The 6 main milk proteins in cattle are encoded by highly polymorphic genes characterized by several nonsynonymous and synonymous mutations, with up to 47 protein variants identified. Such an extensive variation was used for linkage analysis with the description of the casein cluster more than 30 yr ago and has been applied to animal breeding for several years. Casein haplotype effects on productive traits have been investigated considering information on the whole casein complex. Moreover, mutations within the noncoding sequences have been shown to affect the specific protein expression and, as a consequence, milk composition and cheesemaking. Milk protein variants are also a useful tool for breed characterization, diversity, and phylogenetic studies. In addition, they are involved in various aspects of human nutrition. First, the occurrence of alleles associated with a reduced content of different caseins might be exploited for the production of milk with particular nutritional qualities; that is, hypoallergenic milk. On the other hand, the frequency of these alleles can be decreased by selection of sires using simple DNA tests, thereby increasing the casein content in milk used for cheesemaking. Furthermore, the biological activity of peptides released from milk protein digestion can be affected by amino acid exchanges or deletions resulting from gene mutations. Finally, the gene-culture coevolution between cattle milk protein genes and human lactase genes, which has been recently highlighted, is impressive proof of the nonrandom occurrence of milk protein genetic variation over the centuries.

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[18F]-fluorodeoxyglucose (FDG) Positron Emission Tomography (PET) is a widely used diagnostic tool that can detect and quantify pathophysiology, as assessed through changes in cerebral glucose metabolism. [18F]-FDG PET scans can be analyzed using voxel-based statistical methods such as Statistical Parametric Mapping (SPM) that provide statistical maps of brain abnormalities in single patients. In order to perform SPM, a "spatial normalization" of an individual's PET scan is required to match a reference PET template. The PET template currently used for SPM normalization is based on [15O]-H2O images and does not resemble either the specific metabolic features of [18F]-FDG brain scans or the specific morphological characteristics of individual brains affected by neurodegeneration. Thus, our aim was to create a new [18F]-FDG PET aging and dementia-specific template for spatial normalization, based on images derived from both age-matched controls and patients. We hypothesized that this template would increase spatial normalization accuracy and thereby preserve crucial information for research and diagnostic purposes. We investigated the statistical sensitivity and registration accuracy of normalization procedures based on the standard and new template-at the single-subject and group level-independently for subjects with Mild Cognitive Impairment (MCI), probable Alzheimer's Disease (AD), Frontotemporal lobar degeneration (FTLD) and dementia with Lewy bodies (DLB). We found a significant statistical effect of the population-specific FDG template-based normalisation in key anatomical regions for each dementia subtype, suggesting that spatial normalization with the new template provides more accurate estimates of metabolic abnormalities for single-subject and group analysis, and therefore, a more effective diagnostic measure.

The core biomarker pattern is in line with the current pathophysiologic model of AD. Fully normal and fully abnormal pattern is associated with exceptional and universal development of dementia. Cases not in line might be due to atypical neurobiology or inaccurate thresholds for biomarker (ab)normality.

Objectives To evaluate the inter-rater agreement of chest X-ray (CXR) findings in coronavirus disease 2019 (COVID-19) and to determine the value of initial CXR along with demographic, clinical, and laboratory data at emergency department (ED) presentation for predicting mortality and the need for ventilatory support. Methods A total of 340 COVID-19 patients who underwent CXR in the ED setting (March 1–13, 2020) were retrospectively included. Two reviewers independently assessed CXR abnormalities, including ground-glass opacities (GGOs) and consolidation. Two scoring systems (Brixia score and percentage of lung involvement) were applied. Inter-rater agreement was assessed by weighted Cohen’s kappa (κ) or intraclass correlation coefficient (ICC). Predictors of death and respiratory support were identified by logistic or Poisson regression. Results GGO admixed with consolidation (n = 235, 69%) was the most common CXR finding. The inter-rater agreement was almost perfect for type of parenchymal opacity (κ = 0.90), Brixia score (ICC = 0.91), and percentage of lung involvement (ICC = 0.95). The Brixia score (OR: 1.19; 95% CI: 1.06, 1.34; p = 0.003), age (OR: 1.16; 95% CI: 1.11, 1.22; p < 0.001), PaO2/FiO2 ratio (OR: 0.99; 95% CI: 0.98, 1; p = 0.002), and cardiovascular diseases (OR: 3.21; 95% CI: 1.28, 8.39; p = 0.014) predicted death. Percentage of lung involvement (OR: 1.02; 95% CI: 1.01, 1.03; p = 0.001) and PaO2/FiO2 ratio (OR: 0.99; 95% CI: 0.99, 1.00; p < 0.001) were significant predictors of the need for ventilatory support. Conclusions CXR is a reproducible tool for assessing COVID-19 and integrates with patient history, PaO2/FiO2 ratio, and SpO2 values to early predict mortality and the need for ventilatory support. Key Points • Chest X-ray is a reproducible tool for assessing COVID-19 pneumonia. • The Brixia score and percentage of lung involvement on chest X-ray integrate with patient history, PaO2/FIO2ratio, and SpO2values to early predict mortality and the need for ventilatory support in COVID-19 patients presenting to the emergency department.

Objectives: The aim of this study was to investigate predictors of progressive cognitive deterioration in patients with suspected non-Alzheimer disease pathology (SNAP) and mild cognitive impairment (MCI). Methods:We measured markers of amyloid pathology (CSF b-amyloid 42) and neurodegeneration (hippocampal volume on MRI and cortical metabolism on [18 F]-fluorodeoxyglucose-PET) in 201 patients with MCI clinically followed for up to 6 years to detect progressive cognitive deterioration. We categorized patients with MCI as A1/A2 and N1/N2 based on presence/absence of amyloid pathology and neurodegeneration. SNAPs were A2N1 cases.Results: The proportion of progressors was 11% (8/41), 34% (14/41), 56% (19/34), and 71%(60/85) in A2N2, A1N2, SNAP, and A1N1, respectively; the proportion of APOE e4 carriers was 29%, 70%, 31%, and 71%, respectively, with the SNAP group featuring a significantly different proportion than both A1N2 and A1N1 groups (p # 0.005). Hypometabolism in SNAP patients was comparable to A1N1 patients (p 5 0.154), while hippocampal atrophy was more severe in SNAP patients (p 5 0.002). Compared with A2N2, SNAP and A1N1 patients had significant risk of progressive cognitive deterioration (hazard ratio 5 2.7 and 3.8, p 5 0.016 and p , 0.001), while A1N2 patients did not (hazard ratio 5 1.13, p 5 0.771). In A1N2 and A1N1 groups, none of the biomarkers predicted time to progression. In the SNAP group, lower time to progression was correlated with greater hypometabolism (r 5 0.42, p 5 0.073). The amyloid cascade hypothesis 1,2 has so far dominated the Alzheimer disease (AD) field. Jack et al. Conclusions:3,4 proposed a dynamic model that relates disease stage to the best established biomarkers of AD pathology. Based on this, a National Institute on Aging-Alzheimer's Association task force developed recommendations for the diagnosis of preclinical AD based on biomarkers of amyloidosis and neuronal injury.5 Soon afterward, these criteria were operationalized and a

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The analysis of casein polymorphisms in goat species is rather difficult, because of a large number of mutations at each locus, and the tight linkage involving the 4 casein genes. Three goat breeds from Northern Italy, Orobica, Verzasca, and Frisa, were analyzed at the casein complex by milk isoelectrofocusing and analyses at the DNA level to identify the majority of all known polymorphisms. The casein gene structure of the 3 local breeds at alpha(S1)-casein (CSN1S1), beta-casein (CSN2), alpha(S2)-casein (CSN1S2), and kappa-casein (CSN3) was compared with that of Camosciata, a more widely distributed breed. A new allele was identified and characterized at CSN2 gene, which seemed to be specific to the Frisa breed. It was named CSN2*E, and was characterized by a transversion TCT --> TAT responsible for the amino acid exchange Ser(166) --> Tyr(166) in the mature protein. The casein haplotype structure is highly different among breeds. A total of 26 haplotypes showed a frequency higher than 0.01 in at least 1 of the 4 breeds considered, with 12, 3, 5, and 19 haplotypes in Frisa, Orobica, Verzasca, and Camosciata breeds, respectively. Only 13 haplotypes occurred at a frequency higher than 0.05 in at least 1 breed. With the molecular knowledge of each locus, the ancestral haplotype coding for CSN1S1*B, CSN2*A, CSN1S2*A, and CSN3*B protein variants can be postulated. A protein evolutionary model considering the whole casein haplotype is proposed.