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Introduction The diagnosis of psychoactive substance use disorders has been based primarily on descriptive, symptomatic checklist criteria. In opioid addiction, there are no objective biological indicators specific enough to guide diagnosis, monitor disease status, and evaluate efficacy of therapeutic interventions. Proton magnetic resonance spectroscopy (1H MRS) of the brain has potential to identify and quantify biomarkers for the diagnosis of opioid dependence. The purpose of this study was to detect the absolute glutamate concentration in the nucleus accumbens (NAc) of patients with prescription opioid dependence using 1H MRS, and to analyze its clinical associations. Methods Twenty patients with clinically diagnosed definitive prescription opioid dependent (mean age = 26.5 ± 4.3 years) and 20 matched healthy controls (mean age = 26.1 ± 3.8 years) participated in this study. Patients were evaluated with the Barratt Impulsiveness Scale (BIS‐11), the Self‐Rating Anxiety Scale (SAS), and the opiate Addiction Severity Inventory (ASI). We used point‐resolved spectroscopy to quantify the absolute concentrations of metabolites (glutamate, choline, N‐acetylaspartate, glutamine, creatine) within the NAc. The difference between metabolite levels of groups and Pearson's correlation between glutamate levels and psychometric scores in patients were analyzed statistically. Results Glutamate concentrations in the NAc were significantly higher in prescription opiate addicts than in controls (t = 3.84, p = .001). None of the other metabolites differed significantly between the two groups (all ps > .05). The glutamate concentrations correlated positively with BIS‐11 scores in prescription opiate addicts (r = .671, p = .001), but not with SAS score and ASI index. Conclusions Glutamate levels in the NAc measured quantitatively with in vivo 1H MRS could be used as a biomarker to evaluate disease condition in opioid‐dependent patients.

A calcineurin B-like protein-interacting protein kinases (CIPK) gene was cloned (EU 424058) from a thermo-sensitive genic self-incompatibility (TSGI) line, HE97, in maize, which was selected for suppression subtractive hybridization (SSH) library of the self-incompatible and self-compatible silks of the TSGI line under different temperatures. The full-length cDNA of the candidate CIPK-like gene consisted of 1 918 nucleotides and contained a 1332-bp open reading frame in maize. Real-time PCR indicated that the candidate CIPK-like gene was highly expressed in the self-incompatible pollen of the TGSI line, and promoted elevated levels of calcium (Ca 2+ ). High Ca 2+ concentrations in the pollen strongly inhibit pollen tube formation in silk of the same plant, thus inducing self-incompatibility (SI) under high temperature. These results implied that the CIPKs-like gene would play an important role in the regulation of HE97 characteristics under different temperatures, perhaps acting as a secondary messenger in the expression of SI in the TGSI line in maize.

Heterosis is observed for most phenotypic traits and developmental stages in many plants. In this study, the embryos, from germinating seeds after 24 h of soaking, for five elite maize hybrids and their parents were selected to unravel the genetic basis of heterosis using 2-D proteomic method. In total, 257 (80.06%), 363 (58.74%), 351 (79.95%), 242 (54.50%), and 244 (46.30%) nonadditively expressed proteins were identified in hybrids Zhengdan 958, Nongda 108, Yuyu 22, Xundan 20, and Xundan 18, respectively. The nonadditive proteins were divided into above high-parent (++; 811, 55.66%), high-parent (+; 121, 8.30%), partial dominance (+-; 249, 17.09%), low-parent (-; 30, 2.06%), below low-parent (- -; 62, 4.26%), and D (different; 184, 12.63%) expression patterns. The observed patterns indicate the important roles of dominance, partial dominance, and overdominance in regulating seed germination in maize. Additionally, 54 different proteins were identified by mass spectrometry and classified into nine functional groups: metabolism (9), cell detoxification (8), unknown functional proteins (8), chaperones (7), signal transduction (6), development process (5), other (5), transporter (3), and stress response (3). Of these, the most interesting are those involved with germination-related hormone signal transduction and the abscisic acid and gibberellin regulation networks.

In this study, we describe a novel ecological self-incompatibility (SI) line HE97 in maize. The main environmental factors influencing the inbred line characteristics were identified through field sowing trials during a two-year study period (2001 and 2002). The results showed that daily minimum temperature had the greatest effect on floral morphology and breeding system of the SI line. In staminate floret differentiation, when the daily minimum temperature exceeded 24°C, the line exhibited complete self-compatibility; however SI was observed when the daily minimum temperature was below 20°C. Therefore, we characterized the line as exhibiting thermo-sensitive genic self-incompatibility (TGSI). A set of F2 and F2:3 populations, derived from the inbred lines HE97 and Z58, were evaluated for two years to elucidate the TGSI line patterns of inheritance. Classical genetic analyses and QTL mapping results revealed that HE97 self-incompatibility was governed by a single allele, named here astgsi1. Thetgsi1 gene was mapped to chromosome 2 between SSR markers nc131 and bnlg1633, with a distance of 2.40 cM from nc131 and 2.44 cM from bnlg1633.

The QTL mapping results were compared with the genotypically selected and random samples of the same size on the base of a RIL population. The results demonstrated that there were no obvious differences in the trait distribution and marker segregation distortion between the genotypically selected and random samples with the same population size. However, a significant increase in QTL detection power, sensitivity, specificity, and QTL resolution in the genotypically selected samples were observed. Moreover, the highly significant effect was detected in small size of genotypically selected samples. In QTL mapping, phenotyping is a more sensitive limiting factor than genotyping so that the selection of samples could be an attractive strategy for increasing genome-wide QTL mapping resolution. The efficient selection of samples should be more helpful for QTL maker assistant selection, fine mapping, and QTL cloning.

Introduction The diagnosis of psychoactive substance use disorders has been based primarily on descriptive, symptomatic checklist criteria. In opioid addiction, there are no objective biological indicators specific enough to guide diagnosis, monitor disease status, and evaluate efficacy of therapeutic interventions. Proton magnetic resonance spectroscopy (1H MRS) of the brain has potential to identify and quantify biomarkers for the diagnosis of opioid dependence. The purpose of this study was to detect the absolute glutamate concentration in the nucleus accumbens (NAc) of patients with prescription opioid dependence using 1H MRS, and to analyze its clinical associations. Methods Twenty patients with clinically diagnosed definitive prescription opioid dependent (mean age = 26.5 ± 4.3 years) and 20 matched healthy controls (mean age = 26.1 ± 3.8 years) participated in this study. Patients were evaluated with the Barratt Impulsiveness Scale (BIS-11), the Self-Rating Anxiety Scale (SAS), and the opiate Addiction Severity Inventory (ASI). We used point-resolved spectroscopy to quantify the absolute concentrations of metabolites (glutamate, choline, N-acetylaspartate, glutamine, creatine) within the NAc. The difference between metabolite levels of groups and Pearson's correlation between glutamate levels and psychometric scores in patients were analyzed statistically. Results Glutamate concentrations in the NAc were significantly higher in prescription opiate addicts than in controls (t = 3.84, p = .001). None of the other metabolites differed significantly between the two groups (all ps > .05). The glutamate concentrations correlated positively with BIS-11 scores in prescription opiate addicts (r = .671, p = .001), but not with SAS score and ASI index. Conclusions Glutamate levels in the NAc measured quantitatively with in vivo 1H MRS could be used as a biomarker to evaluate disease condition in opioid-dependent patients.