OPAAS: a web server for optimal, permuted, and other alternative alignments of protein structures

The large number of experimentally determined protein 3D structures is a rich resource for studying protein function and evolution, and protein structure comparison (PSC) is a key method for such studies. When comparing two protein structures, almost all currently available PSC servers report a single and sequential (i.e. topological) alignment, whereas the existence of good alternative alignments, including those involving permutations (i.e. non-sequential or non-topological alignments), is well known. We have recently developed a novel PSC method that can detect alternative alignments of statistical significance (alignment similarity P-value <10(−5)), including structural permutations at all levels of complexity. OPAAS, the server of this PSC method freely accessible at our website (), provides an easy-to-read hierarchical layout of output to display detailed information on all of the significant alternative alignments detected. Because these alternative alignments can offer a more complete picture on the structural, evolutionary and functional relationship between two proteins, OPAAS can be used in structural bioinformatics research to gain additional insight that is not readily provided by existing PSC servers

Selective enhancement of emotional, but not motor, learning in monoamine oxidase A-deficient mice

Mice deficient in monoamine oxidase A (MAOA), an enzyme that metabolizes monoamines such as norepinephrine and serotonin, have elevated norepinephrine and serotonin levels in the frontal cortex, hippocampus, and cerebellum, compared with normal wild-type mice. Since monoamines in these areas are critically involved in a variety of behaviors, we examined learning and memory (using emotional and motor tasks) in MAOA mutant mice. The MAOA-deficient mice exhibited significantly enhanced classical fear conditioning (freezing to both tone and contextual stimuli) and step-down inhibitory avoidance learning. In contrast, eyeblink conditioning was normal in these mutant mice. The female MAOA-deficient mice also displayed normal species-typical maternal behaviors (nesting, nursing, and pup retrieval). These results suggest that chronic elevations of monoamines, due to a deletion of the gene encoding MAOA, lead to selective alterations in emotional behavior.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/56225/1/kimPNAS97.pd

Su bstrate Specificity of Mam malian Folylpolyglutamate Synthetase for 5,1 0-Dideazatetrahydrofolate Analogs

SUMMARY The metabolism of 5,1 0-dideazatetrahydrofolate (DDATH

International Veterinary Epilepsy Task Force consensus proposal: Medical treatment of canine epilepsy in Europe

In Europe, the number of antiepileptic drugs (AEDs) licensed for dogs has grown considerably over the last years. Nevertheless, the same questions remain, which include, 1) when to start treatment, 2) which drug is best used initially, 3) which adjunctive AED can be advised if treatment with the initial drug is unsatisfactory, and 4) when treatment changes should be considered. In this consensus proposal, an overview is given on the aim of AED treatment, when to start long-term treatment in canine epilepsy and which veterinary AEDs are currently in use for dogs. The consensus proposal for drug treatment protocols, 1) is based on current published evidence-based literature, 2) considers the current legal framework of the cascade regulation for the prescription of veterinary drugs in Europe, and 3) reflects the authors’ experience. With this paper it is aimed to provide a consensus for the management of canine idiopathic epilepsy. Furthermore, for the management of structural epilepsy AEDs are inevitable in addition to treating the underlying cause, if possible

The APEX Quantitative Proteomics Tool: Generating protein quantitation estimates from LC-MS/MS proteomics results

Mass spectrometry (MS) based label-free protein quantitation has mainly focused on analysis of ion peak heights and peptide spectral counts. Most analyses of tandem mass spectrometry (MS/MS) data begin with an enzymatic digestion of a complex protein mixture to generate smaller peptides that can be separated and identified by an MS/MS instrument. Peptide spectral counting techniques attempt to quantify protein abundance by counting the number of detected tryptic peptides and their corresponding MS spectra. However, spectral counting is confounded by the fact that peptide physicochemical properties severely affect MS detection resulting in each peptide having a different detection probability. Lu et al. (2007) described a modified spectral counting technique, Absolute Protein Expression (APEX), which improves on basic spectral counting methods by including a correction factor for each protein (called O(i) value) that accounts for variable peptide detection by MS techniques. The technique uses machine learning classification to derive peptide detection probabilities that are used to predict the number of tryptic peptides expected to be detected for one molecule of a particular protein (O(i)). This predicted spectral count is compared to the protein's observed MS total spectral count during APEX computation of protein abundances. Results: The APEX Quantitative Proteomics Tool, introduced here, is a free open source Java application that supports the APEX protein quantitation technique. The APEX tool uses data from standard tandem mass spectrometry proteomics experiments and provides computational support for APEX protein abundance quantitation through a set of graphical user interfaces that partition thparameter controls for the various processing tasks. The tool also provides a Z-score analysis for identification of significant differential protein expression, a utility to assess APEX classifier performance via cross validation, and a utility to merge multiple APEX results into a standardized format in preparation for further statistical analysis. Conclusion: The APEX Quantitative Proteomics Tool provides a simple means to quickly derive hundreds to thousands of protein abundance values from standard liquid chromatography-tandem mass spectrometry proteomics datasets. The APEX tool provides a straightforward intuitive interface design overlaying a highly customizable computational workflow to produce protein abundance values from LC-MS/MS datasets.National Institute of Allergy and Infectious Diseases (NIAID) N01-AI15447National Institutes of HealthNational Science Foundation, the Welsh and Packard FoundationsInternational Human Frontier Science ProgramCenter for Systems and Synthetic Biolog

An Abundant Dysfunctional Apolipoprotein A1 in Human Atheroma

Recent studies have indicated that high-density lipoproteins (HDLs) and their major structural protein, apolipoprotein A1 (apoA1), recovered from human atheroma are dysfunctional and are extensively oxidized by myeloperoxidase (MPO). In vitro oxidation of either apoA1 or HDL particles by MPO impairs their cholesterol acceptor function. Here, using phage display affinity maturation, we developed a high-affinity monoclonal antibody that specifically recognizes both apoA1 and HDL that have been modified by the MPO-H2O2-Cl− system. An oxindolyl alanine (2-OH-Trp) moiety at Trp72 of apoA1 is the immunogenic epitope. Mutagenesis studies confirmed a critical role for apoA1 Trp72 in MPO-mediated inhibition of the ATP-binding cassette transporter A1 (ABCA1)-dependent cholesterol acceptor activity of apoA1 in vitro and in vivo. ApoA1 containing a 2-OH-Trp72 group (oxTrp72-apoA1) is in low abundance within the circulation but accounts for 20% of the apoA1 in atherosclerosis-laden arteries. OxTrp72-apoA1 recovered from human atheroma or plasma is lipid poor, virtually devoid of cholesterol acceptor activity and demonstrated both a potent proinflammatory activity on endothelial cells and an impaired HDL biogenesis activity in vivo. Elevated oxTrp72-apoA1 levels in subjects presenting to a cardiology clinic (n = 627) were associated with increased cardiovascular disease risk. Circulating oxTrp72-apoA1 levels may serve as a way to monitor a proatherogenic process in the artery wall

Preservation of Ranking Order in the Expression of Human Housekeeping Genes

Housekeeping (HK) genes fulfill the basic needs for a cell to survive and function properly. Their ubiquitous expression, originally thought to be constant, can vary from tissue to tissue, but this variation remains largely uncharacterized and it could not be explained by previously identified properties of HK genes such as short gene length and high GC content. By analyzing microarray expression data for human genes, we uncovered a previously unnoted characteristic of HK gene expression, namely that the ranking order of their expression levels tends to be preserved from one tissue to another. Further analysis by tensor product decomposition and pathway stratification identified three main factors of the observed ranking preservation, namely that, compared to those of non-HK (NHK) genes, the expression levels of HK genes show a greater degree of dispersion (less overlap), stableness (a smaller variation in expression between tissues), and correlation of expression. Our results shed light on regulatory mechanisms of HK gene expression that are probably different for different HK genes or pathways, but are consistent and coordinated in different tissues

LATE-NC staging in routine neuropathologic diagnosis : an update

An international consensus report in 2019 recommended a classification system for limbic-predominant age-related TDP-43 encephalopathy neuropathologic changes (LATE-NC). The suggested neuropathologic staging system and nomenclature have proven useful for autopsy practice and dementia research. However, some issues remain unresolved, such as cases with unusual features that do not fit with current diagnostic categories. The goal of this report is to update the neuropathologic criteria for the diagnosis and staging of LATE-NC, based primarily on published data. We provide practical suggestions about how to integrate available genetic information and comorbid pathologies [e.g., Alzheimer's disease neuropathologic changes (ADNC) and Lewy body disease]. We also describe recent research findings that have enabled more precise guidance on how to differentiate LATE-NC from other subtypes of TDP-43 pathology [e.g., frontotemporal lobar degeneration (FTLD) and amyotrophic lateral sclerosis (ALS)], and how to render diagnoses in unusual situations in which TDP-43 pathology does not follow the staging scheme proposed in 2019. Specific recommendations are also made on when not to apply this diagnostic term based on current knowledge. Neuroanatomical regions of interest in LATE-NC are described in detail and the implications for TDP-43 immunohistochemical results are specified more precisely. We also highlight questions that remain unresolved and areas needing additional study. In summary, the current work lays out a number of recommendations to improve the precision of LATE-NC staging based on published reports and diagnostic experience.Peer reviewe

Artificial intelligence-assisted remote detection of ST-elevation myocardial infarction using a mini-12-lead electrocardiogram device in prehospital ambulance care

ObjectiveTo implement an all-day online artificial intelligence (AI)-assisted detection of ST-elevation myocardial infarction (STEMI) by prehospital 12-lead electrocardiograms (ECGs) to facilitate patient triage for timely reperfusion therapy.MethodsThe proposed AI model combines a convolutional neural network and long short-term memory (CNN-LSTM) to predict STEMI on prehospital 12-lead ECGs obtained from mini-12-lead ECG devices equipped in ambulance vehicles in Central Taiwan. Emergency medical technicians (EMTs) from the 14 AI-implemented fire stations performed the on-site 12-lead ECG examinations using the mini portable device. The 12-lead ECG signals were transmitted to the AI center of China Medical University Hospital to classify the recordings as “STEMI” or “Not STEMI”. In 11 non-AI fire stations, the ECG data were transmitted to a secure network and read by available on-line emergency physicians. The response time was defined as the time interval between the ECG transmission and ECG interpretation feedback.ResultsBetween July 17, 2021, and March 26, 2022, the AI model classified 362 prehospital 12-lead ECGs obtained from 275 consecutive patients who had called the 119 dispatch centers of fire stations in Central Taiwan for symptoms of chest pain or shortness of breath. The AI's response time to the EMTs in ambulance vehicles was 37.2 ± 11.3 s, which was shorter than the online physicians' response time from 11 other fire stations with no AI implementation (113.2 ± 369.4 s, P &lt; 0.001) after analyzing another set of 335 prehospital 12-lead ECGs. The evaluation metrics including accuracy, precision, specificity, recall, area under the receiver operating characteristic curve, and F1 score to assess the overall AI performance in the remote detection of STEMI were 0.992, 0.889, 0.994, 0.941, 0.997, and 0.914, respectively. During the study period, the AI model promptly identified 10 STEMI patients who underwent primary percutaneous coronary intervention (PPCI) with a median contact-to-door time of 18.5 (IQR: 16–20.8) minutes.ConclusionImplementation of an all-day real-time AI-assisted remote detection of STEMI on prehospital 12-lead ECGs in the field is feasible with a high diagnostic accuracy rate. This approach may help minimize preventable delays in contact-to-treatment times for STEMI patients who require PPCI

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice