Generative Adversarial Network Model to Classify Human Induced Pluripotent Stem Cell-Cardiomyocytes based on Maturation Level.

Objective: Our study develops a generative adversarial network (GAN)-based method that generates faithful synthetic image data of human cardiomyocytes at varying stages in their maturation process, as a tool to significantly enhance the classification accuracy of cells and ultimately assist the throughput of computational analysis of cellular structure and functions. Methods: Human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs) were cultured on micropatterned collagen coated hydrogels of physiological stiffnesses to facilitate maturation and optical measurements were performed for their structural and functional analyses. Control groups were cultured on collagen coated glass well plates. These image recordings were used as the real data to train the GAN model. Results: The results show the GAN approach is able to replicate true features from the real data, and inclusion of such synthetic data significantly improves the classification accuracy compared to usage of only real experimental data that is often limited in scale and diversity. Conclusion: The proposed model outperformed four conventional machine learning algorithms with respect to improved data generalization ability and data classification accuracy by incorporating synthetic data. Significance: This work demonstrates the importance of integrating synthetic data in situations where there are limited sample sizes and thus, effectively addresses the challenges imposed by data availability.

Discovery of Terminal Oxazole-Bearing Natural Products by a Targeted Metabologenomic Approach.

A targeted metabologenomic method was developed to selectively discover terminal oxazole-bearing natural products from bacteria. For this, genes encoding oxazole cyclase, a key enzyme in terminal oxazole biosynthesis, were chosen as the genomic signature to screen bacterial strains that may produce oxazole-bearing compounds. Sixteen strains were identified from the screening of a bacterial DNA library (1,000 strains) using oxazole cyclase gene-targeting polymerase chain reaction (PCR) primers. The PCR amplicon sequences were subjected to phylogenetic analysis and classified into nine clades. 1H-13C coupled-HSQC NMR spectra obtained from the culture extracts of the hit strains enabled the unequivocal detection of the target compounds, including five new oxazole compounds, based on the unique 1JCH values and chemical shifts of oxazole: lenzioxazole (1) possessing an unprecedented cyclopentane, permafroxazole (2) bearing a tetraene conjugated with carboxylic acid, tenebriazine (3) incorporating two modified amino acids, and methyl-oxazolomycins A and B (4 and 5). Tenebriazine displayed inhibitory activity against pathogenic fungi, whereas methyl-oxazolomycins A and B (4 and 5) selectively showed anti-proliferative activity against estrogen receptor-positive breast cancer cells. This metabologenomic method enables the logical and efficient discovery of new microbial natural products with a target structural motif without the need for isotopic labeling.

Rotundifuran Induces Ferroptotic Cell Death and Mitochondria Permeability Transition in Lung Cancer Cells.

Rotundifuran (RF), a potent anti-inflammatory and anti-cancer compound, is a natural compound predominantly present in Vitex Rotundifolia. Herein, we investigated the effects of RF on the growth of lung cancer cells. Our findings suggested that RF inhibits cell growth, highlighting its potential as a therapeutic agent for cancer treatment. Interestingly, we observed that cell growth inhibition was not due to apoptosis, as caspases were not activated and DNA fragmentation did not occur. Furthermore, we found that intracellular vacuoles and autophagy were induced, but RF-induced cell death was not affected when autophagy was inhibited. This prompted us to investigate other possible mechanisms underlying cell growth inhibition. Through a cDNA chip analysis, we confirmed changes in the expression of ferroptosis-related genes and observed lipid peroxidation. We further examined the effect of ferroptosis inhibitors and found that they alleviated cell growth inhibition induced by RF. We also observed the involvement of calcium signaling, ROS accumulation, and JNK signaling in the induction of ferroptosis. Our findings suggested that RF is a potent anti-cancer drug and further studies are needed to validate its clinal use.

Optimization of Ultrasound-Assisted Pretreatment for Accelerating Rehydration of Adzuki Bean (Vigna angularis).

Adzuki bean (Vigna angularis), which provides plant-based proteins and functional substances, requires a long soaking time during processing, which limits its usefulness to industries and consumers. To improve this, ultrasonic treatment using high pressure and shear force was judged to be an appropriate pretreatment method. This study aimed to determine the optimal conditions of ultrasound treatment for the improved hydration of adzuki beans using the response surface methodology (RSM). Independent variables chosen to regulate the hydration process of the adzuki beans were the soaking time (2-14 h, X1), treatment intensity (150-750 W, X2), and treatment time (1-10 min, X3). Dependent variables chosen to assess the differences in the beans post-immersion were moisture content, water activity, and hardness. The optimal conditions for treatment deduced through RSM were a soaking time of 12.9 h, treatment intensity of 600 W, and treatment time of 8.65 min. In this optimal condition, the values predicted for the dependent variables were a moisture content of 58.32%, water activity of 0.9979 aw, and hardness of 14.63 N. Upon experimentation, the results obtained were a moisture content of 58.28 ± 0.56%, water activity of 0.9885 ± 0.0040 aw, and hardness of 13.01 ± 2.82 g, confirming results similar to the predicted values. Proper ultrasound treatment caused cracks in the hilum, which greatly affects the water absorption of adzuki beans, accelerating the rate of hydration. These results are expected to help determine economically efficient processing conditions for specific purposes, in addition to solving industrial problems associated with the low hydration rate of adzuki beans.

Isolation and Identification of Alternaria alternata from Potato Plants Affected by Leaf Spot Disease in Korea: Selection of Effective Fungicides.

Brown leaf spot disease caused by Alternaria spp. is among the most common diseases of potato crops. Typical brown spot symptoms were observed in commercial potato-cultivation areas of northern Korea from June to August 2020-2021. In total, 68 isolates were collected, and based on sequence analysis of the internal transcribed spacer (ITS) region, the collected isolates were identified as Alternaria spp. (80.9%). Phylogenetic analysis revealed that a majority of these isolates clustered within a clade that included A. alternata. Additionally, the ITS region and rpb2 yielded the most informative sequences for the identification of A. alternata. Pathogenicity tests confirmed that the collected pathogens elicited symptoms identical to those observed in the field. In pathogenicity tests performed on seven commercial cultivars, the pathogens exhibited strong virulence in both wound and non-wound inoculations. Among the cultivars tested, Arirang-1ho, Arirang-2ho, and Golden Ball were resistant to the pathogens. Furthermore, among the fungicides tested in vitro, mancozeb and difenoconazole were found to be effective for inhibiting mycelial growth. In summary, our findings suggest that A. alternata plays a critical role in leaf disease in potato-growing regions and emphasise the necessity of continuous monitoring and management to protect against this disease in Korea.

Validation of a Natural Language Machine Learning Model for Safety Literature Surveillance.

INTRODUCTION: As part of routine safety surveillance, thousands of articles of potential interest are manually triaged for review by safety surveillance teams. This manual triage task is an interesting candidate for automation based on the abundance of process data available for training, the performance of natural language processing algorithms for this type of cognitive task, and the small number of safety signals that originate from literature review, resulting in its lower risk profile. However, deep learning algorithms introduce unique risks and the validation of such models for use in Good Pharmacovigilance Practice remains an open question. OBJECTIVE: Qualifying an automated, deep learning approach to literature surveillance for use at AstraZeneca. METHODS: The study is a prospective validation of a literature surveillance triage model, comparing its real-world performance with that of human surveillance teams working in parallel. The biggest risk in modifying this triage process is missing a safety signal (resulting in model false negatives) and hence model recall is the main evaluation metric considered. RESULTS: The model demonstrates consistent global performance from training through testing, with recall rates comparable to that of existing surveillance teams. The model is accepted for use specifically for those products where non-inferiority to the manual process is rigorously demonstrated. CONCLUSION: Characterizing model performance prospectively, under real-world conditions, allows us to thoroughly examine model consistency and failure modes, qualifying it for use in our surveillance processes. We also identify potential future improvements and recognize the opportunity for the community to collaborate on this shared task.

Agrobacterium tumefaciens-Mediated Transformation of the Aquatic Fungus Phialemonium inflatum FBCC-F1546.

Phialemonium inflatum is a useful fungus known for its ability to mineralise lignin during primary metabolism and decompose polycyclic aromatic hydrocarbons (PAHs). However, no functional genetic analysis techniques have been developed yet for this fungus, specifically in terms of transformation. In this study, we applied an Agrobacterium tumefaciens-mediated transformation (ATMT) system to P. inflatum for a functional gene analysis. We generated 3689 transformants using the binary vector pSK1044, which carried either the hygromycin B phosphotransferase (hph) gene or the enhanced green fluorescent protein (eGFP) gene to label the transformants. A Southern blot analysis showed that the probability of a single copy of T-DNA insertion was approximately 50% when the co-cultivation of fungal spores and Agrobacterium tumefaciens cells was performed at 24-36 h, whereas at 48 h, it was approximately 35.5%. Therefore, when performing gene knockout using the ATMT system, the co-cultivation time was reduced to ≤36 h. The resulting transformants were mitotically stable, and a PCR analysis confirmed the genes' integration into the transformant genome. Additionally, hph and eGFP gene expressions were confirmed via PCR amplification and fluorescence microscopy. This optimised transformation system will enable functional gene analyses to study genes of interest in P. inflatum.

Corrigendum: Transcriptional inhibition of STAT1 functions in the nucleus alleviates Th1 and Th17 cell-mediated inflammatory diseases.

[This corrects the article DOI: 10.3389/fimmu.2022.1054472.].

Methyl lucidone inhibits airway inflammatory response by reducing TAK1 activity in human bronchial epithelial NCI-H292 cells.

Background: Methyl lucidone (ML), a methyl derivative of lucidone, has anti-inflammatory properties. However, the molecular mechanisms that reduce the inflammatory effect of ML in human lung epithelial cells remain unkown. This study aimed to elucidate the molecular mechanisms underlying the anti-inflammatory effect of ML. Methods: Four compounds (ML, methyl linderone, kanakugiol, and linderone) from Lindera erythrocarpa Makino were evaluated for their ability to reduce MUC5AC secretion levels in phorbol-12-myristate-13-acetate (PMA)-stimulated NCI-H292 cells using ELISA. The expression and secretion levels of inflammatory response-related proteins were analyzed using quantitative reverse transcription-PCR, ELISA, and western blotting. To determine whether ML directly regulates TGF-ß-activated kinase 1 (TAK1), we performed an in vitro kinase assay. Results: ML treatment effectively reduced the levels of inflammatory cytokines, including interleukin-1ß and TNF-α, increased by stimulation. Furthermore, ML downregulated the pathway cascade of both IκB kinase (IKK)/NF-κB and p38 mitogen-activated protein (MAP) kinase/CREB by inhibiting the upstream kinase TAK1. An in vitro kinase analysis confirmed that ML treatment significantly reduced the kinase activity of TAK1. Conclusion: ML pretreatment repressed the PMA-stimulated inflammation reaction by reducing the TAK1-mediated IKK/NF-κB and p38 MAP kinase/CREB signaling. These findings suggest that ML may improve respiratory health and can be used as a dietary supplement or functional food to prevent inflammatory lung diseases.

Lrig1-expression confers suppressive function to CD4+ cells and is essential for averting autoimmunity via the Smad2/3/Foxp3 axis.

Regulatory T cells (Treg) are CD4+ T cells with immune-suppressive function, which is defined by Foxp3 expression. However, the molecular determinants defining the suppressive population of T cells have yet to be discovered. Here we report that the cell surface protein Lrig1 is enriched in suppressive T cells and controls their suppressive behaviors. Within CD4+ T cells, Treg cells express the highest levels of Lrig1, and the expression level is further increasing with activation. The Lrig1+ subpopulation from T helper (Th) 17 cells showed higher suppressive activity than the Lrig1- subpopulation. Lrig1-deficiency impairs the suppressive function of Treg cells, while Lrig1-deficient naïve T cells normally differentiate into other T cell subsets. Adoptive transfer of CD4+Lrig1+ T cells alleviates autoimmune symptoms in colitis and lupus nephritis mouse models. A monoclonal anti-Lrig1 antibody significantly improves the symptoms of experimental autoimmune encephalomyelitis. In conclusion, Lrig1 is an important regulator of suppressive T cell function and an exploitable target for treating autoimmune conditions.

Garcinia mangostana Suppresses Triacylglycerol Synthesis in Hepatocytes and Enterocytes.

Regulation of diacylglycerol acyltransferase (DGAT) and pancreatic lipase (PL) activities is important in the treatment of triacylglycerol (TG)-related metabolic diseases. Garcinia mangostana, also known as mangosteen, is a traditional medicine ingredient used in the treatment of inflammation in Southeast Asia. In this study, The ethanolic extract of G. mangostana peel inhibited human recombinant DGAT1 and DGAT2, and PL enzyme activities in vitro. The inhibitory activity of DGAT1 and DGAT2 enzymes of four representative bioactive substances in mangosteen was confirmed. In addition, G. mangostana was confirmed to suppress the serum TG levels in C57 mice by inhibiting the absorption and synthesis of TG in the gastrointestinal tract. Through this study, it was revealed that G. mangostana extract could be useful for the prevention and amelioration of TG-related metabolic diseases such as obesity and fatty liver.

Black Ginseng Extract Exerts Potentially Anti-Asthmatic Activity by Inhibiting the Protein Kinase Cθ-Mediated IL-4/STAT6 Signaling Pathway.

Asthma is a chronic inflammatory lung disease that causes respiratory difficulties. Black ginseng extract (BGE) has preventative effects on respiratory inflammatory diseases such as asthma. However, the pharmacological mechanisms behind the anti-asthmatic activity of BGE remain unknown. To investigate the anti-asthmatic mechanism of BGE, phorbol 12-myristate 13-acetate plus ionomycin (PMA/Iono)-stimulated mouse EL4 cells and ovalbumin (OVA)-induced mice with allergic airway inflammation were used. Immune cells (eosinophils/macrophages), interleukin (IL)-4, -5, -13, and serum immunoglobulin E (IgE) levels were measured using an enzyme-linked immunosorbent assay. Inflammatory cell recruitment and mucus secretion in the lung tissue were estimated. Protein expression was analyzed via Western blotting, including that of inducible nitric oxide synthase (iNOS) and the activation of protein kinase C theta (PKCθ) and its downstream signaling molecules. BGE decreased T helper (Th)2 cytokines, serum IgE, mucus secretion, and iNOS expression in mice with allergic airway inflammation, thereby providing a protective effect. Moreover, BGE and its major ginsenosides inhibited the production of Th2 cytokines in PMA/Iono-stimulated EL4 cells. In EL4 cells, these outcomes were accompanied by the inactivation of PKCθ and its downstream transcription factors, such as nuclear factor of activated T cells (NFAT), nuclear factor kappa B (NF-κB), activator of transcription 6 (STAT6), and GATA binding protein 3 (GATA3), which are involved in allergic airway inflammation. BGE also inhibited the activation of PKCθ and the abovementioned transcriptional factors in the lung tissue of mice with allergic airway inflammation. These results highlight the potential of BGE as a useful therapeutic and preventative agent for allergic airway inflammatory diseases such as allergic asthma.

Targeted and Logical Discovery of Piperazic Acid-Bearing Natural Products Based on Genomic and Spectroscopic Signatures.

A targeted and logical discovery method was devised for natural products containing piperazic acid (Piz), which is biosynthesized from ornithine by l-ornithine N-hydroxylase (KtzI) and N-N bond formation enzyme (KtzT). Genomic signature-based screening of a bacterial DNA library (2020 strains) using polymerase chain reaction (PCR) primers targeting ktzT identified 62 strains (3.1%). The PCR amplicons of KtzT-encoding genes were phylogenetically analyzed to classify the 23 clades into two monophyletic groups, I and II. Cultivating hit strains in media supplemented with 15NH4Cl and applying 1H-15N heteronuclear multiple bond correlation (HMBC) along with 1H-15N heteronuclear single quantum coherence (HSQC) and 1H-15N HSQC-total correlation spectroscopy (HSQC-TOCSY) NMR experiments detected the spectroscopic signatures of Piz and modified Piz. Chemical investigation of the hit strains prioritized by genomic and spectroscopic signatures led to the identification of a new azinothricin congener, polyoxyperuin B seco acid (1), previously reported chloptosin (2) in group I, depsidomycin D (3) incorporating two dehydropiperazic acids (Dpz), and lenziamides A and B (4 and 5), structurally novel 31-membered cyclic decapeptides in group II. By consolidating the phylogenetic and chemical analyses, clade-structure relationships were elucidated for 19 of the 23 clades. Lenziamide A (4) inhibited STAT3 activation and induced G2/M cell cycle arrest, apoptotic cell death, and tumor growth suppression in human colorectal cancer cells. Moreover, lenziamide A (4) resensitized 5-fluorouracil (5-FU) activity in both in vitro cell cultures and the in vivo 5-FU-resistant tumor xenograft mouse model. This work demonstrates that the genomic and spectroscopic signature-based searches provide an efficient and general strategy for new bioactive natural products containing specific structural motifs.

Comparison of cancer subtype identification methods combined with feature selection methods in omics data analysis.

BACKGROUND: Cancer subtype identification is important for the early diagnosis of cancer and the provision of adequate treatment. Prior to identifying the subtype of cancer in a patient, feature selection is also crucial for reducing the dimensionality of the data by detecting genes that contain important information about the cancer subtype. Numerous cancer subtyping methods have been developed, and their performance has been compared. However, combinations of feature selection and subtype identification methods have rarely been considered. This study aimed to identify the best combination of variable selection and subtype identification methods in single omics data analysis. RESULTS: Combinations of six filter-based methods and six unsupervised subtype identification methods were investigated using The Cancer Genome Atlas (TCGA) datasets for four cancers. The number of features selected varied, and several evaluation metrics were used. Although no single combination was found to have a distinctively good performance, Consensus Clustering (CC) and Neighborhood-Based Multi-omics Clustering (NEMO) used with variance-based feature selection had a tendency to show lower p-values, and nonnegative matrix factorization (NMF) stably showed good performance in many cases unless the Dip test was used for feature selection. In terms of accuracy, the combination of NMF and similarity network fusion (SNF) with Monte Carlo Feature Selection (MCFS) and Minimum-Redundancy Maximum Relevance (mRMR) showed good overall performance. NMF always showed among the worst performances without feature selection in all datasets, but performed much better when used with various feature selection methods. iClusterBayes (ICB) had decent performance when used without feature selection. CONCLUSIONS: Rather than a single method clearly emerging as optimal, the best methodology was different depending on the data used, the number of features selected, and the evaluation method. A guideline for choosing the best combination method under various situations is provided.

Comparison of the pretreatment methods for enhancing hydration of water-soaked adzuki beans (Vigna angularis).

Five pretreatments methods, cold plasma, pressure drop, heating, and bath-type and probe-type sonications were compared to shorten the rehydration process of adzuki bean (Vigna angularis) soaked before the cooking in terms of the hydration and softening efficacies. Moisture content and water activity of the probe-type sonicated beans were most dramatically increased as 11-45% and 0.59-0.97 after soaking for only 2 h, respectively (non-treated: 11-12% and 0.59-0.66). Accordingly, the probe-type sonicated beans were most rapidly softened as 27-5 N in the 2 h-soaking and exhibited the lowest hardness after soaking/cooking as ~ 0.97 N (non-treated: 27-21 N and ~ 5.5 N, respectively). According to scanning electron micrographs, these results can be attributed to formation of prominent fissures or scars in the hilum of the probe-type sonicated beans. Consequently, this study will be provide valuable information for developing a rational process in food industry to shorten the rehydration of the adzuki beans.

Visual Complexity of Head-Up Display in Automobiles Modulates Attentional Tunneling.

OBJECTIVE: To investigate how the visual complexity of head-up displays (HUDs) influence the allocation of driver's attention in two separate visual domains (near and far domains). BACKGROUND: The types and amount of information displayed on automobile HUDs have increased. With limited human attention capacity, increased visual complexity in the near domain may lead to interference in the effective processing of information in the far domain. METHOD: Near-domain and far-domain vision were separately tested using a dual-task paradigm. In a simulated road environment, 62 participants were to control the speed of the vehicle (SMT; near domain) and manually respond to probes (PDT; far domain) simultaneously. Five HUD complexity levels including a HUD-absent condition were presented block-wise. RESULTS: Near domain performance was not modulated by the HUD complexity levels. However, the far domain detection accuracies were impaired as the HUD complexity level increased, with greater accuracy differences observed between central and peripheral probes. CONCLUSION: Increased HUD visual complexity leads to a biased deployment of driver attention toward the central visual field. Therefore, the formulation of HUD designs must be preceded by an in-depth investigation of the dynamics of human cognition. APPLICATION: To ensure driving safety, HUD designs should be rendered with minimal visual complexity by incorporating only essential information relevant to driving and removing driving-irrelevant or additional visual details.

Epigenetic and Metabolic Changes in Diffuse Intrinsic Pontine Glioma.

Diffuse midline glioma (DMG), hitherto known as diffuse intrinsic pontine glioma (DIPG), is a rare and aggressive form of brain cancer that primarily affects children. Although the exact cause of DMG/DIPG is not known, a large proportion of DMG/DIPG tumors harbor mutations in the gene encoding the histone H3 protein, specifically the H3K27M mutation. This mutation decreases the level of H3K27me3, a histone modification that plays a vital role in regulating gene expression through epigenetic regulation. The mutation also alters the function of polycomb repressive complex 2 (PRC2), thereby preventing the repression of genes associated with cancer development. The decrease in H3K27me3 caused by the histone H3 mutation is accompanied by an increase in the level of H3K27ac, a post-translational modification related to active transcription. Dysregulation of histone modification markedly affects gene expression, contributing to cancer development and progression by promoting uncontrolled cell proliferation, tumor growth, and metabolism. DMG/DIPG alters the metabolism of methionine and the tricarboxylic acid cycle, as well as glucose and glutamine uptake. The role of epigenetic and metabolic changes in the development of DMG/DIPG has been studied extensively, and understanding these changes is critical to developing therapies targeting these pathways. Studies are currently underway to identify new therapeutic targets for DMG/DIPG, which may lead to the development of effective treatments for this devastating disease.

Diplacone Isolated from Paulownia tomentosa Mature Fruit Induces Ferroptosis-Mediated Cell Death through Mitochondrial Ca2+ Influx and Mitochondrial Permeability Transition.

The recently defined type of cell death ferroptosis has garnered significant attention as a potential new approach to cancer treatment owing to its more immunogenic nature when compared with apoptosis. Ferroptosis is characterized by the depletion of glutathione (GSH)/glutathione peroxidase-4 (GPx4) and iron-dependent lipid peroxidation. Diplacone (DP), a geranylated flavonoid compound found in Paulownia tomentosa fruit, has been identified to have anti-inflammatory and anti-radical activity. In this study, the potential anticancer activity of DP was explored against A549 human lung cancer cells. It was found that DP induced a form of cytotoxicity distinct from apoptosis, which was accompanied by extensive mitochondrial-derived cytoplasmic vacuoles. DP was also shown to increase mitochondrial Ca2+ influx, reactive oxygen species (ROS) production, and mitochondrial permeability transition (MPT) pore-opening. These changes led to decreases in mitochondrial membrane potential and DP-induced cell death. DP also induced lipid peroxidation and ATF3 expression, which are hallmarks of ferroptosis. The ferroptosis inhibitors ferrostatin-1 and liproxstatin-1 were effective in counteracting the DP-mediated ferroptosis-related features. Our results could contribute to the use of DP as a ferroptosis-inducing agent, enabling studies focusing on the relationship between ferroptosis and the immunogenic cell death of cancer cells.

Verproside, the Most Active Ingredient in YPL-001 Isolated from Pseudolysimachion rotundum var. subintegrum, Decreases Inflammatory Response by Inhibiting PKCδ Activation in Human Lung Epithelial Cells.

Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory lung disease which causes breathing problems. YPL-001, consisting of six iridoids, has potent inhibitory efficacy against COPD. Although YPL-001 has completed clinical trial phase 2a as a natural drug for COPD treatment, the most effective iridoid in YPL-001 and its mechanism for reducing airway inflammation remain unclear. To find an iridoid most effectively reducing airway inflammation, we examined the inhibitory effects of the six iridoids in YPL-001 on TNF or PMA-stimulated inflammation (IL-6, IL-8, or MUC5AC) in NCI-H292 cells. Here, we show that verproside among the six iridoids most strongly suppresses inflammation. Both TNF/NF-κB-induced MUC5AC expression and PMA/PKCδ/EGR-1-induced IL-6/-8 expression are successfully reduced by verproside. Verproside also shows anti-inflammatory effects on a broad range of airway stimulants in NCI-H292 cells. The inhibitory effect of verproside on the phosphorylation of PKC enzymes is specific to PKCδ. Finally, in vivo assay using the COPD-mouse model shows that verproside effectively reduces lung inflammation by suppressing PKCδ activation and mucus overproduction. Altogether, we propose YPL-001 and verproside as candidate drugs for treating inflammatory lung diseases that act by inhibiting PKCδ activation and its downstream pathways.

Dual fluorescent hollow silica nanofibers for in situ pH monitoring using an optical fiber.

This study reports a sensitive and robust pH sensor based on dual fluorescent doped hollow silica nanofibers (hSNFs) for in situ and real-time pH monitoring. Fluorescein isothiocyanate (FITC) and tris(2,2'-bipyridyl)dichlororuthenium(ii) hexahydrate (Ru(BPY)3) were chosen as a pH sensitive dye and reference dye, respectively. hSNFs were synthesized using a two-step method in a reverse micelle system and were shown to have an average length of 6.20 µm and average diameter of 410 nm. The peak intensity ratio of FITC/Ru(BPY)3 was used to calibrate to solution pH changes. An optical-fiber-based fluorescence detection system was developed that enabled feasible and highly efficient near-field fluorescence detection. The developed system enables fully automated fluorescence detection, where components including the light source, detector, and data acquisition unit are all controlled by a computer. The results show that the developed pH sensor works in a linear range of pH 4.0-9.0 with a fast response time of less than 10 s and minimal sample volume of 50 µL, and can be stored under dark conditions for one month without failure. In addition, the as-prepared hSNF-based pH sensors also have excellent long-term durability. Experimental results from ratiometric sensing confirm the high feasibility, accuracy, stability and simplicity of the dual fluorescent hSNF sensors for the detection of pH in real samples.