LEXpander: Applying colexification networks to automated lexicon expansion.

Recent approaches to text analysis from social media and other corpora rely on word lists to detect topics, measure meaning, or to select relevant documents. These lists are often generated by applying computational lexicon expansion methods to small, manually curated sets of seed words. Despite the wide use of this approach, we still lack an exhaustive comparative analysis of the performance of lexicon expansion methods and how they can be improved with additional linguistic data. In this work, we present LEXpander, a method for lexicon expansion that leverages novel data on colexification, i.e., semantic networks connecting words with multiple meanings according to shared senses. We evaluate LEXpander in a benchmark including widely used methods for lexicon expansion based on word embedding models and synonym networks. We find that LEXpander outperforms existing approaches in terms of both precision and the trade-off between precision and recall of generated word lists in a variety of tests. Our benchmark includes several linguistic categories, as words relating to the financial area or to the concept of friendship, and sentiment variables in English and German. We also show that the expanded word lists constitute a high-performing text analysis method in application cases to various English corpora. This way, LEXpander poses a systematic automated solution to expand short lists of words into exhaustive and accurate word lists that can closely approximate word lists generated by experts in psychology and linguistics.

Using the candidacy framework to conceptualize systems and gaps when developing infant mental health (IMH) services: A qualitative study.

The development of infant mental health (IMH) services globally is still in its early stages. This qualitative study aims to understand the challenges of setting up IMH services and explores the views and experiences of 14 multi-disciplinary stakeholders who are part of the IMH implementation group in a large Scottish health board. Six major themes were identified through thematic analysis. This paper examines the most prominent theme "Systems" alongside the theme "Gaps in Current Service". The theoretical framework of "candidacy" is found to be a valuable way to conceptualize the complex systemic layers of micro, meso, and macro factors that contribute to the challenges of setting up services. At the micro level, key themes included the view that services must be accessible, individualized, and involve families. At the meso level, in line with the aims of the service, multiagency integration, aspects of early intervention, and clear operating conditions were all seen as important. Finally, at the macro level, perhaps the biggest challenge perceived by stakeholders is delivering a service that is entirely infant-focused. These findings will help inform policy makers about factors considered by professionals to be vital in the establishment of IMH services in Scotland and across the globe.

El desarrollo de los servicios de salud mental infantil (IMH) globalmente está aún en sus niveles básicos. Este estudio cualitativo se propone comprender los retos de establecer los servicios IMH y explora los puntos de vista y experiencias de 14 personas interesadas de múltiples disciplinas que son parte de un grupo de implementación de IMH dentro de una extensa junta de salud escocesa. A través de análisis temáticos se identificaron seis temas de mayor importancia. Este estudio examina el tema más prominente según la mayor percepción, "Sistemas," junto con el tema "Vacíos en la Actual Prestación de Servicio." Se estima que el marco teorético de trabajo de "candidatura," es una manera valiosa de conceptualizar los complejos niveles sistémicos de micro, medio y macro factores que contribuyen a los retos de establecer los servicios. Al nivel micro, los temas claves incluyen el punto de vista de que los servicios deben ser accesibles, individualizados y deben involucrar a las familias. Al nivel medio, alineados con las metas del servicio, la integración de agencias múltiples, aspectos de temprana intervención y claras condiciones operativas fueron todas estimadas como importantes. Finalmente, al nivel macro, quizás el mayor reto percibido por las personas interesadas es cumplir con el ofrecimiento de un servicio que esté enteramente enfocado en el infante. Estos resultados ayudarán a informar a quienes determinan las políticas a seguir acerca de los factores que los profesionales consideran vitales en el establecimiento de servicios IMH en Escocia y alrededor del globo.

Au niveau global, le développement de service de santé mentale du nourrisson et de la petite enfance en est encore à ses débuts. Cette étude qualitative s'est donnée pour but de comprendre les défis que pose l'installation de services IMH. Elle explore les vues et les perspectives de 14 parties prenantes de diverses disciplines qui font partie d'un groupe de mise en place IMH dans un grand conseil de santé en Ecosse. Six thèmes principaux ont été identifiés au travers une analyse thématique. Cet article examine le thème ayant été perçu comme le plus grand et proéminent, Systèmes, ainsi que le thème « Brèches dans les services actuels ¼. La structure théorique de la 'candidature' a été utilisée pour trouver une manière utile de conceptualiser les couches systémiques complexes de facteurs micro, méso, et macro qui contribuent aux défis qu'il y a dans l'installation de services. Au niveau micro, les thèmes clés ont inclus l'idée que les services doivent être accessibles, individualisés et engager les familles. Au niveau méso, s'alignant avec les buts du service, l'intégration de plusieurs agences, les aspects d'une intervention précoce et des conditions d'opération claires ont tous été estimé être importants. Enfin, au niveau macro, le défi étant peut-être le plus grand selon les parties prenantes est d'offrir un service qui est entièrement focalisé sur le nourrisson. Ces résultats aideront les décideurs pour ce qui s'agit des facteurs considérés comme étant vitaux par les professionnels pour ce qui concerne l'établissement de services IMH en Ecosse et au travers du globe.

A Cross-Sectional Study of Untoward Reactions Following Homologous and Heterologous COVID-19 Booster Immunizations in Recipients Seventeen Years of Age and Older.

A booster dose after primary COVID-19 vaccination series was considered crucial after the emergence of the B.1.617.2 (Delta) and B.1.1.529 (Omicron) variants. Active surveillance was used to investigate reporting of adverse events post-booster dose of either of the licensed mRNA Comirnaty (Pfizer/BioNTech) or Spikevax (Moderna) vaccines in adult (17 years and older) recipients in central Italy. Eligible participants were enrolled and interviewed via phone using a structured questionnaire. Primary outcomes related to the occurrence of adverse events post-booster were stratified by vaccine, and frequency of local/systemic, mild/moderate/severe events. Of a total of 622 participants interviewed, 554 (89.1%) reported at least one adverse event (88.2% and 92.9% after the Comirnaty or Spikevax vaccine, respectively): 63.4% were female, and 78.5% aged 17 to 64 years, regardless of vaccine. 87.7% and 68.2% of all recipients described at least one local or systemic reaction, respectively: 97.3, 38.6 and 4.7% reported mild, moderate, or severe events, respectively. The most frequent adverse reactions were pain, redness, or swelling at the injection site and fatigue, while malaise and fever significantly occurred after the Comirnaty, and vomiting after the Spikevax booster. Compared to the primary vaccination, lymphadenopathy was more common after the booster (p < 0.001), especially after Comirnaty vaccine. The study findings revealed no serious or unexpected adverse events, and are in agreement with data available on booster dose for both mRNA vaccines. The transient, mild to moderate, and common to very common side reactions reported should be used to reassure potential recipients of the lack of safety concerns.

Active Surveillance of Adverse Events in Healthcare Workers Recipients After Vaccination with COVID-19 BNT162b2 Vaccine (Pfizer-BioNTech, Comirnaty): A Cross-Sectional Study.

In this cross-sectional study, adverse events after the first and second dose of BNT162b2 mRNA (Pfizer-BioNTech, Comirnaty) vaccine against coronavirus disease 2019 were investigated among employees of clinics in central Italy. A 42-items questionnaire was administrated to vaccine recipients. Adverse events were classified based on severity and occurrence as reported in the literature. A descriptive/univariate analysis using Chi-square or Fisher's Exact tests was performed. Odds ratio (OR) and 95% confidence intervals were calculated to assess risk factors. 340 individuals (61.5% females; median age 49 years) participated. Adverse events were reported by 279 (82%) and 281 (82.6%) individuals as induced by the first and second dose, respectively. Mild reactions were mainly reported (80.9% and 80.3%), followed by moderate (11.8% and 37.1%) and severe (3.8% and 4.7%). Adverse events were identical to those already described as very common (81.8% and 80.6%), although vaccine-coincidental events not cited in the literature were reported by 6% and 15.6% following each dose. Age ≤ 55 years was a risk factor for any adverse event after each injection (ORs: 2.942 and 2.818), as well as female sex for those mild (ORs: 1.856 and 2.818) and common (ORs: 3.452 and 2.145). Findings were consistent with national reports as most of the adverse events were mild and associated with female sex and young age, while investigations are needed for reactions not described elsewhere. Data are useful to support the vaccine safety profile, also because largely targeted healthcare personnel more skilled than general population in self-diagnosis of health-related issues.

A SARS-CoV-2 Outbreak Among Nursing Home Residents Vaccinated with a Booster Dose of mRNA COVID-19 Vaccine.

This study describes a SARS-CoV-2 outbreak caused by the Delta (B.1.617.2) variant in a nursing home in Central Italy during October-November 2021. Trained interviewers collected data from residents, staff, and administration officers with an agreed informed consent procedure. Thirty-two (44.5%) out of 72 residents (median age 89 years) and six (26.1%) of 23 healthcare workers were found to be infected with SARS-CoV-2. Infections occurred more often among residents with a higher index of independence in daily living activities, suggesting an increased risk for those with more interactions. Twenty-five infected residents (78.1%) received the booster dose of mRNA anti-COVID-19 vaccine > 7 days before SARS-CoV-2 onset. Half of the infected residents had mild symptoms, and only three required hospitalisation, one of whom died from COVID-19 complications. The study underlines the effectiveness of a booster dose in providing a high protection against severe disease and hospitalisation even among vulnerable individuals infected with the Delta variant of concern.

An automated food protein isolation approach on preparative scale by two-dimensional liquid chromatography with active modulation interface.

In this work, an automated 2D-LC approach for protein isolation from egg samples on preparative scale is proposed. The method is based on the use of a C18 guard column installed in a switching valve to focus the proteins coming from the first dimension column, before their elution in the second column. For the first dimension separation, a size-exclusion column, packed with 3 µm ultrapure silica particles was used. An RP column based on core-shell technology was used for the second dimension separation. A standard mixture of BSA, ß-lactoglobulin, and glucose oxidase, chosen as a protein model system, was used to optimize the chromatographic separation conditions. The fully automated workflow allowed to isolate, in a single-chromatographic analysis, a protein amount of 50 µg for each peak fraction, with a total time of 15 min for the first separation and additional 30 min of the second separation for each trapped protein. The final aim was the development of proper analytical tools for protein isolation from foodstuffs to be used for the molecular identification by MS, as well as for biotherapeutic uses, allergy testing, and large-scale investigations in biological systems.

Mass spectrometry hyphenated techniques for the analysis of volatiles and peptides in soft cheese: Useful tools for the shelf life optimization.

In order to assess the product quality and shelf life of an Italian soft cream cheese under different storage conditions, the volatile and peptide profiles evolution were tested. Volatiles were sampled directly from the head space of cheese packaging by solid-phase microextraction and analyzed by GC-MS. Peptide profiles were obtained by nanoLC-MS/MS, following a novel bioinformatics approach based on scoring distribution associated to the protein hits originating from the database search. In particular, a refined identification by focusing on selected time segments corresponding to the most intense peaks was carried out. A total of 40 compounds including acids, aldehydes, ketones, lactones, alcohols, esters, hydrocarbons, terpene, sulfur, and aromatic compounds were detected. Significant differences in their abundance during the storage in different packagings were observed, as well as an evolution of peptides mainly belonging to αS1-casein. The results demonstrated the usefulness of the above-mentioned hyphenated techniques for the determination of the soft cheese shelf life under different storage conditions.

Learning in the Metaverse: Are University Students Willing to Learn in Immersive Virtual Reality?

Immersive virtual reality (IVR) technology provides several educational affordances that make it a valuable tool for learning, especially from a constructivist learning perspective. Combined with the increasing availability of Metaverse social platforms, such as ENGAGE and AltSpace VR, where students and teachers can meet and work together, IVR may transform how students learn and interact with educational content. However, little is known about students' attitudes toward IVR in education. To address this gap, we surveyed 329 undergraduate students from different universities in Italy. We used the Unified Theory of Acceptance and Use of Technology (UTAUT) to predict students' intention to adopt IVR for learning. We further explored the role that different individual factors, including students' learning styles, affordances perceptions, and personal innovativeness, have on their attitudes toward IVR. A hierarchical multiple regression analysis revealed that the four constructs of the UTAUT, namely performance expectancy, effort expectancy, social influence, and facilitating conditions were the strongest predictors of students' intention to use IVR in education and that individual factors only had little impact on it. Based on these results, this study provides helpful indications for researchers and educators who wish to introduce IVR effectively in educational contexts. Given the new possibilities provided by Metaverse applications based on IVR technology for learning, it is indeed crucial to fully understand the attitudes different stakeholders in education have toward adopting this technology in educational contexts.

'Breaking the cycle': a qualitative study exploring general practitioners' views of infant mental health.

BACKGROUND: Infants living in areas of socioeconomic deprivation are more likely to have adverse childhood experiences (ACEs), which are associated with infant mental health (IMH) problems and poor physical and mental health outcomes throughout the life course. As part of the development of IMH services in Scotland, studies are being conducted to explore various stakeholders' perspectives. AIM: To understand the views and experiences of GPs working in socioeconomically deprived areas in relation to IMH. DESIGN & SETTING: Qualitative study with GPs working in deprived urban communities in Scotland, UK. METHOD: Semi-structured interviews were conducted with 12 GPs from 11 practices. Transcribed interviews were thematically analysed, following the Braun and Clarke framework, using NVivo (version 12) software. RESULTS: The following three overarching themes are presented: (1) Deep End GPs' inherent understanding of IMH, owing to their placement in deprived communities and their under-recognised role in current IMH provision; (2) Factors influencing how communities might perceive IMH, including the potential associations of IMH with parental blame or judgement in areas of socioeconomic deprivation; and (3) Using previous experience to visualise future IMH service delivery, particularly improving on current shortcomings of connectivity and accessibility of services, to develop successful new services. CONCLUSION: GPs in areas of socioeconomic deprivation have a deep understanding of the issues affecting IMH, although do not necessarily relate to the term 'IMH'. New community-based IMH services are much needed, particularly in deprived areas. However, the pre-existing role of primary care must be recognised, supported, and integrated into new services, alongside training to increase IMH awareness among GPs and other primary healthcare professionals (HCPs).

Collective emotions during the COVID-19 outbreak.

The COVID-19 pandemic has exposed the world's population to unprecedented health threats and changes to social life. High uncertainty about the novel disease and its social and economic consequences, together with increasingly stringent governmental measures against the spread of the virus, likely elicited strong emotional responses. We analyzed the digital traces of emotional expressions in tweets during 5 weeks after the start of outbreaks in 18 countries and six different languages. We observed an early strong upsurge of anxiety-related terms in all countries, which was related to the growth in cases and increases in the stringency of governmental measures. Anxiety expression gradually relaxed once stringent measures were in place, possibly indicating that people were reassured. Sadness terms rose and anger terms decreased with or after an increase in the stringency of measures and remained stable as long as measures were in place. Positive emotion words only decreased slightly and briefly in a few countries. Our results reveal some of the most enduring changes in emotional expression observed in long periods of social media data. Such sustained emotional expression could indicate that interactions between users led to the emergence of collective emotions. Words that frequently occurred in tweets suggest a shift in topics of conversation across all emotions, from political ones in 2019, to pandemic related issues during the outbreak, including everyday life changes, other people, and health. This kind of time-sensitive analyses of large-scale samples of emotional expression have the potential to inform risk communication. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

LEIA: Linguistic Embeddings for the Identification of Affect.

The wealth of text data generated by social media has enabled new kinds of analysis of emotions with language models. These models are often trained on small and costly datasets of text annotations produced by readers who guess the emotions expressed by others in social media posts. This affects the quality of emotion identification methods due to training data size limitations and noise in the production of labels used in model development. We present LEIA, a model for emotion identification in text that has been trained on a dataset of more than 6 million posts with self-annotated emotion labels for happiness, affection, sadness, anger, and fear. LEIA is based on a word masking method that enhances the learning of emotion words during model pre-training. LEIA achieves macro-F1 values of approximately 73 on three in-domain test datasets, outperforming other supervised and unsupervised methods in a strong benchmark that shows that LEIA generalizes across posts, users, and time periods. We further perform an out-of-domain evaluation on five different datasets of social media and other sources, showing LEIA's robust performance across media, data collection methods, and annotation schemes. Our results show that LEIA generalizes its classification of anger, happiness, and sadness beyond the domain it was trained on. LEIA can be applied in future research to provide better identification of emotions in text from the perspective of the writer.

Suture-Mediated Patent Foramen Ovale Closure Using the NobleStitch EL: Results from a Hospital-Based HTA.

(1) Background: Patent foramen ovale (PFO) is a congenital abnormality present in up to 25% of the general population, and it is a relevant cause of cryptogenic stroke. We applied the hospital-based HTA model (AdHopHTA) to conduct a multidimensional assessment of NobleStitch EL, an innovative suture-mediated PFO closure device. We compared it to Amplatzer PFO Occluder (APO) to provide evidence to inform technologies' governance in hospital settings. (2) Methods: For each AdHopHTA dimension we: systematically retrieved available evidence from the literature applying the PRISMA guidelines and then analyzed original clinical and cost data of a NobleStitch EL device at San Raffaele research hospital in Milan (Italy). The economic dimension was analyzed through activity-based costing and a cost analysis. We conducted semi-structured interviews with selected healthcare professionals to explore the organizational, legal, social, and ethical impact. (3) Results: A single study was included for the NobleStitch EL, with 10 for APO. Both literature data and original data showed comparable safety. Efficacy data analysis found that the PFO closure was at 89% for NobleStitch EL vs. 89-97% for APO. APO has a better impact on the budget and minor process costs. Consulted experts reported that the organizational impact of NobleStitch EL in the short and the long run as null, albeit a better impact under the social and the ethical aspects. (4) Conclusion: We suggest that there is inadequate evidence to conclude the relative efficacy of NobleStitch EL as compared to APO. Nevertheless, this report shows a good safety profile and higher costs for NobleStitch EL, with no organizational or legal impact. Further studies in selected population are recommended.

Safety of mRNA BNT162b2 COVID-19 (Pfizer-BioNtech) vaccine in children aged 5-11 years: Results from an active pharmacovigilance study in central Italy.

This survey investigated on adverse events after vaccination with mRNA BNT162b2 (Comirnaty, Pfizer-BioNTech) vaccine in children aged 5-11 years in central Italy through active surveillance reporting. During December 2021-January 2022, parents of children who undergone vaccination were interviewed using a structured questionnaire. 197 out of 208 contacted parents participated (94.7% response rate), of whom 166 (84.3%) had one child. Of the 229 children, the mean age was 8.9 years, 50.7% were female. 193 (84.3%) had at least one adverse event after the first dose (mean age 9.1 years; 54.4% female), and 146 (73.4%) of 199 after the second (mean age 8.9 years; 54.8% female), which was not administered to 30 children due to previous COVID-19 history. Local symptoms after the first and second dose occurred in 183 (94.8%) and 141 (96.6%) recipients (p = .435), respectively, while systemic reactions in 62 (32.1%) and 34 (23.3%) (p = .074). Mild events were reported by 81.7% and 69.8% children after the first and second dose, followed by moderate (3.9% and 10.6%) and severe (1.3% and 0.5%). After each dose, injection site reactions (79.5% and 68.8%) were the most frequent, followed by headache (13.1%) and lymphadenopathy (8.5%) after the first and second dose, respectively. The adverse events were reported to pediatricians only for 5.7% and 3.9% of children and treated for 17.6% and 15.8%. This is the first report about safety profile through active surveillance of mRNA BNT162b2 among children in Italy, revealing temporary and mild-to-moderate symptoms with no serious events after each vaccine dose.

Colexification Networks Encode Affective Meaning.

Colexification is a linguistic phenomenon that occurs when multiple concepts are expressed in a language with the same word. Colexification patterns are frequently used to estimate the meaning similarity between words, but the hypothesis that these are related is still missing direct empirical validation at scale. Here, we show for the first time that words linked by colexification patterns capture similar affective meanings. Using pre-existing translation data, we extend colexification databases to cover much longer word lists. We achieve this with an unsupervised method of affective lexicon extension that uses colexification network data to interpolate the affective ratings of words that are not included in the original lexicon. We find positive correlations between network-based estimates and empirical affective ratings, which suggest that colexification networks contain information related to affective meanings. Finally, we compare our network method with state-of-the-art machine learning, trained on a large corpus, and show that our simple linguistics-informed unsupervised algorithm yields comparable performance with high explainability. These results show that it is possible to automatically expand affective norms lexica to cover exhaustive word lists when additional data are available, such as in colexification networks. Supplementary Information: The online version contains supplementary material available at 10.1007/s42761-021-00033-1.

Gratitude and Social Media: A Pilot Experiment on the Benefits of Exposure to Others' Grateful Interactions on Facebook.

Facebook and other social networking sites allow observation of others' interactions that in normal, offline life would simply be undetectable (e.g., a two-voice conversation viewable on the Facebook wall, from the perspective of a real, silent witness). Drawing on this specific property, the theory of social learning, and the most direct implications of emotional contagion, our pilot experiment (N = 49) aimed to test whether the exposure to others' grateful interactions on Facebook enhances (a) users' felt gratitude, (b) expressed gratitude, and (c) their subjective well-being. For the threefold purpose, we created ad hoc Facebook groups in which the exposure to some accomplices' exchange of grateful messages for 2 weeks was experimentally manipulated and users' felt/expressed gratitude and well-being were consequently assessed. Results partially supported both hypotheses. Observing others' exchange of grateful posts/comments on Facebook appeared to enhance participants' in-person expression of gratitude (i.e., self-reported gratitude expression within face-to-face interactions), but not their direct and subjective experiences of gratitude. Similarly, exposure to others' grateful messages improved some components of subjective well-being, such as satisfaction with life, but not negative and positive affect. Taken together, however, our preliminary findings suggest for the first time that social networking sites may actually amplify the spreading of gratitude and its benefits. Implications of our results for professionals and future research in the field of health, education, and social media communication are discussed.

A structured open dataset of government interventions in response to COVID-19.

In response to the COVID-19 pandemic, governments have implemented a wide range of non-pharmaceutical interventions (NPIs). Monitoring and documenting government strategies during the COVID-19 crisis is crucial to understand the progression of the epidemic. Following a content analysis strategy of existing public information sources, we developed a specific hierarchical coding scheme for NPIs. We generated a comprehensive structured dataset of government interventions and their respective timelines of implementation. To improve transparency and motivate collaborative validation process, information sources are shared via an open library. We also provide codes that enable users to visualise the dataset. Standardization and structure of the dataset facilitate inter-country comparison and the assessment of the impacts of different NPI categories on the epidemic parameters, population health indicators, the economy, and human rights, among others. This dataset provides an in-depth insight of the government strategies and can be a valuable tool for developing relevant preparedness plans for pandemic. We intend to further develop and update this dataset until the end of December 2020.

Milk authenticity by ion-trap proteomics following multi-enzyme digestion.

The practice of adding adulterating substances in milk in order to raise profits is unfortunately worldwide. In addition, higher priced milk, coming from minor dairy species, is often illegally integrated with the lower priced cow milk. The presence of species-specific proteins, different from those declared in label, may be a serious problem for people with allergies. The development of proper analytical methods is therefore essential to protect consumer benefits and product authenticity. In this study, a proteomic approach for the detection of adulteration processes of specific milks in mixtures is proposed. Few microliters of milk samples have been digested with trypsin and chymotrypsin and analyzed by nanoLC-ESI-IT-MS/MS. A post-database processing was performed to obtain confident peptide sequence assignments, allowing the detection of milk adulteration at a level lower than 1%. Species-specific peptides from bovine ß-lactoglobulin and αS1 casein were identified as suitable peptide markers of milk authenticity.

Combined use of peptide ion and normalized delta scores to evaluate milk authenticity by ion-trap based proteomics coupled with error tolerant searching.

A fundamental issue in proteomics is the peptide identification by database searching and the assessment of the goodness of fit between experimental and theoretical data. Despite the different number of ways to measure the quality of search results, the definition of a scoring criterion is still highly desirable in ion-trap based proteomics. Indeed, in order to fully take advantage of a low resolution MS/MS dataset, it is essential to strike a balance between greater information capture and reduced number of incorrect peptide assignments. In addition, the development of user-specified rules is a crucial aspect when very similar proteins of the same family are analyzed in order to infer the origin species. In this study, a post-processing validation scheme is provided for the evaluation of proteomic data in shot-gun ion-trap proteomics, when a flexible database searching based on the error tolerant mode is adopted in combination with a low-specificity enzyme to maximize sequence coverage. To validate peptide assignments, we used standard ß-casein digested with trypsin/chymotrypsin or trypsin alone and the popular search engine MASCOT to identify the relevant (known) peptide sequences. A linear combination between peptide ion score and normalized delta score (i.e. the difference between the best and the second best ion score, divided by the best score) is proposed to increase the accuracy in sequence assignments from low-resolution tandem mass spectra. Finally, the optimized post-processing database validation was successfully applied to the direct analysis of milk tryptic/chymotryptic digests of different origin, without resorting to two-dimensional electrophoresis that is usually performed for protein separation in ion-trap proteomics. The identification of species-specific amino acidic sequences among the validated peptide spectrum matches has allowed to fully discriminate between the animal species, so evaluating accurately the milk authenticity.

Pulsed amperometric detection at glassy carbon electrodes: A new waveform for sensitive and reproducible determination of electroactive compounds.

In this work, the application of a new pulsed amperometric detection (PAD) waveform at a glassy carbon electrode, operating in typical chromatographic mobile phases, is proposed for the sensitive and reproducible determination of arylethanolaminic and phenolic moiety based compounds (e.g. beta-agonists and polyphenols). Preliminary experiments by cyclic voltammetry were carried out to investigate the electrochemical behaviour and to select the detection and cleaning electrode potentials. The proposed potential-time profile was designed to prevent the carbon electrode fouling under repeated analyses, thus ensuring a reproducible and sensitive quantitative determination, without the need of any mechanical or chemical electrode cleaning procedure. The waveform electrochemical parameters, including detection and delay times, were optimized in terms of sensitivity, limit of detection and response stability. The optimized waveform allowed the sensitive and stable detection of model compounds, such as clenbuterol and caffeic acid, that showed detection limits of 0.1 µg L(-1) and 14 µg L(-1), quantification limits of 0.4 µg L(-1) and 46 µg L(-1), and linearity up to 100 µg L(-1) (r = 0.9993) and 10 mg L(-1) (r = 0.9998), respectively. Similar results were obtained for other compounds of the same classes, with precision values under repeatability conditions ranging from 3.0 to 5.9%. The proposed method can be then considered as an excellent alternative to the post-column detection of beta-agonists, phenols and polyphenols.