A high-resolution δ18O record and Mediterranean climate variability

A high-resolution, well-dated foraminiferal δ¹⁸O record from a shallow-water core drilled from the Gallipoli Terrace in the Gulf of Taranto (Ionian Sea), previously measured over the last two millennia, has been extended to cover 707 BC–AD 1979. Spectral analysis of this series, performed using singular-spectrum analysis (SSA) and other classical and advanced methods, strengthens the results obtained analysing the shorter δ¹⁸O profile, detecting the same highly significant oscillations of about 600, 380, 170, 130 and 11 years, respectively explaining about 12, 7, 5, 2 and 2% of the time series total variance, plus a millennial trend (18% of the variance). The comparison with the results of multi-channel singular-spectrum analysis (MSSA) applied to a data set of 26 Northern Hemisphere (NH) temperature-proxy records shows that NH temperature anomalies share with our local record a~long-term trend and a bicentennial (170-year period) cycle. These two variability modes, previously identified as temperature-driven, are the most powerful modes in the NH temperature data set. Both the long-term trends and the bicentennial oscillations, when reconstructed locally and hemispherically, show coherent phases. Furthermore, the corresponding local and hemispheric amplitudes are comparable if changes in the precipitation–evaporation balance of the Ionian sea, presumably associated with temperature changes, are taken into account

Effects of candidate gene polymorphisms on the detailed fatty acids profile determined by gas chromatography in bovine milk

Association analyses between candidate genes and bovine milk fatty acids can improve our understanding of genetic variation in milk fatty acid profiles and reveal potential opportunities to tailor milk fat composition through selection strategies. In this work, we investigated the association of 51 single nucleotide polymorphisms (SNP) selected from 37 candidate genes using a functional and positional approach, with 47 fatty acids, 9 fatty acid groups, and 5 \u3b49-desaturation indices in milk samples from Brown Swiss cows. Individual milk samples were collected from 1,158 Italian Brown Swiss cows, and gas chromatography was used to obtain detailed milk fatty acid compositions. A GoldenGate assay system (Illumina, San Diego, CA) was used to perform genotype 96 selected SNP located in 54 genes across 22 chromosomes. In total, 51 polymorphic SNP in 37 candidate genes were retained for the association analysis. A Bayesian linear animal model was used to estimate the contribution of each SNP. A total of 129 tests indicated relevant additive effects between a given SNP and a single fatty acid trait; 38 SNP belonging to 30 genes were relevant for a total of 57 fatty acid traits. Most of the studied fatty acid traits (~81%) were relevantly associated with multiple SNP. Relevantly associated SNP were mainly found in genes related to fat metabolism, linked to or contained in previously identified quantitative trait loci for fat yield or content, or associated with genes previously identified in association analyses with milk fatty acid profiles in other cow breeds. The most representative candidate genes were LEP, PRL, STAT5A, CCL3, ACACA, GHR, ADRB2, LPIN1, STAT1, FABP4, and CSN2. In particular, relevant associations with SNP located on bovine chromosome 19 (BTA19) were found. Two candidate genes on BTA19 (CCL3 and ACACA) were relevantly associated with de novo short- and medium-chain fatty acids, likely explaining the high heritability values found for these fatty acids (with the exception of C6:0). Two additional genes on BTA19 (CCL2 and GH1) showed associations with saturated and branched-chain fatty acids. Our findings provide basic information on genes and SNP affecting the milk fatty acid composition of dairy cows. These results may support the possibility of using genetic selection to modify milk fatty acid profiles to promote beneficial health-related effects

Fluorine variations in the globular cluster NGC 6656 (M22): implications for internal enrichment timescales

Observed chemical (anti)correlations in proton-capture elements among globular cluster stars are presently recognized as the signature of self-enrichment from now extinct, previous generations of stars. This defines the multiple population scenario. Since fluorine is also affected by proton captures, determining its abundance in globular clusters provides new and complementary clues regarding the nature of these previous generations, and supplies strong observational constraints to the chemical enrichment timescales. In this paper we present our results on near-infrared CRIRES spectroscopic observations of six cool giant stars in NGC 6656 (M22): the main objective is to derive the F content and its internal variation in this peculiar cluster, which exhibits significant changes in both light and heavy element abundances. We detected F variations across our sample beyond the measurement uncertainties and found that the F abundances are positively correlated with O and anticorrelated with Na, as expected according to the multiple population framework. Furthermore, our observations reveal an increase in the F content between the two different sub-groups, s-process rich and s-process poor, hosted within M22. The comparison with theoretical models suggests that asymptotic giant stars with masses between 4 and 5 Msun are responsible for the observed chemical pattern, confirming evidence from previous works: the difference in age between the two sub-components in M22 must be not larger than a few hundreds Myr.Comment: Accepted for publication in The Astrophysical Journal, 10 pages, 10 figure

Recent Advances in the Development of Biomimetic Materials

: In this review, we focused on recent efforts in the design and development of materials with biomimetic properties. Innovative methods promise to emulate cell microenvironments and tissue functions, but many aspects regarding cellular communication, motility, and responsiveness remain to be explained. We photographed the state-of-the-art advancements in biomimetics, and discussed the complexity of a "bottom-up" artificial construction of living systems, with particular highlights on hydrogels, collagen-based composites, surface modifications, and three-dimensional (3D) bioprinting applications. Fast-paced 3D printing and artificial intelligence, nevertheless, collide with reality: How difficult can it be to build reproducible biomimetic materials at a real scale in line with the complexity of living systems? Nowadays, science is in urgent need of bioengineering technologies for the practical use of bioinspired and biomimetics for medicine and clinics

Comparison of sampling bags for the analysis of volatile organic compounds in breath

Nalophan, Tedlar and Cali-5-Bond polymeric bags were compared to determine the most suitable type for breath sampling and storage when volatile organic compounds are to be determined. Analyses were performed by thermal desorption gas chromatography mass spectrometry. For each bag, the release of contaminants and the chemical stability of a gaseous standard mixture containing eighteen organic compounds, as well as the CO2 partial pressure were assessed. The selected compounds were representative of breath constituents and belonged to different chemical classes (i.e. hydrocarbons, ketones, aldehydes, aromatics, sulfurs and esters). In the case of Nalophan, the influence of the surface-to-volume ratio, related to the bag's filling degree, on the chemical stability was also evaluated. Nalophan bags were found to be the most suitable in terms of contaminants released during storage (only 2-methyl-1,3-dioxalane), good sample stability (up to 24 h for both dry and humid samples), and very limited costs (about 1 for a 20 liter bag). The (film) surface-to-(sample) volume ratio was found to be an important factor affecting the stability of selected compounds, and therefore we recommended to fill the bag completely

Radiomics and artificial intelligence in malignant uterine body cancers: Protocol for a systematic review

IntroductionUterine body cancers (UBC) are represented by endometrial carcinoma (EC) and uterine sarcoma (USa). The clinical management of both is hindered by the complex classification of patients into risk classes. This problem could be simplified through the development of predictive models aimed at treatment tailoring based on tumor and patient characteristics. In this context, radiomics represents a method of extracting quantitative data from images in order to non-invasively acquire tumor biological and genetic information and to predict response to treatments and prognosis. Furthermore, artificial intelligence (AI) methods are an emerging field of translational research, with the aim of managing the amount of data provided by the various -omics, including radiomics, through the process of machine learning, in order to promote precision medicine.ObjectiveThe aim of this protocol for systematic review is to provide an overview of radiomics and AI studies on UBCs.Methods and analysisA systematic review will be conducted using PubMed, Scopus, and the Cochrane Library to collect papers analyzing the impact of radiomics and AI on UBCs diagnosis, prognostic classification, and clinical outcomes. The PICO strategy will be used to formulate the research questions: What is the impact of radiomics and AI on UBCs on diagnosis, prognosis, and clinical results? How could radiomics or AI improve the differential diagnosis between sarcoma and fibroids? Does Radiomics or AI have a predictive role on UBCs response to treatments? Three authors will independently screen articles at title and abstract level based on the eligibility criteria. The risk of bias and quality of the cohort studies, case series, and case reports will be based on the QUADAS 2 quality assessment tools

Mediterranean Diet and NAFLD: What We Know and Questions That Still Need to Be Answered

open8Non-alcoholic fatty liver disease (NAFLD) is the hepatic manifestation of metabolic syndrome and is expected to become the leading cause of end-stage liver disease worldwide over the next few decades. In fact, NAFLD encompasses different clinical scenarios, from the simple accumulation of fat (steatosis) to steatohepatitis (NASH), NASH-cirrhosis, and cirrhosis complications. In this context, it is fundamental to pursue strategies aimed at both preventing the disease and reducing the progression of liver fibrosis once liver damage is already initiated. As of today, no pharmacological treatment has been approved for NAFLD/NASH, and the only recommended treatment of proven efficacy are life-style modifications, including diet and physical exercise pointing at weight loss of 5%-7%. Different dietetic approaches have been proposed in this setting, and in this review, we will discuss the evidence regarding the efficacy of the Mediterranean Diet as a treatment for NAFLD. In particular, we will report the effects on liver-related outcomes.openPlaz Torres, Maria Corina; Aghemo, Alessio; Lleo, Ana; Bodini, Giorgia; Furnari, Manuele; Marabotto, Elisa; Miele, Luca; Giannini, Edoardo GPlaz Torres, Maria Corina; Aghemo, Alessio; Lleo, Ana; Bodini, Giorgia; Furnari, Manuele; Marabotto, Elisa; Miele, Luca; Giannini, Edoardo

Novel integrative genomic tool for interrogating lithium response in bipolar disorder

We developed a novel integrative genomic tool called GRANITE (Genetic Regulatory Analysis of Networks Investigational Tool Environment) that can effectively analyze large complex data sets to generate interactive networks. GRANITE is an open-source tool and invaluable resource for a variety of genomic fields. Although our analysis is confined to static expression data, GRANITE has the capability of evaluating time-course data and generating interactive networks that may shed light on acute versus chronic treatment, as well as evaluating dose response and providing insight into mechanisms that underlie therapeutic versus sub-therapeutic doses or toxic doses. As a proof-of-concept study, we investigated lithium (Li) response in bipolar disorder (BD). BD is a severe mood disorder marked by cycles of mania and depression. Li is one of the most commonly prescribed and decidedly effective treatments for many patients (responders), although its mode of action is not yet fully understood, nor is it effective in every patient (non-responders). In an in vitro study, we compared vehicle versus chronic Li treatment in patient-derived lymphoblastoid cells (LCLs) (derived from either responders or non-responders) using both microRNA (miRNA) and messenger RNA gene expression profiling. We present both Li responder and non-responder network visualizations created by our GRANITE analysis in BD. We identified by network visualization that the Let-7 family is consistently downregulated by Li in both groups where this miRNA family has been implicated in neurodegeneration, cell survival and synaptic development. We discuss the potential of this analysis for investigating treatment response and even providing clinicians with a tool for predicting treatment response in their patients, as well as for providing the industry with a tool for identifying network nodes as targets for novel drug discovery