The Mammalian Locus Coeruleus Complex—Consistencies and Variances in Nuclear Organization

Descriptions of the nuclear parcellation of the locus coeruleus complex have been provided in approximately 80 mammal species spanning the phylogenetic breadth of this class. Within the mammalian rostral hindbrain, noradrenergic neurons (revealed with tyrosine hydroxylase and dopamine-ß-hydroxylase immunohistochemistry) have been observed within the periventricular grey matter (A4 and A6 nuclei) and parvicellular reticular nucleus (A5 and A7 nuclei), with the one exception to date being the tree pangolin, where no A4/A6 neurons are observed. The alphanumeric nomenclature system, developed in laboratory rodent brains, has been adapted to cover the variation observed across species. Cross-species homology is observed regarding the nuclear organization of noradrenergic neurons located in the parvicellular reticular nucleus (A5 and A7). In contrast, significant variations are observed in the organization of the A6 neurons of the locus coeruleus proper. In most mammals, the A6 is comprised of a moderate density of neurons, but in Murid rodents, primates, and megachiropteran bats, the A6 exhibits a very high density of neurons. In primates and megachiropterans, there is an additional moderate density of A6 neurons located rostromedial to the high-density portion. These variations are of importance in understanding the translation of findings in laboratory rodents to humans.

Impact of Marker Pruning Strategies Based on Different Measurements of Marker Distance on Genomic Prediction in Dairy Cattle

With the availability of high-density single-nucleotide polymorphism (SNP) data and the development of genotype imputation methods, high-density panel-based genomic prediction (GP) has become possible in livestock breeding. It is generally considered that the genomic estimated breeding value (GEBV) accuracy increases with the marker density, while studies have shown that the GEBV accuracy does not increase or even decrease when high-density panels were used. Therefore, in addition to the SNP number, other measurements of ‘marker density’ seem to have impacts on the GEBV accuracy, and exploring the relationship between the GEBV accuracy and the measurements of ‘marker density’ based on high-density SNP or whole-genome sequence data is important for the field of GP. In this study, we constructed different SNP panels with certain SNP numbers (e.g., 1 k) by using the physical distance (PhyD), genetic distance (GenD) and random distance (RanD) between SNPs respectively based on the high-density SNP data of a Germany Holstein dairy cattle population. Therefore, there are three different panels at a certain SNP number level. These panels were used to construct GP models to predict fat percentage, milk yield and somatic cell score. Meanwhile, the mean (d¯) and variance (σd2) of the physical distance between SNPs and the mean (r2¯) and variance (σr22) of the genetic distance between SNPs in each panel were used as marker density-related measurements and their influence on the GEBV accuracy was investigated. At the same SNP number level, the d¯ of all panels is basically the same, but the σd2, r2¯ and σr22 are different. Therefore, we only investigated the effects of σd2, r2¯ and σr22 on the GEBV accuracy. The results showed that at a certain SNP number level, the GEBV accuracy was negatively correlated with σd2, but not with r2¯ and σr22. Compared with GenD and RanD, the σd2 of panels constructed by PhyD is smaller. The low and moderate-density panels (< 50 k) constructed by RanD or GenD have large .σd2., which is not conducive to genomic prediction. The GEBV accuracy of the low and moderate-density panels constructed by PhyD is 3.8~34.8% higher than that of the low and moderate-density panels constructed by RanD and GenD. Panels with 20–30 k SNPs constructed by PhyD can achieve the same or slightly higher GEBV accuracy than that of high-density SNP panels for all three traits. In summary, the smaller the variation degree of physical distance between adjacent SNPs, the higher the GEBV accuracy. The low and moderate-density panels construct by physical distance are beneficial to genomic prediction, while pruning high-density SNP data based on genetic distance is detrimental to genomic prediction. The results provide suggestions for the development of SNP panels and the research of genome prediction based on whole-genome sequence data.

Influence of the densities and nutritional components of bacterial colonies on the culture-enriched gut bacterial community structure

Isolating relevant microorganisms is still a substantial challenge that limits the use of bacteria in the maintenance of human health. To confirm which media and which bacterial colony densities can enrich certain kinds of bacteria, we selected eight common media and used them to enrich the gut microorganisms on agar plates. Then, we calculated the numbers of bacterial colonies and collected the bacterial culture mixtures from each kind of medium. Using the Illumina HiSeq platform, we analyzed the composition and diversity of the culture-enriched gut bacterial community. Our data suggested that medium supplemented with blood could increase the diversity of the bacterial community. In addition, beef powder and peptone could significantly change the culture-enriched bacterial community. A moderate density (100–150 colony-forming units per plate) was optimal for obtaining the highest diversity on the agar. Similarly, membrane transport was significantly enriched in the moderate-density group, which indicated a more active metabolism in this density range. Overall, these results reveal the optimal culture conditions, including the densities of colonies and nutritional components for various gut bacteria, that provide a novel strategy for isolating bacteria in a way that is targeted and avoids blinded and repetitive work.

Pancreatic Cancer Stem Cells May Define Tumor Stromacharacteristics and Recurrence Patterns in Pancreatic Ductal Adenocarcinoma

Background Herein, we investigate the relationship between pancreatic stem cell markers (PCSC markers), CD44, and epithelial-specific antigen (ESA), tumor stroma, and the impact on recurrence outcomes in pancreatic ductal adenocarcinoma (PDAC) patients. Methods PDAC patients who underwent surgical resection between 01/2012 -06/2014 were identified. CD44 and ESA expression was assessed by immunohistochemistry. Stroma was classified as loose, moderate density, and dense based on fibroblast content. Overall survival (OS) and relapse-free survival (RFS) were estimated using the Kaplan-Meier method and compared between subgroups by log-rank test. The association between PCSC markers and stroma type was assessed by Fisher`s exact test. Results N = 93 PDAC patients were identified. The number of PDAC patients with dense, moderate density, and loose stroma was 11 (12%), 51 (54%), and 31 (33%) respectively. PDAC with CD44+/ESA− had highest rate of loose stroma (63%) followed by PDAC CD44+/ESA+ (50%), PDAC CD44−/ESA+ (35%), CD44−/ESA− (9%) (p = 0.0033). No local recurrence was observed in patients with dense stroma and 9 had distant recurrence. The highest rate of cumulative local recurrence observed in patients with loose stroma. No statistically significant difference in RFS and OS were observed among subgroups (P = 0.089). Conclusions These data indicate PCSCs may have an important role in stroma differentiation in PDAC. Although not reaching statistical significance, we observed more local recurrences in patients with loose stroma, and no local recurrence was seen in patients with dense stroma suggesting tumor stroma may influence the recurrence pattern in PDAC patients.

Production and decomposition of mangrove litter in Jang River Estuary, Bukit Bestari District, Tanjungpinang City

The purpose of this study was to analyze the level of mangrove density, the level of production and decomposition of mangrove litter in Jang River Estuary, Bukit Bestari District, Tanjungpinang City. Determination of the research location using purposive sampling method based on development activities around the Muara Jang River mangrove area, including the area of ​​community settlement development (station 1), landfill area for the construction of shop houses and housing (station 2) and the area without development activities (station 3). To measure the density of mangroves using a plot of 10 x 10 m2 with 3 plots, to measure the production of mangrove litter using litter and to measure the decomposition of mangroves using litter with a 0.5 cm mesh size placed under mangrove trees that are still affected by tides. The results showed the level of mangrove density at station 1 was 1033 ± 51 trees/ha with good criteria and moderate density, station 2 was 933 ± 115 trees/ha with rare damage and density criteria, and station 3 was 1367 ± 208 trees/ha with good criteria and moderate density. The level of mangrove litter production at Station 1 is 5.14 grams dry weight / m2, Station 2 is 2.80 grams dry weight / m2, and Station 3 is 6.67 grams dry weight / m2. The mangrove decomposition rate at station 1 was 63.33%, station 2 was 62.05% and station 3 was 67.73%.