scholarly journals Local topology and bifurcation hot-spots in proteins with SARS-CoV-2 spike protein as an example

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0257886
Author(s):  
Xubiao Peng ◽  
Antti J. Niemi
Keyword(s):  
Hot Spots ◽  
Biological Function ◽  
Hot Spot ◽  
Data Bank ◽  
Spike Protein ◽  
Protein Backbone ◽  
Topological Methods ◽  
Expected Outcome ◽  
Protein Research ◽  
Local Topology

Novel topological methods are introduced to protein research. The aim is to identify hot-spot sites where a bifurcation can alter the local topology of the protein backbone. Since the shape of a protein is intimately related to its biological function, a substitution that causes a bifurcation should have an enhanced capacity to change the protein’s function. The methodology applies to any protein but it is developed with the SARS-CoV-2 spike protein as a timely example. First, topological criteria are introduced to identify and classify potential bifurcation hot-spot sites along the protein backbone. Then, the expected outcome of asubstitution, if it occurs, is estimated for a general class of hot-spots, using a comparative analysis of the surrounding backbone segments. The analysis combines the statistics of structurally commensurate amino acid fragments in the Protein Data Bank with general stereochemical considerations. It is observed that the notorious D614G substitution of the spike protein is a good example of a bifurcation hot-spot. A number of topologically similar examples are then analyzed in detail, some of them are even better candidates for a bifurcation hot-spot than D614G. The local topology of the more recently observed N501Y substitution is also inspected, and it is found that this site is proximal to a different kind of local topology changing bifurcation.

scholarly journals Bifurcations and mutation hot-spots in SARS-CoV-2 spike protein

2020 ◽  
Author(s):  
Xubiao Peng ◽  
Antti J. Niemi
Keyword(s):  
Hot Spots ◽  
Large Scale ◽  
Hot Spot ◽  
Data Bank ◽  
High Rate ◽  
Spike Protein ◽  
Novel Approach ◽  
Promising Target ◽  
Protein Research ◽  
Local Topology

AbstractThe spike protein is a most promising target for the development of vaccines and therapeutic drugs against the SARS-CoV-2 infection. But the apparently high rate of mutations makes the development of antiviral inhibitors a challenge. Here a methodology is presented to try and predict mutation hot-spot sites, where a small local change in spike protein’s structure can lead to a large scale conformational effect, and change the protein’s biological function. The methodology starts with a systematic physics based investigation of the spike protein’s Cα backbone in terms of its local topology. This topological investigation is then combined with a statistical examination of the pertinent backbone fragments; the statistical analysis builds on a comparison with high resolution Protein Data Bank (PDB) structures. Putative mutation hot-spot sites are identified as proximal sites to bifurcation points that can change the local topology of the Cα backbone in an essential manner. The likely outcome of a mutation, if it indeed occurs, is predicted by a comparison with residues in best-matching PDB fragments together with general stereochemical considerations. The detailed methodology is developed using the already observed D614G mutation as an example. This is a mutation that could have been correctly predicted by the present approach. Several additional examples of potential hot-spot residues are identified and analyzed in detail, some of them are found to be even better candidates for a mutation hot-spot than D614G.Significance statementA novel approach to predict mutation hot-spots in SARS-CoV-2 spike protein is presented. The approach introduces new topology based techniques to biophysical protein research. For a proof-of-concept the approach is described with the notorious D614G mutation of the spike protein as an example. It is shown that this mutation could have been correctly predicted by the present methods. Several additional mutation hot-spots are then identified and a number of them are shown to be topologically similar to the observed D614G mutation. The methodology can be used to design effective drugs and antibodies against the spike protein. It can also be employed more generally, whenever one needs to search for and identify mutation hot-spots in a protein.

Spatial Hotspot Analysis of Bucharest’s Urban Heat Island (UHI) Using Modis Data

2018 ◽  
Vol 18 (1) ◽  
pp. 14-22 ◽  
Author(s):  
Georgiana Grigoraș ◽  
Bogdan Urițescu
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Hot Spots ◽  
Land Surface ◽  
Hot Spot ◽  
Monitoring Network ◽  
Residential Areas ◽  
Hotspot Analysis ◽  
The City

Abstract The aim of the study is to find the relationship between the land surface temperature and air temperature and to determine the hot spots in the urban area of Bucharest, the capital of Romania. The analysis was based on images from both moderate-resolution imaging spectroradiometer (MODIS), located on both Terra and Aqua platforms, as well as on data recorded by the four automatic weather stations existing in the endowment of The National Air Quality Monitoring Network, from the summer of 2017. Correlation coefficients between land surface temperature and air temperature were higher at night (0.8-0.87) and slightly lower during the day (0.71-0.77). After the validation of satellite data with in-situ temperature measurements, the hot spots in the metropolitan area of Bucharest were identified using Getis-Ord spatial statistics analysis. It has been achieved that the “very hot” areas are grouped in the center of the city and along the main traffic streets and dense residential areas. During the day the "very hot spots” represent 33.2% of the city's surface, and during the night 31.6%. The area where the mentioned spots persist, falls into the "very hot spot" category both day and night, it represents 27.1% of the city’s surface and it is mainly represented by the city center.

The family Orthotrichaceae (Bryophyta) in flora of Russia: results of revision and biogeographical review

2018 ◽  
Vol 52 (2) ◽  
pp. 519-534 ◽  
Author(s):  
V. E. Fedosov
Keyword(s):  
Hot Spots ◽  
Latitudinal Gradient ◽  
Hot Spot ◽  
Spatial Differentiation ◽  
Taxonomic Composition ◽  
Undescribed Species ◽  
Longitudinal Gradient ◽  
Biogeographic Pattern ◽  
The Family ◽  
North Pacific Region

Recent studies on Orthotrichoid mosses in Russia are summarized genus by genus. Orthotrichum furcatum Otnyukova is synonymized with Nyholmiella obtusifolia. Orthotrichum vittii is excluded from the Russian moss flora. Description of O. dagestanicum is amended. Fifty four currently recognized species from 9 genera of the Orthotrichaceae are presently known to occur in Russia; list of species with common synonyms and brief review of distribution in Russia is presented. Numerous problematic specimens with unresolved taxonomy were omitted for future. Revealed taxonomical inconsistencies in the genera Zygodon, Ulota, Lewinskya, Nyholmiella, Orthotrichum are briefly discussed. Main regularities of spatial differentiation of the family Orthotrichaceae in Russia are considered. Recently presented novelties contribute to the certain biogeographic pattern, indicating three different centers of diversity of the family, changing along longitudinal gradient. Unlike European one, continental Asian diversity of Orthotrichaceae is still poorly known, the Siberian specimens which were previously referred to European species in most cases were found to represent other, poorly known or undescribed species. North Pacific Region houses peculiar and poorly understood hot spot of diversity of Orthotrichoid mosses. Thus, these hot spots are obligatory to be sampled in course of revisions of particular groups, since they likely comprise under-recorded cryptic- or semi-cryptic species. Latitudinal gradient also contributes to the spatial differentiation of the revealed taxonomic composition of Orthotrichaceae.

scholarly journals Family Practices and Temporality at Breakfast: Hot Spots, Convenience and Care

Sociology ◽  
2021 ◽  
pp. 003803852110155
Author(s):  
Daniela Pirani ◽  
Vicki Harman ◽  
Benedetta Cappellini
Keyword(s):  
Hot Spots ◽  
Hot Spot ◽  
Family Meals ◽  
Personal Integrity ◽  
Structured Interviews ◽  
Time Saving ◽  
Family Time ◽  
Dominant Feature ◽  
Family Practices ◽  
Cold Spots

Drawing on 34 semi-structured interviews, this study investigates the temporality of family practices taking place in the hot spot. It does so by looking at how breakfast is inserted in the economy of family time in Italy. Our data show that breakfast, contrary to other meals, allows the adoption of more individualised and asynchronous practices, hinged on the consumption of convenience products. These time-saving strategies are normalised as part of doing family. Although the existing literature suggests that convenience and care are in opposition, and consumers of convenience products can experience anxiety and a lack of personal integrity, such features were not a dominant feature of our participants’ accounts. These findings suggest that the dichotomies of hot/cold spots and care/convenience are not always experienced in opposition when embedded within family practices. Hence, this study furthers understandings of family meals, temporality and the distinction between hot and cold spots.

Investigation of On-Chip Hot Spot Cooling Using Microchannel Heat Sink

2013 ◽  
Vol 455 ◽  
pp. 466-469
Author(s):  
Yun Chuan Wu ◽  
Shang Long Xu ◽  
Chao Wang
Keyword(s):  
Heat Flux ◽  
Heat Sink ◽  
Hot Spots ◽  
Hot Spot ◽  
High Heat ◽  
High Heat Flux ◽  
Microchannel Heat Sink ◽  
Three Dimensional Model ◽  
Spot Cooling ◽  
On Chip

With the increase of performance demands, the nonuniformity of on-chip power dissipation becomes greater, causing localized high heat flux hot spots that can degrade the processor performance and reliability. In this paper, a three-dimensional model of the copper microchannel heat sink, with hot spot heating and background heating on the back, was developed and used for numerical simulation to predict the hot spot cooling performance. The hot spot is cooled by localized cross channels. The pressure drop, thermal resistance and effects of hot spot heat flux and fluid flow velocity on the cooling of on-chip hot spots, are investigated in detail.

scholarly journals Distortion Effects in Equal Area Unit Maps

2021 ◽  
Author(s):  
Jochen Schiewe
Keyword(s):  
Hot Spots ◽  
Extreme Values ◽  
Generation Process ◽  
Equal Area ◽  
Topological Relationships ◽  
Area Unit ◽  
Task Oriented ◽  
Local Topology ◽  
Selection Of ◽  
Local Extreme

AbstractMaps that correctly represent the geographic size and shape of regions, taking into account scaling and generalization, have the disadvantage that small regions can easily be overlooked or not seen at all. Hence, for some map use tasks where small regions are of importance, alternative map types are needed. One option is the so-called equal area unit maps (EAUMs), where every enumeration unit has the same area size, possibly also the same basic shape such as squares or hexagons. The geometrical distortion of EAUMs, however, leads to a more difficult search for regions as well as a falsification of topological relationships and spatial patterns. To describe these distortions, a set of analytical measures is proposed. But it turns out that the expressiveness of these measures is rather limited. To better understand and to model the influence of distortions, two user studies were conducted. The study on the search in EAUMs (also with the aim of reconstruct the search strategies of the users) revealed how important it is to consider the local topology (e.g. corner or border positions of regions) during the generation process. With regard to pattern identification, it could be shown that EAUMs significantly increase the detection rate of local extreme values. On the other hand, global lateral gradients or geostatistical hot spots often get blurred or even lost. As a consequence, a task-oriented selection of map types and further developments are recommended.

scholarly journals Deletion Formation Between the Two Salmonella typhimurium Flagellin Genes Encoded on the Mini F Plasmid: Escherichia coli ssb Alleles Enhance Deletion Rates and Change Hot-Spot Preference for Deletion Endpoints

Genetics ◽  
1997 ◽  
Vol 145 (3) ◽  
pp. 563-572 ◽  
Author(s):  
Takafumi Mukaihara ◽  
Masatoshi Enomoto
Keyword(s):  
Escherichia Coli ◽  
Salmonella Typhimurium ◽  
Hot Spots ◽  
Hot Spot ◽  
Direct Repeats ◽  
Replication Slippage ◽  
Detection Systems ◽  
Deletion Formation ◽  
Homologous Sequences ◽  
Deletion Detection

Deletion formation between the 5′-mostly homologous sequences and between the 3′-homeologous sequences of the two Salmonella typhimurium flagellin genes was examined using plasmid-based deletion-detection systems in various Escherichia coli genetic backgrounds. Deletions in plasmid pLC103 occur between the 5′ sequences, but not between the 3′ sequences, in both RecA-independent and RecA-dependent ways. Because the former is predominant, deletion formation in a recA background depends on the length of homologous sequences between the two genes. Deletion rates were enhanced 30- to 50-fold by the mismatch repair defects, mutS, mutL and uvrD, and 250-fold by the ssb-3 allele, but the effect of the mismatch defects was canceled by the ΔrecA allele. Rates of the deletion between the 3′ sequences in plasmid pLC107 were enhanced 17- to 130-fold by ssb alleles, but not by other alleles. For deletions in pLC107, 96% of the endpoints in the recA+ background and 88% in ΔrecA were in the two hot spots of the 60- and 33-nucleotide (nt) homologous sequences, whereas in the ssb-3 background >50% of the endpoints were in four- to 14-nt direct repeats dispersed in the entire 3′ sequences. The deletion formation between the homeologous sequences is RecA-independent but depends on the length of consecutive homologies. The mutant ssb allele lowers this dependency and results in the increase in deletion rates. Roles of mutant SSB are discussed with relation to misalignment in replication slippage.

scholarly journals Does Entrepreneurship Contribute to Innovation Performance When Considering Spatial Spillover Effects? Evidence From the Automobile Industrial Cluster in China

SAGE Open ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 215824402098299
Author(s):  
Haishi Li ◽  
Xiangyi Xu ◽  
Shuaishuai Li
Keyword(s):  
Automobile Industry ◽  
Hot Spots ◽  
Hot Spot ◽  
Empirical Support ◽  
Temporal Patterns ◽  
Spillover Effects ◽  
Industrial Clusters ◽  
Innovation Performance ◽  
Spatial Spillover ◽  
Spatio Temporal

Entrepreneurship, as one of the important factors to promote industrial innovation, is closely related to the development of the regional economy. Based on the methods of Kernel density and standard deviation ellipse, this article presents the spatio-temporal patterns of entrepreneurship and innovation performance. The article also examines the spatial spillover mechanism of entrepreneurship on innovation performance by establishing spatial Durbin models. The heterogeneous results of the spatial regression models in six clusters are also discussed. The final results show that the spatio-temporal patterns of entrepreneurship are gradually presenting three major hot spots and two secondary hot spots while the spatio-temporal patterns of innovation performance are presenting four major hot spots and a secondary hot spot; the spatial distribution of both entrepreneurship and innovation performance are changing regularly; the spillover effects of entrepreneurship and innovation performance are both significant; the spatial spillover mechanisms in six automobile industrial clusters are different. The results can provide empirical support for decision-making in the automobile industry in China in the future.

scholarly journals Prediction of Hourly Effect of Land Use on Crime

2018 ◽  
Vol 8 (1) ◽  
pp. 16 ◽  
Author(s):  
Irina Matijosaitiene ◽  
Peng Zhao ◽  
Sylvain Jaume ◽  
Joseph Gilkey Jr
Keyword(s):  
Machine Learning ◽  
Land Use ◽  
Logistic Regression ◽  
Hot Spots ◽  
Urban Areas ◽  
Prediction Models ◽  
Hot Spot ◽  
Time Range ◽  
Land Uses ◽  
Police Departments

Predicting the exact urban places where crime is most likely to occur is one of the greatest interests for Police Departments. Therefore, the goal of the research presented in this paper is to identify specific urban areas where a crime could happen in Manhattan, NY for every hour of a day. The outputs from this research are the following: (i) predicted land uses that generates the top three most committed crimes in Manhattan, by using machine learning (random forest and logistic regression), (ii) identifying the exact hours when most of the assaults are committed, together with hot spots during these hours, by applying time series and hot spot analysis, (iii) built hourly prediction models for assaults based on the land use, by deploying logistic regression. Assault, as a physical attack on someone, according to criminal law, is identified as the third most committed crime in Manhattan. Land use (residential, commercial, recreational, mixed use etc.) is assigned to every area or lot in Manhattan, determining the actual use or activities within each particular lot. While plotting assaults on the map for every hour, this investigation has identified that the hot spots where assaults occur were ‘moving’ and not confined to specific lots within Manhattan. This raises a number of questions: Why are hot spots of assaults not static in an urban environment? What makes them ‘move’—is it a particular urban pattern? Is the ‘movement’ of hot spots related to human activities during the day and night? Answering these questions helps to build the initial frame for assault prediction within every hour of a day. Knowing a specific land use vulnerability to assault during each exact hour can assist the police departments to allocate forces during those hours in risky areas. For the analysis, the study is using two datasets: a crime dataset with geographical locations of crime, date and time, and a geographic dataset about land uses with land use codes for every lot, each obtained from open databases. The study joins two datasets based on the spatial location and classifies data into 24 classes, based on the time range when the assault occurred. Machine learning methods reveal the effect of land uses on larceny, harassment and assault, the three most committed crimes in Manhattan. Finally, logistic regression provides hourly prediction models and unveils the type of land use where assaults could occur during each hour for both day and night.

Thermal Decomposition Conditions of Emulsion Matrix in the Emulsifier

2014 ◽  
Vol 1082 ◽  
pp. 387-390
Author(s):  
Hui Sheng Zhou ◽  
Xing Hua Xie ◽  
Kang Xu
Keyword(s):  
Thermal Decomposition ◽  
Ammonium Nitrate ◽  
Hot Spots ◽  
Hot Spot ◽  
Decomposition Mechanism ◽  
Heat Accumulation ◽  
Emulsion Explosives ◽  
Starting Point ◽  
Emulsion Matrix

The main background was the "3.11" accident in this paper. The starting point was based on the experts’ conclusions of investigation and analysis in the accident. Combining the decomposition mechanism of ammonium nitrate in the emulsion explosives and the lessons from the production of emulsion explosives explosion, the conditions of the emulsion explosives (matrix) thermal decomposition in the emulsifier are given that are the formation of hot spot and the accumulation of heat. Then the factors of hot spots generated in the production of emulsion explosives and the occurred conditions of the heat accumulation are analyzed and summarized.

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