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135 results for “Microalgae”
Fig. 5 in Transcriptome-wide study in the green microalga Messastrum gracile SE-MC4 identifies prominent roles of photosynthetic integral membrane protein genes during exponential growth stage
Fig. 5. Top DEG pathway enrichment involved during different growth stages. Summary of differential expressed genes (DEGs) identified in photosynthesis pathway (most enriched pathway) of M. gracile SE-MC4 according to Kyoto Encyclopedia of Genes and Genomes (KEGG) functional annotation analysis. The genes at early stationary growth phase were normalized against genes at early exponential growth phase. Green color means down-regulated DEGs; red color means up-regulated DEGs; black color means no DEGs. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 3 in Transcriptome-wide study in the green microalga Messastrum gracile SE-MC4 identifies prominent roles of photosynthetic integral membrane protein genes during exponential growth stage
Fig. 3. Differential expressed gene analysis (DEG) of transcriptome. DEG in Volcano plot (log transform of early exponential growth and early stationary growth phases versus inverse log Padj – corrected P-value). Up-regulated DEGs are in red color dots, down-regulated DEGs are in blue dots, while grey dots represent no significant DEGs. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 2 in Transcriptome-wide study in the green microalga Messastrum gracile SE-MC4 identifies prominent roles of photosynthetic integral membrane protein genes during exponential growth stage
Fig. 2. Transcriptome expression analysis during different growth stages. (a) Venn diagram for specific treatment genes. Venn diagram constructed based on subset between gene pools in the early exponential and early stationary growth phases of M. gracile SEMC4 cultures. The total number of early exponential growth-specific (EEG-specific) genes (blue subset); early stationary growth-specific (ESG-specific) genes (pink sub set) and regulatory genes (purple sub set) are as indicated. (b) Soft clustering based on time series analysis on expression changes between early exponential growth and early stationary growth phases of M. gracile SE-MC4 cultures. R1, R2 and R3 are the biological replicates of each early exponential (day 1) and early stationary (day 12) growth phase of M. gracile SE-MC4 cultures. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 3 in Fatty acids as chemotaxonomic and ecophysiological traits in green microalgae (desmids, Zygnematophyceae, Streptophyta): A discriminant analysis approach
Fig. 3. Linear discriminant analysis based on fatty acid profiles of desmid strains belonging to the time-isolation group. (a) Discrimination of the clusters ("very old", "old" and "new") at the start of cultivation (2 days). (b) Discrimination of the clusters at the end of cultivation (24 days). DF1 – the first discrimination function 1; DF2 – the second discrimination function; red triangles – strains cultivated> 35 years ("very old"); green quadrangles – strains cultivated between 15 and 35 years ("old"); blue circles – strains cultivated ≤ 15 years ("new"). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 2 in Fatty acids as chemotaxonomic and ecophysiological traits in green microalgae (desmids, Zygnematophyceae, Streptophyta): A discriminant analysis approach
Fig. 2. Linear discriminant analysis based on fatty acid profiles of desmid strains belonging to the trophic-preference group. (a) Discrimination of the clusters (oligotrophic, meso-oligotrophic, meso-eutrophic, and eutrophic) at the start of cultivation (2 days). (b) Discrimination of the clusters at the end of cultivation (24 days). DF1 – the first discrimination function 1; DF2 – the second discrimination function; red triangles – eutrophic strains; orange quadrangles – meso-eutrophic strains; green pentangles – meso-oligotrophic strains; blue circles – oligotrophic strains. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Efficacy of a Microalgae Extract PhaeoSOL Combined With Natural Stimulant on Cognitive Function and Gaming Performance of Video Gamers
ClinicalTrials.gov study NCT04851899. IPD Sharing: NO. Countries: 1. Publications: 1.
Effects of a Microalgae Extract Dietary Supplement on Gut Health, Anxiety, and Immune Function
ClinicalTrials.gov study NCT06425094. IPD Sharing: NO. Countries: 1. Publications: 4.
Intervention With Long-chain n-3 Polyunsaturated Fatty Acids From Microalgae Oil in Patients With Rheumatoid Arthritis
ClinicalTrials.gov study NCT01742468. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Effect of BrainPhyt, a Microalgae Based Ingredient on Cognitive Function in Healthy Older Subjects
ClinicalTrials.gov study NCT04832412. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Microalgae Extract Phaeosol Combined to Exercise in Healthy Overweight Women : Efficacy on Body Weight Management
ClinicalTrials.gov study NCT04761406. IPD Sharing: NO. Countries: 1. Publications: 2.
Data from: Direct effects of microalgae and protists on herring (Clupea harengus) yolk sac larvae
Open the record for dataset details and reuse information.
Data from: Allelopathy as an emergent, exploitable public good in the bloom-forming microalga Prymnesium parvum
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Dataset of biofouling epibionts on microalgae compiled from literature and environmental variables from open access databases
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Data and code for: Microalgae-blend tilapia feed eliminates fishmeal and fish oil, improves growth, and is cost viable
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Data from: Treatment of aquaculture effluent with Chlorella vulgaris and Tetradesmus obliquus: the effect of pretreatment on microalgae growth and nutrient removal efficiency
The ongoing and increasing worldwide demand for fish has caused a steady increase in aquaculture production during the last decades. This emphasizes the importance of farming systems with a low ecological footprint, like recirculating aquaculture systems (RAS), which are an alternative to traditional open systems. Furthermore, implementing microalgae treatments in RAS, sustainable water management and low discharge of concentrated wastewater could be achieved, allowing its reuse in the system. The influence of three factors on microalgae treatment efficiency in RAS water were studied: i) microalgae species (Chlorella vulgaris, Tetradesmus obliquus), ii) water pre-treatment (sterile filtration), and iii) sampling location within the RAS (e.g. from fish tank, after UV-disinfection, etc.). To this end, fully factorial, replicated cultivations were carried out in 100-ml flasks, and nutrient removal, microalgae growth, and density of bacteria and protozoa were measured for up to 18 days. Results show that both species are able to grow in RAS water and effectively remove nutrients in it, yet their performance depended greatly on water quality. In sterile RAS water, growth and nutrient removal efficiency of C. vulgaris surpassed that of T. obliquus. In non-sterile RAS water, the pattern reversed because of grazing proto- zoa. The location of sampling within the RAS had no discernible effect on microalgae growth or nutrient removal efficiency. The results confirm that a microalgae-based technology to treat and valorise RAS water is technically feasible, yet caution that inferences made can be reversed depending on the choice of the species and the pre- treatment of the RAS water prior to cultivation.
Data from: Coral feeding on microalgae assessed with molecular trophic markers
Herbivory in corals, especially for symbiotic species, remains controversial. To investigate the capacity of scleractinian and soft corals to capture microalgae, we conducted controlled laboratory experiments offering five algal species: the cryptophyte Rhodomonas marina, the haptophytes Isochrysis galbana and Phaeocystis globosa, and the diatoms Conticribra weissflogii and Thalassiosira pseudonana. Coral species included the symbiotic soft corals Heteroxenia fuscescens and Sinularia flexibilis, the asymbiotic scleractinian coral Tubastrea coccinea, and the symbiotic scleractinian corals Stylophora pistillata, Pavona cactus and Oculina arbuscula. Herbivory was assessed by end-point PCR amplification of algae-specific 18S rRNA gene fragments purified from coral tissue genomic DNA extracts. The ability to capture microalgae varied with coral and algal species and could not be explained by prey size or taxonomy. Herbivory was not detected in S. flexibilis and S. pistillata. P. globosa was the only algal prey that was never captured by any coral. Although predation defence mechanisms have been shown for Phaeocystis spp. against many potential predators, this study is the first to suggest this for corals. This study provides new insights on herbivory in symbiotic corals and suggests that corals may be selective herbivorous feeders.
Figure 1 in Effect of untreated and pretreated sugarcane molasses on growth performance of Haematococcus pluvialis microalgae in inorganic fertilizer and macrophyte extract culture media
Figure 1. Diagram of Haematococcus pluviais, where: (A) maintenance of strain in 10 mL with WC culture medium; (B) initial culture in 250 mL with WC culture medium; (C) culture in 2 L with NPK culture medium; (D) experiment of mixotrophic cultivation with untreated and pretreated sugarcane molasses with two different culture media, NPK and ME (macrophyte extract).
Fig. 5 in Efeitos da depleção de nitrogênio sobre a biomassa e produção lipídica de três espécies de microalgas
Fig. 5. Curvas de crescimento das culturas de Ankistrodesmus fusiformis submetidas a diferentes concentrações de nitrato de sódio (A0 = Controle; A1 = 40%; A2 = 20%).
Fig. 2 in Efeitos da depleção de nitrogênio sobre a biomassa e produção lipídica de três espécies de microalgas
Fig. 2. Massa seca das culturas de Desmodesmus spinosus submetidas a diferentes concentrações de nitrato de sódio (D0 = Controle; D1 = 40%; D2 = 20%).
Fig. 1 in Do we similarly assess diversity with microscopy and high-throughput sequencing? Case of microalgae in lakes
Fig. 1 Location of the sampled lakes in the French Northern Alps
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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)
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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
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.