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Fig. 1 in ON THE VECTOR PROPERTIES OF HENOSEPILACHNA VIGINTIOCTOMACULATA MOTSCHULSKY, 1858 (COLEOPTERA: COCCINELLIDAE) IN THE TRANSMISSION OF POTATO VIRUSES
Fig. 1. Chemo-orientation of Henosepilachna vigintioctomaculata. Reduction: 1 – % of healthy insects on leaves of healthy plants; 2 – % of infected insects on leaves of healthy plants; 3 – % of healthy insects on potato leaves infected with plant viruses (PVY, PVM, PVX, PVS, PLRV, PSTVd); 4 – % of infected insects on potato leaves infected with plant virus (PVY, PVM, PVX, PVS, PLRV, PSTVd); healthy insects – H. vigintioctomaculata with no potato viruses detected in their bodies; infected insects – H. vigintioctomaculata with certain potato viruses detected in their bodies (PVY, PVM, PVX, PVS, PLRV, and PSTVd); healthy plants – the potato leaves that were not infected with any plant virus; infected plants – the potato leaves that were infected with one or several plant viruses (PVY, PVM, PVX, PVS, PLRV, and PSTVd). 19
Fig. 3 in ON THE VECTOR PROPERTIES OF HENOSEPILACHNA VIGINTIOCTOMACULATA MOTSCHULSKY, 1858 (COLEOPTERA: COCCINELLIDAE) IN THE TRANSMISSION OF POTATO VIRUSES
Fig. 3. Chemo-orientation of infected Henosepilachna vigintioctomaculata. Reduction: 1 – % of infected insects on leaves of healthy plants; 2 – % of infected insects on potato leaves infected with plant virus (PVY, PVM, PVX, PVS, PLRV, PSTVd); infected insects – H. vigintioctomaculata with certain potato viruses detected in their bodies (PVY, PVM, PVX, PVS, PLRV, and PSTVd); healthy plants – the potato leaves that were not infected with any plant virus; infected plants – the potato leaves that were infected with one or several plant viruses (PVY, PVM, PVX, PVS, PLRV, and PSTVd).
Data accompanying "Unipolar Quantum Optoelectronics for High Speed Direct Modulation and Transmission in 8-14 µm Atmospheric Window"
<p>This dataset contains measurement data for the results presented in "Unipolar Quantum Optoelectronics for High Speed Direct Modulation and Transmission in 8-14 µm Atmospheric Window".</p>
Figure 7 in Pilot study: investigating the role of biofouling in transmission of Ostreid herpesvirus 1 (OsHV-1)
Figure 7. Detection of OsHV-1 DNA in serial dilutions prepared with tissue homogenates from various taxa. Data points are the average Ct value for duplicate tissue samples spiked with for each quantity of starting template.
Figure 3 in Pilot study: investigating the role of biofouling in transmission of Ostreid herpesvirus 1 (OsHV-1)
Figure 3. Settlement array structures used for collection of biofouling assemblages. (A) Diagram of the PVC pipe holding the collecting plates; (B, C) Array structures within a mesh basket to reduce predation when fixed to an intertidal oyster tray or deployed in a floating basket.
Figure 5 in Pilot study: investigating the role of biofouling in transmission of Ostreid herpesvirus 1 (OsHV-1)
Figure 5. Frequency of biofouling taxa on settlement plates deployed for the laboratory challenge experiment (n = 44).
Figure 4 in Pilot study: investigating the role of biofouling in transmission of Ostreid herpesvirus 1 (OsHV-1)
Figure 4. Experimental design to test for transmission of OsHV-1 from biofouling organisms recruited from the Georges River when challenged with OsHV-1 by cohabitation with Pacific oysters infected by injection. The number of replicate tanks is indicated along with the number and type of organisms present in each tank for the of acclimation, and two periods of cohabitation.
Figure 1. Scenarios and experimental design for assessing a in Pilot study: investigating the role of biofouling in transmission of Ostreid herpesvirus 1 (OsHV-1)
Figure 1. Scenarios and experimental design for assessing a range of biofouling organisms for the potential to spread OsHV-1. A. Scenario for the OsHV-1 transmission pathway evaluated by field surveillance. B.1 Scenario for the vessel biofouling OsHV-1 transmission pathway. B.2 Adaptation of the vessel biofouling scenario for a laboratory infection trial with Pacific oysters and biofouling organisms evaluated as intermediates for transmission from injected Pacific oysters to naïve Pacific oysters.
Figure 2 in Pilot study: investigating the role of biofouling in transmission of Ostreid herpesvirus 1 (OsHV-1)
Figure 2. Location of the three surveillance and sampling sites (A, B, and C) within Woolooware Bay and the Georges River estuary, NSW, Australia. Site A (Latitude: −34.0339; Longitude: 151.1467); Site B (−34.0260; 151.1413); and Site C (−34.0119; 151.1465).
Nanoparticle Size Estimation by Scanning Transmission Electron Microscopy and Generative AI
<p>The "raw" directories contain unaltered simulated and experimental data. The train and val directories contain normalized data used to train the models of the manuscript. The dataframes directory contains all information about the atomic models. Exp info contains info about the raw experimental data (excluding the gas-cell data). </p>
Data from: Climate change could fuel urinary schistosomiasis transmission in Africa and Europe
<p>This dataset contains primary, intermediate, and output data for "Climate change could fuel urinary schistosomiasis transmission in Africa and Europe". In this paper, we use mechanistic and correlative modelling to predict the distribution of schistosomiasis intermediate host snail <em>Bulinus truncatus.</em> Model projections suggest the suitable habitat for <em>B. truncatus</em> will increase by 17%, with new suitable habitat in Southern Europe and Central Africa, and a reduction in suitable habitat in the Sahel region.</p>
◂Fig. 4 Gynoecium of C. crenata %yellow frames), C. cf. grandicalyx %blue frames) and C. sinensis %pink frames; A–R light microscopy; TS in horizontal orientation). A Secantial section. B, C TS %note cellular organisation). D Secantial section. E, F TS %note cellular organisation). G Secantial section of young gynoecium showing cellular organisation. H–J TS %note lacking cellular organisation, localisation in K–M). K–M LS at different levels from outside to inside of the same specimen %note strongly stained peripheral tissue; asterisks indicate tissue illustrated in H–J). N TS %note dehiscence lines of the prospective endocarp). O, P TS showing transmission tissue and dorsal bundles at top of style. Q vascularisation at base of gynoecium %note strongly stained peripheral tissue). R Vascularisation at base of flower %LS, longisection; TS, transverse section; db, dorsal bundle; dl, dehiscent line; ep, epidermis; lb, lateral bundle; tt, transmission tissue; ut, peripheral tissue; vb, ventral bundle; vs, ventral slit) in Observations on flower and fruit anatomy in dioecious species of Cordia (Cordiaceae, Boraginales) with evolutionary interpretations
◂Fig. 4 Gynoecium of C. crenata %yellow frames), C. cf. grandicalyx %blue frames) and C. sinensis %pink frames; A–R light microscopy; TS in horizontal orientation). A Secantial section. B, C TS %note cellular organisation). D Secantial section. E, F TS %note cellular organisation). G Secantial section of young gynoecium showing cellular organisation. H–J TS %note lacking cellular organisation, localisation in K–M). K–M LS at different levels from outside to inside of the same specimen %note strongly stained peripheral tissue; asterisks indicate tissue illustrated in H–J). N TS %note dehiscence lines of the prospective endocarp). O, P TS showing transmission tissue and dorsal bundles at top of style. Q vascularisation at base of gynoecium %note strongly stained peripheral tissue). R Vascularisation at base of flower %LS, longisection; TS, transverse section; db, dorsal bundle; dl, dehiscent line; ep, epidermis; lb, lateral bundle; tt, transmission tissue; ut, peripheral tissue; vb, ventral bundle; vs, ventral slit)
◂Fig. 3 Gynoecium of C. crenata %yellow frames), C. cf. grandicalyx %blue frames) and C. sinensis %pink frames; A, B stack shot images; C–K light microscopy; G polarised light; TS in horizontal orientation). A, B Anthetic female flower, calyx and corolla partly removed. B LS of gynoecium. C LS of functionally female flower %note strongly stained peripheral tissue of corolla, anther and gynoecium). D LS of gynoecium. E, F TS of functionally female flower %note strongly stained, peripheral tissue). G TS of functionally female flower %note crystal deposition). H LS of ovule %note stalked embryo sac). J TS of functionally male flower with non-functional ovules. K LS of functionally male flower %style lacking, original position indicated by an asterisk) %LS, longisection; TS, transverse section; a,anther; bs, basal septum; c, calyx; car, carpel; co, corolla; db, dorsal bundles; es, embryo sac; fs, false septum; lb, lateral bundles; o, ovule; stg, stigma; sty, style; t, trichomes; tt, transmission tissue; ut, peripheral, strongly stained tissue; vb, ventral bundles; vs, ventral slit) in Observations on flower and fruit anatomy in dioecious species of Cordia (Cordiaceae, Boraginales) with evolutionary interpretations
◂Fig. 3 Gynoecium of C. crenata %yellow frames), C. cf. grandicalyx %blue frames) and C. sinensis %pink frames; A, B stack shot images; C–K light microscopy; G polarised light; TS in horizontal orientation). A, B Anthetic female flower, calyx and corolla partly removed. B LS of gynoecium. C LS of functionally female flower %note strongly stained peripheral tissue of corolla, anther and gynoecium). D LS of gynoecium. E, F TS of functionally female flower %note strongly stained, peripheral tissue). G TS of functionally female flower %note crystal deposition). H LS of ovule %note stalked embryo sac). J TS of functionally male flower with non-functional ovules. K LS of functionally male flower %style lacking, original position indicated by an asterisk) %LS, longisection; TS, transverse section; a,anther; bs, basal septum; c, calyx; car, carpel; co, corolla; db, dorsal bundles; es, embryo sac; fs, false septum; lb, lateral bundles; o, ovule; stg, stigma; sty, style; t, trichomes; tt, transmission tissue; ut, peripheral, strongly stained tissue; vb, ventral bundles; vs, ventral slit)
Fig. 3 in Environmental determinants of spatial and temporal variations in the transmission of Toxoplasma gondii in its definitive hosts
Fig. 3. Predicted relationships between NAO winter index and the probability of seropositivity for Toxoplasma gondii in all cats sampled; (a) juveniles and (b) adults. Points represent the observed seoprevalence values with 95% confidence intervals as whiskers. A median farm density (0.68 farm/km2) was used to calculate the predictions (full line). Minimal farm density (0 farm/km2) observed among sampled communes was used to calculate the minimal predictions of the model (dotted lines). High values of farm density (2 and 4 farms/km2) were used to calculate the maximal predictions of the model (dashed and dotted-dashed lines).
Fig. 2 in Environmental determinants of spatial and temporal variations in the transmission of Toxoplasma gondii in its definitive hosts
Fig. 2. Interannual variations in Toxoplasma gondii seroprevalence in the three types of cats standardised by age (bars) during the study period. Line segments represent the 95% confidence intervals for seroprevalence, and the numbers in brackets indicate the sample sizes. Wildcats (Felis s. silvestris), domestic cats (Felis s. catus) and hybrids are pooled.
Fig. 1 in Environmental determinants of spatial and temporal variations in the transmission of Toxoplasma gondii in its definitive hosts
Fig. 1. European wildcat (Felis s. silvestris) distribution in France (grey area; Léger et al., 2008; Say et al., 2012), and locations of samples from domestic cats (Felis s. catus), wildcats and their hybrids. Cat types are represented by different symbols (see the bottom left of the map). One location might correspond to several individuals (1, 2, 3, or 8), the size of the dot being proportional to the number (indicated at the right of the symbols) of individuals collected in each commune.
Fig. 1 in Testing the robustness of transmission network models to predict ectoparasite loads. One lizard, two ticks and four years
Fig. 1. Transmission networks generated with (a) a short time window of infection; and (b) a long time window of infection, from the GPS location data of the lizards in the study population in 2010. Nodes represent individual lizards and edges between nodes are directed towards the lizard that is at risk of infection. The edges are weighted as described in the main text and the thicker the line the more weight is associated with that edge.
Fig. 2 in Networks and the ecology of parasite transmission: A framework for wildlife parasitology
Fig. 2. How do we use networks to understand the ecology of parasite transmission? Networks allow us to describe how the behaviour of individuals collectively affects the transmission of parasites within wildlife populations. They provide a flexible framework that enables analysis at three different levels; individual (panel A), dyadic (pair-wise associations) (panel B) and the network (population) level (panel C). Within each level of analysis, there are different metrics and analytical approaches that can be used to explore the ecology of parasite transmission.
Fig. 1 in Networks and the ecology of parasite transmission: A framework for wildlife parasitology
Fig. 1. What is a network? A network in its most elementary form is an adjacency matrix, where row and column labels represent the individuals in the network, and the remaining cells represent the pair-wise associations among individuals in the network (panel A). These associations can be weighted, as below (panel A), where stronger relationships are assigned a higher value (for example, the duration or frequency of contact). They can also be directed, to reflect the direction of the association; in this instance, the direction of possible parasite transmission. In this case, rows represent donor nodes, and columns represent recipient nodes (e.g., in panel A: from node C (donor) to node D (recipient), there is a score of 1). The matrix can be visualised as a network diagram (panel B), consisting of nodes, which represent the epidemiological unit of interest (usually individuals) connected together by a series of edges representing the measure of association (the potential for parasite transmission). In context of understanding the ecology of parasite transmission, edges represent a 'contact' between two hosts that provides an opportunity for parasite transfer. The weighting of edges represents the likelihood of parasite transmission (e.g., the frequency or intensity of contact among hosts). The definition of a contact will depend on the type of parasite considered, and how it is passed from one host to another.
Fig. 1 in Generalists at the interface: Nematode transmission between wild and domestic ungulates
Fig. 1. Correlation between degree (vertical axis) and number of references (horizontal axis) for nematode parasites of wild ungulate species (black dots). Blue line is fitted linear model, and gray area shows standard error.
ScienceDex guides
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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.