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Purpose: Malignant melanoma is an aggressive cancer, and there is a notable dearth on epidemiology, clinical and treatment characterization within the Portuguese population. We performed a scoping review to identify real-world evidence studies focused in Portuguese adult patients with malignant melanoma., Methods: A comprehensive search was conducted. After screening, we described the studies by design, sample size, geographics, setting, population, and outcomes reported., Results: The search yielded 54 studies, mainly retrospective (79.6%). The population assessed was heterogeneous varying from patients with melanoma in general to specific types of melanoma, or even more restricted to patients with specific conditions. The evidence found was mostly concerning clinical outcomes (n=46), patients' clinical profile (n=44) and demographic characterization (n=48). Treatment information was described in 30 studies whereas only 18 reported epidemiological parameters. Studies were mainly performed by the major oncology centers in Lisbon, Oporto and Coimbra, and only two evaluated the entire Portuguese population. To allow comparability, only studies including patients with cutaneous malignant melanoma were considered (13 of the 54) for outcomes evaluation analysis. Median OS varied from 18 to 36 months, assessed after melanoma treatment. Incidence was the most reported epidemiological parameter, confirming the increasing number of cutaneous malignant melanoma patients over the years. Only one study reported prevalence and four reported mortality rates., Conclusions: The evidence found confirms the lack of information about malignant melanoma in Portugal, highlighting the need of real-world studies to assess melanoma prevalence and incidence rates, current treatment approaches, and clinical characterization of these patients., (© 2024. The Author(s), under exclusive licence to Federación de Sociedades Españolas de Oncología (FESEO).)

The application of artificial intelligence and machine learning methods for several biomedical applications, such as protein-protein interaction prediction, has gained significant traction in recent decades. However, explainability is a key aspect of using machine learning as a tool for scientific discovery. Explainable artificial intelligence approaches help clarify algorithmic mechanisms and identify potential bias in the data. Given the complexity of the biomedical domain, explanations should be grounded in domain knowledge which can be achieved by using ontologies and knowledge graphs. These knowledge graphs express knowledge about a domain by capturing different perspectives of the representation of real-world entities. However, the most popular way to explore knowledge graphs with machine learning is through using embeddings, which are not explainable. As an alternative, knowledge graph-based semantic similarity offers the advantage of being explainable. Additionally, similarity can be computed to capture different semantic aspects within the knowledge graph and increasing the explainability of predictive approaches. We propose a novel method to generate explainable vector representations, KGsim2vec, that uses aspect-oriented semantic similarity features to represent pairs of entities in a knowledge graph. Our approach employs a set of machine learning models, including decision trees, genetic programming, random forest and eXtreme gradient boosting, to predict relations between entities. The experiments reveal that considering multiple semantic aspects when representing the similarity between two entities improves explainability and predictive performance. KGsim2vec performs better than black-box methods based on knowledge graph embeddings or graph neural networks. Moreover, KGsim2vec produces global models that can capture biological phenomena and elucidate data biases., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Breast cancer (BC) is the most prevalent malignancy affecting women worldwide, including Portugal. While the majority of BC cases are sporadic, hereditary forms account for 5-10% of cases. The most common inherited mutations associated with BC are germline mutations in the BReast CAncer (BRCA) 1/2 gene ( gBRCA1/2 ). They are found in approximately 5-6% of BC patients and are inherited in an autosomal dominant manner, primarily affecting younger women. Pathogenic variants within BRCA1/2 genes elevate the risk of both breast and ovarian cancers and give rise to distinct clinical phenotypes. BRCA proteins play a key role in maintaining genome integrity by facilitating the repair of double-strand breaks through the homologous recombination (HR) pathway. Therefore, any mutation that impairs the function of BRCA proteins can result in the accumulation of DNA damage, genomic instability, and potentially contribute to cancer development and progression. Testing for gBRCA1/2 status is relevant for treatment planning, as it can provide insights into the likely response to therapy involving platinum-based chemotherapy and poly[adenosine diphosphate (ADP)-ribose] polymerase inhibitors (PARPi). The aim of this review was to investigate the impact of HR deficiency in BC, focusing on BRCA mutations and their impact on the modulation of responses to platinum and PARPi therapy, and to share the experience of Unidade Local de Saúde Santa Maria in the management of metastatic BC patients with DNA damage targeted therapy, including those with the Portuguese c.156_157insAlu BRCA2 founder mutation., Competing Interests: The authors declare no conflicts of interest., (© The Author(s) 2024.)

Background and Objectives: Deescalation strategies omitting anthracyclines (AC) have been explored in early human epidermal growth factor receptor 2-positive breast cancer (HER2+ EBC), showing similar efficacy regarding pathological complete response (pCR) and long-term outcomes as AC-containing regimens. The standard treatment for this tumor subtype is based on chemotherapy and dual HER2 blockade with trastuzumab and pertuzumab, with AC-containing regimens remaining a frequent option for these patients, even in non-high-risk cases. The primary aim of this study was to assess and compare the effectiveness of neoadjuvant regimens with and without AC used in the treatment of HER2+ EBC in the clinical practice according to the pCR achieved with each., Methods: This retrospective multicentric study included patients with HER2+ EBC from Portuguese, Spanish, and Chilean hospitals (January 2018-December 2021). Patients receiving neoadjuvant therapy (NAT) with dual HER2 blockade (trastuzumab and pertuzumab), followed by surgery, were included. Statistical analysis used chi-squared/Fisher's exact test for associations, multivariate logistic regression for pCR, and Kaplan-Meier method for event-free survival (EFS). IBM SPSS Statistics 29.0 analyzed the data., Results: The study included 371 patients from eight hospitals. Among them, 237 received sequential AC and taxane-based chemotherapy with 4 cycles of trastuzumab and pertuzumab, while 134 received 6 cycles of TCHP (docetaxel, carboplatinum, trastuzumab, and pertuzumab). The average age of the patients was 52.8 years and 52.7 years, respectively. Omitting AC from the neoadjuvant approach did not preclude achieving pCR [p = 0.246, 95% confidence interval (CI) 0.235-0.257] and was safe regardless of patient characteristics. Relapse rates were 6.8% (16 patients) in the AC group and 4.5% (6 patients) in the TCHP group. Over a median follow-up of 2.9 years, the estimated 3-year EFS was 92.5% in the AC group and 95.4% in the TCHP group (hazard ratio 0.602, 95% CI 0.234-1.547, p = 0.292, favoring TCHP)., Conclusion: This study reports real-world evidence showing similar pCR and EFS outcomes with treatment regimens with and without AC and raises awareness of possible overtreatment and long-term toxicity in some patients with HER2+ EBC with the use of AC., (© 2023. The Author(s).)

Background: Predicting gene-disease associations typically requires exploring diverse sources of information as well as sophisticated computational approaches. Knowledge graph embeddings can help tackle these challenges by creating representations of genes and diseases based on the scientific knowledge described in ontologies, which can then be explored by machine learning algorithms. However, state-of-the-art knowledge graph embeddings are produced over a single ontology or multiple but disconnected ones, ignoring the impact that considering multiple interconnected domains can have on complex tasks such as gene-disease association prediction., Results: We propose a novel approach to predict gene-disease associations using rich semantic representations based on knowledge graph embeddings over multiple ontologies linked by logical definitions and compound ontology mappings. The experiments showed that considering richer knowledge graphs significantly improves gene-disease prediction and that different knowledge graph embeddings methods benefit more from distinct types of semantic richness., Conclusions: This work demonstrated the potential for knowledge graph embeddings across multiple and interconnected biomedical ontologies to support gene-disease prediction. It also paved the way for considering other ontologies or tackling other tasks where multiple perspectives over the data can be beneficial. All software and data are freely available., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Breast sarcomas (BSs), phyllodes tumors (PTs), and desmoid tumors (DTs) are rare entities that arise from connective tissue. BSs can be classified as either primary or secondary, whether they develop de novo or after radiation exposure or lymphedema. PIK3CA seems to play an important common role in different BS. Malignant PTs show similar behavior to BSs, while DTs are locally aggressive but rarely metastasize. BSs usually present as unilateral, painless, rapidly growing masses with rare nodal involvement. The diagnosis should be based on magnetic resonance imaging and a core needle biopsy. Staging should comprise a chest computed tomography (CT) scan (except for benign PT and DT), while abdominal and pelvic CT scans and bone scans should be added in certain subtypes. The mainstay of treatment for localized BS is surgery, with margin goals that vary according to subtype. Radiotherapy and chemotherapy can be used as neoadjuvant or adjuvant approaches, but their use in these settings is not standard. Advanced BS should be treated with systemic therapy, consistent with recommendations for advanced soft tissue sarcomas of other topographies. Given the rarity and heterogeneity of these entities, multidisciplinary and multi-institutional collaboration and treatment at reference centers are critical.

Tumor-infiltrating lymphocytes (TILs) have shown prognostic value in breast cancer. This study evaluated the TILs scores in 186 Portuguese patients diagnosed with early breast cancer, with special focus on HER2 subtype. Stromal TILs were scored on the core needle biopsies, as well as in the resected specimen in HER2+ patients submitted to neoadjuvant treatment with trastuzumab and pertuzumab. TILs were higher in tumors with negative hormone receptor status and HER2 amplifications, and in triple-negative breast cancer. In HER2+ patients treated with dual anti-HER neoadjuvant therapy, the TILs score on the surgical specimen was generally lower than in the biopsy.

Bipolar disorder (BD) is a highly variable and burdensome disease for patients and caregivers. A BD diagnosis almost triples the likelihood of developing dementia as the disease progresses. Neurocognitive reserve appears to be one of the most important influences on lifelong functional outcomes and quality of life in BD. Though several prior studies have assessed the effects of lithium on regional gray and white matter volumes in this population, representative cohorts are typically middle-aged, have a more severe pathology, and are not as commonly assessed in the depressive phase (which represents the majority of most patients' lifespans outside of remission). Here we have shown that positive adaptations with lithium can be observed throughout the brain after only six weeks of monotherapy at low-therapeutic serum levels. Importantly, these results remove some confounders seen in prior studies (patients were treatment free at time of enrollment and mostly treatment naïve). This cohort also includes underrepresented demographics in the literature (young adult patients, mostly bipolar II, and exclusively in the depressed phase). These findings bolster the extensive body of evidence in support of long-term lithium therapy in BD, furthering the possibility of its expanded use to wider demographics., (Copyright © 2022. Published by Elsevier B.V.)

Background: Comorbid anxiety is pervasive and carries an immense psychosocial burden for patients with bipolar disorder. Despite this, trials reporting anxiety-related outcomes in this population are uncommon, particularly with regards to monotherapies., Methods: Patients (n = 31) with both bipolar I or II disorder in current depressive episodes were enrolled in a six-week, open-label, single-center trial assessing the efficacy of lithium monotherapy in treating symptoms depression and comorbid anxiety. Patients were mostly medication-free and lithium-naïve at baseline., Results: Significant improvements in depression (HAMD) and anxiety (HAM-A) were observed at the six-week endpoint, with remission and response rates greater than 50%. There was a positive correlation between endpoint HAM-A scores and HAM-D scores, r = 0.80, (p < 0.01). Improvements were realized at low serum lithium concentrations (0.49 ± 0.20 mEq/L)., Limitations: Lack of placebo control and small sample size warrants validation in larger randomized studies., Conclusions: Taken in the context of prior evidence, lithium may have an important role in treating comorbid anxiety in bipolar disorder, both as adjunct and monotherapy. Lower doses of lithium may provide equivalent efficacy and enhance tolerability and compliance., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Minerals are required in small amounts to sustain metabolic activity in animals, but mineral deficiencies can also lead to metabolic bottlenecks and mineral excesses can induce toxicity. For these reasons, we could reasonably expect that micronutrients are actively regulated around nutritional optima. Honeybees have co-evolved with flowering plants such that their main sources of nutrients are floral pollen and nectar. Like other insects, honeybees balance their intake of multiple macronutrients during food consumption using a combination of pre- and post-ingestive mechanisms. How they regulate their intake of micronutrients using these mechanisms has rarely been studied. Using two-choice feeding assays, we tested whether caged and broodless young workers preferred solutions containing individual salts (NaCl, KCl, CaCl 2 , MgCl 2 ) or metals (FeCl 3 , CuCl 2 , ZnCl 2 , MnCl 2 ) in a concentration-dependent manner. We found that young adult workers could only self-select and optimize their dietary intake around specific concentrations of sodium, iron and copper. Bees largely avoided high concentration mineral solutions to minimize toxicity. These experiments demonstrate the limits of the regulation of intake of micronutrients in honeybees. This is the first study to compare this form of behaviour in one organism for eight different micronutrients. This article is part of the theme issue 'Natural processes influencing pollinator health: from chemistry to landscapes'.

Recently, a new two-dimensional carbon allotrope named biphenylene network (BPN) was experimentally realized. The BPN structure consists of four-, six-, and eight-membered rings of sp 2 -hybridized carbon atoms. In this work, we carried out fully-atomistic reactive (ReaxFF) molecular dynamics simulations to study the mechanical properties and fracture patterns of non-defective and defective (nanocracks) BPN. Results show that, under uniaxial tensile loading, BPN is converted into four distinct morphologies before fracture starts. This conversion process is dependent on the stretching direction. Some of the formed structures contain mainly eight-membered rings, which have different shapes in each morphology. In one of them, a graphitization process occurs before the complete fracture. Importantly, in the presence of nanocracks, no new morphologies are formed. BPN exhibits a distinct fracture process when contrasted to graphene. After the critical strain threshold, the graphene transitions from an elastic to a brittle regime, while BPN can exhibit different inelastic stages. These stages are associated with the appearance of new morphologies. However, BPN shares some of the exceptional graphene properties. BPN Young's modulus and melting point are comparable to graphene, about 1019.4 GPa and 4024 K, respectively.

Automatized scalable healthcare support solutions allow real-time 24/7 health monitoring of patients, prioritizing medical treatment according to health conditions, reducing medical appointments in clinics and hospitals, and enabling easy exchange of information among healthcare professionals. With recent health safety guidelines due to the COVID-19 pandemic, protecting the elderly has become imperative. However, state-of-the-art health wearable device platforms present limitations in hardware, parameter estimation algorithms, and software architecture. This paper proposes a complete framework for health systems composed of multi-sensor wearable health devices (MWHD), high-resolution parameter estimation, and real-time monitoring applications. The framework is appropriate for real-time monitoring of elderly patients' health without physical contact with healthcare professionals, maintaining safety standards. The hardware includes sensors for monitoring steps, pulse oximetry, heart rate (HR), and temperature using low-power wireless communication. In terms of parameter estimation, the embedded circuit uses high-resolution signal processing algorithms that result in an improved measure of the HR. The proposed high-resolution signal processing-based approach outperforms state-of-the-art HR estimation measurements using the photoplethysmography (PPG) sensor., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Pinheiro, Miranda, Praciano, Santos, Mendonça, Javidi, da Costa and de Sousa.)

The most common breast cancer (BC) subtypes are hormone-dependent, being either estrogen receptor-positive (ER + ), progesterone receptor-positive (PR + ), or both, and altogether comprise the luminal subtype. The mainstay of treatment for luminal BC is endocrine therapy (ET), which includes several agents that act either directly targeting ER action or suppressing estrogen production. Over the years, ET has proven efficacy in reducing mortality and improving clinical outcomes in metastatic and nonmetastatic BC. However, the development of ET resistance promotes cancer survival and progression and hinders the use of endocrine agents. Several mechanisms implicated in endocrine resistance have now been extensively studied. Based on the current clinical and pre-clinical data, the present article briefly reviews the well-established pathways of ET resistance and continues by focusing on the three most recently uncovered pathways, which may mediate resistance to ET, namely receptor activator of nuclear factor kappa B ligand (RANKL)/receptor activator of nuclear factor kappa B (RANK), nuclear factor kappa B (NFκB), and Notch. It additionally overviews the evidence underlying the approval of combined therapies to overcome ET resistance in BC, while highlighting the relevance of future studies focusing on putative mediators of ET resistance to uncover new therapeutic options for the disease., Competing Interests: The authors declare that they have no conflicts of interest., (© The Author(s) 2022.)

The diagnosis and treatment of bipolar depression (BDep) poses complex clinical challenges for psychiatry. Proton magnetic resonance spectroscopy ( 1 H-MRS) is a useful imaging tool for investigating in vivo levels of brain neuro-metabolites, critical to understanding the process of mood dysregulation in Bipolar Disorder. Few studies have evaluated longitudinal clinical outcomes in BDep associated with 1 H-MRS metabolic changes. This study aimed to longitudinally assess brain 1 H-MRS metabolites in the anterior cingulate cortex (ACC) correlated with improvement in depression (from BDep to euthymia) after lithium treatment in BDep patients versus matched healthy controls (HC). Twenty-eight medication-free BDep patients and 28 HC, matched for age and gender, were included in this study. All subjects were submitted to a 3-Tesla brain 1 H-MRS scan in the ACC using a single-voxel (8cm 3 ) PRESS sequence at baseline. At follow-up (6 weeks), 14 BDep patients repeated the exam in euthymia. Patients with current BDep had higher baseline Myo-inositol/Cr (mI/Cr) and Choline/Cr (Cho/Cr) compared to HC. After six weeks, mI/Cr or Cho/Cr levels in subjects that achieved euthymia no longer differed to levels in HC, while high Cho/Cr levels persisted in non-responders . Elevated ACC mI/Cr and Cho/Cr in BDep might indicate increased abnormal membrane phospholipid metabolism and phosphatidylinositol (PI) cycle activity. Return of mI/Cr and Cho/Cr to normal levels after lithium-induced euthymia suggests a critical regulatory effect of lithium targeting the PI cycle involved in mood regulation., Competing Interests: Declaration of Competing Interest None of the authors report biomedical financial interests or potential conflicts of interest., (Copyright © 2021. Published by Elsevier B.V.)

Currently, social networks present information of great relevance to various government agencies and different types of companies, which need knowledge insights for their business strategies. From this point of view, an important technique for data analysis is to create and maintain an environment for collecting data and transforming them into intelligence information to enable analysts to observe the evolution of a given topic, elaborate the analysis hypothesis, identify botnets, and generate data to aid in the decision-making process. Focusing on collecting, analyzing, and supporting decision-making, this paper proposes an architecture designed to monitor and perform anonymous real-time searches in tweets to generate information allowing sentiment analysis on a given subject. Therefore, a technological structure and its implementation are defined, followed by processes for data collection and analysis. The results obtained indicate that the proposed solution provides a high capacity to collect, process, search, analyze, and view a large number of tweets in several languages, in real-time, with sentiment analysis capabilities, at a low cost of implementation and operation.

Molecular crystals have been used as prototypes for studying the energetic and dynamic properties of charge carriers in organic electronics. The growing interest in oligoacenes and fused-ring oligothiophenes in the last two decades is due, in particular, to the success achieved in conceiving pentacene-based organic photovoltaic devices. In the present work, a one-dimensional Holstein-Peierls model is designed to study the temperature-dependent polaron transport in pentathienoacene (PTA) lattices. The tight-binding Hamiltonian employed here takes into account intra and intermolecular electron-lattice interactions. Results reveal that polarons in PTAs can be stable structures even at high temperatures, about 400 K. During the dynamical process, these charge carriers present a typical 1D random walk diffusive motion with a low activation energy of 13 meV and a room temperature diffusivity constant of 1.07 × 10 -3 cm 2 s -1 . Importantly, these critical values for the polaron diffusion and activation energy are related to the choice of model parameters, which are adopted to describe pristine lattices.

Due to the drastic increase of electricity prosumers, i.e., energy consumers that are also producers, smart grids have become a key solution for electricity infrastructure. In smart grids, one of the most crucial requirements is the privacy of the final users. The vast majority of the literature addresses the privacy issue by providing ways of hiding user's electricity consumption. However, open issues in the literature related to the privacy of the electricity producers still remain. In this paper, we propose a framework that preserves the secrecy of prosumers' identities and provides protection against the traffic analysis attack in a competitive market for energy trade in a Neighborhood Area Network (NAN). In addition, the amount of bidders and of successful bids are hidden from malicious attackers by our framework. Due to the need for small data throughput for the bidders, the communication links of our framework are based on a proprietary communication system. Still, in terms of data security, we adopt the Advanced Encryption Standard (AES) 128 bit with Exclusive-OR (XOR) keys due to their reduced computational complexity, allowing fast processing. Our framework outperforms the state-of-the-art solutions in terms of privacy protection and trading flexibility in a prosumer-to-prosumer design.

Background: In recent years, biomedical ontologies have become important for describing existing biological knowledge in the form of knowledge graphs. Data mining approaches that work with knowledge graphs have been proposed, but they are based on vector representations that do not capture the full underlying semantics. An alternative is to use machine learning approaches that explore semantic similarity. However, since ontologies can model multiple perspectives, semantic similarity computations for a given learning task need to be fine-tuned to account for this. Obtaining the best combination of semantic similarity aspects for each learning task is not trivial and typically depends on expert knowledge., Results: We have developed a novel approach, evoKGsim, that applies Genetic Programming over a set of semantic similarity features, each based on a semantic aspect of the data, to obtain the best combination for a given supervised learning task. The approach was evaluated on several benchmark datasets for protein-protein interaction prediction using the Gene Ontology as the knowledge graph to support semantic similarity, and it outperformed competing strategies, including manually selected combinations of semantic aspects emulating expert knowledge. evoKGsim was also able to learn species-agnostic models with different combinations of species for training and testing, effectively addressing the limitations of predicting protein-protein interactions for species with fewer known interactions., Conclusions: evoKGsim can overcome one of the limitations in knowledge graph-based semantic similarity applications: the need to expertly select which aspects should be taken into account for a given application. Applying this methodology to protein-protein interaction prediction proved successful, paving the way to broader applications.

The ability to compare entities within a knowledge graph is a cornerstone technique for several applications, ranging from the integration of heterogeneous data to machine learning. It is of particular importance in the biomedical domain, where semantic similarity can be applied to the prediction of protein-protein interactions, associations between diseases and genes, cellular localization of proteins, among others. In recent years, several knowledge graph-based semantic similarity measures have been developed, but building a gold standard data set to support their evaluation is non-trivial. We present a collection of 21 benchmark data sets that aim at circumventing the difficulties in building benchmarks for large biomedical knowledge graphs by exploiting proxies for biomedical entity similarity. These data sets include data from two successful biomedical ontologies, Gene Ontology and Human Phenotype Ontology, and explore proxy similarities calculated based on protein sequence similarity, protein family similarity, protein-protein interactions and phenotype-based gene similarity. Data sets have varying sizes and cover four different species at different levels of annotation completion. For each data set, we also provide semantic similarity computations with state-of-the-art representative measures. Database URL: https://github.com/liseda-lab/kgsim-benchmark., (© The Author(s) 2020. Published by Oxford University Press.)

Armchair graphene nanoribbons (AGNRs) may present intrinsic semiconducting bandgaps, being of potential interest in developing new organic-based optoelectronic devices. The induction of a bandgap in AGNRs results from quantum confinement effects, which reduce charge mobility. In this sense, quasiparticles' effective mass becomes relevant for the understanding of charge transport in these systems. In the present work, we theoretically investigate the drift of different quasiparticle species in AGNRs employing a 2D generalization of the Su-Schrieffer-Heeger Hamiltonian. Remarkably, our findings reveal that the effective mass strongly depends on the nanoribbon width and its value can reach 60 times the mass of one electron for narrow lattices. Such underlying property for quasiparticles, within the framework of gap tuning engineering in AGNRs, impact the design of their electronic devices.

Although Global Navigation Satellite Systems (GNSS) receivers currently achieve high accuracy when processing their geographic location under line of sight (LOS), multipath interference and noise degrades the accuracy considerably. In order to mitigate multipath interference, receivers based on multiple antennas became the focus of research and technological development. In this context, tensor-based approaches based on Parallel Factor Analysis (PARAFAC) models have been proposed in the literature, providing optimum performance. State-of-the-art techniques for antenna array based GNSS receivers compute singular value decomposition (SVD) for each new sample, implying into a high computational complexity, being, therefore, prohibitive for real-time applications. Therefore, in order to reduce the computational complexity of the parameter estimates, subspace tracking algorithms are essential. In this work, we propose a tensor-based subspace tracking framework to reduce the overall computational complexity of the highly accurate tensor-based time-delay estimation process.

Purpose The Radiological Society of North America (RSNA) Pediatric Bone Age Machine Learning Challenge was created to show an application of machine learning (ML) and artificial intelligence (AI) in medical imaging, promote collaboration to catalyze AI model creation, and identify innovators in medical imaging. Materials and Methods The goal of this challenge was to solicit individuals and teams to create an algorithm or model using ML techniques that would accurately determine skeletal age in a curated data set of pediatric hand radiographs. The primary evaluation measure was the mean absolute distance (MAD) in months, which was calculated as the mean of the absolute values of the difference between the model estimates and those of the reference standard, bone age. Results A data set consisting of 14 236 hand radiographs (12 611 training set, 1425 validation set, 200 test set) was made available to registered challenge participants. A total of 260 individuals or teams registered on the Challenge website. A total of 105 submissions were uploaded from 48 unique users during the training, validation, and test phases. Almost all methods used deep neural network techniques based on one or more convolutional neural networks (CNNs). The best five results based on MAD were 4.2, 4.4, 4.4, 4.5, and 4.5 months, respectively. Conclusion The RSNA Pediatric Bone Age Machine Learning Challenge showed how a coordinated approach to solving a medical imaging problem can be successfully conducted. Future ML challenges will catalyze collaboration and development of ML tools and methods that can potentially improve diagnostic accuracy and patient care. © RSNA, 2018 Online supplemental material is available for this article. See also the editorial by Siegel in this issue.

Learning Objective: After participating in this activity, learners should be better able to evaluate the evidence supporting the antidepressant effects of glutamatergic modulators.Both preclinical and clinical studies have implicated glutamatergic system dysfunction in the pathophysiology of mood disorders such as bipolar depression and major depressive disorder. In particular, rapid reductions in depressive symptoms have been noted in response to subanesthetic doses of the glutamatergic modulator ketamine in subjects with major depressive disorder or bipolar depression. These results have prompted the repurposing or development of other glutamatergic modulators, both as monotherapy or adjunctive to other therapies. Here, we highlight the evidence supporting the antidepressant effects of various glutamatergic modulators, including (1) broad glutamatergic modulators (ketamine, esketamine, dextromethorphan, dextromethorphan-quinidine [Nuedexta], AVP-786, nitrous oxide [N2O], AZD6765), (2) subunit (NR2B)-specific N-methyl-D-aspartate (NMDA) receptor antagonists (CP-101,606/traxoprodil, MK-0657 [CERC-301]), (3) glycine-site partial agonists (D-cycloserine, GLYX-13, sarcosine, AV-101), and (4) metabotropic glutamate receptor modulators (AZD2066, RO4917523/basimglurant, JNJ40411813/ADX71149, R04995819 [RG1578]).

Organic nanofibers have found various applications in optoelectronic devices. In such devices, exciton diffusion is a major aspect concerning their efficiency. In the case of singlet excitons, Förster transfer is the mechanism responsible for this process. Temperature and morphology are factors known to influence exciton diffusion but are not explicitly considered in the expressions for the Förster rate. In this work, we employ a Kinetic Monte Carlo (KMC) model to investigate singlet exciton diffusion in para-hexaphenyl (P6P) and α-sexithiophene (6T) nanofibers. Building from previous experimental and theoretical studies that managed to obtain temperature dependent values for Förster radii, exciton average lifetimes and intermolecular distances, our model is able to indicate how these parameters translate into diffusion coefficients and diffusion lengths. Our results indicate that these features strongly depend on the coordination number in the material. Furthermore, we show how all these features influence the emitted light color in systems composed of alternating layers of P6P and 6T. Finally, we present evidence that the distribution of exciton displacements may result in overestimation of diffusion lengths in experimental setups.

Patients with major depressive disorder (MDD) have clinically relevant, significant decreases in bone mineral density (BMD). We sought to determine if predictive markers of bone inflammation-the osteoprotegerin (OPG)-RANK-RANKL system or osteopontin (OPN)-play a role in the bone abnormalities associated with MDD and, if so, whether ketamine treatment corrected the abnormalities. The OPG-RANK-RANKL system plays the principal role in determining the balance between bone resorption and bone formation. RANKL is the osteoclast differentiating factor and diminishes BMD. OPG is a decoy receptor for RANKL, thereby increasing BMD. OPN is the bone glue that acts as a scaffold between bone tissues matrix composition to bind them together and is an important component of bone strength and fracture resistance. Twenty-eight medication-free inpatients with treatment-resistant MDD and 16 healthy controls (HCs) participated in the study. Peripheral bone marker levels and their responses to IV ketamine infusion in MDD patients and HCs were measured at four time points: at baseline, and post-infusion at 230 min, Day 1, and Day 3. Patients with MDD had significant decreases in baseline OPG/RANKL ratio and in plasma OPN levels. Ketamine significantly increased both the OPG/RANKL ratio and plasma OPN levels, and significantly decreased RANKL levels. Bone marker levels in HCs remained unaltered. We conclude that the OPG-RANK-RANKL system and the OPN system play important roles in the serious bone abnormalities associated with MDD. These data suggest that, in addition to its antidepressant effects, ketamine also has a salutary effect on a major medical complication of depressive illness.

The dynamical properties of polarons in armchair graphene nanoribbons (GNR) is numerically investigated in the framework of a two-dimensional tight-binding model that considers spin-orbit (SO) coupling and electron-lattice (e-l) interactions. Within this physical picture, novel polaron properties with no counterparts to results obtained from conventional tight-binding models are obtained. Our findings show that, depending on the system's width, the presence of SO coupling changes the polaron's charge localization giving rise to different degrees of stability for the charge carrier. For instance, the joint action of SO coupling and e-l interactions could promote a slight increase on the charge concentration in the center of the lattice deformation associated to the polaron. As a straightforward consequence, this process of increasing stability would lead to a depreciation in the polaron's motion by decreasing its saturation velocity. Our finds are in good agreement with recent experimental investigations for the charge localization in GNR, mostly when it comes to the influence of SO coupling. Moreover, the contributions reported here provide a reliable method for future works to evaluate spin-orbit influence on the performance of graphene nanoribbons.

Genetic-neuroimaging paradigms could provide insights regarding the pathophysiology of bipolar disorder (BD). Nevertheless, findings have been inconsistent across studies. A systematic review of gene-imaging studies involving individuals with BD was conducted across electronic major databases from inception until January 9th, 2017. Forty-four studies met eligibility criteria (N=2122 BD participants). Twenty-six gene variants were investigated across candidate gene studies and 4 studies used a genome-wide association approach. Replicated evidence (i.e. in >2 studies) suggests that individuals with BD carrying the BDNF Val66Met risk allele could have reduced hippocampal volumes compared to non-carriers. This review underscores the potential of gene-neuroimaging paradigms to provide mechanistic insights for BD. However, this systematic review found a single replicated finding. Suggestions to improve the reproducibility of this emerging field are provided, including the adoption of a trans-diagnostic approach., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Both bipolar disorder (BD) and major depressive disorder (MDD) have high morbidity and share a genetic background. Treatment options for these mood disorders are currently suboptimal for many patients; however, specific genetic variables may be involved in both pathophysiology and response to treatment. Agents such as the glutamatergic modulator ketamine are effective in treatment-resistant mood disorders, underscoring the potential importance of the glutamatergic system as a target for improved therapeutics. Here we review genetic studies linking the glutamatergic system to the pathophysiology and therapeutics of mood disorders. We screened 763 original genetic studies of BD or MDD that investigated genes encoding targets of the pathway/mediators related to the so-called tripartite glutamate synapse, including pre- and post-synaptic neurons and glial cells; 60 papers were included in this review. The findings suggest the involvement of glutamate-related genes in risk for mood disorders, treatment response, and phenotypic characteristics, although there was no consistent evidence for a specific gene. Target genes of high interest included GRIA3 and GRIK2 (which likely play a role in emergent suicidal ideation after antidepressant treatment), GRIK4 (which may influence treatment response), and GRM7 (which potentially affects risk for mood disorders). There was stronger evidence that glutamate-related genes influence risk for BD compared with MDD. Taken together, the studies show a preliminary relationship between glutamate-related genes and risk for mood disorders, suicide, and treatment response, particularly with regard to targets on metabotropic and ionotropic receptors.

Objective: Mitochondrial dysfunction and energy metabolism impairment are key components in the pathophysiology of bipolar disorder (BD) and may involve a shift from aerobic to anaerobic metabolism. Measurement of brain lactate in vivo using proton magnetic resonance spectroscopy (H-MRS) represents an important tool to evaluate mitochondrial and metabolic dysfunction during mood episodes, as well as to monitor treatment response. To date, very few studies have quantified brain lactate in BD. In addition, no study has longitudinally evaluated lactate using H-MRS during depressive episodes or its association with mood stabilizer therapy. This study aimed to evaluate cingulate cortex (CC) lactate using 3-T H-MRS during acute depressive episodes in BD and the possible effects induced by lithium monotherapy., Methods: Twenty medication-free outpatients with short length of BD (80% drug-naive) in a current major depressive episode were matched with control subjects. Patients were treated for 6 weeks with lithium monotherapy at therapeutic doses in an open-label trial (blood level, 0.48 ± 0.19 mmol/L). Cingulate cortex lactate was measured before (week 0) and after lithium therapy (week 6) using H-MRS. Antidepressant efficacy was assessed with the 21-item Hamilton Depression Rating Scale as the primary outcome., Results: Subjects with BD depression showed a significantly higher CC lactate in comparison to control subjects. Furthermore, a significant decrease in CC lactate was observed after 6 weeks of lithium treatment compared with baseline (P = 0.002). CC Lactate levels was associated with family history of mood disorders and plasma lithium levels., Conclusions: This is the first report of increased CC lactate in patients with bipolar depression and lower levels after lithium monotherapy for 6 weeks. These findings indicate a shift to anaerobic metabolism and a role for lactate as a state marker during mood episodes. Energy and redox dysfunction may represent key targets for lithium's therapeutic actions., Competing Interests: DECLARATION OF INTEREST A patent for the use of ketamine in depression has been awarded that lists Dr. Zarate among the inventors; he has assigned his rights on the patent to the US government, but will share a percentage of any royalties that may be received by the government. All other authors declare no potential conflict of interest.

Introduction: Real-world effectiveness trials suggest that antidepressant efficacy is limited in many patients with mood disorders, underscoring the urgent need for novel therapeutics to treat these disorders. Areas covered: Here, we review the clinical evidence supporting the use of novel modulators for the treatment of mood disorders, including specific glutamate modulators such as: 1) high-trapping glutamatergic modulators; 2) subunit (NR2B)-specific N-methyl-D-aspartate (NMDA) receptor antagonists; 3) NMDA receptor glycine-site partial agonists; and 4) metabotropic glutamate receptor (mGluR) modulators. We also discuss other promising, non-glutamatergic targets for potential rapid antidepressant effects in mood disorders, including the cholinergic system, the glucocorticoid system, and the inflammation pathway, as well as several additional targets of interest. Clinical evidence is emphasized, and non-pharmacological somatic treatments are not reviewed. In general, this paper only explores agents available in the United States. Expert commentary: Of these novel targets, the most promising - and the ones for whom the most evidence exists - appear to be the ionotropic glutamate receptors. However, moving forward will require us to fully embrace the goal of personalized medicine and will require health professionals to pre-emptively identify potential responders.

We previously found that body mass index (BMI) strongly predicted response to ketamine. Adipokines have a key role in metabolism (including BMI). They directly regulate inflammation and neuroplasticity pathways and also influence insulin sensitivity, bone metabolism and sympathetic outflow; all of these have been implicated in mood disorders. Here, we sought to examine the role of three key adipokines-adiponectin, resistin and leptin-as potential predictors of response to ketamine or as possible transducers of its therapeutic effects. Eighty treatment-resistant subjects who met DSM-IV criteria for either major depressive disorder (MDD) or bipolar disorder I/II and who were currently experiencing a major depressive episode received a single ketamine infusion (0.5 mg kg -1 for 40 min). Plasma adipokine levels were measured at three time points (pre-infusion baseline, 230 min post infusion and day 1 post infusion). Overall improvement and response were assessed using percent change from baseline on the Montgomery-Asberg Depression Rating Scale and the Hamilton Depression Rating Scale. Lower baseline levels of adiponectin significantly predicted ketamine's antidepressant efficacy, suggesting an adverse metabolic state. Because adiponectin significantly improves insulin sensitivity and has potent anti-inflammatory effects, this finding suggests that specific systemic abnormalities might predict positive response to ketamine. A ketamine-induced decrease in resistin was also observed; because resistin is a potent pro-inflammatory compound, this decrease suggests that ketamine's anti-inflammatory effects may be transduced, in part, by its impact on resistin. Overall, the findings suggest that adipokines may either predict response to ketamine or have a role in its possible therapeutic effects., Competing Interests: CAZ is listed as a co-inventor on a patent application for the use of ketamine and its metabolites in major depression. He has assigned his rights in the patent to the US government but will share a percentage of any royalties that may be received by the government. The remaining authors declare no conflict of interest.

This study analyzes the number of medical appointments and referrals performed in primary health care in Brazil focusing on the Mais Médicos Program (More Doctors Program). It is a cross-sectional study on the work of physicians included, or not, to the Mais Médicos Program in 2014. Based on validation protocols, a unified database was created from two health information system databases - SIAB and ESUS. Absolute indicators were defined: the total of medical appointments per month; medical referrals and community health education activities. In addition, other indicators were considered, such as weekly rates and productivity of appointments, in line with the profile of Brazilian municipalities. The mean of all appointments was 285 per month corresponding to an average of 14.4 appointments/day. In the poorest municipalities, the figures for the Mais Médicos Program physicians were higher than national rates. The educational activities provided by primary care teams that included a Mais Médicos Program professional were higher in Brazilian capital cities. The Mais Médicos Program achieved one of its main goals, which was to increase health access for vulnerable populations and to contribute towards the consolidation of primary health care in Brazil.

Background: Major depressive disorder (MDD) is a highly prevalent, heterogeneous and systemic medical condition. Treatment options are limited, and recent studies have suggested that physical exercise can play an important role in the therapeutics of MDD. The aim of this study was to evaluate the antidepressant efficacy of adjunctive aerobic activity in association with pharmacotherapy (selective serotonin reuptake inhibitor) in symptomatic MDD as well as its association with physiological biomarkers., Methods: In this randomized, single-blind, add-on, controlled clinical trial, 57 patients (18-55 years of age) were followed-up for 28 days. All patients were drug-free, had been diagnosed with symptomatic MDD and received flexible dose of sertraline during the trial. Patients were randomized to either a 4-week program (4x/week) of add-on aerobic exercise (exercise group, N = 29) or no activity (control group, N = 28). Depression severity was assessed using the Hamilton Rating Scale for Depression (HAM-D) as the primary outcome. At baseline and endpoint, all patients underwent a comprehensive metabolic/cardiopulmonary exercise testing-including determination of maximal oxygen uptake (VO2max), VO2 at the second ventilatory threshold (VO2-VT2), and oxygen pulse (O2 pulse)., Results: Depression scores significantly decreased in both groups after intervention. Importantly, patients in the aerobic exercise group required lower sertraline dose compared to the control group (sertraline monotherapy). The VO2max and O2 pulse parameters increased over time only in the exercise group and remained unchanged in the control group., Conclusions: The present findings suggest that a 4-week training of aerobic exercise significantly improves functional capacity in patients with MDD and may be associated with antidepressant efficacy. This approach may also decrease the need for higher doses of antidepressants to achieve response. Further studies in unmedicated and treatment-resistant MDD patients are needed in order to confirm the utility of short-term aerobic exercise as an alternative therapeutic approach in MDD., Trial Registration: ClinicalTrials.gov NCT02427789.

Objective: The objective of this study was to evaluate brain lithium levels using (7) Li magnetic resonance spectroscopy after 6 weeks of lithium therapy in bipolar depression to test the hypothesis that brain and plasma lithium are correlated. It was also tested whether responders and remitters have different pharmacokinetics, blood and brain lithium levels (ratio) compared with those presenting suboptimal antidepressant improvement., Method: Twenty-three patients with bipolar disorder (I and II) during depressive episodes were included and followed up for 6 weeks at the University of Sao Paulo using flexible dose of lithium (450-900 mg/day). Sixteen patients were drug-naïve. At endpoint, patients underwent a (7) Li-MRS scan and brain lithium concentrations were calculated., Results: A significant association between central and peripheral lithium levels was found only in remitters (r = 0.7, P = 0.004) but not in non-remitters (r = -0.12, P = 0.76). Also, brain lithium (but not plasma) was inversely correlated with age (r = -0.46, P = 0.025). Plasma lithium did not correlate with any clinical outcome, lithium dosage or adverse effects., Conclusion: These findings suggest that non-remitters may not transport lithium properly to the brain, which may underlie treatment resistance to lithium in BD. Future studies with (7) Li-MRS integrated with the evaluation of blood-brain barrier transport mechanisms and longitudinal clinical outcomes in BD and aging are warranted., (© 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

The anterior cingulate cortex (ACC) is a key area in mood regulation. To date, no longitudinal study has specifically evaluated lithium׳s effects on ACC metabolites using (1)H-MRS, as well as its association with clinical improvement in bipolar depression. This (1)H-MRS (TE=35ms) study evaluated 24 drug-free BD patients during depressive episodes and after lithium treatment at therapeutic levels. Brain metabolite levels (N-acetyl aspartate (NAA), creatine (tCr), choline, myo-inositol, and glutamate levels) were measured in the ACC at baseline (week 0) and after lithium monotherapy (week 6). The present investigation showed that ACC glutamate (Glu/tCr) and glutamate+glutamine (Glx/tCr) significantly increased after six weeks of lithium therapy. Regarding the association with clinical improvement, remitters showed an increase in myoinositol levels (mI/tCr) after lithium treatment compared to non-remitters. The present findings reinforce a role for ACC glutamate-glutamine cycling and myoinositol pathway as key targets for lithium׳s therapeutic effects in BD., (Published by Elsevier B.V.)

Several lines of evidence suggest a role for mitochondrial dysfunction in the pathophysiology of bipolar disorder (BD). The tricarboxylic acid cycle (TCA cycle) is fundamental for mitochondrial energy production and produces substrates used in oxidative phosphorylation by the mitochondrial electron transport chain. The activity of the key TCA cycle enzymes citrate synthase, malate dehydrogenase, and succinate dehydrogenase has never been evaluated in BD. In the present study, these enzymes were assayed from leukocytes of drug-naïve BD patients in a major depressive episode (n=18) and compared to 24 age-matched healthy controls. Drug-naïve BD patients did not show differences in activities of citrate synthase (p=0.79), malate dehydrogenase (p=0.17), and succinate dehydrogenase (p=0.35) compared with healthy controls. No correlation between any TCA cycle enzyme activity and severity of depressive symptoms was observed. Overall, these data suggest that the activities of the TCA cycle enzymes are not altered in major depressive episodes of recent-onset BD, which may support the concept of illness staging and neuroprogression in BD., (Published by Elsevier Ireland Ltd.)

Objective: To assess the relationship between cognitive function, a proposed schizophrenia endophenotype, and two genetic polymorphisms related to dopamine function, catechol-O-methyl transferase (COMT) Val158Met and dopamine receptor 3 (DRD3) Ser9Gly., Methods: Fifty-eight outpatients with schizophrenia/schizoaffective disorder and 88 healthy controls underwent neurocognitive testing and genotyping. Analyses of covariance (ANCOVAs) using age, sex, and years of education as covariates compared cognitive performance for the proposed genotypes in patients and controls. ANCOVAs also tested for the epistatic effect of COMT and DRD3 genotype combinations on cognitive performance., Results: For executive functioning, COMT Val/Val patients performed in a similar range as controls (30.70-33.26 vs. 35.53-35.67), but as COMT Met allele frequency increased, executive functioning worsened. COMT Met/Met patients carrying the DRD3 Ser/Ser genotype performed poorest (16.184 vs. 27.388-31.824). Scores of carriers of this COMT/DRD3 combination significantly differed from all DRD3 Gly/Gly combinations (p < 0.05), from COMT Val/Met DRD3 Ser/Gly (p = 0.02), and from COMT Val/Val DRD3 Ser/Ser (p = 0.01) in patients. It also differed significantly from all control scores (p < 0.001)., Conclusion: Combined genetic polymorphisms related to dopamine neurotransmission might influence executive function in schizophrenia. Looking at the effects of multiple genes on a single disease trait (epistasis) provides a comprehensive and more reliable way to determine genetic effects on endophenotypes.

Strong evidence implicates intracellular signaling cascades dysfunction in the pathophysiology of Bipolar Disorder (BD). Regulation of AKT/mTOR pathway is a critical signaling pathway in synaptic neurotransmission and plasticity, also modulating cell proliferation and migration. Gene expression of the AKT/mTOR pathway was assessed in 25 BD (DSM-IV-TR criteria) unmedicated depressed individuals at baseline and after 6 weeks of lithium therapy and 31 matched healthy controls. Decreases in blood AKT1 and mTOR mRNA expression, as well as in BAD/BCL-2 expression ratio were observed in short-term BD patients during depressive episodes in comparison to healthy controls. There was no significant change in the expression of AKT1, mTOR, BCL-2, BAD and NDUFA6 after lithium therapy in the total group of BD subjects. However, the changes in AKT1 expression after lithium treatment were positively correlated with depression improvement. An integrated activity within this pathway was observed at both baseline and post-treatment. The present results support an integrated AKT/mTOR signaling pathway activity in a similar fashion to the described in previous human postmortem and rodents brain studies. Overall, the results reinforce a role for AKT1 and mTOR in the pathophysiology of BD and support the relevance of blood mRNA expression as a valid surrogate biological source to study brain intracellular signaling cascades changes and convergent molecular pathways in psychiatric disorders., (Published by Elsevier B.V.)

Background: Glycogen synthase kinase-3 β (GSK3β) is an intracellular enzyme directly implicated in several neural processes relevant to bipolar disorder (BD) pathophysiology. GSK3β is also an important target for lithium and antidepressants. When phosphorylated at serine-9, GSK3β becomes inactive. Few studies evaluated serine-9 phosphorylated GSK3β (phospho-GSK3β) levels in BD subjects in vivo and no study has assessed it specifically in bipolar depression. Also, the effect of lithium monotherapy on GSK3β has never been studied in humans., Methods: In 27 patients with bipolar depression, total GSK3β and phospho-GSK3β were assessed in platelets by enzyme immunometric assay. Subjects were evaluated before and after 6 weeks of lithium treatment at therapeutic levels. Healthy subjects (n = 22) were used as a control group., Results: No differences in phospho-GSK3β or total GSK3β were observed when comparing drug-free BD subjects in depression and healthy controls. Baseline HAM-D scores were not correlated with phospho-GSK3β and total GSK3β levels. From baseline to endpoint, lithium treatment inactivated GSK3β by significantly increasing phospho-GSK3β levels (p = 0.010). Clinical improvement (baseline HAM-D - endpoint HAM-D) negatively correlated with the increase in phospho-GSK3β (p = 0.03)., Conclusion: The present results show that lithium inactivates platelet GSK3β in BD during mood episodes. No direct association with pathophysiology of BD was observed. Further studies are needed to clarify the role of GSK3β as a key biomarker in BD and its association with treatment response as well as the relevance of GSK3β in other neuropsychiatric disorders and as a new therapeutic target per se., (Published by Elsevier Ltd.)

Background: Bipolar disorder (BD) has been associated with diverse abnormalities in neural plasticity and cellular resilience. Neurotrophin-3 (NT-3) and neurotrophin-4/5 (NT-4/5) support synaptic neuronal survival and differentiation. NT-3 and NT-4/5 levels were found to be altered in BD, potentially representing a physiological response against cellular stress. However, the use of psychopharmacological agents and heterogeneous mood states may constitute important biases in such studies. Thus, we aimed to assess NT-3 and NT-4/5 levels in medication-free BD type I or II individuals in a current depressive episode, before and after 6 weeks of lithium monotherapy and matched with healthy controls., Methods: Twenty-three patients with BD type I or II during a depressive episode and 28 healthy controls were studied. Patients were required to have a 21-item Hamilton Depression Rating Scale score ≥18 and had not undergone any psychopharmacological treatment for at least 6 weeks prior to study entry. Patients were treated with lithium for 6 weeks and plasma NT-3 and NT-4/5 levels were determined at baseline and endpoint using ELISA method., Results: Baseline plasma levels of both NT-3 and NT-4/5 were significantly increased in acutely depressed BD subjects in comparison to healthy controls (p=0.040 and 0.039, respectively). The NT-3 and NT-4/5 levels did not significantly change after lithium treatment. NT-3 and NT-4/5 levels were positively correlated to illness duration in BD (p=0.032 and 0.034, respectively)., Conclusion: Our findings suggest that NT-3 and NT-4/5 levels are increased in the depressive phase of BD, which seems directly associated with illness duration. The increased levels of NT-3 and NT-4/5 may underlie a biological response to cellular stress associated with the course of BD., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Major depressive disorder (MDD) is associated with a significant burden and costs to the society. As remission of depressive symptoms is achieved in only one-third of the MDD patients after the first antidepressant trial, unsuccessful treatments contribute largely to the observed suffering and social costs of MDD. The present article provides a summary of the therapeutic strategies that have been tested for treatment-resistant depression (TRD). A computerized search on MedLine/PubMed database from 1975 to September 2014 was performed, using the keywords "treatment-resistant depression", "major depressive disorder", "adjunctive", "refractory" and "augmentation". From the 581 articles retrieved, two authors selected 79 papers. A manual searching further considered relevant articles of the reference lists. The evidence found supports adding or switching to another antidepressant from a different class is an effective strategy in more severe MDD after failure to an initial antidepressant trial. Also, in subjects resistant to two or more classes of antidepressants, some augmentation strategies and antidepressant combinations should be considered, although the overall response and remission rates are relatively low, except for fast acting glutamatergic modulators. The wide range of available treatments for TRD reflects the complexity of MDD, which does not underlie diverse key features of the disorder. Larger and well-designed studies applying dimensional approaches to measure efficacy and effectiveness are warranted.

Rationale: Different lines of evidence suggest that mitochondrial dysfunction may be implicated in bipolar disorder (BD) pathophysiology. Mitochondrial electron transport chain (ETC) is a key target to evaluate mitochondrial function, but its activity has never been assessed in unmedicated BD or during mood episodes. Also, lithium has been shown to increase ETC gene expression/activity in preclinical models and in postmortem brains of BD subjects, but to date, no study has evaluated lithium's direct effects on ETC activity in vivo., Objectives: This study aims to evaluate leukocyte ETC complexes I-IV activities in acute depressive episode in BD (compared to controls) and the effect of lithium treatment on ETC activity., Methods: Subjects with short-term BD during a depressive episode (n=25) were treated for 6 weeks with lithium. Leukocytes were collected at baseline and endpoint and mitochondrial ETC complexes I-IV activities were evaluated and compared to age-matched healthy controls (n=24)., Results: Lithium significantly increased mitochondrial complex I activity from baseline to endpoint (p=0.02), with no changes in other complexes after 6 weeks. Also, plasma lithium levels were significantly correlated to mitochondrial complex I activity after treatment (p=0.003). Mitochondrial complexes I-IV activities did not differ during depressive episodes in BD compared to healthy controls., Conclusions: Our findings demonstrate for the first time an increase in mitochondrial ETC complex I activity in vivo after lithium treatment in BD, which was positively associated with plasma lithium levels. Further studies are warranted to clarify the potential role of this target in neuroprotection-related drug development.

Objective: TNF system (TNF and its soluble receptors sTNFR1 and 2) has been investigated as a potential molecular target in bipolar disorder. The aim of the study was to compare plasma levels of these receptors in unmedicated bipolar depressed patients compared with healthy controls, and to evaluate the effects of a 6-week lithium treatment on sTNFR1 and sTNFR2 levels., Methods: The study enrolled 29 patients with unmedicated bipolar disorder in a major depressive episode and 27 matched controls. Patients had blood collected at baseline and after 6 weeks of lithium treatment. The concentration of sTNFRs was measured by ELISA., Results: sTNFR1 and sTNFR2 levels were significantly increased in bipolar depression in comparison with healthy subjects. Lithium treatment did not significantly change sTNFR1 and sTNFR2 levels from baseline to endpoint. There was no correlation between improvement in depressive symptoms and the change in sTNFR1 or sTNFR1 levels., Conclusion: These results reinforce the involvement of an activated immune response system in the pathophysiology of bipolar disorder, with no impact of lithium treatment on the related biomarkers., (Copyright © 2014 John Wiley & Sons, Ltd.)

Background: The hippocampus has been highly implicated in the pathophysiology of bipolar disorder (BD). Nevertheless, no study has longitudinally evaluated hippocampal metabolite levels in bipolar depression under treatment with lithium., Methods: Nineteen medication-free BD patients (78.9% treatment-naïve and 73.7% with BD type II) presenting an acute depressive episode and 17 healthy controls were studied. Patients were treated for 6 weeks with lithium in an open-label trial. N-acetyl aspartate (NAA), creatine, choline, myo-Inositol, and glutamate levels were assessed in the left hippocampus before (week 0) and after (week 6) lithium treatment using 3T proton magnetic resonance spectroscopy (1H-MRS). The metabolite concentrations were estimated using internal water as reference and voxel segmentation for partial volume correction., Results: At baseline, acutely depressed BD patients and healthy controls exhibited similar hippocampal metabolites concentrations, with no changes after 6 weeks of lithium monotherapy. A significant correlation between antidepressant efficacy and increases in NAA concentration over time was observed. Also, there was a significant positive correlation between the changes in glutamate concentrations over follow-up and plasma lithium levels at endpoint. Mixed effects model analysis revealed a bimodal effect of lithium plasma levels in hippocampal glutamate concentrations: levels of 0.2 to 0.49 mmol/L (n=9) were associated with a decrease in glutamate concentrations, whereas the subgroup of BD subjects with "standard" lithium levels (≥ 0.50 mmol/L; n = 10) showed an overall increase in glutamate concentrations over time., Conclusions: These preliminary results suggest that lithium has a bimodal action in hippocampal glutamate concentration depending on the plasma levels., (© The Author 2015. Published by Oxford University Press on behalf of CINP.)

Introduction: Bipolar disorder (BPD) is a severe illness with few treatments available. Understanding BPD pathophysiology and identifying potential relevant targets could prove useful for developing new treatments. Remarkably, subtle impairments of mitochondrial function may play an important role in BPD pathophysiology., Areas Covered: This article focuses on human studies and reviews evidence of mitochondrial dysfunction in BPD as a promising target for the development of new, improved treatments. Mitochondria are crucial for energy production, generated mainly through the electron transport chain (ETC) and play an important role in regulating apoptosis and calcium (Ca²⁺) signaling as well as synaptic plasticity. Mitochondria move throughout the neurons to provide energy for intracellular signaling. Studies showed polymorphisms of mitochondria-related genes as risk factors for BPD. Postmortem studies in BPD also show decreased ETC activity/expression and increased nitrosative and oxidative stress (OxS) in patient brains. BPD has been also associated with increased OxS, Ca²⁺ dysregulation and increased proapoptotic signaling in peripheral blood. Neuroimaging studies consistently show decreased energy levels and pH in brains of BPD patients., Expert Opinion: Targeting mitochondrial function, and their role in energy metabolism, synaptic plasticity and cell survival, may be an important avenue for development of new mood-stabilizing agents.

Lithium has a narrow therapeutic index with a subtle balance between effectiveness and adverse effects. Current guidelines recommend the use of lithium as a treatment for acute bipolar depression; however, the therapeutic range for the treatment has not been fully defined. Recently, the adjunctive lower lithium dose in bipolar depression has revealed potential efficacy; however, no study has investigated it predominantly in monotherapy. In this open-label, proof-of-concept study, 31 individuals with bipolar disorder during a depressive episode were randomized and 29 were followed up for six weeks with flexible lithium dosing. All subjects had a 21-item Hamilton Rating Scale for Depression (HAM-D) score of ≥18 at baseline. Subjects were divided into two groups, with higher (Li ≥0.5 mEq/l) or lower (Li <0.5 mEq/l) blood lithium levels. Response and remission rates were evaluated using the HAM-D scores. Following 6 weeks of lithium treatment, the remission rate for all patients was 62.0%. The plasma lithium levels did not impact the clinical response. However, subjects with higher blood lithium levels had an increased prevalence of nausea, restlessness, headaches and cognitive complaints. The results indicate that the lithium dose for the treatment of bipolar depression in an individual should be based on the clinical efficacy and side-effects. In the context of personalized psychiatric treatments, it is necessary to evaluate the therapeutic action of lithium with individual regimens in order to develop more tolerable and effective treatment approaches.

Background: Altered nitric oxide (NO) signaling has been associated with the pathophysiology of Bipolar Disorder (BD), directly affecting neurotransmitter release and synaptic plasticity cascades. Lithium has shown to regulate NO levels in preclinical models. However, no study has addressed peripheral NO levels in unmedicated BD. Also, lithium's effects on NO levels have not been studied in humans., Methods: Plasma NO was evaluated in subjects with BD I and II during a depressive episode (n = 26). Subjects had a score of ≥18 in the 21-item Hamilton Depression Rating Scale and were followed-up during a 6-week trial with lithium. Plasma NO levels were also compared to matched healthy controls (n = 28). NO was determined by chemiluminescence method., Results: Lithium treatment significantly increased plasma NO levels after 6 weeks of treatment in comparison to baseline levels in bipolar depression (p = 0.016). Baseline NO levels during depressive episodes showed no difference when matching up to healthy controls (p = 0.66)., Conclusion: The present findings suggest that lithium upregulates NO signaling in unmedicated BD with short illness duration. Further studies with larger samples are needed to confirm the effects of lithium on NO pathway and its association with synaptic plasticity and therapeutics of BD., (Published by Elsevier Ltd.)