Identifying clinical clusters with distinct trajectories in first-episode psychosis through an unsupervised machine learning technique

The extreme variability in symptom presentation reveals that individuals diagnosed with a first-episode psychosis (FEP) may encompass different sub-populations with potentially different illness courses and, hence, different treatment needs. Previous studies have shown that sociodemographic and family environment factors are associated with more unfavorable symptom trajectories. The aim of this study was to examine the dimensional structure of symptoms and to identify individuals’ trajectories at early stage of illness and potential risk factors associated with poor outcomes at follow-up in non-affective FEP. One hundred and forty-four non-affective FEP patients were assessed at baseline and at 2-year follow-up. A Principal component analysis has been conducted to identify dimensions, then an unsupervised machine learning technique (fuzzy clustering) was performed to identify clinical subgroups of patients. Six symptom factors were extracted (positive, negative, depressive, anxiety, disorganization and somatic/cognitive). Three distinct clinical clusters were determined at baseline: mild; negative and moderate; and positive and severe symptoms, and five at follow-up: minimal; mild; moderate; negative and depressive; and severe symptoms. Receiving a low-dose antipsychotic, having a more severe depressive symptomatology and a positive family history for psychiatric disorders were risk factors for poor recovery, whilst having a high cognitive reserve and better premorbid adjustment may confer a better prognosis. The current study provided a better understanding of the heterogeneous profile of FEP. Early identification of patients who could likely present poor outcomes may be an initial step for the development of targeted interventions to improve illness trajectories and preserve psychosocial functioning

Impact of dietary incorporation of Spirulina (Arthrospira platensis) and exogenous enzymes on broiler performance, carcass traits and meat quality

This study assessed the effect of Spirulina (Arthrospira platensis), individually and in combination with exogenous enzymes, on growth performance, carcass traits, and meat quality of broiler chickens. One hundred and twenty Ross 308 male chickens were allocated into 40 battery brooders, with 3 birds per cage, and fed ad libitum a corn-based diet during the first 21 D of the trial. The experimental period lasted from day 21 to 35, during which birds were fed 4 different diets: a corn-soybean basal diet, taken as the control group, a basal diet containing 15% Spirulina (MA), a basal diet containing 15% Spirulina plus 0.005% Rovabio Excel AP (MAR), and a basal diet containing 15% Spirulina plus 0.01% lysozyme (MAL). Body weight gain (P , 0.001) and feed conversion rate (P , 0.001) were improved in control chickens, when compared with those fed with Spirulina. In addition, Spirulina increased the length of duodenum plus jejunum in relation to the other treatment (P , 0.01). Chickens on the MAL diet showed a considerable increase in digesta viscosity (P , 0.05) compared with the control group. Breast and thigh meats from chickens fed with Spirulina, with or without the addition of exogenous enzymes, had higher values of yellowness (b*) (P , 0.001), total carotenoids (P , 0.001), and saturated fatty acids (P , 0.001), whereas n-3 polyunsaturated fatty acid (P , 0.01) and a-tocopherol (P , 0.001) decreased, when compared with the control. In conclusion, the incorporation of 15% Spirulina in broiler diets, individually or combined with exogenous enzymes, reduced birds’ performance through a higher digesta viscosity, which is likely associated with the gelation of microalga indigestible proteins. In addition, cell wall of Spirulina was successfully broken by the addition of lysozyme, but not by Rovabio Excel AP. Therefore, we anticipate that the combination of lysozyme with an exogenous specific peptidase could improve the digestibility of proteins from this microalga and avoid their detrimental gelationinfo:eu-repo/semantics/publishedVersio

Genome-wide association meta-analyses and fine-mapping elucidate pathways influencing albuminuria

Increased levels of the urinary albumin-to-creatinine ratio (UACR) are associated with higher risk of kidney disease progression and cardiovascular events, but underlying mechanisms are incompletely understood. Here, we conduct trans-ethnic (n = 564,257) and European-ancestry specific meta-analyses of genome-wide association studies of UACR, including ancestry- and diabetes-specific analyses, and identify 68 UACR-associated loci. Genetic correlation analyses and risk score associations in an independent electronic medical records database (n = 192,868) reveal connections with proteinuria, hyperlipidemia, gout, and hypertension. Fine-mapping and trans-Omics analyses with gene expression in 47 tissues and plasma protein levels implicate genes potentially operating through differential expression in kidney (including TGFB1, MUC1, PRKCI, and OAF), and allow coupling of UACR associations to altered plasma OAF concentrations. Knockdown of OAF and PRKCI orthologs in Drosophila nephrocytes reduces albumin endocytosis. Silencing fly PRKCI further impairs slit diaphragm formation. These results generate a priority list of genes and pathways for translational research to reduce albuminuria

Design philosophy and use of high voltage power systems for multi-megawatt ion beam accelerators

The requirements for a neutral beam high voltage power system are derived from the characteristics of the ion source. High voltage system component characteristic requirements and choices are described. (MHR

Asian soybean rust control efficacy as a function of application timing under epidemic conditions in Londrina, PR

Com o objetivo de estudar a eficiência do controle da ferrugem asiática da soja em função do momento de aplicação foram conduzidos ensaios em Londrina, PR, Brasil, durante as safras 2005/06 e 2006/07. A mistura de 60 g azoxistrobina ha-1 + 24 g ciproconazol ha-1 foi aplicada em diferentes estádios fenológicos, iniciando em R2 até R5.5, em aplicações únicas e seqüenciais. A severidade foi estimada periodicamente para o cálculo da área abaixo da curva de progresso da doença (AACPD) e a produtividade avaliada no final do ciclo. Nas duas safras, os sintomas iniciais foram observados no final do estádio vegetativo. Na safra 2005/06, o tratamento com aplicações seqüenciais, em R2 e R5.1, foi o mais eficiente na redução da severidade e da AACPD e apresentou a maior produtividade. Na safra 2006/07, os tratamentos com aplicações seqüenciais, em R2 e R5.1, e a aplicação única em R3 apresentaram as menores severidades, menores AACPD e maiores produtividades. Correlações negativas foram encontradas entre as variáveis severidade em R6 e AACPD e a produtividade (-0,83 e -0,84 em 2005/06 e -0,87 e -0,89 em 2006/07). As aplicações realizadas com níveis elevados de severidade, ao redor de 50%, apresentaram produtividade igual à testemunha não tratada.Fungicide trials were carried out in Londrina, PR, Brazil, during the 2005/06 and 2006/07 growing seasons with the objective of evaluating the efficacy of fungicide in Asian soybean rust control at different application times. A premix of 60 g azoxystrobin ha-1 + 24 g cyproconazole ha-1 was applied at different growth stages starting at R2 up to R5.5, and compared to two applications at R2 and R5.1. Following disease onset, disease severity was assessed periodically to calculate the area under disease progress curve (AUDPC). Plot yield was evaluated at harvest. Disease onset in both growing seasons occurred at the vegetative stage. In the 2005/06 season, the two-application treatment was the most efficient in reducing severity and AUDPC and increasing yield. In the 2006/07 season, both two applications and a single application at R3 reduced severity and AUDPC and increased yield compared to other treatments. A highly significant negative correlation was found between disease variables (severity at R6 and AUDPC) and yield in the two seasons (-0.83 and -0.84 in 2005/06 and -0.87 and -0.89 in 2006/07). Fungicide application with disease severity levels around 50% resulted in yield similar to the untreated control

Asian soybean rust control efficacy as a function of application timing under epidemic conditions in Londrina, PR

Com o objetivo de estudar a eficiência do controle da ferrugem asiática da soja em função do momento de aplicação foram conduzidos ensaios em Londrina, PR, Brasil, durante as safras 2005/06 e 2006/07. A mistura de 60 g azoxistrobina ha-1 + 24 g ciproconazol ha-1 foi aplicada em diferentes estádios fenológicos, iniciando em R2 até R5.5, em aplicações únicas e seqüenciais. A severidade foi estimada periodicamente para o cálculo da área abaixo da curva de progresso da doença (AACPD) e a produtividade avaliada no final do ciclo. Nas duas safras, os sintomas iniciais foram observados no final do estádio vegetativo. Na safra 2005/06, o tratamento com aplicações seqüenciais, em R2 e R5.1, foi o mais eficiente na redução da severidade e da AACPD e apresentou a maior produtividade. Na safra 2006/07, os tratamentos com aplicações seqüenciais, em R2 e R5.1, e a aplicação única em R3 apresentaram as menores severidades, menores AACPD e maiores produtividades. Correlações negativas foram encontradas entre as variáveis severidade em R6 e AACPD e a produtividade (-0,83 e -0,84 em 2005/06 e -0,87 e -0,89 em 2006/07). As aplicações realizadas com níveis elevados de severidade, ao redor de 50%, apresentaram produtividade igual à testemunha não tratada.Fungicide trials were carried out in Londrina, PR, Brazil, during the 2005/06 and 2006/07 growing seasons with the objective of evaluating the efficacy of fungicide in Asian soybean rust control at different application times. A premix of 60 g azoxystrobin ha-1 + 24 g cyproconazole ha-1 was applied at different growth stages starting at R2 up to R5.5, and compared to two applications at R2 and R5.1. Following disease onset, disease severity was assessed periodically to calculate the area under disease progress curve (AUDPC). Plot yield was evaluated at harvest. Disease onset in both growing seasons occurred at the vegetative stage. In the 2005/06 season, the two-application treatment was the most efficient in reducing severity and AUDPC and increasing yield. In the 2006/07 season, both two applications and a single application at R3 reduced severity and AUDPC and increased yield compared to other treatments. A highly significant negative correlation was found between disease variables (severity at R6 and AUDPC) and yield in the two seasons (-0.83 and -0.84 in 2005/06 and -0.87 and -0.89 in 2006/07). Fungicide application with disease severity levels around 50% resulted in yield similar to the untreated control

Identifying clinical clusters with distinct trajectories in first-episode psychosis through an unsupervised machine learning technique

Altres ajuts: Ministerio de Ciencia, Innovación y Universidades; Fondo Europeo de Desarrollo Regional (FEDER); CIBER of Mental Health (CIBERSAM); CERCA Programme (Generalitat de Catalunya); Ministerio de Economía y Competitividad; Fundació La Caixa (ID 100010434, under the agreement LCF/PR/GN18/50310006).The extreme variability in symptom presentation reveals that individuals diagnosed with a first-episode psychosis (FEP) may encompass different sub-populations with potentially different illness courses and, hence, different treatment needs. Previous studies have shown that sociodemographic and family environment factors are associated with more unfavorable symptom trajectories. The aim of this study was to examine the dimensional structure of symptoms and to identify individuals' trajectories at early stage of illness and potential risk factors associated with poor outcomes at follow-up in non-affective FEP. One hundred and forty-four non-affective FEP patients were assessed at baseline and at 2-year follow-up. A Principal component analysis has been conducted to identify dimensions, then an unsupervised machine learning technique (fuzzy clustering) was performed to identify clinical subgroups of patients. Six symptom factors were extracted (positive, negative, depressive, anxiety, disorganization and somatic/cognitive). Three distinct clinical clusters were determined at baseline: mild; negative and moderate; and positive and severe symptoms, and five at follow-up: minimal; mild; moderate; negative and depressive; and severe symptoms. Receiving a low-dose antipsychotic, having a more severe depressive symptomatology and a positive family history for psychiatric disorders were risk factors for poor recovery, whilst having a high cognitive reserve and better premorbid adjustment may confer a better prognosis. The current study provided a better understanding of the heterogeneous profile of FEP. Early identification of patients who could likely present poor outcomes may be an initial step for the development of targeted interventions to improve illness trajectories and preserve psychosocial functioning