Investigating prehistoric diet and lifeways of early farmers in central northern Spain (3000-1500 CAL BC) using stable isotope techniques

This work focuses on reconstructing past diets and animal management during Prehistory in Central Northern Spain, spanning the NE area of the Old Castilian Plateau to the Cantabrian coast, from c. 3000-1500 BCE. During this time, early farming communities made changes in their models of production and social reproduction that crystallised in the emergence of social complexity. To investigate these changes, we reconstructed the past diet of these early farming populations by using stable isotope analysis (?13C, ?15N, ?34S) of human and animal remains from the recently excavated sites of Abrigo de la Castañera in Cantabria and Arroyal I, El Hornazo, Fuente Celada and Ferrocarril-La Dehesa in Burgos. The human remains derived from a range of burial contexts including pit graves, megalithic monuments and burial caves. To provide initial insights into animal management during this timeframe, associated faunal remains were also studied as a baseline. In total, 52 samples were analysed, including 17 human burials and 35 animal specimens (cattle, sheep, pig, red deer and dog). Results show that humans in these sites consumed relatively similar diets, comprising of a predominantly C3 diet including animal protein. Animal management patterns indicate a wider use of the landscape for herbivore grazing. The differing diets of dogs at El Hornazo provide insights into the relationship that they had with humans and tentatively suggests differences in the diet of working animals versus household pets. The ?34S values of two individuals from Arroyal I indicate that they came from different regions, implying a level of inland mobility during the Chalcolithic

Evolving neural network optimization of cholesteryl ester separation by reversed-phase HPLC

Cholesteryl esters have antimicrobial activity and likely contribute to the innate immunity system. Improved separation techniques are needed to characterize these compounds. In this study, optimization of the reversed-phase high-performance liquid chromatography separation of six analyte standards (four cholesteryl esters plus cholesterol and tri-palmitin) was accomplished by modeling with an artificial neural network–genetic algorithm (ANN-GA) approach. A fractional factorial design was employed to examine the significance of four experimental factors: organic component in the mobile phase (ethanol and methanol), column temperature, and flow rate. Three separation parameters were then merged into geometric means using Derringer’s desirability function and used as input sources for model training and testing. The use of genetic operators proved valuable for the determination of an effective neural network structure. Implementation of the optimized method resulted in complete separation of all six analytes, including the resolution of two previously co-eluting peaks. Model validation was performed with experimental responses in good agreement with model-predicted responses. Improved separation was also realized in a complex biological fluid, human milk. Thus, the first known use of ANN-GA modeling for improving the chromatographic separation of cholesteryl esters in biological fluids is presented and will likely prove valuable for future investigators involved in studying complex biological samples

Ang pakikipagtalastasan ng mga lalaking namamasukan sa parlor

Ang pag-aaral na ito ay tungkol sa mga salitang balbal na madalas gamitin ng mga bakla, ang kahulugan ng mga salita na ginagamit, ang pinagmulan ng mga salitang bakla at ang mga sitwasyong pinaggagamitan nito. Ang pangkalahatang disenyo ng pag-aaral ay deskriptibo na ginamitan ng metodong pagtatanong-tanong. Tatlumput-apat (34) na baklang mula sa mga iba\u27t-ibang beauty parlor ng Metro Manila ang naging bahagi ng pag-aaral na ito na pinili sa pamamagitan ng pagtatanong-tanong. Napag-alaman ang mga salitang madalas gamitin ng mga bakla at ang kahulugan ng mga ito. Sa pamamagitan ng pagsusuri ng nilalaman, ang mga salitang bakla ay ikinategorya sa labing-pitong sitwasyon. Napag-alaman na ang ilan sa mga salitang bakla ay hinango sa iba\u27t-ibang dayalekto habang ang iba ay mga salitang binaligtad. May mga salitang dinadagdagan ng mga letrang ch, j, s, ing, er, tsina at is at mayroon namang mga salitang inimbento at binigyang-kahulugan ng mga bakla. Ang mga salitang bakla, ano man ang kahulugan at ano man ang kanilang pinaggalingan ay sumasalamin sa isip at damdamin ng mga bakla

Human Periodontal Cells Initiate Mineral‐Like Nodules In Vitro

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141790/1/jper0499.pd

Metabolomics of oncogene-specific metabolic reprogramming during breast cancer

Abstract Background The complex yet interrelated connections between cancer metabolism and oncogenic driver genes are relatively unexplored but have the potential to identify novel biomarkers and drug targets with prognostic and therapeutic value. The goal of this study was to identify global metabolic profiles of breast tumors isolated from multiple transgenic mouse models and to identify unique metabolic signatures driven by these oncogenes. Methods Using mass spectrometry (GC-MS, LC-MS/MS, and capillary zone electrophoresis (CZE)-MS platforms), we quantified and compared the levels of 374 metabolites in breast tissue from normal and transgenic mouse breast cancer models overexpressing a panel of oncogenes (PyMT, PyMT-DB, Wnt1, Neu, and C3-TAg). We also compared the mouse metabolomics data to published human metabolomics data already linked to clinical data. Results Through analysis of our metabolomics data, we identified metabolic differences between normal and tumor breast tissues as well as metabolic differences unique to each initiating oncogene. We also quantified the metabolic profiles of the mammary fat pad versus mammary epithelium by CZE-MS/MS. However, the differences between the tissues did not account for the majority of the metabolic differences between the normal mammary gland and breast tumor tissues. Therefore, the differences between the cohorts were unlikely due to cellular heterogeneity. Of the mouse models used in this study, C3-TAg was the only cohort with a tumor metabolic signature composed of ten metabolites that had significant prognostic value in breast cancer patients. Gene expression analysis identified candidate genes that may contribute to the metabolic reprogramming. Conclusions This study identifies oncogene-induced metabolic reprogramming within mouse breast tumors and compares the results to that of human breast tumors, providing a unique look at the relationship between and clinical value of oncogene initiation and metabolism during breast cancer

Additional file 2: of Metabolomics of oncogene-specific metabolic reprogramming during breast cancer

Mouse models used in the study. Related to Fig. 1. This table includes the mouse models and the number of mice in each group, including mouse genotype, age, and weight of sample sent. (XLSX 13 kb

Additional file 9: of Metabolomics of oncogene-specific metabolic reprogramming during breast cancer

Raw Data for Patient Survival Prediction Using Model Specific Metabolites. Related to Table 1. Using a Cox proportional hazards model, different metabolites and sets of metabolites were used as input to predict patient survival in a previously published human breast cancer patient metabolomics dataset. The p-values for each individual metabolite as well as a combination of the metabolites are listed. (XLSX 11 kb