Skeletal muscle dysfunction is associated with derangements in mitochondrial bioenergetics (but not UCP3) in a rodent model of sepsis

Muscle dysfunction is a common feature of severe sepsis and multi-organ failure. Recent evidence implicates bioenergetic dysfunction and oxidative damage as important underlying pathophysiological mechanisms. Increased abundance of uncoupling protein-3 (UCP-3) in sepsis suggests increased mitochondrial proton leak, which may reduce mitochondrial coupling efficiency but limit ROS production. Using a murine model, we examined metabolic, cardiovascular and skeletal muscle contractile changes following induction of peritoneal sepsis in wild-type and Ucp3(-/-) mice. Mitochondrial membrane potential (Δψm) was measured using two-photon microscopy in living diaphragm, and contractile function was measured in diaphragm muscle strips. The kinetic relationship between membrane potential and oxygen consumption was determined using a modular kinetic approach in isolated mitochondria. Sepsis was associated with significant whole body metabolic suppression, hypothermia and cardiovascular dysfunction. Maximal force generation was reduced and fatigue accelerated in ex vivo diaphragm muscle strips from septic mice. Mitochondrial membrane potential was lower in the isolated diaphragm from septic mice despite normal substrate oxidation kinetics and proton leak in skeletal muscle mitochondria. Even though wild-type mice exhibited an absolute 26 ± 6% higher UCP-3 protein abundance at 24 hours, no differences were seen in whole animal or diaphragm physiology, nor in survival rates, between wild-type and Ucp3(-/-) mice. In conclusion, this murine sepsis model shows a hypometabolic phenotype with evidence of significant cardiovascular and muscle dysfunction. This was associated with lower Δψm and alterations in mitochondrial ATP turnover and phosphorylation pathway. However, UCP-3 does not play an important functional role, despite its upregulation

Sensor-Based Locomotion Data Mining for Supporting the Diagnosis of Neurodegenerative Disorders: A Survey

Locomotion characteristics and movement patterns are reliable indicators of neurodegenerative diseases (NDDs). This survey provides a systematic literature review of locomotion data mining systems for supporting NDD diagnosis. We discuss techniques for discovering low-level locomotion indicators, sensor data acquisition and processing methods, and NDD detection algorithms. The survey presents a comprehensive discussion on the main challenges for this active area, including the addressed diseases, locomotion data types, duration of monitoring, employed algorithms, and experimental validation strategies. We also identify prominent open challenges and research directions regarding ethics and privacy issues, technological and usability aspects, and availability of public benchmarks

Implementation science in adolescent healthcare research: an integrative review.

BACKGROUND: Multiple theories, models and frameworks have been developed to assist implementation of evidence-based practice. However, to date there has been no review of implementation literature specific to adolescent healthcare. This integrative review therefore aimed to determine what implementation science theories, models and frameworks have been applied, what elements of these frameworks have been identified as influential in promoting the implementation and sustainability of service intervention, and to what extent, in what capacity and at what time points has the contribution of adolescent consumer perspectives on evidence implementation been considered.  METHODS: An integrative design was used and reported based on a modified form of the PRISMA (2020) checklist. Seven databases were searched for English language primary research which included any implementation science theory, model or framework developed for/with adolescents or applied in relation to adolescent healthcare services within the past 10 years. Content and thematic analysis were applied with the Consolidated Framework for Implementation Research (CFIR) used to frame analysis of the barriers and facilitators to effective implementation of evidence-informed interventions within youth health settings. RESULTS: From 8717 citations, 13 papers reporting 12 studies were retained. Nine different implementation science theories, frameworks or approaches were applied; six of 12 studies used the CFIR, solely or with other models. All CFIR domains were represented as facilitators and barriers for implementation in included studies. However, there was little or no inclusion of adolescents in the development or review of these initiatives. Only three mentioned youth input, occurring in the pre-implementation or implementation stages. CONCLUSIONS: The few studies found for this review highlight the internationally under-developed nature of this topic. Flagging the importance of the unique characteristics of this particular age group, and of the interventions and strategies to target it, the minimal input of adolescent consumers is cause for concern. Further research is clearly needed and must ensure that youth consumers are engaged from the start and consistently throughout; that their voice is prioritised and not tokenistic; that their contribution is taken seriously. Only then will age-appropriate evidence implementation enable innovations in youth health services to achieve the evidence-based outcomes they offer. TRIAL REGISTRATION: PROSPERO 2020 CRD42020201142 https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=201142

Effect of illness perception improvement on risk factors of coronary artery disease

Background: Illness perception can affect health-related behaviors and disease outcomes. Objectives: To determine the effect of an educational intervention of improving illness perception on some modifiable risk factors of coronary artery disease. Methods: In this clinical trial, 100 patients undergoing coronary angiography that met the inclusion criteria were divided randomly into two intervention and control groups. In the intervention group, three educational sessions were conducted individually, while usual care was conducted for the control group. Measurements on fasting blood glucose, cholesterol, triglyceride, blood pressure, body mass index, and smoking status were gathered at baseline, immediately and six months after the intervention in both groups. Data were analyzed using the SPSS. Results: The mean of systolic blood pressure (p<0.005), fasting triglycerides (p<0.005), and fasting blood glucose (p<0.005) were significantly different before and after the intervention between the two groups. Conclusion: Improvement illness perception through educational intervention can affect risk factors of coronary artery disease

Sensitivity of remotely sensed pigment concentration via Mixture Density Networks (MDNs) to uncertainties from atmospheric correction

Lake Erie, the shallowest of the five North American Laurentian Great Lakes, exhibits degraded water quality associated with recurrent phytoplankton blooms. Optical remote sensing of these optically com�plex inland waters is challenging due to the uncertainties stemming from atmospheric correction (AC) procedures. In this study, the accuracy of remote sensing reflectance (Rrs) derived from three different AC algorithms applied to Ocean and Land Colour Instrument (OLCI) observations of western Lake Erie (WLE) is evaluated through comparison to a regional radiometric dataset. The effects of uncertainties in Rrs products on the retrieval of near-surface concentration of pigments, including chlorophyll-a (Chla) and phycocyanin (PC), from Mixture Density Networks (MDNs) are subsequently investigated. Results show that iCOR contained the fewest number of processed (unflagged) days per pixel, compared to ACOLITE and POLYMER, for parts of the lake. Limiting results to the matchup dataset in common between the three AC algorithms shows that iCOR and ACOLITE performed closely at 665 nm, while out�performing POLYMER, with the Median Symmetric Accuracy (MdSA) of �30 %, 28 %, and 53 %, respec�tively. MDN applied to iCOR- and ACOLITE-corrected data (MdSA < 37 %) outperformed MDN applied to POLYMER-corrected data in estimating Chla. Large uncertainties in satellite-derived Rrs propagated to uncertainties �100 % in PC estimates, although the model was able to recover concentrations along the 1:1 line. Despite the need for improvements in its cloud-masking scheme, we conclude that iCOR combined with MDNs produces adequate OLCI pigment products for studying and monitoring Chla across WL

A comparative study of long interspersed element-1 protein immunoreactivity in cutaneous malignancies

Background: Skin cancer is the most common cancer worldwide and commonly classified into malignant melanoma (MM) and Nonmelanoma skin cancers (NMSCs), which mainly include basal cell carcinoma (BCC) and squamous cell carcinoma (SCC). The extent to which Long Interspersed Element-1 (LINE-1, L1) ORF1p is expressed in cutaneous malignancies remains to be evaluated. This study aimed to assess LINE-1 ORF1p immunoreactivity in various skin cancer subtypes. Method: The expression level of LINE-1 ORF1p was evaluated in 95 skin cancer specimens comprising 36 (37.9) BCC, 28 (29.5) SCC, and 31 (32.6) melanoma using the tissue microarray (TMA) technique. Then the association between expression of LINE-1 encoded protein and clinicopathological parameters was analyzed. Results: We showed that LINE-1 ORF1p expression level was substantially higher in BCC and SCC patients compared with melanoma samples (p 0.05). Conclusions: According to our observation, LINE-1 ORF1p immunoreactivity in various skin tumor subtypes extends previous studies of LINE-1 expression in different cancers. LINE-1ORF1p overexpression in NMSCs compared with MM can be considered with caution as a tumor-specific antigen for NMSCs. © 2020 The Author(s)

Disclosing ambiguous gene aliases by automatic literature profiling

Submitted by Nuzia Santos ([email protected]) on 2015-01-14T10:55:18Z No. of bitstreams: 1 Disclosing ambiguous gene aliases by automatic.pdf: 217573 bytes, checksum: ce54aa2c4ea49eb989f9e7308d827ce6 (MD5)Approved for entry into archive by Nuzia Santos ([email protected]) on 2015-01-14T10:55:25Z (GMT) No. of bitstreams: 1 Disclosing ambiguous gene aliases by automatic.pdf: 217573 bytes, checksum: ce54aa2c4ea49eb989f9e7308d827ce6 (MD5)Approved for entry into archive by Nuzia Santos ([email protected]) on 2015-01-14T11:01:59Z (GMT) No. of bitstreams: 1 Disclosing ambiguous gene aliases by automatic.pdf: 217573 bytes, checksum: ce54aa2c4ea49eb989f9e7308d827ce6 (MD5)Made available in DSpace on 2015-01-14T11:01:59Z (GMT). No. of bitstreams: 1 Disclosing ambiguous gene aliases by automatic.pdf: 217573 bytes, checksum: ce54aa2c4ea49eb989f9e7308d827ce6 (MD5) Previous issue date: 2010Fundação Oswaldo Cruz. Centro de Pesquisa René Rachou. Centro de Excelência em Bioinformática. Belo Horizonte, MG, Brasil/Fundação Oswaldo Cruz. Centro de Pesquisa René Rachou. Grupo de Genômica e Biologia Computacional. Belo Horizonte, MG, BrasilGlaxoSmithKline Moore Dr. Molecular Discovery Research. Research Triangle Park, NC, USAFundação Oswaldo Cruz. Centro de Pesquisa René Rachou. Centro de Excelência em Bioinformática. Belo Horizonte, MG, Brasil/Fundação Oswaldo Cruz. Centro de Pesquisa René Rachou. Grupo de Genômica e Biologia Computacional. Belo Horizonte, MG, BrasilBackground Retrieving pertinent information from biological scientific literature requires cutting-edge text mining methods which may be able to recognize the meaning of the very ambiguous names of biological entities. Aliases of a gene share a common vocabulary in their respective collections of PubMed abstracts. This may be true even when these aliases are not associated with the same subset of documents. This gene-specific vocabulary defines a unique fingerprint that can be used to disclose ambiguous aliases. The present work describes an original method for automatically assessing the ambiguity levels of gene aliases in large gene terminologies based exclusively in the content of their associated literature. The method can deal with the two major problems restricting the usage of current text mining tools: 1) different names associated with the same gene; and 2) one name associated with multiple genes, or even with non-gene entities. Important, this method does not require training examples. Results Aliases were considered “ambiguous” when their Jaccard distance to the respective official gene symbol was equal or greater than the smallest distance between the official gene symbol and one of the three internal controls (randomly picked unrelated official gene symbols). Otherwise, they were assigned the status of “synonyms”. We evaluated the coherence of the results by comparing the frequencies of the official gene symbols in the text corpora retrieved with their respective “synonyms” or “ambiguous” aliases. Official gene symbols were mentioned in the abstract collections of 42 % (70/165) of their respective synonyms. No official gene symbol occurred in the abstract collections of any of their respective ambiguous aliases. In overall, querying PubMed with official gene symbols and “synonym” aliases allowed a 3.6-fold increase in the number of unique documents retrieved. Conclusions These results confirm that this method is able to distinguish between synonyms and ambiguous gene aliases based exclusively on their vocabulary fingerprint. The approach we describe could be used to enhance the retrieval of relevant literature related to a gen

Cationic surfactants for demulsification of produced water from alkaline-surfactant-polymer flooding

In this research, demulsification of produced water (which is an oil-in-water emulsion) from alkaline–surfactant–polymer flooding, containing sodium alkyl sulfate, was evaluated using five different surfactants from the classes of nonionic, amphoteric, and cationic. It was observed that only single-tail cationic surfactants, namely, dodecyltriemthylammonium chloride (DTAC) and alkyltrimethylammonium bromide (ATAB), with a concentration of 1000 ppm, were capable of attaining transparent separated water phases following 3 h separation at room temperature with relative separation efficiencies, determined using fluorescence spectroscopy, of 89.4 and 59%, respectively. However, the cationic surfactant dimethyldioctadecylammonium chloride (DDOAC) could achieve a relative separation efficiency of only 28.4% after 13 days, in contrast to nonionic and amphoteric surfactants that did not reveal any progress in demulsification. Similarly, given the demulsifier concentration of 1000 ppm, only DTAC and ATAB reduced the negative surface charge of oil droplets in the produced water after 3 h separation, and large droplets were formed owing to their coalescence after the addition of the respective demulsifiers as viewed by optical microscopy. The dominant emulsification mechanism is believed to be electrostatic stabilization. Consequently, the proposed demulsification mechanism is the formation/adsorption of cationic–anionic pairs at the oil–water interface. When comparing the demulsification performances of various demulsifying surfactants, although high interfacial activity (low interfacial tension (IFT)) is an essential feature for a demulsifier to be considered effective, it was concluded that lower equilibrium IFT does not necessarily result in superior separation efficiency, and other parameters such as type, tail branch number (i.e., single-tail or double-tail), and purity of surfactant may have profound effects on both separation efficiency and demulsification speed of the emulsion. From the dynamic IFT data, it was realized that DTAC and ATAB caused faster demulsification than DDOAC. The undesirable demulsification performance of DDOAC might have been due to its double-tail structure, which confined its interfacial adsorption. The operational variables, including salinity, pH, and temperature, in the demulsification process by DTAC were optimized with respect to the changes of IFT, and the optimum values were found to be 2 wt %, 7.0, and 35 °C, respectively

Synergistic drug-cytokine induction of hepatocellular death as an in vitro approach for the study of inflammation-associated idiosyncratic drug hepatotoxicity

Idiosyncratic drug hepatotoxicity represents a major problem in drug development due to inadequacy of current preclinical screening assays, but recently established rodent models utilizing bacterial LPS co-administration to induce an inflammatory background have successfully reproduced idiosyncratic hepatotoxicity signatures for certain drugs. However, the low-throughput nature of these models renders them problematic for employment as preclinical screening assays. Here, we present an analogous, but high-throughput, in vitro approach in which drugs are administered to a variety of cell types (primary human and rat hepatocytes and the human HepG2 cell line) across a landscape of inflammatory contexts containing LPS and cytokines TNF, IFNγ, IL-1α, and IL-6. Using this assay, we observed drug–cytokine hepatotoxicity synergies for multiple idiosyncratic hepatotoxicants (ranitidine, trovafloxacin, nefazodone, nimesulide, clarithromycin, and telithromycin) but not for their corresponding non-toxic control compounds (famotidine, levofloxacin, buspirone, and aspirin). A larger compendium of drug–cytokine mix hepatotoxicity data demonstrated that hepatotoxicity synergies were largely potentiated by TNF, IL-1α, and LPS within the context of multi-cytokine mixes. Then, we screened 90 drugs for cytokine synergy in human hepatocytes and found that a significantly larger fraction of the idiosyncratic hepatotoxicants (19%) synergized with a single cytokine mix than did the non-hepatotoxic drugs (3%). Finally, we used an information theoretic approach to ascertain especially informative subsets of cytokine treatments for most highly effective construction of regression models for drug- and cytokine mix-induced hepatotoxicities across these cell systems. Our results suggest that this drug–cytokine co-treatment approach could provide a useful preclinical tool for investigating inflammation-associated idiosyncratic drug hepatotoxicity.Pfizer Inc.Institute for Collaborative BiotechnologiesMIT Center for Cell Decision ProcessesNational Institute of Mental Health (U.S.) (grant P50-GM68762)National Institute of Mental Health (U.S.) (grant T32-GM008334)Massachusetts Institute of Technology. Biotechnology Process Engineering CenterMassachusetts Institute of Technology. Center for Environmental Health SciencesNational Institute of Mental Health (U.S.) (grant U19ES011399)Whitaker Foundatio