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Polyester or epoxy: assessing embedding product efficacy in paleohistological methods.

ABSTRACT: Histological examination of bone microstructure provides insight into extant and extinct vertebrate physiology. Fossil specimens sampled for histological examination are typically first embedded in an inexpensive polyester resin and then cut into thin sections, mounted on slides, and polished for viewing. Modern undecalcified bone is chemically processed prior to embedding in plastic resin, sectioning, mounting, and polishing. Conversely, small fossil material and modern undecalcified bone are typically embedded in higher priced epoxy resin because these specimen types require final sections near or below 100 µm thick. Anecdotal evidence suggests thin sections made of polyester resin embedded material polished thinner than 100 µm increases likelihood of sample peeling, material loss, and is unsuitable for modern tissue and small fossil material. To test this assertion, a sample of modern bones and fossil bones, teeth, and scales were embedded in either polyester resin or epoxy resin. Embedded specimens were sectioned and mounted following standard published protocol. Thin sections were ground on a lapidary wheel using decreasing grit sizes until tissue microstructure was completely discernible when viewed under a polarizing light microscope. Additionally, eight prepared thin sections (four from polyester resin embedded specimens and four from epoxy resin embedded specimens) were continuously ground on a lapidary wheel using 600 grit carbide paper until peeling occurred or material integrity was lost. Slide thickness when peeling occurred was measured for comparing slide thickness when specimen integrity was lost between the two resin types. Final slide thickness ranged from 38 µm to 247 µm when tissue was identifiable using a polarizing microscope. Finished slide thickness varied between resin types despite similar tissue visibility. However, finished slide thickness appears more dependent on hard tissue composition than resin type. Additionally, we did not find a difference of slide thickness when material was lost between resin types. The results of this preliminary study suggest that polyester resins can be used for embedding undecalcified modern hard tissues and fossilized hard tissues without loss of tissue visibility or material integrity, at least in the short term.

SUBMITTER: Heck CT

PROVIDER: S-EPMC7747682 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Polyester or epoxy: assessing embedding product efficacy in paleohistological methods.

Heck Christian T CT Volkmann Gwyneth G Woodward Holly N HN

PeerJ 20201215

Histological examination of bone microstructure provides insight into extant and extinct vertebrate physiology. Fossil specimens sampled for histological examination are typically first embedded in an inexpensive polyester resin and then cut into thin sections, mounted on slides, and polished for viewing. Modern undecalcified bone is chemically processed prior to embedding in plastic resin, sectioning, mounting, and polishing. Conversely, small fossil material and modern undecalcified bone are t ...[more]

PMID: 33362969

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Project description:Motivation: Graph embedding learning that aims to automatically learn low-dimensional node representations, has drawn increasing attention in recent years. To date, most recent graph embedding methods are evaluated on social and information networks and are not comprehensively studied on biomedical networks under systematic experiments and analyses. On the other hand, for a variety of biomedical network analysis tasks, traditional techniques such as matrix factorization (which can be seen as a type of graph embedding methods) have shown promising results, and hence there is a need to systematically evaluate the more recent graph embedding methods (e.g. random walk-based and neural network-based) in terms of their usability and potential to further the state-of-the-art.Results: We select 11 representative graph embedding methods and conduct a systematic comparison on 3 important biomedical link prediction tasks: drug-disease association (DDA) prediction, drug-drug interaction (DDI) prediction, protein-protein interaction (PPI) prediction; and 2 node classification tasks: medical term semantic type classification, protein function prediction. Our experimental results demonstrate that the recent graph embedding methods achieve promising results and deserve more attention in the future biomedical graph analysis. Compared with three state-of-the-art methods for DDAs, DDIs and protein function predictions, the recent graph embedding methods achieve competitive performance without using any biological features and the learned embeddings can be treated as complementary representations for the biological features. By summarizing the experimental results, we provide general guidelines for properly selecting graph embedding methods and setting their hyper-parameters for different biomedical tasks.Availability and implementation: As part of our contributions in the paper, we develop an easy-to-use Python package with detailed instructions, BioNEV, available at: https://github.com/xiangyue9607/BioNEV, including all source code and datasets, to facilitate studying various graph embedding methods on biomedical tasks.Supplementary information: Supplementary data are available at Bioinformatics online.

Project description:Purpose: Identical predicted small interfering RNA (siRNA) sequences targeting Apolipoprotein B100 (siApoB) were embedded in shRNA (shApoB) or miRNA (miApoB) scaffolds and a direct compariso of the possible aspecific off-target effects in vivo was performed. Next generation sequencing (NGS) of small RNAs originating from shApoB- or miApoB-transfected cells revealed substantial differences in processing, resulting in different siApoB length, 5M-bM-^@M-^Y and 3M-bM-^@M-^Y cleavage sites and abundance of the guide or passenger strands. Methods [1]: Total liver RNA sequencing libraries for the Illumina sequencing platform were generated using high-quality total RNA as input and the Illumina TrueSeq RNA v2 Sample preparation kit according to the manufacturerM-bM-^@M-^Ys protocol. Each read file (sample), in the FASTQ format, was individually aligned against the mouse reference genome (15 May 2012 NCBI build 38.1) using CLC Bio-Genomic Workbench and the expression abundance for each gene (RPKM) was calculated according to Montazavi et al. Result [1]s: Based on our previous observations that shApoB and miApoB are differentially processed and that miApoB has a different passenger, we checked for possible aspecific off-target effects in vivo. NGS liver transcriptome analysis was performed 8 weeks p.i. for animals injected with 1x1011 gc AAV encoding shScr, shApoB, miScr and miApoB. We investigated whether shApoB and miApoB processing differences translate into differences in gene expression in injected animals. A total number of 266 genes were significantly changing (p <0,05) in miApoB-injected mice compared to miScr. Additionally 106 genes were found to be significantly up or down-regulated in the shApoB mice compared to shScr. Off-target predictions using Smith-Waterman algorithm for the most abundant guide and passenger strand variants were performed to investigate if any of the observed changes results from aspecific interactions. None of the changing genes had predicted targets for the guide or passenger strands of shApoB or miApoB. Conclusions [1]: An important observation is that none of the changes in gene expression in AAV-miApoB and AAV-shApoB can be explained by possible aspecific down-regulation of non-target transcripts. Methods [2]: For NGS analysis cells were transfected with 4 M-BM-5g shApoB- or miApoB-expression plasmids using Lipofectamine 2000 reagent and total RNA was isolated from cells 48 hr post-transfection using Trizol (Invitrogen, Carlsbad, CA) according to the manufacturerM-bM-^@M-^Ys protocol. Total RNA sequencing libraries for the Illumina sequencing platform were generated using high-quality total RNA as input and the Illumina TrueSeq RNA v2 Sample preparation kit according to the manufacturerM-bM-^@M-^Ys protocol. The NGS small RNA raw data set was analyzed using the CLC_bio genomic workbench (CLC Bio, Aarhus, Denmark). The obtained reads were adaptor-trimmed, which decreased the average read size from ~36bp to ~25bp. The custom adapter sequenced used for trimming all the bases extending 5M-bM-^@M-^Y was: GTGACTGGAGTTCC-TTGGCACCCGAGAATTCCA. All reads containing ambiguity N symbols, reads shorter than 15 nt, longer than 55 nt in length and reads represented less than 10 times were discarded. Next, both data sets from shApoB and miApoB samples were grouped based on the match to the reference sequence and the obtained unique small RNAs were aligned to the sequence of pre-miApoB: GATCCTGGAGGCTTGC-TGAAGGCTGTATGCTGATGGACAGGTCAATCAATCTTGTTTTGGCCACTGACTGACAAGATTGAGACCTGTCCATCAGGACACAAGGCCTGTTACTAGCACTCACATGGAACAAATGGCCCAGATCTGGCCGCAG or shApoB: GATCCCCGATTGATTGACCTGTCCATTTCAAGAGAATGGACAGGTCAATCAATC-TTTTTCAGCTT sequence, respectively. To relatively represent the expression counts for the small RNAs obtained in the experiment, reads per million (rpm) or percentage of reads based on the total number of reads matching the reference shApoB or miApoB sequence were calculated Results [2]: The small RNAs were aligned against their reference sequence resulting in 541.939 reads matching shApoB and 1.525.211 reads matching miApoB (Fig S1 and S2). Analysis of the length distribution of the reads indicated that siApoB guide strand originating from shApoB ranged between 19 and 23 nt, with the most abundant one being 21 nt-long. Surprisingly, siApoB guide from miApoB scaffold ranged from 23 to 25 nt with the 24 nt-long strand being the predominant variant. This finding was rather unexpected considering that the predicted guide strand of siApoB was 21 nt long for both shApoB and miApoB scaffolds. Analysis of the processed 5M-bM-^@M-^Y ends of the siApoB guide strand indicated that most of the reads matched position +1 relative to the predicted cleavage site for shApoB, while all the reads matched position 0 for miApoB. The 3M-bM-^@M-^Y ends of the siApoB guide strand had a more heterogeneous pattern and ranged from -1 to +3 for shApoB and +1 to +4 for miApoB. Next, we looked at the sequence distribution and percentage of reads for both the guide and passenger siApoB strands originating from the shApoB and miApoB scaffolds. A substantial difference between the two is that the guide from shApoB is in the 3M-bM-^@M-^Y arm and hence Dicer or other endonuclease defines the cleavage position while the guide is present in the 5M-bM-^@M-^Y arm of miApoB, where Drosha defines the cleavage. Thus, defining the length and exact cleavage position for the guide and passenger strands is very important since even single nucleotide differences may result in significant changes in the predicted targets of the siRNAs. Moreover, the passenger siRNA* strand, if not degraded efficiently, may bind to unanticipated targets and cause off-target effects. As expected, 44.4% of the reads originating from shApoB matched the siApoB guide strand but processing was shifted at position +1 (Fig. 2d, upper panel). Surprisingly only 12.1% of the reads matched perfectly the predicted siApoB guide strand of 21 nt and starting at position 0. The reads matching the passenger siApoB* strand were represented in much lower percentage with the predominant one being only 5.3%. Analysis of the guide strand from the siApoB reads originating from the miApoB scaffold indicated that they all started at the predicted cleavage site. Surprisingly, the predominant, 22.3% of reads were 24 nt-long. Furthermore 5.1% reads were 23 nt- and 1.9% were 25 nt-long. A substantial number of 62% of the reads was found matching the passenger siApoB* strand and ranged between 20 and 22 nt in length. In conclusion, both shApoB and miApoB scaffolds did not yield the predicted siApoB guide or siApoB* passenger sequences after processing from the cellular RNAi machinery. The guide from miApoB was cleaved much more precisely by Drosha at its 5M-bM-^@M-^Y end compared to shApoB that gave more heterogeneous pools of sequences following processing. Conclusions[2]: An unexpected discovery in the current study was that siRNA processing by the cellular RNAi machinery did not follow the generally accepted and described cleavage sites for both molecules shApoB and miApoB siApoB guide strand originating from the shApoB scaffold was more heterogeneous in cleavage sites and length compared to the product originating from the miApoB scaffold. Most likely, differential cleavage mechanism defined the heterogeneity in the guide and passenger strands. Additionally, shRNAs with 19 bp stem or less are not necessarily recognized by Dicer and maybe be processed differently. The heterogeneity seen with the shApoB can also be explained by the potential for 2 or 3 uridines to be added following termination of pol III transcription. The main pool of guide sequences originating from miApoB was 24 nt-long although we used the scaffold of cellular pri-mir-155 that produces a 23 nt mature miRNA. However, a 24 nt-long siApoB sequence did not compromise efficacy because when placed in the miApoB scaffold, the ApoB target sequence was extended at the 3M-bM-^@M-^Y end with 4 nt until the loop. Another important observation is that the siApoB* Liver mRNA profiles of C57BL/6 9 weeks after intravenous AAV injection of 1x1011 gc per animal (~4x1012 gc/kg) of AAV-shRNA, AAV-miRNA or PBS via the tail vein. Next Generation Sequencing on Illumina platform

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Polyester or epoxy: assessing embedding product efficacy in paleohistological methods.

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Polyester or epoxy: assessing embedding product efficacy in paleohistological methods.

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