The role of initial geometry in experimental models of wound closing

Wound healing assays are commonly used to study how populations of cells, initialised on a two-dimensional surface, act to close an artificial wound space. While real wounds have different shapes, standard wound healing assays often deal with just one simple wound shape, and it is unclear whether varying the wound shape might impact how we interpret results from these experiments. In this work, we describe a new kind of wound healing assay, called a sticker assay, that allows us to examine the role of wound shape in a series of wound healing assays performed with fibroblast cells. In particular, we show how to use the sticker assay to examine wound healing with square, circular and triangular shaped wounds. We take a standard approach and report measurements of the size of the wound as a function of time. This shows that the rate of wound closure depends on the initial wound shape. This result is interesting because the only aspect of the assay that we change is the initial wound shape, and the reason for the different rate of wound closure is unclear. To provide more insight into the experimental observations we describe our results quantitatively by calibrating a mathematical model, describing the relevant transport phenomena, to match our experimental data. Overall, our results suggest that the rates of cell motility and cell proliferation from different initial wound shapes are approximately the same, implying that the differences we observe in the wound closure rate are consistent with a fairly typical mathematical model of wound healing. Our results imply that parameter estimates obtained from an experiment performed with one particular wound shape could be used to describe an experiment performed with a different shape. This fundamental result is important because this assumption is often invoked, but never tested

Acute kidney disease following COVID-19 vaccination: a single-center retrospective study

BackgroundRare cases of de novo or relapsed kidney diseases associated with vaccination against coronavirus disease 2019 (COVID-19) have been increasingly reported. The aim of this study was to report the incidence, etiologies, and outcomes of acute kidney disease (AKD) following COVID-19 vaccination.MethodsThis retrospective study extracted cases from renal registry of a single medical center from 1 March 2021 to 30 April 2022, prior to the significant surge in cases of the Omicron variant of COVID-19 infection in Taiwan. Adult patients who developed AKD after COVID-19 vaccination were included. We utilized the Naranjo score as a causality assessment tool for adverse vaccination reactions and charts review by peer nephrologists to exclude other causes. The etiologies, characteristics, and outcomes of AKD were examined.ResultsTwenty-seven patients (aged 23 to 80 years) with AKD were identified from 1,897 vaccines (estimated rate of 13.6 per 1000 patient-years within the renal registry). A majority (77.8%) of vaccine received messenger RNA-based regimens. Their median (IQR) Naranjo score was 8 (6-9) points, while 14 of them (51.9%) had a definite probability (Naranjo score ≥ 9). The etiologies of AKD included glomerular disease (n = 16) consisting of seven IgA nephropathy, four anti-neutrophil cytoplasmic antibodies-associated glomerulonephritis (AAN), three membranous glomerulonephritis, two minimal change diseases, and chronic kidney disease (CKD) with acute deterioration (n = 11). Extra-renal manifestations were found in four patients. Over a median (IQR) follow-up period of 42 (36.5–49.5) weeks, six patients progressed to end-stage kidney disease (ESKD).ConclusionBesides glomerulonephritis (GN), the occurrence of AKD following COVID-19 vaccination may be more concerning in high-risk CKD patients receiving multiple doses. Patients with the development of de novo AAN, concurrent extra-renal manifestations, or pre-existing moderate to severe CKD may exhibit poorer kidney prognosis

Clinical characteristics and risk behavior as a function of HIV status among heroin users enrolled in methadone treatment in northern Taiwan

<p>Abstract</p> <p>Background</p> <p>Methadone treatment was introduced in Taiwan in 2006 as a harm-reduction program in response to the human immunodeficiency virus (HIV), which is endemic among Taiwanese heroin users. The present study was aimed at examining the clinical and behavioral characteristics of methadone patients in northern Taiwan according to their HIV status.</p> <p>Methods</p> <p>The study was conducted at four methadone clinics. Participants were patients who had undergone methadone treatment at the clinics and who voluntarily signed a consent form. Between August and November 2008, each participant completed a face-to-face interview that included questions on demographics, risk behavior, quality of life, and psychiatric symptoms. Data on HIV and hepatitis C virus (HCV) infections, methadone dosage, and morphine in the urine were retrieved from patient files on the clinical premises, with permission of the participants.</p> <p>Results</p> <p>Of 576 participants, 71 were HIV positive, and 514 had hepatitis C. There were significant differences between the HIV-positive and HIV-negative groups on source of treatment payment, HCV infection, urine test results, methadone dosage, and treatment duration. The results indicate that HIV-negative heroin users were more likely to have sexual intercourse and not use condoms during the 6 months prior to the study. A substantial percent of the sample reported anxiety (21.0%), depression (27.2%), memory loss (32.7%), attempted suicide (32.7%), and administration of psychiatric medications (16.1%). There were no significant differences between the HIV-positive and HIV-negative patients on psychiatric symptoms or quality of life.</p> <p>Conclusions</p> <p>HIV-positive IDUs were comorbid with HCV, indicating the need to refer both HIV- and HCV-infected individuals for treatment in methadone clinics. Currently, there is a gap between psychiatric/psychosocial services and patient symptoms, and more integrated medical services should be provided to heroin-using populations.</p

Fosmid library end sequencing reveals a rarely known genome structure of marine shrimp Penaeus monodon

<p>Abstract</p> <p>Background</p> <p>The black tiger shrimp (<it>Penaeus monodon</it>) is one of the most important aquaculture species in the world, representing the crustacean lineage which possesses the greatest species diversity among marine invertebrates. Yet, we barely know anything about their genomic structure. To understand the organization and evolution of the <it>P. monodon </it>genome, a fosmid library consisting of 288,000 colonies and was constructed, equivalent to 5.3-fold coverage of the 2.17 Gb genome. Approximately 11.1 Mb of fosmid end sequences (FESs) from 20,926 non-redundant reads representing 0.45% of the <it>P. monodon </it>genome were obtained for repetitive and protein-coding sequence analyses.</p> <p>Results</p> <p>We found that microsatellite sequences were highly abundant in the <it>P. monodon </it>genome, comprising 8.3% of the total length. The density and the average length of microsatellites were evidently higher in comparison to those of other taxa. AT-rich microsatellite motifs, especially poly (AT) and poly (AAT), were the most abundant. High abundance of microsatellite sequences were also found in the transcribed regions. Furthermore, <it>via </it>self-BlastN analysis we identified 103 novel repetitive element families which were categorized into four groups, <it>i.e</it>., 33 WSSV-like repeats, 14 retrotransposons, 5 gene-like repeats, and 51 unannotated repeats. Overall, various types of repeats comprise 51.18% of the <it>P. monodon </it>genome in length. Approximately 7.4% of the FESs contained protein-coding sequences, and the Inhibitor of Apoptosis Protein (IAP) gene and the Innexin 3 gene homologues appear to be present in high abundance in the <it>P. monodon </it>genome.</p> <p>Conclusions</p> <p>The redundancy of various repeat types in the <it>P. monodon </it>genome illustrates its highly repetitive nature. In particular, long and dense microsatellite sequences as well as abundant WSSV-like sequences highlight the uniqueness of genome organization of penaeid shrimp from those of other taxa. These results provide substantial improvement to our current knowledge not only for shrimp but also for marine crustaceans of large genome size.</p

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

An efficient crawling algorithm for large-scale real-time social stream data collection based on popularity prediction

社群網路近年來改變了我們的溝通方式，累積巨量人類行為活動資料，吸引許多新興研究主題與社群網路行為分析結合。進行問題分析的過程中往往需要一個龐大的數據量，最近更朝向時域上分析，每隔一段時間必須對特定的研究標的做一次快照，熱門的訊息尤需要更密集的快照以洞察使用者行為隨著時間上變化。受限於這些社群網路有複雜的網絡，以及爬蟲對於數據存取量和頻率限制，對於多數機構的數據採集部門而言並不容易，且於資料取得之效能上無法進行有效優化。為了取得即時且足夠的資料，必須高頻率對社群網路存取，不僅浪費網路資源，亦增加社群網路的負荷。此外，目前社群網路隱私政策不允許不同單位共享數據，Facebook甚至透過加密的ID來保護使用者使用者資料。這些限制增加單一研究機構與其他機構共享數據，無法利用現有的爬行調度算法與其他機構分配資料收集方式。在本文中，我們提出了一種新爬行排序演算法，考慮用戶過去的行為，隨著收集的資料越多，越能預測該收集標的是否熱門以及有更多文章發布。所設計的演算法可以解決大型立式爬行資源分配與動態網頁無法通過一般的履帶採用的問題。在本研究中，我們運用單位資源內收集的訊息熱度來評估爬行性能。實驗結果呈現我們的演算法在收集社群網路99.5%熱門的訊息能最高節省40％爬蟲網路呼叫次數。Social media has greatly changed the way we communicate and huge amount of social behavior data is thus recorded and accumulated simultaneously. The data is now widely applied to many emerging research issues in combination with social behavior analysis. More recently, time domain analysis is especially popular on conducting behavior change investigation, in which people take snapshots on a particular subject of network on regular intervals, and hot messages (posts) are in urgent need of snapshot so as to precisely learn about user’s behavior as time moves. Scraping social networking sites such as Twitter, Facebook, etc. is not an easy task for data acquisition departments of most institutions since these sites often have complex structures and also restrict the amount and frequency of the data that they let out to common crawlers. To get more snapshots, groups often consume more computation power and network resources; even increase the load of OSN (Online Social Network) sites. In addition, the current privacy control policies do not allow different groups to share data with one another. These become challenges for an individual research group to collect sufficient data by using existing crawling scheduling algorithms or collaborating with other partners. In this paper, we propose “Novel Crawling Ordering Algorithm”, which allows our crawlers to focus on popular content by collecting and analyzing user behaviors. The designed crawler can also solve the problems of large-scale vertical crawling and dynamic web page problems. The performance of our crawling ordering algorithm” is evaluated by some designed metrics. And the experimental results tell us that this algorithm can save up to 40% of requests by crawling top 99.5 % popular social stream

Copper-mediated Trimethylsilyl Azide In Amination Of Bromoflavonoids To Synthesize Unique Aminoflavonoids

Aminoflavonoids are unique antioxidants comparing to other abundant flavonoids in nature. Their syntheses and biological activities were scarcely reported. An effectively copper-mediated amination of the corresponding bromoflavonoids to synthesize a series of new aminoflavonoids is described. © 2014 Elsevier Ltd. All rights reserved

Hole-closing model reveals exponents for nonlinear degenerate diffusivity functions in cell biology

Continuum mathematical models for collective cell motion normally involve reaction–diffusion equations, such as the Fisher–KPP equation, with a linear diffusion term to describe cell motility and a logistic term to describe cell proliferation. While the Fisher–KPP equation and its generalisations are commonplace, a significant drawback for this family of models is that they are not able to capture the moving fronts that arise in cell invasion applications such as wound healing and tumour growth. An alternative, less common, approach is to include nonlinear degenerate diffusion in the models, such as in the Porous-Fisher equation, since solutions to the corresponding equations have compact support and therefore explicitly allow for moving fronts. We consider here a hole-closing problem for the Porous-Fisher equation whereby there is initially a simply connected region (the hole) with a nonzero population outside of the hole and a zero population inside. We outline how self-similar solutions (of the second kind) describe both circular and non-circular fronts in the hole-closing limit. Further, we present new experimental and theoretical evidence to support the use of nonlinear degenerate diffusion in models for collective cell motion. Our methodology involves setting up a two-dimensional wound healing assay that has the geometry of a hole-closing problem, with cells initially seeded outside of a hole that closes as cells migrate and proliferate. For a particular class of fibroblast cells, the aspect ratio of an initially rectangular wound increases in time, so the wound becomes longer and thinner as it closes; our theoretical analysis shows that this behaviour is consistent with nonlinear degenerate diffusion but is not able to be captured with commonly used linear diffusion. This work is important because it provides a clear test for degenerate diffusion over linear diffusion in cell lines, whereas standard one-dimensional experiments are unfortunately not capable of distinguishing between the two approaches

Increased risk of benign prostate hyperplasia in sleep apnea patients: a nationwide population-based study.

BACKGROUND: Sleep apnea (SA) is a common sleep disorder characterized by chronic intermittent hypoxia (IH). Chronic IH induces systemic inflammatory processes, which can cause tissue damage and contribute to prostatic enlargement. The purpose of this study was to evaluate the association between benign prostate hyperplasia (BPH) and SA in a Taiwanese population. METHODS: The study population was identified from Taiwan's National Health Insurance Research Database (NHIRD) and contained 202 SA patients and 1010 control patients. The study cohort consisted of men aged ≥ 30 years who were newly diagnosed with SA between January 1997 and December 2005. Each patient was monitored for 5 years from the index date for the development of BPH. A Cox regression analysis was used to calculate the hazard ratios (HRs) for BPH in the SA and control patients. RESULTS: During the 5-year follow-up, 18 SA patients (8.9%) and 32 non-SA control patients (3.2%) developed BPH. The adjusted HR for BPH was 2.35-fold higher in the patients with SA than in the control patients (95% confidence interval (CI) 1.28-4.29, P<.01). We further divided the SA patients into 4 age groups. After adjusting for potential confounding factors, the highest adjusted HR for BPH in the SA patients compared with the control patients was 5.59 (95% CI = 2.19-14.31, P<.001) in the patients aged between 51 and 65 years. CONCLUSION: Our study results indicate that patients with SA are associated with increased longitudinal risk of BPH development, and that the effects of SA on BPH development are age-dependent

Recognizing the Differentiation Degree of Human Induced Pluripotent Stem Cell-Derived Retinal Pigment Epithelium Cells Using Machine Learning and Deep Learning-Based Approaches

Induced pluripotent stem cells (iPSCs) can be differentiated into mesenchymal stem cells (iPSC-MSCs), retinal ganglion cells (iPSC-RGCs), and retinal pigmental epithelium cells (iPSC-RPEs) to meet the demand of regeneration medicine. Since the production of iPSCs and iPSC-derived cell lineages generally requires massive and time-consuming laboratory work, artificial intelligence (AI)-assisted approach that can facilitate the cell classification and recognize the cell differentiation degree is of critical demand. In this study, we propose the multi-slice tensor model, a modified convolutional neural network (CNN) designed to classify iPSC-derived cells and evaluate the differentiation efficiency of iPSC-RPEs. We removed the fully connected layers and projected the features using principle component analysis (PCA), and subsequently classified iPSC-RPEs according to various differentiation degree. With the assistance of the support vector machine (SVM), this model further showed capabilities to classify iPSCs, iPSC-MSCs, iPSC-RPEs, and iPSC-RGCs with an accuracy of 97.8%. In addition, the proposed model accurately recognized the differentiation of iPSC-RPEs and showed the potential to identify the candidate cells with ideal features and simultaneously exclude cells with immature/abnormal phenotypes. This rapid screening/classification system may facilitate the translation of iPSC-based technologies into clinical uses, such as cell transplantation therapy