Carboplatin, nab-paclitaxel plus atezolizumab in Impower 130 trial: New weapons beyond controversies

Letter to edito

Methanol masers reveal the magnetic field of the high-mass protostar IRAS 18089-1732

Context. The importance of the magnetic field in high-mass-star formation is not yet fully clear and there are still many open questions concerning its role in the accretion processes and generation of jets and outflows. In the past few years, masers have been successfully used to probe the magnetic field morphology and strength at scales of a few au around massive protostars, by measuring linear polarisation angles and Zeeman splitting. The massive protostar IRAS 18089-1732 is a well studied high-mass-star forming region, showing a hot core chemistry and a disc-outflow system. Previous SMA observations of polarised dust revealed an ordered magnetic field oriented around the disc of IRAS 18089-1732. Aims. We want to determine the magnetic field in the dense region probed by 6.7 GHz methanol maser observations and compare it with observations in dust continuum polarisation, to investigate how the magnetic field in the compact maser region relates to the large-scale field around massive protostars. Methods. We reduced MERLIN observations at 6.7 GHz of IRAS 18089-1732 and we analysed the polarised emission by methanol masers. Results. Our MERLIN observations show that the magnetic field in the 6.7 GHz methanol maser region is consistent with the magnetic field constrained by the SMA dust polarisation observations. A tentative detection of circularly polarised line emission is also presented. Conclusions. We found that the magnetic field in the maser region has the same orientation as in the disk. Thus the large-scale field component, even at the au scale of the masers, dominates over any small-scale field fluctuations. We obtained, from the circular polarisation tentative detection, a field strength along the line of sight of 5.5 mG which appeared to be consistent with the previous estimates.Comment: 12 pages, 7 figures, accepted for publication in A&

Genome-wide association studies for 30 haematological and blood clinical-biochemical traits in Large White pigs reveal genomic regions affecting intermediate phenotypes

Haematological and clinical-biochemical parameters are considered indicators of the physiological/health status of animals and might serve as intermediate phenotypes to link physiological aspects to production and disease resistance traits. The dissection of the genetic variability affecting these phenotypes might be useful to describe the resilience of the animals and to support the usefulness of the pig as animal model. Here, we analysed 15 haematological and 15 clinical-biochemical traits in 843 Italian Large White pigs, via three genome-wide association scan approaches (single-trait, multi-trait and Bayesian). We identified 52 quantitative trait loci (QTLs) associated with 29 out of 30 analysed blood parameters, with the most significant QTL identified on porcine chromosome 14 for basophil count. Some QTL regions harbour genes that may be the obvious candidates: QTLs for cholesterol parameters identified genes (ADCY8, APOB, ATG5, CDKAL1, PCSK5, PRL and SOX6) that are directly involved in cholesterol metabolism; other QTLs highlighted genes encoding the enzymes being measured [ALT (known also as GPT) and AST (known also as GOT)]. Moreover, the multivariate approach strengthened the association results for several candidate genes. The obtained results can contribute to define new measurable phenotypes that could be applied in breeding programs as proxies for more complex traits

ALMA reveals the magnetic field evolution in the high-mass star forming complex G9.62+0.19

Context. The role of magnetic fields during the formation of high-mass stars is not yet fully understood, and the processes related to the early fragmentation and collapse are largely unexplored today. The high-mass star forming region G9.62+0.19 is a well known source, presenting several cores at different evolutionary stages. Aims. We determine the magnetic field morphology and strength in the high-mass star forming region G9.62+0.19, to investigate its relation to the evolutionary sequence of the cores. Methods. We use Band 7 ALMA observations in full polarisation mode and we analyse the polarised dust emission. We estimate the magnetic field strength via the Davis-Chandrasekhar-Fermi and the Structure Function methods. Results. We resolve several protostellar cores embedded in a bright and dusty filamentary structure. The polarised emission is clearly detected in six regions. Moreover the magnetic field is oriented along the filament and appears perpendicular to the direction of the outflows. We suggest an evolutionary sequence of the magnetic field, and the less evolved hot core exhibits a magnetic field stronger than the more evolved one. We detect linear polarisation from thermal line emission and we tentatively compared linear polarisation vectors from our observations with previous linearly polarised OH masers observations. We also compute the spectral index, the column density and the mass for some of the cores. Conclusions. The high magnetic field strength and the smooth polarised emission indicate that the magnetic field could play an important role for the fragmentation and the collapse process in the star forming region G9.62+019 and that the evolution of the cores can be magnetically regulated. On average, the magnetic field derived by the linear polarised emission from dust, thermal lines and masers is pointing in the same direction and has consistent strength.Comment: accepted by A&A, version after language editin

Impact of sialyltransferase ST6GAL1 overexpression on different colon cancer cell types

Cancer-associated glycan structures can be both tumor markers and engines of disease progression. The structure Sia\u3b12,6Gal\u3b21,4GlcNAc (Sia6LacNAc), synthesized by sialyltransferase ST6GAL1, is a cancer-associated glycan. Although ST6GAL1/Sia6LacNAc are often overexpressed in colorectal cancer (CRC), their biological and clinical significance remains unclear. To get insights into the clinical relevance of ST6GAL1 expression in CRC, we interrogated The Cancer Genome Atlas with mRNA expression data of hundreds of clinically characterized CRC and normal samples. We found an association of low ST6GAL1 expression with microsatellite instability (MSI), BRAF mutations and mucinous phenotype but not with stage, response to therapy and survival. To investigate the impact of ST6GAL1 expression in experimental systems, we analyzed the transcriptome and the phenotype of the CRC cell lines SW948 and SW48 after retroviral transduction with ST6GAL1 cDNA. The two cell lines display the two main pathways of CRC transformation: chromosomal instability and MSI, respectively. Constitutive ST6GAL1 expression induced much deeper transcriptomic changes in SW948 than in SW48 and affected different genes in the two cell lines. ST6GAL1 expression affected differentially the tyrosine phosphorylation induced by hepatocyte growth factor, the ability to grow in soft agar, to heal a scratch wound and to invade Matrigel in the two cell lines. These results indicate that the altered expression of a cancer-associated glycosyltransferase impacts the gene expression profile, as well as the phenotype, although in a cancer subtype-specific manner

Targeted metabolomic profiles of piglet plasma reveal physiological changes over the suckling period

The suckling phase is a critical period for the piglets due to their incomplete immune system development and their rapid growth rates. In this study, we analysed the metabolomic profiles of piglets over this period. Eighteen piglets (nine males and nine females) from three different litters were included in the study. Body weight was recorded at birth (T0), 12 (T1) and 21 (T2) days after birth. Plasma samples were collected at two critical time points of the suckling phase (T1 and T2) and about 180 metabolites of five different biochemical classes (glycerophospholipids, amino acids, biogenic amines, hexoses and acylcarnitines) were analyzed using a target metabolomics approach based on Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS). Metabolites whose levels could discriminate the plasma profiles at T1 and T2 were identified using the sparse version of Multilevel Partial Least Squares Discriminant Analysis (sMLPLS-DA), coupled with a stability test based on a Leave One Out (LOO) procedure. The level of twenty-three metabolites differed significantly (P < 0.1; both for stability and the effect size) between the two time points. Higher levels of six acylcarnitine (C14:1, C14:1-OH, C16-OH, C4, C5 and C5-OH), serine, threonine and tyrosine, and one phosphatidylcholine (PC ae C42:3) were observed at T1, whereas one biogenic amine (creatinine), eight phosphatidylcholines including PC aa C30:2, PC ae C30:0, PC ae C32:1, PC ae C38:4, PC ae C40:4, PC ae C42:4, PC ae C42:5 and PC ae C44:6, and four sphingomyelins, including SM (OH) C22:1, SM C16:0, SM C16:1 and SM C18:0, were more abundant at T2. The Metabolite Set Enrichment Analysis and the Pathway Analysis modules suggested a perturbation of the \u201cglycine and serine metabolism\u201d and the \u201csphingolipid metabolism\u201d. Differences of these metabolites between these two time points might be related to the rapid growth and immunological maturation phases of the piglets in this period. Our results provided new information that could describe the biological changes of the piglets over the suckling period. The identified metabolites may be useful markers of the developmental processes occurring in the piglets over this critical pre-weaned phase

Prediction of vascular aging based on smartphone acquired PPG signals

Photoplethysmography (PPG) measured by smartphone has the potential for a large scale, non-invasive, and easy-to-use screening tool. Vascular aging is linked to increased arterial stiffness, which can be measured by PPG. We investigate the feasibility of using PPG to predict healthy vascular aging (HVA) based on two approaches: machine learning (ML) and deep learning (DL). We performed data preprocessing, including detrending, demodulating, and denoising on the raw PPG signals. For ML, ridge penalized regression has been applied to 38 features extracted from PPG, whereas for DL several convolutional neural networks (CNNs) have been applied to the whole PPG signals as input. The analysis has been conducted using the crowd-sourced Heart for Heart data. The prediction performance of ML using two features (AUC of 94.7%) \u2013 the a wave of the second derivative PPG and tpr, including four covariates, sex, height, weight, and smoking \u2013 was similar to that of the best performing CNN, 12-layer ResNet (AUC of 95.3%). Without having the heavy computational cost of DL, ML might be advantageous in finding potential biomarkers for HVA prediction. The whole workflow of the procedure is clearly described, and open software has been made available to facilitate replication of the results

Prediction of vascular aging based on smartphone acquired PPG signals

Photoplethysmography (PPG) measured by smartphone has the potential for a large scale, non-invasive, and easy-to-use screening tool. Vascular aging is linked to increased arterial stiffness, which can be measured by PPG. We investigate the feasibility of using PPG to predict healthy vascular aging (HVA) based on two approaches: machine learning (ML) and deep learning (DL). We performed data preprocessing, including detrending, demodulating, and denoising on the raw PPG signals. For ML, ridge penalized regression has been applied to 38 features extracted from PPG, whereas for DL several convolutional neural networks (CNNs) have been applied to the whole PPG signals as input. The analysis has been conducted using the crowd-sourced Heart for Heart data. The prediction performance of ML using two features (AUC of 94.7%) – the a wave of the second derivative PPG and tpr, including four covariates, sex, height, weight, and smoking – was similar to that of the best performing CNN, 12-layer ResNet (AUC of 95.3%). Without having the heavy computational cost of DL, ML might be advantageous in finding potential biomarkers for HVA prediction. The whole workflow of the procedure is clearly described, and open software has been made available to facilitate replication of the results

Exploiting within-breed variability in the autochthonous Reggiana breed identified several candidate genes affecting pigmentation-related traits, stature and udder defects in cattle

Autochthonous cattle breeds constitute important reservoirs of genetic diversity. Reggiana is an Italian local cattle breed reared in the north of Italy for the production of a mono-breed Parmigiano–Reggiano cheese. Reggiana cattle usually have a classical solid red coat colour and pale muzzle. As part of the strategies designed for the sustainable conservation of this genetic resource, we investigated at the genome-wise level the within-breed detected variability of three pigmentation-related traits (intensity of red coat colour, based on three classes – light/diluted, normal and dark; spotted patterns/piebaldism that sometime emerge in the breed; muzzle colour – pink/pale, grey and black), stature, presence/absence and number of supernumerary teats and teat length. A total of 1776 Reggiana cattle (about two-thirds of the extant breed population) were genotyped with the GeneSeek GGP Bovine 150k SNP array and single-marker and haplotype-based GWASs were carried out. The results indicated that two main groups of genetic factors affect the intensity of red coat colour: darkening genes (including EDN3 and a few other genes) and diluting genes (including PMEL and a few other genes). Muzzle colour was mainly determined by MC1R gene markers. Piebaldism was mainly associated with KIT gene markers. Stature was associated with BTA6 markers upstream of the NCAPG–LCORL genes. Teat defects were associated with TBX3/TBX5, MCC and LGR5 genes. Overall, the identified genomic regions not only can be directly used in selection plans in the Reggiana breed, but also contribute to clarifying the genetic mechanisms involved in determining exterior traits in cattle

Strategies for improved yield and water use efficiency of lettuce (Lactuca sativa L.) through simplified soilless cultivation under semi-arid climate

Simplified soilless cultivation (SSC) systems have globally spread as growing solutions for low fertility soil regions, low availability of water irrigation, small areas and polluted environments. In the present study, four independent experiments were conducted for assessing the applicability of SSC in the northeast of Brazil (NE-Brazil) and the central dry zone of Myanmar (CDZ-Myanmar). In the first two experiments, the potentiality for lettuce crop production and water use efficiency (WUE) in an SSC system compared to traditional on-soil cultivation was addressed. Then, the definition of how main crop features (cultivar, nutrient solution concentration, system orientation and crop position) within the SSC system affect productivity was evidenced. The adoption of SSC improved yield (+35% and +72%, in NE-Brazil and CDZ-Myanmar) and WUE (7.7 and 2.7 times higher, in NE-Brazil and CDZ-Myanmar) as compared to traditional on-soil cultivation. In NE-Brazil, an eastern orientation of the system enabled achievement of higher yield for some selected lettuce cultivars. Furthermore, in both the considered contexts, a lower concentration of the nutrient solution (1.2 vs. 1.8 dS m−1) and an upper plant position within the SSC system enabled achievement of higher yield and WUE. The experiments validate the applicability of SSC technologies for lettuce cultivation in tropical areas