Verbal fluency in schizophrenia and bipolar disorder - A longitudinal, family study.

Verbal fluency (VF) has been proposed as a putative neurocognitive endophenotype in schizophrenia (SZ) and bipolar disorder (BD). However, this hypothesis has not been examined using a longitudinal family approach. We conducted a five-group, comparative study.

Inflammation and weight change related to neurocognitive and functional impairment in diabetes and psychiatric disorders.

Introduction: Obesity is a global pandemic associated with various cardio-metabolic and psychiatric disorders. Neurocognitive and functional deficits have been associated with several somatic and psychiatric disorders. Adiposity-related inflammation has recently emerged as a key risk factor for neurocognitive and functional impairments.

Inflammation and lipid metabolism as potential biomarkers of memory impairment across type 2 diabetes mellitus and severe mental disorders.

Introduction: Neurocognitive impairment is a transdiagnostic feature across several psychiatric and cardiometabolic conditions. The relationship between inflammatory and lipid metabolism biomarkers and memory performance is not fully understood. This study aimed to identify peripheral biomarkers suitable to signal memory decline from a transdiagnostic and longitudinal perspective.

MICEmi: A method to identify cognitive endophenotypes of mental illnesses.

Background: Characterizing neurocognitive endophenotypes of mental illnesses (MIs) could be useful for identifying at-risk individuals, increasing early diagnosis, improving disease subtyping, and proposing therapeutic strategies to reduce the negative effects of the symptoms, in addition to serving as a scientific basis to unravel the physiopathology of the disease. However, a standardized algorithm to determine cognitive endophenotypes has not yet been developed. The main objective of this study was to present a method for the identification of endophenotypes in MI research.

Public stigma profile toward mental disorders across different university degrees in the University of Valencia (Spain).

Background: A large proportion of studies carried out in recent years in different populations have shown that stigma toward mental disorders is highly prevalent. In the present study we conducted a comprehensive assessment of stigma to describe and compare stigma toward mental disorders in students enrolled in five different university degrees.

Methods: Three hundred and twenty-five students from the University of Valencia (Spain), attending the second term of their first-degree courses in the faculties of medicine, psychology, teaching, economics, and data science participated in this cross-sectional study.

Online polarization and cross-fertilization in multi-cleavage societies: the case of Spain.

The impact of the social media (SM) has been seen on the one hand as the cause of large exacerbation of negative messages, responsible for massively harmful societal phenomenon against democracies. On the other hand, recent studies have begun to look at how these online channels were able to provide a new impulse in human communication. The novelty of our work resides on analysing several axes of polarizations related to different societal topics.

Prediction of the risk of cancer and the grade of dysplasia in leukoplakia lesions using deep learning.

Objectives: To estimate the probability of malignancy of an oral leukoplakia lesion using Deep Learning, in terms of evolution to cancer and high-risk dysplasia.

Materials And Methods: A total of 261 oral leukoplakia lesions with a mean of 5.5 years follow-up were analysed from standard digital photographs.

Immune-Inflammatory Biomarkers Predict Cognition and Social Functioning in Patients With Type 2 Diabetes Mellitus, Major Depressive Disorder, Bipolar Disorder, and Schizophrenia: A 1-Year Follow-Up Study.

Background: Systemic, low-grade immune-inflammatory activity, together with social and neurocognitive performance deficits are a transdiagnostic trait of people suffering from type 2 diabetes mellitus (T2DM) and severe mental illnesses (SMIs), such as schizophrenia (SZ), major depressive disorder (MDD), and bipolar disorder (BD). We aimed to determine if immune-inflammatory mediators were significantly altered in people with SMIs or T2DM compared with healthy controls (HC) and whether these biomarkers could help predict their cognition and social functioning 1 year after assessment.

Methods: We performed a prospective, 1-year follow-up cohort study with 165 participants at baseline (TB), including 30 with SZ, 42 with BD, 35 with MDD, 30 with T2DM, and 28 HC; and 125 at 1-year follow-up (TY), and determined executive domain (ED), global social functioning score (GSFS), and peripheral blood immune-inflammatory and oxidative stress biomarkers.

Specific metabolic syndrome components predict cognition and social functioning in people with type 2 diabetes mellitus and severe mental disorders.

Objective: Obesity and metabolic diseases such as metabolic syndrome (MetS) are more prevalent in people with type 2 diabetes mellitus (T2DM), major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ). MetS components might be associated with neurocognitive and functional impairments in these individuals. The predictive and discriminatory validity of MetS and its components regarding those outcomes were assessed from prospective and transdiagnostic perspectives.

Transdiagnostic neurocognitive deficits in patients with type 2 diabetes mellitus, major depressive disorder, bipolar disorder, and schizophrenia: A 1-year follow-up study.

Background: Neurocognition impairments are critical factors in patients with major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ), and also in those with somatic diseases such as type 2 diabetes mellitus (T2DM). Intriguingly, these severe mental illnesses are associated with an increased co-occurrence of diabetes (direct comorbidity). This study sought to investigate the neurocognition and social functioning across T2DM, MDD, BD, and SZ using a transdiagnostic and longitudinal approach.

Is processing speed a valid neurocognitive endophenotype in bipolar disorder? Evidence from a longitudinal, family study.

Background: Substantial evidence supports the existence of neurocognitive endophenotypes in bipolar disorder (BD), but very few longitudinal studies have included unaffected relatives. In a 5-year, follow-up, family study, we have recently suggested that deficits in manual motor speed and visual memory could be endophenotype candidates for BD. We aimed to explore whether this also applies to processing speed.

Cognitive impairment and consumption of mental healthcare resources in outpatients with bipolar disorder.

Cognitive dysfunction is a major predictor of functional outcomes, and loss of occupational functioning is usually linked with a higher cost of illness. However, the association between cognitive impairment and consumption of health resources has not been studied in bipolar disorder to date. This study aims to examine this relationship.

Grip Strength, Neurocognition, and Social Functioning in People WithType-2 Diabetes Mellitus, Major Depressive Disorder, Bipolar Disorder, and Schizophrenia.

Background: Frailty is a common syndrome among older adults and patients with several comorbidities. Grip strength (GS) is a representative parameter of frailty because it is a valid indicator of current and long-term physical conditions in the general population and patients with severe mental illnesses (SMIs). Physical and cognitive capacities of people with SMIs are usually impaired; however, their relationship with frailty or social functioning have not been studied to date.

Visual memory dysfunction as a neurocognitive endophenotype in bipolar disorder patients and their unaffected relatives. Evidence from a 5-year follow-up Valencia study.

Background: Scarce research has focused on Visual Memory (VM) deficits as a possible neurocognitive endophenotype of bipolar disorder (BD). The main aim of this longitudinal, family study with healthy controls was to explore whether VM dysfunction represents a neurocognitive endophenotype of BD.

Methods: Assessment of VM by Rey-Osterrieth Complex Figure Test (ROCF) was carried out on a sample of 317 subjects, including 140 patients with BD, 60 unaffected first-degree relatives (BD-Rel), and 117 genetically-unrelated healthy controls (HC), on three occasions over a 5-year period (T1, T2, and T3).

Duration of euthymia and predominant polarity in bipolar disorder.

Background: The concept of Predominant Polarity (PP) provides relevant information for clinical practice and has been widely described as course specifier for Bipolar Disorder (BD), however it has not been incorporated in DSM-5 yet. A descriptive study was conducted to identify clinical patterns associated with PP in outpatients attending a Mental Health Unit.

Methods: Clinical and socio-demographic characteristics were assessed from a sample of 118 euthymic outpatients fulfilling DSM 5 criteria for BDI or II recruited at a catchment area.

Manual motor speed dysfunction as a neurocognitive endophenotype in euthymic bipolar disorder patients and their healthy relatives. Evidence from a 5-year follow-up study.

Background: Few studies have examined Manual Motor Speed (MMS) in bipolar disorder (BD). The aim of this longitudinal, family study was to explore whether dysfunctional MMS represents a neurocognitive endophenotype of BD.

Methods: A sample of 291 subjects, including 131 BD patients, 77 healthy first-degree relatives (BD-Rel), and 83 genetically-unrelated healthy controls (HC), was assessed with the Finger-Tapping Test (FTT) on three occasions over a 5-year period.

Optimization of anemia treatment in hemodialysis patients via reinforcement learning.

Objective: Anemia is a frequent comorbidity in hemodialysis patients that can be successfully treated by administering erythropoiesis-stimulating agents (ESAs). ESAs dosing is currently based on clinical protocols that often do not account for the high inter- and intra-individual variability in the patient's response. As a result, the hemoglobin level of some patients oscillates around the target range, which is associated with multiple risks and side-effects.

Application of machine learning techniques to analyse the effects of physical exercise in ventricular fibrillation.

This work presents the application of machine learning techniques to analyse the influence of physical exercise in the physiological properties of the heart, during ventricular fibrillation. To this end, different kinds of classifiers (linear and neural models) are used to classify between trained and sedentary rabbit hearts. The use of those classifiers in combination with a wrapper feature selection algorithm allows to extract knowledge about the most relevant features in the problem.

BELM: Bayesian extreme learning machine.

The theory of extreme learning machine (ELM) has become very popular on the last few years. ELM is a new approach for learning the parameters of the hidden layers of a multilayer neural network (as the multilayer perceptron or the radial basis function neural network). Its main advantage is the lower computational cost, which is especially relevant when dealing with many patterns defined in a high-dimensional space.

Design of a configurable multispectral imaging system based on an AOTF.

In this paper, we present a configurable multispectral imaging system based on an acousto-optic tunable filter (AOTF). Typically, AOTFs are used to filter a single wavelength at a time, but thanks to the use of a versatile sweeping frequency generator implemented with a direct digital synthesizer, the imager may capture a configurable spectral range. Experimental results show a good spectral and imaging response of the system for spectral bandwidth up to a 50 nm.