Showing papers by "University of Victoria published in 2018"

Spatial and temporal patterns of mass bleaching of corals in the Anthropocene.

Abstract: Tropical reef systems are transitioning to a new era in which the interval between recurrent bouts of coral bleaching is too short for a full recovery of mature assemblages. We analyzed bleaching records at 100 globally distributed reef locations from 1980 to 2016. The median return time between pairs of severe bleaching events has diminished steadily since 1980 and is now only 6 years. As global warming has progressed, tropical sea surface temperatures are warmer now during current La Nina conditions than they were during El Nino events three decades ago. Consequently, as we transition to the Anthropocene, coral bleaching is occurring more frequently in all El Nino–Southern Oscillation phases, increasing the likelihood of annual bleaching in the coming decades.

Learning to Find Good Correspondences

Abstract: We develop a deep architecture to learn to find good correspondences for wide-baseline stereo. Given a set of putative sparse matches and the camera intrinsics, we train our network in an end-to-end fashion to label the correspondences as inliers or outliers, while simultaneously using them to recover the relative pose, as encoded by the essential matrix. Our architecture is based on a multi-layer perceptron operating on pixel coordinates rather than directly on the image, and is thus simple and small. We introduce a novel normalization technique, called Context Normalization, which allows us to process each data point separately while embedding global information in it, and also makes the network invariant to the order of the correspondences. Our experiments on multiple challenging datasets demonstrate that our method is able to drastically improve the state of the art with little training data.

Plant functional trait change across a warming tundra biome

Abstract: The tundra is warming more rapidly than any other biome on Earth, and the potential ramifications are far-reaching because of global feedback effects between vegetation and climate. A better understanding of how environmental factors shape plant structure and function is crucial for predicting the consequences of environmental change for ecosystem functioning. Here we explore the biome-wide relationships between temperature, moisture and seven key plant functional traits both across space and over three decades of warming at 117 tundra locations. Spatial temperature-trait relationships were generally strong but soil moisture had a marked influence on the strength and direction of these relationships, highlighting the potentially important influence of changes in water availability on future trait shifts in tundra plant communities. Community height increased with warming across all sites over the past three decades, but other traits lagged far behind predicted rates of change. Our findings highlight the challenge of using space-for-time substitution to predict the functional consequences of future warming and suggest that functions that are tied closely to plant height will experience the most rapid change. They also reveal the strength with which environmental factors shape biotic communities at the coldest extremes of the planet and will help to improve projections of functional changes in tundra ecosystems with climate warming.

Gaps and Rings in an ALMA Survey of Disks in the Taurus Star-forming Region

Abstract: Rings are the most frequently revealed substructure in ALMA dust observations of protoplanetary disks, but their origin is still hotly debated. In this paper, we identify dust substructures in 12 disks and measure their properties to investigate how they form. This subsample of disks is selected from a high-resolution ($\sim0.12''$) ALMA 1.33 mm survey of 32 disks in the Taurus star-forming region, which was designed to cover a wide range of sub-mm brightness and to be unbiased to previously known substructures. While axisymmetric rings and gaps are common within our sample, spiral patterns and high contrast azimuthal asymmetries are not detected. Fits of disk models to the visibilities lead to estimates of the location and shape of gaps and rings, the flux in each disk component, and the size of the disk. The dust substructures occur across a wide range of stellar mass and disk brightness. Disks with multiple rings tend to be more massive and more extended. The correlation between gap locations and widths, the intensity contrast between rings and gaps, and the separations of rings and gaps could all be explained if most gaps are opened by low-mass planets (super-Earths and Neptunes) in the condition of low disk turbulence ($\alpha=10^{-4}$). The gap locations are not well correlated with the expected locations of CO and N$_2$ ice lines, so condensation fronts are unlikely to be a universal mechanism to create gaps and rings, though they may play a role in some cases.

Energy investment needs for fulfilling the Paris Agreement and achieving the sustainable development goals

Abstract: Low-carbon investments are necessary for driving the energy system transformation that is called for by both the Paris Agreement and Sustainable Development Goals. Improving understanding of the scale and nature of these investments under diverging technology and policy futures is therefore of great importance to decision makers. Here, using six global modelling frameworks, we show that the pronounced reallocation of the investment portfolio required to transform the energy system will not be initiated by the current suite of countries’ Nationally Determined Contributions. Charting a course toward ‘well below 2 °C’ instead sees low-carbon investments overtaking fossil investments globally by around 2025 or before and growing thereafter. Pursuing the 1.5 °C target demands a marked upscaling in low-carbon capital beyond that of a 2 °C-consistent future. Actions consistent with an energy transformation would increase the costs of achieving the goals of energy access and food security, but reduce the costs of achieving air-quality goals. The scale and nature of energy investments under diverging technology and policy futures is of great importance to decision makers. Here, a multi-model study projects investment needs under countries’ nationally determined contributions and in pathways consistent with achieving the 2 °C and 1.5 °C targets as well as certain SDGs.

Search for dark matter and other new phenomena in events with an energetic jet and large missing transverse momentum using the ATLAS detector

Abstract: Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses proton-proton collision data corresponding to an integrated luminosity of 36.1 fb−1 at a centre-of-mass energy of 13 TeV collected in 2015 and 2016 with the ATLAS detector at the Large Hadron Collider. Events are required to have at least one jet with a transverse momentum above 250 GeV and no leptons (e or μ). Several signal regions are considered with increasing requirements on the missing transverse momentum above 250 GeV. Good agreement is observed between the number of events in data and Standard Model predictions. The results are translated into exclusion limits in models with pair-produced weakly interacting dark-matter candidates, large extra spatial dimensions, and supersymmetric particles in several compressed scenarios.

Recent Asian origin of chytrid fungi causing global amphibian declines

Abstract: Globalized infectious diseases are causing species declines worldwide, but their source often remains elusive. We used whole-genome sequencing to solve the spatiotemporal origins of the most devastating panzootic to date, caused by the fungus Batrachochytrium dendrobatidis, a proximate driver of global amphibian declines. We traced the source of B. dendrobatidis to the Korean peninsula, where one lineage, BdASIA-1, exhibits the genetic hallmarks of an ancestral population that seeded the panzootic. We date the emergence of this pathogen to the early 20th century, coinciding with the global expansion of commercial trade in amphibians, and we show that intercontinental transmission is ongoing. Our findings point to East Asia as a geographic hotspot for B. dendrobatidis biodiversity and the original source of these lineages that now parasitize amphibians worldwide.

Production and integration of the ATLAS Insertable B-Layer

Abstract: During the shutdown of the CERN Large Hadron Collider in 2013-2014, an additional pixel layer was installed between the existing Pixel detector of the ATLAS experiment and a new, smaller radius beam pipe. The motivation for this new pixel layer, the Insertable B-Layer (IBL), was to maintain or improve the robustness and performance of the ATLAS tracking system, given the higher instantaneous and integrated luminosities realised following the shutdown. Because of the extreme radiation and collision rate environment, several new radiation-tolerant sensor and electronic technologies were utilised for this layer. This paper reports on the IBL construction and integration prior to its operation in the ATLAS detector.

The Dark Side of Transformation: Latent Risks in Contemporary Sustainability Discourse

Abstract: The notion of transformation is gaining traction in contemporary sustainability debates. New ways of theorising and supporting transformations are emerging and, so the argument goes, opening exciting spaces to (re)imagine and (re)structure radically different futures. Yet, questions remain about how the term is being translated from an academic concept into an assemblage of normative policies and practices, and how this process might shape social, political, and environmental change. Motivated by these questions, we identify five latent risks associated with discourse that frames transformation as apolitical and/or inevitable. We refer to these risks as the dark side of transformation. While we cannot predict the future of radical transformations towards sustainability, we suggest that scientists, policymakers, and practitioners need to consider such change in more inherently plural and political ways.

Trajectory Tracking Control of an Autonomous Underwater Vehicle Using Lyapunov-Based Model Predictive Control

Abstract: This paper studies the trajectory tracking control problem of an autonomous underwater vehicle (AUV). We develop a novel Lyapunov-based model predictive control (LMPC) framework for the AUV to utilize computational resource (online optimization) to improve the trajectory tracking performance. Within the LMPC framework, the practical constraints, such as actuator saturation, can be explicitly considered. Also, the thrust allocation subproblem can be addressed simultaneously with the LMPC controller design. Taking advantage of a nonlinear backstepping tracking control law, we construct the contraction constraint in the formulated LMPC problem so that the closed-loop stability is theoretically guaranteed. Sufficient conditions that ensure the recursive feasibility, and hence the closed-loop stability, are provided analytically. A guaranteed region of attraction is explicitly characterized. In the meantime, the robustness of the tracking control can be improved by the receding horizon implementation that is adopted in the LMPC control algorithm. Simulation results on the Saab SeaEye Falcon model AUV demonstrate the significantly enhance trajectory tracking control performance via the proposed LMPC method.

Targeting Oxidative Stress and Mitochondrial Dysfunction in the Treatment of Impaired Wound Healing: A Systematic Review.

Abstract: Wound healing is a well-tuned biological process, which is achieved via consecutive and overlapping phases including hemostasis, inflammatory-related events, cell proliferation and tissue remodeling Several factors can impair wound healing such as oxygenation defects, aging, and stress as well as deleterious health conditions such as infection, diabetes, alcohol overuse, smoking and impaired nutritional status Growing evidence suggests that reactive oxygen species (ROS) are crucial regulators of several phases of healing processes ROS are centrally involved in all wound healing processes as low concentrations of ROS generation are required for the fight against invading microorganisms and cell survival signaling Excessive production of ROS or impaired ROS detoxification causes oxidative damage, which is the main cause of non-healing chronic wounds In this context, experimental and clinical studies have revealed that antioxidant and anti-inflammatory strategies have proven beneficial in the non-healing state Among available antioxidant strategies, treatments using mitochondrial-targeted antioxidants are of particular interest Specifically, mitochondrial-targeted peptides such as elamipretide have the potential to mitigate mitochondrial dysfunction and aberrant inflammatory response through activation of nucleotide-binding oligomerization domain (NOD)-like family receptors, such as the pyrin domain containing 3 (NLRP3) inflammasome, nuclear factor-kappa B (NF-κB) signaling pathway inhibition, and nuclear factor (erythroid-derived 2)-like 2 (Nrf2)

The unity and diversity of executive functions: A systematic review and re-analysis of latent variable studies.

Abstract: Confirmatory factor analysis (CFA) has been frequently applied to executive function measurement since first used to identify a three-factor model of inhibition, updating, and shifting; however, subsequent CFAs have supported inconsistent models across the life span, ranging from unidimensional to nested-factor models (i.e., bifactor without inhibition). This systematic review summarized CFAs on performance-based tests of executive functions and reanalyzed summary data to identify best-fitting models. Eligible CFAs involved 46 samples (N = 9,756). The most frequently accepted models varied by age (i.e., preschool = one/two-factor; school-age = three-factor; adolescent/adult = three/nested-factor; older adult = two/three-factor), and most often included updating/working memory, inhibition, and shifting factors. A bootstrap reanalysis simulated 5,000 samples from 21 correlation matrices (11 child/adolescent; 10 adult) from studies including the three most common factors, fitting seven competing models. Model results were summarized as the mean percent accepted (i.e., average rate at which models converged and met fit thresholds: CFI ≥ .90/RMSEA ≤ .08) and mean percent selected (i.e., average rate at which a model showed superior fit to other models: ΔCFI ≥ .005/.010/ΔRMSEA ≤ -.010/-.015). No model consistently converged and met fit criteria in all samples. Among adult samples, the nested-factor was accepted (41-42%) and selected (8-30%) most often. Among child/adolescent samples, the unidimensional model was accepted (32-36%) and selected (21-53%) most often, with some support for two-factor models without a differentiated shifting factor. Results show some evidence for greater unidimensionality of executive function among child/adolescent samples and both unity and diversity among adult samples. However, low rates of model acceptance/selection suggest possible bias toward the publication of well-fitting but potentially nonreplicable models with underpowered samples. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

LF-Net: Learning Local Features from Images.

Abstract: We present a novel deep architecture and a training strategy to learn a local feature pipeline from scratch, using collections of images without the need for human supervision. To do so we exploit depth and relative camera pose cues to create a virtual target that the network should achieve on one image, provided the outputs of the network for the other image. While this process is inherently non-differentiable, we show that we can optimize the network in a two-branch setup by confining it to one branch, while preserving differentiability in the other. We train our method on both indoor and outdoor datasets, with depth data from 3D sensors for the former, and depth estimates from an off-the-shelf Structure-from-Motion solution for the latter. Our models outperform the state of the art on sparse feature matching on both datasets, while running at 60+ fps for QVGA images.

Oncolytic viruses as engineering platforms for combination immunotherapy.

Abstract: To effectively build on the recent successes of immune checkpoint blockade, adoptive T cell therapy and cancer vaccines, it is critical to rationally design combination strategies that will increase and extend efficacy to a larger proportion of patients. For example, the combination of anti-cytotoxic T lymphocyte-associated antigen 4 (CTLA4) and anti-programmed cell death protein 1 (PD1) immune checkpoint inhibitors essentially doubles the response rate in certain patients with metastatic melanoma. However, given the heterogeneity of cancer, it seems likely that even more complex combinations of immunomodulatory agents may be required to obtain consistent, durable therapeutic responses against a broad spectrum of cancers. This carries serious implications in terms of toxicities for patients, feasibility for care providers and costs for health-care systems. A compelling solution is offered by oncolytic viruses (OVs), which can be engineered to selectively replicate within and destroy tumour tissue while simultaneously augmenting antitumour immunity. In this Opinion article, we argue that the future of immunotherapy will include OVs that function as multiplexed immune-modulating platforms expressing factors such as immune checkpoint inhibitors, tumour antigens, cytokines and T cell engagers. We illustrate this concept by following the trials and tribulations of tumour-reactive T cells from their initial priming through to the execution of cytotoxic effector function in the tumour bed. We highlight the myriad opportunities for OVs to help overcome critical barriers in the T cell journey, leading to new synergistic mechanisms in the battle against cancer.

Contrasting the relative importance of species sorting and dispersal limitation in shaping marine bacterial versus protist communities.

Abstract: A central challenge in microbial ecology is to understand the underlying mechanisms driving community assembly, particularly in the continuum of species sorting and dispersal limitation. However, little is known about the relative importance of species sorting and dispersal limitation in shaping marine microbial communities; especially, how they are related to organism types/traits and water depth. Here, we used variation partitioning and null model analysis to compare mechanisms driving bacterial and protist metacommunity dynamics at the basin scale in the East China Sea, based on MiSeq paired-end sequencing of 16S ribosomal DNA (rDNA) and 18S rDNA, respectively, in surface, deep chlorophyll maximum and bottom layers. Our analyses indicated that protist communities were governed more strongly by species sorting relative to dispersal limitation than were bacterial communities; this pattern was consistent across the three-depth layers, albeit to different degrees. Furthermore, we detected that bacteria exhibited wider habitat niche breadths than protists, whereas, passive dispersal abilities were not appreciably different between them. Our findings support the 'size-plasticity' hypothesis: smaller organisms (bacteria) are less environment filtered than larger organisms (protists), as smaller organisms are more likely to be plastic in metabolic abilities and have greater environmental tolerance.

Connecting the Sustainable Development Goals by their energy inter-linkages

Abstract: The United Nations' Sustainable Development Goals (SDGs) provide guide-posts to society as it attempts to respond to an array of pressing challenges One of these challenges is energy; thus, the SDGs have become paramount for energy policy-making Yet, while governments throughout the world have already declared the SDGs to be 'integrated and indivisible', there are still knowledge gaps surrounding how the interactions between the energy SDG targets and those of the non-energy-focused SDGs might play out in different contexts In this review, we report on a large-scale assessment of the relevant energy literature, which we conducted to better our understanding of key energy-related interactions between SDGs, as well as their context-dependencies (relating to time, geography, governance, technology, and directionality) By (i) evaluating the nature and strength of the interactions identified, (ii) indicating the robustness of the evidence base, the agreement of that evidence, and our confidence in it, and (iii) highlighting critical areas where better understanding is needed or context dependencies should be considered, our review points to potential ways forward for both the policy making and scientific communities First, we find that positive interactions between the SDGs outweigh the negative ones, both in number and magnitude Second, of relevance for the scientific community, in order to fill knowledge gaps in critical areas, there is an urgent need for interdisciplinary research geared toward developing new data, scientific tools, and fresh perspectives Third, of relevance for policy-making, wider efforts to promote policy coherence and integrated assessments are required to address potential policy spillovers across sectors, sustainability domains, and geographic and temporal boundaries The task of conducting comprehensive science-to-policy assessments covering all SDGs, such as for the UN's Global Sustainable Development Report, remains manageable pending the availability of systematic reviews focusing on a limited number of SDG dimensions in each case

Measurements of Higgs boson properties in the diphoton decay channel with 36 fb−1 of pp collision data at s√=13 TeV with the ATLAS detector

Abstract: Properties of the Higgs boson are measured in the two-photon final state using 36.1 fb-1 of proton? proton collision data recorded at ffiffi √s = 13 TeV by the ATLAS experiment at the Large Hadron Collider. Cross-section measurements for the production of a Higgs boson through gluon-gluon fusion, vectorboson fusion, and in association with a vector boson or a top-quark pair are reported. The signal strength, defined as the ratio of the observed to the expected signal yield, is measured for each of these production processes as well as inclusively. The global signal strength measurement of 0.99 ± 0.14 improves on the precision of the ATLAS measurement at √s = 7 and 8 TeV by a factor of two. Measurements of gluon-gluon fusion and vector-boson fusion productions yield signal strengths compatible with the Standard Model prediction. Measurements of simplified template cross sections, designed to quantify the different Higgs boson production processes in specific regions of phase space, are reported. The cross section for the production of the Higgs boson decaying to two isolated photons in a fiducial region closely matching the experimental selection of the photons is measured to be 55 ± 10 fb, which is in good agreement with the Standard Model prediction of 64 ± 2 fb. Furthermore, cross sections in fiducial regions enriched in Higgs boson production in vector-boson fusion or in association with large missing transverse momentum, leptons or top-quark pairs are reported. Differential and double-differential measurements are performed for several variables related to the diphoton kinematics as well as the kinematics and multiplicity of the jets produced in association with a Higgs boson. These differential cross sections are sensitive to higher order QCD corrections and properties of the Higgs boson, such as its spin and CP quantum numbers. No significant deviations from a wide array of Standard Model predictions are observed. Finally, the strength and tensor structure of the Higgs boson interactions are investigated using an effective Lagrangian, which introduces additional CP-even and CP-odd interactions. No significant new physics contributions are observed.

Prognostic significance of tumor-infiltrating B cells and plasma cells in human cancer

Abstract: There is abundant evidence that tumor-infiltrating CD8+ T cells contribute positively to antitumor immunity; however, the role of tumor-infiltrating B cells (TIL-B) and plasma cells (PC) remains controversial, leading to differing opinions about whether immunotherapies should be designed to enhance or inhibit these cells. Through a comprehensive PubMed search, we reviewed publications with cohorts of 50 or more cases in which the prognostic value of TIL-B/PC was assessed by immunohistochemistry and/or gene-expression analysis. Sixty-nine studies representing 19 cancers met our review criteria. The large majority of studies assessed TIL-B by immunohistochemical detection of CD20. Of these, 50.0% reported a positive prognostic effect for CD20+ TIL-B, whereas the remainder found a neutral (40.7%) or negative (9.3%) effect. These differences in prognostic effect were not attributable to cancer type, other clinicopathologic factors, or differing technical approaches. The prognostic significance of TIL-B/PC was generally concordant with that of CD3+ and/or CD8+ T cells, and the prognostic effect of T cells was generally stronger when TIL-B and/or PC were also present. Additionally, 21 studies inferred the presence of TIL-B/PC from gene-expression data, and a large majority reported a positive prognostic effect. Although more studies are required involving additional cancer types and independent patient cohorts, the weight of evidence supports a positive role for TIL-B and PC in antitumor immunity, suggesting that enhancement of these responses should be considered in the design of cancer immunotherapies.

Detecting opinion spams and fake news using text classification

Abstract: *Correspondence Traore, Issa, ECE Department, University of Victoria, Victoria, BC, Canada. Email: itraore@ece.uvic.ca In recent years, deceptive content such as fake news and fake reviews, also known as opinion spams, have increasingly become a dangerous prospect for online users. Fake reviews have affected consumers and stores alike. Furthermore, the problem of fake news has gained attention in 2016, especially in the aftermath of the last U.S. presidential elections. Fake reviews and fake news are a closely related phenomenon as both consist of writing and spreading false information or beliefs. The opinion spam problem was formulated for the first time a few years ago, but it has quickly become a growing research area due to the abundance of user-generated content. It is now easy for anyone to either write fake reviews or write fake news on the web. The biggest challenge is the lack of an efficient way to tell the difference between a real review and a fake one; even humans are often unable to tell the difference. In this paper, we introduce a new n-gram model to detect automatically fake contents with a particular focus on fake reviews and fake news. We study and compare 2 different features extraction techniques and 6 machine learning classification techniques. Experimental evaluation using existing public datasets and a newly introduced fake news dataset indicate very encouraging and improved performances compared to the state-of-the-art methods.

Debris Disks: Structure, Composition, and Variability

Abstract: Debris disks are tenuous, dust-dominated disks commonly observed around stars over a wide range of ages. Those around main sequence stars are analogous to the Solar System's Kuiper Belt and zodiaca...

LF-Net: Learning Local Features from Images

Abstract: We present a novel deep architecture and a training strategy to learn a local feature pipeline from scratch, using collections of images without the need for human supervision. To do so we exploit depth and relative camera pose cues to create a virtual target that the network should achieve on one image, provided the outputs of the network for the other image. While this process is inherently non-differentiable, we show that we can optimize the network in a two-branch setup by confining it to one branch, while preserving differentiability in the other. We train our method on both indoor and outdoor datasets, with depth data from 3D sensors for the former, and depth estimates from an off-the-shelf Structure-from-Motion solution for the latter. Our models outperform the state of the art on sparse feature matching on both datasets, while running at 60+ fps for QVGA images.

Taking account of context in population health intervention research: guidance for producers, users and funders of research

Abstract: Additional co-authors: Blake Poland, Valery Ridde, Jeannie Shoveller, Sarah Viehbeck,and Daniel Wight

Performance of missing transverse momentum reconstruction with the ATLAS detector using proton-proton collisions at s√ = 13 TeV

Abstract: The performance of the missing transverse momentum ( ETmiss ) reconstruction with the ATLAS detector is evaluated using data collected in proton-proton collisions at the LHC at a centre-of-mass energy of 13 TeV in 2015. To reconstruct ETmiss , fully calibrated electrons, muons, photons, hadronically decaying τ-leptons , and jets reconstructed from calorimeter energy deposits and charged-particle tracks are used. These are combined with the soft hadronic activity measured by reconstructed charged-particle tracks not associated with the hard objects. Possible double counting of contributions from reconstructed charged-particle tracks from the inner detector, energy deposits in the calorimeter, and reconstructed muons from the muon spectrometer is avoided by applying a signal ambiguity resolution procedure which rejects already used signals when combining the various ETmiss contributions. The individual terms as well as the overall reconstructed ETmiss are evaluated with various performance metrics for scale (linearity), resolution, and sensitivity to the data-taking conditions. The method developed to determine the systematic uncertainties of the ETmiss scale and resolution is discussed. Results are shown based on the full 2015 data sample corresponding to an integrated luminosity of 3.2fb-1 .

Search for Higgs boson pair production in the γ γ bb¯ final state with 13 TeV pp collision data collected by the ATLAS experiment

Abstract: A search is performed for resonant and non-resonant Higgs boson pair production in the $ \upgamma \upgamma b\overline{b} $ final state. The data set used corresponds to an integrated luminosity of 36.1 fb$^{−1}$ of proton-proton collisions at a centre-of-mass energy of 13 TeV recorded by the ATLAS detector at the CERN Large Hadron Collider. No significant excess relative to the Standard Model expectation is observed. The observed limit on the non-resonant Higgs boson pair cross-section is 0.73 pb at 95% confidence level. This observed limit is equivalent to 22 times the predicted Standard Model cross-section. The Higgs boson self-coupling (κ$_{λ}$ = λ$_{HHH}$/λ$_{HHH}^{SM}$ ) is constrained at 95% confidence level to −8.2 < κ$_{λ}$ < 13.2. For resonant Higgs boson pair production through $ X\to HH\to \upgamma \upgamma b\overline{b} $ , the limit is presented, using the narrow-width approximation, as a function of m$_{X}$ in the range 260 GeV < m$_{X}$ < 1000 GeV. The observed limits range from 1.1 pb to 0.12 pb over this mass range.

Mitochondria and Mood: Mitochondrial Dysfunction as a Key Player in the Manifestation of Depression.

Abstract: Human and animal studies suggest an intriguing link between mitochondrial diseases and depression. Although depression has historically been linked to alterations in monoaminergic pharmacology and adult hippocampal neurogenesis, new data increasingly implicate broader forms of dampened plasticity, including plasticity within the cell. Mitochondria are the cellular powerhouse of eukaryotic cells, and they also regulate brain function through oxidative stress and apoptosis. In this paper, we make the case that mitochondrial dysfunction could play an important role in the pathophysiology of depression. Alterations in mitochondrial functions such as oxidative phosphorylation (OXPHOS) and membrane polarity, which increase oxidative stress and apoptosis, may precede the development of depressive symptoms. However, the data in relation to antidepressant drug effects are contradictory: some studies reveal they have no effect on mitochondrial function or even potentiate dysfunction, whereas other studies show more beneficial effects. Overall, the data suggest an intriguing link between mitochondrial function and depression that warrants further investigation. Mitochondria could be targeted in the development of novel antidepressant drugs, and specific forms of mitochondrial dysfunction could be identified as biomarkers to personalize treatment and aid in early diagnosis by differentiating between disorders with overlapping symptoms.