ZEA and DON co-exposure in a zebrafish model. The findings indicated that NOM pretreatment alleviated cardiac developmental toxicity induced by ZEA and DON and normalized the expression of key genes involved in heart development, including gata4, vmhc, nkx2.5, and sox9b. Co-exposure to NOM, ZEA, and DON enhanced SOD and catalase activity, increased glutathione levels, and reduced ROS and malondialdehyde production. Furthermore, NOM reduced cardiac oxidative damage by activating the Keap1/Nrf2 signaling pathway. In summary, this study offers new insights for preventive interventions against congenital heart disease caused by mycotoxin exposure.

Identification of nsLTP family in Chinese white pear (Pyrus bretschneideri) reveals its potential roles in russet skin formation.

MAIN CONCLUSION: Identification of PbLTP genes in pear and functional characterization of PbLTP4 in the transport of suberin monomers of russet skin formation. Non-specific lipid-transfer protein (nsLTP) is an abundant and diverse alkaline small molecule protein in the plant kingdom with complex and diverse biophysiological functions, such as transfer of phospholipids, reproductive development, pathogen defence and abiotic stress response. Up to now, only a tiny fraction of nsLTPs have been functionally identified, and the distribution of nsLTPs in pear (Pyrus bretschneideri) (PbLTPs) has not been fully characterized. In this study, the genome-wide analysis of the nsLTP gene family in the pear genome identified 67 PbLTP proteins, which could be divided into six types (1, 2, C, D, E, and G). Similar intron/exon structural patterns were observed in the same type, strongly supporting their close evolutionary relationship. In addition, PbLTP4 was highly expressed in russet pear skin compared with green skin, which was located in the plasma membrane. Coexpression network analysis showed that PbLTP4 closely related to suberin biosynthetic genes. The biological function of PbLTP4 in promoting suberification has been demonstrated by overexpression in Arabidopsis. Identification of suberin monomers showed that PbLTP4 promotes suberification by regulating 9,12-octadecadienoic acid and hexadecanoic acid transport. These results provide helpful insights into the characteristics of PbLTP genes and their biological function in the transport of suberin monomers of russet skin formation.