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.

MIDASim: a fast and simple simulator for realistic microbiome data.

BACKGROUND: Advances in sequencing technology has led to the discovery of associations between the human microbiota and many diseases, conditions, and traits. With the increasing availability of microbiome data, many statistical methods have been developed for studying these associations. The growing number of newly developed methods highlights the need for simple, rapid, and reliable methods to simulate realistic microbiome data, which is essential for validating and evaluating the performance of these methods. However, generating realistic microbiome data is challenging due to the complex nature of microbiome data, which feature correlation between taxa, sparsity, overdispersion, and compositionality. Current methods for simulating microbiome data are deficient in their ability to capture these important features of microbiome data, or can require exorbitant computational time. METHODS: We develop MIDASim (MIcrobiome DAta Simulator), a fast and simple approach for simulating realistic microbiome data that reproduces the distributional and correlation structure of a template microbiome dataset. MIDASim is a two-step approach. The first step generates correlated binary indicators that represent the presence-absence status of all taxa, and the second step generates relative abundances and counts for the taxa that are considered to be present in step 1, utilizing a Gaussian copula to account for the taxon-taxon correlations. In the second step, MIDASim can operate in both a nonparametric and parametric mode. In the nonparametric mode, the Gaussian copula uses the empirical distribution of relative abundances for the marginal distributions. In the parametric mode, a generalized gamma distribution is used in place of the empirical distribution. RESULTS: We demonstrate improved performance of MIDASim relative to other existing methods using gut and vaginal data. MIDASim showed superior performance by PERMANOVA and in terms of alpha diversity and beta dispersion in either parametric or nonparametric mode. We also show how MIDASim in parametric mode can be used to assess the performance of methods for finding differentially abundant taxa in a compositional model. CONCLUSIONS: MIDASim is easy to implement, flexible and suitable for most microbiome data simulation situations. MIDASim has three major advantages. First, MIDASim performs better in reproducing the distributional features of real data compared to other methods, at both the presence-absence level and the relative-abundance level. MIDASim-simulated data are more similar to the template data than competing methods, as quantified using a variety of measures. Second, MIDASim makes few distributional assumptions for the relative abundances, and thus can easily accommodate complex distributional features in real data. Third, MIDASim is computationally efficient and can be used to simulate large microbiome datasets. Video Abstract.

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.

A Mixed Effect Similarity Matrix Regression Model (SMRmix) for Integrating Multiple Microbiome Datasets at Community Level and its Application in HIV.

Recent studies have highlighted the importance of human microbiota in our health and diseases. However, in many areas of research, individual microbiome studies often offer inconsistent results due to the limited sample sizes and the heterogeneity in study populations and experimental procedures. Integrative analysis of multiple microbiome datasets is necessary. However, statistical methods that incorporate multiple microbiome datasets and account for the study heterogeneity are not available in the literature. In this paper, we develop a mixed effect similarity matrix regression (SMRmix) approach for identifying community level microbiome shifts between outcomes. SMRmix has a close connection with the microbiome kernel association test, one of the most popular approaches for such a task but is only applicable when we have a single study. Via extensive simulations, we show that SMRmix has well-controlled type I error and higher power than some potential competitors. We also applied SMRmix to data from the HIV-reanalysis consortium, a collective effort that obtained all publicly available data on gut microbiome and HIV at December 2017, and obtained consistent associations of gut microbiome with HIV infection, and with MSM status (i.e. men who have sex with men).

Does early time-restricted eating reduce body weight and preserve fat-free mass in adults? A systematic review and meta-analysis of randomized controlled trials.

BACKGROUND: This meta-analysis evaluated whether weight loss caused by early time-restricted eating could promote fat mass loss while preserving fat-free mass, thereby leading to improvements in inflammation and metabolic health. METHODS: Relevant randomized controlled trials (RCTs) published up to March 28, 2023, were identified in six databases, including PubMed, Web of Science, and Embase. RESULTS: We initially screened 1279 articles, thirteen RCTs with 859 patients were ultimately included. Compared with nontime-restricted eating, early time-restricted eating significantly reduced body weight (-1.84 kg [-2.28, -1.41]; I2 = 56 %; P < 0.00001), fat mass (-1.10 kg [-1.47, -0.74]; I2 = 42 %; P < 0.00001), waist circumstance (-3.21 cm [-3.90, -2.51]; I2 = 43 %; P < 0.00001), visceral fat area (-9.76 cm2 [-13.76, -5.75]; I2 = 2 %; P < 0.00001), and inflammation as measured by tumour necrosis factor-α (-1.36 pg/mL [-2.12, -0.60]; I2 = 42 %; P < 0.001). However, early time-restricted eating did not lead to a significant change in fat-free mass (-0.56 kg [-1.16, 0.03]; I2 = 59 %; P = 0.06). Subgroup analysis showed that the early time-restricted eating of the 16:08 (fasting-time versus eating-time) strategy had a superior effect on preserving fat-free mass (-0.25 kg [-0.68, 0.18]; I2 = 0 %; P = 0.25) while significantly reducing body weight (-1.60 kg [-2.09, -1.11]; I2 = 0 %; P < 0.001) and improving metabolic outcomes. CONCLUSIONS: Early time-restricted eating, especially 16:08 strategy, appears to be an effective strategy to decrease body weight, fat mass, abdominal obesity and inflammation, but less likely to decrease fat-free mass.

MIDASim: a fast and simple simulator for realistic microbiome data.

Background: Advances in sequencing technology has led to the discovery of associations between the human microbiota and many diseases, conditions, and traits. With the increasing availability of microbiome data, many statistical methods have been developed for studying these associations. The growing number of newly developed methods highlights the need for simple, rapid, and reliable methods to simulate realistic microbiome data, which is essential for validating and evaluating the performance of these methods. However, generating realistic microbiome data is challenging due to the complex nature of microbiome data, which feature correlation between taxa, sparsity, overdispersion, and compositionality. Current methods for simulating microbiome data are deficient in their ability to capture these important features of microbiome data, or can require exorbitant computational time. Methods: We develop MIDASim ( MI crobiome DA ta Sim ulator), a fast and simple approach for simulating realistic microbiome data that reproduces the distributional and correlation structure of a template microbiome dataset. MIDASim is a two-step approach. The first step generates correlated binary indicators that represent the presence-absence status of all taxa, and the second step generates relative abundances and counts for the taxa that are considered to be present in step 1, utilizing a Gaussian copula to account for the taxon-taxon correlations. In the second step, MIDASim can operate in both a nonparametric and parametric mode. In the nonparametric mode, the Gaussian copula uses the empirical distribution of relative abundances for the marginal distributions. In the parametric mode, an inverse generalized gamma distribution is used in place of the empirical distribution. Results: We demonstrate improved performance of MIDASim relative to other existing methods using gut and vaginal data. MIDASim showed superior performance by PER-MANOVA and in terms of alpha diversity and beta dispersion in either parametric or nonparametric mode. We also show how MIDASim in parametric mode can be used to assess the performance of methods for finding differentially abundant taxa in a compositional model. Conclusions: MIDASim is easy to implement, flexible and suitable for most microbiome data simulation situations. MIDASim has three major advantages. First, MIDASim performs better in reproducing the distributional features of real data compared to other methods at both presence-absence level and relative-abundance level. MIDASim-simulated data are more similar to the template data than competing methods, as quantified using a variety of measures. Second, MIDASim makes few distributional assumptions for the relative abundances, and thus can easily accommodate complex distributional features in real data. Third, MIDASim is computationally efficient and can be used to simulate large microbiome datasets.

Identification of geographical origins of Radix Paeoniae Alba using hyperspectral imaging with deep learning-based fusion approaches.

The Radix Paeoniae Alba (Baishao) is a traditional Chinese medicine (TCM) with numerous clinical and nutritional benefits. Rapid and accurate identification of the geographical origins of Baishao is crucial for planters, traders and consumers. Hyperspectral imaging (HSI) was used in this study to acquire spectral images of Baishao samples from its two sides. Convolutional neural network (CNN) and attention mechanism was used to distinguish the origins of Baishao using spectra extracted from one side. The data-level and feature-level deep fusion models were proposed using information from both sides of the samples. CNN models outperformed the conventional machine learning methods in classifying Baishao origins. The generalized Gradient-weighted Class Activation Mapping (Grad-CAM++) was utilized to visualize and identify important wavelengths that significantly contribute to model performance. The overall results illustrated that HSI combined with deep learning strategies was effective in identifying the geographical origins of Baishao, having good prospects of real-world applications.

Hyperspectral Imaging with Machine Learning Approaches for Assessing Soluble Solids Content of Tribute Citru.

Tribute Citru is a natural citrus hybrid with plenty of vitamins and nutrients. Fruits' soluble solids content (SSC) is a critical quality index. This study used hyperspectral imaging at two spectral ranges (400-1000 nm and 900-1700 nm) to determine SSC in Tribute Citru. Partial least squares regression (PLSR) and support vector regression (SVR) models were established in order to determine SSC using the spectral information of the calyx and blossom ends. The average spectra of both ends as well as their fusion was studied. The successive projections algorithm (SPA) and the correlation coefficient analysis (CCA) were used to examine the differences in characteristic wavelengths between the two ends. Most models achieved performances with the correlation coefficient of the training, validation, and testing sets over 0.6. Results showed that differences in the performances among the models using the one-sided and two-sided spectral information. No particular regulation could be found for the differences in model performances and characteristic wavelengths. The results illustrated that the sampling side was an influencing factor but not the determinant factor for SSC determination. These results would help with the development of real-world applications for citrus quality inspection without concerning the sampling sides and the spectral ranges.

Paeoniflorin attenuates monocrotaline-induced pulmonary arterial hypertension in rats by suppressing TAK1-MAPK/NF-κB pathways.

Pulmonary arterial hypertension (PAH) characterized by pulmonary vascular remodeling is a lethal disease. Paeoniflorin (PF) is a monoterpene glycoside with numerous beneficial functions, such as vasodilation, anti-inflammation and immunomodulation. This study aims to investigate the effects of PF on monocrotaline (MCT)-induced PAH rats. Our data showed that both prophylactic or therapeutic administration of PF alleviated MCT-induced increasing of right ventricular systolic pressure (RVSP), prevented right ventricle hypertrophy and pulmonary arterial remodeling, as well as inhibited inflammatory cell infiltration around pulmonary arteries. Meanwhile, PF blocked MCT-induced endothelial-mesenchymal transition (EndMT) as indicated by the restored expression of endothelial markers in lung. Moreover, PF inhibited MCT-induced down-regulation of bone morphogenetic protein receptor 2 (BMPR2) and suppressed MCT-induced phosphorylation of transforming growth factor-ß (TGFß) activated kinase 1 (TAK1) in vivo. In vitro studies indicated that PF prevented human pulmonary arterial smooth muscle cells (PASMCs) from platelet-derived growth factor-BB (PDGF-BB)-stimulated proliferation and migration. PF also partially reversed TGFß1, interleukin-1ß (IL-1ß) and tumor necrosis factor (TNF-α) co-stimulated endothelial-to-mesenchymal transition (EndMT) in cultured human pulmonary artery endothelial cells (HPAECs). Signaling pathway analysis demonstrated that the underlying mechanism might be associated with the inhibition of TAK1-MAPK/NF-κB pathways. Taken together, our results suggested that PF could be a potential drug for the treatment of PAH.

MiRKAT-MC: A Distance-Based Microbiome Kernel Association Test With Multi-Categorical Outcomes.

Increasing evidence has elucidated that the microbiome plays a critical role in many human diseases. Apart from continuous and binary traits that measure the extent or presence of a disease, multi-categorical outcomes including variations/subtypes of a disease or ordinal levels of disease severity are commonly seen in clinical studies. On top of that, studies with clustered design (i.e., family-based and longitudinal studies) are popular alternatives to population-based ones as they are able to identify characteristics on both individual and population levels and to investigate the trajectory of traits of interest over time. However, existing methods for microbiome association analysis are inadequate to handle multi-categorical outcomes, neither independent nor clustered data. We propose a microbiome kernel association test with multi-categorical outcomes (MiRKAT-MC). Our method is versatile to deal with both nominal and ordinal outcomes for independent and clustered data. In addition, it incorporates multiple ecological distances to allow for different association patterns between outcomes and microbiome compositions to be incorporated. A computationally efficient pseudo-permutation strategy is used to evaluate the statistical significance. Comprehensive simulations show that MiRKAT-MC preserves the nominal type I error and increases statistical powers under various scenarios and data types. We also apply MiRKAT-MC to real data sets with nominal and ordinal outcomes to gain biological insights. MiRKAT-MC is easy to implement, and freely available via an R package at https://github.com/Zhiwen-Owen-Jiang/MiRKATMC with a Graphical User Interface through R Shinny also available.

Topotecan plus Platinum-Based Chemotherapy versus Etoposide plus Platinum-Based Chemotherapy for Small-Cell Lung Cancer: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

BACKGROUND: Whether topotecan plus platinum-based chemotherapy (TP) can achieve better results than etoposide plus platinum-based chemotherapy (EP) for small-cell lung cancer (SCLC) treatment is still controversial in clinical applications. We compared the effectiveness and toxicity of TP versus EP in this meta-analysis. METHODS: We searched PubMed, ScienceDirect, Cochrane Library, Scopus, Ovid MEDLINE, Embase, Web of Science, and Google Scholar databases for completeness one by one to find articles that met the conditions. Overall survival (OS) and progression-free survival (PFS) were analyzed as primary endpoints, and the objective response rate (ORR), disease control rate (DCR), and adverse events (AEs) were analyzed as secondary endpoints. RESULTS: In total, 2,480 articles were retrieved, and 6 randomized controlled trials (RCTs) contained results based on 1,924 patients. EP suggested conspicuously better OS (hazard ratio [HR]: 1.24 [1.02, 1.50], p = 0.03) and PFS (HR: 1.39 [1.17, 1.64], p = 0.0001) in SCLC treatment than TP, and ORR (54.1% vs. 60.2%, risk ratio [RR]: 0.77 [0.57, 1.06], p = 0.11), and DCR (74.9% vs. 84.4%, RR: 0.89 [0.79, 1.00], p = 0.06) tended to favor EP. Subgroup analysis of subsistence showed that EP had prominent benefit in the following subgroups: Asian, median age > 60, first-line treatment, ECOG 0-2, intravenous topotecan, and cisplatin. AEs illustrated that EP had conspicuously more anemia and alopecia than TP. CONCLUSIONS: Compared with TP, EP was noticeably better in OS and PFS, but EP was toxic in terms of anemia and alopecia. More multicenter, better planned RCTs are needed.

Use of dexamethasone and a 5-HT3 receptor antagonist with or without aprepitant to prevent chemotherapy-induced nausea and vomiting among patients with lung cancer who are treated with platinum-based chemotherapy: a systematic review and meta-analysis of randomized controlled trials.

BACKGROUND: Researchers have not clearly determined whether adding aprepitant (ADH) to dexamethasone and one 5-HT3 receptor antagonist (DH) is clinically effective at preventing chemotherapy-induced nausea and vomiting (CINV) among patients with lung cancer (LC) treated with platinum-based chemotherapy (PBC). Therefore, we conducted a meta-analysis to examine the efficacy and safety of ADH and DH. METHODS: We searched the PubMed, ScienceDirect, Cochrane Library, and Scopus databases, among others, for relevant studies. The primary outcomes were the complete response (CR) and the no nausea rate (NNR). The secondary endpoints were the number of patients who needed rescue antiemetic treatment (RAT), adverse events (AEs), and the Functional Living Index Emesis (FLIE) score. RESULTS: We initially screened 2,118 articles; ultimately, four randomized controlled trials (RCTs) with 518 patients were included. The ADH group had a superior overall CR [risk ratio (RR): 1.16 (1.06, 1.27), P=0.002] and a lower number of patients who needed RAT [RR: 0.44 (0.29, 0.65), P<0.0001]. The ADH group also had a better overall NNR [RR: 1.11 (0.97, 1.26), P=0.12] and delayed CR [RR: 1.12 (0.97, 1.31), P=0.13]. No significant differences were observed in acute CR, acute NNR, or delayed NNR. In the subgroup analysis of the overall CR and NNR, ADH was superior in certain clinical characteristics (China, cisplatin-based chemotherapy, 2nd-generation 5-HT3 receptor antagonist, ADC <50%, and Eastern Cooperative Oncology Group (ECOG) score of 0-2). No significant differences in the AEs characterized as hematological or nonhematological toxicity were observed between the groups. CONCLUSIONS: Compared with DH, ADH appears to be superior at preventing CINV and achieving a better CR among patients with LC treated with PBC.

Comparison of transcatheter arterial chemoembolization combined with radiofrequency ablation or microwave ablation for the treatment of unresectable hepatocellular carcinoma: a systemic review and meta-analysis.

Background: Transcatheter arterial chemoembolization (TACE), radiofrequency ablation (RFA), and microwave ablation (MWA) are regarded as effective therapies for treating unresectable hepatocellular carcinoma (HCC). We conducted this study to compare the efficiency and safety of TACE combined with RFA (TR group) or MWA (TM group).Method: PubMed, the Cochrane Library, Ovid Medline, Web of Science, Scopus, Embase, ScienceDirect, and Google Scholar were searched. The primary endpoints were overall survival (OS), progression-free survival (PFS), response rates, and complications.Result: Eight cohort studies and one randomized controlled trial were included. The TM group had better OS (Hazard ratio [HR]: 1.55; 95% confidence interval [CI]: 1.09-2.21, p = 0.01) and a better 2- and 3-year OS rate, 24-month PFS rate (Risk ratio [RR]: 0.67; 95% CI: 0.46-0.96, p = 0.03), and complete response rate (RR: 0.87; 95% CI: 0.79-0.96, p = 0.003) than the TR group. Furthermore, the TM and TR groups did not show significant differences in PFS, the disease control rate or complications. The advantage of TM was mainly reflected in younger patients (50-60 years old) compared with patients aged 60-70 years, as well as in patients with larger tumors (≥3 cm) compared with patients with tumors <3 cm. Moreover, patients treated with conventional TACE (cTACE) in the TM group showed longer OS, while patients treated with drug-eluting bead transarterial chemoembolization (DEB-TACE) in the TR group showed a higher overall response rate.Conclusion: TM seems to be a more effective therapy than TR for unresectable HCC, with better survival and similar safety.

Iptakalim ameliorates hypoxia-impaired human endothelial colony-forming cells proliferation, migration, and angiogenesis via Akt/eNOS pathways.

Hypoxia-associated pulmonary hypertension is characterized by pulmonary vascular remodeling. Pulmonary arterial endothelial cells dysfunction is considered as the initial event. As precursor of endothelial cells, endothelial colony-forming cells (ECFCs) play significant roles in maintenance of endothelium integrity and restoration of normal endothelial cell function. Accumulating data have indicated that hypoxia leads to a decrease in the number and function of ECFCs with defective capacity of endothelial regeneration. Previous studies have reported that the activation of ATP-sensitive potassium channels (KATP) shows therapeutic effects in pulmonary hypertension. However, there have been few reports focusing on the impact of KATP on ECFC function under hypoxic condition. Therefore, the aim of this study was to investigate whether the opening of KATP could regulate hypoxia-induced ECFC dysfunction. Using ECFCs derived from adult peripheral blood, we observed that Iptakalim (Ipt), a novel KATP opener (KCO), significantly promoted ECFC function including cellular viability, proliferation, migration, angiogenesis, and apoptosis compared with ECFCs exposed to hypoxia. Glibenclamide (Gli), a nonselective KATP blocker, could eliminate the effects. The protective role of Ipt is attributed to an increased production of nitric oxide (NO), as well as an enhanced activation of angiogenic transduction pathways, containing Akt and endothelial nitric oxide synthase. Our observations demonstrated that KATP activation could improve ECFC function in hypoxia via Akt/endothelial nitric oxide synthase pathways, which may constitute increase ECFC therapeutic potential for hypoxia-associated pulmonary hypertension treatment.

Plasma indoleamine 2,3-dioxygenase activity as a potential biomarker for early diagnosis of multidrug-resistant tuberculosis in tuberculosis patients.

Purpose: Multidrug-resistant tuberculosis (MDR-TB) remains a challenge of global TB control, with difficulty in early detection of drug-sensitive tuberculosis (DS-TB). We investigate the diagnostic significance of IDO as a potential biomarker to discriminate MDR patients among the TB patients. Patients and methods: Plasma indoleamine 2,3-dioxygenase (IDO) was measured by the ratio of kynurenine (Kyn) to tryptophan (Trp) concentrations, using high performance liquid chromatography-mass spectrometry (LC-MS/MS). Chest computed tomography (CT) imaging signs from TB patients were collected and analyzed in 18 DS-TB patients, 16 MDR-TB patients, 6 lung cancer (LC) patients, and 11 healthy individuals. Lung imaging signs from TB patients were collected and analyzed. Results: We found that plasma IDO activity was significantly higher in the MDR-TB patients than in the DS-TB patients (p=0.012) and in the LC patients (p=0.003). We evaluated the diagnostic significance of plasma IDO activity in discriminating the MDR-TB group from the DS-TB group using a receiver operating characteristic (ROC) curve. With a cutoff level of 46.58 uM/mM, the diagnostic sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for IDO activity were 87.50%, 72.22%, 73.68%, and 86.67%, respectively. Plasma IDO activity was higher in cavity cases than in non-cavity cases (p=0.042), proving a positive correlation between lung cavity number and cavity size (p<0.05, separately) among all the TB patients studied. Conclusion: Our findings confirmed that plasma IDO activity might have an auxiliary diagnosis value for early discrimination of MDR-TB patients from DS-TB patients. Among the TB patients with cavitary lung lesions, higher plasma IDO activity can indicate a higher risk of MDR-TB.

Nicorandil Attenuates LPS-Induced Acute Lung Injury by Pulmonary Endothelial Cell Protection via NF-κB and MAPK Pathways.

Acute lung injury (ALI) is a devastating critical disease characterized by diffuse inflammation and endothelial dysfunction. Increasing evidence, including from our laboratory, has revealed that the opening of ATP-sensitive potassium (KATP) channels has promising anti-inflammation and endothelial protection activities in various disorders. However, the impacts of KATP channels on ALI remain obscure. In this study, we used nicorandil (Nico), a classic KATP channel opener, to investigate whether opening of KATP channels could alleviate ALI with an emphasis on human pulmonary artery endothelial cell (HPAEC) modulation. The results showed that Nico inhibited lipopolysaccharide- (LPS-) induced inflammatory response, protein accumulation, myeloperoxidase activity, and endothelial injury. In vitro, Nico reduced LPS-induced HPAEC apoptosis and the expression of cleaved-caspase-3, caspase-9, and CCAAT/enhancer-binding protein homologous protein (CHOP). Additionally, Nico inhibited inflammation by suppressing monocyte-endothelial adhesion and decreasing the expression of proinflammatory proteins. Moreover, Nico restored the expression and the distribution of adherens junction vascular endothelial- (VE-) cadherin. Further, Nico abolished the increase in intracellular reactive oxygen species (ROS) and the activation of NF-κB and mitogen-activated protein kinase (MAPK) in HPAECs. Glibenclamide (Gli), a nonselective KATP channel blocker, abrogated the effects of Nico, implying that opening of KATP channels contributes to the relief of ALI. Together, our findings indicated that Nico alleviated LPS-induced ALI by protecting ECs function via preventing apoptosis, suppressing endothelial inflammation and reducing oxidative stress, which may be attributed to the inhibition of NF-κB and MAPK signaling pathways.

The Superior Antitumor Effect of Self-Assembled Paclitaxel Nanofilaments for Lung Cancer Cells.

OBJECTIVES: Paclitaxel (Ptx) has been regarded as one of the most effective chemotherapeutic drugs for lung cancers. Increasing studies focused on the nano-delivery system of Ptx due to its poor solubility and hypersensitivity. The aim of the recent study was to investigate the antitumor effects of self-assembled Ptx nano-filaments for lung cancer cells. METHODS: In the present study, we designed and synthesized novel Ptx-loaded nano-filaments through conjugation of Ptx and succinic acid (SA) (Ptx-SA, P-NFs). Non-small cell lung cancer (NSCLC) A549 and H460 cells were used for detecting the antitumor effects of P-NFs, including cytotoxicity, apoptosis, and migration. Western blotting was performed for analyzing mechanism. RESULTS: P-NFs nano-filaments exerted superior antitumor effects against NSCLC cells compared with free Ptx using cytotoxicity tests. Furthermore, P-NFs nano-filaments were much more effective in inducing NSCLC cells apoptosis and inhibiting A549 cells migration than free Ptx. To elucidate the underlying mechanisms, the expression of apoptotic and endoplasmic reticulum (ER) stress proteins was detected. The results indicated that P-NFs nano-filaments enhanced the expression of bax/bcl-2, protein kinase RNA-like endoplasmic reticulum kinase (PERK), inositol-requiring enzyme 1α (IRE1α), phospho- c-Jun N-terminal kinase (p-JNK), and C/EPB homologous protein (CHOP), which suggested that the strong antitumor effect of P-NFs nano-filaments may be partially attributed to the activation ER stress. CONCLUSION: The current work demonstrated that P-NFs nano-filaments showed superior cytotoxicity of lung cancer cells, highlighting a novel profile of nano-filaments delivery systems as potential strategies for facilitating the therapeutic efficacy of Ptx in lung cancer treatment.

Inhibition of Shp2 ameliorates monocrotaline-induced pulmonary arterial hypertension in rats.

BACKGROUND: Src homology 2 containing protein tyrosine phosphatase (PTP) 2 (Shp2) is a typical tyrosine phosphatase interacting with receptor tyrosine kinase to regulate multiple signaling pathways in diverse pathological processes. Here, we will investigate the effect of Shp2 inhibition on pulmonary arterial hypertension (PAH) in a rat model and its potential cellular and molecular mechanisms underlying. METHODS: Monocrotaline (MCT)-induced PAH rat model was used in this study. Phps-1, a highly selective inhibitor for Shp2, was administered from 21 days to 35 days after MCT single-injection. Microcatheter method was applied to detected hemodynamic parameters. Histological methods were used to determine PVR changes in PAH rats. Moreover, cultured pulmonary artery smooth muscle cells (PASMCs) treated by platelet-derived growth factor (PDGF) with or without Phps-1 was used to investigate the potential cellular and molecular mechanisms underlying in vitro. RESULTS: Inhibition of Shp2 significantly attenuated MCT-induced increases of mean pulmonary arterial pressure (mPAP), right ventricular systolic pressure (RVSP) and right ventricular hypertrophy (RVH) in rats. Shp2 inhibition effectively decreased thickening of pulmonary artery media and cardiomyocyte hypertrophy as well as perivascular and myocardial fibrosis in MCT-treated rats. Moreover, Shp2 inhibition ameliorated muscularization of pulmonary arterioles in MCT-induced PAH rats. Shp2 inhibition significantly reduced platelet-derived growth factor (PDGF)-triggered proliferation and migration of human pulmonary artery smooth muscle cells (PASMCs), which might be attributed to the inactivations of Akt and Stat3 pathways. CONCLUSIONS: Shp2 contributes to the development of PAH in rats, which might be a potential target for the treatment of PAH.

Dipeptidyl peptidase IV (DPP-4) inhibition alleviates pulmonary arterial remodeling in experimental pulmonary hypertension.

Dipeptidyl peptidase IV (DPP-4) is well known for its role in glucose homeostasis, and DPP-4 inhibitor (DPP-4i) exhibits multiple actions in cardiovascular diseases. However, the effect of DPP-4i on pulmonary hypertension (PH) remains unclear. Therefore, this study aims to investigate the effect of DPP-4i on pulmonary arterial remodeling in rats with PH and the potential underlying mechanisms. Our results show that DPP-4 was expressed in epithelial cells, endothelial cells, smooth muscle cells, and inflammatory cells in lung. DPP-4i (Sitagliptin) attenuated right ventricular systolic pressure (RVSP), right ventricle remodeling, hypertrophy of pulmonary arterial medial layer, inflammatory cell infiltration, and endothelial-mesenchymal transition (EndMT) in monocrotaline (MCT)-induced PH rats. Similarly, DPP-4i also alleviated bleomycin- and chronic hypoxia-induced PH in rats. In cultured human pulmonary arterial smooth muscle cells (PASMCs), DPP-4i inhibited platelet derived growth factor (PDGF)-BB-induced proliferation and migration, which was abolished by phosphatase and tensin homolog deleted on chromosome ten (PTEN) knockout. These results demonstrate that DPP-4 inhibition alleviates pulmonary arterial remodeling in experimental PH by inhibiting proliferation and migration of PASMCs.