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277 results for “co-infections”
Data from: Pathogen community composition and co-infection patterns in a wild community of rodents
<p><strong>ABSTRACT</strong></p> <p>Rodents are major reservoirs of pathogens that can cause disease in humans and livestock. It is therefore important to know what pathogens naturally circulate in rodent populations, and to understand the factors that may influence their distribution in the wild. Here, we describe the incidence and distribution patterns of a range of endemic and zoonotic pathogens circulating among rodent communities in northern France. The community sample consisted of 713 rodents, including 11 host species from diverse habitats. Rodents were screened for virus exposure (hantaviruses, cowpox virus, Lymphocytic choriomeningitis virus, Tick-borne encephalitis virus) using antibody assays. Bacterial communities were characterized using 16S rRNA amplicon sequencing of splenic samples. Multiple correspondence (MCA), regression and association screening (SCN) analyses were used to determine the degree to which extrinsic factors contributed to pathogen community structure, and to identify patterns of associations between pathogens within hosts. We found a rich diversity of bacterial genera, with 36 known or suspected to be pathogenic. We revealed that host species is the most important determinant of pathogen community composition, and that hosts that share habitats can have very different pathogen communities. Pathogen diversity and co-infection rates also vary among host species. Aggregation of pathogens responsible for zoonotic diseases suggests that some rodent species may be more important for transmission risk than others. Moreover we detected positive associations between several pathogens, including <em>Bartonella</em>, <em>Mycoplasma</em> species, Cowpox virus (CPXV) and hantaviruses, and these patterns were generally specific to particular host species. Altogether, our results suggest that host and pathogen specificity is the most important driver of pathogen community structure, and that interspecific pathogen-pathogen associations also depend on host species.</p> <p><strong>FILE DESCRIPTION:</strong></p> <p><strong>MiSeq raw sequences of the 16Sv4 rRNA gene from spleen rodent samples</strong></p> <p>This ZIP file contains the FASTQ files of the paired-end reads (R1: reads 1; R2: reads 2) produced for each spleen rodent sample using the MiSeq platform. The 749 multiplexed PCR products were indexed using both forward and reverse indices. Information of the multiplexed samples (<em>n</em>=363 in replicate) and positive (<em>n</em>= 6) & negative controls (<em>n</em>= 17) is provided in the following XLSX file titled: 16S_raw_abundance_data.xlsx</p> <p>File name: <strong>MiSeq raw sequences of the V4 region 16S rRNA gene.zip</strong></p> <p><strong>Raw input and output files generated by the mothur program</strong></p> <p>This ZIP file contains all the input and output files generated during the MiSeq sequence analysis with the mothur program.</p> <p>File name: <strong>Raw input and output files generated by the mothur program.zip</strong></p> <p><strong>Log file generated by the mothur program</strong></p> <p>This TXT file contains is the history of all the command lines and parameters used during the MiSeq sequence analysis with the mothur program.</p> <p>File name: <strong>mothur.1428506786.logfile</strong></p> <p><strong>Raw abundance table of the 16v4 rRNA gene from spleen rodent samples before data filtering</strong></p> <p>This XLSX file contains the number of reads for each distinct Operational Taxonomic Unit (OTU) and each of the PCR products, including the 332 spleen rodent samples analyzed in the study and the negative & positive controls, sequenced in the MiSeq run before the data filtering. This file contains also the following information: Study_site, Study_year, Sample_habitat, Host_species, Host_age, Host_sex, PCR_ID and the taxonomic classification (Kingdom to Genus) of each OTU.</p> <p>File name: <strong>16S_raw_abundance_data.xlsx</strong></p> <p><strong>Occurrence table of the 16v4 rRNA gene from spleen rodent samples after data filtering</strong></p> <p>This XLSX file contains the occurrences (presence: 1 ; absence: 0) after data filtering of each putative pathogenic Operational Taxonomic Unit (OTU) for each of the 332 spleen rodent samples analyzed in the study.</p> <p>File name: <strong>16S_presence_absence_data.xlsx</strong></p> <p><strong>Statistical Analysis Scripts and Data File</strong></p> <p>This ZIP file contains the R scripts for performing statistical analyses reported in the main text and supplemental materials. There is one main file (Analyses.R), as well as two source scripts required for association screening analyses (SCN.txt and FctTestScreenENV.txt). It also includes an R-legible data file containing occurrences (presence: 1 ; absence: 0) for all pathogen exposure variables on which statistical analyses were conducted (PA_DATA.csv) for each of the 332 spleen rodent samples analyzed in the study. The column names for bacterial exposures correspond to the “Pathogen Code” given in the 16S_presence_absence_data.xlsx file.</p> <p>File name: <strong>Statistical Analysis Scripts and Data File.zip</strong></p>
Identification of co-infections in a cohort of patients diagnosed with Lyme Disease
<p>Serlogy test data used in the study: Identification of co-infections in a cohort of patients diagnosed with Lyme Disease</p>
Fig. 2 in . Study of Nosema spp. in the Tomsk region, Siberia: co-infection is widespread in honeybee colonies
Fig. 2. Distribution of Nosema species in bee colonies (Apis mellifera) throughout the Tomsk region (dots A–I). Bee colonies not infected by Nosema are indicated in yellow; bee
Fig. 4 in Nematode-coccidia parasite co-infections in African buffalo: Epidemiology and associations with host condition and pregnancy
Fig. 4. Predicted mean and standard error body condition scores show associations with infection presence and season, with co-infected buffalo in much lower condition in the early wet season (Table S2). Coccidia infection status is represented with C– and C+; nematode infection status is represented with N– and N+.
Fig. 5 in Nematode-coccidia parasite co-infections in African buffalo: Epidemiology and associations with host condition and pregnancy
Fig. 5. Season and co-infection differences in nematode aggregation. (a) Aggregation patterns in calves (b) and non-calves. (c) In non-calves, the distribution of nematode parasites in the late wet season shows that k is not significantly different in coccidia positive vs. negative buffalo. (d) In the early wet season coccidia positive buffalo have a truncated distribution, resulting in significantly reduced aggregation. Arrows indicate nematode intensity values in the tail of the distribution of coccidia negative buffalo. Coccidia infection status is represented with C– and C+.
Fig. 3 in Nematode-coccidia parasite co-infections in African buffalo: Epidemiology and associations with host condition and pregnancy
Fig. 3. Patterns of parasite egg/oocyst counts with co-infection for (a) nematodes and (b) coccidia. (c), the mean nematode intensity in calves is higher in early wet season than in the late wet season independent of co-infection with coccidia. (d) Co-infection with coccidia alters the seasonal patterns of nematode intensity in non-calf buffalo (>1 year, juvenile through senescent). Calf vs. non-calf division is based on model paramters (Table 1).
Fig. 2 in Nematode-coccidia parasite co-infections in African buffalo: Epidemiology and associations with host condition and pregnancy
Fig. 2. Age specific patterns of parasite prevalence with co-infection. (a) Prevalence of nematodes is higher in buffalo co-infected with coccidia (C+) compared to coccidia negative buffalo (C–) in all age categories (N = 33, 318, 166, 272, 162 for calf, juvenile, subadult, adult and senescent C– buffalo; N = 58, 237, 55, 54, 20 for C+ buffalo). (b) Prevalence of coccidia is higher in buffalo co-infected with nematodes (N+) compared to nematode negative buffalo (N–) in calf, juvenile, subadult, and senescent buffalo but not adult buffalo (N = 13, 107, 92, 144, 56 for calf, juvenile, subadult, adult and senescent N– buffalo; N = 38, 448, 129, 208, 100 for N+ buffalo).
Fig. 1 in Nematode-coccidia parasite co-infections in African buffalo: Epidemiology and associations with host condition and pregnancy
Fig. 1. Age, sex and seasonal patterns of infection. Both parasites had the highest (a) prevalence (sample size for calf, juvenile, subadult, adult, and senescent respectively: N = 91, 555, 221, 326, 182) and (b) mean intensity in calves and juveniles (nematode N = 78, 448, 129, 208, 100; coccidia N = 58, 237, 55, 60, 14). (c) Males had lower estimated nematode prevalence and (d) higher estimated coccidia intensity compared to female buffalo. (e) The estimated nematode prevalence, coccidia prevalence, and (f) mean coccidia intensity were all increased in the early wet season compared to the late wet season. ‡Indicates significant differences at p <0.05.
Fig. 3 in Co-infection patterns of intestinal parasites in arboreal primates (proboscis monkeys, Nasalis larvatus) in Borneo
Fig. 3. Differences in width among trichurid egg morphotypes found in proboscis monkey feces. (T1 n = 11, T2 n = 30, T3 n = 30, T4 n = 2, and T5 n = 10). Median, boxes define the 25th and 75th percentiles, whiskers extend to maximum ± 1.5 times the interquartile range (IQR = middle 50% of the records). *p = 0.05; **p = 0.001; ***p = 0.0001.
Fig. 2 in Co-infection patterns of intestinal parasites in arboreal primates (proboscis monkeys, Nasalis larvatus) in Borneo
Fig. 2. Taxonomic diversity of helminth parasites found in proboscis monkeys. The five detected helminth orders were: the order Enoplida, trichurids (morphotypes T1-T4 genus Trichuris, T5 genus Anatrichosoma), the order Strongylida (morphotypes S1 genus Trichostrongylus, S2 genus Oesophagostomum/Ternidens, S3 unknown strongylid), the order Rhabditida, genus Strongyloides (R), the order Ascaridida, genus Ascaris (with exfoliated rough brown outer shell layer) (A) and the order Oxyurida, genus Enterobius (O). Scale bars = 50 Mm. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article).
Fig. 1 in Co-infection patterns of intestinal parasites in arboreal primates (proboscis monkeys, Nasalis larvatus) in Borneo
Fig. 1. Sample collection sites along the Kinabatangan River in Borneo. The island of Borneo, South-East Asia, with position of Lot 6 on the southern riverbank in the Lower Kinabatangan Wildlife Sanctuary in Sabah, Malaysian Borneo. Map reproduced according to GPS data points collected and mapped via Garmin Map Source (version 6.16.3).
Fig. 4 in Co-infection patterns of intestinal parasites in arboreal primates (proboscis monkeys, Nasalis larvatus) in Borneo
Fig. 4. Differences in length among strongylid egg morphotypes found in proboscis monkey feces. (S1 n = 30, S2 n = 30, and S3 n = 17). Median, boxes define the 25th and 75th percentiles, whiskers extend to maximum ± 1.5 times the interquartile range (IQR = middle 50% of the records). *p = 0.05; **p = 0.001; ***p = 0.0001.
Fig. 1 in Prevalence and co-infection with tick-borne Anaplasma phagocytophilum and Babesia spp. in red deer (Cervus elaphus) and roe deer (Capreolus capreolus) in Southern Norway
Fig. 1. Phylogenetic tree of Babesia isolates and samples of this study (●), based on fragments of 18S rRNA, generated using the Maximum-Likelihood clustering method in MEGA 6 software (1000 replicates; bootstrap values indicated at the nodes). Abbreviations: AU - Austria, BE - Belgium, CA - Canada, DE - Germany, FR - France, HU - Hungary, IT - Italy, JP - Japan, LT - Lithuania, NO - Norway, PL - Poland, RU - Russia, SK - Slovakia, SP - Spain, TU - Turkey, US - United States.
Fig. 2 in Trypanosome co-infections increase in a declining marsupial population
Fig. 2. The proportion of woylie captures detected with (a) T. copemani and (b) T. vegrandis in individual sampling trips across the study period (n = 32, 8, 20, 6, 14, 29, 37, 54, 31, 31, 21, 25, 25, 32, 15, 13, 2, 8, 13, 11, 9, 8), with the x-axis representing continuous time. Error bars represent 95% Jeffrey's confidence intervals of prevalence estimates. Overlaid on prevalence estimates are the capture rates (the number of independent captures as a proportion of the total number of traps set, derived from Wayne et al., 2015) for each of the sampling periods to indicate the woylie population trends over the same period.
Fig. 3 in Trypanosome co-infections increase in a declining marsupial population
Fig. 3. The proportion of woylie captures detected with (a) T. copemani and (b) T. vegrandis across years (categorized into groups for plotting purposes: 2006–2007, 2008, 2009–2010, 2011–2012) for woylies that were either co-infected by the other trypanosome species (blue) or individuals not co-infected by the other trypanosome species (red). Error bars represent 95% Jeffrey's confidence intervals of prevalence estimates. Numbers above the x-axis represent the sample sizes for each group. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 1. A in Trypanosome co-infections increase in a declining marsupial population
Fig. 1. A map of Australia indicating the location of Keninup (our sampling site), with the location of Perth provided for reference.
Fig. 1 in Detecting co-infections of Echinococcus multilocularis and Echinococcus canadensis in coyotes and red foxes in Alberta, Canada using real-time PCR
Fig. 1. Standard curve for qPCR assays to detect E. canadensis and E. multilocularis using Cox143 and Nad234 primers/probes, respectively.
Figs 1-7 in Host-Parasite relationships and co-infection of nasal mites of Chrysomus ruficapillus (Passeriformes: Icteridae) in southern Brazil
Figs 1-7. Nasal mites parasites of Chrysomus ruficapillus (Vieillot, 1819) (Passeriformes: Icteridae) from southern of Brazil: 1, cavity nasal parasitized, circle highlights the location of mites in the nasal turbinates (Bar = 80 mm); 2, specimens of Ereynetidae and Rhinonyssidae (Bar =30 mm); 3; Boydaia agelaii Fain & Aitken, 1967 (Bar = 0.09 mm); 4, Sternostoma strandtmanni Furman, 1957 (Bar = 0.12 mm); 5, Ptilonyssus icteridius (Strandtmann & Furman, 1956) (Bar = 0.14 mm); 6, Ptilonyssus sairae Castro, 1948 (Bar = 0.15 mm); 7, Ptilonyssus sp (Bar = 0.2 mm).
Fig. 2 in Double trouble: Co-infection of Angiostrongylus vasorum and Dirofilaria immitis in golden jackal (Canis aureus) in Friuli Venezia Giulia, Italy
Fig. 2. Pathological findings in case of co-infection with D. immitis and A. vasorum in a golden jackal. (A) Presence of adult D. immitis within the right cardiac chambers (bar = 1 cm). (B) Lung parenchyma show multifocal poorly defined red to yellow-brown nodular firmer areas in the ventral edges of lung lobes (white circle and inset). Multifocal dark brown-black areas representing thrombotic infarcts are also often visible (white square and inset). (bar = 2 cm). (C) Female adult of A. vasorum nematode within a small pulmonary artery (bar = 1 cm). (D) Cross section of adult A. vasorum (black stars) and a thrombus (Th) in the lumen of a small pulmonary artery. Hematoxylin and eosin. (E) Lung parenchyma show multifocal granulomatous interstitial pneumonia. The granulomatous areas contained small central necrotic tissue and occasionally small, calcified areas. Giant macrophagic cells are visible within granulomatous areas (white circle). Embryonated eggs and first-stage larvae of A. vasorum are embedded within these inflammatory foci (black arrows). Masson's trichrome.
Fig. 1 in Double trouble: Co-infection of Angiostrongylus vasorum and Dirofilaria immitis in golden jackal (Canis aureus) in Friuli Venezia Giulia, Italy
Fig. 1. Georeferencing of recovery sites of golden jackal infected by A. vasorum (red dots), D. immitis (yellow dots) and co-infections (black dots) in the period between 2020 and 2023 in FVG region.
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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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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.
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