On the Long Range Clustering of Global Seismicity and its Correlation With Solar Activity: A New Perspective for Earthquake Forecasting

Large earthquakes occurring worldwide have long been recognized to be non Poisson distributed, so involving some large scale correlation mechanism, which could be internal or external to the Earth. We have recently demonstrated this observation can be explained by the correlation of global seismicity with solar activity. We inferred such a clear correlation, highly statistically significant, analyzing the ISI-GEM catalog 1996–2016, as compared to the Solar and Heliospheric Observatory satellite data, reporting proton density and proton velocity in the same period. However, some questions could arise that the internal correlation of global seismicity could be mainly due to local earthquake clustering, which is a well-recognized process depending on physical mechanisms of local stress transfer. We then apply, to the ISI-GEM catalog, a simple and appropriate de-clustering procedure, meant to recognize and eliminate local clustering. As a result, we again obtain a non poissonian, internally correlated catalog, which shows the same, high level correlation with the proton density linked to solar activity. We can hence confirm that global seismicity contains a long-range correlation, not linked to local clustering processes, which is clearly linked to solar activity. Once we explain in some details the proposed mechanism for such correlation, we also give insight on how such mechanism could be used, in a near future, to help in earthquake forecasting

Characterization of single-nucleotide polymorphisms in 20 genes affecting milk quality in cattle, sheep, goat and buffalo

AbstractMilk products are important dietary sources of nutrients, providing energy, high quality proteins, and a variety of vitamins and minerals. Recent researches have focused on altering fat and protein contents of milk, in order to improve its nutrient content to more suitably reflect current dietary recommendations and trends. We characterized single nucleotide polymorphisms (SNPs) in 20 candidate genes expected to have an influence on fat composition of milk in four ruminant species (cattle, sheep, goat and buffalo). Genes belonged to different families, including transporters, fatty acid biosynthesis, receptors and enzymes for saturation/desaturation. For each gene, PCR primers were designed using bovine sequence to amplify 3 gene fragments, that covered coding and non coding regions. For each gene, we found polymorphisms in at least one species, but none that was present in homologous fragments of all four species. As expected, different SNPs were found across species, but for a very few genes. We..

Weight gain in a sample of patients affected by overweight/obesity with and without a psychiatric diagnosis during the covid-19 lockdown

The present study aimed at identifying psychological and psychosocial variables that might predict weight gain during the COVID-19 lockdown in patients affected by overweight/obesity with and without a psychiatric diagnosis. An online survey was administered between 25 April and 10 May 2020, to investigate participants’ changes in dietary habits during the lockdown period. 110 participants were recruited and allocated to two groups, 63 patients had no psychiatric diagnosis; there were 47 patients with psychiatric diagnosis. ANOVA analyses compared the groups with respect to psychological distress levels, risk perception, social support, emotion regulation, and eating behaviors. For each group, a binary logistic regression analysis was conducted, including the factors that were found to significantly differ between groups. Weight gain during lockdown was reported by 31 of the participants affected by overweight/obesity without a psychiatric diagnosis and by 31 patients with a psychiatric diagnosis. Weight gain predictors were stress and low depression for patients without a psychiatric diagnosis and binge eating behaviors for patients with a psychiatric diagnosis. Of patients without a psychiatric diagnosis, 60% reported much more frequent night eating episodes. The risk of night eating syndrome in persons affected by overweight/obesity with no psychiatric diagnosis should be further investigated to inform the development of tailored medical, psychological, and psychosocial interventions

Biological effects of a software-controlled voltage pulse generator (PhyBack PBK-2C) on the release of vascular endothelial growth factor (VEGF)

Electrical stimulation (ES) may induce vascular permeability and physiological angiogenesis. ES of rat muscles significantly increases the microvessel density and vascular endothelial growth factor (VEGF) protein levels. Thus, a pilot study was designed to analyze the effects of low-voltage electric impulses on VEGF levels in patients with dystrophic ulcers

Structure of cattle, sheep, goat and buffalo populations using single nucleotide polymorphisms in genes affecting lipid metabolism

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European cattle breed cluster accordingly to their meat quality parameters

The concept of breed is rather questionable and it's used more as a tool for "labelling" production systems than as a biological category. Here, production system is intended as a whole set of animal units, techniques, breeding schemes, marketing, etc. However, man has demonstrated to be very quick in capturing and disseminating good characteristics whence they appear in a breed by mutation or by selection. Therefore, it might be expected that breeds, nevertheless of recent origin, could bear distinguished productive characteristics. Due to the quan- titative nature of them, more characteristics should be measured in order to obtain a clear and statistically significant distinction. We have measured several meat characteristics in 15 European breeds (30 individuals for each breed), mostly with beef attitude, reared in similar conditions. This was accomplished to better reveal the genetic background of breeds. A canonical discriminant analysis showed a clear distinction among breeds. In particular lipid composition of meat was able to assign individuals to breeds with 57% and 63% of individuals correctly classified respectively for neutral and phospholipids. The classification is generally good for all breeds except for the Spanish ones,indicating probably some crossing in the past for these breeds. Neutral lipids can classify double muscled breeds with high precision (84% and 95% in Asturiana de los Valles and Piedmontese respectively). Tenderness related measures (collagen, µ-calpain, m-calpain, calpastatin, MFI) poorly assign indi- viduals to breeds (average 22%). The good classification of individuals to breeds for lipid composition suggests distinctive genetic features and encourages to look further to genetic determination of fat composition in the meat, as well as to exploit particular breeds to obtain products suitable for categories of consumers needing/searching for special components in their diet

Between and within-herd variation in blood and milk biomarkers in Holstein cows in early lactation

Both blood- and milk-based biomarkers have been analysed for decades in research settings, although often only in one herd, and without focus on the variation in the biomarkers that are specifically related to herd or diet. Biomarkers can be used to detect physiological imbalance and disease risk and may have a role in precision livestock farming (PLF). For use in PLF, it is important to quantify normal variation in specific biomarkers and the source of this variation. The objective of this study was to estimate the between- and within-herd variation in a number of blood metabolites (β-hydroxybutyrate (BHB), non-esterified fatty acids, glucose and serum IGF-1), milk metabolites (free glucose, glucose-6-phosphate, urea, isocitrate, BHB and uric acid), milk enzymes (lactate dehydrogenase and N-acetyl-β-D-glucosaminidase (NAGase)) and composite indicators for metabolic imbalances (Physiological Imbalance-index and energy balance), to help facilitate their adoption within PLF. Blood and milk were sampled from 234 Holstein dairy cows from 6 experimental herds, each in a different European country, and offered a total of 10 different diets. Blood was sampled on 2 occasions at approximately 14 days-in-milk (DIM) and 35 DIM. Milk samples were collected twice weekly (in total 2750 samples) from DIM 1 to 50. Multilevel random regression models were used to estimate the variance components and to calculate the intraclass correlations (ICCs). The ICCs for the milk metabolites, when adjusted for parity and DIM at sampling, demonstrated that between 12% (glucose-6-phosphate) and 46% (urea) of the variation in the metabolites’ levels could be associated with the herd-diet combination. Intraclass Correlations related to the herd-diet combination were generally higher for blood metabolites, from 17% (cholesterol) to approximately 46% (BHB and urea). The high ICCs for urea suggest that this biomarker can be used for monitoring on herd level. The low variance within cow for NAGase indicates that few samples would be needed to describe the status and potentially a general reference value could be used. The low ICC for most of the biomarkers and larger within cow variation emphasises that multiple samples would be needed - most likely on the individual cows - for making the biomarkers useful for monitoring. The majority of biomarkers were influenced by parity and DIM which indicate that these should be accounted for if the biomarker should be used for monitoring

Measuring CMB spectral distortions from Antarctica with COSMO: blackbody calibrator design and performance forecast

COSMO is a ground-based instrument to measure the spectral distortions (SD) of the Cosmic Microwave Background (CMB). In this paper, we present preliminary results of electromagnetic simulations of its reference blackbody calibrator. HFSS simulations provide a calibrator reflection coefficient of R∼ 10 - 6, corresponding to an emissivity ϵ= 1 - R= 0.999999. We also provide a forecast for the instrument performance by using an ILC-based simulation. We show that COSMO can extract the isotropic Comptonization parameter (modeled as | y| = 1.77 · 10 - 6) as | y| = (1.79 ± 0.19) · 10 - 6, in the presence of the main Galactic foreground (thermal dust) and of CMB anisotropies, and assuming perfect atmospheric emission removal

A second generation radiation hybrid map to aid the assembly of the bovine genome sequence

BACKGROUND: Several approaches can be used to determine the order of loci on chromosomes and hence develop maps of the genome. However, all mapping approaches are prone to errors either arising from technical deficiencies or lack of statistical support to distinguish between alternative orders of loci. The accuracy of the genome maps could be improved, in principle, if information from different sources was combined to produce integrated maps. The publicly available bovine genomic sequence assembly with 6× coverage (Btau_2.0) is based on whole genome shotgun sequence data and limited mapping data however, it is recognised that this assembly is a draft that contains errors. Correcting the sequence assembly requires extensive additional mapping information to improve the reliability of the ordering of sequence scaffolds on chromosomes. The radiation hybrid (RH) map described here has been contributed to the international sequencing project to aid this process. RESULTS: An RH map for the 30 bovine chromosomes is presented. The map was built using the Roslin 3000-rad RH panel (BovGen RH map) and contains 3966 markers including 2473 new loci in addition to 262 amplified fragment-length polymorphisms (AFLP) and 1231 markers previously published with the first generation RH map. Sequences of the mapped loci were aligned with published bovine genome maps to identify inconsistencies. In addition to differences in the order of loci, several cases were observed where the chromosomal assignment of loci differed between maps. All the chromosome maps were aligned with the current 6× bovine assembly (Btau_2.0) and 2898 loci were unambiguously located in the bovine sequence. The order of loci on the RH map for BTA 5, 7, 16, 22, 25 and 29 differed substantially from the assembled bovine sequence. From the 2898 loci unambiguously identified in the bovine sequence assembly, 131 mapped to different chromosomes in the BovGen RH map. CONCLUSION: Alignment of the BovGen RH map with other published RH and genetic maps showed higher consistency in marker order and chromosome assignment than with the current 6× sequence assembly. This suggests that the bovine sequence assembly could be significantly improved by incorporating additional independent mapping information

Prediction of key milk biomarkers in dairy cows through milk MIR spectra and international collaborations.

peer reviewedAt the individual cow level, sub-optimum fertility, mastitis, negative energy balance and ketosis are major issues in dairy farming. These problems are widespread on dairy farms and have an important economic impact. The objectives of this study were: 1) to assess the potential of milk Mid Infrared (MIR) spectra to predict key biomarkers of energy deficit (citrate, isocitrate, glucose-6P, free glucose), ketosis (BHB and acetone), mastitis (NAGase and LDH), and fertility (progesterone); 2) to test alternative methodologies to partial least square regression (PLS) to better account for the specific asymmetric distribution of the biomarkers; and 3) to create robust models by merging large data sets from 5 international or national projects. Benefiting from this international collaboration, the data set comprised a total of 9,143 milk samples from 3,758 cows located in 589 herds across 10 countries and represented 7 breeds. The samples were analyzed by reference chemistry for biomarker contents while the MIR analyses were performed on 30 instruments from different models and brands, with spectra harmonized into a common format. Four quantitative methodologies were evaluated to address the strongly skewed distribution of some biomarkers. PLS was used as the reference basis, and compared with a random modification of distribution associated with PLS (Random-downsampling-PLS), an optimized modification of distribution associated with PLS (KennardStone-downsampling-PLS) and Support Vector Machine (SVM). When the ability of MIR to predict biomarkers was too low for quantification, different qualitative methodologies were tested to discriminate low vs high values of biomarkers. For each biomarker, 20% of the herds were randomly removed within all countries to be used as the validation data set. The remaining 80% of herds were used as the calibration data set. In calibration, the 3 alternative methodologies outperform the PLS performances for the majority of biomarkers. However, in the external herd validation, PLS provided the best results for isocitrate, glucose-6P, free glucose and LDH (R2v = 0.48, 0.58, 0.28, and 0.24). For other molecules, PLS-Random-downsampling and PLS-KennardStone-downsampling outperformed PLS in the majority of cases, but the best results were provided by SVM for citrate, BHB, acetone, NAGase and progesterone (R2v = 0.94, 0.58, 0.76, 0.68, and 0.15). Hence, PLS and SVM based on the entire data set provided the best results for normal and skewed distributions, respectively. Complementary to the quantitative methods, the qualitative discriminant models enabled the discrimination of high and low values for BHB, acetone, and NAGase with a global accuracy around 90%, and glucose-6P with an accuracy of 83%. In conclusion, MIR spectra of milk can enable quantitative screening of citrate as a biomarker of energy deficit and discrimination of low and high values of BHB, acetone, and NAGase, as biomarkers of ketosis and mastitis. Finally, progesterone could not be predicted with sufficient accuracy from milk MIR spectra to be further considered. Consequently, MIR spectrometry can bring valuable information regarding the occurrence of energy deficit, ketosis and mastitis in dairy cows, which in turn have major influences on their fertility and survival