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

Re-designing nano-silver technology exploiting one-pot hydroxyethyl cellulose-driven green synthesis

Re-designing existing nano-silver technologies to optimize efficacy and sustainability has a tangible impact on preventing infections and limiting the spread of pathogenic microorganisms. Advancements in manufacturing processes could lead to more cost-effective and scalable production methods, making nano-silver-based antimicrobial products more accessible in various applications, such as medical devices, textiles, and water purification systems. In this paper, we present a new, versatile, and eco-friendly one-pot process for preparing silver nanoparticles (AgNPs) at room temperature by using a quaternary ammonium salt of hydroxyethyl cellulose (HEC), a green ingredient, acting as a capping and reducing agent. The resulting nano-hybrid phase, AgHEC, consists of AgNPs embedded into a hydrogel matrix with a tunable viscosity depending on the conversion grade, from ions to nanoparticles, and on the pH. To investigate the synthesis kinetics, we monitored the reaction progress within the first 24 h by analyzing the obtained NPs in terms of particle size (dynamic light scattering (DLS), field emission scanning electron microscopy (FE-SEM), transmission electron microscopy (TEM)), Z-potential (ELS), surface plasmon resonance (UV-VIS), crystallographic phase (XRD), viscosity, and reaction yield (inductively coupled plasma-optical emission spectrometry (ICP-OES)). To explore the design space associated with AgHEC synthesis, we prepared a set of sample variants by changing two independent key parameters that affect nucleation and growth steps, thereby impacting the physicochemical properties and the investigated antimicrobial activity. One of the identified design alternatives pointed out an improved antimicrobial activity in the suspension, which was confirmed after application as a coating on nonwoven cellulose fabrics. This enhancement was attributed to a lower particle size distribution and a positive synergistic effect with the HEC matrix

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

Re-designing nano-silver technology exploiting one-pot hydroxyethyl cellulose-driven green synthesis

Re-designing existing nano-silver technologies to optimize efficacy and sustainability has a tangible impact on preventing infections and limiting the spread of pathogenic microorganisms. Advancements in manufacturing processes could lead to more cost-effective and scalable production methods, making nano-silver-based antimicrobial products more accessible in various applications, such as medical devices, textiles, and water purification systems. In this paper, we present a new, versatile, and eco-friendly one-pot process for preparing silver nanoparticles (AgNPs) at room temperature by using a quaternary ammonium salt of hydroxyethyl cellulose (HEC), a green ingredient, acting as a capping and reducing agent. The resulting nano-hybrid phase, AgHEC, consists of AgNPs embedded into a hydrogel matrix with a tunable viscosity depending on the conversion grade, from ions to nanoparticles, and on the pH. To investigate the synthesis kinetics, we monitored the reaction progress within the first 24 h by analyzing the obtained NPs in terms of particle size (dynamic light scattering (DLS), field emission scanning electron microscopy (FE-SEM), transmission electron microscopy (TEM)), Z-potential (ELS), surface plasmon resonance (UV-VIS), crystallographic phase (XRD), viscosity, and reaction yield (inductively coupled plasma-optical emission spectrometry (ICP-OES)). To explore the design space associated with AgHEC synthesis, we prepared a set of sample variants by changing two independent key parameters that affect nucleation and growth steps, thereby impacting the physicochemical properties and the investigated antimicrobial activity. One of the identified design alternatives pointed out an improved antimicrobial activity in the suspension, which was confirmed after application as a coating on nonwoven cellulose fabrics. This enhancement was attributed to a lower particle size distribution and a positive synergistic effect with the HEC matrix

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)

Safe-by-design assessment of an SiO2@ZnO multi-component nanomaterial used in construction

Safety aspects of chemicals/materials are transversal in all sustainability dimensions, representing a pillar at the early innovation stages of the European Commission's "safe and sustainable by design" (SSbD) framework for chemicals and materials. The first three of the five SSbD framework steps cover different safety aspects, namely, hazard assessment based on intrinsic properties (step 1), occupational health and safety (including exposure) assessment during the production/processing phase (step 2) and exposure in the final application phase (step 3). The goal of this work was to identify a set of characterization tools/procedures to support the operationalization of the first three safety steps in multi-component nanomaterials (MCNMs), applying the findings to an SiO2 core-ZnO shell MCNM. The safety of this MCNM, which is used as an additive to silicate/calcium hydroxide mortar to improve air quality through photocatalytic NOx removal, was investigated from different perspectives along its value chain. Existing and newly generated data on its hazard profile were collected, the exposure of workers during its synthesis was assessed, and potential exposure to hazardous substances during its final application phase was investigated. In step 1, physico-chemical properties, hazard classification and cytotoxicity assays were considered. In step 2, a three-tiered established methodology for evaluating occupational exposure assessment was performed. Lastly, in step 3, the release of inorganic substances from MCNM-based mortars in the final application phase was investigated. Safety assessment according to the SSbD framework was performed by selecting tools and procedures suitable for application in the early innovation stage, resulting in a preliminary hazard assessment of MCNMs and a suggestion for redesigning a step in the process

In Vitro Antibacterial Activity of Cysteine Protease Inhibitor from Kiwifruit (Actinidia deliciosa)

The need for replacing traditional pesticides with alternative agents for the management of agricultural pathogens is rising worldwide. In this study, a cysteine proteinase inhibitor (CPI), 11 kDa in size, was purified from green kiwifruit to homogeneity. We examined the growth inhibition of three plant pathogenic Gram-negative bacterial strains by kiwi CPI and attempted to elucidate the potential mechanism of the growth inhibition. CPI influenced the growth of phytopathogenic bacteria Agrobacterium tumefaciens (76.2 % growth inhibition using 15 mu M CPI), Burkholderia cepacia (75.6 % growth inhibition) and, to a lesser extent, Erwinia carotovora (44.4 % growth inhibition) by inhibiting proteinases that are excreted by these bacteria. Identification and characterization of natural plant defense molecules is the first step toward creation of improved methods for pest control based on naturally occurring molecules