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Data from: Sequence-based detection of emerging antigenically novel influenza A viruses
<p>The detection of evolutionary transitions in influenza A (H3N2) viruses' antigenicity is a major obstacle to effective vaccine design and development. In this study, we describe NIAViD, an unsupervised machine learning tool, adept at identifying these transitions, using HA1 sequence and associated physicochemical properties. NIAViD, performed with 88.9% (95% CI, 56.5%–98.0%) and 72.7% (95% CI,43.4%– 90.3%) sensitivity in training and validation respectively, outperforming the uncalibrated null model – 33.3% (95% CI,12.1%–64.6%) and does not require the need for potentially biased, time-consuming and costly laboratory assays. The pivotal role of Boman's index, indicative of the virus's cell surface binding potential, is underscored, enhancing the precision of detecting antigenic transitions. NIAViD's efficacy is not only in identifying influenza isolates that belong to novel antigenic clusters, but also in pinpointing potential sites driving significant antigenic changes, without the reliance on explicit modeling of hemagglutinin inhibition titers. Our approach holds immense promise to augment existing surveillance networks, offering timely insights for the development of updated, effective influenza vaccines. Consequently, NIAViD, in conjunction with other resources, could be used to support surveillance efforts and inform the development of updated influenza vaccines.</p>
Fig. 4 in A novel method to obtain accurate length estimates of carnivorous reef fishes from a single video camera
Fig. 4. Boxplots showing the length distributions (mm) for Acanthistius patachonicus in five Submarine Parks within Golfo Nuevo, estimated by the naive (n = 132), Reference scale at the bait level (RSB) (n = 98) and Mirrored baited underwater video system (MBUV) (n = 132) methods. The numbers of fish measured with the MBUV in each reef are indicated, and the widths of the boxes within each reef are proportional to those numbers. The x-axis was truncated to avoid loss of detail.
Fig. 1 in A novel method to obtain accurate length estimates of carnivorous reef fishes from a single video camera
Fig. 1. Mirrored baited underwater video system (MBUV). (a) MBUV settled on bottom for calibration purposes: 1) video signal and remote control, 2) strained cables marked every 200 mm segments, 3) placement of the bait holder, 4) mirrored surface; (b) Camera view of a MBUV deployment showing the naive length of a sea bass Acanthistius patachonicus (NL), the length of its reflected image (LRI), and the reference scales (RS = 200 mm) used for applying the MBUV and Reference scale at the bait level (RSB) procedures. Four fishes (1-4) could be accurately measured in this snapshot; fish #4 could be sized even when its body laid wholly outside of the mirrored area but was partially reflected by it.
Fig. 3 in A novel method to obtain accurate length estimates of carnivorous reef fishes from a single video camera
Fig. 3. Histogram and boxplot showing the distribution of the relative errors of length estimates for three plastic silhouettes of 112 mm, 360 mm and 444 mm. The boxplot below indicates a median relative error = -0.9%.
Fig. 5 in A novel method to obtain accurate length estimates of carnivorous reef fishes from a single video camera
Fig. 5. Scatter plots with marginal histograms showing fish length estimates (mm) obtained with (a) Mirrored baited underwater video system (MBUV) and naive methods (n = 132), and with (b) MBUV and Reference scale at the bait level (RSB) methods (n = 67), in five Submarine Parks within Golfo Nuevo. Solid circles in (a) represent truncated lengths (>550 mm). The corresponding naive estimates for the truncated lengths are indicated next to the circles. Solid black lines represent the regression 1:1 in both boxes.
Fig. 2 in A novel method to obtain accurate length estimates of carnivorous reef fishes from a single video camera
Fig. 2. Calibration (a) and 'Height' (b) functions for the Mirrored baited underwater video system (MBUV) system. The solid lines represent the fitted models. Shaded areas represent 95% confidence regions. Jittered rugs on the x-axis indicate the distribution of the NL/LRI ratio and NL/LRI ratio-1 data, respectively. NL = naive length, LRI = length of the reflected image.
Figures 5‒6 in Novel ecological information for Silvery Pigeon Columba argentina, with first description of the chick
Figures 5‒6. Fig fruits Ficus sp., a food resource of Silvery Pigeon Columba argentina, Linggam Island, Aceh province, Sumatra, 8 July 2021 (Muhammad Iqbal)
Figure 1 in Novel ecological information for Silvery Pigeon Columba argentina, with first description of the chick
Figure 1. Silvery Pigeon Columba argentina chick, collected on Tepi Island, Aceh province, Sumatra, 3 July 2021 (Muhammad Iqbal)
Figure 4 in Novel ecological information for Silvery Pigeon Columba argentina, with first description of the chick
Figure 4. Coconut frond where the Silvery Pigeon Columba argentina chick in Fig. 1 was reportedly found, Tepi Island, Aceh province, Sumatra, 4 July 2021 (Muhammad Iqbal)
Figure 3 in Novel ecological information for Silvery Pigeon Columba argentina, with first description of the chick
Figure 3. Adult Silvery Pigeon Columba argentina, Tepi Island, Aceh province, Sumatra, 4 July 2021 (Muhammad Iqbal)
Figure 7‒8. Chinese Bayan fruit Ficus microcarpa, reportedly a in Novel ecological information for Silvery Pigeon Columba argentina, with first description of the chick
Figure 7‒8. Chinese Bayan fruit Ficus microcarpa, reportedly a major food resource of Silvery Pigeon Columba argentina, Bulu Hadik, Teluk Dalam subdistrict, Aceh province, Sumatra, 10 July 2021 (Muhammad Iqbal)
FIG. 4 in A journey through Cyanobacteria in Brazil: a review of novel genera and 16S rRNA sequences
FIG. 4. — Phylogenetic analysis of Brasilonema Fiore, Sant'Anna, de Paiva Azevedo, Komarek, Kaštovský, Sulek & Lorenzi and other Cyanobacteria reference strains. Brazilian strains are in bold.
FIG. 5 in A journey through Cyanobacteria in Brazil: a review of novel genera and 16S rRNA sequences
FIG. 5. — Phylogenetic analysis of Capilliphycus T.A.Caires, Sant'Anna & J.M.Nunes and other Cyanobacteria reference strains. Brazilian strains are in bold.
FIG. 3 in A journey through Cyanobacteria in Brazil: a review of novel genera and 16S rRNA sequences
FIG. 3. — Phylogenetic reconstruction of 16S rDNA of Brazilian strains and reference strains of Cyanobacteria. The strains marked in green are Brazilian genera. The stripe colors represent taxonomical orders.
FIG. 2 in A journey through Cyanobacteria in Brazil: a review of novel genera and 16S rRNA sequences
FIG. 2. — Flowchart of search methods for identification and selection of Brazilian 16S rDNA sequences from GenBank (NCBI).
Concise Synthesis of Pseudane IX, its N-Oxide and Novel Carboxamide Analogs with Antibacterial Activity - NMR Data
<p>This archive contains raw 1H/13C FIDs and associated data in Bruker-specific format that can be viewed with Bruker’s TopSpin or other appropriate NMR processing software. The subfolders are named in accordance with the compound numbering in the associated research paper (Concise Synthesis of Pseudane IX, its N-Oxide and Novel Carboxamide Analogs with Antibacterial Activity).</p> <p>Correspondence: angelov@uni-plovdiv.bg</p>
Fig. 3 in Novel aspects of Drosophila suzukii (Diptera: Drosophilidae) biology and an improved method for culturing this invasive species with a modified D. melanogaster diet
Fig. 3. Effect of triethylamine anesthetic exposure on the recovery of Drosophila adults: D. melanogaster (white circles, n = 181 adults), D. suzukii (black circles, n = 175 adults).
Fig. 2 in Novel aspects of Drosophila suzukii (Diptera: Drosophilidae) biology and an improved method for culturing this invasive species with a modified D. melanogaster diet
Fig. 2. Effects of dietary ethanol (normal environmental ethanol range ≈ 0– 9% ethanol) on Drosophila suzukii survival when compared with D. melanogaster tolerance to ethanol (top graph) and sex-specific sensitivities of D. suzukii adults to ethanol (bottom graph). Summary of probit analyses are provided and statistics with bo = intercept estimate, b1 = estimated slope estimate for each fly species, with b1 = 0 for the baseline control in each graph (D. suzukii [top graph], D. suzukii males [bottom graph]).
Fig. 1 in Novel aspects of Drosophila suzukii (Diptera: Drosophilidae) biology and an improved method for culturing this invasive species with a modified D. melanogaster diet
Fig. 1. Dietary manipulation of Drosophila suzukii cultures based on the use of 5 berry species (blackberry, strawberry, black cherry, blueberry, and grape) with a no-fruit (No Fruit) control (grey bars), and cultures to which yeast was added (+Y) or omitted (−Y) from 4-24® drosophila media (white bars). Asterisks indicate mean differences from 2 respective baseline controls (B), i.e., Blackberry−Y (14 d) and Blackberry+Y (21 d), according to multiple Wilcoxon 2-sample tests.
Fig. 10 in Host-parasite interactions during a biological invasion: The fate of lungworms (Rhabdias spp.) inside native and novel anuran hosts
Fig. 10. Comparisons of inflammatory cells recruited to inflammatory foci in cane toads, Rhinella marina (a) and native frogs, Cyclorana australis (b). Each anuran species was exposed to infective larvae of Rhabdias hylae (white bars) and Rhabdias pseudosphaerocephala (grey bars). Graphs show average values ± 1 S.E.M.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.