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In this study we investigated the effect of the single strain in stabilization of type I sourdough microbial associations by crossing six different Fructilactobacillus sanfranciscensis with five Kazachstania humilis strains. Furthermore, we compared three predictive models, Zwitwering based on Gompertz's equation, Baranyi and Roberts' function and Schiraldi's function to evaluate which one best fitted the experimental data in determining the behaviour of co-cultivated microorganisms. Specific growth rates (µm) and lag time (λ) values for each mixed population were assessed. Results showed that the different F. sanfranciscensis strains significantly steer the growth kinetics within the pair and affect the ratio bacterial/yeast cells, as data analysis confirmed, whereas K. humilis accommodates to the bacterial strain. To compare the growth models, Root Mean Square (RMS) values were calculated for each predicted curve by implementing an algorithm based on an iterative process to minimize the deviation among observed and calculated data. Schiraldi's function performed better than the others, revealing, on average, the smallest RMS values and providing the best fitting for over 70% of co-cultivation experiments. Models prove to be consistent in predicting growth kinetics of microbial consortia too.
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Bactérias/química , Bactérias/crescimento & desenvolvimento , Pão/microbiologia , Consórcios Microbianos , Bactérias/isolamento & purificação , Bactérias/metabolismo , Fermentação , Farinha/microbiologia , Microbiologia de Alimentos , Cinética , Triticum/microbiologiaRESUMO
BACKGROUND: Mood and anxiety disorders are prevalent in women during peripartum. AIMS: Purpose of the present article was to study the relationship between oxytocin (OT) plasma levels and affective symptoms in women during the third trimester of pregnancy. METHODS: Thirty-four pregnant women (13 with an affective disorder, 9 with preeclampsia, and 12 controls) were evaluated through the Edinburgh Postnatal Depression Scale (EPDS), the State/Trait Anxiety Inventory Form Y (STAI-Y), and the Prenatal Attachment Inventory (PAI). A blood sample was collected from all participants, and OT plasma levels have been compared between diagnostic groups. The total sample has been divided into two groups, according to OT median plasma levels, and compared using (a) χ2 tests for qualitative variables and (b) a multivariate analysis of covariance for quantitative ones. RESULTS: No statistically significant difference was found among the diagnostic groups in terms of OT plasma levels (F = 0.49, p = .62). Women with lower OT plasma levels, independent from the presence of preeclampsia or an affective disorder, showed worse EPDS and STAI-S total scores than individuals with higher hormone levels (F = 5.93, p = .02 and F = 7.57, p = .01, respectively). CONCLUSIONS: OT may play a role in the etiology of anxious/depressive symptoms during perinatal period independent from a medical or psychiatric diagnosis. This result has a clear effect on the quality of the relationship of patients with mental health professionals, including nurses, and higher levels of this hormone, in the light of its anxiolytic and antidepressive effect, may make easier medical and nursing procedures.
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Ocitocina , Gestantes , Transtornos de Ansiedade , Feminino , Humanos , Saúde Mental , Parto , GravidezRESUMO
The lifetime presence of psychotic symptoms is associated with more clinical severity, poorer outcome and biological changes in patients affected by bipolar disorder (BD). Epigenetic mechanisms have been evoked to explain the onset of psychotic symptoms in BD as well as the associated biological changes. The main objective of the present study was to evaluate the expression profiles of circulating microRNAs (miRNAs) in drug-free manic psychotic bipolar patients versus healthy controls (HC), to identify possible non-invasive molecular markers of the disorder. 15 drug-free manic psychotic bipolar patients and 9 HC were enrolled and 800 miRNAs expression profile was measured by Nanostring nCounter technology on plasma samples and validated through qPCR. Overall, twelve miRNAs showed a significantly altered expression between the two groups (p < 0.05). Functional annotation of predicted miRNAs targets by MultiMIR R tool showed repression in bipolar patients of genes with a role in neurodevelopment and neurogenesis, and upregulation of genes involved in metabolism regulation. We identified a signature of circulating miRNA characteristic of manic psychotic bipolar patients, suggesting a possible role in neurodevelopment and metabolic processes regulation.
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Transtornos Psicóticos Afetivos/genética , Transtorno Bipolar/genética , Epigênese Genética/genética , Mania/genética , MicroRNAs/genética , Transcriptoma/genética , Adulto , Transtornos Psicóticos Afetivos/sangue , Transtorno Bipolar/sangue , Feminino , Humanos , Masculino , Mania/sangue , MicroRNAs/sangue , Adulto JovemRESUMO
The milling industry envisions solutions to become fully compatible with the industry 4.0 technology where sensors interconnect devices, machines and processes. In this contest, the work presents an integrated solution merging a deeper understanding and control of the process due to real-time data collection by MicroNIR sensors (VIAVI, Santa Rosa, CA)-directly from the manufacturing process-and data analysis by Chemometrics. To the aim the sensors were positioned at wheat cleaning and at the flour blends phase and near infrared spectra (951-1608 nm) were collected online. Regression models were developed merging the spectra information with the results obtained by reference analyses, i.e., chemical composition and rheological properties of dough by Farinograph® (Brabender GmbH and Co., Duisburg, Germany), Alveograph® (Chopin, NG Villeneuve-la-Garenne Cedex, France) and Extensograph®.(Brabender GmbH and Co., Duisburg, Germany) The model performance was tested by an external dataset obtaining, for most of the parameters, RPRED higher than 0.80 and Root Mean Squares Errors in prediction lower than two-fold the value of the reference method errors. The real-time implementation resulted in optimal (100% of samples) or really good (99.9%-80% of samples) prediction ability. The proposed work succeeded in the implementation of a process analytical approach with Industrial Internet of Things near infrared (IIoT NIR) devices for the prediction of relevant grain and flour characteristics of common wheat at the industrial level.
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Eletricidade , Espectroscopia de Luz Próxima ao Infravermelho/instrumentação , Triticum/química , Automação , Calibragem , Farinha/análise , Análise dos Mínimos Quadrados , Padrões de Referência , Reologia , Espectroscopia de Luz Próxima ao Infravermelho/métodosRESUMO
Background: A number of studies reported obstetric complications (OCs) to be a risk factor for the development of psychiatric conditions in the adulthood, including mood disorders.Aim: The aim of this study was to review the literature about the link between OCs during the perinatal period (items of Lewis-Murray scale) and the future risk of developing a mood disorder in adulthood, such as the major depressive disorder (MDD) or the bipolar disorder (BD).Methods: A research in the main database sources has been conducted to obtain an overview of the association mentioned above.Results: Few studies have investigated the role of OCs in the development of mood disorders in adulthood. The most robust evidence is that low birth weight (LBW) and preterm birth may be risk factors for the development of MDD in the future, even if some of the available data come from studies with small sample sizes or a retrospective design.Conclusion: OCs may confer a risk of developing mood disorders in adulthood. Future research should confirm these preliminary findings and clarify if other obstetric or neonatal complications (e.g. cyanosis or newborn epileptic seizures) may have a role in the future onset of mood disorders.
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The evaluation of meat and fish quality is crucial to ensure that products are safe and meet the consumers' expectation. The present work aims at developing a new low-cost, portable, and simplified electronic nose system, named Mastersense, to assess meat and fish freshness. Four metal oxide semiconductor sensors were selected by principal component analysis and were inserted in an "ad hoc" designed measuring chamber. The Mastersense system was used to test beef and poultry slices, and plaice and salmon fillets during their shelf life at 4 °C, from the day of packaging and beyond the expiration date. The same samples were tested for Total Viable Count, and the microbial results were used to define freshness classes to develop classification models by the K-Nearest Neighbours' algorithm and Partial Least Square-Discriminant Analysis. All the obtained models gave global sensitivity and specificity with prediction higher than 83.3% and 84.0%, respectively. Moreover, a McNemar's test was performed to compare the prediction ability of the two classification algorithms, which resulted in comparable values (p > 0.05). Thus, the Mastersense prototype implemented with the K-Nearest Neighbours' model is considered the most convenient strategy to assess meat and fish freshness.
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Algoritmos , Nariz Eletrônico , Produtos Pesqueiros/análise , Análise de Alimentos/instrumentação , Carne/análise , Animais , Bovinos , Desenho de Equipamento , Análise de Alimentos/métodos , Microbiologia de Alimentos , Qualidade dos Alimentos , Análise dos Mínimos Quadrados , Modelos Teóricos , Análise de Componente Principal , SalmãoRESUMO
OBJECTIVE: Endocrine pathways seem to play a role in the etiology of major psychoses. The identification of biomarkers associated with psychotic symptoms in schizophrenia (SKZ) and mood disorders would allow the identification of high-risk subjects for delusions and hallucinations. The aim of this study was to evaluate dehydroepiandrosterone sulfate (DHEA-S) and progesterone plasma levels in drug-free patients with major psychoses and their relation with the diagnosis and history of psychotic symptoms. METHODS: Eighty-nine consecutive drug-free male inpatients with SKZ or mood disorders were recruited, and DHEA-S and progesterone plasma levels were measured. The groups, divided according to pathological/normal-range hormone levels, were compared in terms of clinical variables using x03C7;2 tests with Bonferroni's corrections or multivariate analyses of variance. The same analyses were performed for groups divided according to the presence/absence of lifetime psychotic symptoms. Binary logistic regression analysis was performed using hormone levels as independent variables and history of lifetime psychotic symptoms as a dependent one. RESULTS: A higher number of patients with abnormal DHEA-S levels was found to have a family history of major depressive disorder (p < 0.05). Higher DHEA-S levels (F = 8.31; p = 0.005) were found in patients with a history of psychotic symptoms. In addition, binary logistic regression confirmed that DHEA-S levels were associated with a higher probability of lifetime psychotic symptoms (p = 0.037). CONCLUSIONS: Our results confirm previous data about the role of endocrine factors in the etiology of major psychoses. A high DHEA-S level might be a risk factor for psychotic symptoms. Studies with larger samples are needed to confirm these data.
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Sulfato de Desidroepiandrosterona/sangue , Transtornos do Humor/sangue , Progesterona/sangue , Transtornos Psicóticos/sangue , Esquizofrenia/sangue , Adulto , Transtorno Depressivo Maior/sangue , Transtorno Depressivo Maior/genética , Humanos , Modelos Logísticos , Masculino , Pessoa de Meia-Idade , Análise MultivariadaAssuntos
Transtorno Depressivo Maior , Obstetrícia , Complicações na Gravidez , Depressão , Feminino , Humanos , Gravidez , Estudos ProspectivosRESUMO
Low-Field Nuclear Magnetic Resonance (LF-NMR) can be a valid tool in food fingerprint analyses to detect commercial frauds. Thus, the work aims at exploring the potential of LF-NMR, coupled with chemometrics, in discriminating authentic white wine vinegars from products adulterated with alcohol vinegars (i.e., 5-25% v/v adulteration levels). The monodimensional spectra and transverse relaxation times (T2) of 88 samples, including 32 authentic vinegars and 56 adulterated samples, were collected. Three different spectral regions were investigated (i.e., 3.75-0.90, 3.75-2.00, and 1.50-0.90 ppm) and, for each, fifteen variables were selected from the pretreated monodimensional spectra. Linear Discriminant Analysis (LDA) on monodimensional spectra in the range 3.75-0.90 ppm gave 100% correct classification of authentic and adulterated vinegars in prediction, whereas LDA models developed with acetic acid or water T2 failed. In conclusion, LF-NMR spectra can be effectively used to detect, in a rapid and non-destructive way, white wine vinegar adulteration with alcohol vinegar.
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Ácido Acético , Contaminação de Alimentos , Espectroscopia de Ressonância Magnética , Vinho , Ácido Acético/análise , Ácido Acético/química , Vinho/análise , Contaminação de Alimentos/análise , Análise DiscriminanteRESUMO
Alongside the increasing proofs of efficacy of miniaturized NIR instruments in food-related scenarios, it is progressively growing the number of end-users, even incentivized by the low-cost of the sensors. While attention is paid to the analytical protocol-from sampling to data collection, up to the data processing, the importance of error investigation in raw data is generally underestimated. Understanding the sources and the structure of uncertainty related to the raw data improves the quality of measurements and suggests the correct planning of the experiments, as well as helps in chemometric model development. The goal of chemometric modeling is to separate information from noise; therefore, a description of the nature of measurement error structure is necessary. Among the different approaches, we present the study of the Error Covariance Matrices (ECMs) and their decomposition in a bilinear structure as a powerful method to study the main sources of variability when using miniaturized NIR sensors in the actual way of use. Granulated and lump sugar samples were chosen as the case study and analyzed with two miniaturized spectrometers working in the NIR regions around 1350-2550 nm and 900-1750 nm, respectively, in dispersive reflectance mode. Results show that having some insights on multivariate measurement errors associated with spectra could be interesting in paving the way for several applications.
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BACKGROUND: Vocal disorders are frequent in people with multiple sclerosis (MS). Cognitive impairment, fatigue, depression, and other clinical characteristics can be associated with treatment effectiveness in rehabilitation. Finding baseline characteristics that identify those who are responding to treatment can help the clinical decision-making process, which can then help improve the effectiveness of voice treatment. We developed a model to identify factors associated with treatment-related improvement on voice intensity in people with MS. METHODS: Data are from a randomized controlled trial of the effects of voice therapy. Forty-four people with MS were enrolled and randomized to receive Lee Silverman Voice Treatment LOUD, specifically addressing voice intensity, or conventional speech-therapy group. Voice intensity (dB) was measured during monologue before and after treatment and was used to differentiate those who responded (posttreatment voice intensity > 60 dB) from those who did not. Possible associated factors were cognitive impairment, fatigue, depression, disability, and disease duration. Associations were assessed by univariate logistic regression and univariate and multivariate linear regressions. RESULTS: Mean ± SD monologue voice intensity is improved in the whole sample (before rehabilitation: 51.8 ± 4.2 dB; and after rehabilitation 57.0 ± 6.5 dB; P < .001), and 11 people with MS (27.5%) responded to treatment. Specificity of treatment was associated with the return to normal voice intensity (OR, 14.28; 95% CI, 12.17-309.56) and we found a linear association between voice improvement and the specificity of treatment (6.65 [SE = 1.54] dB; P < .05). Moreover, the analysis revealed a nonlinear association between improvement and fatigue, suggesting increased benefits for people with MS with moderate fatigue. Other factors were not significantly associated with treatment effectiveness. CONCLUSIONS: Moderate fatigue and the specificity of the intervention seem to be key factors associated with clinically relevant improvement in voice intensity even in people with MS with a high level of disability and long disease duration.
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BACKGROUND: Cardiovascular diseases represent one of the most important problems for public health. Research indicates that elderly patients consider sexual satisfaction as a fundamental aspect of their quality of life and a better sexual function is related to higher general wellbeing. OBJECTIVE: The main objective of this study was to investigate the mediating role of anxiety and depression in the relationship between quality of life and sexual satisfaction in cardiovascular (CVD) patients. METHODS: The sample comprised 128 adult patients, males and females, hospitalized in a Cardiology Rehabilitation clinical center. To collect data, the following were used: a demographic information sheet, the left ventricular ejection fraction (EF) to evaluate cardiac function, cardiovascular diagnosis type, the HADS scale to evaluate anxiety and depression states, a test for sexual satisfaction evaluation (SAS) and the SF-36 survey to measure quality of life. RESULTS: The results indicated that only SF-36 physical health is indirectly related to SAS through its relationship with anxiety. CONCLUSION: A mediating model was proposed to explore the underlying association between sexual satisfaction and quality of life. We recommend investigating perceived general health and sexuality as clinical indicators for therapeutic decisions and risk evaluation for the management of cardiovascular diseases.
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Rising challenges for food innovation and environmental issues have led to an increased interest in bio-economy and more sustainable food production [...].
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Adulteration and fraud are amongst the wrong practices followed nowadays due to the attitude of some people to gain more money or their tendency to mislead consumers. Obviously, the industry follows stringent controls and methodologies in order to protect consumers as well as the origin of the food products, and investment in these technologies is highly critical. In this context, chemometric techniques proved to be very efficient in detecting and even quantifying the number of substances used as adulterants. The extraction of relevant information from different kinds of data is a crucial feature to achieve this aim. However, these techniques are not always used properly. In fact, training is important along with investment in these technologies in order to cope effectively and not only reduce fraud but also advertise the geographical origin of the various food and drink products. The aim of this paper is to present an overview of the different chemometric techniques (from clustering to classification and regression applied to several analytical data) along with spectroscopy, chromatography, electrochemical sensors, and other on-site detection devices in the battle against milk adulteration. Moreover, the steps which should be followed to develop a chemometric model to face adulteration issues are carefully presented with the required critical discussion.
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The immune and antioxidant systems are intimately connected and their role in the etiology of major psychiatric disorders is currently under study. The aim of this study was to evaluate the potential associations between inflammatory/antioxidant peripheral markers and presence of psychotic symptoms or severity of illness in patients affected by major psychiatric disorders. One hundred and twenty-six drug-free patients were included. A blood sample was collected to measure total/B/T lymphocytes and plasma levels of albumin, total bilirubin, uric acid, C-reactive protein, and vitamins A and E. Severity of illness was assessed using psychometric scales. Groups of patients divided according to diagnosis were compared in terms of measured markers using multivariate analyses of variance (MANOVAs). Linear and logistic regression analyses were performed to investigate the potential association between markers and severity of illness or presence/absence of psychotic symptoms. Albumin plasma levels were higher in patients with substance-induced psychotic disorder (SIPD) than subjects affected by schizophrenia (F â= â4.923; p â= â0.003). Lower vitamin E (OR â= â0.81; p â= â0.014) and T lymphocyte (OR â= â0.99; p â= â0.048) plasma levels were predictive of lifetime psychotic symptoms. Lower vitamin A levels were associated with higher Montgomery-Åsberg Depression Rating Scale scores (ß â= â-24.26; p â= â0.029), independent of diagnosis. Patients with SIPD may be less vulnerable to oxidative stress. The severity of depressive symptoms, inversely associated with vitamin A plasma levels, is likely to be modulated by the degree of inflammation. Patients presenting with lifetime psychotic symptoms may be more vulnerable to oxidative stress and may have a higher activation of humoral immunity.
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The ripening process of dry-cured meat products is characterised by the development of fungi on the product's surface. This population plays a beneficial role, but, uncontrolled moulds represent a health risk, since some of them may produce mycotoxins, such as ochratoxin A (OTA). The aim of the present work is to assess the potential of near-infrared spectroscopy (NIRS) for the detection of OTA-producing mould species on dry-cured ham-based agar. The collected spectra were used to develop Support Vector Machines-Discriminant Analysis (SVM-DA) models by a hierarchical approach. Firstly, an SVM-DA model was tested to discriminate OTA and non-OTA producers; then, two models were tested to discriminate species among the OTA producers and the non-OTA producers. OTA and non-OTA-producing moulds were discriminated with 85% sensitivity and 86% specificity in the prediction. Furthermore, the SVM-DA model could differentiate non-OTA-producing species with a 95% sensitivity and specificity. Promising results were obtained for the prediction of the four OTA-producing species tested, with a 69% and 90% sensitivity and specificity, respectively. The preliminary approach demonstrated the high potential of NIR spectroscopy, coupled with Chemometrics, to be used as a real-time automated routine monitorization of dry-cured ham surfaces.
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Quimiometria , Ocratoxinas/análise , Carne de Porco/microbiologia , Espectroscopia de Luz Próxima ao Infravermelho/métodosRESUMO
The development of non-destructive methodologies based on Hyperspectral Imaging (HSI), Nuclear Magnetic Resonance (NMR) and Magnetic Resonance Imaging (MRI) techniques to determine quality characteristics of fresh meat has been reviewed in this study. It has been focused primarily on research published in the last decade, and has placed particular attention on the instrumentation, data acquisition and main applications of each technique, finding a wide variety of possibilities for systems and methodologies as well as evidence of accurate and promising results. Most samples analysed were pork and beef, followed by lamb and chicken, with few studies on fresh meat from rabbit and duck. The overall evaluation is that work has been performed primarily in an experimental way but generally still lacks real application in the meat industry. In that respect, these non-destructive techniques should be improved, especially regarding speed, price and influence of external factors.
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Qualidade dos Alimentos , Carne/análise , Animais , Bovinos , Galinhas , Patos , Imageamento Hiperespectral/métodos , Imageamento por Ressonância Magnética/métodos , Espectroscopia de Ressonância Magnética/métodos , Coelhos , Ovinos , SuínosRESUMO
The study proposes a process analytical technology (PAT) approach for the control of milk coagulation through near infrared spectroscopy (NIRS), computing multivariate statistical process control (MSPC) charts, based on principal component analysis (PCA). Reconstituted skimmed milk and commercial pasteurized skimmed milk were mixed at two different ratios (60:40 and 40:60). Each mix ratio was prepared in six replicates and used for coagulation trials, monitored by fundamental rheology, as a reference method, and NIRS by inserting a probe directly in the coagulation vat and collecting spectra at two different acquisition times, i.e., 60 s or 10 s. Furthermore, three failure coagulation trials were performed, deliberately changing temperature or rennet and CaCl2 concentration. The comparison with fundamental rheology results confirmed the effectiveness of NIRS to monitor milk renneting. The reduced spectral acquisition time (10 s) showed data highly correlated (r > 0.99) to those acquired with longer acquisition time. The developed decision trees, based on PC1 scores and T2 MSPC charts, confirmed the suitability of the proposed approach for the prediction of coagulation times and for the detection of possible failures. In conclusion, the work provides a robust but simple PAT approach to assist cheesemakers in monitoring the coagulation step in real-time.