Detecting Coastal Marsh Change from Aerial Imagery using Spectral and Textural Methods: Pascagoula River Estuary, Mississippi, 1955-2014

As sea level rise accelerates, coastal marsh ecosystems are increasingly vulnerable. Vertical accretion rates must exceed or keep pace with rates of sea level rise to prevent transition to open water or inland migration of marsh vegetation. While some marsh systems along the northern Gulf of Mexico coast have remained stable, others, e.g., the marshes of the Louisiana Gulf Coast, have experienced high rates of conversion to open water. This study examined the historical extent of intertidal marsh at the mouth of the Pascagoula River in Jackson County, Mississippi to determine whether marsh extent changed during the period 1955-2014 and to ascertain rates of change. Marsh extent was mapped at 3 meters GSD using spectral and textural aerial image data for image dates of February 13, 1955 (black and white), February 12, 1996 (color-infrared), and October 5-16, 2014 (color-infrared). Waterways represented in the imagery were classified using a near-infrared band threshold for 1996 and 2014 and a CV-band threshold for 1955. Land cover was classified into three groups–marsh, woodland/shrubs, and unvegetated–using a Maximum Likelihood Classifier. Change detection analysis revealed a net marsh loss of 1314.4 ha (19.9%) between 1955 and 2014. Classified marsh extent decreased by 1068.3 ha (16.1%) between 1955 and 1996, and 246.1 ha (4.4%) between 1996 and 2014. Linear regression of marsh extent with year yielded a slope of -22.9 ha/year with a coefficient of determination of r2 = 0.98. The results indicate that marsh extent will continue to decrease in the Pascagoula River Estuary

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Using Aerial Imagery to Determine the Effects of Sea-Level Rise on Fluvial Marshes at the Mouth of the Pascagoula River (Mississippi, U.S.A.)

Coastal marshes provide valuable ecosystem services yet are increasingly vulnerable to sea level rise (SLR).To facilitate a better understanding of how fluvial marshes along the Gulf of Mexico coast are responding to regional SLR of around 3.7 mm per year, this study used aerial imagery to map land cover at the mouth of the Pascagoula River at 20-year intervals, beginning in 1955 and ending in 2014. High-resolution land cover maps were created for each image date based on a maximum likelihood classification scheme using spectral and textural image features. This marsh ecosystem, at the mouth of the largest free-flowing river by volume in the contiguous United States, should be more resilient to sea level rise than other Gulf Coast marshes, with little restriction to sediment supply and relatively low subsidence rates measured nearby. However, the results of this study show that marsh area declined by 1073 ha (17.5%) and rates of marsh conversion to open water increased over the studied time period. Although modeling studies indicate that coastal marshes worldwide may persist under accelerated SLR, these observations suggest that marsh extent in the sediment-rich Pascagoula River Estuary will continue to decline, signifying vulnerability among other marsh ecosystems along the northern Gulf of Mexico coast

Using Aerial Imagery to Determine the Effects of Sea-Level Rise On Fluvial Marshes at the Mouth of the Pascagoula River (Mississippi, USA)

Coastal marshes provide valuable ecosystem services yet are increasingly vulnerable to sea level rise (SLR). To facilitate a better understanding of how fluvial marshes along the Gulf of Mexico coast are responding to regional SLR of around 3.7 mm per year, this study used aerial imagery to map land cover at the mouth of the Pascagoula River at 20-year intervals, beginning in 1955 and ending in 2014. High-resolution land cover maps were created for each image date based on a maximum likelihood classification scheme using spectral and textural image features. This marsh ecosystem, at the mouth of the largest free-flowing river by volume in the contiguous United States, should be more resilient to sea level rise than other Gulf Coast marshes, with little restriction to sediment supply and relatively low subsidence rates measured nearby. However, the results of this study show that marsh area declined by 1073 ha (17.5%) and rates of marsh conversion to open water increased over the studied time period. Although modeling studies indicate that coastal marshes worldwide may persist under accelerated SLR, these observations suggest that marsh extent in the sediment-rich Pascagoula River Estuary will continue to decline, signifying vulnerability among other marsh ecosystems along the northern Gulf of Mexico coast

Whole-genome sequencing reveals host factors underlying critical COVID-19

Altres ajuts: Department of Health and Social Care (DHSC); Illumina; LifeArc; Medical Research Council (MRC); UKRI; Sepsis Research (the Fiona Elizabeth Agnew Trust); the Intensive Care Society, Wellcome Trust Senior Research Fellowship (223164/Z/21/Z); BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070, BBS/E/D/30002275); UKRI grants (MC_PC_20004, MC_PC_19025, MC_PC_1905, MRNO2995X/1); UK Research and Innovation (MC_PC_20029); the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z); the Edinburgh Clinical Academic Track (ECAT) programme; the National Institute for Health Research, the Wellcome Trust; the MRC; Cancer Research UK; the DHSC; NHS England; the Smilow family; the National Center for Advancing Translational Sciences of the National Institutes of Health (CTSA award number UL1TR001878); the Perelman School of Medicine at the University of Pennsylvania; National Institute on Aging (NIA U01AG009740); the National Institute on Aging (RC2 AG036495, RC4 AG039029); the Common Fund of the Office of the Director of the National Institutes of Health; NCI; NHGRI; NHLBI; NIDA; NIMH; NINDS.Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care or hospitalization after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes-including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)-in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press