Three-Dimensional Printing Hollow Polymer Template-Mediated Graphene Lattices with Tailorable Architectures and Multifunctional Properties

It is a significant challenge to concurrently achieve scalable fabrication of graphene aerogels with three-dimensional (3D) tailorable architectures (<i>e.g.,</i> lattice structure) and controllable manipulation of microstructures on the multiscale. Herein, we highlight 3D graphene lattices (GLs) with complex engineering architectures that were delicately designed and manufactured <i><i>via</i></i> 3D stereolithography printed hollow polymer template-mediated hydrothermal process coupled with freeze-drying strategies. The resulting GLs with overhang beams and columns show a 3D geometric configuration with hollow-carved features at the macroscale, while the construction elements of graphene cellular on the microscale exhibit a well-ordered and honeycomb-like microstructure with high porosity. These GLs demonstrate multifunctional properties with robust structure, high electrical conductivity, low thermal conductivity, and superior absorption capacitance of organic solvents. Moreover, the GLs were utilized as a subtle sensor for the fast detection of chemical agents. Aforementioned superior properties of GLs confirm that the combination of 3D tailorable manipulation and self-organization design of structures on the multiscale is an effective strategy for the scalable fabrication of advanced multifunctional graphene monoliths, suggesting their promising applications as chemical detection sensors, environmental remediation absorbers, conductive electrodes, and engineering metamaterials

Characterization of the Altered Gene Expression Profile in Early Porcine Embryos Generated from Parthenogenesis and Somatic Cell Chromatin Transfer

<div><p>The <i>in vitro</i> production of early porcine embryos is of particular scientific and economic interest. In general, embryos produced from <i>in vitro</i> Assisted Reproductive Technologies (ART) manipulations, such as somatic cell chromatin transfer (CT) and parthenogenetic activation (PA), are less developmentally competent than <i>in vivo</i>–derived embryos. The mechanisms underlying the deficiencies of embryos generated from PA and CT have not been completely understood. To characterize the altered genes and gene networks in embryos generated from CT and PA, comparative transcriptomic analyses of <i>in vivo</i> (IVV) expanded blastocysts (XB), IVV hatched blastocyst (HB), PA XB, PA HB, and CT HB were performed using a custom microarray platform enriched for genes expressed during early embryonic development. Differential expressions of 1492 and 103 genes were identified in PA and CT HB, respectively, in comparison with IVV HB. The “eIF2 signalling”, “mitochondrial dysfunction”, “regulation of eIF4 and p70S6K signalling”, “protein ubiquitination”, and “mTOR signalling” pathways were down-regulated in PA HB. Dysregulation of notch signalling–associated genes were observed in both PA and CT HB. TP53 was predicted to be activated in both PA and CT HB, as 136 and 23 regulation targets of TP53 showed significant differential expression in PA and CT HB, respectively, in comparison with IVV HB. In addition, dysregulations of several critical pluripotency, trophoblast development, and implantation-associated genes (<i>NANOG</i>, <i>GATA2</i>, <i>KRT8</i>, <i>LGMN</i>, and <i>DPP4</i>) were observed in PA HB during the blastocyst hatching process. The critical genes that were observed to be dysregulated in CT and PA embryos could be indicative of underlying developmental deficiencies of embryos produced from these technologies.</p></div

Altered biological function categories in PA and CT-derived HB.

<p>Bar chart shows the significantly altered biological function categories in IPA biological function (bio-function) analysis. Major Y axis on the left shows the number of differentially expressed genes that involved in the biological function category. Secondary Y axis on the right shows the significance (-log (B-H P-value)) of the altered biological function category. The orange line shows the significance threshold of cut off of -log (B-H P-value = 0.05).</p

Model choice and performance of the ABC analysis.

*<p>P(SC2) is the proportion of pseudo-observed simulated datasets using each competing scenario (SC1 to SC3) for which SC2 was selected because it had the highest posterior probability.</p>‡<p>For SC1 and SC3, P(SC2) represents an empirical estimate of the model-specific type II error rate (here, 2.8%+9.4% = 12.2%).</p>§<p>For SC2, 1 − P(SC2) provides an empirical estimate of the type I error rate (here, 15.8%).</p

Details from the 19 sampled populations.

<p>Lat and Long represent latitude (north) and longitude (east), respectively.</p><p>An *indicates that the 10 STR genotyping was performed in this study.</p

Results of PCA.

<p>Principal coordinate analyses (PCA) were performed according to A.) <i>F</i>_ST, B.) <i>D_A</i>, C.) <i>D</i>_ST, D.) Latter’s <i>F</i>_ST<i>*</i> distance and E.) <i>D_C</i>. Percentages of variance accounted for by the three components are indicated in the labels. Populations are colored according to their linguistic affiliations for better visual comparison.</p

QPCR verification result.

<p>QPCR verification result of 14 selected genes. The mRNA expression levels of these genes were normalized with the external control gene (Xeno), and were calculated with 2^−ΔΔCt relative quantification. Bar charts showing the relative expression levels of PSEN2, ANXA8, HES1, JAG1, HEY2, NCSTN, KRT18, KRT8, GATA2, NANOG, SLC36A2, KCTD3, DPP4, and LGMN genes in IVV XB, IVV HB, PA XB, PA HB, and CT HB (KCTD3, SLC36A2, and LGMN genes were not tested in CT HB). The relative expression levels of in each sample were standardized with their expression Error bars shows the standard error (*: P < 0.05). Dashed lines indicate 1.0 expression level. ND: not detected. NT: not tested.</p

Altered canonical pathways in PA and CT-derived HB.

<p>Bar chart shows the altered canonical pathways in IPA canonical pathways analysis. Major Y axis on the left shows the number of differentially expressed genes that involved in the canonical pathway. Secondary Y axis on the right shows the significance (-log (B-H P-value)) of the canonical pathway. The orange line shows the significance threshold cut off of -log (B-H P-value = 0.05).</p

The prior distributions of demographic parameters for the ABC simulation.

<p>The prior distributions of demographic parameters for the ABC simulation.</p

Migratory routes of Tai and populations’ information.

<p>Geographical location of the 19 sampled populations and the migratory routes from the three different hypotheses.</p