Analysis of corrections to the eikonal approximation

Various corrections to the eikonal approximations are studied for two- and three-body nuclear collisions with the goal to extend the range of validity of this approximation to beam energies of 10 MeV/nucleon. Wallace's correction does not improve much the elastic-scattering cross sections obtained at the usual eikonal approximation. On the contrary, a semiclassical approximation that substitutes the impact parameter by a complex distance of closest approach computed with the projectile-target optical potential efficiently corrects the eikonal approximation. This opens the possibility to analyze data measured down to 10 MeV/nucleon within eikonal-like reaction models.Comment: 10 pages, 8 figure

Age is the strongest component that affects gut microbiota composition at the KEGG pathway level.

<p>Samples were named using “A” plus infant ages according to months. Fig 3 indicates that the first and second dimension can account for 41.34% and 18.29% of the variation, respectively, and that the distribution of all samples in two dimensions and indicates that all samples could be divided into two groups based on age bifurcated at 1 year of age.</p

Significant enriched pathways revealed by Student’s <i>t-</i>test in younger (<1 year old) and older (>1 year old) groups of babies.

<p>Significant enriched pathways revealed by Student’s <i>t-</i>test in younger (<1 year old) and older (>1 year old) groups of babies.</p

Diversity of Gut Microbiota Metabolic Pathways in 10 Pairs of Chinese Infant Twins

<div><p>Early colonization of gut microbiota in human gut is a complex process. It remains unclear when gut microbiota colonization occurs and how it proceeds. In order to study gut microbiota composition in human early life, the present study recruited 10 healthy pairs of twins, including five monozygotic (MZ) and five dizygotic (DZ) twin pairs, whose age ranged from 0 to 6 years old. 20 fecal samples from these twins were processed by shotgun metagenomic sequencing, and their averaged data outputs were generated as 2G per sample. We used MEGAN5 to perform taxonomic and functional annotation of the metagenomic data, and systematically analyzed those 20 samples, including Jaccard index similarity, principle component, clustering, and correlation analyses. Our findings indicated that within our study group: 1) MZ-twins share more microbes than DZ twins or non-twin pairs, 2) gut microbiota distribution is relatively stable at metabolic pathways level, 3) age represents the strongest factor that can account for variation in gut microbiota, and 4) a clear metabolic pathway shift can be observed, which speculatively occurs around the age of 1 year old. This research will serve as a base for future studies of gut microbiota-related disease research.</p></div

Sample characteristics of 10 pairs of co-twins.

<p>Sample characteristics of 10 pairs of co-twins.</p

Gut microbiota are not stable and gut metabolism becomes stable with age.

<p>Fig 2a (top) is a stacked line of gut microbiota at the phylum level. The figures show that gut microbiota distribution are not stable at the taxonomic level. Fig 2b (lower) is a local fitting of gut microbiota at the KEGG level 1, the unique reads which are normalized to 1 million reads per sample annotated in each sectors are regressed against age (months) of 10 co-twins. The lines are drawn by R’s lowess according to a weighted polynomial regression method for the local fitting of KEGG level data. As the age increases, there is a trend that the KEGG functions for gut microbiota began to stabilize.</p

MZ co-twin pairs share more gut microbes than pairs of DZ co-twins or inter-twins.

<p>The sample distances between any two samples were computed using the 1–Jaccard index. MZ (monozygotic) and DZ (dizygotic) twins are marked with red and black font, respectively. This figure shows that compared with DZ and non-twins, MZ twins are more tightly clustered.</p

Comparison of mutation rate in <i>MTTP</i> rs2306986 and SLC6A2 rs3743788 between NAFLD group and non-NAFLD group (of Chinese Han ethnicity).

<p>Comparison of mutation rate in <i>MTTP</i> rs2306986 and SLC6A2 rs3743788 between NAFLD group and non-NAFLD group (of Chinese Han ethnicity).</p

Revealing age-related KEGG pathways.

<p>Samples were renamed using “A” plus infant ages in months. The red color means these pathways are older age group enriched, the blue color means that these pathways are younger age group enriched. Significant, one year of age was used as the dividing line and samples were divided into two groups. All pathways with read count above 1000, a p-value less than 0.001, and a FDR value less than 0.05 were selected and clustered. The probability of several signaling pathways, such as renal cell carcinoma and arachidonic acid, occurring in the younger group is higher than for the older group.</p

Anthropometric and biochemical characters in NAFLD and non-NAFLD groups (of Han Chinese ethnicity).

<p>Anthropometric and biochemical characters in NAFLD and non-NAFLD groups (of Han Chinese ethnicity).</p