Single-run separation of closely related cationic and anionic compounds by CE-ESI-MS: application to the simultaneous analysis of melamine and its analogs in milk

In recent years, two adulteration incidents concerning the addition of melamine, a nitrogen-rich industrial small polar compound, to pet food and infant formula products have occurred in China. These issues prompted laboratories to develop methods for the analysis of melamine and related compounds in a wide variety of food products and ingredients. In this context, a CE-ESI-MS method was developed to simultaneously analyze melamine and its related products (ammeline, ammelide and cyanuric acid) that possess close physico-chemical properties. This method allows the simultaneous analysis of both cations and anions in a single run, using CE to divide the run into two time segments in normal polarity mode. For this purpose, ESI polarity was switched once during the run, increasing sensitivity and data quality. The method was applied to spiked powdered milk and melamine-contaminated powdered milk, with two sample preparation procedures

Single-run separation of closely related cationic and anionic compounds by CE-ESI-MS: application to the simultaneous analysis of melamine and its analogs in milk

In recent years, two adulteration incidents concerning the addition of melamine, a nitrogen-rich industrial small polar compound, to pet food and infant formula products have occurred in China. These issues prompted laboratories to develop methods for the analysis of melamine and related compounds in a wide variety of food products and ingredients. In this context, a CE-ESI-MS method was developed to simultaneously analyze melamine and its related products (ammeline, ammelide and cyanuric acid) that possess close physico-chemical properties. This method allows the simultaneous analysis of both cations and anions in a single run, using CE to divide the run into two time segments in normal polarity mode. For this purpose, ESI polarity was switched once during the run, increasing sensitivity and data quality. The method was applied to spiked powdered milk and melamine-contaminated powdered milk, with two sample preparation procedures

Neuropsychological and neurophysiological correlates of fatigue in post-acute patients with neurological manifestations of COVID-19: Insights into a challenging symptom

More than half of patients who recover from COVID-19 experience fatigue. We studied fatigue using neuropsychological and neurophysiological investigations in post-COVID-19 patients and healthy subjects. Neuropsychological assessment included: Fatigue Severity Scale (FSS), Fatigue Rating Scale, Beck Depression Inventory, Apathy Evaluation Scale, cognitive tests, and computerized tasks. Neurophysiological examination was assessed before (PRE) and 2 min after (POST) a 1-min fatiguing isometric pinching task and included: maximum compound muscle action potential (CMAP) amplitude in first dorsal interosseous muscle (FDI) following ulnar nerve stimulation, resting motor threshold, motor evoked potential (MEP) amplitude and silent period (SP) duration in right FDI following transcranial magnetic stimulation of the left motor cortex. Maximum pinch strength was measured. Perceived exertion was assessed with the Borg-Category-Ratio scale. Patients manifested fatigue, apathy, executive deficits, impaired cognitive control, and reduction in global cognition. Perceived exertion was higher in patients. CMAP and MEP were smaller in patients both PRE and POST. CMAP did not change in either group from PRE to POST, while MEP amplitudes declined in controls POST. SP duration did not differ between groups PRE, increased in controls but decreased in patients POST. Patients' change of SP duration from PRE to POST was negatively correlated to FSS. Abnormal SP shortening and lack of MEP depression concur with a reduction in post-exhaustion corticomotor inhibition, suggesting a possible GABAB-ergic dysfunction. This impairment might be related to the neuropsychological alterations. COVID-19-associated inflammation might lead to GABAergic impairment, possibly representing the basis of fatigue and explaining apathy and executive deficits

Dopamine replacement therapy, learning and reward prediction in Parkinson’s disease: Implications for rehabilitation

The principal feature of Parkinson’s disease (PD) is the impaired ability to acquire and express habitual-automatic actions due to the loss of dopamine in the dorsolateral striatum, the region of the basal ganglia associated with the control of habitual behavior. Dopamine replacement therapy (DRT) compensates for the lack of dopamine, representing the standard treatment for different motor symptoms of PD (such as rigidity, bradykinesia and resting tremor). On the other hand, rehabilitation treatments, exploiting the use of cognitive strategies, feedbacks and external cues, permit to “learn to bypass” the defective basal ganglia (using the dorsolateral area of the prefrontal cortex) allowing the patients to perform correct movements under executive-volitional control. Therefore, DRT and rehabilitation seem to be two complementary and synergistic approaches. Learning and reward are central in rehabilitation: both of these mechanisms are the basis for the success of any rehabilitative treatment. Anyway, it is known that “learning resources” and reward could be negatively influenced from dopaminergic drugs. Furthermore, DRT causes different well-known complications: among these, dyskinesias, motor fluctuations, and dopamine dysregulation syndrome (DDS) are intimately linked with the alteration in the learning and reward mechanisms and could impact seriously on the rehabilitative outcomes. These considerations highlight the need for careful titration of DRT to produce the desired improvement in motor symptoms while minimizing the associated detrimental effects. This is important in order to maximize the motor re-learning based on repetition, reward and practice during rehabilitation. In this scenario, we review the knowledge concerning the interactions between DRT, learning and reward, examine the most impactful DRT side effects and provide suggestions for optimizing rehabilitation in PD. � 2016 Ferrazzoli, Carter, Ustun, Palamara, Ortelli, Maestri, Y�cel and Frazzitta

A new statistical model for binge drinking pattern classification in college-student populations

BackgroundBinge drinking (BD) among students is a frequent alcohol consumption pattern that produces adverse consequences. A widely discussed difficulty in the scientific community is defining and characterizing BD patterns. This study aimed to find homogenous drinking groups and then provide a new tool, based on a model that includes several key factors of BD, to assess the severity of BD regardless of the individual’s gender.MethodsUsing the learning sample (N1 = 1,271), a K-means clustering algorithm and a partial proportional odds model (PPOM) were used to isolate drinking and behavioral key factors, create homogenous groups of drinkers, and estimate the probability of belonging to these groups. Robustness of our findings were evaluated with Two validations samples (N2 = 2,310, N3 = 120) of French university students (aged 18–25 years) were anonymously investigated via demographic and alcohol consumption questionnaires (AUDIT, AUQ, Alcohol Purchase Task for behavioral economic indices).ResultsThe K-means revealed four homogeneous groups, based on drinking profiles: low-risk, hazardous, binge, and high-intensity BD. The PPOM generated the probability of each participant, self-identified as either male or female, to belong to one of these groups. Our results were confirmed in two validation samples, and we observed differences between the 4 drinking groups in terms of consumption consequences and behavioral economic demand indices.ConclusionOur model reveals a progressive severity in the drinking pattern and its consequences and may better characterize binge drinking among university student samples. This model provides a new tool for assessing the severity of binge drinking and illustrates that frequency of drinking behavior and particularly drunkenness are central features of a binge drinking model

Optimization of cognitive assessment in Parkinsonisms by applying artificial intelligence to a comprehensive screening test.

The assessment of cognitive deficits is pivotal for diagnosis and management in patients with parkinsonisms. Low levels of correspondence are observed between evaluations assessed with screening cognitive tests in comparison with those assessed with in-depth neuropsychological batteries. A new tool, we named CoMDA (Cognition in Movement Disorders Assessment), was composed by merging Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Frontal Assessment Battery (FAB). In total, 500 patients (400 with Parkinson's disease, 41 with vascular parkinsonism, 31 with progressive supranuclear palsy, and 28 with multiple system atrophy) underwent CoMDA (level 1-L1) and in-depth neuropsychological battery (level 2-L2). Machine learning was developed to classify the CoMDA score and obtain an accurate prediction of the cognitive profile along three different classes: normal cognition (NC), mild cognitive impairment (MCI), and impaired cognition (IC). The classification accuracy of CoMDA, assessed by ROC analysis, was compared with MMSE, MoCA, and FAB. The area under the curve (AUC) of CoMDA was significantly higher than that of MMSE, MoCA and FAB (p < 0.0001, p = 0.028 and p = 0.0007, respectively). Among 15 different algorithmic methods, the Quadratic Discriminant Analysis algorithm (CoMDA-ML) showed higher overall-metrics performance levels in predictive performance. Considering L2 as a 3-level continuous feature, CoMDA-ML produces accurate and generalizable classifications: micro-average ROC curve, AUC = 0.81; and AUC = 0.85 for NC, 0.67 for MCI, and 0.83 for IC. CoMDA and COMDA-ML are reliable and time-sparing tools, accurate in classifying cognitive profile in parkinsonisms.This study has been registered on ClinicalTrials.gov (NCT04858893)

Transgene × Environment Interactions in Genetically Modified Wheat

BACKGROUND: The introduction of transgenes into plants may cause unintended phenotypic effects which could have an impact on the plant itself and the environment. Little is published in the scientific literature about the interrelation of environmental factors and possible unintended effects in genetically modified (GM) plants. METHODS AND FINDINGS: We studied transgenic bread wheat Triticum aestivum lines expressing the wheat Pm3b gene against the fungus powdery mildew Blumeria graminis f.sp. tritici. Four independent offspring pairs, each consisting of a GM line and its corresponding non-GM control line, were grown under different soil nutrient conditions and with and without fungicide treatment in the glasshouse. Furthermore, we performed a field experiment with a similar design to validate our glasshouse results. The transgene increased the resistance to powdery mildew in all environments. However, GM plants reacted sensitive to fungicide spraying in the glasshouse. Without fungicide treatment, in the glasshouse GM lines had increased vegetative biomass and seed number and a twofold yield compared with control lines. In the field these results were reversed. Fertilization generally increased GM/control differences in the glasshouse but not in the field. Two of four GM lines showed up to 56% yield reduction and a 40-fold increase of infection with ergot disease Claviceps purpurea compared with their control lines in the field experiment; one GM line was very similar to its control. CONCLUSIONS: Our results demonstrate that, depending on the insertion event, a particular transgene can have large effects on the entire phenotype of a plant and that these effects can sometimes be reversed when plants are moved from the glasshouse to the field. However, it remains unclear which mechanisms underlie these effects and how they may affect concepts in molecular plant breeding and plant evolutionary ecology

Comparative Genomics of the Anopheline Glutathione S-Transferase Epsilon Cluster

Enzymes of the glutathione S-transferase (GST) family play critical roles in detoxification of xenobiotics across many taxa. While GSTs are ubiquitous both in animals and plants, the GST epsilon class (GSTE) is insect-specific and has been associated with resistance to chemical insecticides. While both Aedes aegypti and Anopheles gambiae GSTE clusters consist of eight members, only four putative orthologs are identifiable between the species, suggesting independent expansions of the class in each lineage. We used a primer walking approach, sequencing almost the entire cluster from three Anopheles species (An. stephensi, An. funestus (both Cellia subgenus) and An. plumbeus (Anopheles subgenus)) and compared the sequences to putative orthologs in An. gambiae (Cellia) in an attempt to trace the evolution of the cluster within the subfamily Anophelinae. Furthermore, we measured transcript levels from the identified GSTE loci by real time reverse transcription PCR to determine if all genes were similarly transcribed at different life stages. Among the species investigated, gene order and orientation were similar with three exceptions: (i) GSTE1 was absent in An. plumbeus; (ii) GSTE2 is duplicated in An. plumbeus and (iii) an additional transcriptionally active pseudogene (ψAsGSTE2) was found in An. stephensi. Further statistical analysis and protein modelling gave evidence for positive selection on codons of the catalytic site in GSTE5 albeit its origin seems to predate the introduction of chemical insecticides. Gene expression profiles revealed differences in expression pattern among genes at different life stages. With the exception of GSTE1, ψAsGSTE2 and GSTE2b, all Anopheles species studied share orthologs and hence we assume that GSTE expansion generally predates radiation into subgenera, though the presence of GSTE1 may also suggest a recent duplication event in the Old World Cellia subgenus, instead of a secondary loss. The modifications of the catalytic site within GSTE5 may represent adaptations to new habitats