Detection of adulterations in fruit juices using machine learning methods over FT-IR spectroscopic data

Fruit juices are one of the most adulterated beverages, usually because of the addition of water, sugars, or less expensive fruit juices. This study presents a method based on Fourier transform infrared spectroscopy (FT-IR), in combination with machine learning methods, for the correct identification and quantification of adulterants in juices. Thus, three types of 100% squeezed juices (pineapple, orange, and apple) were evaluated and adulterated with grape juice at different percentages (5%, 10%, 15%, 20%, 30%, 40%, and 50%). The results of the exploratory data analysis revealed a clear clustering trend of the samples according to the type of juice analyzed. The supervised learning analysis, based on the development of models for the detection of adulteration, obtained significant results for all tested methods (i.e., support-vector machines or SVM), random forest or RF, and linear discriminant analysis or LDA) with an accuracy above 97% on the test set. Regarding quantification, the best results are obtained with the support vector regression and with partial least square regression showing an R2 greater than 0.99 and a root mean square error (RMSE) less than 1.4 for the test setPeer ReviewedPostprint (published version

Characterization of Biodegraded Ignitable Liquids by Headspace-Ion Mobility Spectrometry

The detection of ignitable liquids (ILs) can be crucial when it comes to determining arson cases. Such identification of ILs is a challenging task that may be affected by a number of factors. Microbial degradation is considered one of three major processes that can alter the composition of IL residues. Since biodegradation is a time related phenomenon, it should be studied at different stages of development. This article presents a method based on ion mobility spectroscopy (IMS) which has been used as an electronic nose. In particular, ion mobility sum spectrum (IMSS) in combination with chemometric techniques (hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA)) has been applied for the characterization of different biodegraded ILs. This method intends to use IMSS to identify a range of ILs regardless of their degree of biodegradation. Three ILs (diesel, gasoline and kerosene) from three different commercial brands were evaluated after remaining in a soil substrate for several lengths of time (0, 2, 5, 13 and 38 days). The HCA results showed the samples' trend to fall into categories characterized by ILs type and biodegradation time. The LDAs allowed a 99% successful classification of the samples according to the IL type. This is the first time that an HS-IMS technique has been used to detect ILs that have undergone biodegradation processes. The results show that IMS may be a promising alternative to the current standard method based on gas-chromatography for the analysis of biodegraded ILs. Furthermore, no pretreatment of the samples nor the use of a solvent is required

Comparison of different processing approaches by SVM and RF on HS-MS eNose and NIR Spectrometry data for the discrimination of gasoline samples

In the quality control of flammable and combustible liquids, such as gasoline, both rapid analysis and automated data processing are of great importance from an economical viewpoint for the petroleum industry. The present work aims to evaluate the chemometric tools to be applied on the Headspace Mass Spectrometry (HS-MS eNose) and Near-Infrared Spectroscopy (NIRS) results to discriminate gasoline according to their Research Octane Number (RON). For this purpose, data from a total of 50 gasoline samples of two types of RON-95 and 98-analyzed by the two above-mentioned techniques were studied. The HS-MS eNose and NIRS data were com-bined with non-supervised exploratory techniques, such as Hierarchical Cluster Analysis (HCA), as well as other supervised classification techniques, namely Support Vector Machine (SVM) and Random Forest (RF). For su-pervised classification, the low-level data fusion was additionally applied to evaluate if the combined use of the data increases the scope of relevant information. The HCA results showed a clear clustering trend of the gasoline samples according to their RON with HS-MS eNose data. SVM in combination with 5-Fold Cross-Validation successfully classified 100% of the samples with the HS-MS eNose data set. The RF algorithm in combination with 5-Fold Cross-Validation achieved the best accuracy rate for the test set with the low-level data fusion system. Furthermore, it allowed us to identify the most important features that could define the differences between RON 95 and RON 98 gasoline. On the other hand, using the HS-MS eNose and NIRS low-level data fusion reached better results than those obtained using NIRS data individually, with accuracy rates of 100% in both SVM and RF performances with the test set. In general, the performance of the SVM and RF algorithms was found to be similar

A Methodology Based on FT-IR Data Combined with Random Forest Model to Generate Spectralprints for the Characterization of High-Quality Vinegars

Sherry wine vinegar is a Spanish gourmet product under Protected Designation of Origin (PDO). Before a vinegar can be labeled as Sherry vinegar, the product must meet certain requirements as established by its PDO, which, in this case, means that it has been produced following the traditional solera and criadera ageing system. The quality of the vinegar is determined by many factors such as the raw material, the acetification process or the aging system. For this reason, mainly producers, but also consumers, would benefit from the employment of effective analytical tools that allow precisely determining the origin and quality of vinegar. In the present study, a total of 48 Sherry vinegar samples manufactured from three different starting wines (Palomino Fino, Moscatel, and Pedro Ximenez wine) were analyzed by Fourier-transform infrared (FT-IR) spectroscopy. The spectroscopic data were combined with unsupervised exploratory techniques such as hierarchical cluster analysis (HCA) and principal component analysis (PCA), as well as other nonparametric supervised techniques, namely, support vector machine (SVM) and random forest (RF), for the characterization of the samples. The HCA and PCA results present a clear grouping trend of the vinegar samples according to their raw materials. SVM in combination with leave-one-out cross-validation (LOOCV) successfully classified 100% of the samples, according to the type of wine used for their production. The RF method allowed selecting the most important variables to develop the characteristic fingerprint ("spectralprint") of the vinegar samples according to their starting wine. Furthermore, the RF model reached 100% accuracy for both LOOCV and out-of-bag (OOB) sets.The authors would like to thank the winery Bodegas Paez Morilla S.A. for providing the Sherry vinegar samples and for the interest shown in the results of this study and Programa de Fomento e Impulso de la Actividad de Investigacion y Transferencia de la Universidad de Cadiz for the financial support of this manuscript

The influence of maternal respiratory allergy on obstetrics and perinatal outcomes: a nested case–control study

Objective: To evaluate the influence of respiratory allergy on obstetrics and perinatal outcomes. Methods: A nested case–control retrospective study on 41 035 pregnant women. Obstetrics and perinatal outcomes of women with or without respiratory allergy were compared. Rates of preterm delivery (<37 weeks of gestation), low birth weight (<2500 g), neonatal acidosis (pH < 7.20), low 5-min APGAR score (<7), cesarean section rate and indications, and perinatal morbidity and mortality were analyzed. Results are expressed as number and percentages. χ2 and Fisher exact tests were used for comparisons. Logistic regression was used. Statistical significance was set at 95% level (P < 0.05). Results: A total of 724 (1.8%) patients had respiratory allergy, and their rates of preterm delivery and low birth weight were significantly higher than those of control women (both P < 0.001). Nevertheless, analyzing the causes, multiple gestation rate was significantly higher in this group, and adjusting by this, no statistical difference was found in any of the perinatal outcomes studied. In addition, in vitro fertilization and sterility were also significantly higher in the respiratory allergy group (both P < 0.001). Conclusion: Women with respiratory allergy are at higher risks of prematurity and low birth weight but these results are mediated by sterility, in vitro fertilization, and multiple gestation rate. Nonetheless, participation of inflammatory mechanisms should be further studiedThis study did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sector

Single fetal demise in monochorionic twins: how to predict cerebral injury in the survivor co-twin?

The aims of the study were to evaluate perinatal outcome in monochorionic (MC) twins complicated with single intrauterine fetal death, spontaneously vs after fetal therapy, and to assess antenatal events that increase the risk of cerebral injury. Material and methods: Historical cohort study of MC pregnancies with single intrauterine fetal death diagnosed or referred to a tertiary referral hospital (2012–2020). Adverse perinatal outcome included termination of pregnancy, perinatal death, abnormal fetal or neonatal neuroimaging and abnormal neurological development. Results: A total of 68 MC pregnancies with single intrauterine fetal death after 14 weeks of gestation were included. Sixty-five (95.6%) occurred in complicated MC pregnancies (twin to twin transfusion syndrome: 35/68 [51.5%]; discordant malformation: 13/68 [19.1%], selective intrauterine growth restriction: 10/68 [14.7%], twin reversed arterial perfusion sequence: 5/68 [7.3%] and cord entanglement in monoamniotic twins: 2/68 [2.94%]). In 52 cases (76.5%) single intrauterine fetal demise occurred after fetal therapy and in 16 (23.5%) occurred spontaneously. Cerebral damage included 14/68 cases (20.6%): 6/68 cases (8.82%) were prenatal lesions and 8/68 cases (11.8%) were postnatal. Risk of cerebral damage tended to be higher in the spontaneous death group (6/16, 37.5%) compared to the therapy-group (8/52, 15.38%) (p = 0.07). The risk increased with gestational age at intrauterine death (OR 1.21, 95% CI: 1.04–1.41, p = 0.014) and was higher in those surviving co-twins who developed anemia (OR 9.27, 95% CI: 1.50–57.12, p = 0.016). Pregnancies complicated with selective intrauterine growth restriction tended to be at higher risk for neurological damage (OR 2.85, 95% CI: 0.68–11.85, p = 0.15). Preterm birth rate (<37 weeks of pregnancy) was 61.7% (37/60). Seven of eight postnatal cerebral lesions (87.5%) were related to extreme prematurity. Overall perinatal survival rate was 88.3% (57/68) and 7% (4/57) of children had an abnormal neurological outcome. Conclusions: Risk of cerebral damage in single intrauterine fetal death is especially high when it occurs spontaneously. Gestational age at single intrauterine fetal death, selective intrauterine growth restriction and anemia of the surviving co-twin are the main predictors for prenatal lesions and might be useful in parent counseling. Abnormal postnatal neurological outcome is closely related to extreme prematurityThis study has been funded by “Instituto de Salud Carlos III” (ISCIII) through the project 19/00904, and co-funded by the European Union

Tularemia Outbreaks in Spain from 2007 to 2020 in Humans and Domestic and Wild Animals

[EN] In this study, tularemia outbreaks associated with humans and several domestic and wild animals (Iberian hares, wild rabbits, voles, mice, grey shrews, sheep, dogs, foxes, wolves, ticks, and river crayfish) are reported in Spain from 2007 to 2020. Special attention was paid to the outbreaks in humans in 2007-2009 and 2014-2015, when the most important waves occurred. Moreover, positive rates of tularemia in lagomorphs were detected in 2007-2010, followed by negative results in 2011-2013, before again returning to positive rates in 2014 and in 2017 and in 2019-2020. Lagomorphs role in spreading Francisella tularensis in the epidemiological chain could not be discarded. F. tularensis is described for the first time infecting the shrew Crocidura russula worldwide, and it is also reported for the first time infecting wild rabbits (Oryctolagus cuniculus) in Spain. Serological positives higher than 0.4% were seen for sheep only from 2007-2009 and again in 2019, while serological rates greater than 1% were revealed in dogs in 2007-2008 and in wild canids in 2016. F. tularensis were detected in ticks in 2009, 2014-2015, 2017, and 2019. Lastly, negative results were achieved for river crayfish and also in environmental water samples from 2007 to 2020SIThis research received no external funding but was supported by the contract-project called Caracterización molecular de las cepas de Francisella tularensis aisladas en lagomorfos y roedores de Castilla y León, financed by the Dirección General de Producción Agropecuaria e Infraestructuras, Servicio de Sanidad Animal, Consejería de Agricultura y Ganadería de la Junta de Castilla y León. All the isolates are owned by the Junta de Castilla y Leó

Risk of suicide attempt repetition after an index attempt: A systematic review and meta-analysis

Objectives To estimate the risk of suicide attempt repetition among individuals with an index attempt. It also aims to study the role of risk factors and prevention programme in repetition. Methods This systematic review and meta-analysis was conducted in keeping with the PRISMA 2020 guidelines. Studies on attempt repetition (both cohort studies and intervention studies) were searched from inception to 2022. Results A total of 110 studies comprising 248,829 attempters was reviewed. The overall repetition rate was 0.20 (0.17, 0.22). Repetition risk linearly increased over time. A higher risk of attempt repetition was associated with female sex and index attempts in which self-cutting methods were used. Moreover, a mental disorder diagnosis was associated with an increasing repetition risk (OR = 2.02, p < .01). The delivery of a preventive programme reduced the repetition risk, OR = 0.76, p < .05; however, this effect was significant for psychotherapy interventions, OR = 0.38, p < .01. Conclusion One in five suicide attempters will engage in a new suicide attempt. An elevated repetition risk is associated with being female, more severe index methods and psychiatric disorder diagnosis. Preventive programmes, particularly psychotherapy, may contribute to reducing repetition risk and eventually save lives.This study was supported by the Instituto de Salud Carlos III-FIS research grants (PI16/00187, PI19/00236, PI19/00569, PI19/00685, PI19/00941, PI19/00954, PI19/01027, PI19/01256, PI19/01484, PI20/00229), co-funded by the European Regional Development Fund (ERDF) “A Way to Build Europe”; the Government of the Principality of Asturias (grant ref.: PCTI-2018-2022 IDI/2018/235); Secretaria d'Universitats i Recerca from the Departament d'Economia i Coneixement (ref.: 2017SGR1365 and 2017SGR134), and Generalitat de Catalunya (Government of Catalonia), CERCA Programme

Desarrollo de algoritmos predictivos por inteligencia artificial (Deep-learning) para asegurar el éxito del alumno

Breve descripción La adaptación de los planes de estudio a la normativa y a los criterios propuestos por el Espacio Europeo de Educación Superior (EEES) ha conllevado un importante reto de innovación pedagógica, y cambios significativos en el proceso enseñanza-aprendizaje. El sistema universitario español acumula ya una trayectoria y un bagaje importante de experiencias, buenas prácticas e innovaciones que se han ido encaminando hacia la continua mejora de la calidad de la formación ofertada. El proceso de cambio en el que está inmersa hoy en día la Educación Superior demanda nuevos sistemas y procedimientos de enseñanza y evaluación. Dos de los cambios derivados de la implantación del EEES son la elaboración de los plantes de estudio por competencias generales, transversales y específicas, y el diseño de herramientas e iniciativas de mejora de la calidad de los programas formativos, entre otros aspectos. En el contexto anterior, en el presente proyecto se han aplicado una serie de herramientas tecnológicas con el objetivo de mejorar la actividad docente que pretenden implantarse de forma transversal entre asignaturas del grado de Nutrición y Dietética Humana de la Facultad de Medicina de la Universidad Complutense. Además, esta novedosa iniciativa podría utilizarse en cualquier asignatura de cualquier grado de cualquier Facultad de la Universidad Complutense o incluso de otras Universidades. En concreto, el proyecto identifica al comienzo del curso académico a aquellos/as alumnos/as que tendrán dificultades para superar diferentes asignaturas del grado de Nutrición y Dietética Humana, para que el profesorado tome diferentes medidas docentes preventivas desde el mismo comienzo del curso académico. La identificación de estos alumnos al comienzo del curso académico se realizó mediante técnicas de inteligencia artificial para generar un algoritmo de predicción autoalimentado, considerando fundamentalmente una serie de parámetros académicos de los alumnos/as. El proyecto busca reforzar el aprendizaje de los/as alumnos/as que presenten dificultades en superar una asignatura. Esta iniciativa Innova-Docencia es una propuesta innovadora, que conlleva la realización de una actividad común en el que han intervenido personal PDI, PAS y estudiantes

Susceptibility to type 1 diabetes conferred by the PTPN22 C1858T polymorphism in the Spanish population

<p>Abstract</p> <p>Background</p> <p>The protein tyrosine phosphatase N22 gene (<it>PTPN22</it>) encodes a lymphoid-specific phosphatase (LYP) which is an important downregulator of T cell activation. A <it>PTPN22 </it>polymorphism, C1858T, was found associated with type 1 diabetes (T1D) in different Caucasian populations. In this study, we aimed at confirming the role of this variant in T1D predisposition in the Spanish population.</p> <p>Methods</p> <p>A case-control was performed with 316 Spanish white T1D patients consecutively recruited and 554 healthy controls, all of them from the Madrid area. The <it>PTPN22 </it>C1858T SNP was genotyped in both patients and controls using a TaqMan Assay in a 7900 HT Fast Real-Time PCR System.</p> <p>Results</p> <p>We replicated for the first time in a Spanish population the association of the 1858T allele with an increased risk for developing T1D [carriers of allele T vs. CC: OR (95%) = 1.73 (1.17–2.54); p = 0.004]. Furthermore, this allele showed a significant association in female patients with diabetes onset before age 16 years [carriers of allele T vs. CC: OR (95%) = 2.95 (1.45–6.01), female patients vs female controls p = 0.0009]. No other association in specific subgroups stratified for gender, HLA susceptibility or age at onset were observed.</p> <p>Conclusion</p> <p>Our results provide evidence that the <it>PTPN22 </it>1858T allele is a T1D susceptibility factor also in the Spanish population and it might play a different role in susceptibility to T1D according to gender in early-onset T1D patients.</p