Multiple sclerosis (MS) is a multifaceted neurological condition characterized by challenges in timely diagnosis and personalized patient management. The application of Artificial Intelligence (AI) to MS holds promises for early detection, accurate diagnosis, and predictive modeling. The objectives of this study are: 1) to propose new MS trajectory descriptors that could be employed in Machine Learning (ML) regressors and classifiers to predict patient evolution; 2) to explore the contribution of ML models in discerning MS trajectory descriptors using only baseline Magnetic Resonance Imaging (MRI) studies. This study involved 446 MS patients who had a baseline MRI, at least two measurements of Expanded Disability Status Scale (EDSS), and a 1-year follow-up. Patients were divided into two groups: 1) for model development and 2) for evaluation. Three descriptors: β₁, β₂, and EDSS(t), were related to baseline MRI parameters using regression and classification XGBoost models. Shapley Additive Explanations (SHAP) analysis enhanced model transparency by identifying influential features. The results of this study demonstrate the potential of AI in predicting MS progression using the proposed patient trajectories and baseline MRI scans, outperforming classic Multiple Linear Regression (MLR) methods. In conclusion, MS trajectory descriptors are crucial; incorporating AI analysis into MRI assessments presents promising opportunities to advance predictive capabilities. SHAP analysis enhances model interpretation, revealing feature importance for clinical decisions.

Schizophrenia (SZ) is a serious mental disorder that is typically treated with antipsychotic medication. Treatment-resistant schizophrenia (TRS) is the condition where symptoms remain after pharmacological intervention, resulting in long-lasting functional and social impairments. As the identification and treatment of a TRS patient requires previous failed treatments, early mechanisms of detection are needed in order to quicken the access to effective therapy, as well as improve treatment adherence. In this study, we aim to find a microRNA (miRNA) signature for TRS, as well as to shed some light on the molecular pathways potentially involved in this severe condition. To do this, we compared the blood miRNAs of schizophrenia patients that respond to medication and TRS patients, thus obtaining a 16-miRNA TRS profile. Then, we assessed the ability of this signature to separate responders and TRS patients using hierarchical clustering, observing that most of them are grouped correctly (~70% accuracy). We also conducted a network, pathway analysis, and bibliography search to spot molecular pathways potentially altered in TRS. We found that the response to stress seems to be a key factor in TRS and that proteins p53, SIRT1, MDM2, and TRIM28 could be the potential mediators of such responses. Finally, we suggest a molecular pathway potentially regulated by the miRNAs of the TRS profile.

: Nabiximols oromucosal spray,a cannabis-based medicine containing a balanced ratio of Δ-9-tetrahydrocannabinol and cannabidiol, is approved widely as an add-on therapy for symptomatic relief of sp...

The Insulin-like growth factor 2 (IGF-2) has been recently proven to alleviate depressive-like behaviors in both rats and mice models. However, its potential role as a peripheral biomarker has not been evaluated in depression. To do this, we measured plasma IGF-2 and other members of the IGF family such as Binding Proteins (IGFBP-1, IGFBP-3, IGFBP-5 and IGFBP-7) in a depressed group of patients (n = 51) and in a healthy control group (n = 48). In some of these patients (n = 15), we measured these proteins after a period (19 ± 6 days) of treatment with antidepressants. The Hamilton Depressive Rating Scale (HDRS) and the Self-Assessment Anhedonia Scale (SAAS) were used to measure depression severity and anhedonia, respectively. The general cognition state was assessed by the Mini-Mental State Examination (MMSE) test and memory with the Free and Cued Selective Reminding Test (FCSRT). The levels of both IGF-2 and IGFBP-7 were found to be significantly increased in the depressed group; however, only IGF-2 remained significantly elevated after correction by age and sex. On the other hand, the levels of IGF-2, IGFBP-3 and IGFBP-5 were significantly decreased after treatment, whereas only IGFBP-7 was significantly increased. Therefore, peripheral changes in the IGF family and their response to antidepressants might represent alterations at the brain level in depression.

HIV-associated neurocognitive disorders (HANDs) still persist despite improved life expectancy, reduced viral loads, and decreased infection severity. The number of patients affected by HANDs ranges from (30 to 50) % of HIV-infected individuals. The pathological mechanisms contributing to HANDs and the most serious manifestation of the disease, HIV-associated dementia (HAD), are not yet well understood. Evidence suggests that these mechanisms are likely multifactorial, producing neurocognitive complications involving disorders such as neurogenesis, autophagy, neuroinflammation, and mitochondrial dysfunction. Over the years, multiple pharmacological approaches with specific mechanisms of action acting upon distinct targets have been approved. Although these therapies are effective in reducing viral loading to undetectable levels, they also present some disadvantages such as common side effects, the need for administration with a very high frequency, and the possibility of drug resistance. Genetic studies on HANDs provide insights into the biological pathways and mechanisms that contribute to cognitive impairment in people living with HIV-1. Furthermore, they also help identify genetic variants that increase susceptibility to HANDs and can be used to tailor treatment approaches for HIV-1 patients. Identification of the genetic markers associated with disease progression can help clinicians predict which individuals require more aggressive management and by understanding the genetic basis of the disorder, it will be possible to develop targeted therapies to mitigate cognitive impairment. The main goal of this review is to provide details on the epidemiological data currently available and to summarise the genetic (specifically, the genetic makeup of the immune system), transcriptomic, and epigenetic studies available on HANDs to date. In addition, we address the potential pharmacological therapeutic strategies currently being investigated. This will provide valuable information that can guide clinical care, drug development, and our overall understanding of these diseases.

Introduction: Peripheral neurofilament light chain (NfL) reflect neuronal and axonal damage. Most studies have been focused on NfL cerebrospinal fluid measures since peripheral levels were difficult to detect. However, with recent advent of single molecule array (SIMOA) technology, NfL is now detectable peripherally at small concentrations (pg/ml). In neurodegenerative disorders, NfL peripheral levels have been found significantly elevated compared against psychiatric disorders. However, there is still controversy of whether NfL peripheral levels might be altered in psychiatric disorders like major depressive disorder (MDD) when compared against a normal population.Methods: We have measured NfL plasma levels by using single molecule array (SIMOA) technology in a Spanish small cohort of MDD patients (n = 15) and a HC group (n = 15). We have used subjective scales to estimate depression severity (HDRS), anhedonia (SAAS), the general cognitive state (MMSE) and episodic memory (FCSRT) in MDD patients.Results: We have not detected a significant alteration in NfL plasma levels in MDD patients when compared against the HC subjects (U = 97, p-value = 0.532). Moreover, we have not detected any significant correlation between NfL plasma levels with any subjective scales. The only parameter that significantly and positively correlated with NfL plasma levels was age in both MDD and HC.Discussion: Significant alteration in NfL plasma levels in MDD patients might reflect neurobiological changes behind the predisposition to develop future neurodegenerative disorders such as Alzheimer’s or Parkinson’s diseases for which depression represents a risk factor. However, whether there is an increase in NfL due to MDD regardless of the ageing process is still a matter of debate.