High-sensitivity trace gas detection based on differential Helmholtz photoacoustic cell with dense spot pattern.

A high-sensitivity photoacoustic spectroscopy (PAS) sensor based on differential Helmholtz photoacoustic cell (DHPAC) with dense spot pattern is reported in this paper for the first time. A multi-pass cell based on two concave mirrors was designed to achieve a dense spot pattern, which realized 212 times excitation of incident laser. A finite element analysis was utilized to simulate the sound field distribution and frequency response of the designed DHPAC. An erbium-doped fiber amplifier (EDFA) was employed to amplify the output optical power of the laser to achieve strong excitation. In order to assess the designed sensor's performance, an acetylene (C2H2) detection system was established using a near infrared diode laser with a central wavelength 1530.3 nm. According to experimental results, the differential characteristics of DHPAC was verified. Compared to the sensor without dense spot pattern, the photoacoustic signal with dense spot pattern had a 44.73 times improvement. The minimum detection limit (MDL) of the designed C2H2-PAS sensor can be improved to 5 ppb when the average time of the sensor system is 200 s.

Construction of a panoramic mRNA map of adult noncystic fibrosis bronchiectasis and a preliminary study of the underlying molecular mechanisms.

BACKGROUND: The pathogenesis of noncystic fibrosis bronchiectasis in adults is complex, and the relevant molecular mechanisms remain unclear. In this study, we constructed a panoramic map of bronchiectasis mRNA, explored the potential molecular mechanisms, and identified potential therapeutic targets, thus providing a new clinical perspective for the preventive management of bronchiectasis and its acute exacerbation. METHODS: The mRNA profiles of peripheral blood and bronchiectasis tissues were obtained through transcriptome sequencing and public databases, and bioinformatics methods were used to screen for differentially expressed genes (DEGs). The DEGs were then subjected to biological function and pathway analyses. Some DEGs were validated using a real-time quantitative polymerase chain reaction (RT-qPCR) in peripheral blood. Spearman's correlation analysis was used to analyse the correlation between DEGs and clinical indicators. RESULTS: Based on transcriptome sequencing and public databases, the mRNA profile of bronchiectasis was determined. DEGs were obtained from the peripheral blood sequencing dataset (985 DEGs), tissue sequencing dataset (2919 DEGs), and GSE97258 dataset (1083 DEGs). Bioinformatics analysis showed that upregulated DEGs had enriched neutrophil-related pathways, and downregulated DEGs had enriched ribosome-related pathways. RT-qPCR testing confirmed the upregulated expression of VCAN, SESTD1, SLC12A1, CD177, IFI44L, SIGLEC1, and RSAD2 in bronchiectasis. These genes were related to many clinical parameters, such as neutrophils, C-reactive protein, and procalcitonin (P < 0.05). CONCLUSIONS: Transcriptomic methods were used to construct a panoramic map of bronchiectasis mRNA expression. The findings showed that neutrophil activation, chronic inflammation, immune regulation, impaired ribosomal function, oxidative phosphorylation, and energy metabolism disorders are important factors in the development of bronchiectasis. VCAN, SESTD1, SLC12A1, CD177, IFI44L, SIGLEC1, and RSAD2 may play important roles in the pathogenesis of bronchiectasis and are potential therapeutic targets.

Npc1 deficiency impairs microglia function via TREM2-mTOR signaling in Niemann-Pick disease type C.

Niemann-Pick disease Type C (NPC) is a neurodegenerative disease mainly caused by the mutation in NPC1 gene, leading to massive accumulation of unesterified cholesterol in the late endosome/lysosome of cells. Impaired phenotype of microglia is a hallmark in Npc1 mutant mice (Npc1-/- mice). However, the mechanism of Npc1 in regulating microglial function is still unclear. Here, we showed that the reactive microglia in the neonatal Npc1-/- mice indicated by the increased lysosome protein CD68 and phagocytic activity were associated with disrupted TREM2-mTOR signaling in microglia. Furthermore, in Npc1-deficient BV2 cells, genetic deletion of Trem2 partially restored microglial function, probably via restored mTOR signaling. Taken together, our findings indicated that loss of Npc1 in microglia caused changes of their morphologies and the impairment of lysosomal function, which were linked to the TREM2-mTOR signaling pathway.

A Study of Assisted Screening for Alzheimer's Disease Based on Handwriting and Gait Analysis.

Background: Alzheimer's disease (AD) is a progressive neurodegenerative disease that is not easily detected in the early stage. Handwriting and walking have been shown to be potential indicators of cognitive decline and are often affected by AD. Objective: This study proposes an assisted screening framework for AD based on multimodal analysis of handwriting and gait and explores whether using a combination of multiple modalities can improve the accuracy of single modality classification. Methods: We recruited 90 participants (38 AD patients and 52 healthy controls). The handwriting data was collected under four handwriting tasks using dot-matrix digital pens, and the gait data was collected using an electronic trail. The two kinds of features were fused as inputs for several different machine learning models (Logistic Regression, SVM, XGBoost, Adaboost, LightGBM), and the model performance was compared. Results: The accuracy of each model ranged from 71.95% to 96.17%. Among them, the model constructed by LightGBM had the best performance, with an accuracy of 96.17%, sensitivity of 95.32%, specificity of 96.78%, PPV of 95.94%, NPV of 96.74%, and AUC of 0.991. However, the highest accuracy of a single modality was 93.53%, which was achieved by XGBoost in gait features. Conclusions: The research results show that the combination of handwriting features and gait features can achieve better classification results than a single modality. In addition, the assisted screening model proposed in this study can achieve effective classification of AD, which has development and application prospects.

Procaine induces cell cycle arrest, apoptosis and autophagy through the inhibition of the PI3K/AKT and ERK pathways in human tongue squamous cell carcinoma.

Procaine (PCA), a local anesthetic commonly used in stomatology, exhibits antitumor activity in some human malignancies. However, the precise mechanism underlying PCA activity remains unknown, and its antitumor effect in human tongue squamous carcinoma cells has not been reported. Flow cytometry and western blotting were used to assess the effects of PCA on mitochondrial membrane potential (ΔΨm), intracellular reactive oxygen species (ROS) production, cell cycle and apoptosis. The results suggested that PCA inhibits CAL27 and SCC-15 cell proliferation, and clone formation in a dose-dependent manner. CAL27 cells were more sensitive to PCA than SCC-15 cells. PCA also significantly inhibited cell migration, induced mitochondrial damage, reduced ΔΨm and increased intracellular ROS production. PCA causes G2/M cycle arrest and induces apoptosis. The possible mechanism for the inhibition of human tongue squamous carcinoma cell proliferation is through the regulation of ERK phosphorylation and PI3K/AKT-mediated signaling pathways. The results further suggested that autophagy occurs during PCA-induced apoptosis in CAL27 cells, and the addition of the autophagy inhibitor hydroxychloroquine sulfate further enhanced the sensitivity of PCA to inhibit cell proliferation, indicating that autophagy plays an important role in protecting cancer cells from apoptosis. PCA shows potential as an anticancer drug and its combination with autophagy inhibitors enhances its sensitivity.

Single intravenous and oral dose pharmacokinetics of the antiseizure medication brivaracetam in healthy cats.

The number of available antiseizure medications with demonstrated efficacy in cats is limited. As such, there is a need to evaluate the pharmacokinetics of newer medications so that proper dosing regimens can be made. Brivaracetam (BRV) is a more potent analogue of levetiracetam, and is Food and Drug Administration approved for use in people. The goal of this study was to describe the pharmacokinetics of intravenous and oral doses of BRV in healthy cats. A cross-over study involving eight healthy cats, that were administered 10 mg of BRV intravenously as a bolus and orally in the fasted state. Blood samples were collected over 24 h. Analysis was performed using liquid chromatography-mass spectrometry. Data were subjected to non-compartmental analysis. Median (min-max) of maximal concentration, time to maximal concentration, area under the curve, elimination half-life and oral absolute bioavailability were 902 (682-1036) ng/mL, 0.6 (0.5-2.0) h, 6.4 (5.2-7.2) h, 8145 (6669-9351) ng × h/mL and 100% (85-110) respectively. BRV appeared to be well tolerated by all cats. A single dose of BRV is well tolerated both orally and intravenously. Maximal concentrations are produced rapidly and within the human reference interval considered to be therapeutic.

A novel method combining deep learning with the Kennard-Stone algorithm for training dataset selection for image-based rice seed variety identification.

BACKGROUND: Different varieties of rice vary in planting time, stress resistance, and other characteristics. With advances in rice-breeding technology, the number of rice varieties has increased significantly, making variety identification crucial for both trading and planting. RESULTS: This study collected RGB images of 20 hybrid rice seed varieties. An enhanced deep super-resolution network (EDSR) was employed to enhance image resolution, and a variety classification model utilizing the high-resolution dataset demonstrated superior performance to that of the model using the low-resolution dataset. A novel training sample selection methodology was introduced integrating deep learning with the Kennard-Stone (KS) algorithm. Convolutional neural networks (CNN) and autoencoders served as supervised and unsupervised feature extractors, respectively. The extracted feature vectors were subsequently processed by the KS algorithm to select training samples. The proposed methodologies exhibited superior performance over the random selection approach in rice variety classification, with an approximately 10.08% improvement in overall classification accuracy. Furthermore, the impact of noise on the proposed methodology was investigated by introducing noise to the images, and the proposed methodologies maintained superior performance relative to the random selection approach on the noisy image dataset. CONCLUSION: The experimental results indicate that both supervised and unsupervised learning models performed effectively as feature extractors, and the deep learning framework significantly influenced the selection of training set samples. This study presents a novel approach for training sample selection in classification tasks and suggests the potential for extending the proposed method to image datasets and other types of datasets. Further exploration of this potential is warranted. © 2024 Society of Chemical Industry.

Simultaneous determination of pigments of spinach (Spinacia oleracea L.) leaf for quality inspection using hyperspectral imaging and multi-task deep learning regression approaches.

Rapid and accurate determination of pigment content is important for quality inspection of spinach leaves during storage. This study aimed to use hyperspectral imaging at two spectral ranges (visible/near-infrared, VNIR: 400-1000 nm; NIR: 900-1700 nm) to simultaneously determine the pigment (chlorophyll a, chlorophyll b, total chlorophyll, and carotenoids) content in spinach stored at different durations and conditions (unpackaged and packaged). Partial least squares (PLS), back propagation neural network (BPNN) and convolutional neural network (CNN) were used to establish single-task and multi-task regression models. Single-task CNN (STCNN) models and multi-task CNN (MTCNN) models obtained better performances than the other models. The models using VNIR spectra were superior to those using NIR spectra. The overall results indicated that hyperspectral imaging with multi-task learning could predict the quality attributes of spinach simultaneously for spinach quality inspection under various storage conditions. This research will guide food quality inspection by simultaneously inspecting multiple quality attributes.

Magnetic Field-induced Disordered Phase of Spinel Oxides for High Battery Performance.

The disordered phase of spinel LiMn1.5Ni0.5O4 (LNMO) is more appealing as high-voltage cathode due to its superior electrochemical performance compared to its ordered counterpart. Various methods are developed to induce a phase transition. However, the resulting materials often suffer from capacity degradation due to the adverse influence of accompanying Mn3+ ions. This study presents the utilization of local magnetic fields generated by a magnetic Fe3O4 shell to induce a disordered phase transition in LNMO at lower temperature, transitioning it from an order state without significantly increasing the Mn3+ content. The pivotal role played by the local magnetic fields is evidenced through comparisons with samples with nonmagnetic Al2O3 shell, samples subjected to sole heat treatment, and samples heat-treated within magnetic fields. The key finding is that magnetic fields can initiate a radical pair mechanism, enabling the induction of order-disorder phase transition even at lower temperatures. The disordered spinal LNMO with a magnetic Fe3O4 shell exhibits excellent cycling stability and kinetic properties in electrochemical characterization as a result. This innovation not only unravels the intricate interplay between the disordered phase and Mn3+ content in the cathode spinel but also pioneers the use of magnetic field effects for manipulating material phases.

Scorpiones, Scolopendra and Gekko Inhibit Lung Cancer Growth and Metastasis by Ameliorating Hypoxic Tumor Microenvironment via PI3K/AKT/mTOR/HIF-1α Signaling Pathway.

OBJECTIVE: To investigate whether Buthus martensii karsch (Scorpiones), Scolopendra subspinipes mutilans L. Koch (Scolopendra) and Gekko gecko Linnaeus (Gekko) could ameliorate the hypoxic tumor microenvironment and inhibit lung cancer growth and metastasis by regulating phosphoinositide 3-kinase/protein kinase B/mammalian target of rapamycin/hypoxia-inducible factor-1α (PI3K/AKT/mTOR/HIF-1α) signaling pathway. METHODS: Male C57BL/6J mice were inoculated with luciferase labeled LL/2-luc-M38 cell suspension to develop lung cancer models, with rapamycin and cyclophosphamide as positive controls. Carboxy methyl cellulose solutions of Scorpiones, Scolopendra and Gekko were administered intragastrically as 0.33, 0.33, and 0.83 g/kg, respectively once daily for 21 days. Fluorescent expression were detected every 7 days after inoculation, and tumor growth curves were plotted. Immunohistochemistry was performed to determine CD31 and HIF-1α expressions in tumor tissue and microvessel density (MVD) was analyzed. Western blot was performed to detect the expression of PI3K/AKT/mTOR/HIF-1α signaling pathway-related proteins. Enzyme-linked immunosorbent assay was performed to detect serum basic fibroblast growth factor (bFGF), transforming growth factor-ß1 (TGF-ß1) and vascular endothelial growth factor (VEGF) in mice. RESULTS: Scorpiones, Scolopendra and Gekko prolonged the survival time and inhibited lung cancer metastasis and expression of HIF-1α (all P<0.01). Moreover, Scorpiones, Scolopendra and Gekko inhibited the phosphorylation of AKT and ribosomal protein S6 kinase (p70S6K) (P<0.05 or P<0.01). In addition, they also decreased the expression of CD31, MVD, bFGF, TGF-ß1 and VEGF compared with the model group (P<0.05 or P<0.01). CONCLUSION: Scorpiones, Scolopendra and Gekko all showed beneficial effects on lung cancer by ameliorating the hypoxic tumor microenvironment via PI3K/AKT/mTOR/HIF-1α signaling pathway.

Three new endophytic Apiospora species (Apiosporaceae, Amphisphaeriales) from China.

Apiospora species are widely distributed fungi with diverse lifestyles, primarily functioning as plant pathogens, as well as exhibiting saprophytic and endophytic behaviors. This study reports the discovery of three new species of Apiospora, namely A.gongcheniae, A.paragongcheniae, and A.neogongcheniae, isolated from healthy Poaceae plants in China. These novel species were identified through a multi-gene phylogenetic analysis. The phylogenetic analysis of the combined ITS, LSU, tef1, and tub2 sequence data revealed that the three new species formed a robustly supported clade with A.garethjonesii, A.neogarethjonesii, A.setostroma, A.subrosea, A.mytilomorpha, and A.neobambusae. Detailed descriptions of the newly discovered species are provided and compared with closely related species to enhance our understanding of the genus Apiospora.

IGF2BP2 inhibits invasion and migration of clear cell renal cell carcinoma via targeting Netrin-4 in an m6A-dependent manner.

Clear cell renal cell carcinoma (ccRCC), the most common subtype of renal cell carcinoma, often leads to a poor prognosis due to metastasis. The investigation of N6-methyladenosine (m6A) methylation, a crucial RNA modification, and its role in ccRCC, particularly through the m6A reader insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2), revealed significant insights. We found that IGF2BP2 was notably downregulated in ccRCC, which correlated with tumor aggressiveness and poor prognosis. Thus, IGFBP2 has emerged as an independent prognostic factor of ccRCC. Moreover, a strong positive correlation was observed between the expression of IGF2BP2 and Netrin-4. Netrin-4 was also downregulated in ccRCC, and its lower levels were associated with increased malignancy and poor prognosis. Overexpression of IGF2BP2 and Netrin-4 suppressed the invasion and migration of ccRCC cells, while Netrin-4 knockdown reversed these effects in ccRCC cell lines. RNA immunoprecipitation (RIP)-quantitative polymerase chain reaction validated the robust enrichment of Netrin-4 mRNA in anti-IGF2BP2 antibody immunoprecipitates. MeRlP showed significantly increased Netrin4 m6A levels after lGF2BP2 overexpression. Moreover, we found that IGF2BP2 recognized and bound to the m6A site within the coding sequence of Netrin-4, enhancing its mRNA stability. Collectively, these results showed that IGF2BP2 plays a suppressive role in the invasion and migration of ccRCC cells by targeting Netrin-4 in an m6A-dependent manner. These findings underscore the potential of IGF2BP2/Netrin-4 as a promising prognostic biomarker and therapeutic target in patients with ccRCC metastasis.

Genomic landscape and functional characterization of structural variations in schizophrenia and bipolar disorder.

Multiple types of variations have been postulated to confer risk of schizophrenia and bipolar disorder, but majority of present GWAS solely focused on SNPs or small indels, and the impacts of structural variations (SVs) remain less understood. Nevertheless, accumulating evidence suggest that SVs may explain the association signals in certain GWAS hits. Here, we conducted pairwise linkage disequilibrium (LD) analyses of SNPs and SVs in populations from 1000 Genomes Project. Among the 299 psychiatric GWAS loci, 1213 SVs showed an LD of r2 > 0.1 with GWAS risk SNPs, and 66 of them were in moderate to strong LD (r2 > 0.6) with at least one GWAS risk SNP. Nine SVs were subject to further explorative analyses, including eQTL analysis in DLPFC, luciferase reporter gene assays, CRISPR/Cas9-mediated genome deletion and RT-qPCR. These assays highlighted several functional SVs showing regulatory effects on transcriptional activities, and some risk genes (e.g., BORCS7, GNL3) affected by the SVs were also annotated. Finally, mice overexpressing Borcs7 in the mPFC exhibited schizophrenia-like behaviors, such as abnormal prepulse inhibition and social dysfunction. These data suggest that SNPs association signals at GWAS loci might be driven by SVs, highlighting the necessities of considering such variants in future.

Sinomenine attenuates pulmonary fibrosis by downregulating TGF-ß1/Smad3, PI3K/Akt and NF-κB signaling pathways.

BACKGROUND: Since COVID-19 became a global epidemic disease in 2019, pulmonary fibrosis (PF) has become more prevalent among persons with severe infections, with IPF being the most prevalent form. In traditional Chinese medicine, various disorders are treated using Sinomenine (SIN). The SIN's strategy for PF defense is unclear. METHODS: Bleomycin (BLM) was used to induce PF, after which inflammatory factors, lung histological alterations, and the TGF-/Smad signaling pathway were assessed. By administering various dosages of SIN and the TGF- receptor inhibitor SB-431,542 to human embryonic lung fibroblasts (HFL-1) and A549 cells, we were able to examine proliferation and migration as well as the signaling molecules implicated in Epithelial-Mesenchymal Transition (EMT) and Extra-Cellular Matrix (ECM). RESULTS: In vivo, SIN reduced the pathological changes in the lung tissue induced by BLM, reduced the abnormal expression of inflammatory cytokines, and improved the weight and survival rate of mice. In vitro, SIN inhibited the migration and proliferation by inhibiting TGF-ß1/Smad3, PI3K/Akt, and NF-κB pathways, prevented the myofibroblasts (FMT) of HFL-1, reversed the EMT of A549 cells, restored the balance of matrix metalloenzymes, and reduced the expression of ECM proteins. CONCLUSION: SIN attenuated PF by down-regulating TGF-ß/Smad3, PI3K/Akt, and NF-κB signaling pathways, being a potential effective drug in the treatment of PF.

Risk prediction models of depression in older adults with chronic diseases.

BACKGROUND: Detecting potential depression and identifying the critical predictors of depression among older adults with chronic diseases are essential for timely intervention and management of depression. Therefore, risk prediction models (RPMs) of depression in elderly people should be further explored. METHODS: A total of 3959 respondents aged 60 years or over from the wave four survey of the China Health and Retired Longitudinal Study (CHARLS) were included in this study. We used five machine learning (ML) algorithms and three data balancing techniques to construct RPMs of depression and calculated feature importance scores to determine which features are essential to depression. RESULTS: The prevalence of depression was 19.2 % among older Chinese adults with chronic diseases in the wave four survey. The random forest (RF) model was more accurate than the other models after balancing the data using the Synthetic Minority Oversampling Technique (SMOTE) algorithm, with an area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve (AUPRC) of 0.957 and 0.920, respectively, a balanced accuracy of 0.891 and a sensitivity of 0.875. Furthermore, we further identified several important predictors between male and female patients via constructed sex-stratified models. LIMITATIONS: Further research on the clinical impact studies of our models and external validation are needed. CONCLUSIONS: After several techniques were used to address class imbalance issues, most RPMs achieved satisfactory accuracy in predicting depression among elderly people with chronic diseases. RPMs may thus become valuable screening tools for both older individuals and healthcare practitioners to assess the risk of depression.

Quercetin exerts anti-tumor immune mechanism by regulating IL-6/JAK2/STAT3 signaling pathway to deplete Treg cells.

Breast cancer is still the leading cause of death among women worldwide. Due to the lack of effective drug targets, triple-negative breast cancer has a worse prognosis and higher mortality compared with other types of breast cancer, and chemotherapy is still the main treatment for triple-negative breast cancer at present. Quercetin (QUE) is a flavonoid compound found in a variety of fruits and vegetables. The mechanism of QUE has been extensively studied, such as prostate cancer, colon cancer, ovarian cancer, etc. However, the anti-tumor immune mechanism of QUE in triple-negative breast cancer remains unclear. Therefore, we assessed the anti-tumor immune effects of QUE on triple-negative breast cancer using both 4T1 cells and a xenograft mouse model of 4T1 cells. In vitro, we examined the inhibitory effects of QUE on 4T1 cells and its molecular mechanisms through MTT, Transwell, ELISA, and Western blotting. In vivo, by establishing a xenograft mouse model, we utilized flow cytometry, immunohistochemistry, ELISA, and Western blotting to evaluate the anti-tumor immune effects of QUE on triple-negative breast cancer. The results indicate that QUE inhibits the proliferation, migration, and invasion of 4T1 cells, concurrently significantly suppressing the IL-6/JAK2/STAT3 signaling pathway. Furthermore, it depletes Treg cell content in 4T1 xenograft mice, thereby improving the tumor immune microenvironment and promoting the cytotoxicity of relevant tumor immune cells. These findings suggest that QUE may serve as a potential adjuvant for immune therapy in triple-negative breast cancer.

Tumor-repopulating cells evade ferroptosis via PCK2-dependent phospholipid remodeling.

Whether stem-cell-like cancer cells avert ferroptosis to mediate therapy resistance remains unclear. In this study, using a soft fibrin gel culture system, we found that tumor-repopulating cells (TRCs) with stem-cell-like cancer cell characteristics resist chemotherapy and radiotherapy by decreasing ferroptosis sensitivity. Mechanistically, through quantitative mass spectrometry and lipidomic analysis, we determined that mitochondria metabolic kinase PCK2 phosphorylates and activates ACSL4 to drive ferroptosis-associated phospholipid remodeling. TRCs downregulate the PCK2 expression to confer themselves on a structural ferroptosis-resistant state. Notably, in addition to confirming the role of PCK2-pACSL4(T679) in multiple preclinical models, we discovered that higher PCK2 and pACSL4(T679) levels are correlated with better response to chemotherapy and radiotherapy as well as lower distant metastasis in nasopharyngeal carcinoma cohorts.

A nomogram for predicting cerebral white matter lesions in elderly men.

Objective: This study aimed to develop a nomogram tool to predict cerebral white matter lesions (WMLs) in elderly men. Methods: Based on a retrospective cohort from January 2017 to December 2019, a multivariate logistic analysis was performed to construct a nomogram for predicting WMLs. The nomogram was further validated using a follow-up cohort between January 2020 and December 2022. The calibration curve, receiver operating characteristics (ROC) curves, and the decision curves analysis (DCA) were used to evaluate discrimination and calibration of this nomogram. Result: A total of 436 male patients were enrolled in this study, and all 436 patients were used as the training cohort and 163 follow-up patients as the validation cohort. A multivariate logistic analysis showed that age, cystatin C, uric acid, total cholesterol, platelet, and the use of antiplatelet drugs were independently associated with WMLs. Based on these variables, a nomogram was developed. The nomogram displayed excellent predictive power with the area under the ROC curve of 0.951 [95% confidence interval (CI), 0.929-0.972] in the training cohort and 0.915 (95% CI, 0.864-0.966) in the validation cohort. The calibration of the nomogram was also good, as indicated by the Hosmer-Lemeshow test with p-value of 0.594 in the training cohort and 0.178 in the validation cohort. The DCA showed that the nomogram holds good clinical application value. Conclusion: We have developed and validated a novel nomogram tool for identifying elderly men at high risk of WMLs, which exhibits excellent predictive power, discrimination, and calibration.

Clinical significance and potential pathogenesis of VCAN in adult non-cystic fibrosis bronchiectasis: a retrospective study.

BACKGROUND: The pathogenesis of adult non-cystic fibrosis (CF) bronchiectasis is complex, and the relevant molecular mechanism remains ambiguous. Versican (VCAN) is a key factor in inflammation through interactions with adhesion molecules. This study constructs a stable panoramic map of mRNA, reveals the possible pathogenesis of bronchiectasis, and provides new ideas and methods for bronchiectasis. METHODS: Peripheral blood and tissue gene expression data from patients with bronchiectasis and normal control were selected by bioinformatics analysis. The expression of VCAN in peripheral blood and bronchial tissues of bronchiectasis were obtained by transcriptome sequencing. The protein expression levels of VCAN in serums were verified by the enzyme-linked immunosorbent assay (ELISA). The mRNA expression levels of VCAN in co-culture of Pseudomonas aeruginosa and bronchial epithelial cells were verified by real-time quantitative polymerase chain reaction (RT-qPCR). In addition, the biological function of VCAN was detected by the transwell assay. RESULTS: The expression of VCAN was upregulated in the bronchiectasis group by sequencing analysis (P < 0.001). The expression of VCAN in the bronchial epithelial cell line BEAS-2B was increased in P. aeruginosa (P.a), which was co-cultured with BEAS-2B cells (P < 0.05). The concentration of VCAN protein in the serum of patients with bronchiectasis was higher than that in the normal control group (P < 0.05). Transwell experiments showed that exogenous VCAN protein induced the migration of neutrophils (P < 0.0001). CONCLUSIONS: Our findings indicate that VCAN may be involved in the development of bronchiectasis by increasing the migration of neutrophils and play an important role in bronchial pathogenesis.