Early postpartum resting‐state functional connectivity for mothers receiving buprenorphine treatment for opioid use disorder: A pilot study

Between 1999 and 2014, the prevalence of opioid use disorder (OUD) among pregnant women quadrupled in the USA. The standard treatment for peripartum women with OUD is buprenorphine. However, the maternal behavior neurocircuit that regulates maternal behavior and mother‐infant bonding has not been previously studied for human mothers receiving buprenorphine treatment for OUD (BT). Rodent research shows opioid effects on reciprocal inhibition between maternal care and defence maternal brain subsystems: the hypothalamus and periaqueductal gray, respectively. We conducted a longitudinal functional magnetic resonance imaging (fMRI) pilot study in humans to specifically examine resting‐state functional connectivity (rs‐FC) between the periaqueductal gray and hypothalamus, as well as to explore associations with maternal bonding for BT. We studied 32 mothers who completed fMRI scans at 1 month (T1) and 4 months postpartum (T2), including seven mothers receiving buprenorphine for OUD and 25 non‐OUD mothers as a comparison group (CG). The participants underwent a 6‐minute resting‐state fMRI scan at each time point. We measured potential bonding impairments using the Postpartum Bonding Questionnaire to explore how rs‐FC with periaqueductal gray is associated with bonding impairments. Compared to CG, BT mothers differed in periaqueductal gray‐dependent rs‐FC with the hypothalamus, amygdala, insular cortex and other brain regions at T1, with many of these differences disappearing at T2, suggesting potential therapeutic effects of continuing buprenorphine treatment. In contrast, the “rejection and pathological anger” subscale of the Postpartum Bonding Questionnaire at T1 and T2 was associated with the T1‐to‐T2 increases in periaqueductal gray‐dependent rs‐FC with the hypothalamus and amygdala. Preliminary evidence links maternal bonding problems for mothers with OUD early in the postpartum to connectivity between specific care and defence maternal brain circuits, which may be mitigated by buprenorphine treatment. This exploratory study supports a potential mechanism for investigating both the therapeutic benefits and risks of opioids for maternal care and bonding with infants.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151866/1/jne12770.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151866/2/jne12770_am.pd

Interpreting the results of patient reported outcome measures in clinical trials: The clinician's perspective

This article deals with the problem of interpreting health-related quality of life (HRQL) outcomes in clinical trials. First, we will briefly describe how dichotomization and item response theory can facilitate interpretation. Based on examples from the medical literature for the interpretation of HRQL scores we will show that dichotomies may help clinicians understand information provided by HRQL instruments in RCTs. They can choose thresholds to calculate proportions of patients benefiting based on absolute scores or change scores. For example, clinicians interpreting clinical trial results could consider the difference in the proportion of patients who achieve a mean score of 50 before and after an intervention on a scale from 1 to 100. For the change score approach, they could consider the proportion of patients who have changed by a score of 5 or more. Finally, they can calculate the proportion of patients benefiting and transform these numbers into a number needed to treat or natural frequencies. Second, we will describe in more detail an approach to the interpretation of HRQL scores based on the minimal important difference (MID) and proportions. The MID is the smallest difference in score in the outcome of interest that informed patients or informed proxies perceive as important, either beneficial or harmful, and that would lead the patient or clinician to consider a change in the management. Any change in management will depend on the downsides, including cost and inconvenience, associated with the intervention. Investigators can help with the interpretation of HRQL scores by determining the MID of an HRQL instrument and provide mean differences in relation to the MID. For instance, for an MID of 0.5 on a seven point scale investigators could provide the mean change on the instrument as well as the proportion of patients with scores greater than the MID. Thus, there are several steps investigators can take to facilitate this process to help bringing HRQL information closer to the bedside

Surgical Video Motion Magnification with Suppression of Instrument Artefacts

Video motion magnification could directly highlight subsurface blood vessels in endoscopic video in order to prevent inadvertent damage and bleeding. Applying motion filters to the full surgical image is however sensitive to residual motion from the surgical instruments and can impede practical application due to aberration motion artefacts. By storing the temporal filter response from local spatial frequency information for a single cardiovascular cycle prior to tool introduction to the scene, a filter can be used to determine if motion magnification should be active for a spatial region of the surgical image. In this paper, we propose a strategy to reduce aberration due to non-physiological motion for surgical video motion magnification. We present promising results on endoscopic transnasal transsphenoidal pituitary surgery with a quantitative comparison to recent methods using Structural Similarity (SSIM), as well as qualitative analysis by comparing spatio-temporal cross sections of the videos and individual frames.Comment: Early accept to the Internation Conference on Medical Imaging Computing and Computer Assisted Intervention (MICCAI) 2020 Presentation available here: https://www.youtube.com/watch?v=kKI_Ygny76Q Supplementary video available here: https://www.youtube.com/watch?v=8DUkcHI149

Introduction: Examined Live – An Epistemological Exchange Between Philosophy and Cultural Psychology on Reflection

Besides the general agreement about the human capability of reflection, there is a large area of disagreement and debate about the nature and value of “reflective scrutiny” and the role of “second-order states” in everyday life. This problem has been discussed in a vast and heterogeneous literature about topics such as epistemic injustice, epistemic norms, agency, understanding, meta-cognition etc. However, there is not yet any extensive and interdisciplinary work, specifically focused on the topic of the epistemic value of reflection. This volume is one of the first attempts aimed at providing an innovative contribution, an exchange between philosophy, epistemology and psychology about the place and value of reflection in everyday life. Our goal in the next sections is not to offer an exhaustive overview of recent work on epistemic reflection, nor to mimic all of the contributions made by the chapters in this volume. We will try to highlight some topics that have motivated a new resumption of this field and, with that, drawing on chapters from this volume where relevant. Two elements defined the scope and content of this volume, on the one hand, the crucial contribution of Ernest Sosa, whose works provide original and thought-provoking contributions to contemporary epistemology in setting a new direction for old dilemmas about the nature and value of knowledge, giving a central place to reflection. On the other hand, the recent developments of cultural psychology, in the version of the “Aalborg approach”, reconsider the object and scope of psychological sciences, stressing that “[h]uman conduct is purposeful”

Self-organizing ontology of biochemically relevant small molecules

<p>Abstract</p> <p>Background</p> <p>The advent of high-throughput experimentation in biochemistry has led to the generation of vast amounts of chemical data, necessitating the development of novel analysis, characterization, and cataloguing techniques and tools. Recently, a movement to publically release such data has advanced biochemical structure-activity relationship research, while providing new challenges, the biggest being the curation, annotation, and classification of this information to facilitate useful biochemical pattern analysis. Unfortunately, the human resources currently employed by the organizations supporting these efforts (e.g. ChEBI) are expanding linearly, while new useful scientific information is being released in a seemingly exponential fashion. Compounding this, currently existing chemical classification and annotation systems are not amenable to automated classification, formal and transparent chemical class definition axiomatization, facile class redefinition, or novel class integration, thus further limiting chemical ontology growth by necessitating human involvement in curation. Clearly, there is a need for the automation of this process, especially for novel chemical entities of biological interest.</p> <p>Results</p> <p>To address this, we present a formal framework based on Semantic Web technologies for the automatic design of chemical ontology which can be used for automated classification of novel entities. We demonstrate the automatic self-assembly of a structure-based chemical ontology based on 60 MeSH and 40 ChEBI chemical classes. This ontology is then used to classify 200 compounds with an accuracy of 92.7%. We extend these structure-based classes with molecular feature information and demonstrate the utility of our framework for classification of functionally relevant chemicals. Finally, we discuss an iterative approach that we envision for future biochemical ontology development.</p> <p>Conclusions</p> <p>We conclude that the proposed methodology can ease the burden of chemical data annotators and dramatically increase their productivity. We anticipate that the use of formal logic in our proposed framework will make chemical classification criteria more transparent to humans and machines alike and will thus facilitate predictive and integrative bioactivity model development.</p

Decision tree supported substructure prediction of metabolites from GC-MS profiles

Gas chromatography coupled to mass spectrometry (GC-MS) is one of the most widespread routine technologies applied to the large scale screening and discovery of novel metabolic biomarkers. However, currently the majority of mass spectral tags (MSTs) remains unidentified due to the lack of authenticated pure reference substances required for compound identification by GC-MS. Here, we accessed the information on reference compounds stored in the Golm Metabolome Database (GMD) to apply supervised machine learning approaches to the classification and identification of unidentified MSTs without relying on library searches. Non-annotated MSTs with mass spectral and retention index (RI) information together with data of already identified metabolites and reference substances have been archived in the GMD. Structural feature extraction was applied to sub-divide the metabolite space contained in the GMD and to define the prediction target classes. Decision tree (DT)-based prediction of the most frequent substructures based on mass spectral features and RI information is demonstrated to result in highly sensitive and specific detections of sub-structures contained in the compounds. The underlying set of DTs can be inspected by the user and are made available for batch processing via SOAP (Simple Object Access Protocol)-based web services. The GMD mass spectral library with the integrated DTs is freely accessible for non-commercial use at http://gmd.mpimp-golm.mpg.de/. All matching and structure search functionalities are available as SOAP-based web services. A XML + HTTP interface, which follows Representational State Transfer (REST) principles, facilitates read-only access to data base entities

Mechanosensitivity during lower extremity neurodynamic testing is diminished in individuals with Type 2 Diabetes Mellitus and peripheral neuropathy: a cross sectional study

<p>Abstract</p> <p>Background</p> <p>Type 2 Diabetes Mellitus (T2DM) and diabetic symmetrical polyneuropathy (DSP) impact multiple modalities of sensation including light touch, temperature, position sense and vibration perception. No study to date has examined the mechanosensitivity of peripheral nerves during limb movement in this population. The objective was to determine the unique effects T2DM and DSP have on nerve mechanosensitivity in the lower extremity.</p> <p>Methods</p> <p>This cross-sectional study included 43 people with T2DM. Straight leg raise neurodynamic tests were performed with ankle plantar flexion (PF/SLR) and dorsiflexion (DF/SLR). Hip flexion range of motion (ROM), lower extremity muscle activity and symptom profile, intensity and location were measured at rest, first onset of symptoms (P1) and maximally tolerated symptoms (P2).</p> <p>Results</p> <p>The addition of ankle dorsiflexion during SLR testing reduced the hip flexion ROM by 4.3° ± 6.5° at P1 and by 5.4° ± 4.9° at P2. Individuals in the T2DM group with signs of severe DSP (n = 9) had no difference in hip flexion ROM between PF/SLR and DF/SLR at P1 (1.4° ± 4.2°; paired t-test p = 0.34) or P2 (0.9° ± 2.5°; paired t-test p = 0.31). Movement induced muscle activity was absent during SLR with the exception of the tibialis anterior during DF/SLR testing. Increases in symptom intensity during SLR testing were similar for both PF/SLR and DF/SLR. The addition of ankle dorsiflexion induced more frequent posterior leg symptoms when taken to P2.</p> <p>Conclusions</p> <p>Consistent with previous recommendations in the literature, P1 is an appropriate test end point for SLR neurodynamic testing in people with T2DM. However, our findings suggest that people with T2DM and severe DSP have limited responses to SLR neurodynamic testing, and thus may be at risk for harm from nerve overstretch and the information gathered will be of limited clinical value.</p

Pneumonic Tularemia in Rabbits Resembles the Human Disease as Illustrated by Radiographic and Hematological Changes after Infection

Background: Pneumonic tularemia is caused by inhalation of the gram negative bacterium, Francisella tularensis. Because of concerns that tularemia could be used as a bioterrorism agent, vaccines and therapeutics are urgently needed. Animal models of pneumonic tularemia with a pathophysiology similar to the human disease are needed to evaluate the efficacy of these potential medical countermeasures. Principal Findings: Rabbits exposed to aerosols containing Francisella tularensis strain SCHU S4 developed a rapidly progressive fatal pneumonic disease. Clinical signs became evident on the third day after exposure with development of a fever (>40.5°C) and a sharp decline in both food and water intake. Blood samples collected on day 4 found lymphopenia and a decrease in platelet counts coupled with elevations in erythrocyte sedimentation rate, alanine aminotransferase, cholesterol, granulocytes and monocytes. Radiographs demonstrated the development of pneumonia and abnormalities of intestinal gas consistent with ileus. On average, rabbits were moribund 5.1 days after exposure; no rabbits survived exposure at any dose (190-54,000 cfu). Gross evaluation of tissues taken at necropsy showed evidence of pathology in the lungs, spleen, liver, kidney and intestines. Bacterial counts confirmed bacterial dissemination from the lungs to the liver and spleen. Conclusions/Significance: The pathophysiology of pneumonic tularemia in rabbits resembles what has been reported for humans. Rabbits therefore are a relevant model of the human disease caused by type A strains of F. tularensis. © 2011 Reed et al

First observations of separated atmospheric nu_mu and bar{nu-mu} events in the MINOS detector

The complete 5.4 kton MINOS far detector has been taking data since the beginning of August 2003 at a depth of 2070 meters water-equivalent in the Soudan mine, Minnesota. This paper presents the first MINOS observations of nuµ and [overline nu ]µ charged-current atmospheric neutrino interactions based on an exposure of 418 days. The ratio of upward- to downward-going events in the data is compared to the Monte Carlo expectation in the absence of neutrino oscillations, giving Rup/downdata/Rup/downMC=0.62-0.14+0.19(stat.)±0.02(sys.). An extended maximum likelihood analysis of the observed L/E distributions excludes the null hypothesis of no neutrino oscillations at the 98% confidence level. Using the curvature of the observed muons in the 1.3 T MINOS magnetic field nuµ and [overline nu ]µ interactions are separated. The ratio of [overline nu ]µ to nuµ events in the data is compared to the Monte Carlo expectation assuming neutrinos and antineutrinos oscillate in the same manner, giving R[overline nu ][sub mu]/nu[sub mu]data/R[overline nu ][sub mu]/nu[sub mu]MC=0.96-0.27+0.38(stat.)±0.15(sys.), where the errors are the statistical and systematic uncertainties. Although the statistics are limited, this is the first direct observation of atmospheric neutrino interactions separately for nuµ and [overline nu ]µ