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Figure 4. A - Sentinel 2 in Perception of Amazonian fishers regarding environmental changes as causes of drastic events of fish mortality

Figure 4. A - Sentinel 2 satellite image of Lago do Rei on 20th November 2018. B - Sentinel 2 satellite image of the Lago do Rei on 20th June 2018. C - Sentinel 2 satellite image of the Lago do Rei on 15th November 2019. D - Sentinel 2 satellite image of Lago do Rei on 6th January 2020.

Figure 2. A in Perception of Amazonian fishers regarding environmental changes as causes of drastic events of fish mortality

Figure 2. A biplot is showing the years by the number of days with river level below 18 meters and the amplitude (meters) of the annual flood pulse.

Figure 5 in Perception of Amazonian fishers regarding environmental changes as causes of drastic events of fish mortality

Figure 5. Relationship between the river level, measured in the Port of Manaus – Station 14990000, and the Oceanic Niño Index (ONI), from 2009 to 2020, taking as reference the level of disconnection between Lago do Rei and the Amazon River.

Figure 3 in Perception of Amazonian fishers regarding environmental changes as causes of drastic events of fish mortality

Figure 3. Analysis of the water surface of Lago do Rei using the modified normalized difference water index for the years 2015 to 2020.

opencc-by-4.0Sep 2015View details →

Fig. 1 in Mortality and food consumption in Spodoptera frugiperda (Lepidoptera: Noctuidae) larvae treated with spinosad alone or in mixtures with a nucleopolyhedrovirus

Fig. 1. Percentage (mean ± SE) of leaf area consumed per surviving Spodoptera frugiperda 3rd instar feeding either on untreated maize-leaf pieces or on maizeleaf pieces treated with spinosad (mg/L). Mortality was recorded at 72 h afer treatment. Different letters above the error bars indicate statistically significant differences based on the Kruskall-Wallis test (P <0.05).

Fig. 6 in RNA interference mediated serine protease gene (Spbtry1) knockdown affects growth and mortality in the soybean pod borer (Lepidoptera: Olethreutidae)

Fig. 6. The mortality of the larvae feed on an artficial diet with added dsRNA. (*Student's t-test, n = 3, P <0.05; **Student's t-test, n = 3, P <0.01).

Fig. 4 in RNA interference mediated serine protease gene (Spbtry1) knockdown affects growth and mortality in the soybean pod borer (Lepidoptera: Olethreutidae)

Fig. 4. Relatve trypsin gene (Spbtry1) expression levels as determined by qPCR at different tme points. Actn was used as an internal reference gene. (*Student's t-test, n = 3, P <0.05; **Student's t-test, n = 3, P <0.01).

Fig. 5 in RNA interference mediated serine protease gene (Spbtry1) knockdown affects growth and mortality in the soybean pod borer (Lepidoptera: Olethreutidae)

Fig. 5. Effect of Spbtry1 RNAi on Leguminivora glycinivorella larval development. (A) The body weight of larvae fed on an artficial diet with added dsRNA at different tme points. (B) Pictures of the larvae showing reduced body size and developmental stage afer 15 days on an artficial diet with added dsRNA. (*Student's t-test, n = 3, P <0.05; **Student's t-test, n = 3, P <0.01).

Fig. 3. A in RNA interference mediated serine protease gene (Spbtry1) knockdown affects growth and mortality in the soybean pod borer (Lepidoptera: Olethreutidae)

Fig. 3. A) Relatve Spbtry1 gene expression levels was determined by qPCR (histograms) and RT-PCR (gel pictures) in the synganglion (SY), cutcle (CU), salivary (SA), midgut (MG), ovary (OV), tests (TE), and fat body (FT) in the 3rd instar soybean pod borer larvae. Actn was used as an internal reference gene. (B) Relatve trypsin gene (Spbtry1) expression levels as determined by qPCR (histograms) and RT-PCR (gel pictures) in soybean pod borer eggs (EG), 1st (N1), 2nd (N2), 3rd (N3), 4th (N4) instar larvae and pupae (PU), and adults (AD). Actn was used as an internal reference gene. Relatve Spbtry1 gene expression was analyzed by MJ Optcon Monitor Sofware Version 3.1.

Fig. 2 in RNA interference mediated serine protease gene (Spbtry1) knockdown affects growth and mortality in the soybean pod borer (Lepidoptera: Olethreutidae)

Fig. 2. Phylogenetc tree analysis of Spbtry1 and 13 homologues of other lepidopteran trypsin- and chymotrypsin-like serine proteases. The phylogenetc tree analysis was performed using the neighbor-joining algorithm to estmate evolutonary distances in MEGA 6.method at a gap penalty of 10, a gap length penalty of 0.2, and a bootstrap value of 1,000 iteratons.

opencc-by-4.0Jul 2024View details →

NCHS mortality data 2014-2022

This is a database (parquet format) containing publicly available multiple cause mortality data from the US (CDC/NCHS) for 2014-2022. Not all variables are included on this export. Please see below for restrictions on the use of these data imposed by NCHS. You can use the arrow package in R to open the file. See here for example analysis; https://github.com/DanWeinberger/pneumococcal_mortality/blob/main/analysis_nongeo.Rmd . For instance, save this file in a folder called "parquet3":   library(arrow) library(dplyr) pneumo.deaths.in <-  open_dataset("R:/parquet3", format = "parquet")  %>% #open the dataset   filter(grepl("J13|A39|J181|A403|B953|G001", all_icd)) %>% #filter to records that have the selected ICD codes  collect()  #call the dataset into memory. Note you should do any operations you canbefore calling 'collect()" due to memory issues   The variables included are named: (see full dictionary:https://www.cdc.gov/nchs/nvss/mortality_public_use_data.htm) year: Calendar year of death month: Calendar month of death age_detail_number: number indicating year or part of year; can't be interpreted itself here. see agey variable instead sex: M/F place_of_death: Place of Death and Decedent’s Status Place of Death and Decedent’s Status 1 ... Hospital, Clinic or Medical Center  - Inpatient 2 ... Hospital, Clinic or Medical Center  - Outpatient or admitted to Emergency Room 3 ... Hospital, Clinic or Medical Center  - Dead on Arrival 4 ... Decedent’s home 5 ... Hospice facility 6 ... Nursing home/long term care 7 ... Other 9 ... Place of death unknown  all_icd: Cause of death coded as ICD10 codes. ICD1-ICD21 pasted into a single string, with separation of codes by an underscore  hisp_recode: 0=Non-Hispanic; 1=Hispanic; 999= Not specified race_recode: race coding prior to 2018 (reconciled in race_recode_new) race_recode_alt:  race coding after 2018 (reconciled in race_recode_new) race_recode_new:   1='White'   2= 'Black'   3='Hispanic'   4='American Indian'   5='Asian/Pacific Islanders' agey:   age in years (or partial years for kids <12months)     https://www.cdc.gov/nchs/data_access/restrictions.htm Please Read Carefully Before Using NCHS Public Use Survey Data The National Center for Health Statistics (NCHS), Centers for Disease Control and Prevention (CDC), conducts statistical and epidemiological activities under the authority granted by the Public Health Service Act (42 U.S.C. § 242k). NCHS survey data are protected by Federal confidentiality laws including Section 308(d) Public Health Service Act [42 U.S.C. 242m(d)] and the Confidential Information Protection and Statistical Efficiency Act or CIPSEA [Pub. L. No. 115-435, 132 Stat. 5529 § 302]. These confidentiality laws state the data collected by NCHS may be used only for statistical reporting and analysis. Any effort to determine the identity of individuals and establishments violates the assurances of confidentiality provided by federal law.   Terms and Conditions NCHS does all it can to assure that the identity of individuals and establishments cannot be disclosed. All direct identifiers, as well as any characteristics that might lead to identification, are omitted from the dataset. Any intentional identification or disclosure of an individual or establishment violates the assurances of confidentiality given to the providers of the information. Therefore, users will: <ol> <li>Use the data in this dataset for statistical reporting and analysis only.</li> </ol> <ol> <li>Make no attempt to learn the identity of any person or establishment included in these data.</li> </ol> <ol> <li>Not link this dataset with individually identifiable data from other NCHS or non-NCHS datasets.</li> </ol> <ol> <li>Not engage in any efforts to assess disclosure methodologies applied to protect individuals and establishments or any research on methods of re-identification of individuals and establishments.</li> </ol> By using these data you signify your agreement to comply with the above-stated statutorily based requirements.   Sanctions for Violating NCHS Data Use Agreement Willfully disclosing any information that could identify a person or establishment in any manner to a person or agency not entitled to receive it, shall be guilty of a class E felony and imprisoned for not more than 5 years, or fined not more than $250,000, or both.

opencc-by-4.0Nov 2018View details →

Fig. 2 in Cetacean mortality along the Bulgarian Black Sea Coast during 2017

Fig. 2. Distribution of recorded cetacean strandings along the (a) North Bulgarian coast and (b) South Bulgarian coast.

opencc-by-4.0Nov 2018View details →

Fig. 1 in Cetacean mortality along the Bulgarian Black Sea Coast during 2017

Fig. 1. Percentage distribution (a), timing (b) and location (c) of the stranded cetaceans along Bulgarian Black Sea Coast during 2017.

opencc-by-4.0Nov 2018View details →

Fig. 3 in Cetacean mortality along the Bulgarian Black Sea Coast during 2017

Fig. 3. Distribution frequency of different stages of decomposition of the stranded cetaceans by species (Tt - Tursiops truncatus ponticus, Pp - Phocoena phocoena relicta, Dd - Delphinus delphis ponticus, UI – Unidentified). Stage 1 – alive; stage 2 - fresh corpse; stage 3 - decayed, but the organs are mostly preserved; stage 4 - the organs could not be identified; stage 5 - mummified animal parts/a skeleton and its parts.

Fig. 5 in A retrospective study of Babesia macropus associated with morbidity and mortality in eastern grey kangaroos (Macropus giganteus) and agile wallabies (Macropus agilis)

Fig. 5. Phylogenetic tree of heat shock protein 70 (hsp70) gene sequences of eastern grey kangaroo and agile wallaby Babesia and other piroplasm hsp70 sequences in the GenBank nucleotide database. For each sequence, the GenBank GI number is followed by the species name. The representative Babesia isolates from eastern grey kangaroos and an agile wallaby in this study are shown with a - and a ♦ respectively. The evolutionary history was inferred using the Maximum Likelihood method based on the TamuraNei model (Tamura and Nei, 1993). The tree with the highest log likelihood (−6290.3774) is shown. Initial tree for the heuristic search was obtained automatically as follows. When the number of common sites was <100 or less than one fourth of the total number of sites, the maximum parsimony method was used; otherwise, BIONJ method with MCL distance matrix was used. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. The scale bar represents the number of substitutions per nucleotide. All positions containing gaps and missing data were eliminated. There are limited data available on this locus within the public data repositories and as such there is some lack of consistency with the 18S ribosomal RNA tree.

Fig. 4 in A retrospective study of Babesia macropus associated with morbidity and mortality in eastern grey kangaroos (Macropus giganteus) and agile wallabies (Macropus agilis)

Fig. 4. Phylogenetic tree of 18S ribosomal RNA (18S rRNA) gene sequences of eastern grey kangaroo and agile wallaby Babesia and other piroplasms that are in the GenBank nucleotide database. For each sequence, the GenBank GI number is followed by the species name. The representative Babesia isolates from eastern grey kangaroos and an agile wallaby in this study are shown with a - and a ♦ respectively. Evolutionary history was inferred using the Maximum Likelihood method based on the Tamura 3-parameter model. The tree with the highest log likelihood (−1820.5242) is shown. Initial tree for the heuristic search was obtained automatically as follows. When the number of common sites was <100 or less than one fourth of the total number of sites, the maximum parsimony method was used; otherwise, BIONJ method with MCL distance matrix was used. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. The scale bar represents the number of substitutions per nucleotide. All positions containing gaps and missing data were eliminated. Evolutionary analyses were conducted in MEGA6 (Tamura et al., 2011).

Fig. 1 in A retrospective study of Babesia macropus associated with morbidity and mortality in eastern grey kangaroos (Macropus giganteus) and agile wallabies (Macropus agilis)

Fig. 1. Map showing the distribution of the 38 cases of Babesia infection in eastern grey kangaroos in coastal New South Wales and southeastern Queensland over the period 1995–2013. Insert also shows the two locations of the three cases identified in agile wallabies in northern Queensland in 2009 and 2013. The locations of cases were converted to GPS coordinates and mapped using GPS Visualizer on 21/05/2014 (www.gpsvisualizer.com).

Fig. 3 in A retrospective study of Babesia macropus associated with morbidity and mortality in eastern grey kangaroos (Macropus giganteus) and agile wallabies (Macropus agilis)

Fig. 3. Transmission electron micrographs showing the intravascular location and structure of Babesia organisms in the kidney and brain of eastern grey kangaroos. (A) Kidney, the cytoplasm of two adjacent erythrocytes contains Babesia merozoites (arrows) with a membrane-bound nucleus (N) and cytoplasm containing polymorphic vacuoles and some electron dense particles (C) (scale bar = 1.0 μm). (B) Brain, adjacent to an intact erythrocyte and the nucleus of an endothelial cell is a cluster of extraerythrocytic Babesia organisms containing electron dense micronemes and developing pellicles (arrows) (scale bar = 2.0 μm). (C) Brain, within the capillary lumen is a cluster of eight or nine extraerythrocytic organisms (thick arrow) and a distorted erythrocyte (thin arrow) containing four intracytoplasmic parasites (scale bar = 5.0 μm).

Fig. 2 in A retrospective study of Babesia macropus associated with morbidity and mortality in eastern grey kangaroos (Macropus giganteus) and agile wallabies (Macropus agilis)

Fig. 2. Photomicrographs showing the forms of Babesia seen in cytological preparations and tissue sections in macropods. (A) Agile wallaby. Giemsa stained peripheral blood smear showing extraerythrocytic zoites (thin arrow) and merozoites (thick arrow) within an intact erythrocyte. (B) Eastern grey kangaroo. Diff-Quik-stained renal impression smear demonstrating 2 or 4 merozoites within intact erythrocytes (thick arrows) and clusters of extraerythrocytic zoites (thin arrows). (C) Eastern grey kangaroo. DiffQuik-stained brain squash preparation showing large clusters of intravascular zoites (arrows). (D) Eastern grey kangaroo. H&E stained section of kidney glomerulus showing merozoites within intact erythrocytes (thick arrows) and as large extraerythrocytic clusters of zoites (thin arrows). All scale bars = 20 μm.