Spatial Distribution of Petroleum Hydrocarbons in Sediment Cores from Blind Pass, St. Pete Beach, Florida

One hundred and one sediment cores were collected to characterize the spatial distribution of petroleum hydrocarbons within and just outside Blind Pass, St. Pete Beach, Florida. Twenty-five percent of the cores exhibited levels of petroleum hydrocarbons above detection limits of the gas chromatograph/flame ionization detector (GC/FID) (0.01 mg/Kg), but at generally low concentrations. Petroleum hydrocarbon speciation studies of these samples (gas chromatography/mass spectroscopy [GC/MS]) indicate above-detection level (1 μg/Kg) petroleum hydrocarbons are similar to the non-volatile petroleum hydrocarbons found in a Bouchard 155 reference sample collected after the 1993 oil spill in the area, but are in a much degraded and weathered state. Individual petroleum hydrocarbons were, in all but one case, below the threshold effective level (TEL) described in the literature (MacDonald, 1994). The petroleum hydrocarbons were primarily found at 100-300 cm depth in Blind Pass cores. Above-detection level petroleum hydrocarbons were generally found in samples from cores in the center of the channel, near the edges of the shoal, and just outside of Blind Pass. A second mixture of hydrocarbons, primarily phthalates, ketones, and ether, was found at relatively shallow core depths (0-99 cm) in the Mid- and North End Channel cores. These suggest a separate source of contamination, possibly storm water runoff. The fuel fluorescence detector (FFD) probe was investigated for its ability to detect petroleum hydrocarbons in marine sediments. When analyzed with the FFD, all sediments from the cores produced peaks of fluorescence, but none above the background levels of Blind Pass native sediments. All but two samples analyzed by GC/FID were below the detection limits (100 ppm) of the FFD. These samples were found in dark-colored sediments. The combination of the detection limits of the instrument, sediment color, and the degraded nature of the heavier weight petroleum hydrocarbons may have resulted in fluorescence outputs below background levels. These studies demonstrate that the distribution of petroleum hydrocarbons within Blind Pass sediments is generally low and patchy. However, 25% of the cores exhibited levels above detection using GC/FID/MS. These cores could be subjected to individual speciation studies which indicate generally below TEL levels and an association of some, but not all, with the 1993 oil spill in Blind Pass. Appendix A provides photographs and tables for sediment subsamples which exhibited total petroleum hydrocarbon concentrations above detection limits, while Appendix B presents the results from fuel fluorescence detector probe analyses. A discussion of the results of the study in relation to sediment quality guidelines and soil cleanup target level guidance documents is included as Appendix C. Some preliminary results using the above techniques on core samples from the nearby John’s Pass are presented in Appendix D

Mental Health Status, Risk and Protective Factors for Healthcare Staff Prior to the First Major COVID-19 Outbreak in Western Australia

Objectives: Western Australia’s unique public health response delayed the first wave of community COVID-19 transmission for 2 years. We aimed to determine the status of post-traumatic stress (PTSS), depressive, and anxiety symptoms among healthcare staff in major tertiary hospitals, together with associated risk and protective factors prior to the first substantial outbreak of COVID-19.Methods: A cross-sectional study was conducted with 431 healthcare staff immediately prior to the Western Australian border re-opening in 2022. Staff were recruited via notices in email newsletters, at four tertiary hospitals and a public mental health clinic in metropolitan Perth. Validated and original questionnaires were administered via Qualtrics.Results: Moderate levels of PTSS (22.3%), depression (21.9%), and anxiety (25.9%) were reported. Pathway analyses indicated that sleep difficulties, workplace stressors, and infectious disease training were associated with higher PTSS, depression and anxiety symptoms, and younger age was associated with higher levels of depression and anxiety. Nursing roles were associated with higher PTSS. Social support and workplace support were associated with lower levels of depression and anxiety but were not associated with PTSS.Conclusion: The findings illustrate high levels of resilience, but indicate a need for structural supports within the health system to foster staff mental health prior to the onset of emergencies

Comparative genomics of the type VI secretion systems of Pantoea and Erwinia species reveals the presence of putative effector islands that may be translocated by the VgrG and Hcp proteins

<p>Abstract</p> <p>Background</p> <p>The Type VI secretion apparatus is assembled by a conserved set of proteins encoded within a distinct locus. The putative effector proteins Hcp and VgrG are also encoded within these loci. We have identified numerous distinct Type VI secretion system (T6SS) loci in the genomes of several ecologically diverse <it>Pantoea </it>and <it>Erwinia </it>species and detected the presence of putative effector islands associated with the <it>hcp </it>and <it>vgrG </it>genes.</p> <p>Results</p> <p>Between two and four T6SS loci occur among the <it>Pantoea </it>and <it>Erwinia </it>species. While two of the loci (T6SS-1 and T6SS-2) are well conserved among the various strains, the third (T6SS-3) locus is not universally distributed. Additional orthologous loci are present in <it>Pantoea </it>sp. aB-valens and <it>Erwinia billingiae </it>Eb661. Comparative analysis of the T6SS-1 and T6SS-3 loci showed non-conserved islands associated with the <it>vgrG </it>and <it>hcp</it>, and <it>vgrG </it>genes, respectively. These regions had a G+C content far lower than the conserved portions of the loci. Many of the proteins encoded within the <it>hcp </it>and <it>vgrG </it>islands carry conserved domains, which suggests they may serve as effector proteins for the T6SS. A number of the proteins also show homology to the C-terminal extensions of evolved VgrG proteins.</p> <p>Conclusions</p> <p>Extensive diversity was observed in the number and content of the T6SS loci among the <it>Pantoea </it>and <it>Erwinia </it>species. Genomic islands could be observed within some of T6SS loci, which are associated with the <it>hcp </it>and <it>vgrG </it>proteins and carry putative effector domain proteins. We propose new hypotheses concerning a role for these islands in the acquisition of T6SS effectors and the development of novel evolved VgrG and Hcp proteins.</p

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

Non-structural carbohydrates in woody plants compared among laboratories

Non-structural carbohydrates (NSC) in plant tissue are frequently quantified to make inferences about plant responses to environmental conditions. Laboratories publishing estimates of NSC of woody plants use many different methods to evaluate NSC. We asked whether NSC estimates in the recent literature could be quantitatively compared among studies. We also asked whether any differences among laboratories were related to the extraction and quantification methods used to determine starch and sugar concentrations. These questions were addressed by sending sub-samples collected from five woody plant tissues, which varied in NSC content and chemical composition, to 29 laboratories. Each laboratory analyzed the samples with their laboratory-specific protocols, based on recent publications, to determine concentrations of soluble sugars, starch and their sum, total NSC. Laboratory estimates differed substantially for all samples. For example, estimates for Eucalyptus globulus leaves (EGL) varied from 23 to 116 (mean = 56) mg g⁻¹ for soluble sugars, 6–533 (mean = 94) mg g⁻¹ for starch and 53–649 (mean = 153) mg g⁻¹ for total NSC. Mixed model analysis of variance showed that much of the variability among laboratories was unrelated to the categories we used for extraction and quantification methods (method category R² = 0.05–0.12 for soluble sugars, 0.10–0.33 for starch and 0.01–0.09 for total NSC). For EGL, the difference between the highest and lowest least squares means for categories in the mixed model analysis was 33 mg g⁻¹ for total NSC, compared with the range of laboratory estimates of 596 mg g⁻¹. Laboratories were reasonably consistent in their ranks of estimates among tissues for starch (r = 0.41–0.91), but less so for total NSC (r = 0.45–0.84) and soluble sugars (r = 0.11–0.83). Our results show that NSC estimates for woody plant tissues cannot be compared among laboratories. The relative changes in NSC between treatments measured within a laboratory may be comparable within and between laboratories, especially for starch. To obtain comparable NSC estimates, we suggest that users can either adopt the reference method given in this publication, or report estimates for a portion of samples using the reference method, and report estimates for a standard reference material. Researchers interested in NSC estimates should work to identify and adopt standard methods.This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by Oxford University Press. The published article can be found at: http://treephys.oxfordjournals.org/Keywords: soluble sugars, starch, particle size, reference method, standardization, non-structural carbohydrate chemical analysis, extraction and quantification consistenc

Metastatic susceptibility locus, an 8p hot-spot for tumour progression disrupted in colorectal liver metastases: 13 candidate genes examined at the DNA, mRNA and protein level-3

Op centromeric end bottom. LOH (open circle), retention (closed circle) and Non-informative (line) are indicated. The boxed region indicates markers selected for analysis of larger series of LM samples results shown in Figure 1b. . Selected markers D8S1786-NEFL on 8p21 in LM for 21 patients. Markers are ordered and oriented with telomeric end top centromeric end bottom. LOH (open circle), retention (closed circle) and Non-informative (line) are indicated. The boxed region highlights the minimal region of loss identified in patient #22. . Loss of microsatellite marker D8S1181 (arrow) defining the minimal region of loss in patient #22. Retention of markers D8S1734, NEFL and D8S1048 and loss of D8S1181 in tumour (LM liver metastases) compared to normal (B, blood) are shown.. Metastasis Specific Loss at D8S1181. Gel images illustrating loss (arrow) of D8S1811 in liver metastases (LM) but not matched normal (B, blood) or colon tumour (CT) in 2 patients.<p><b>Copyright information:</b></p><p>Taken from "Metastatic susceptibility locus, an 8p hot-spot for tumour progression disrupted in colorectal liver metastases: 13 candidate genes examined at the DNA, mRNA and protein level"</p><p>http://www.biomedcentral.com/1471-2407/8/187</p><p>BMC Cancer 2008;8():187-187.</p><p>Published online 1 Jul 2008</p><p>PMCID:PMC2488356.</p><p></p

Metastatic susceptibility locus, an 8p hot-spot for tumour progression disrupted in colorectal liver metastases: 13 candidate genes examined at the DNA, mRNA and protein level-0

Op centromeric end bottom. LOH (open circle), retention (closed circle) and Non-informative (line) are indicated. The boxed region indicates markers selected for analysis of larger series of LM samples results shown in Figure 1b. . Selected markers D8S1786-NEFL on 8p21 in LM for 21 patients. Markers are ordered and oriented with telomeric end top centromeric end bottom. LOH (open circle), retention (closed circle) and Non-informative (line) are indicated. The boxed region highlights the minimal region of loss identified in patient #22. . Loss of microsatellite marker D8S1181 (arrow) defining the minimal region of loss in patient #22. Retention of markers D8S1734, NEFL and D8S1048 and loss of D8S1181 in tumour (LM liver metastases) compared to normal (B, blood) are shown.. Metastasis Specific Loss at D8S1181. Gel images illustrating loss (arrow) of D8S1811 in liver metastases (LM) but not matched normal (B, blood) or colon tumour (CT) in 2 patients.<p><b>Copyright information:</b></p><p>Taken from "Metastatic susceptibility locus, an 8p hot-spot for tumour progression disrupted in colorectal liver metastases: 13 candidate genes examined at the DNA, mRNA and protein level"</p><p>http://www.biomedcentral.com/1471-2407/8/187</p><p>BMC Cancer 2008;8():187-187.</p><p>Published online 1 Jul 2008</p><p>PMCID:PMC2488356.</p><p></p

Metastatic susceptibility locus, an 8p hot-spot for tumour progression disrupted in colorectal liver metastases: 13 candidate genes examined at the DNA, mRNA and protein level-2

Terest compared to the 18s control (dCt) and relative expression calculated using the comparative Cmethod with fold change (2). Fold change is shown on a logarithmic scale. . Fold change gene expression of colorectal tumours (black) and liver metastases (white) relative to the matched colon normal. Fold change is presented on a logarithmic scale and was calculated as above.<p><b>Copyright information:</b></p><p>Taken from "Metastatic susceptibility locus, an 8p hot-spot for tumour progression disrupted in colorectal liver metastases: 13 candidate genes examined at the DNA, mRNA and protein level"</p><p>http://www.biomedcentral.com/1471-2407/8/187</p><p>BMC Cancer 2008;8():187-187.</p><p>Published online 1 Jul 2008</p><p>PMCID:PMC2488356.</p><p></p