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Estimation of the level of durum wheat germplasm genetic diversity is important for its classification and efficient use in breeding programmes. The aim of this study was to assess genetic diversity of durum wheat genotypes developed at the Institute of Field and Vegetable Crops in Novi Sad, Serbia, with 26 morphological characteristics based on the International Union for Protection of New Varieties of Plants guidelines. The Shannon diversity index was used as an indicator of morphological diversity and it ranged from 0.283 for glaucosity of lower side of the flag leaf blade and density of hairiness of uppermost node of the culm, to 0.950 for the ear colour, with the mean value of 0.616, indicating a medium to high level of morphological diversity. On average, the diversity was higher for traits relating to generative organs than for those associated with vegetative plant organs. The 21 morphological characteristics were sufficient to distinguish unique profiles of all durum wheat genotypes. The estimation of varietal diversity and identification of morphological characteristics with the highest discriminative power were done by multiple correspondence analysis. The traits that contributed the most to the distinction of genotypes were the ear colouration, length of beak of the lower glume, lower glume shape, ear length of awns at tip relative to ear length and colour of awns. Morphological characterization using the traits with the highest discriminative power could be a useful complementary method for durum wheat germplasm classification and diversity analysis. Ocena genetičke raznolikosti germplazme tvrde pšenice je važna za njenu klasifikaciju i efikasno korišćenje u oplemenjivačkim programma. Cilj ovog rada bio je da se proceni genetička raznolikost genotipova tvrde pšenice stvorenih u Institutu za ratarstvo i povrtarstvo u Novom Sadu, sa 26 morfoloških osobina prema uputstvu Međunarodne unije za zaštitu novih biljnih sorti (UPOV). Šenonov indeks diverziteta je korišćen kao indikator morfološke raznolikosti i kretao se od 0,283 za prevlaku na rukavcu zastavičara i dlakavosti vršne internodije, do 0,950 za boju klasa. Prosečna vrednost Šenonovog indeksa od 0,616 ukazuje na srednje visok nivo morfološke raznolikosti. U proseku, raznovrsnost je bila veća za osobine koje se odnose na generativne biljne organe nego za vegetativne. Utvrđeno je da je 21 morfološka osobina bila dovoljna za razlikovanje jedinstvenih profila svih genotipova tvrde pšenice. Procena sortne raznolikosti i identifikacija morfoloških osobina sa najvećim diskriminativnim vrednostima je urađena pomoću višestruke korespodentne analize. Osobine koje su najviše doprinele razlikovanju genotipova su bile: boja klasa, dužina zadnje strane glume, oblik donje glume, odnos dužine osja i klasa, kao i boja osja. Morfološka karakterizacija pomoću osobina sa najvećim diskriminativnim vrednostima može biti korisna dopunska metoda za klasifikaciju i analizu diverziteta germplazme tvrde pšenice.

The production of the first permanent, publicly available sunflower (Helianthus annuus L.) association mapping population (UGA-SAM1) provided material to test the usability of morphological descriptors for discriminating germplasm accessions. The objective of this study was to evaluate the phenotypic diversity in the UGA-SAM1 population and evaluate the usefulness of qualitative traits for the discrimination of genotypes. The SAM1 population consists of 285 accessions characterized for 20 morphological traits. The Shannon–Weaver diversity index (H′) was used to determine phenotypic diversity, whereas HOMALS (homogeneity analysis by alternating least squares) and association statistics were used to determine discriminative power of the descriptors. Phenotypic diversity was moderately high for the traits (0.74). The highest diversity was found in the less developed genotypes followed by non-oil genotypes. Pronounced associations in individual genotype groups and category traits, most notably for the maturity trait in the restorer line (RHA) oil group, resulted in both high association and diversity index values. The association test proved to be a useful addition to HOMALS analysis for determining the trait discriminative power. Adequate selection of traits used in germplasm evaluation can improve the efficiency of breeding programs, whereas the loss of variability could be lowered if diversity focused traits were used including leaf, seed, and certain flower traits, instead of only focusing on yield and quality. This is the peer-reviewed version of the following article: Terzić S., Zorić M., Seiler G. Qualitative traits in sunflower breeding: UGA-SAM1 phenotyping case study. Crop Science 2020, 60 (1), 303 – 319. [https://doi.org/10.1002/csc2.20059]

Probing food experience or liking through verbal ratings has its shortcomings. We compare explicit ratings to a range of (neuro)physiological and behavioral measures with respect to their performance in distinguishing drinks associated with different emotional experience. Seventy participants tasted and rated the valence and arousal of eight regular drinks and a &ldquo, ground truth&rdquo, high-arousal, low-valence vinegar solution. The discriminative power for distinguishing between the vinegar solution and the regular drinks was highest for sip size, followed by valence ratings, arousal ratings, heart rate, skin conductance level, facial expression of &ldquo, disgust,&rdquo, pupil diameter, and Electroencephalogram (EEG) frontal alpha asymmetry. Within the regular drinks, a positive correlation was found between rated arousal and heart rate, and a negative correlation between rated arousal and Heart Rate Variability (HRV). Most physiological measures showed consistent temporal patterns over time following the announcement of the drink and taking a sip. This was consistent over all nine drinks, but the peaks were substantially higher for the vinegar solution than for the regular drinks, likely caused by emotion. Our results indicate that implicit variables have the potential to differentiate between drinks associated with different emotional experiences. In addition, this study gives us insight into the physiological temporal response patterns associated with taking a sip.

Arousal systems are one of the recently announced NIMH Research Domain Criteria to inform future diagnostics and treatment prediction. In major depressive disorder (MDD), altered central nervous system (CNS) wakefulness regulation and an increased sympathetic autonomic nervous system (ANS) activity have been identified as biomarkers with possible discriminative value for prediction of antidepressant treatment response. Therefore, the hypothesis of a more pronounced decline of CNS and ANS-arousal being predictive for a positive treatment outcome to selective-serotonin-reuptake-inhibitor (SSRI) treatment was derived from a small, independent exploratory dataset (N = 25) and replicated using data from the randomized international Study to Predict Optimized Treatment Response in Depression (iSPOT-D). There, 1008 MDD participants were randomized to either a SSRI (escitalopram or sertraline) or a serotonin-norepinephrine-reuptake-inhibitor (SNRI-venlafaxine) arm. Treatment response was established after eight weeks using the 17-item Hamilton Rating Scale for Depression. CNS-arousal (i.e. electroencephalogram-vigilance), ANS-arousal (heart rate) and their change across time were assessed during rest. Responders and remitters to SSRI treatment were characterized by a faster decline of CNS-arousal during rest whereas SNRI responders showed a significant increase of ANS-arousal. Furthermore, SSRI responders/remitters showed an association between ANS- and CNS-arousal regulation in comparison to non-responders/non-remitters while this was not the case for SNRI treatment arm. Since positive treatment outcome to SSRI and SNRI was linked to distinct CNS and ANS-arousal profiles, these predictive markers probably are not disorder specific alterations but reflect the responsiveness of the nervous system to specific drugs. (C) 2015 Elsevier Ltd. All rights reserved.

Background Neuroinflammation has gained increasing attention as a potential contributing factor in Alzheimer’s disease (AD) pathology. A clinical cerebrospinal fluid biomarker capable of monitoring this process during the course of the disease has yet to emerge, chiefly owing to contradictory research findings. In this study, we sought to clarify the utility of inflammatory biomarkers in diagnostic procedures of AD in three steps: (1) to screen for proteins that are robustly detectable in cerebrospinal fluid; (2) based on this analysis, to explore any associations between the analytically robust markers and salient pathological features of AD; and (3) to determine the discriminative power of these markers in the clinical diagnosis of AD. Methods From a total of 46 proteins, 15 that were robustly detectable in cerebrospinal fluid were identified. A subsequent analysis of these markers in a cohort of 399 patients (nondemented subjects, patients with mild cognitive impairment [MCI], and patients with AD, supplemented by smaller cohorts of other diseases) was conducted. Fluid biomarker data were related to AD pathology and neuropsychological markers and adjusted for confounders such as age, sex, apolipoprotein E genotype, and biobank storage time. Results Cerebrospinal fluid levels of C-reactive protein and soluble TREM2 differed between nondemented subjects, patients with MCI, or patients with AD and were associated with amyloid and tau pathology. Several markers were associated with tau pathology only or with other neurodegenerative diseases. Correlations between neuropsychological performance and inflammatory markers were weak, but they were most prominent in AD and for the most challenging cognitive tests. All investigated covariates had significant influence, with varying effects across the markers. Still, none of the markers achieved discriminative power of more than 70% to distinguish between patient groups defined by clinical or neuropathological categories. Conclusions Basic analytical considerations proved indispensable for this type of study because only one-third of the tested markers were robustly detectable in cerebrospinal fluid. Detectable inflammatory protein markers were associated in multiple ways with AD pathology. Yet, even significantly associated markers were not powerful enough in terms of effect strength, sensitivity, and specificity, and hence they were not suited for direct use in clinical diagnostic practice. Targets other than those most commonly considered in this field of research might provide results with better clinical applicability. Electronic supplementary material The online version of this article (10.1186/s13195-018-0353-3) contains supplementary material, which is available to authorized users.

AIMS/HYPOTHESIS: We determined whether single nucleotide polymorphisms (SNPs) previously associated with diabetogenic traits improve the discriminative power of a type 2 diabetes genetic risk score. METHODS: Participants (n = 2,751) were genotyped for 73 SNPs previously associated with type 2 diabetes, fasting glucose/insulin concentrations, obesity or lipid levels, from which five genetic risk scores (one for each of the four traits and one combining all SNPs) were computed. Type 2 diabetes patients and non-diabetic controls (n = 1,327/1,424) were identified using medical records in addition to an independent oral glucose tolerance test. RESULTS: Model 1, including only SNPs associated with type 2 diabetes, had a discriminative power of 0.591 (p < 1.00 x 10(-20) vs null model) as estimated by the area under the receiver operator characteristic curve (ROC AUC). Model 2, including only fasting glucose/insulin SNPs, had a significantly higher discriminative power than the null model (ROC AUC 0.543; p = 9.38 x 10(-6) vs null model), but lower discriminative power than model 1 (p = 5.92 x 10(-5)). Model 3, with only lipid-associated SNPs, had significantly higher discriminative power than the null model (ROC AUC 0.565; p = 1.44 x 10(-9)) and was not statistically different from model 1 (p = 0.083). The ROC AUC of model 4, which included only obesity SNPs, was 0.557 (p = 2.30 x 10(-7) vs null model) and smaller than model 1 (p = 0.025). Finally, the model including all SNPs yielded a significant improvement in discriminative power compared with the null model (p < 1.0 x 10(-20)) and model 1 (p = 1.32 x 10(-5)); its ROC AUC was 0.626. CONCLUSIONS/INTERPRETATION: Adding SNPs previously associated with fasting glucose, insulin, lipids or obesity to a genetic risk score for type 2 diabetes significantly increases the power to discriminate between people with and without clinically manifest type 2 diabetes compared with a model including only conventional type 2 diabetes loci.