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Fig. 4 in Molecular characterization of the re-emerging West Nile virus in avian species and equids in Israel, 2018, and pathological description of the disease

Fig. 4 Replication of yellow-legged seagull-derived WNV in Vero and C6/36 cells. Cytopathic effect (left) was observed after one passage in both cell lines. The control cells (right) were grown under the same conditions. Scale-bars: 100 µM

opencc-by-4.0Oct 2020View details →

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Fig. 5 in Molecular characterization of the re-emerging West Nile virus in avian species and equids in Israel, 2018, and pathological description of the disease

Fig. 5 Phylogenetic analysis of West Nile viruses (WNVs) from avian and equine hosts studied in Israel during 2016 and 2018. The analysis was conducted on a nucleotide sequence of the genes encoding the capsid, pre-membrane protein, and membrane protein, using the neighbor-joining method implemented in MEGA X software. The robustness of branching pattern was tested by 1000 bootstrap replications. The rates among sites algorithm used was gamma distribution with invariant sites (G+I). The bar denotes 0.02 nucleotide substitutions per site. Lineage 1 and 2 reference strains are present with country and year of isolation. The GenBank annotated sequences are underlined and the sequences obtained in this study (during 2016 and 2018) are marked with rectangles

opencc-by-4.0Oct 2020View details →

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Tractography Templates for White Matter Microstructure Analysis in Aging and Alzheimer's Disease

This dataset contains tractography templates derived from several studies focused on white matter microstructure and its associations with neurodegenerative diseases, particularly Alzheimer's disease and Parkinsonism. These templates span key tracts relevant to both cognitive decline and motor function, including but not limited to the medial temporal lobe white matter, transcallosal fibers, sensorimotor tracts, and the fornix. The templates were developed and validated using advanced diffusion MRI techniques across various populations, including aging individuals, dementia patients, and those at risk of neurodegenerative conditions. This resource serves as a valuable tool for researchers investigating the structural integrity of white matter in both health and disease, allowing for cross-study comparability and enhancing the understanding of neurodegenerative processes.

opencc-by-4.0Sep 2024View details →

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Classification of Text Data on Rare Diseases

<div>A dataset with text and labels for 3 categories: </div> <div> <div> </div> <div>- Rare Diseases</div> <div>- Non-Rare Diseases</div> <div>- Other</div> </div> <div> </div> <div>It is a subset of abstracts obtained from PubMed and sorted into the 3 classes on the basis of their MeSH terms.</div> <div> </div> <div>The dataset is provided for demonstration and methodology validation purposes. The original PubMed data was randomly under-sampled. </div> The dataset consists of 3 files in the Tab-Separated Values (TSV) format, corresponding to the 3 splits used in the article: Rei L, Pita Costa J, Zdol&scaron;ek Draksler T. Automatic Classification and Visualization of Text Data on Rare Diseases. _Journal of Personalized Medicine_. 2024; 14(5):545. https://doi.org/10.3390/jpm14050545

opencc-by-4.0May 2024View details →

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The dataset of article "Early Detection of Cognitive Impairment in End-Stage Renal Disease Patients Undergoing Hemodialysis: Insights from Resting-State Functional Connectivity Analysis"

This is a file as dataset of the article "Early Detection of Cognitive Impairment in End-Stage Renal Disease Patients Undergoing Hemodialysis: Insights from Resting-State Functional Connectivity Analysis". It includes fMRI brain imaging data of subjects included in the case group (ESRD group) and healthy control group (HC group).

opencc-by-4.0Oct 2024View details →

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GINGIVAL HYPERPLASIA AND SYSTEMIC DISEASE: A COMPLEX INTERPLAY

This study investigated the association between gingival hyperplasia and various systemic diseases and medications. Data from 1055 patients were analyzed, including those with leukemia, pregnancy, diabetes, and those taking medications known to induce gingival hyperplasia (phenytoin, cyclosporine, calcium channel blockers). Results indicated a significantly higher prevalence of gingival hyperplasia in patients with leukemia (40%, 95% CI: 30-50%) and poorly controlled diabetes (25%, 95% CI: 20-30%) compared to the control group (4%, 95% CI: 2-6%). Pregnancy also showed a statistically significant increase in gingival hyperplasia, with prevalence rising from 15% in the first trimester to 25% in the third trimester. Drug-induced gingival hyperplasia was observed in a substantial proportion of patients receiving phenytoin (35%), cyclosporine (25%), and calcium channel blockers (27%). Clinical characteristics of gingival hyperplasia varied depending on the underlying etiology, with leukemia-associated hyperplasia often presenting as severe, generalized, and friable tissue. These findings highlight the importance of considering systemic factors and medication profiles when assessing and managing gingival hyperplasia. Further research is needed to elucidate the mechanisms underlying these associations and to optimize treatment strategies.

opencc-by-4.0Oct 2024View details →

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Linked collectors and determiners for: New Zealand Fungal and Plant Disease Collection (PDD).

Natural history specimen data linked to collectors and determiners held within, "New Zealand Fungal and Plant Disease Collection (PDD)". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/ee27b1b0-3b55-11dc-8c18-b8a03c50a862">https://bionomia.net/dataset/ee27b1b0-3b55-11dc-8c18-b8a03c50a862</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/ee27b1b0-3b55-11dc-8c18-b8a03c50a862">https://gbif.org/dataset/ee27b1b0-3b55-11dc-8c18-b8a03c50a862</a>. Formatted as a Frictionless Data package.

opencc-zeroJan 2024View details →

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Identifying the Fusarium species involved in foot rot disease of beans in the UK using a combined molecular and microbiological approach

Materials and methods Fungal isolation Isolates (113) were prepared from both soil and infected plant samples that were received from the Plant Clinic at the Processors and Growers Research Organisation (PGRO). The samples were from different regions of England, United Kingdom (Table 1). <a name="_Ref165642771"></a>Table 1: The locations and number of isolates obtained for infected faba bean and soil samples used in the study. * = includes soil isolates <table> <tbody> <tr> <td> Location </td> <td> Number of isolates obtained </td> <td> Month(s) </td> </tr> <tr> <td> PGRO experimental plots </td> <td> 29* (13 soil, 16 plant) </td> <td> November 2022 </td> </tr> <tr> <td> Cambridgeshire </td> <td> 2 </td> <td> June 2023 </td> </tr> <tr> <td> Oxfordshire </td> <td> 3 </td> <td> June-July 2023 </td> </tr> <tr> <td> Durham </td> <td> 3 </td> <td> July 2023 </td> </tr> <tr> <td> Shropshire </td> <td> 4 </td> <td> July and August2023 </td> </tr> <tr> <td> Lincolnshire </td> <td> 5 </td> <td> July and August 2023 </td> </tr> <tr> <td> Northumberland </td> <td> 5 </td> <td> July and August 2023 </td> </tr> <tr> <td> Staffordshire </td> <td> 4 </td> <td> July  and August 2023 </td> </tr> <tr> <td> Suffolk </td> <td> 4 </td> <td> July 2023 </td> </tr> <tr> <td> Leicestershire </td> <td> 2 </td> <td> July 2023 </td> </tr> <tr> <td> Essex </td> <td> 4 </td> <td> July 2023 </td> </tr> <tr> <td> Norfolk </td> <td> 34 </td> <td> August 2023 </td> </tr> <tr> <td> Yorkshire </td> <td> 6 </td> <td> September 2023 </td> </tr> <tr> <td> Hampshire </td> <td> 2 </td> <td> July 2023 </td> </tr> <tr> <td> Undisclosed PGRO locations </td> <td> 6 </td> <td> Undisclosed </td> </tr> </tbody> </table>   Infected plant samples were disinfected by placing pieces of infected stems/root in 10 % sodium hypochlorite solution for 5 min. The samples were rinsed twice using sterilised distilled water and placed on sterilised filter paper to be dried for 10 min at room temperature inside a laminar flow hood. The dried samples were moved to potato dextrose agar medium (PDA) inside 9 cm diameter plastic Petri dishes. Petri dishes were incubated at 22<a name="_Hlk134433128"></a> °C with 12 h fluorescent photoperiod, <a name="_Hlk165887610"></a>and light intensity of 20-25 µMol.m-2.s-1. Once colonies had formed, clonal isolates were prepared from the colonies as follows. Approximately 1 mm2 of the colony was collected using a flame-sterilised inoculation loop and was sequentially spread onto three Petri dishes containing 2 % water agar, to dilute the inoculum gradually. The Petri dishes were incubated for 24 h as described above. The third Petri dish for each isolate was examined under a stereoscope, and one separated hypha was transferred using a flame-sterilised scalpel to another Petri dish containing PDA medium, and incubated for seven days to provide a clonal isolate. The isolates were stored for future use using two methods, for routine or long-term storage. For routine storage (months), three discs of the PDA medium containing the clonal isolate were transferred to a 2 ml microcentrifuge tube containing 1 ml of sterilised distilled water, the tube sealed with parafilm and stored at -20 °C. For long-term storage (3-4 years) the clonal isolate was plated onto a Petri dish containing many pieces of 1 cm long sterilised filter paper on PDA medium, and the colony was allowed to grow for seven days to cover the filter paper. The pieces of filter paper were removed and placed inside an empty Petri dish and dried for seven days at room temperature. The filter paper pieces were then transferred to an empty 2 ml plastic microcentrifuge tube and stored at -20 °C. Koch`s postulates were confirmed for each of the isolates by re-isolation, inoculation, and identification.   Pathogenicity testing Pathogenicity testing was conducted using susceptible faba bean seedlings (cv. Lynx) grown in test tubes in a mixture of perlite/vermiculite. The growth media was prepared by adding one volume of vermiculite (the capacity of a 1000 ml plastic beaker) to one volume of perlite inside an autoclave bag; this was mixed to ensure equal distribution of each component, and 1 litre of distilled water was added. The autoclave bag was closed and autoclaved for 20 min at 121 °C, and the mixture was transferred to fill 2/3 of the test tubes (150 x 24 mm, 1.2 ml wall; borosilicate glass 150 x 24 mm, rimless, Appleton Woods Ltd), which were then sealed with cotton wool and aluminium foil, prior to being autoclaved. Seeds were soaked in sterilized distilled water overnight and placed in 10 % sodium hypochlorite for 5 min. The seeds were washed three times with sterilised distilled water and placed on sterilised filter paper until dry. The seeds were then transferred to 9 cm petri dishes containing 1.2 % Tap Water Agar (12 g agar in 1 l of tap water, autoclaved in a 2 l conical flask), where they were allowed to germinate for four days in the incubator at 24 °C before being transferred to test tubes containing the vermiculite/perlite mixture. Following transfer, the seedlings were allowed to grow for five to seven days until they were suitable for inoculation (4-5 cm root length). The seedlings were inoculated by placing a 10 mm block of PDA medium containing a ten-day old fungal culture against the stem base. A small piece of sterilised cotton was placed around the stem to ensure adequate moisture at the inoculation site. The inoculated seedlings were incubated at 24 °C, with a 12 h photoperiod and light intensity of 20-25 µMol.m-2.s-1. Disease severity was monitored daily from 5-6 days after inoculation. Root and stem infection were scored on days 15 and 25 using a 5-point scale (Figure 2): 0 = healthy roots, no discolouration. 1 = up to 20 % root or stem base discoloured. 2 = 20-40 % root or stem base discoloured. 3 = 40-60 % root or stem base discoloured. 4 = 60-80 % root or stem base discoloured, stunting of plant. 5 = total discoloration, dead plant. DNA extraction Clonal colonies were cultured on 50 ml of Potato Dextrose Broth (PDB) medium (FORMEDIUMTM) in a 250 ml flask and incubated for seven days on a rotary shaker (22 °C with 70 RPM). The mycelium for each isolate was harvested by transferring the contents of each flask into a 50 ml falcon tube and centrifuging at 5000 RPM for 10 min. The supernatant was discarded, and the mycelium pellet stored at -20 °C. Mycelium (1 ml) was transferred to a 2 ml safe-lock microcentrifuge tube. The tubes were covered with parafilm which was pierced to allow moisture to evaporate. Samples were freeze-dried (-45 °C, 0.133 mbar) for 48 h. Freeze-dried mycelium (15 mg) was transferred to a 2 ml safe lock microcentrifuge tube containing two carbon steel ball bearings (3 mm diameter, grade 1000, SimplyBearings). The mycelium was homogenised for 4 min using a TissueLyser (Retsch MM400; 30 RPS), after which 120 µl of TNES buffer was added and the samples were homogenised again as before. Total DNA was extracted from the samples following the BOMB-Bio nucleic acid tissue DNA extraction protocol (Oberacker et al., 2019). The samples were incubated at 55 °C overnight after adding 2 µl of proteinase K and 3 µl of RNAase A. Following incubation, 240 µl of GITC lysis buffer was added, mixed and samples incubated at room temperature for 5 min. Isopropanol (480 µl) was added and, following centrifugation (5000 RPM; 5 min), 650 µl was transferred to a new tube with 200 µl of 1X BOMB-Bio magnetic bead solution (1:50 carboxylated SeraMag Speed Beads magnetic beads in TE) and mixed. The solution was placed on a magnetic rack to hold the beads with DNA bound to them in place whilst the supernatant was removed. The beads with bound DNA were washed once with isopropanol (400 µl) and twice with 80 % ethanol (400 µl). The solution was removed from the magnet, beads were allowed to dry briefly and 70 µl of nuclease free water was added to elute the DNA. The beads were removed by placing the samples back on the magnetic rack and transferring the supernatant to a new tube. The extracted DNA concentration was estimated using a Qubit 4 and 1X dsDNA High Sensitivity (HS) Assay Kit (Invitrogen) according to the manufacturer’s instructions. Polymerase Chain Reaction (PCR) DNA was amplified using PCR with three sets of primers: Internal Transcribed Spacer (ITS) primers ITS1/ITS4 (Raja et al., 2017) and two sets of Translation Elongation Factor one α primers, 1018F/1620R and EF1/EF2 (O’Donnell et al., 1998; Raja et al., 2017). Prior to PCR, the template DNA concentration was adjusted to<a name="_Hlk133674492"></a> 5 ng/μl using molecular grade water. The PCR mix <a name="_Hlk133674557"></a>contained: 12.5 µl of 2x MyTaq Red Mix (Meridian Bioscience), 3 µl of template DNA, 1 µl of each primer (10 µM) and 7.5 µl of nuclease free water to a final volume of 25 µl. The cycling conditions and sequence of each primer are given in Table 2. The PCR products were separated alongside a 1 kbp ladder (GeneRuler 1 kb Plus DNA Ladder Thermo scientific SM1331) using gel electrophoresis in a 1 % agarose gel in TAE buffer stained with GelRed® nucleic acid stain (Sigma Aldrich). Gels were visualised with a UV transilluminator (BioRad) to confirm successful amplification. <a name="_Ref162427061"></a>Table 2: The ITS (ITS1 and ITS4) and TEF1α (1018F, 1620R, EF1 and EF2) primer sequences and PCR conditions. <table> <tbody> <tr> <td> Primer </td> <td> Sequence (5’-3’) </td> <td> Initial Melt </td> <td> Melt </td> <td> Anneal </td> <td> Extension </td> <td> Final extension </td> </tr> <tr> <td> ITS1: ITS4:  (Raja et al., 2017) </td> <td> CGTAGGTGAACCTGCGG TCCTCCGCTTATTGATATGC </td> <td> 94 °C 5 min </td> <td> 94°C 30 sec </td> <td> 55 °C 1 min </td> <td> 72 °C 2 min </td> <td> 72 °C 7 min </td> </tr> <tr> <td> 35 cycles </td> </tr> <tr> <td> 1018F: 1620R: (O’Donnell et al., 1998; Raja et al., 2017) </td> <td> GAYTTCATCAAGAACATGAT GACGTTGAADCCRACRTTGTC </td> <td> 94 °C 5 min   </td> <td> 94 °C 30 sec </td> <td> Touch down 66-56 °C 1 min   </td> <td> 72 °C 1 min </td> <td> 72 °C 10 min </td> </tr> <tr> <td> 9 cycles </td> </tr> <tr> <td> 94 °C 30 sec </td> <td> 56 °C 1 min   </td> <td> 72 °C 1 min </td> </tr> <tr> <td> Remaining 26 cycles </td> </tr> <tr> <td> EF1: EF2: (O’Donnell et al., 1998) (Raja et al., 2017) </td> <td> ATGGGTAAGGARGACAAGAC GGARGTACCAGT SATCATGTT   </td> <td> 95 °C 2 min </td> <td> 95 °C 30 sec </td> <td> 54.1 °C 1 min </td> <td> 72 °C 1 min </td> <td> 72 °C 5 min </td> </tr> <tr> <td> 35 cycles </td> </tr> <tr> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> </tbody> </table>   Prior to sequencing, the PCR products were purified using solid-phase reversible immobilisation (SPRI) magnetic beads. To each PCR product, 1 X SPRI beads were added at a 1:2 ratio of PCR product to bead solution (50 µl PCR product to 100 µl SPRI beads) and the mixture incubated for 5 min at room temperature. The tubes were transferred to the magnetic plate for 5 min until the solution was clear, at which point the supernatant was discarded and the beads were washed twice with 80% ethanol for 60 s each time. Ethanol was removed and the beads held on the magnetic plate were allowed to dry for 5-10 min at room temperature. The tubes containing the dry beads were removed from the magnetic plate, and 50 µl of molecular grade nuclease free water was added to each tube, mixed and incubated for 5 min, allowing the DNA to elute. The tubes were placed back on the magnetic plate for 5 min until the solution was clear, at which point the supernatant was transferred to a new 1.5 ml microcentrifuge tube. Sanger sequencing was carried out using ITS1, ITS4 primers and EF1, EF2 primers. All sequencing was carried out by Eurofins Genomics. Following sequencing, the chromatograms obtained were trimmed and analysed using Geneious Prime (version 2023.0.4). First, low-quality bases (e.g., overlapping peaks) were trimmed from each end and the sequence upstream from that site, including the primer sequence, was deleted. The forward and reverse sequence for each sample were assembled using the de novo assemble function in Geneious at the highest sensitivity to create a consensus sequence (highest threshold quality: 60%). A basic local alignment search tool (BLAST) search was carried out for the consensus sequences using the NCBI-NR database for the ITS sequences, and, for the TEF1α sequences, the data available on the Fusarium ID database (Torres-Cruz et al., 2022). All of the TEF1α consensus sequences from all samples were subsequently aligned with the available sequences on the Fusarium ID database (Geneious global alignment with free end gaps, 65% similarity), and a phylogenetic tree was generated (genetic distance model Tamura-Nei, neighbour joining method, bootstrap with 100 replicates).

opencc-by-4.0Oct 2024View details →

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Global cellular proteo-lipidomic profiling of diverse lysosomal storage disease mutants using nMOST

<div> <div> <div> <div> Lysosomal storage diseases (LSDs) comprise ~50 monogenic disorders marked by the buildup of cellular material in lysosomes, yet systematic global molecular phenotyping of proteins and lipids is lacking. We present a nanoflow-based multi-omic single-shot technology (nMOST) workflow that quantifies HeLa cell proteomes and lipidomes from over two dozen LSD mutants. Global cross-correlation analysis between lipids and proteins identified autophagy defects, notably the accumulation of ferritinophagy substrates and receptors, especially in NPC1-/- and NPC2-/- mutants, where lysosomes accumulate cholesterol. Autophagic and endocytic cargo delivery failures correlated with elevated lyso-phosphatidylcholine species and multi-lamellar structures visualized by cryo-electron tomography. Loss of mitochondrial cristae, MICOS-complex components, and OXPHOS components rich in iron-sulfur cluster proteins in NPC2-/- cells was largely alleviated when iron was provided through the transferrin system. This study reveals how lysosomal dysfunction affects mitochondrial homeostasis and underscores nMOST as a valuable discovery tool for identifying molecular phenotypes across LSDs. </div> </div> </div> </div>

opencc-by-4.0Oct 2024View details →

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Code and data of "Uncovering disease-related multicellular pathway modules on large-scale single-cell transcriptomes with scPAFA"

Code and data to reproduce the analyses and figures presented in "Uncovering disease-related multicellular pathway modules on large-scale single-cell transcriptomes with scPAFA"

opencc-by-4.0Nov 2024View details →

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Digital Collections Data and Tracking Disease Workshop 2: Introduction and Museum Perspectives Talks

Recordings of talks by speakers in the Museum Perspectives section of our Digital Collections Data and Tracking Disease Workshop 2 at the American Society of Mammalogists Meeting in Boulder, Colorado in June of 2024. <ul> <li>Topic -- A Museum Perspective <ul> <li>Museums and Emerging Pathogens in the Americas, Joe Cook, University of New Mexico </li> <li>Museums and pathogens: Challenges, potential, and management, <a href="https://orcid.org/0000-0002-6931-6420" target="_blank" rel="noopener">Adam Ferguson</a>, Field Museum of Natural History</li> <li>The UX Side of Extended Specimen Databases, <a href="https://orcid.org/0000-0002-8775-7254" target="_blank" rel="noopener">Kelly Speer</a></li> <li>Preventing the next viral pandemic via elucidation of mammalian reservoirs, Rick White, University of North Carolina-Charlotte</li> <li>Scientific collections and public health surveillance: institutional weaknesses and perspectives from Uruguay, <a href="https://orcid.org/0000-0002-4055-9277" target="_blank" rel="noopener">Germán Botto Nuñez</a>, Universidad de la República <ul> <li>(note talk sound did not work for this presentation)</li> </ul> </li> <li>Building integrated archives for parasite and pathogen discovery <a href="https://orcid.org/0000-0002-8065-0833" target="_blank" rel="noopener">Kurt Galbreath</a>, Northern Michigan University</li> <li>The Dark Side of the Light: Fireflies, Snails, and Viromes, <a href="https://orcid.org/0000-0001-5067-3316" target="_blank" rel="noopener">Oliver Keller</a>, University of Michigan</li> </ul> </li> </ul>

opencc-by-4.0Jun 2024View details →

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Web sourced dataset for plant disease detection

The web-sourced dataset consists of plant leaf images collected from online platforms, primarily through sources like Google Images, to capture a wide range of real-world scenarios and environmental conditions. Unlike controlled laboratory datasets, these images feature diverse backgrounds, lighting variations, and different stages of plant diseases, representing how diseases appear in natural agricultural settings. The dataset includes multiple plant species and disease types, augmenting existing datasets by adding greater variability. This diversity aims to improve model robustness and generalization, enabling more accurate disease detection across varying agricultural environments.

opencc-by-4.0Nov 2024View details →

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An Analysis of Plant Disease and Their Detection

One of the biggest revolutions of modern history is the invention of agriculture for a healthier lifestyle. It significantly changed the human culture and played an important role in the development of the population and biological improvements in food production and domestication. The frequency of pests on food crops increased because environmental circumstances were changing, and diseases on crops increased rapidly. These diseases inflict catastrophic social, economic, and ecological casualties, and this extraordinary challenge is a concern for the correct and prompt detection of diseases. In this contest, technology has left its mark on the potential of farmers and is still to be exploited. As input for making the right decision, farmers need timely and credible sources of knowledge. Study into Agriculture have to be planned by improving the disease diagnostics method with the use of newer technology to enhance efficiency and quantity for agricultural production and its allied operation. In various applications of the agricultural industry, computer methodologies have been used for automation. Timely farming decisions and disease management are taken using image analysis and machinery of learning techniques in planning and creating a method for the diagnosis of diseases.

opencc-by-4.0Oct 2024View details →

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Data for "Deep learning-based model for diagnosing Alzheimer's disease and tauopathies"

Image datasets and tuned models used in the paper (Koga et al., 2021). Data.zip contains image and text files for training models. Test.zip contains 12 images from 4 patients, which are a part of the hold-out dataset images used in the paper. There are 9 CSV files, which contain the results of tau burden quantification. Python code is available at GitHub (<a href="https://github.com/Koga-MD/DL-Tauopathies">https://github.com/Koga-MD/DL-Tauopathies</a>).

opencc-by-4.0Jul 2021View details →

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VISION Invited lecture - Bariatric surgery and non-alcoholic fatty liver disease

Recording and presentation of the invited lecture that took place online on 16 June 2021 - Pantelis Antonakis, MD, PhD - Bariatric surgery and non-alcoholic fatty liver disease. Bariatric surgery is a documented solution for morbid obesity. Additionally to excess weight loss, significant improvement in comorbidities is an established benefit after bariatric operations. In recent years, non-alcoholic fatty liver disease (NAFLD) has emerged as one of these comorbidities. Herein we will review the data supporting the positive effect of bariatric surgery in patients with NAFLD.

opencc-by-4.0Jul 2021View details →

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Statistical analysis code for output from a model used to simulate foot-and-mouth disease dynamics in the United Kingdom

Epidemics can sometimes be managed through reductions of host density, such as social distancing for human diseases, reducing plant density through cultural and genetic means, and host culling for epizootics. These approaches allow for a certain density of hosts to remain within a targeted area. By contrast, total ring depopulation is often used as a management strategy for emerging infectious diseases in livestock. In this study, we explore the trade-offs of a density-based culling strategy to determine if fewer livestock farms can be culled within rings while maintaining a decrease in disease transmission. To do so, we evaluated a farm-density-based ring culling strategy to control foot-and-mouth disease (FMD) in the United Kingdom. This strategy may allow for some farms within rings around infected premises (IPs) to escape depopulation, with the aim to prevent over-culling during outbreaks. Using a spatially-explicit, stochastic, state-transition simulation algorithm originally developed by Keeling et al. 2001 to model FMD spread in the United Kingdom, we simulated this reduced-farm-density, or "target density" strategy. We modeled FMD disease spread in four counties in the UK (Aberdeenshire, Cumbria, Devon, and North Yorkshire) that have different farm demographies. We ran 740,000 simulations in a full-factorial analysis of epidemic impact measurements (i.e. culled animals, culled farms, epidemic length) and cull strategy parameters (i.e. target farm density, daily farm cull capacity, cull radius). We found that all of the cull strategy parameters were drivers of epidemic impact. We found that outbreaks in Cumbria had higher epidemic impacts and were more likely to take off compared with other counties with more outbreaks being likely to take off in Cumbria. Most importantly, in all counties, our proposed target density strategy was more effective at combatting FMD compared with traditional 'total ring depopulation' when considering average culled animals and culled farms. The differences in epidemic impact between the counties are likely driven by farm demography, especially differences in cattle and farm density. This target density strategy can be applied to many different systems, including other livestock and agricultural systems, to reduce host density as opposed to over-culling hosts.

opencc-zeroAug 2021View details →

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Dateset related to article "Cytokines as potential biomarkers of disease clinical course in muscular dystrophies "

This database includes a comprehensive profile of circulating pro- and anti-inflammatory molecules (cytokines, chemokines and growth factors) obtained from a group of 53 patients with muscular laminopathy, 10 with non-muscular laminopathy, 22 with other muscular disorders and 35 healthy controls. Data obtained by Luminex multiple immune-assay identify TGF-b2, IL-17 and G-CSF as potential biomarkers in discriminating  between muscle-related laminopathy and healthy subjects. The different expression  of IL-1b, IL-4 and IL-8 among the different forms of laminopathy provides a new hint for the understanding of the pathogenic mechanisms underlying the diverse phenotypes caused by LMNA mutations.

opencc-by-4.0Aug 2021View details →

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An Open-access Database for the Evaluation of Cardio-mechanical Signals from Patients with Valvular Heart Diseases

This dataset is for the paper "An Open-access Database for the Evaluation of Cardio-mechanical Signals from Patients with Valvular Heart Diseases" published to Frontiers in Physiology. Please cite "Yang C, Fan F, Aranoff N, Green P, Li Y, Liu C and Tavassolian N (2021) An Open-Access Database for the Evaluation of Cardio-Mechanical Signals From Patients With Valvular Heart Diseases. Front. Physiol. 12:750221. doi: 10.3389/fphys.2021.750221" when using this database. The archive comprises SCG and GCG recordings sourced from and processed at multiple sites worldwide, including Columbia University Medical Center and Stevens Institute of Technology in the USA, as well as Southeast University, Nanjing Medical University, and the first affiliated hospital of Nanjing Medical University in China. It includes electrocardiogram (ECG), SCG, and GCG recordings collected from 100 patients with various conditions of valvular heart diseases, such as aortic and mitral stenosis. The recordings were collected from clinical environments with the same types of wearable sensor patch. Besides the raw recordings of ECG, SCG and GCG signals, a set of hand-corrected fiducial point annotations is provided by manually checking the results of the annotated algorithm. The database also includes relevant echocardiogram parameters associated with each subject such as ejection fraction, valve area, and mean gradient pressure.

opencc-by-4.0Aug 2021View details →

zenodo40/100

Data files for manuscript "Prevalence of hereditary tubulointerstitial kidney diseases in the German Chronic Kidney Disease study"

#2021-09-19 #Summary This ZIP-file contains the Excel files used for all analyses for the manuscript "Prevalence of hereditary tubulointerstitial kidney diseases in the German Chronic Kidney Disease study". #File structure README.txt                                            This README file. File S1 ("FileS1_GCKD-ADTKD.cohort.xlsx")            Cohort characteristics, sequencing quality parameters and fingerprinting results. File S2 ("FileS2_GCKD-ADTKD.content.xlsx")            Sequencing panel design/ content with information on gene domains used for Figure 2. File S3 ("FileS3_GCKD-ADTKD.variants.xlsx")            Information on small variants, CNVs and MUC1 analyses (SNaPshot and adVNTR). File S4 ("FileS4_GCKD-ADTKD.simulation.xlsx")        Curated variant and individual data from the Groopman study with results of the simulation for Figure 4. #Files and checksums 2D6184BC145987D3EE2E0DC6873DDDDB    ./README.txt 10EE4C3C9D9ED6417647F26A09583820    ./FileS1_GCKD-ADTKD.cohort.xlsx 9F95661845215FB7875EB053F887AB36    ./FileS2_GCKD-ADTKD.content.xlsx 2AC19FBC6103CB48905F64716428AE5B    ./FileS3_GCKD-ADTKD.variants.xlsx 2D6184BC145987D3EE2E0DC6873DDDDB    ./FileS4_GCKD-ADTKD.simulation.xlsx

opencc-by-4.0Sep 2021View details →

dryad40/100

Single-synapse analyses of Alzheimer's disease implicate pathologic tau, DJ1, CD47, and ApoE

Synaptic molecular characterization is limited for Alzheimer's disease (AD). Our newly invented mass cytometry-based method, Synaptometry by Time of Flight (SynTOF), was used to measure 38 antibody probes in approximately 17 million single-synapse events from human brains without pathologic change or with pure AD or Lewy body disease (LBD), non-human primates (NHP), and PS/APP mice. Synaptic molecular integrity in humans and NHP was similar. Although not detected in human synapses, Aβ was in PS/APP mice single-synapse events. Clustering and pattern identification of human synapses showed expected disease-specific differences, like increased hippocampal pathologic tau in AD and reduced caudate dopamine transporter in LBD, and revealed novel findings including increased hippocampal CD47 and lowered DJ1 in AD and higher ApoE in AD with dementia. Our results were independently supported by multiplex ion beam imaging of intact tissue. This highlights the higher depth and breadth of insight on neurodegenerative diseases obtainable through SynTOF.

opencc-zeroSep 2021View details →

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Allen Brain Atlas

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neuroscienceopenDocumentation, web resources, and API references are available online.

Last verified 2026-04-30Open record

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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.

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Last verified 2026-04-30Open record

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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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behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.

Last verified 2026-04-29Open record

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.

openneuro

neuroscienceopenPublished datasets are available on demand over the internet.

Last verified 2026-04-29Open record

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Data files for manuscript "Prevalence of hereditary tubulointerstitial kidney diseases in the German Chronic Kidney Disease study"

Single-synapse analyses of Alzheimer's disease implicate pathologic tau, DJ1, CD47, and ApoE

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Allen Brain Atlas

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