Preventive effects of inotodiol on polyinosinic-polycytidylic acid-induced inflammation in human dermal fibroblasts.

Double-strand RNA(dsRNA), which can induce inflammation, can be generated by necrotic keratinocytes in the skin environment. As an analog of dsRNA, polyinosinic-polycytidylic acid (poly(I:C)) is used to induce inflammation via the Toll-like Receptor 3 (TLR3) signaling pathway. Inotodiol, isolated from Inonotus obliquus, known as Chaga mushroom, is a natural lanostane-type triterpenoid with significant pharmacological activity and notable anti-inflammatory effects. However, the functions of inotodiol on dsRNA-induced inflammation in human dermal fibroblast (HDFs) remains unclear. In this study, we evaluated the anti-inflammatory effects of inotodiol inflammation induced on by poly(I:C) in HDFs. After pre-treatment with inotodiol, poly (I:C) was used to induce inflammation. Subsequently, mRNA expression and protein secretion of inflammatory cytokines, as well as TLR3 signaling protein levels were assessed. Inflammatory cytokines IL-1ß, IL-6, and TNF-α's increased mRNA expression by poly(I:C) in HDFs was significantly suppressed in the inotodiol pre-treatment group in a dose-dependent manner. A similar pattern was evaluated in the protein levels of these three cytokines. The inflammatory signals of TLR3 via p-IKK, p-p38, and NF-κB was reduced by inotodiol pre-treatment. Taken together, inotodiol possesses strong anti-inflammatory activity against poly(I:C)-induced inflammation in HDFs. Therefore, our findings support potential application of inotodiol as an effective anti-inflammatory agent in cosmetics.

Small Files Problem Resolution via Hierarchical Clustering Algorithm.

The Small Files Problem in Hadoop Distributed File System (HDFS) is an ongoing challenge that has not yet been solved. However, various approaches have been developed to tackle the obstacles this problem creates. Properly managing the size of blocks in a file system is essential as it saves memory and computing time and may reduce bottlenecks. In this article, a new approach using a Hierarchical Clustering Algorithm is suggested for dealing with small files. The proposed method identifies the files by their structure and via a special Dendrogram analysis, and then recommends which files can be merged. As a simulation, the proposed algorithm was applied via 100 CSV files with different structures, containing 2-4 columns with different data types (integer, decimal and text). Also, 20 files that were not CSV files were created to demonstrate that the algorithm only works on CSV files. All data were analyzed via a machine learning hierarchical clustering method, and a Dendrogram was created. According to the merge process that was performed, seven files from the Dendrogram analysis were chosen as appropriate files to be merged. This reduced the memory space in the HDFS. Furthermore, the results showed that using the suggested algorithm led to efficient file management.

Roles and current applications of S-nitrosoglutathione in anti-infective biomaterials.

Bacterial infections can compromise the physical and biological functionalities of humans and pose a huge economical and psychological burden on infected patients. Nitric oxide (NO) is a broad-spectrum antimicrobial agent, whose mechanism of action is not affected by bacterial resistance. S-nitrosoglutathione (GSNO), an endogenous donor and carrier of NO, has gained increasing attention because of its potent antibacterial activity and efficient biocompatibility. Significant breakthroughs have been made in the application of GSNO in biomaterials. This review is based on the existing evidence that comprehensively summarizes the progress of antimicrobial GSNO applications focusing on their anti-infective performance, underlying antibacterial mechanisms, and application in anti-infective biomaterials. We provide an accurate overview of the roles and applications of GSNO in antibacterial biomaterials and shed new light on the avenues for future studies.

DNA-directed coimmobilization of multiple enzymes on organic-inorganic hybrid DNA flowers.

The artificial multienzyme systems developed by mimicking nature has attracted much interest. However, precisely controlled compositions and ratios of multienzymatic co-immobilization systems are still limited by the indistinguishable nature of enzymes. Herein, a strategy for fabricating DNA-directed immobilization of horseradish peroxidase (HRP) and glucose oxidase (GOx) on hybrid DNA nanoflowers (GOx-HRP@hDFs) is presented. The preparation of micron-sized hybrid DNA flowers (hDFs) begins with the predetermined repeatable polymer-like DNA sequences which contained two strands. The hDFs structure is generated through one-pot rolling circle amplification (RCA) and self-assembly with magnesium pyrophosphate inorganic crystals. Based on the rigid-base pairing, GOx and HRP conjugated with sequences complementary to strands would be anchored to the predesigned locations, respectively. By adjusting the loading amount/ratio of enzymes properly, the maximal catalytic efficiency can be precisely regulated. The reaction activity of GOx-HRP@hDFs was 7.4 times higher than that of the free GOx-HRP under the optimal mole ratio (GOx/HRP 4:1). In addition, this multienzyme catalyst system exhibits excellent precision, specificity, reproducibility, and long-term storage stability when applied to real human blood samples. The preceding results validate that GOx-HRP@hDFs are promising candidates for personal diabetes detection.

Effects of conditioned medium obtained from human adipose-derived stem cells on skin inflammation.

Introduction: Cell therapy using adipose-derived mesenchymal stem cells (ASCs) is a promising avenue of regenerative medicine for the treatment of various diseases. It has been considered that ASCs exert their therapeutic effects through the secretion of multiple factors that are critical for tissue remodeling or the suppression of inflammation. Recently, conditioned medium (CM) from ASCs that contains a complex of secreted factors has received attention as a cost-effective alternative to cell therapy. Methods: We investigated the effects of CM obtained from ASCs (ASCs-CM) using human dermal fibroblasts (hDFs) and human epidermal keratinocytes with or without interleukin (IL)-1ß and examined mRNA levels of marker genes. We also examined alterations in cell proliferation and morphology of hDFs following treatment with ASCs-CM. We further investigated the effects of ASCs-CM treatment on prevention of skin inflammation using a mouse model. Results: In hDFs and human epidermal keratinocytes, the ASCs-CM treatment suppressed pro-inflammatory factors and enhanced regenerative and remodeling factors with or without interleukin (IL)-1ß exposure. The ASCs-CM treatment also enhanced cell proliferation of hDFs and prevented morphological changes in response to IL-1ß exposure. Furthermore, in a mouse model of skin inflammation, treatment with ASCs-CM reduced the inflammatory reactions, including redness and thickness. Conclusions: CM from ASCs may represent a potential alternative to ASC therapy for the treatment of inflammatory skin conditions.

Continuous Production of Highly Tuned Silk/Calcium-Based Composites: Exploring New Pathways for Skin Regeneration.

Calcium plays an important role in barrier function repair and skin homeostasis. In particular, calcium phosphates (CaPs) are well established materials for biomedical engineering due to their biocompatibility. To generate biomaterials with a more complete set of biological properties, previously discarded silk sericin (SS) has been recovered and used as a template to grow CaPs. Crucial characteristics for skin applications, such as antibacterial activity, can be further enhanced by doping CaPs with cerium (Ce) ions. The effectiveness of cell attachment and growth on the materials highly depends on their morphology, particle size distribution, and chemical composition. These characteristics can be tailored through the application of oscillatory flow technology, which provides precise mixing control of the reaction medium. Thus, in the present work, CaP/SS and CaP/SS/Ce particles were fabricated for the first time using a modular oscillatory flow plate reactor (MOFPR) in a continuous mode. Furthermore, the biological behavior of both these composites and of previously produced pure CaPs was assessed using human dermal fibroblasts (HDFs). It was demonstrated that both CaP based with plate-shaped nanoparticles and CaP-SS-based composites significantly improved cell viability and proliferation over time. The results obtained represent a first step towards the reinvention of CaPs for skin engineering.

A novel 3D polycaprolactone high-throughput system for evaluation of toxicity in normoxia and hypoxia.

Two-dimensional (2D) culturing of cancer cells has been indispensable for the development of anti-cancer drugs. Drug development, however, is lengthy and costly with a high attrition rate, calling to mind that 2D culturing does not mimic the three-dimensional (3D) tumour microenvironment in vivo. Thus, began the development of 3D culture models for cancer research. We have constructed a 3D 96-well plate using electrospun fibres made of biocompatible polycaprolactone (PCL). Finely-cut PCL fibre pieces in water/ethanol solution was pipetted to the wells of hydrophobic 96-well plates. A fibrous network of approximately 200 µm thickness and high porosity was formed after crosslinking and drying. Human JIMT-1 breast cancer cells or fibroblasts were seeded into the network. Confocal microscopy shows that the cells grow throughout the fibre network. The toxicity of paclitaxel and an experimental salinomycin analogue was assessed and compared in 2D and 3D cultures incubated under conditions of normoxia and hypoxia often found in tumours. The toxicity of both compounds is lower when the cells are cultured in 3D compared to 2D in either normoxia or hypoxia. We conclude that our 96-well assay is a cost-efficient tool that may be used for high-throughput pre-clinical screening of potential anti-cancer compounds.

High Glucose Causes Distinct Expression Patterns of Primary Human Skin Cells by RNA Sequencing.

Diabetes-related skin problems represent the most common long-term complications in diabetes mellitus patients. These complications, which include diabetic dermopathy, diabetic blisters, necrobiosis lipoidica diabeticorum, and eruptive xanthomatosis, may dramatically impair patients' quality of life and cause long-lasting disability. However, the cellular and molecular mechanisms linking diabetes-related hyperglycemia and skin complications are still incompletely understood. To assess the role of the various skin-cell types in hyperglycemia-induced skin disorders, we performed RNA sequencing-based transcriptome analysis, measuring gene expression patterns in biological replicates in normal- and high glucose-stimulated skin cells. Three primary human skin-cell types were examined, i.e., epidermal keratinocytes, dermal fibroblasts, and dermal microvascular endothelial cells. For each separate cell type, we identified gene expression. Comparing gene abundances and expression levels revealed that transcription profiles exhibit distinct patterns in the three skin-cell types exposed to normal (i.e., physiological) glucose treatment and high (i.e., supraphysiological) glucose treatment. The obtained data indicate that high glucose induced differential gene expression and distinct activity patterns in signaling pathways in each skin-cell type. We are adding these data to the public database in the hope that they will facilitate future studies to develop novel targeted interventions for diabetic skin complications.

Anti-Inflammatory Effects of Alnus Sibirica Extract on In Vitro and In Vivo Models.

Alnus sibirica extracts (ASex) have long been used in Oriental medicine to treat various conditions. To provide a scientific basis for this application and the underlying mechanism, we investigated the anti-inflammatory effects of ASex in vitro and in vivo. The in vitro model was established using human dermal fibroblasts (HDFs) treated with inflammatory stimulants (lipopolysaccharide, tumor necrosis factor-alpha, interferon-gamma). Lactate dehydrogenase and reverse transcription-polymerase chain reaction showed that ASex inhibited the increased expression of acute-phase inflammatory cytokines. The in vivo model was established by inducing skin inflammation in NC/Nga mice via the repeated application of house dust mite (HDM) ointment to the ears and back of the mice for eight weeks. HDM application increased the severity of skin lesions, eosinophil/mast cell infiltration, and serum immunoglobulin E levels, which were all significantly decreased by ASex treatment, demonstrating the same degree of protection as hydrocortisone. Overall, ASex showed excellent anti-inflammatory effects both in vitro and in vivo, suggesting its potential as an excellent candidate drug to reduce skin inflammation.

Attribute based honey encryption algorithm for securing big data: Hadoop distributed file system perspective.

Hadoop has become a promising platform to reliably process and store big data. It provides flexible and low cost services to huge data through Hadoop Distributed File System (HDFS) storage. Unfortunately, absence of any inherent security mechanism in Hadoop increases the possibility of malicious attacks on the data processed or stored through Hadoop. In this scenario, securing the data stored in HDFS becomes a challenging task. Hence, researchers and practitioners have intensified their efforts in working on mechanisms that would protect user's information collated in HDFS. This has led to the development of numerous encryption-decryption algorithms but their performance decreases as the file size increases. In the present study, the authors have enlisted a methodology to solve the issue of data security in Hadoop storage. The authors have integrated Attribute Based Encryption with the honey encryption on Hadoop, i.e., Attribute Based Honey Encryption (ABHE). This approach works on files that are encoded inside the HDFS and decoded inside the Mapper. In addition, the authors have evaluated the proposed ABHE algorithm by performing encryption-decryption on different sizes of files and have compared the same with existing ones including AES and AES with OTP algorithms. The ABHE algorithm shows considerable improvement in performance during the encryption-decryption of files.

HaRD: a heterogeneity-aware replica deletion for HDFS.

The Hadoop distributed file system (HDFS) is responsible for storing very large data-sets reliably on clusters of commodity machines. The HDFS takes advantage of replication to serve data requested by clients with high throughput. Data replication is a trade-off between better data availability and higher disk usage. Recent studies propose different data replication management frameworks that alter the replication factor of files dynamically in response to the popularity of the data, keeping more replicas for in-demand data to enhance the overall performance of the system. When data gets less popular, these schemes reduce the replication factor, which changes the data distribution and leads to unbalanced data distribution. Such an unbalanced data distribution causes hot spots, low data locality and excessive network usage in the cluster. In this work, we first confirm that reducing the replication factor causes unbalanced data distribution when using Hadoop's default replica deletion scheme. Then, we show that even keeping a balanced data distribution using WBRD (data-distribution-aware replica deletion scheme) that we proposed in previous work performs sub-optimally on heterogeneous clusters. In order to overcome this issue, we propose a heterogeneity-aware replica deletion scheme (HaRD). HaRD considers the nodes' processing capabilities when deleting replicas; hence it stores more replicas on the more powerful nodes. We implemented HaRD on top of HDFS and conducted a performance evaluation on a 23-node dedicated heterogeneous cluster. Our results show that HaRD reduced execution time by up to 60%, and 17% when compared to Hadoop and WBRD, respectively.

Isolating human dermal fibroblasts using serial explant culture.

BACKGROUND: The purpose of this study was to introduce an applicable culture technique to isolate human dermal fibroblasts (HDFs); which could also contribute to research, clinical practices, as well as tissue engineering. METHODS: Samples from the human skin were dissected and cultured via serial explant technique. Subsequently, the isolated fibroblasts were assessed for their protein markers and genetic variations via immunofluorescence (IF) and karyotyping; respectively. Following the employment of this technique, a small piece of explant completely disappeared; while no dermis remained after 10 days. RESULTS: The quantity of HDFs harvested through this culture technique was reported at a normal level. The results of immunostaining also indicated that the isolated fibroblasts had expressed vimentin and fibronectin; whereas no cells had shown cytokeratin and epidermal marker. Moreover, karyotyping results for the fibroblasts isolated by the given technique revealed no chromosomal diversity after passage 20. CONCLUSIONS: It was concluded that serial explant culture was an efficient technique for isolating HDFs from a small piece of skin in short-time periods; which could also preserve their normal morphology and molecular characteristics.

Phenotype Algorithm based Big Data Analytics for Cancer Diagnose.

Nowadays, Cancer diagnosis is one of the major challenging characteristics for treating cancer. The reality of cancer patients rely on the diagnosis of cancer at the early stages (either in stage 1 or stage 2). If the cancer is diagnosed in stage 3 or later stages means the changes of survival of the patient will become more critical. Normally, single patient records will generate a huge amount of data if the data could be manage and analyze means to solve many problems for identifying the patterns it will leads to diagnose the cancer. Recent work several machine learning algorithms are introduced for the classification of cancer. However still the classification accuracy of machine learning algorithms are reduced because of huge number of samples. So the proposed work introduces a new Hadoop Distributed File System (HDFS) is focused in this work. In this paper, the proposed phenotype techniques are used which handle and classifies the raw EHR (Electronic Health Record) and EMR (Electronic Medical Record). It is based on the HDFS and Two-Phase Map Reduce. Phenotype algorithm uses NLP (National Language Processing) tool which will analyze and classify the cancer patient data like gene mapping, age related data, image and ultrasonic frequency processing, identification and analysis of irregularities, disease and personal histories. In this paper, the three factorized model is used which calculates the mean score values. The values are calculated by disease stage, pain status, etc. This paper focuses big data analytics for cancer diagnosis and the simulation results shows the proposed system produces the highest performance.

Protective effect of green tea catechin against urban fine dust particle-induced skin aging by regulation of NF-κB, AP-1, and MAPKs signaling pathways.

The increase in ambient fine dust particles (FDP) due to urbanization and industrialization has been identified as a major contributor to air pollution. It has become a serious issue that threatens human health because it causes respiratory diseases and skin aging. In the present study, the protective effect of the green tea catechin, (-)-epigallocatechin gallate (EGCG), against FDP (ERM-CZ100)-stimulated skin aging in human dermal fibroblasts (HDFs) was investigated. The results demonstrate that EGCG significantly and dose-dependently scavenged intracellular reactive oxygen species (ROS) in and increased the viability of FDP-stimulated HDFs. In addition, EGCG dose-dependently recovered collagen synthesis and inhibited intracellular elastase and collagenase activities. Moreover, EGCG decreased the expression of human matrix metalloproteinases (MMPs) via regulation of nuclear factor kappa B (NF-κB), activator protein 1 (AP-1), and mitogen-activated protein kinases (MAPKs) signaling pathways in FDP-stimulated HDFs. This study suggests that EGCG is a potential anti-aging candidate that can be used for FDP-induced skin aging as a therapeutic agent itself or as an ingredient in pharmaceutical and cosmeceutical products.

Histological evaluation of tendon formation using a scaffold-free three-dimensional-bioprinted construct of human dermal fibroblasts under in vitro static tensile culture.

INTRODUCTION: Tendon tissue engineering requires scaffold-free techniques for safe and long-term clinical applications and to explore alternative cell sources to tenocytes. Therefore, we histologically assessed tendon formation in a scaffold-free Bio-three-dimensional (3D) construct developed from normal human dermal fibroblasts (NHDFs) using our Bio-3D printer system under tensile culture in vitro. METHODS: Scaffold-free ring-like tissues were constructed from 120 multicellular spheroids comprising NHDFs using a bio-3D printer. Ring-like tissues were cultured in vitro under static tensile-loading with or without in-house tensile devices (tension-loaded and tension-free groups), with increases in tensile strength applied weekly to the tensile-loaded group. After a 4 or 8-week culture on the device, we evaluated histological findings according to tendon-maturing score and immunohistological findings of the middle portion of the tissues for both groups (n = 4, respectively). RESULTS: Histology of the tension-loaded group revealed longitudinally aligned collagen fibers with increased collagen deposition and spindle-shaped cells with prolonged culture. By contrast, the tension-free group showed no organized cell arrangement or collagen fiber structure. Additionally, the tension-loaded group showed a significantly improved tendon-maturing score as compared with that for the tension-free group at week 8. Moreover, immunohistochemistry revealed tenascin C distribution with a parallel arrangement in the tensile-loading direction at week 8 in the tension-loaded group, which exhibited stronger scleraxis-staining intensity than that observed in the tension-free group at weeks 4 and 8. CONCLUSIONS: The NHDF-generated scaffold-free Bio-3D construct underwent remodeling and formed tendon-like structures under tensile culture in vitro.

Effects of low-dose ALA-PDT on fibroblast photoaging induced by UVA irradiation and the underlying mechanisms.

OBJECTIVES: To investigate the effects of low-dose aminolevulinic acid photodynamic therapy (ALA-PDT) on photoaging in human dermal fibroblasts (HDFs) and to explore the mechanism of Nuclear factor erythroid 2-related factor 2(Nrf2)-mediated photorejuvenation in vitro. METHODS: A photoaging model was established through repeated exposure of HDFs to UVA. Total superoxide dismutase (SOD) expression was detected by a SOD activity assay. Nrf2 was knocked down through adenovirus infection, and successful knockdown was confirmed by Western blot analysis and quantitative polymerase chain reaction. RESULTS: Sustained exposure to UVA induced photoaging in HDFs. Total SOD activity was significantly increased by low-dose aminolevulinic acid (ALA)-PDT. Upon application of low doses of ALA-PDT to photoaging HDFs, Nrf2 was translocated to the nucleus; in addition, the expression of Nrf2, transforming growth factor-ß1 (TGF-ß1), type I and III collagen (COL1 and COL3), heme oxygenase 1 (HO-1), and p-ERK was increased, while the expression of matrix metalloproteinase 9 (MMP-9) was decreased. However, after Nrf2 was knocked down in HDFs, the expression of TGF-ß1, COL1, COL3, and HO-1 was significantly decreased, while the expression of MMP-9 was increased. CONCLUSION: This study revealed that low-dose ALA-PDT decreases UVA-mediated photoaging through an Nrf2-mediated antioxidant effect.

ParStream-seq: An improved method of handling next generation sequence data.

The exponential growth of next generation sequencing (NGS) data has put forward the challenge for its storage as well as its efficient and faster analysis. Storing the entire amount of data for a particular experiment and its alignment to the reference genome is an essential step for any quantitative analysis of NGS data. Here, we introduce streaming access technique 'ParStream-seq' that splits the bulk sequence data, accessed from a remote repository into short manageable packets followed by executing their alignment process in parallel in each of the compute core. The optimal packet size with fixed number of reads is determined in the stream that maximizes system utilization. Result shows a reduction in the execution time and improvement in the memory footprint. Overall, this streaming access technique provides means to overcome the hurdle of storing the entire volume of sequence data corresponding to a particular experiment, prior to its analysis.

Restoring Effects of Natural Anti-Oxidant Quercetin on Cellular Senescent Human Dermal Fibroblasts.

The oxidative damage initiated by reactive oxygen species (ROS) is a major contributor to the functional decline and disability that characterizes aging. The anti-oxidant flavonoid, quercetin, is a plant polyphenol that may be beneficial for retarding the aging process. We examined the restoring properties of quercetin on human dermal fibroblasts (HDFs). Quercetin directly reduced either intracellular or extracellular ROS levels in aged HDFs. To find the aging-related target genes by quercetin, microarray analysis was performed and two up-regulated genes LPL and KCNE2 were identified. Silencing LPL increased the expression levels of senescence proteins such as p16INK4A and p53 and silencing KCNE2 reversed gene expressions of EGR1 and p-ERK in quercetin-treated aged HDFs. Silencing of LPL and KCNE2 decreased the expression levels of anti-oxidant enzymes such as superoxide dismutase and catalase. Also, the mitochondrial dysfunction in aged HDFs was ameliorated by quercetin treatment. Taken together, these results suggest that quercetin has restoring effect on the cellular senescence by down-regulation of senescence activities and up-regulation of the gene expressions of anti-oxidant enzymes in aged HDFs.

Effect of adipose-derived stem cell conditioned medium on UVB damage of human dermal fibroblasts in different senescent degrees / 中华医学美学美容杂志

Objective To study the differences of UVB damage among yong,intermediate and aged human dermal fibroblasts (HDFs),the recovery effect of adipose-derived stem cell conditioned medium (ADSC-CM) on UVB damage and the relationship between the recovery effect and ADSC-CM concentration as well as its treating period.Methods HDFs were cultured at different senescent degrees in vitro to establish UVB damage model of HDFs,and then the HDFs were cultured in different concentration ADSC-CM and cellular proliferation was detected.Results The optimal treating period and concentration of ADSC-CM were 48h and 100％ respectively.As to HDFs in different senescent degrees,ADSC-CM was able to accelerate cellular proliferation in both UVB group and control group.Conclusions Independently or simultaneously,the intrinsic and extrinsic factors can cause ageing damages on HDFs.To some extent,ADSC-CM has recovery effect on the damages through secretomes from ADSC.

Efficient Retrieval of Massive Ocean Remote Sensing Images via a Cloud-Based Mean-Shift Algorithm.

The rapid development of remote sensing (RS) technology has resulted in the proliferation of high-resolution images. There are challenges involved in not only storing large volumes of RS images but also in rapidly retrieving the images for ocean disaster analysis such as for storm surges and typhoon warnings. In this paper, we present an efficient retrieval of massive ocean RS images via a Cloud-based mean-shift algorithm. Distributed construction method via the pyramid model is proposed based on the maximum hierarchical layer algorithm and used to realize efficient storage structure of RS images on the Cloud platform. We achieve high-performance processing of massive RS images in the Hadoop system. Based on the pyramid Hadoop distributed file system (HDFS) storage method, an improved mean-shift algorithm for RS image retrieval is presented by fusion with the canopy algorithm via Hadoop MapReduce programming. The results show that the new method can achieve better performance for data storage than HDFS alone and WebGIS-based HDFS. Speedup and scaleup are very close to linear changes with an increase of RS images, which proves that image retrieval using our method is efficient.