Quality control for next-generation liquefaction case histories

The Next-Generation Liquefaction (NGL) database is an open-source, global database of liquefaction and non-ground failure case-histories. The database is part of a multi-year research effort with the main goal of developing improved procedures to evaluate liquefaction susceptibility, triggering, and consequences. In NGL, a case-history is defined as the intersection of three components: (1) a site, (2) an earthquake event, and (3) post-earthquake observations. The NGL database hosts case-histories used to develop existing liquefaction models, as well as new data derived from recent earthquakes such as the 2010-2011 Canterbury earthquake sequence, the 2011 Tohoku-Oki earthquake, and the 2012 Emilia earthquake. The database also hosts lateral spread case-histories, and a substantial number of liquefaction sites characterized by the presence of co-located recording stations. All of the data present in the NGL database are reviewed by the NGL Database Working Group. The NGL formal vetting process is described for an example case-history

Amino Acid Similarity Accounts for T Cell Cross-Reactivity and for “Holes” in the T Cell Repertoire

Background: Cytotoxic T cell (CTL) cross-reactivity is believed to play a pivotal role in generating immune responses but the extent and mechanisms of CTL cross-reactivity remain largely unknown. Several studies suggest that CTL clones can recognize highly diverse peptides, some sharing no obvious sequence identity. The emerging realization in the field is that T cell receptors (TcR) recognize multiple distinct ligands. Principal Findings: First, we analyzed peptide scans of the HIV epitope SLFNTVATL (SFL9) and found that TCR specificity is position dependent and that biochemically similar amino acid substitutions do not drastically affect recognition. Inspired by this, we developed a general model of TCR peptide recognition using amino acid similarity matrices and found that such a model was able to predict the cross-reactivity of a diverse set of CTL epitopes. With this model, we were able to demonstrate that seemingly distinct T cell epitopes, i.e., ones with low sequence identity, are in fact more biochemically similar than expected. Additionally, an analysis of HIV immunogenicity data with our model showed that CTLs have the tendency to respond mostly to peptides that do not resemble self-antigens. Conclusions: T cell cross-reactivity can thus, to an extent greater than earlier appreciated, be explained by amino acid similarity. The results presented in this paper will help resolving some of the long-lasting discussions in the field of T cel

Degenerate T-cell Recognition of Peptides on MHC Molecules Creates Large Holes in the T-cell Repertoire

The cellular immune system screens peptides presented by host cells on MHC molecules to assess if the cells are infected. In this study we examined whether the presented peptides contain enough information for a proper self/nonself assessment by comparing the presented human (self) and bacterial or viral (nonself) peptides on a large number of MHC molecules. For all MHC molecules tested, only a small fraction of the presented nonself peptides from 174 species of bacteria and 1000 viral proteomes (0.2%) is shown to be identical to a presented self peptide. Next, we use available data on T-cell receptor-peptide-MHC interactions to estimate how well T-cells distinguish between similar peptides. The recognition of a peptide-MHC by the T-cell receptor is flexible, and as a result, about one-third of the presented nonself peptides is expected to be indistinguishable (by T-cells) from presented self peptides. This suggests that T-cells are expected to remain tolerant for a large fraction of the presented nonself peptides, which provides an explanation for the “holes in the T-cell repertoire” that are found for a large fraction of foreign epitopes. Additionally, this overlap with self increases the need for efficient self tolerance, as many self-similar nonself peptides could initiate an autoimmune response. Degenerate recognition of peptide-MHC-I complexes by T-cells thus creates large and potentially dangerous overlaps between self and nonself

Centrioles: active players or passengers during mitosis?

Centrioles are cylinders made of nine microtubule (MT) triplets present in many eukaryotes. Early studies, where centrosomes were seen at the poles of the mitotic spindle led to their coining as “the organ for cell division”. However, a variety of subsequent observational and functional studies showed that centrosomes might not always be essential for mitosis. Here we review the arguments in this debate. We describe the centriole structure and its distribution in the eukaryotic tree of life and clarify its role in the organization of the centrosome and cilia, with an historical perspective. An important aspect of the debate addressed in this review is how centrioles are inherited and the role of the spindle in this process. In particular, germline inheritance of centrosomes, such as their de novo formation in parthenogenetic species, poses many interesting questions. We finish by discussing the most likely functions of centrioles and laying out new research avenues

Systematic Review of Potential Health Risks Posed by Pharmaceutical, Occupational and Consumer Exposures to Metallic and Nanoscale Aluminum, Aluminum Oxides, Aluminum Hydroxide and Its Soluble Salts

Aluminum (Al) is a ubiquitous substance encountered both naturally (as the third most abundant element) and intentionally (used in water, foods, pharmaceuticals, and vaccines); it is also present in ambient and occupational airborne particulates. Existing data underscore the importance of Al physical and chemical forms in relation to its uptake, accumulation, and systemic bioavailability. The present review represents a systematic examination of the peer-reviewed literature on the adverse health effects of Al materials published since a previous critical evaluation compiled by Krewski et al. (2007). Challenges encountered in carrying out the present review reflected the experimental use of different physical and chemical Al forms, different routes of administration, and different target organs in relation to the magnitude, frequency, and duration of exposure. Wide variations in diet can result in Al intakes that are often higher than the World Health Organization provisional tolerable weekly intake (PTWI), which is based on studies with Al citrate. Comparing daily dietary Al exposures on the basis of “total Al”assumes that gastrointestinal bioavailability for all dietary Al forms is equivalent to that for Al citrate, an approach that requires validation. Current occupational exposure limits (OELs) for identical Al substances vary as much as 15-fold. The toxicity of different Al forms depends in large measure on their physical behavior and relative solubility in water. The toxicity of soluble Al forms depends upon the delivered dose of Al+ 3 to target tissues. Trivalent Al reacts with water to produce bidentate superoxide coordination spheres [Al(O2)(H2O4)+ 2 and Al(H2O)6 + 3] that after complexation with O2•−, generate Al superoxides [Al(O2•)](H2O5)]+ 2. Semireduced AlO2• radicals deplete mitochondrial Fe and promote generation of H2O2, O2 • − and OH•. Thus, it is the Al+ 3-induced formation of oxygen radicals that accounts for the oxidative damage that leads to intrinsic apoptosis. In contrast, the toxicity of the insoluble Al oxides depends primarily on their behavior as particulates. Aluminum has been held responsible for human morbidity and mortality, but there is no consistent and convincing evidence to associate the Al found in food and drinking water at the doses and chemical forms presently consumed by people living in North America and Western Europe with increased risk for Alzheimer\u27s disease (AD). Neither is there clear evidence to show use of Al-containing underarm antiperspirants or cosmetics increases the risk of AD or breast cancer. Metallic Al, its oxides, and common Al salts have not been shown to be either genotoxic or carcinogenic. Aluminum exposures during neonatal and pediatric parenteral nutrition (PN) can impair bone mineralization and delay neurological development. Adverse effects to vaccines with Al adjuvants have occurred; however, recent controlled trials found that the immunologic response to certain vaccines with Al adjuvants was no greater, and in some cases less than, that after identical vaccination without Al adjuvants. The scientific literature on the adverse health effects of Al is extensive. Health risk assessments for Al must take into account individual co-factors (e.g., age, renal function, diet, gastric pH). Conclusions from the current review point to the need for refinement of the PTWI, reduction of Al contamination in PN solutions, justification for routine addition of Al to vaccines, and harmonization of OELs for Al substances

Development and characterization of phytosterol-enriched oil microcapsules for foodstuff application

Phytosterols are lipophilic compounds contained in plants and have several biological activities. The use of phytosterols in food fortification is hampered due to their high melting temperature, chalky taste, and low solubility in an aqueous system. Also, phytosterols are easily oxidized and are poorly absorbed by the human body. Formulation engineering coupled with microencapsulation could be used to overcome these problems. The aim of this study was to investigate the feasibility of encapsulating soybean oil enriched with phytosterols by spray-drying using ternary mixtures of health-promoting ingredients, whey protein isolate (WPI), inulin, and chitosan as carrier agents. The effect of different formulations and spray-drying conditions on the microencapsules properties, encapsulation efficiency, surface oil content, and oxidation stability were studied. It was found that spherical WPI-inulin-chitosan phytosterol-enriched soybean oil microcapsules with an average size below 50 μm could be produced with good encapsulation efficiency (85%), acceptable level of surface oil (11%), and water activity (0.2–0.4) that meet industrial requirements. However, the microcapsules showed very low oxidation stability with peroxide values reaching 101.7 meq O2/kg of oil just after production, and further investigations and optimization are required before any industrial application of this encapsulated system

Quality control for next-generation liquefaction case histories

The Next-Generation Liquefaction (NGL) database is an open-source, global database of liquefaction and non-ground failure case-histories. The database is part of a multi-year research effort with the main goal of developing improved procedures to evaluate liquefaction susceptibility, triggering, and consequences. In NGL, a case-history is defined as the intersection of three components: (1) a site, (2) an earthquake event, and (3) post-earthquake observations. The NGL database hosts case-histories used to develop existing liquefaction models, as well as new data derived from recent earthquakes such as the 2010-2011 Canterbury earthquake sequence, the 2011 Tohoku-Oki earthquake, and the 2012 Emilia earthquake. The database also hosts lateral spread case-histories, and a substantial number of liquefaction sites characterized by the presence of co-located recording stations. All of the data present in the NGL database are reviewed by the NGL Database Working Group. The NGL formal vetting process is described for an example case-history

A Hybrid Approach for the Sentiment Analysis of Turkish Twitter Data

Social media is now playing an important role in influencing people’s sentiments. It also helps analyze how people, particularly consumers, feel about a particular topic, product or an idea. One of the recent social media platforms that people use to express their thoughts is Twitter. Due to the fact that Turkish is an agglutinative language, its complexity makes it difficult for people to perform sentiment analysis. In this study, a sum of 13K Turkish tweets has been collected from Twitter using the Twitter API and their sentiments are being analyzed using machine learning classifiers. Random forests and support vector machines are the two kinds of classifiers that are adopted. Preprocessing methods were applied on the obtained data to remove links, numbers, punctuations and un-meaningful characters. After the preprocessing phase, unsuitable data have been removed and 10,500 out of the 13K downloaded dataset are taken as the main dataset. The datasets are classified to be either positive, negative or neutral based on their contents. The main dataset was converted to a stemmed dataset by removing stopwords, applying tokenization and also applying stemming on the dataset, respectively. A portion of 3,000 and 10,500 of the stemmed data with equal distribution from each class has been identified as the first dataset and second dataset to be used in the testing phase. Experimental results have shown that while support vector machines perform better when it comes to classifying negative and neutral stemmed data, random forests algorithm perform better in classifying positive stemmed data and thus a hybrid approach which consists of the hierarchical combination of random forest and support vector machines has also been developed and used to find the result of the data. Finally, the applied methodologies have been tested on both the first and the second dataset. It has been observed that while both support vector machines and random forest algorithms could not achieve an accuracy of up to 77% on the first and 72% on the second dataset, the developed hybrid approach achieve an accuracy of up to 86.4% and 82.8% on the first and second dataset, respectively. © 2020, Springer Nature Switzerland AG