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1,693 results for “Hypoxia”
Shipboard Conductivity–Temperature–Depth (CTD) and dissolved oxygen profile data collected during hypoxia surveys along six hydrographic sampling lines within Olympic Coast National Marine Sanctuary, 2004–2015
<p>This data set includes Conductivity-Temperature-Depth (CTD) and dissolved oxygen profile data that were collected along Washington State’s outer coast within Olympic Coast National Marine Sanctuary (OCNMS). Measurements were made along six cross-shelf hydrographic sampling lines during a series of hypoxia survey cruises from 2004 – 2015. The 398 CTD profiles were acquired using Sea-Bird Scientific 19 SeaCAT or 19plus SeaCAT CTD profilers with associated SBE-43 (Sea-Bird Electronics) or Beckman or YSI-type (Yellow Springs Instruments) dissolved oxygen sensors. The data were processed via Sea-Bird Scientific’s SBE Data Processing application using six of the modules in the following order: Data Conversion, Filter, Align CTD, Loop Edit, Derive, and Bin Average. These processing steps and associated methods are the same as those used to process CTD data collected during OCNMS mooring maintenance cruises (<a href="https://www.sciencedirect.com/science/article/pii/S2352340924001422">Risien et al., 2024</a>) and along the Newport Hydrographic Line (<a href="https://www.sciencedirect.com/science/article/pii/S2352340922001342">Risien et al., 2022</a>) located off the central Oregon coast.</p> <table> <tbody> <tr> <td><strong>Station Name </strong></td> <td><strong>Latitude</strong></td> <td><strong>Longitude</strong></td> <td><strong>Water Depth (m, MLLW)</strong></td> </tr> <tr> <td><strong>Cape Alava (CA)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>CA010</td> <td>48.1661oN</td> <td>124.7540oW</td> <td>10</td> </tr> <tr> <td>CA020</td> <td>48.1661oN</td> <td>124.7598oW</td> <td>20</td> </tr> <tr> <td>CA030</td> <td>48.1659oN</td> <td>124.7783oW</td> <td>30</td> </tr> <tr> <td>CA040</td> <td>48.1659oN</td> <td>124.7852oW</td> <td>40</td> </tr> <tr> <td>CA045</td> <td>48.1659oN</td> <td>124.8335oW</td> <td>45</td> </tr> <tr> <td>CA050</td> <td>48.1658oN</td> <td>124.8578oW</td> <td>50</td> </tr> <tr> <td>CA060</td> <td>48.1659oN</td> <td>124.8843oW</td> <td>60</td> </tr> <tr> <td>CA070</td> <td>48.1655oN</td> <td>124.9011oW</td> <td>70</td> </tr> <tr> <td>CA080</td> <td>48.1657oN</td> <td>124.9141oW</td> <td>80</td> </tr> <tr> <td>CA090</td> <td>48.1659oN</td> <td>124.9247oW</td> <td>90</td> </tr> <tr> <td>CA100</td> <td>48.1658oN</td> <td>124.9319oW</td> <td>100</td> </tr> <tr> <td><strong>Teahwhit Head (TH)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>TH030</td> <td>47.8759oN</td> <td>124.6481oW</td> <td>30</td> </tr> <tr> <td>TH035</td> <td>47.8761oN</td> <td>124.7024oW</td> <td>35</td> </tr> <tr> <td>TH040</td> <td>47.8760oN</td> <td>124.7281oW</td> <td>40</td> </tr> <tr> <td>TH050</td> <td>47.8761oN</td> <td>124.7567oW</td> <td>50</td> </tr> <tr> <td>TH060</td> <td>47.8765oN</td> <td>124.7822oW</td> <td>60</td> </tr> <tr> <td>TH070</td> <td>47.8765oN</td> <td>124.8084oW</td> <td>70</td> </tr> <tr> <td>TH080</td> <td>47.8768oN</td> <td>124.8415oW</td> <td>80</td> </tr> <tr> <td>TH090</td> <td>47.8769oN</td> <td>124.8868oW</td> <td>90</td> </tr> <tr> <td>TH100</td> <td>47.8769oN</td> <td>124.9182oW</td> <td>100</td> </tr> <tr> <td><strong>Hoh Head (HH)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>HH025</td> <td>47.7688oN</td> <td>124.5605oW</td> <td>25</td> </tr> <tr> <td>HH042</td> <td>47.7688oN</td> <td>124.6428oW</td> <td>42</td> </tr> <tr> <td>HH065</td> <td>47.7688oN</td> <td>124.7401oW</td> <td>65</td> </tr> <tr> <td><strong>Raft River (RR)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>RR015</td> <td>47.4632oN</td> <td>124.3748oW</td> <td>15</td> </tr> <tr> <td>RR020</td> <td>47.4644oN</td> <td>124.4510oW</td> <td>20</td> </tr> <tr> <td>RR042</td> <td>47.4632oN</td> <td>124.5199oW</td> <td>42</td> </tr> <tr> <td>RR065</td> <td>47.4629oN</td> <td>124.6074oW</td> <td>65</td> </tr> <tr> <td><strong>Cape Elizabeth (CE)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>CE010</td> <td>47.3541oN</td> <td>124.3347oW</td> <td>10</td> </tr> <tr> <td>CE020</td> <td>47.354oN</td> <td>124.3608oW</td> <td>20</td> </tr> <tr> <td>CE030</td> <td>47.3538oN</td> <td>124.3913oW</td> <td>30</td> </tr> <tr> <td>CE040</td> <td>47.3534oN</td> <td>124.4678oW</td> <td>40</td> </tr> <tr> <td>CE050</td> <td>47.3532oN</td> <td>124.5064oW</td> <td>50</td> </tr> <tr> <td>CE060</td> <td>47.3529oN</td> <td>124.5510oW</td> <td>60</td> </tr> <tr> <td>CE070</td> <td>47.3528oN</td> <td>124.5823oW</td> <td>70</td> </tr> <tr> <td>CE080</td> <td>47.3527oN</td> <td>124.6158oW</td> <td>80</td> </tr> <tr> <td>CE090</td> <td>47.3526oN</td> <td>124.6491oW</td> <td>90</td> </tr> <tr> <td>CE100</td> <td>47.3522oN</td> <td>124.6754oW</td> <td>100</td> </tr> <tr> <td><strong>Moclips (MO)</strong></td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>MO010</td> <td>47.2214oN</td> <td>124.2394oW</td> <td>10</td> </tr> <tr> <td>MO015</td> <td>47.2214oN</td> <td>124.2599oW</td> <td>15</td> </tr> <tr> <td>MO020</td> <td>47.2214oN</td> <td>124.2791oW</td> <td>20</td> </tr> <tr> <td>MO030</td> <td>47.2195oN</td> <td>124.3347oW</td> <td>30</td> </tr> <tr> <td>MO042</td> <td>47.2195oN</td> <td>124.3958oW</td> <td>42</td> </tr> </tbody> </table>
Dataset supporting the paper: Deciphering Oxygen Distribution and Hypoxia Profiles in the Tumor Microenvironment: A Data-Driven Mechanistic Modeling Approach
<p>The necessary image files for the paper titled "Deciphering Oxygen Distribution and Hypoxia Profiles in the Tumor Microenvironment: A Data-Driven Mechanistic Modeling Approach"</p>
Experimental microcosm incubations assessing the effect of hypoxia on aqueous iron and organic carbon, pH, sediment organic carbon, and sediment iron-bound organic carbon
To assess the effect of changing oxygen concentrations on coupled carbon and iron cycling in freshwater ecosystems, we performed 6-week microcosm incubations. Incubations were inoculated with sediment and water from Falling Creek Reservoir, Vinton, VA, USA. We started the experiment with 102 microcosms split evenly into oxic and hypoxic treatments. After two weeks, we switched the treatment of approximately half of the remaining microcosms, generating a total of four oxygen regimes: hypoxic, oxic, hypoxic to oxic, and oxic to hypoxic. We sampled the microcosms destructively approximately twice per week, collecting aqueous samples for total and dissolved carbon and iron, as well as sediment samples for organic carbon and iron-bound organic carbon analysis. Iron-bound organic carbon was determined using citrate-bicarbonate-dithionite extractions.
Fig. 1 in Temperature affects the hypoxia tolerance of neotropical Cichlid Geophagus brasiliensis
Fig. 1. Malate Dehydrogenase enzyme activity of Geophagus brasiliensis exposed to normoxic (90% oxygen saturation) and hypoxia (20% oxygen saturation) conditions for 8 hours at 20°C, 24°C and 28°C. a. in liver; b. in white muscle; and c. in heart. Asterisks indicates significant differences between treatments at the same temperature, p <0.05. Different lowercase letters indicate significant differences for the same treatment at the temperatures studied, p <0.05.
Fig. 3 in Temperature affects the hypoxia tolerance of neotropical Cichlid Geophagus brasiliensis
Fig. 3. Citrate Synthase enzyme activity of Geophagus brasiliensis exposed to normoxic (90% oxygen saturation) and hypoxic (20% oxygen saturation) conditions for 8 hours at 20°C, 24°C and 28°C. a. in liver; b. in white muscle; and c. in heart. Asterisks indicates significant differences between treatments at the same temperature, p <0.05. Different lowercase letters indicate significant differences for the same treatment at the temperatures studied, p <0.05.
Fig. 3 in Phenotypic plasticity associated to environmental hypoxia in the neotropical serrasalmid Piaractus mesopotamicus (Holmberg, 1887) (Characiformes: Serrasalmidae)
Fig. 3. Response curves of three morphological variables of Piaractus mesopotamicus (proportion of increase) respect to dissolved oxygen gradient. Black arrow indicates the DO concentration determined for the inflection point of the reaction norm.
Fig. 1 in Phenotypic plasticity associated to environmental hypoxia in the neotropical serrasalmid Piaractus mesopotamicus (Holmberg, 1887) (Characiformes: Serrasalmidae)
Fig. 1. Development and reversion of the three morphological variables exposed to nine hours of hypoxia, followed by three hours of normoxia in Piaractus mesopotamicus. (a) lower lip, (b) maxillary, and (c) opercular valve. Capital letters above box plots indicate groups in multiple comparisons (Tukey's tests) after repeated measures ANOVA.
Fig. 4 in Phenotypic plasticity associated to environmental hypoxia in the neotropical serrasalmid Piaractus mesopotamicus (Holmberg, 1887) (Characiformes: Serrasalmidae)
Fig. 4. Response curves of behavioral and respiratory variables of Piaractus mesopotamicus respect to dissolved oxygen gradient. Black arrow indicates inflection point given by the four parameters logistic function. The curve fitted to data points is not shown for horizontal and vertical movements due to the great dispersion.
Fig. 5 in Phenotypic plasticity associated to environmental hypoxia in the neotropical serrasalmid Piaractus mesopotamicus (Holmberg, 1887) (Characiformes: Serrasalmidae)
Fig. 5. Comparisons of plasticity among behavioral (a), respiratoy (b) and morphological traits (c) of Piaractus mesopotamicus as measured by the coefficient of variation (CV) across the DO gradient. Capital letters above box plots indicate groups in multiple comparison Tukey's tests after a one way ANOVA. Names of traits as defined in the text.
Fig. 2 in Phenotypic plasticity associated to environmental hypoxia in the neotropical serrasalmid Piaractus mesopotamicus (Holmberg, 1887) (Characiformes: Serrasalmidae)
Fig. 2. Photographs showing increases in size of the three morphological traits of Piaractus mesopotamicus analyzed exposed to extreme hypoxia: (a) lower lip, (b) maxillary, and (c) opercular valve. White arrow indicates the area where the expansion of dermal tissue occurred.
ASPH and Hypoxia Marker Expression in Head and Neck Carcinomas: Implications for HPV-Associated Tumours
<p><strong>Data open:</strong> file with parametres used for the multivariate evaluation. </p>
Data from: Coral hypoxia response curve analysis
<p>Oxygen (O<sub>2</sub>) availability is essential for healthy coral reef functioning, yet how continued loss of dissolved O<sub>2</sub> via ocean deoxygenation impacts performance of reef building corals remains unclear. Here we examine how intra-colony spatial geometry of important Great Barrier Reef (GBR) coral species <em>Acropora</em> may influence variation in hypoxic thresholds for upregulation, to better understand capacity to tolerate future reductions in O<sub>2</sub> availability. We first evaluate application of more streamlined models used to parameterise Hypoxia Response Curve data, models that have been used historically to identify variable oxyregulatory capacity. Using closed-system respirometry to analyse O<sub>2</sub> drawdown rate, we show that a 2-parameter model returns similar outputs as previous 12<sup>th</sup> order models for descriptive statistics such as the average oxyregulation capacity (T<sub>pos</sub>) and the ambient O<sub>2</sub> level at which the coral exerts maximum regulation effort (P<sub>cmax</sub>), for diverse <em>Acropora</em> species<em>. </em>Following an experiment to evaluate whether stress induced by coral fragmentation for respirometry affected O<sub>2</sub> drawdown rate, we subsequently identify differences in hypoxic response for the interior and exterior colony locations for the species <em>Acropora abrotanoides</em>, <em>Acropora cf. microphthalma</em>, and <em>Acropora elseyi</em>. Average regulation capacity across species was greater (0.78 to 1.03 ± SE 0.08) at the colony interior compared to exterior (0.60 to 0.85 ± SE 0.08). Moreover, P<sub>cmax</sub> occurred at relatively low <em>p</em>O<sub>2</sub> of <30% (± 1.24; SE) air saturation for all species, across the colony. When compared against ambient O<sub>2</sub> availability, these factors corresponded to differences in mean intra-colony oxyregulation, suggesting that lower variation in dissolved O<sub>2</sub> corresponds with higher capacity for oxyregulation. Collectively our data shows that intra-colony spatial variation affects coral oxyregulation hypoxic thresholds, potentially driving differences in <em>Acropora </em>oxyregulatory capacity.</p>
Data from: Hypoxia blunts angiogenic signaling and upregulates the antioxidant system in elephant seal endothelial cells
<p><strong><em>Background</em></strong></p> <p>Elephant seals exhibit extreme hypoxemic tolerance derived from repetitive hypoxia/reoxygenation episodes they experience during diving bouts. Real-time assessment of the molecular changes underlying protection against hypoxic injury in seals remains restricted by their at-sea inaccessibility. Hence, we developed a proliferative arterial endothelial cell culture model from elephant seals and used RNA-seq, functional assays, and confocal microscopy to assess the molecular response to prolonged hypoxia.</p> <p><strong><em>Results</em></strong></p> <p>Seal and human endothelial cells exposed to 1% O<sub>2</sub> for up to 6 h respond differently to acute and prolonged hypoxia. Seal cells decouple stabilization of the hypoxia-sensitive transcriptional regulator HIF-1α from angiogenic signaling. Rapid upregulation of genes involved in glutathione (GSH) metabolism supports the maintenance of GSH pools, and intracellular succinate increases in seal but not human cells. High maximal and spare respiratory capacity in seal cells after hypoxia exposure occurs in concert with increasing mitochondrial branch length and independent from major changes in extracellular acidification rate, suggesting that seal cells recover oxidative metabolism without significant glycolytic dependency after hypoxia exposure.</p> <p><strong><em>Conclusions</em></strong></p> <p>We found that the glutathione antioxidant system is upregulated in seal cells during hypoxia, while this system remains static in comparable human cells. Furthermore, we found that in contrast to human cells, hypoxia exposure rapidly activates HIF-1 in seal cells, but this response is decoupled from the canonical HIF-angiogenesis pathway. These results highlight the unique mechanisms that confer extraordinary tolerance to limited oxygen availability in a champion diving mammal.</p>
Dataset: Osmoregulation and hypoxia tolerance in the cenote isopod Creaseriella anops: Insights into its distribution in Karst Subterranean Estuaries
<p>This data set contains the information supporting the research article "Osmoregulation and hypoxia tolerance in the cenote isopod Creaseriella anops: Insights into its distribution in Karst Subterranean Estuaries" </p> <p>It contains Respirometry, indicators of cellular damage and Antioxidant system, critical temperatures, and Temperature induced metabolic rates of the isopod Creaseriella anops, and endemic species of the Karst Subterranean Estuaries from the Yucatan Peninsula Mexico.</p>
Data from 'Disparate inventories of hypoxia gene sets across corals align with inferred environmental resilience'
<p>Aquatic deoxygenation has been flagged as an overlooked but key factor driving mass bleaching-induced coral mortality as oxygen supplies lower to concentrations that can elicit an aerobic metabolic crisis i.e., hypoxia. Surprisingly little is known of the fundamental hypoxia responsive gene set inventory corals possess to respond to deoxygenation. It is unclear whether variation in gene copy number across species exist that potentially affect gene expression with subsequent differences in the effectiveness of a given stress response. Here, we used an ortholog-based meta-analysis to investigate how hypoxia gene inventories differed amongst coral species to assess putative copy number variation (CNV) across 24 coral protein sets from species with a sequenced genome that span corals from the robust and complex clade. We found approximately a third of the investigated genes exhibited copy number differences, and these differences were species-specific rather than the robust-complex split.</p> <p>Zipped folders of OrthoFinder results:</p> <p>'Results_Feb16' contains results including all 24 coral species from 7 genera (<em>Acropora, Pocillopora, Stylophora, Montastrea, Montipora, Obricella, Porites</em>).</p> <p>'gene_sets_acropora_acuminata_only' contains results including just one species per genera with <em>Acropora acuminata</em>.</p> <p>'gene_sets_acropora_cytherea_only' contains results including just one species per genera with <em>Acropora cytherea</em>.</p> <p>'gene_sets_acropora_digitifera_only' contains results including just one species per genera with <em>Acropora digitifera</em>.</p> <p> </p> <p>Results and Interpretations from these analyses are published open access here: <a href="https://doi.org/10.3389/fmars.2022.834332">https://doi.org/10.3389/fmars.2022.834332</a></p> <p>Full citation: Alderdice R, Hume BCC, Kühl M, Pernice M, Suggett DJ, Voolstra CR. Disparate inventories of hypoxia gene sets across corals align with inferred environmental resilience. Front Mar Sci. 2022;9. doi:10.3389/fmars.2022.834332</p> <p>Scripts are available here: <a href="https://zenodo.org/record/6396671#.YoYpoS8RoZg">https://github.com/didillysquat/alderdice_2021</a></p>
The interplay between prior selection, mild intermittent exposure, and acute severe exposure in phenotypic and transcriptional response to hypoxia
<p>Hypoxia has profound and diverse effects on aerobic organisms, disrupting oxidative phosphorylation and activating several protective pathways. Predictions have been made that exposure to mild intermittent hypoxia may be protective against more severe exposure and may extend lifespan. Both effects are likely to depend on prior selection on phenotypic and transcriptional plasticity in response to hypoxia, and may therefore show signs of local adaptation. Here we report the lifespan effects of chronic, mild, intermittent hypoxia (CMIH) and short-term survival in acute severe hypoxia (ASH) in four clones of <em>Daphnia magna</em> originating from either permanent or intermittent habitats, the latter regularly drying up with frequent hypoxic conditions. We show that CMIH extended the lifespan in the two clones originating from intermittent habitats but had the opposite effect in the two clones from permanent habitats, which also showed lower tolerance to ASH. Exposure to CMIH did not protect against ASH; to the contrary, <em>Daphnia</em> from the CMIH treatment had lower ASH tolerance than normoxic controls. Few transcripts changed their abundance in response to the CMIH treatment in any of the clones. After 12 hours of ASH treatment, the transcriptional response was more pronounced, with numerous protein-coding genes with functionality in mitochondrial and respiratory metabolism, oxygen transport, and, unexpectedly, gluconeogenesis showing up-regulation. While clones from intermittent habitats showed somewhat stronger differential expression in response to ASH than those from permanent habitats, there were no significant hypoxia-by-habitat of origin or CMIH-by-ASH interactions. GO enrichment analysis revealed a possible hypoxia tolerance role by accelerating the molting cycle and regulating neuron survival through up-regulation of cuticular proteins and neurotrophins, respectively.</p>
Latitudinal cline for hypoxia but not low pH in Tigriopus californicus
<p>Intertidal organisms must tolerate daily fluctuations in environmental parameters, and repeated exposure to co-occurring conditions may result in tolerance to multiple stressors correlating. The intertidal copepod <em>Tigriopus californicus</em> experiences diurnal variation in dissolved oxygen levels and pH as the opposing processes of photosynthesis and cellular respiration lead to coordinated highs during the day and lows at night. While environmental parameters with overlapping spatial gradients frequently result in correlated traits, less attention has been given to exploring temporally correlated stressors. We investigated whether hypoxia tolerance correlates with low pH tolerance by separately testing the hypoxia and low pH stress tolerance separately of 6 genetically differentiated populations of <em>T. californicus</em>. We independently checked for similarities in tolerance for each of the two stressors by latitude, sex, size, and time since collection as predictors. We found that although hypoxia tolerance correlated with latitude, low pH tolerance did not, and no predictor was significant for both stressors. We concluded that temporally coordinated exposure to low pH and low oxygen did not result in populations developing equivalent tolerance for both. Although climate change alters several environmental variables simultaneously, organisms' abilities to tolerate these changes may not be similarly coupled. </p>
Fig. 4 in Effects of the interannual variations in the flood pulse mediated by hypoxia tolerance: the case of the fish assemblages in the upper Paraná River floodplain
Fig. 4. Ordination of the samples of the upper Paraná River floodplain, through the detrended correspondence analysis (DCA), in years of short (diamond: 2000 white, 2001 gray) and moderate floods (square: 2002 gray, 2003 black). Numbers 1-6 are codes of the sampling stations (see Fig. 1).
Fig. 5 in Effects of the interannual variations in the flood pulse mediated by hypoxia tolerance: the case of the fish assemblages in the upper Paraná River floodplain
Fig. 5. Fish assemblage attributes in the main habitats of the upper Paraná River floodplain in years of short (2000 and 2001) and moderate (2002 and 2003) floods. The black area of the bars represents the proportion of STH. Numbers 1-6 on the abscissa are codes of the sampling stations (see Fig. 1).
Fig. 2 in Effects of the interannual variations in the flood pulse mediated by hypoxia tolerance: the case of the fish assemblages in the upper Paraná River floodplain
Fig. 2. Monthly (a) and daily level (b, between January and March) of the upper Paraná River recorded in Porto São José municipality. In b (right axis), the number of days between January and March, when the upper Paraná River surpassed the threshold of 350 cm (horizontal braked line). The years 2000 and 2001 were considered as years of short floods and 2002 and 2003 as years of moderate floods. Source: National Department of Waters and Electric Energy.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
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