Sensemaking for Broad Topics via Automated Extraction and Recursive Search

The availability of vast amounts of diverse information related to a broad topic makes it difficult and time-consuming for users to find and digest the right information regarding various low-level topics within the broader space. Current approaches to addressing these challenges include providing curated topical pages, relevant query refinement suggestions, list of subtopics, etc. However, these approaches do not scale and offer inadequate support for sensemaking. This disclosure describes automated techniques that extract information from online information sources by using a query related to a high-level topic to recursively formulate additional queries for subtopics to construct a hierarchical set of topics related to the broad query. The results can be utilized to provide a user interface using the hierarchical topic levels which can make it faster and easier for users to understand and navigate information regarding a high-level topic

Automated Extraction of Pivot Topics for Sideways Expansion of Search Scope

Users benefit from mechanisms that can help them refine their queries to facilitate searching for information connected to their underlying intent. Apart from refinements to narrow the scope of a query, users can benefit from suggestions that can help them pivot their information seeking by expanding their search sideways to related topics. This disclosure describes computational techniques for automated determination of suitable topics and/or queries for helping users expand the scope of their information search by pivoting to topics related to their query. The techniques involve selecting a meta-query, performing query expansion, identifying, aggregating, and deduplicating related entities. The identified entities are clustered and ranked to enable selection of particular entities that can be shown to users as pivot topics

Association of polymorphisms in inflammatory cytokines encoding genes with severe cases of influenza A/H1N1 and B in an Iranian population

Background: The increased levels of blood cytokines is the main immunopathological process that were attributed to severe clinical outcomes in cases of influenza A, influenza B and people with influenza-like illness (ILI). Functional genetic polymorphisms caused by single nucleotide polymorphisms (SNPs) in inflammatory cytokines genes can influence their functions either qualitatively or quantitatively, which is associated with the possibility of severe influenza infections. The aim of the present case-control study was to investigate the association of polymorphisms in inflammatory cytokines genes with influenza patients and ILI group in an Iranian population. Methods: Total number of 30 influenza B, 50 influenza A (H1N1) and 96 ILI inpatient individuals were confirmed by Real-time RT-PCR and HI assays. The genotype determination was assessed for defined SNPs in IL-1β, IL-17, IL-10 and IL-28 genes. Results: The frequencies of the IL-1β rs16944 (P = 0.007) and IL-17 rs2275913 (P = 0.006) genotypes were associated with severe influenza disease, while the frequencies of IL-10 rs1800872 and IL-28 rs8099917 were not associated with the disease (P > 0.05). Also, the absence of A allele in IL-17 rs2275913 SNP increased the risk of influenza A (H1N1) infection (P = 0.008). Conclusions: This study demonstrated that influenza A-(H1N1) and B-infected patients and also ILI controls have different profiles of immune parameters, and individuals carrying the specific cytokine-derived polymorphisms may show different immune responses towards severe outcome

Integrative Analysis of Circulating Metabolite Profiles and Magnetic Resonance Imaging Metrics in Patients with Traumatic Brain Injury

Recent evidence suggests that patients with traumatic brain injuries (TBIs) have a distinct circulating metabolic profile. However, it is unclear if this metabolomic profile corresponds to changes in brain morphology as observed by magnetic resonance imaging (MRI). The aim of this study was to explore how circulating serum metabolites, following TBI, relate to structural MRI (sMRI) findings. Serum samples were collected upon admission to the emergency department from patients suffering from acute TBI and metabolites were measured using mass spectrometry-based metabolomics. Most of these patients sustained a mild TBI. In the same patients, sMRIs were taken and volumetric data were extracted (138 metrics). From a pool of 203 eligible screened patients, 96 met the inclusion criteria for this study. Metabolites were summarized as eight clusters and sMRI data were reduced to 15 independent components (ICs). Partial correlation analysis showed that four metabolite clusters had significant associations with specific ICs, reflecting both the grey and white matter brain injury. Multiple machine learning approaches were then applied in order to investigate if circulating metabolites could distinguish between positive and negative sMRI findings. A logistic regression model was developed, comprised of two metabolic predictors (erythronic acid and myo-inositol), which, together with neurofilament light polypeptide (NF-L), discriminated positive and negative sMRI findings with an area under the curve of the receiver-operating characteristic of 0.85 (specificity = 0.89, sensitivity = 0.65). The results of this study show that metabolomic analysis of blood samples upon admission, either alone or in combination with protein biomarkers, can provide valuable information about the impact of TBI on brain structural changes

Emerging advances of nanotechnology in drug and vaccine delivery against viral associated respiratory infectious diseases (VARID)

Viral-associated respiratory infectious diseases are one of the most prominent subsets of respiratory failures, known as viral respiratory infections (VRI). VRIs are proceeded by an infection caused by viruses infecting the respiratory system. For the past 100 years, viral associated respiratory epidemics have been the most common cause of infectious disease worldwide. Due to several drawbacks of the current anti-viral treatments, such as drug resistance generation and non-targeting of viral proteins, the development of novel nanotherapeutic or nano-vaccine strategies can be considered essential. Due to their specific physical and biological properties, nanoparticles hold promising opportunities for both anti-viral treatments and vaccines against viral infections. Besides the specific physiological properties of the respiratory system, there is a significant demand for utilizing nano-designs in the production of vaccines or antiviral agents for airway-localized administration. SARS-CoV-2, as an immediate example of respiratory viruses, is an enveloped, positive-sense, single-stranded RNA virus belonging to the coronaviridae family. COVID-19 can lead to acute respiratory distress syndrome, similarly to other members of the coronaviridae. Hence, reviewing the current and past emerging nanotechnology-based medications on similar respiratory viral diseases can identify pathways towards generating novel SARS-CoV-2 nanotherapeutics and/or nano-vaccines. © 2021 by the authors. Licensee MDPI, Basel, Switzerland

The ER Stress/UPR axis in chronic obstructive pulmonary disease and idiopathic pulmonary fibrosis

Cellular protein homeostasis in the lungs is constantly disrupted by recurrent exposure to various external and internal stressors, which may cause considerable protein secretion pressure on the endoplasmic reticulum (ER), resulting in the survival and differentiation of these cell types to meet the increased functional demands. Cells are able to induce a highly conserved adaptive mechanism, known as the unfolded protein response (UPR), to manage such stresses. UPR dysregulation and ER stress are involved in numerous human illnesses, such as metabolic syndrome, fibrotic diseases, and neurodegeneration, and cancer. Therefore, effective and specific compounds targeting the UPR pathway are being considered as potential therapies. This review focuses on the impact of both external and internal stressors on the ER in idiopathic pulmonary fibrosis (IPF) and chronic obstructive pulmonary disease (COPD) and discusses the role of the UPR signaling pathway activation in the control of cellular damage and specifically highlights the potential involvement of non-coding RNAs in COPD. Summaries of pathogenic mechanisms associated with the ER stress/UPR axis contributing to IPF and COPD, and promising pharmacological intervention strategies, are also presented

Heart and systemic effects of statin pretreatment in a rat model of abdominal sepsis. Assessment by Tc99m-sestamibi biodistribition

PURPOSE: To evaluate the heart and the Tc-99m-sestamibi biodistribution after statin pretreatment in a rat model of abdominal sepsis. METHODS: Twenty-four Wistar rats were randomly distributed into four groups (n=6 per group): 1) sepsis with simvastatin treatment, 2) sepsis with vehicle, 3) sham control with simvastatin and 4) sham control with vehicle. 24 hours after cecal ligation and puncture rats received 1.0MBq of Tc-99m-sestamibi i.v. 30min after, animals were euthanized for ex-vivo tissue counting and myocardium histological analysis. RESULTS: Myocardial histologic alterations were not detected 24 hours post-sepsis. There was significantly increased cardiac Tc-99m-sestamibi activity in the sepsis group with simvastatin treatment (1.9$\pm$0.3%ID/g, p<0.001) in comparison to the sepsis group+vehicle (1.0$\pm$0.2% ID/g), control sham group+ simvastatin (1.2$\pm$0.3% ID/g) and control sham group (1.3$\pm$0.2% ID/g). Significant Tc-99m-sestamibi activity in liver, kidney and lungs was also detected in the sepsis group treated with simvastatinin comparison to the other groups. CONCLUSIONS: Statin treatment altered the biodistribution of Tc-99m-sestamibi with increased cardiac and solid organ activity in rats with abdominal sepsis, while no impact on controls. Increased myocardial tracer activity may be a result of a possible protection effect due to increased tissue perfusion mediated by statins

The Integrin Receptor in Biologically Relevant Bilayers: Insights from Molecular Dynamics Simulations

Integrins are heterodimeric (αβ) cell surface receptors that are potential therapeutic targets for a number of diseases. Despite the existence of structural data for all parts of integrins, the structure of the complete integrin receptor is still not available. We have used available structural data to construct a model of the complete integrin receptor in complex with talin F2–F3 domain. It has been shown that the interactions of integrins with their lipid environment are crucial for their function but details of the integrin/lipid interactions remain elusive. In this study an integrin/talin complex was inserted in biologically relevant bilayers that resemble the cell plasma membrane containing zwitterionic and charged phospholipids, cholesterol and sphingolipids to study the dynamics of the integrin receptor and its effect on bilayer structure and dynamics. The results of this study demonstrate the dynamic nature of the integrin receptor and suggest that the presence of the integrin receptor alters the lipid organization between the two leaflets of the bilayer. In particular, our results suggest elevated density of cholesterol and of phosphatidylserine lipids around the integrin/talin complex and a slowing down of lipids in an annulus of ~30 Å around the protein due to interactions between the lipids and the integrin/talin F2–F3 complex. This may in part regulate the interactions of integrins with other related proteins or integrin clustering thus facilitating signal transduction across cell membranes

Admission Levels of Interleukin 10 and Amyloid β 1–40 Improve the Outcome Prediction Performance of the Helsinki Computed Tomography Score in Traumatic Brain Injury

Background: Blood biomarkers may enhance outcome prediction performance of head computed tomography scores in traumatic brain injury (TBI). Objective: To investigate whether admission levels of eight different protein biomarkers can improve the outcome prediction performance of the Helsinki computed tomography score (HCTS) without clinical covariates in TBI. Materials and methods: Eighty-two patients with computed tomography positive TBIs were included in this study. Plasma levels of β-amyloid isoforms 1–40 (Aβ40) and 1–42 (Aβ42), glial fibrillary acidic protein, heart fatty acid-binding protein, interleukin 10 (IL-10), neurofilament light, S100 calcium-binding protein B, and total tau were measured within 24 h from admission. The patients were divided into favorable (Glasgow Outcome Scale—Extended 5–8, n = 49) and unfavorable (Glasgow Outcome Scale—Extended 1–4, n = 33) groups. The outcome was assessed 6–12 months after injury. An optimal predictive panel was investigated with the sensitivity set at 90–100%. Results: The HCTS alone yielded a sensitivity of 97.0% (95% CI: 90.9–100) and specificity of 22.4% (95% CI: 10.2–32.7) and partial area under the curve of the receiver operating characteristic of 2.5% (95% CI: 1.1–4.7), in discriminating patients with favorable and unfavorable outcomes. The threshold to detect a patient with unfavorable outcome was an HCTS > 1. The three best individually performing biomarkers in outcome prediction were Aβ40, Aβ42, and neurofilament light. The optimal panel included IL-10, Aβ40, and the HCTS reaching a partial area under the curve of the receiver operating characteristic of 3.4% (95% CI: 1.7–6.2) with a sensitivity of 90.9% (95% CI: 81.8–100) and specificity of 59.2% (95% CI: 40.8–69.4). Conclusion: Admission plasma levels of IL-10 and Aβ40 significantly improve the prognostication ability of the HCTS after TBI