Inhibition of LSD1 via SP2509 attenuated the progression of rheumatoid arthritis.

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by synovial hyperplasia, pannus formation, and cartilage and bone destruction. Lysine-specific demethylase 1 (LSD1), an enzyme involved in transcriptional regulation, has an unclear role in synovial inflammation, fibroblast-like synoviocytes migration, and invasion during RA pathogenesis. In this study, we observed increased LSD1 expression in RA synovial tissues and in TNF-α-stimulated MH7A cells. SP2509, an LSD1 antagonist, directly reduced LSD1 expression and reversed the elevated levels of proteins associated with inflammation, apoptosis, proliferation, and autophagy induced by TNF-α. Furthermore, SP2509 inhibited the migratory capacity of MH7A cells, which was enhanced by TNF-α. In CIA models, SP2509 treatment ameliorated RA development, reducing the expression of pro-inflammatory cytokines and alleviating joint pathological symptoms. These findings underscore the significance of LSD1 in RA and propose the therapeutic potential of SP2509.

A deep learning based multi-model approach for predicting drug-like chemical compound's toxicity.

Ensuring the safety and efficacy of chemical compounds is crucial in small-molecule drug development. In the later stages of drug development, toxic compounds pose a significant challenge, losing valuable resources and time. Early and accurate prediction of compound toxicity using deep learning models offers a promising solution to mitigate these risks during drug discovery. In this study, we present the development of several deep-learning models aimed at evaluating different types of compound toxicity, including acute toxicity, carcinogenicity, hERG_cardiotoxicity (the human ether-a-go-go related gene caused cardiotoxicity), hepatotoxicity, and mutagenicity. To address the inherent variations in data size, label type, and distribution across different types of toxicity, we employed diverse training strategies. Our first approach involved utilizing a graph convolutional network (GCN) regression model to predict acute toxicity, which achieved notable performance with Pearson R 0.76, 0.74, and 0.65 for intraperitoneal, intravenous, and oral administration routes, respectively. Furthermore, we trained multiple GCN binary classification models, each tailored to a specific type of toxicity. These models exhibited high area under the curve (AUC) scores, with an impressive AUC of 0.69, 0.77, 0.88, and 0.79 for predicting carcinogenicity, hERG_cardiotoxicity, mutagenicity, and hepatotoxicity, respectively. Additionally, we have used the approved drug dataset to determine the appropriate threshold value for the prediction score in model usage. We integrated these models into a virtual screening pipeline to assess their effectiveness in identifying potential low-toxicity drug candidates. Our findings indicate that this deep learning approach has the potential to significantly reduce the cost and risk associated with drug development by expediting the selection of compounds with low toxicity profiles. Therefore, the models developed in this study hold promise as critical tools for early drug candidate screening and selection.

Small-Molecule Inhibitors of TIPE3 Protein Identified through Deep Learning Suppress Cancer Cell Growth In Vitro.

Tumor necrosis factor-α-induced protein 8-like 3 (TNFAIP8L3 or TIPE3) functions as a transfer protein for lipid second messengers. TIPE3 is highly upregulated in several human cancers and has been established to significantly promote tumor cell proliferation, migration, and invasion and inhibit the apoptosis of cancer cells. Thus, inhibiting the function of TIPE3 is expected to be an effective strategy against cancer. The advancement of artificial intelligence (AI)-driven drug development has recently invigorated research in anti-cancer drug development. In this work, we incorporated DFCNN, Autodock Vina docking, DeepBindBC, MD, and metadynamics to efficiently identify inhibitors of TIPE3 from a ZINC compound dataset. Six potential candidates were selected for further experimental study to validate their anti-tumor activity. Among these, three small-molecule compounds (K784-8160, E745-0011, and 7238-1516) showed significant anti-tumor activity in vitro, leading to reduced tumor cell viability, proliferation, and migration and enhanced apoptotic tumor cell death. Notably, E745-0011 and 7238-1516 exhibited selective cytotoxicity toward tumor cells with high TIPE3 expression while having little or no effect on normal human cells or tumor cells with low TIPE3 expression. A molecular docking analysis further supported their interactions with TIPE3, highlighting hydrophobic interactions and their shared interaction residues and offering insights for designing more effective inhibitors. Taken together, this work demonstrates the feasibility of incorporating deep learning and MD simulations in virtual drug screening and provides inhibitors with significant potential for anti-cancer drug development against TIPE3-.

Radiomics model based on intratumoral and peritumoral features for predicting major pathological response in non-small cell lung cancer receiving neoadjuvant immunochemotherapy.

Objective: To establish a radiomics model based on intratumoral and peritumoral features extracted from pre-treatment CT to predict the major pathological response (MPR) in patients with non-small cell lung cancer (NSCLC) receiving neoadjuvant immunochemotherapy. Methods: A total of 148 NSCLC patients who underwent neoadjuvant immunochemotherapy from two centers (SRRSH and ZCH) were retrospectively included. The SRRSH dataset (n=105) was used as the training and internal validation cohort. Radiomics features of intratumoral (T) and peritumoral regions (P1 = 0-5mm, P2 = 5-10mm, and P3 = 10-15mm) were extracted from pre-treatment CT. Intra- and inter- class correlation coefficients and least absolute shrinkage and selection operator were used to feature selection. Four single ROI models mentioned above and a combined radiomics (CR: T+P1+P2+P3) model were established by using machine learning algorithms. Clinical factors were selected to construct the combined radiomics-clinical (CRC) model, which was validated in the external center ZCH (n=43). The performance of the models was assessed by DeLong test, calibration curve and decision curve analysis. Results: Histopathological type was the only independent clinical risk factor. The model CR with eight selected radiomics features demonstrated a good predictive performance in the internal validation (AUC=0.810) and significantly improved than the model T (AUC=0.810 vs 0.619, p<0.05). The model CRC yielded the best predictive capability (AUC=0.814) and obtained satisfactory performance in the independent external test set (AUC=0.768, 95% CI: 0.62-0.91). Conclusion: We established a CRC model that incorporates intratumoral and peritumoral features and histopathological type, providing an effective approach for selecting NSCLC patients suitable for neoadjuvant immunochemotherapy.

The cGAS-Ku80 complex regulates the balance between two end joining subpathways.

As the major DNA sensor that activates the STING-TBK1 signaling cascade, cGAS is mainly present in the cytosol. A number of recent reports have indicated that cGAS also plays critical roles in the nucleus. Our previous work demonstrated for the first time that cGAS is translocated to the nucleus upon the occurrence of DNA damage and inhibits homologous recombination (HR), one of the two major pathways of DNA double strand break (DSB) repair. However, whether nuclear cGAS regulates the other DSB repair pathway, nonhomologous end joining (NHEJ), which can be further divided into the less error-prone canonical NHEJ (c-NHEJ) and more mutagenic alternative NHEJ (alt-NHEJ) subpathways, has not been characterized. Here, we demonstrated that cGAS tipped the balance of the two NHEJ subpathways toward c-NHEJ. Mechanistically, the cGAS-Ku80 complex enhanced the interaction between DNA-PKcs and the deubiquitinase USP7 to improve DNA-PKcs protein stability, thereby promoting c-NHEJ. In contrast, the cGAS-Ku80 complex suppressed alt-NHEJ by directly binding to the promoter of Polθ to suppress its transcription. Together, these findings reveal a novel function of nuclear cGAS in regulating DSB repair, suggesting that the presence of cGAS in the nucleus is also important in the maintenance of genome integrity.

In silico analysis of the wheat BBX gene family and identification of candidate genes for seed dormancy and germination.

BACKGROUND: B-box (BBX) proteins are a type of zinc finger proteins containing one or two B-box domains. They play important roles in development and diverse stress responses of plants, yet their roles in wheat remain unclear. RESULTS: In this study, 96 BBX genes were identified in the wheat genome and classified into five subfamilies. Subcellular localization prediction results showed that 68 TaBBXs were localized in the nucleus. Protein interaction prediction analysis indicated that interaction was one way that these proteins exerted their functions. Promoter analysis indicated that TaBBXs may play important roles in light signal, hormone, and stress responses. qRT-PCR analysis revealed that 14 TaBBXs were highly expressed in seeds compared with other tissues. These were probably involved in seed dormancy and germination, and their expression patterns were investigated during dormancy acquisition and release in the seeds of wheat varieties Jing 411 and Hongmangchun 21, showing significant differences in seed dormancy and germination phenotypes. Subcellular localization analysis confirmed that the three candidates TaBBX2-2 A, TaBBX4-2 A, and TaBBX11-2D were nuclear proteins. Transcriptional self-activation experiments further demonstrated that TaBBX4-2A was transcriptionally active, but TaBBX2-2A and TaBBX11-2D were not. Protein interaction analysis revealed that TaBBX2-2A, TaBBX4-2A, and TaBBX11-2D had no interaction with each other, while TaBBX2-2A and TaBBX11-2D interacted with each other, indicating that TaBBX4-2A may regulate seed dormancy and germination by transcriptional regulation, and TaBBX2-2A and TaBBX11-2D may regulate seed dormancy and germination by forming a homologous complex. CONCLUSIONS: In this study, the wheat BBX gene family was identified and characterized at the genomic level by bioinformatics analysis. These observations provide a theoretical basis for future studies on the functions of BBXs in wheat and other species.

Functional analysis of a wheat class III peroxidase gene, TaPer12-3A, in seed dormancy and germination.

BACKGROUND: Class III peroxidases (PODs) perform crucial functions in various developmental processes and responses to biotic and abiotic stresses. However, their roles in wheat seed dormancy (SD) and germination remain elusive. RESULTS: Here, we identified a wheat class III POD gene, named TaPer12-3A, based on transcriptome data and expression analysis. TaPer12-3A showed decreasing and increasing expression trends with SD acquisition and release, respectively. It was highly expressed in wheat seeds and localized in the endoplasmic reticulum and cytoplasm. Germination tests were performed using the transgenic Arabidopsis and rice lines as well as wheat mutant mutagenized with ethyl methane sulfonate (EMS) in Jing 411 (J411) background. These results indicated that TaPer12-3A negatively regulated SD and positively mediated germination. Further studies showed that TaPer12-3A maintained H2O2 homeostasis by scavenging excess H2O2 and participated in the biosynthesis and catabolism pathways of gibberellic acid and abscisic acid to regulate SD and germination. CONCLUSION: These findings not only provide new insights for future functional analysis of TaPer12-3A in regulating wheat SD and germination but also provide a target gene for breeding wheat varieties with high pre-harvest sprouting resistance by gene editing technology.

Deep Learning-Based construction of a Drug-Like compound database and its application in virtual screening of HsDHODH inhibitors.

The process of virtual screening relies heavily on the databases, but it is disadvantageous to conduct virtual screening based on commercial databases with patent-protected compounds, high compound toxicity and side effects. Therefore, this paper utilizes generative recurrent neural networks (RNN) containing long short-term memory (LSTM) cells to learn the properties of drug compounds in the DrugBank, aiming to obtain a new and virtual screening compounds database with drug-like properties. Ultimately, a compounds database consisting of 26,316 compounds is obtained by this method. To evaluate the potential of this compounds database, a series of tests are performed, including chemical space, ADME properties, compound fragmentation, and synthesizability analysis. As a result, it is proved that the database is equipped with good drug-like properties and a relatively new backbone, its potential in virtual screening is further tested. Finally, a series of seedling compounds with completely new backbones are obtained through docking and binding free energy calculations.

A wheat heat shock transcription factor gene, TaHsf-7A, regulates seed dormancy and germination.

Heat shock transcription factors (Hsfs) play multifaceted roles in plant growth, development, and responses to environmental factors. However, their involvement in seed dormancy and germination processes has remained elusive. In this study, we identified a wheat class B Hsf gene, TaHsf-7A, with higher expression in strong-dormancy varieties compared to weak-dormancy varieties during seed imbibition. Specifically, TaHsf-7A expression increased during seed dormancy establishment and subsequently declined during dormancy release. Through the identification of a 1-bp insertion (ins)/deletion (del) variation in the coding region of TaHsf-7A among wheat varieties with different dormancy levels, we developed a CAPS marker, Hsf-7A-1319, resulting in two allelic variations: Hsf-7A-1319-ins and Hsf-7A-1319-del. Notably, the allele Hsf-7A-1319-ins correlated with a reduced seed germination rate and elevated dormancy levels, while Hsf-7A-1319-del exhibited the opposite trend across 175 wheat varieties. The association of TaHsf-7A allelic status with seed dormancy and germination levels was confirmed in various genetically modified species, including Arabidopsis, rice, and wheat. Results from the dual luciferase assay demonstrated notable variations in transcriptional activity among transformants harboring distinct TaHsf-7A alleles. Furthermore, the levels of abscisic acid (ABA) and gibberellin (GA), along with the expression levels of ABA and GA biosynthesis genes, showed significant differences between transgenic rice lines carrying different alleles of TaHsf-7A. These findings represent a significant step towards a comprehensive understanding of TaHsf-7A's involvement in the dormancy and germination processes of wheat seeds.

A New Co(II)-coordination Polymer: Fluorescence Performances, Loaded with Paclitaxel-hydrogel on Breast Cancer and Molecular Docking Study.

In the current context of the increasing incidence of breast cancer, we aim to develop an efficient drug carrier for breast cancer by constructing an innovative complex consisting of a metal-organic framework (MOF) and a hydrogel. The aim of this initiative is to provide new ideas and tools for breast cancer treatment strategies through scientific research, so as to address the current challenges in breast cancer treatment. In the present study, by employment of a new Co(II)-based coordination polymer with the chemical formula of [Co(H2O)(CH3OH)L]n (1) (H2L = 5-(1 H-tetrazol-5-yl)nicotinic acid) was solvothermally synthesized by reaction of Co(NO3)2·6H2O a mixed solvent of MeOH and water. The characteristics of ligand-based absorption and emission, as unveiled by ultraviolet and fluorescence spectroscopy tests, offer insights into the distinctive electronic transitions and structural features originating from the ligand in compound 1. Using natural polysaccharide hyaluronic acid (HA) and carboxymethyl chitosan (CMCS) as raw materials, HA/CMCS hydrogels were successfully prepared by chemical method and their internal morphology was studied by scanning electron microscopy. Using paclitaxel as a drug model, we further designed and synthesized a novel metal gel particle-loaded paclitaxel drug and evaluated its inhibitory effect on breast cancer cells. Finally, the hypothesized interactions between the complex and the receptor have been confirmed through molecular docking simulation, and multiple polar interactions have been verified, which further proves the potential anti-cancer capability and excellent bioactivity. Based on this, this composite material prepared from a novel Co(II)-coordinated polymer with paclitaxel hydrogel could provide a useful pathway for the identification and treatment of breast cancer.

Quantitative detection of T315I mutations of BCR::ABL1 using digital droplet polymerase chain reaction.

BACKGROUND: T315I mutations of the BCR::ABL1 gene lead to resistance to tyrosine kinase inhibitors (TKIs). This study evaluated the performance of digital droplet polymerase chain reaction (ddPCR) in quantifying T315I mutations and their frequency in Philadelphia chromosome (Ph) positive hematological patients. METHODS: The course of disease and BCR::ABL1 fusion transcripts (e13a2, e14a2 and e1a2) were retrospectively reviewed in 21 patients with acute lymphoblastic leukemia (ALL) and 85 patients with chronic myeloid leukemia (CML). T315I mutation analysis was carried out using ddPCR and the limit of detection was assessed using mutant T315I DNA at varying variant allele fractions. RESULTS: T315I mutations were found in two ALL patients and one CML patient without remission in molecular biology and with mutation burdens of 29.20%, 40.85%, and 3.00%, respectively. The mutation burden of ALL patients was higher than that of CML patients, but there was no significant difference between the two (p-value = 0.0536). The test's limit of detection was 0.02% with a correlation coefficient greater than 0.99 between the expected and actual detection abundances. CONCLUSION: T315I mutations have a high incidence in Ph-positive ALL patients even if the course of disease is short. In molecular biology, T315I mutation detection is indicated for CML patients not in remission.

Cysteine protease inhibitor S promotes lymph node metastasis of esophageal cancer cells via VEGF-MAPK/ERK-MMP9/2 pathway.

Cysteine protease inhibitor S (CST4) plays a pivotal role in the regulation of growth, invasion, and metastasis of a variety of malignancies. However, the potential mechanism behind how CST4 contributes to CST4 in lymph node metastasis (LNM) and tumor-associated lymphangiogenesis of esophageal cancer (EC) cells has not been elucidated previously. Short hairpin RNA technique was utilized to upregulate the CST4 gene expression. Different experiments, including the tubule formation assay and immunofluorescence, were conducted to observe the cellular behavior. Enzyme-linked immunosorbent assay (ELISA) and Western blot analyses were employed to determine the expression levels of relevant proteins. In our study, we discovered that high expression of CST4 in EC cells had multiple effects. It stimulated cell proliferation, invasion, and migration and caused epithelial-mesenchymal transition (EMT). Moreover, it also inhibited the apoptosis of EC cells and caused them to stagnate in the G2/M phase. High expression of CST4 promoted the secretion of lymphangiogenic markers (TGFß1, VEGF, VEGF-C/D) in EC cells. In addition, high expression of CST4 in EC cells not only enhanced the proliferation and migration of HLECs, but also stimulated the lumen formation and F-actin expression and rearrangement of HLECs. The elevated expression of CST4 also facilitated the secretion of p-ERK1/2, MMP9, and MMP-2 in HLECs. However, various tumor-promoting effects of high expression of CST4 on HLECs could be inhibited by VEGF inhibitors in EC cells. Overall, our findings indicate that CST4 plays a significant role in the accumulation, migration, and EMT of EC cells. CST4 can activate the VEGF-MAPK/ERK-MMP9/2 signaling axis to promote LNM and lymphangiogenesis in EC.

Identification of genetic loci and candidate genes underlying freezing tolerance in wheat seedlings.

KEY MESSAGE: Ten stable loci for freezing tolerance (FT) in wheat were detected by genome-wide association analysis. The putative candidate gene TaRPM1-7BL underlying the major locus QFT.ahau-7B.2 was identified and validated. Frost damage restricts wheat growth, development, and geographical distribution. However, the genetic mechanism of freezing tolerance (FT) remains unclear. Here, we evaluated FT phenotypes of 245 wheat varieties and lines, and genotyped them using a Wheat 90 K array. The association analysis showed that ten stable loci were significantly associated with FT (P < 1 × 10-4), and explained 6.45-26.33% of the phenotypic variation. In particular, the major locus QFT.ahau-7B.2 was consistently related to all nine sets of FT phenotypic data. Based on five cleaved amplified polymorphic sequence (CAPS) markers closely linked to QFT.ahau-7B.2, we narrowed down the target region to the 570.67-571.16 Mb interval (0.49 Mb) on chromosome 7B, in which four candidate genes were annotated. Of these, only TaRPM1-7BL exhibited consistent differential expression after low temperature treatment between freezing-tolerant and freezing-sensitive varieties. The results of cloning and whole-exome capture sequencing indicated that there were two main haplotypes for TaRPM1-7BL, including freezing-tolerant Hap1 and freezing-sensitive Hap2. Based on the representative SNP (+1956, A/G), leading to an amino acid change in the NBS domain, a CAPS marker (CAPS-TaRPM1-7BL) was developed and validated in 431 wheat varieties (including the above 245 materials) and 318 F2 lines derived from the cross of 'Annong 9267' (freezing-tolerant) × 'Yumai 9' (freezing-sensitive). Subsequently, the TaRPM1-7BL gene was silenced in 'Yumai 9' by virus-induced gene silencing (VIGS), and these silenced wheat seedlings exhibited enhanced FT phenotypes, suggesting that TaRPM1-7BL negatively regulates FT. These findings are valuable for understanding the complex genetic basis of FT in wheat.

Remnant cholesterol traits and risk of stroke: A multivariable Mendelian randomization study.

Observational epidemiological studies have reported a relationship between remnant cholesterol and stroke. However, the results are inconclusive, and causality remains unclear due to confounding or reverse causality. Our objective in this study was to investigate the causal relevance of remnant cholesterol and the risk of stroke and its subtypes using the Mendelian randomization (MR) approach. Genome-wide association studies (GWASs) including 115,082 European individuals (UK Biobank) were used to identify instruments for remnant cholesterol, including intermediate-density lipoprotein (IDL) cholesterol and very-low-density lipoprotein (VLDL) cholesterol. Summary-level data for total stroke, intracerebral hemorrhage, subarachnoid hemorrhage, ischemic stroke (IS), and IS subtypes were obtained from GWAS meta-analyses conducted by the MEGASTROKE consortium. Univariable and multivariable MR analyses were performed. The GWAS identified multiple single-nucleotide polymorphisms after clumping for remnant cholesterol (n = 52), IDL cholesterol (n = 62), and VLDL cholesterol (n = 67). Assessed individually using MR, remnant cholesterol (weighted median: odds ratio [OR] 1.32 per 1-SD higher trait; 95% CI: 1.04-1.67; P = 0.024) had effect estimates consistent with a higher risk of LAS-IS, driven by IDL cholesterol (OR 1.32; 95% CI: 1.04-1.68; P = 0.022). In multivariable MR, IDL cholesterol (OR 1.46; 95% CI: 1.10-1.93; P = 0.009) retained a robust effect on LAS-IS after controlling for VLDL cholesterol and high-density lipoprotein cholesterol. The MR analysis did not indicate causal associations between remnant cholesterol and other stroke subtypes. This study suggests that remnant cholesterol is causally associated with the risk of LAS-IS driven by IDL cholesterol.

Prediction of microvascular invasion and pathological differentiation of hepatocellular carcinoma based on a deep learning model.

PURPOSE: To develop a deep learning (DL) model based on preoperative contrast-enhanced computed tomography (CECT) images to predict microvascular invasion (MVI) and pathological differentiation of hepatocellular carcinoma (HCC). METHODS: This retrospective study included 640 consecutive patients who underwent surgical resection and were pathologically diagnosed with HCC at two medical institutions from April 2017 to May 2022. CECT images and relevant clinical parameters were collected. All the data were divided into 368 training sets, 138 test sets and 134 validation sets. Through DL, a segmentation model was used to obtain a region of interest (ROI) of the liver, and a classification model was established to predict the pathological status of HCC. RESULTS: The liver segmentation model based on the 3D U-Network had a mean intersection over union (mIoU) score of 0.9120 and a Dice score of 0.9473. Among all the classification prediction models based on the Swin transformer, the fusion models combining image information and clinical parameters exhibited the best performance. The area under the curve (AUC) of the fusion model for predicting the MVI status was 0.941, its accuracy was 0.917, and its specificity was 0.908. The AUC values of the fusion model for predicting poorly differentiated, moderately differentiated and highly differentiated HCC based on the test set were 0.962, 0.957 and 0.996, respectively. CONCLUSION: The established DL models established can be used to noninvasively and effectively predict the MVI status and the degree of pathological differentiation of HCC, and aid in clinical diagnosis and treatment.

A new method to estimate the histological stage of primary biliary cholangitis.

OBJECTIVE: To analyze the diagnostic efficacy of the periportal hypoechoic band (PHB) in the histological stage of patients with primary biliary cholangitis (PBC). METHODS: We prospectively included 77 cases of PBC pathologically or clinically confirmed, and high-frequency ultrasound (HFUS) measurements of the PHB were performed in all included patients. Ludwig staging system of histopathology was used as the gold standard. RESULTS: The width of the PHB was positively correlated with histological staging (r = 0.844, p < 0.001). By area under the receiving operating characteristic curve (AUROC), the best cutoff value for PHB for advanced stage (≥ stage 3) was 2.4 mm (AUROC: 0.934; 95%CI: 0.841-0.981) and 0.93 for sensitivity, and 0.91 for specificity, the concordance rates of PHB vs. liver biopsy was 90.3%. The correct rate for early-stage PBC was 87.9% and for the progressive stage was 93.1%. After multi-factor regression analysis, the PHB (OR = 1.331, CI = 1.105-1.603, p = 0.003) and total bilirubin (OR = 1.156, CI = 1.041-1.285, p = 0.007) were independent influencing factors for progressive PBC. CONCLUSIONS: Measurement of the PHB to assess advanced PBC is a simple and effective method. This method may complement current methods for the histological staging assessment of patients with PBC. REGISTRATION: Clinical trial registration: ChiCTR 2000032053, 2020/04/19. CLINICAL RELEVANCE STATEMENT: The measurement of periportal hypoechoic band (PHB) provides a simple and easy assessment of the degree of disease progression in patients with PBC and provides an important clinical reference in predicting the histological staging of PBC from an ultrasound perspective. KEY POINTS: • The PHB is correlated with histological staging in the patient with PBC. • The area under the ROC curves of PHB for detecting advanced stage (≥ stage 3) were 0.934 and 0.93 for sensitivity, and 0.91 for specificity, the concordance rates of PHB vs. liver biopsy was 90.3%. The application of PHB can better assess the advanced PBC. • Measurement of the PHB to assess advanced PBC is a simple and effective method that can significantly reduce the need for liver biopsy.

Covalent and non-covalent interaction of myofibrillar protein and cyanidin-3-O-glucoside: focus on structure, binding sites and in vitro digestion properties.

BACKGROUND: The aim of this study was to investigate the effects of covalent and non-covalent interactions between myofibrillar protein (MP) and cyanidin-3-O-glucoside (C3G) on protein structure, binding sites, and digestion properties. Four methods of inducing covalent cross-linking were used in the preparation of MP-C3G conjugates, including tyrosinase-catalyzed oxidation, alkaline pH shift treatment, free radical grafting, and ultrasonic treatment. A comparison was made between MP-C3G conjugates and complexes, and the analysis included sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), C3G binding ratio, liquid chromatography-tandem mass spectrometry (LC-MS/MS), protein side-chain amino acids, circular dichroism spectroscopy, three-dimensional fluorescence, particle size, and in vitro simulated digestion. RESULTS: Covalent bonding between C3G and amino acid side chains in MP was confirmed by LC-MS/MS. In covalent bonding, tryptophan residues, free amino groups and sulfhydryl groups were all implicated. Among the 22 peptides covalently modified by C3G, 30 modification sites were identified, located in lysine, histidine, tryptophan, arginine and cysteine. In vitro simulated digestion experiments showed that the addition of C3G significantly reduced the digestibility of MP, with the covalent conjugate showing lower digestibility than the non-covalent conjugate. Moreover, the digestibility of protein decreased more during intestinal digestion, possibly because covalent cross-linking of C3G and MP further inhibited trypsin targeting sites (lysine and arginine). CONCLUSION: Covalent cross-linking of C3G with myofibrillar proteins significantly affected protein structure and reduced protein digestibility by occupying more trypsin binding sites. © 2023 Society of Chemical Industry.

Association of Abnormal Lung Function and Its Subtypes With Arterial Stiffness: A Longitudinal Cohort Study.

BACKGROUND: Prior studies have reported the cross-sectional relationship between lung function and arterial stiffness, while the longitudinal association remains unclear to date. This study aimed to investigate whether abnormal lung function and its subtypes at baseline are associated with increased arterial stiffness using a cohort. METHODS AND RESULTS: This was a secondary analysis extracting 2461 participants from Beijing Health Management Cohort as baseline and annually followed for development of arterial stiffness. Abnormal lung function was defined by forced expiratory volume in 1s <80% of the predicted value, forced vital capacity of the predicted value, or forced expiratory volume in 1s/forced vital capacity ratio <70%. Increased arterial stiffness was determined by brachial-ankle pulse wave velocity ≥1400 cm/s. Cox proportional hazards model was used to calculate the hazard ratio and population attributable fraction. The mean age was 42.8±8.1 years, and 444 (18.0%) cases developed increased arterial stiffness during a median follow-up of 3.0 years. The adjusted hazard ratio (95% CI) of arterial stiffness was 1.47 (95% CI, 1.10-1.96) for abnormal lung function, with a population attributable fraction of 3.9% (95% CI, 0.8-7.1). Of subtypes, only obstructive ventilatory dysfunction was significantly associated with arterial stiffness (adjusted hazard ratio, 2.06 [95% CI, 1.27-3.36]), not restricted ventilatory dysfunction (adjusted hazard ratio, 0.95 [95% CI, 0.54-1.65]). Consistent results were observed on multiple sensitivity analyses. CONCLUSIONS: Our study indicated a longitudinal association of abnormal lung function with increased arterial stiffness using a large cohort, especially for the obstructive ventilatory dysfunction.

Fascin actin-bundling protein 1 regulates non-small cell lung cancer progression by influencing the transcription and splicing of tumorigenesis-related genes.

Background: High mortality rates are prevalent among patients with non-small-cell lung cancer (NSCLC), and effective therapeutic targets are key prognostic factors. Fascin actin-bundling protein 1 (FSCN1) promotes NSCLC; however, its role as an RNA-binding protein in NSCLC remains unexplored. Therefore, we aimed to explore FSCN1 expression and function in A549 cells. Method: We screened for alternative-splicing events and differentially expressed genes (DEGs) after FSCN1 silence via RNA-sequencing (RNA-seq). FSCN1 immunoprecipitation followed by RNA-seq were used to identify target genes whose mRNA expression and pre-mRNA alternative-splicing levels might be influenced by FSCN1. Results: Silencing FSCN1 in A549 cells affected malignant phenotypes; it inhibited proliferation, migration, and invasion, and promoted apoptosis. RNA-seq analysis revealed 2,851 DEGs and 3,057 alternatively spliced genes. Gene ontology-based functional enrichment analysis showed that downregulated DEGs and alternatively splicing genes were enriched for the cell-cycle. FSCN1 promoted the alternative splicing of cell-cycle-related mRNAs involved in tumorigenesis (i.e., BCCIP, DLGAP5, PRC1, RECQL5, WTAP, and SGO1). Combined analysis of FSCN1 RNA-binding targets and RNA-seq data suggested that FSCN1 might affect ACTG1, KRT7, and PDE3A expression by modulating the pre-mRNA alternative-splicing levels of NME4, NCOR2, and EEF1D, that were bound to long non-coding RNA transcripts (RNASNHG20, NEAT1, NSD2, and FTH1), which were highly abundant. Overall, extensive transcriptome analysis of gene alternative splicing and expression levels was performed in cells transfected with FSCN1 short-interfering RNA. Our data provide global insights into the regulatory mechanisms associated with the roles of FSCN1 and its target genes in lung cancer.

Nuclear cGAS restricts L1 retrotransposition by promoting TRIM41-mediated ORF2p ubiquitination and degradation.

Cyclic GMP-AMP synthase (cGAS), initially identified as a cytosolic DNA sensor, detects DNA fragments to trigger an innate immune response. Recently, accumulating evidence reveals the presence of cGAS within the nucleus. However, the biological functions of nuclear cGAS are not fully understood. Here, we demonstrate that nuclear cGAS represses LINE-1 (L1) retrotransposition to preserve genome integrity in human cells. Mechanistically, the E3 ligase TRIM41 interacts with and ubiquitinates ORF2p to influence its stability, and cGAS enhances the association of ORF2p with TRIM41, thereby promoting TRIM41-mediated ORF2p degradation and the suppression of L1 retrotransposition. In response to DNA damage, cGAS is phosphorylated at serine residues 120 and 305 by CHK2, which promotes cGAS-TRIM41 association, facilitating TRIM41-mediated ORF2p degradation. Moreover, we show that nuclear cGAS mediates the repression of L1 retrotransposition in senescent cells induced by DNA damage agents. We also identify several cancer-associated cGAS mutations that abolish the suppressive effect on L1 retrotransposition by disrupting the CHK2-cGAS-TRIM41-ORF2p regulatory axis. Together, these findings indicate that nuclear cGAS exhibits an inhibitory function in L1 retrotransposition which could provide avenues for future interventions in both aging and tumorigenesis.