A Quantitative, Non-Destructive Methodology for Habitat Characterisation and Benthic Monitoring at Offshore Renewable Energy Developments

Following governments' policies to tackle global climate change, the development of offshore renewable energy sites is likely to increase substantially over coming years. All such developments interact with the seabed to some degree and so a key need exists for suitable methodology to monitor the impacts of large-scale Marine Renewable Energy Installations (MREIs). Many of these will be situated on mixed or rocky substrata, where conventional methods to characterise the habitat are unsuitable. Traditional destructive sampling is also inappropriate in conservation terms, particularly as safety zones around (MREIs) could function as Marine Protected Areas, with positive benefits for biodiversity. Here we describe a technique developed to effectively monitor the impact of MREIs and report the results of its field testing, enabling large areas to be surveyed accurately and cost-effectively. The methodology is based on a high-definition video camera, plus LED lights and laser scale markers, mounted on a “flying array” that maintains itself above the seabed grounded by a length of chain, thus causing minimal damage. Samples are taken by slow-speed tows of the gear behind a boat (200 m transects). The HD video and randomly selected frame grabs are analysed to quantify species distribution. The equipment was tested over two years in Lyme Bay, UK (25 m depth), then subsequently successfully deployed in demanding conditions at the deep (>50 m) high-energy Wave Hub site off Cornwall, UK, and a potential tidal stream energy site in Guernsey, Channel Islands (1.5 ms−1 current), the first time remote samples from such a habitat have been achieved. The next stage in the monitoring development process is described, involving the use of Remote Operated Vehicles to survey the seabed post-deployment of MREI devices. The complete methodology provides the first quantitative, relatively non-destructive method for monitoring mixed-substrate benthic communities beneath MPAs and MREIs pre- and post-device deployment

Estimating internationally imported cases during the early COVID-19 pandemic

Early in the COVID-19 pandemic, predictions of international outbreaks were largely based on imported cases from Wuhan, China, potentially missing imports from other cities. We provide a method, combining daily COVID-19 prevalence and flight passenger volume, to estimate importations from 18 Chinese cities to 43 international destinations, including 26 in Africa. Global case importations from China in early January came primarily from Wuhan, but the inferred source shifted to other cities in mid-February, especially for importations to African destinations. We estimate that 10.4 (6.2 - 27.1) COVID-19 cases were imported to these African destinations, which exhibited marked variation in their magnitude and main sources of importation. We estimate that 90% of imported cases arrived between 17 January and 7 February, prior to the first case detections. Our results highlight the dynamic role of source locations, which can help focus surveillance and response efforts

MS4a4B, a CD20 Homologue in T Cells, Inhibits T Cell Propagation by Modulation of Cell Cycle

MS4a4B, a CD20 homologue in T cells, is a novel member of the MS4A gene family in mice. The MS4A family includes CD20, FcεRIβ, HTm4 and at least 26 novel members that are characterized by their structural features: with four membrane-spanning domains, two extracellular domains and two cytoplasmic regions. CD20, FcεRIβ and HTm4 have been found to function in B cells, mast cells and hematopoietic cells respectively. However, little is known about the function of MS4a4B in T cell regulation. We demonstrate here that MS4a4B negatively regulates mouse T cell proliferation. MS4a4B is highly expressed in primary T cells, natural killer cells (NK) and some T cell lines. But its expression in all malignant T cells, including thymoma and T hybridoma tested, was silenced. Interestingly, its expression was regulated during T cell activation. Viral vector-driven overexpression of MS4a4B in primary T cells and EL4 thymoma cells reduced cell proliferation. In contrast, knockdown of MS4a4B accelerated T cell proliferation. Cell cycle analysis showed that MS4a4B regulated T cell proliferation by inhibiting entry of the cells into S-G2/M phase. MS4a4B-mediated inhibition of cell cycle was correlated with upregulation of Cdk inhibitory proteins and decreased levels of Cdk2 activity, subsequently leading to inhibition of cell cycle progression. Our data indicate that MS4a4B negatively regulates T cell proliferation. MS4a4B, therefore, may serve as a modulator in the negative-feedback regulatory loop of activated T cell

Segmentation of Fluorescence Microscopy Cell Images Using Unsupervised Mining

The accurate measurement of cell and nuclei contours are critical for the sensitive and specific detection of changes in normal cells in several medical informatics disciplines. Within microscopy, this task is facilitated using fluorescence cell stains, and segmentation is often the first step in such approaches. Due to the complex nature of cell issues and problems inherent to microscopy, unsupervised mining approaches of clustering can be incorporated in the segmentation of cells. In this study, we have developed and evaluated the performance of multiple unsupervised data mining techniques in cell image segmentation. We adapt four distinctive, yet complementary, methods for unsupervised learning, including those based on k-means clustering, EM, Otsu’s threshold, and GMAC. Validation measures are defined, and the performance of the techniques is evaluated both quantitatively and qualitatively using synthetic and recently published real data. Experimental results demonstrate that k-means, Otsu’s threshold, and GMAC perform similarly, and have more precise segmentation results than EM. We report that EM has higher recall values and lower precision results from under-segmentation due to its Gaussian model assumption. We also demonstrate that these methods need spatial information to segment complex real cell images with a high degree of efficacy, as expected in many medical informatics applications

Plasminogen Activator Inhibitor-1 4G/5G Gene Polymorphism and Coronary Artery Disease in the Chinese Han Population: A Meta-Analysis

Background: The polymorphism of plasminogen activator inhibitor-1 (PAI-1) 4G/5G gene has been indicated to be correlated with coronary artery disease (CAD) susceptibility, but study results are still debatable. Objective and Methods: The present meta-analysis was performed to investigate the association between PAI-1 4G/5G gene polymorphism and CAD in the Chinese Han population. A total of 879 CAD patients and 628 controls from eight separate studies were involved. The pooled odds ratio (OR) for the distribution of the 4G allele frequency of PAI-1 4G/5G gene and its corresponding 95 % confidence interval (CI) was assessed by the random effect model. Results: The distribution of the 4 G allele frequency was 0.61 for the CAD group and 0.51 for the control group. The association between PAI-1 4G/5G gene polymorphism and CAD in the Chinese Han population was significant under an allelic genetic model (OR = 1.70, 95 % CI = 1.18 to 2.44, P = 0.004). The heterogeneity test was also significant (P,0.0001). Meta-regression was performed to explore the heterogeneity source. Among the confounding factors, the heterogeneity could be explained by the publication year (P = 0.017), study region (P = 0.014), control group sample size (P = 0.011), total sample size (P = 0.011), and ratio of the case to the control group sample size (RR) (P = 0.019). In a stratified analysis by the total sample size, significantly increased risk was only detected in subgroup 2 under an allelic genetic model (OR = 1.93, 95% CI = 1.09 to 3.35, P = 0.02)

Expression of miRNA-106b in conventional renal cell carcinoma is a potential marker for prediction of early metastasis after nephrectomy

<p>Abstract</p> <p>Background</p> <p>MicroRNAs are endogenously expressed regulatory noncoding RNAs. Previous studies have shown altered expression levels of several microRNAs in renal cell carcinoma.</p> <p>Methods</p> <p>We examined the expression levels of selected microRNAs in 38 samples of conventional renal cell carcinoma (RCC) and 10 samples of non-tumoral renal parenchyma using TaqMan real-time PCR method.</p> <p>Results</p> <p>The expression levels of miRNA-155 (p < 0.0001), miRNA-210 (p < 0.0001), miRNA-106a (p < 0.0001) and miRNA-106b (p < 0.0001) were significantly over-expressed in tumor tissue, whereas the expression of miRNA-141 (p < 0.0001) and miRNA-200c (p < 0.0001) were significantly decreased in RCC samples. There were no significant differences between expression levels of miRNA-182 and miRNA-200b in tumor samples and renal parenchyma. Our data suggest that expression levels of miRNA-106b are significantly lower in tumors of patients who developed metastasis (p = 0.030) and miR-106b is a potential predictive marker of early metastasis after nephrectomy in RCC patients (long-rank p = 0.032).</p> <p>Conclusions</p> <p>We have confirmed previous observations obtained by miRNA microarray analysis using standardized real-time PCR method. For the first time, we have identified a prognostic significance of miRNA-106b, which, after validation on a larger group of patients, maybe useful as a promising biomarker in patients with RCC.</p

Temporal trend and climate factors of hemorrhagic fever with renal syndrome epidemic in Shenyang City, China

<p>Abstract</p> <p>Background</p> <p>Hemorrhagic fever with renal syndrome (HFRS) is an important infectious disease caused by different species of hantaviruses. As a rodent-borne disease with a seasonal distribution, external environmental factors including climate factors may play a significant role in its transmission. The city of Shenyang is one of the most seriously endemic areas for HFRS. Here, we characterized the dynamic temporal trend of HFRS, and identified climate-related risk factors and their roles in HFRS transmission in Shenyang, China.</p> <p>Methods</p> <p>The annual and monthly cumulative numbers of HFRS cases from 2004 to 2009 were calculated and plotted to show the annual and seasonal fluctuation in Shenyang. Cross-correlation and autocorrelation analyses were performed to detect the lagged effect of climate factors on HFRS transmission and the autocorrelation of monthly HFRS cases. Principal component analysis was constructed by using climate data from 2004 to 2009 to extract principal components of climate factors to reduce co-linearity. The extracted principal components and autocorrelation terms of monthly HFRS cases were added into a multiple regression model called principal components regression model (PCR) to quantify the relationship between climate factors, autocorrelation terms and transmission of HFRS. The PCR model was compared to a general multiple regression model conducted only with climate factors as independent variables.</p> <p>Results</p> <p>A distinctly declining temporal trend of annual HFRS incidence was identified. HFRS cases were reported every month, and the two peak periods occurred in spring (March to May) and winter (November to January), during which, nearly 75% of the HFRS cases were reported. Three principal components were extracted with a cumulative contribution rate of 86.06%. Component 1 represented MinRH₀, MT₁, RH₁, and MWV₁; component 2 represented RH₂, MaxT₃, and MAP₃; and component 3 represented MaxT₂, MAP₂, and MWV₂. The PCR model was composed of three principal components and two autocorrelation terms. The association between HFRS epidemics and climate factors was better explained in the PCR model (<it>F </it>= 446.452, <it>P </it>< 0.001, adjusted <it>R</it>²= 0.75) than in the general multiple regression model (<it>F </it>= 223.670, <it>P </it>< 0.000, adjusted <it>R</it>²= 0.51).</p> <p>Conclusion</p> <p>The temporal distribution of HFRS in Shenyang varied in different years with a distinctly declining trend. The monthly trends of HFRS were significantly associated with local temperature, relative humidity, precipitation, air pressure, and wind velocity of the different previous months. The model conducted in this study will make HFRS surveillance simpler and the control of HFRS more targeted in Shenyang.</p

Chromosomal-level assembly of the Asian Seabass genome using long sequence reads and multi-layered scaffolding

We report here the ~670 Mb genome assembly of the Asian seabass (Lates calcarifer), a tropical marine teleost. We used long-read sequencing augmented by transcriptomics, optical and genetic mapping along with shared synteny from closely related fish species to derive a chromosome-level assembly with a contig N50 size over 1 Mb and scaffold N50 size over 25 Mb that span ~90% of the genome. The population structure of L. calcarifer species complex was analyzed by re-sequencing 61 individuals representing various regions across the species' native range. SNP analyses identified high levels of genetic diversity and confirmed earlier indications of a population stratification comprising three clades with signs of admixture apparent in the South-East Asian population. The quality of the Asian seabass genome assembly far exceeds that of any other fish species, and will serve as a new standard for fish genomics

Specification and guideline for technical aspects and scanning parameter settings of neonatal lung ultrasound examination

Lung ultrasound (LUS) is now widely used in the diagnosis and monitor of neonatal lung diseases.Nevertheless, in the published literatures,the LUS images may display a significant variation in technical execution,while scanning parameters may influence diagnostic accuracy.The inter- and intra-observer reliabilities of ultrasound exam have been extensively studied in general and in LUS.As expected,the reliability declines in the hands of novices when they perform the point-of-care ultrasound (POC US).Consequently,having appropriate guidelines regarding to technical aspects of neonatal LUS exam is very important especially because diagnosis is mainly based on interpretation of artifacts produced by the pleural line and the lungs.The present work aimed to create an instrument operation specification and parameter setting guidelines for neonatal LUS.Technical aspects and scanning parameter settings that allow for standardization in obtaining LUS images include (1)select a high-end equipment with high-frequency linear array transducer (12-14 MHz).(2)Choose preset suitable for lung examination or small organs.(3)Keep the probe perpendicular to the ribs or parallel to the intercostal space.(4)Set the scanning depth at 4-5 cm.(5)Set 1-2 focal zones and adjust them close to the pleural line.(6)Use fundamental frequency with speckle reduction 2-3 or similar techniques.(7)Turn off spatial compounding imaging.(8)Adjust the time-gain compensation to get uniform image from the near-to far-field