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Pharmacogenomic technology is a developing field with enthusiastic interest and broad application potential. Three large, controlled studies have been published exploring the benefit of pharmacogenomically guided antidepressant treatment selection. Though all three studies did not show significant benefit of using this technology, these studies laid the foundation for further research that should address the limitations of this previous research and currently available commercial platforms. Future research needs to include large scale pharmacogenomic trials with GWAS analytics across diverse groups with attention to cost-effectiveness models, particularly for cases of treatment resistance and polypharmacy. The application of results from these large scale pharmacogenomic trials must also include exploring optimal EHR user interface design.

Tracking visual objects while maintaining stable gaze is complicated by the different computational requirements for figure-ground discrimination, and the distinct behaviors that these computations coordinate. Drosophila melanogaster uses smooth optomotor head and body movements to stabilize gaze, and impulsive saccades to pursue elongated vertical bars. Directionally selective motion detectors T4 and T5 cells provide inputs to large-field neurons in the lobula plate, which control optomotor gaze stabilization behavior. Here, we hypothesized that an anatomically parallel pathway represented by T3 cells, which provide inputs to the lobula, drives bar tracking body saccades. We combined physiological and behavioral experiments to show that T3 neurons respond omnidirectionally to the same visual stimuli that elicit bar tracking saccades, silencing T3 reduced the frequency of tracking saccades, and optogenetic manipulation of T3 acted on the saccade rate in a push–pull manner. Manipulating T3 did not affect smooth optomotor responses to large-field motion. Our results show that parallel neural pathways coordinate smooth gaze stabilization and saccadic bar tracking behavior during flight.

The hallmark of bipolar disorder is hypomania or mania, and the predominant phase of illness is depression. Affecting approximately 40 million individuals worldwide, bipolar disorder is associated with a substantial psychosocial, medical, and financial burden and increased mortality from suicide and other causes. Diagnosis can be challenging due to symptom overlap with attention-deficit hyperactivity disorder, major depressive disorder, psychotic spectrum disorders, and personality disorders, which often leads to a delay in diagnosis. Recent advancements in understanding disease risk and pathophysiology have identified multigene risk and possible infectious and mitochondrial causes. Treatment approaches include pharmacotherapy, psychotherapy, and lifestyle modifications, which should always be patient-centred and aligned with individual goals and priorities. Future directions for bipolar disorder care include increasing the availability of psychosocial interventions aimed at self-management, addressing treatment-resistant bipolar depression, deepening the understanding of pathophysiology, and exploring novel interventions, such as ketamine, esketamine, other rapid-acting antidepressants, and various neuromodulation approaches.

During their trajectories in still air, fruit flies (Drosophila melanogaster) explore their landscape using a series of straight flight paths punctuated by rapid 90 degrees body-saccades [1]. Some saccades are triggered by visual expansion associated with collision avoidance. Yet many saccades are not triggered by visual cues, but rather appear spontaneously. Our analysis reveals that the control of these visually independent saccades and the flight intervals between them constitute an optimal scale-free active searching strategy. Two characteristics of mathematical optimality that are apparent during free-flight in Drosophila are inter-saccade interval lengths distributed according to an inverse square law, which does not vary across landscape scale, and 90 degrees saccade angles, which increase the likelihood that territory will be revisited and thereby reduce the likelihood that near-by targets will be missed. We also show that searching is intermittent, such that active searching phases randomly alternate with relocation phases. Behaviorally, this intermittency is reflected in frequently occurring short, slow speed inter-saccade intervals randomly alternating with rarer, longer, faster inter-saccade intervals. Searching patterns that scale similarly across orders of magnitude of length (i.e., scale-free) have been revealed in animals as diverse as microzooplankton, bumblebees, albatrosses, and spider monkeys, but these do not appear to be optimised with respect to turning angle, whereas Drosophila free-flight search does. Also, intermittent searching patterns, such as those reported here for Drosophila, have been observed in foragers such as planktivorous fish and ground foraging birds. Our results with freely flying Drosophila may constitute the first reported example of searching behaviour that is both scale-free and intermittent.

Many insects use patterns of polarized light in the sky to orient and navigate. Here, we functionally characterize neural circuitry in the fruit fly, Drosophila melanogaster , that conveys polarized light signals from the eye to the central complex, a brain region essential for the fly’s sense of direction. Neurons tuned to the angle of polarization of ultraviolet light are found throughout the anterior visual pathway, connecting the optic lobes with the central complex via the anterior optic tubercle and bulb, in a homologous organization to the ‘sky compass’ pathways described in other insects. We detail how a consistent, map-like organization of neural tunings in the peripheral visual system is transformed into a reduced representation suited to flexible processing in the central brain. This study identifies computational motifs of the transformation, enabling mechanistic comparisons of multisensory integration and central processing for navigation in the brains of insects.

Electronic health records (EHR) are rich heterogeneous collections of patient health information, whose broad adoption provides clinicians and researchers unprecedented opportunities for health informatics, disease-risk prediction, actionable clinical recommendations, and precision medicine. However, EHRs present several modeling challenges, including highly sparse data matrices, noisy irregular clinical notes, arbitrary biases in billing code assignment, diagnosis-driven lab tests, and heterogeneous data types. To address these challenges, we present MixEHR, a multi-view Bayesian topic model. We demonstrate MixEHR on MIMIC-III, Mayo Clinic Bipolar Disorder, and Quebec Congenital Heart Disease EHR datasets. Qualitatively, MixEHR disease topics reveal meaningful combinations of clinical features across heterogeneous data types. Quantitatively, we observe superior prediction accuracy of diagnostic codes and lab test imputations compared to the state-of-art methods. We leverage the inferred patient topic mixtures to classify target diseases and predict mortality of patients in critical conditions. In all comparison, MixEHR confers competitive performance and reveals meaningful disease-related topics. Electronic Health Records (EHR) are subject to noise, biases and missing data. Here, the authors present MixEHR, a multi-view Bayesian framework related to collaborative filtering and latent topic models for EHR data integration and modeling.

Major Depressive Disorder (MDD) is characterized by high stress sensitivity and unsatisfactory response rates to standard treatments. Stress and depression share a bidirectional relationship. We, therefore, conducted a pilot randomized control trial (RCT) to understand if adjunctive stress management and resiliency training tailored for depression(SMART-D), can improve treatment outcomes in patients with MDD, receiving treatment as usual(TAU) with standard treatments (medications and/or psychotherapy), in real-world clinical settings, compared to a group receiving TAU. Participants with MDD, in a current depressive episode, were randomized to adjunctive SMART-D (delivered by video telehealth over 8 weeks), compared to TAU alone. Random assignment, blinding of raters and statistician were utilized. The primary outcome measure was baseline to end point change in depression [Hamilton Rating Scale for Depression (HAM-D] over a 6-month follow-up period using a mixed model regression analysis. 27 participants (mean age 47.9 ± 14 years, female 67%) enrolled in the study (TAU = 14, SMART-D + TAU = 13). Baseline mood ratings were in mild-moderate symptom severity (HAM-D)- SMART-D + TAU = 12.2 ± 6.6, TAU = 13.9 ± 5.7). Linear mixed model analysis showed significant Group*Time interaction for measures of depression (HAM-D) (B = 6.1 (CI = 1.5-10.8, P = .01) and perceived stress (PSS) (B = 5.5(0.5-10.6), p = .03) between the 2 groups at 3 months post follow-up ((HAMD)-SMART-D + TAU = 8.7 ± 4.3 Vs. TAU = 16.1 ± 6.3), but not at 6-months (SMART-D + TAU = 8.1 ± 5.4 Vs. TAU = 12.3 ± 5.5). A RCT of 27 adults with MDD provide initial support that an adjunctive resiliency intervention (SMART-D) for patients with MDD may positively impact symptoms of depression and perceived stress, earlier than standard care. A small sample size limits ability to draw firm conclusions. Further investigation is warranted, using larger samples. Clinical Trials Registration I.D.# NCT04388748.

After a series of serendipitous discoveries of pharmacological treatments for mania and depression several decades ago, relatively little progress has been made for novel hypothesis-driven drug development in mood disorders. Multifactorial etiologies of, and lack of a full understanding of, the core neurobiology of these conditions clearly have contributed to these development challenges. There are, however, relatively novel targets that have raised opportunities for progress in the field, such as glutamate and cholinergic receptor modulators, circadian regulators, and enzyme inhibitors, for alternative treatment. This review will discuss these promising new treatments in mood disorders, the underlying mechanisms of action, and critical issues of their clinical application. For these new treatments to be successful in clinical practice, it is also important to design innovative clinical trials that identify the specific actions of new drugs, and, ideally, to develop biomarkers for monitoring individualized treatment response. It is predicted that future drug development will identify new agents targeting the molecular mechanisms involved in the pathophysiology of mood disorders.

There is an urgent need for more rapidly effective pharmacotherapies for major depressive disorder and bipolar disorder (BP) that are efficacious and tolerable for depressed patients who respond poorly to conventional treatments. Multiple controlled trials have now demonstrated a rapid, nonsustained antidepressive response to a single intravenous infusion of ketamine. Early controlled studies of intranasal or serial infusion therapy appear promising. The effective dose for depression is lower than the typical anesthetic doses, and side‐effects are generally mild and transient. The data investigating the adjunctive use of concurrent ketamine in the course of electroconvulsive therapy (ECT) for depression do not suggest efficacy or tolerability. The therapeutic potential of ketamine has stimulated considerable excitement among clinicians, patients, and industry, and has led to the increasing use of ketamine as an off‐label substitute for ECT and other antidepressive treatments. This clinical review of ketamine will assess the evidence‐based use of ketamine and initial clinical implications of further development of a potentially novel treatment for rapid reduction of symptoms in depressed patients.

Sensory systems rely on neuromodulators, such as serotonin, to provide flexibility for information processing as stimuli vary, such as light intensity throughout the day. Serotonergic neurons broadly innervate the optic ganglia of Drosophila melanogaster, a widely used model for studying vision. It remains unclear whether serotonin modulates the physiology of interneurons in the optic ganglia. To address this question, we first mapped the expression patterns of serotonin receptors in the visual system, focusing on a subset of cells with processes in the first optic ganglion, the lamina. Serotonin receptor expression was found in several types of columnar cells in the lamina including 5-HT2B in lamina monopolar cell L2, required for spatiotemporal luminance contrast, and both 5-HT1A and 5-HT1B in T1 cells, whose function is unknown. Subcellular mapping with GFP-tagged 5-HT2B and 5-HT1A constructs indicated that these receptors localize to layer M2 of the medulla, proximal to serotonergic boutons, suggesting that the medulla neuropil is the primary site of serotonergic regulation for these neurons. Exogenous serotonin increased basal intracellular calcium in L2 terminals in layer M2 and modestly decreased the duration of visually induced calcium transients in L2 neurons following repeated dark flashes, but otherwise did not alter the calcium transients. Flies without functional 5-HT2B failed to show an increase in basal calcium in response to serotonin. 5-HT2B mutants also failed to show a change in amplitude in their response to repeated light flashes but other calcium transient parameters were relatively unaffected. While we did not detect serotonin receptor expression in L1 neurons, they, like L2, underwent serotonin-induced changes in basal calcium, presumably via interactions with other cells. These data demonstrate that serotonin modulates the physiology of interneurons involved in early visual processing in Drosophila.