AIM: To investigate the expression of mast cell tryptase and carboxypeptidase A in drug-related fatal anaphylaxis.METHODS: The expression of mast cell tryptase and carboxypeptidase A in 15 autopsy cases of drugrelated...AIM: To investigate the expression of mast cell tryptase and carboxypeptidase A in drug-related fatal anaphylaxis.METHODS: The expression of mast cell tryptase and carboxypeptidase A in 15 autopsy cases of drugrelated fatal anaphylaxis and 20 normal autopsy cases were detected. First, the expression of mast cell tryptase was determined in stomach, jejunum, lung, heart, and larynx by immunofluorescence. Different tissues were removed and fixed in paraformaldehyde solution, then paraffin sections were prepared for immunofluorescence. Using specific mast cell tryptase and carboxypeptidase A antibodies, the expression of tryptase and carboxypeptidase A in gastroenterology tract and other tissues were observed using fluorescent microscopy. The postmortem serum and pericardial fluid were collected from drug-related fatal anaphylaxis and normal autopsy cases. The level of mast cell tryptase and carboxypeptidase A in postmortem serum and pericardial fluid were measured using fluor enzyme linked immunosorbent assay(FEIA) and enzyme linked immunosorbent assay(ELISA) assay. The expression of mast cell tryptase and carboxypeptidase A was analyzed in drug-related fatal anaphylaxis cases and compared to normal autopsy cases.RESULTS: The expression of carboxypeptidase A was less in the gastroenterology tract and other tissues from anaphylaxis-related death cadavers than normal controls. Immunofluorescence revealed that tryptase expression was significantly increased in multiple organs, especially the gastrointestinal tract, from anaphylaxis-related death cadavers compared to normal autopsy cases(46.67 ± 11.11 vs 4.88 ± 1.56 in stomach, 48.89 ± 11.02 vs 5.21 ± 1.34 in jejunum, 33.72 ± 5.76 vs 1.30 ± 1.02 in lung, 40.08 ± 7.56 vs 1.67 ± 1.03 in larynx, 7.11 ± 5.67 vs 1.10 ± 0.77 in heart, P < 0.05). Tryptase levels, as measured with FEIA, were significantly increased in both sera(43.50 ± 0.48 μg/L vs 5.40 ± 0.36 μg/L, P < 0.05) and pericardial fluid(28.64 ± 0.32 μg/L vs 4.60 ± 0.48 μg/L, P < 0.05) from the anaphylaxis group in comparison with the control group. As measured by ELISA, the concentration of carboxypeptidase A was also increased more than 2-fold in the anaphylaxis group compared to control(8.99 ± 3.91 ng/m L vs 3.25 ± 2.30 ng/m L in serum, 4.34 ± 2.41 ng/m L vs 1.43 ± 0.58 ng/m L in pericardial fluid, P < 0.05).CONCLUSION: Detection of both mast cell tryptase and carboxypeptidase A could improve the forensic identification of drug-related fatal anaphylaxis.展开更多
Patients with type II diabetes mellitus(T2DM)and hypertension(HTN)are at increased threat for long experiencing various problems related to medicine as they frequently received different medications for managing their...Patients with type II diabetes mellitus(T2DM)and hypertension(HTN)are at increased threat for long experiencing various problems related to medicine as they frequently received different medications for managing their condition.Recently,there were no studies done locally on drug-related problems(DRPs)among T2DM patients with HTN.Thus,this study aims to assess the DRPs among T2DM patients with HTN admitted at Kibuye Referral Hospital(KRH).DRPs were drug safety problems,drug effectiveness problems and other drug problems.Methods:A retrospective cross-sectional study involved patients'files with T2DM and HTN,who were admitted at KRH from January 2013 to December 2017.The identification and classification of DRPs were based on pharmaceutical care network Europe(PCNE)classification system version 8.02.A simple random sampling technique was used to choose study participants from the target population.Data that met inclusion and exclusion criteria were analyzed using STATA version 13.The Fisher exact test(bivariate analysis)and logistic regression(multivariate)were used to test association and p-value≤0.05 was considered as statistically significant.An adjusted odd ratio(AOR)with a confidence interval(CI)of 95% was determined using binary logistic regression.Results:Findings revealed that the prevalence of DRPs was 81.29%(313/385)and most of them each patient had at least two DRPs(69.05%).The patients aged above 55 years old were more likely to develop DRPs than those with age below 35 years(AOR=1.2;P=0.02;95%CI:0.2-2.3).Nevertheless,there was no significant association between DRPs and middle age(between 35 and 54 age of old).The patients who consumed more than or equal to 5 drugs were 2.4 times more likely to develop DRPs than those who took the number of medicines less than 5(AOR=15.4;P<0.001;95%CI:8.8-26.8).Also,traditional medicines use(AOR=1.9;P=0.016;95%CI:1.1-3.5)and having drug-related complication(AOR=2.4;P<0.001;95%CI:1.9-3)had shown significant associations.The total causes of DRPs identified were 1626 and most causes of DRPs were arisen from drug use(45.01%)and prescribing(37.83%).The drug/dose selections were the most frequent causes of DRPs(36.97%).Conclusion:Since the prevalence of DRPs were relatively high,various factors influencing DRPs were established and most causes of DRPs were arising from drug use&drug prescribing among T2DM patients with HTN.Early detection needed to enhance patient’s life quality.Conducting studies in other hospitals needed to establish the national planning of DRPs to eradicate DRPs among patients T2DM with HTN.展开更多
The increasing rate of insecurity in Nigeria, especially the southwest requires a paradigm shift from popular approach to crime hotspots detection. This study employed geospatial technologies to integrate spatio-tempo...The increasing rate of insecurity in Nigeria, especially the southwest requires a paradigm shift from popular approach to crime hotspots detection. This study employed geospatial technologies to integrate spatio-temporal crime, social media and field observation data from the communities in all the six states in the southwest to develop crime hotspots that can serve as preliminary information to assist in allocating resources for crime control and prevention. Historical crime data from January 1972 to April, 2021 were compiled and updated with rigorous field survey in September, 2021. The field data were encoded, input to the SPSS 17 and analyzed using descriptive statistics and multivariate analysis. A total 936 crime locations data were geolocated and exported to ArcGIS 10.5 for spatial mapping using point map operation and further imported to e-Spatial web-based and QGIS for the generation of hotspot map using heatmap tool. The results revealed that armed robbery, assassination and cultism were more pronounced in Lagos and Ogun States. Similarly, high incidences of farmers/herdsmen conflicts are observed in Oyo and Osun States. Increasing incidences of kidnapping are common in all the south-western states but very prominent in Ondo, Lagos and Oyo States. Most of the violent crime incidents took place along the highways, with forests being their hideouts. Violent crimes are dominantly caused by high rate of unemployment while farmer/herdsmen conflicts were majorly triggered by the scarcity of grazing fields and destruction of arable crops. The conflicts have resulted in the increasing cases of rape and disruption of social group, intake of hard drugs, cult-related activities, low income and revenue generation, and displacement of farmers and infrastructural damages. The study advocates regular retraining and equipping of security agents, establishment of cattle ranch, and installation of sophisticated IP Camera at the crime hotspots to assist in real-time crime monitoring and management.展开更多
Every day,the media reports tons of crimes that are considered by a large number of users and accumulate on a regular basis.Crime news exists on the Internet in unstructured formats such as books,websites,documents,an...Every day,the media reports tons of crimes that are considered by a large number of users and accumulate on a regular basis.Crime news exists on the Internet in unstructured formats such as books,websites,documents,and journals.From such homogeneous data,it is very challenging to extract relevant information which is a time-consuming and critical task for the public and law enforcement agencies.Keyword-based Information Retrieval(IR)systems rely on statistics to retrieve results,making it difficult to obtain relevant results.They are unable to understandthe user’s query and thus facewordmismatchesdue to context changes andthe inevitable semanticsof a given word.Therefore,such datasets need to be organized in a structured configuration,with the goal of efficiently manipulating the data while respecting the semantics of the data.An ontological semantic IR systemis needed that can find the right investigative information and find important clues to solve criminal cases.The semantic system retrieves information in view of the similarity of the semantics among indexed data and user queries.In this paper,we develop anontology-based semantic IRsystemthat leverages the latest semantic technologies including resource description framework(RDF),semantic protocol and RDF query language(SPARQL),semantic web rule language(SWRL),and web ontology language(OWL).We have conducted two experiments.In the first experiment,we implemented a keyword-based textual IR systemusing Apache Lucene.In the second experiment,we implemented a semantic systemthat uses ontology to store the data and retrieve precise results with high accuracy using SPARQL queries.The keyword-based system has filtered results with 51%accuracy,while the semantic system has filtered results with 95%accuracy,leading to significant improvements in the field and opening up new horizons for researchers.展开更多
The objective of crime prediction,one of the most important technologies in social computing,is to extract useful information from many existing criminal records to predict the next process-related crime.It can aid th...The objective of crime prediction,one of the most important technologies in social computing,is to extract useful information from many existing criminal records to predict the next process-related crime.It can aid the police in obtaining criminal information and warn the public to be vigilant in certain areas.With the rapid growth of big data,the Internet of Things,and other technologies,as well as the increasing use of artificial intelligence in forecasting models,crime prediction models based on deep learning techniques are accelerating.Therefore,it is necessary to classify the existing crime prediction algorithms and compare in depth the attributes and conditions that play an essential role in the analysis of crime prediction algorithms.Existing crime prediction methods can be roughly divided into two categories:those based on conventional machine learning and those based on contemporary deep learning.This survey analyses the fundamental theories and procedures.The most frequently used data sets are then enumerated,and the fundamental procedures of various algorithms are also analyzed in this paper.In light of the insufficient scale of existing data in this field,the ambiguity of data types used to predict crimes,and the absence of public data sets that have a significant impact on the research of algorithm models,this survey proposes the construction of a machine learning-based big data research model to address these issues.Future researchers who will enter this field are provided with a guide to the direction of future research development.展开更多
The study examines the Spatial Pattern and Distribution of Crime in Suleja LGA, Niger State, Nigeria. The study used GIS and statistical methods to analyse the pattern and distribution of crime incidence in the study ...The study examines the Spatial Pattern and Distribution of Crime in Suleja LGA, Niger State, Nigeria. The study used GIS and statistical methods to analyse the pattern and distribution of crime incidence in the study area. The records of each crime incidence were geocoded. Microsoft Excel was used to collate and organise the crime entries before they were imported into the ArcGIS Pro 2.0 environment. A geodatabase was created where the spatial and aspatial data were encoded and geospatial analysis was performed. The study reveals that the crime distribution pattern is generally clustered with a Global Moran’s I index of 0.097, a Z-score of 1.87, and a P-value < 0.06. Furthermore, the study reveals that armed robbery (61), kidnapping (40), car theft (33), culpable homicide (31), rape (29), and robbery (13) cases rank the highest in crime rate. Equally, findings of the study show that Chaza, Kwamba, Madalla, Suleja central, and Gaboda are the major crime hotspot zones at 90% confidence, as analysed using the Getis-Ord Gi* (Hot spot analysis) spatial statistics tool in ArcGIS Pro 2.0. The research therefore recommends that more effort be put into fighting crime, especially in areas where there are low-security formations, as they mostly have the highest record of crimes committed. Also, the patrol units should be equipped with GPS for better surveillance and real-time tracking of criminal activities.展开更多
基金Supported by the National Natural Science Foundation of ChinaNo.81172905+1 种基金Shanxi Province Science Foundation for YouthsNo.2012021032-2
文摘AIM: To investigate the expression of mast cell tryptase and carboxypeptidase A in drug-related fatal anaphylaxis.METHODS: The expression of mast cell tryptase and carboxypeptidase A in 15 autopsy cases of drugrelated fatal anaphylaxis and 20 normal autopsy cases were detected. First, the expression of mast cell tryptase was determined in stomach, jejunum, lung, heart, and larynx by immunofluorescence. Different tissues were removed and fixed in paraformaldehyde solution, then paraffin sections were prepared for immunofluorescence. Using specific mast cell tryptase and carboxypeptidase A antibodies, the expression of tryptase and carboxypeptidase A in gastroenterology tract and other tissues were observed using fluorescent microscopy. The postmortem serum and pericardial fluid were collected from drug-related fatal anaphylaxis and normal autopsy cases. The level of mast cell tryptase and carboxypeptidase A in postmortem serum and pericardial fluid were measured using fluor enzyme linked immunosorbent assay(FEIA) and enzyme linked immunosorbent assay(ELISA) assay. The expression of mast cell tryptase and carboxypeptidase A was analyzed in drug-related fatal anaphylaxis cases and compared to normal autopsy cases.RESULTS: The expression of carboxypeptidase A was less in the gastroenterology tract and other tissues from anaphylaxis-related death cadavers than normal controls. Immunofluorescence revealed that tryptase expression was significantly increased in multiple organs, especially the gastrointestinal tract, from anaphylaxis-related death cadavers compared to normal autopsy cases(46.67 ± 11.11 vs 4.88 ± 1.56 in stomach, 48.89 ± 11.02 vs 5.21 ± 1.34 in jejunum, 33.72 ± 5.76 vs 1.30 ± 1.02 in lung, 40.08 ± 7.56 vs 1.67 ± 1.03 in larynx, 7.11 ± 5.67 vs 1.10 ± 0.77 in heart, P < 0.05). Tryptase levels, as measured with FEIA, were significantly increased in both sera(43.50 ± 0.48 μg/L vs 5.40 ± 0.36 μg/L, P < 0.05) and pericardial fluid(28.64 ± 0.32 μg/L vs 4.60 ± 0.48 μg/L, P < 0.05) from the anaphylaxis group in comparison with the control group. As measured by ELISA, the concentration of carboxypeptidase A was also increased more than 2-fold in the anaphylaxis group compared to control(8.99 ± 3.91 ng/m L vs 3.25 ± 2.30 ng/m L in serum, 4.34 ± 2.41 ng/m L vs 1.43 ± 0.58 ng/m L in pericardial fluid, P < 0.05).CONCLUSION: Detection of both mast cell tryptase and carboxypeptidase A could improve the forensic identification of drug-related fatal anaphylaxis.
文摘Patients with type II diabetes mellitus(T2DM)and hypertension(HTN)are at increased threat for long experiencing various problems related to medicine as they frequently received different medications for managing their condition.Recently,there were no studies done locally on drug-related problems(DRPs)among T2DM patients with HTN.Thus,this study aims to assess the DRPs among T2DM patients with HTN admitted at Kibuye Referral Hospital(KRH).DRPs were drug safety problems,drug effectiveness problems and other drug problems.Methods:A retrospective cross-sectional study involved patients'files with T2DM and HTN,who were admitted at KRH from January 2013 to December 2017.The identification and classification of DRPs were based on pharmaceutical care network Europe(PCNE)classification system version 8.02.A simple random sampling technique was used to choose study participants from the target population.Data that met inclusion and exclusion criteria were analyzed using STATA version 13.The Fisher exact test(bivariate analysis)and logistic regression(multivariate)were used to test association and p-value≤0.05 was considered as statistically significant.An adjusted odd ratio(AOR)with a confidence interval(CI)of 95% was determined using binary logistic regression.Results:Findings revealed that the prevalence of DRPs was 81.29%(313/385)and most of them each patient had at least two DRPs(69.05%).The patients aged above 55 years old were more likely to develop DRPs than those with age below 35 years(AOR=1.2;P=0.02;95%CI:0.2-2.3).Nevertheless,there was no significant association between DRPs and middle age(between 35 and 54 age of old).The patients who consumed more than or equal to 5 drugs were 2.4 times more likely to develop DRPs than those who took the number of medicines less than 5(AOR=15.4;P<0.001;95%CI:8.8-26.8).Also,traditional medicines use(AOR=1.9;P=0.016;95%CI:1.1-3.5)and having drug-related complication(AOR=2.4;P<0.001;95%CI:1.9-3)had shown significant associations.The total causes of DRPs identified were 1626 and most causes of DRPs were arisen from drug use(45.01%)and prescribing(37.83%).The drug/dose selections were the most frequent causes of DRPs(36.97%).Conclusion:Since the prevalence of DRPs were relatively high,various factors influencing DRPs were established and most causes of DRPs were arising from drug use&drug prescribing among T2DM patients with HTN.Early detection needed to enhance patient’s life quality.Conducting studies in other hospitals needed to establish the national planning of DRPs to eradicate DRPs among patients T2DM with HTN.
文摘The increasing rate of insecurity in Nigeria, especially the southwest requires a paradigm shift from popular approach to crime hotspots detection. This study employed geospatial technologies to integrate spatio-temporal crime, social media and field observation data from the communities in all the six states in the southwest to develop crime hotspots that can serve as preliminary information to assist in allocating resources for crime control and prevention. Historical crime data from January 1972 to April, 2021 were compiled and updated with rigorous field survey in September, 2021. The field data were encoded, input to the SPSS 17 and analyzed using descriptive statistics and multivariate analysis. A total 936 crime locations data were geolocated and exported to ArcGIS 10.5 for spatial mapping using point map operation and further imported to e-Spatial web-based and QGIS for the generation of hotspot map using heatmap tool. The results revealed that armed robbery, assassination and cultism were more pronounced in Lagos and Ogun States. Similarly, high incidences of farmers/herdsmen conflicts are observed in Oyo and Osun States. Increasing incidences of kidnapping are common in all the south-western states but very prominent in Ondo, Lagos and Oyo States. Most of the violent crime incidents took place along the highways, with forests being their hideouts. Violent crimes are dominantly caused by high rate of unemployment while farmer/herdsmen conflicts were majorly triggered by the scarcity of grazing fields and destruction of arable crops. The conflicts have resulted in the increasing cases of rape and disruption of social group, intake of hard drugs, cult-related activities, low income and revenue generation, and displacement of farmers and infrastructural damages. The study advocates regular retraining and equipping of security agents, establishment of cattle ranch, and installation of sophisticated IP Camera at the crime hotspots to assist in real-time crime monitoring and management.
文摘Every day,the media reports tons of crimes that are considered by a large number of users and accumulate on a regular basis.Crime news exists on the Internet in unstructured formats such as books,websites,documents,and journals.From such homogeneous data,it is very challenging to extract relevant information which is a time-consuming and critical task for the public and law enforcement agencies.Keyword-based Information Retrieval(IR)systems rely on statistics to retrieve results,making it difficult to obtain relevant results.They are unable to understandthe user’s query and thus facewordmismatchesdue to context changes andthe inevitable semanticsof a given word.Therefore,such datasets need to be organized in a structured configuration,with the goal of efficiently manipulating the data while respecting the semantics of the data.An ontological semantic IR systemis needed that can find the right investigative information and find important clues to solve criminal cases.The semantic system retrieves information in view of the similarity of the semantics among indexed data and user queries.In this paper,we develop anontology-based semantic IRsystemthat leverages the latest semantic technologies including resource description framework(RDF),semantic protocol and RDF query language(SPARQL),semantic web rule language(SWRL),and web ontology language(OWL).We have conducted two experiments.In the first experiment,we implemented a keyword-based textual IR systemusing Apache Lucene.In the second experiment,we implemented a semantic systemthat uses ontology to store the data and retrieve precise results with high accuracy using SPARQL queries.The keyword-based system has filtered results with 51%accuracy,while the semantic system has filtered results with 95%accuracy,leading to significant improvements in the field and opening up new horizons for researchers.
文摘The objective of crime prediction,one of the most important technologies in social computing,is to extract useful information from many existing criminal records to predict the next process-related crime.It can aid the police in obtaining criminal information and warn the public to be vigilant in certain areas.With the rapid growth of big data,the Internet of Things,and other technologies,as well as the increasing use of artificial intelligence in forecasting models,crime prediction models based on deep learning techniques are accelerating.Therefore,it is necessary to classify the existing crime prediction algorithms and compare in depth the attributes and conditions that play an essential role in the analysis of crime prediction algorithms.Existing crime prediction methods can be roughly divided into two categories:those based on conventional machine learning and those based on contemporary deep learning.This survey analyses the fundamental theories and procedures.The most frequently used data sets are then enumerated,and the fundamental procedures of various algorithms are also analyzed in this paper.In light of the insufficient scale of existing data in this field,the ambiguity of data types used to predict crimes,and the absence of public data sets that have a significant impact on the research of algorithm models,this survey proposes the construction of a machine learning-based big data research model to address these issues.Future researchers who will enter this field are provided with a guide to the direction of future research development.
文摘The study examines the Spatial Pattern and Distribution of Crime in Suleja LGA, Niger State, Nigeria. The study used GIS and statistical methods to analyse the pattern and distribution of crime incidence in the study area. The records of each crime incidence were geocoded. Microsoft Excel was used to collate and organise the crime entries before they were imported into the ArcGIS Pro 2.0 environment. A geodatabase was created where the spatial and aspatial data were encoded and geospatial analysis was performed. The study reveals that the crime distribution pattern is generally clustered with a Global Moran’s I index of 0.097, a Z-score of 1.87, and a P-value < 0.06. Furthermore, the study reveals that armed robbery (61), kidnapping (40), car theft (33), culpable homicide (31), rape (29), and robbery (13) cases rank the highest in crime rate. Equally, findings of the study show that Chaza, Kwamba, Madalla, Suleja central, and Gaboda are the major crime hotspot zones at 90% confidence, as analysed using the Getis-Ord Gi* (Hot spot analysis) spatial statistics tool in ArcGIS Pro 2.0. The research therefore recommends that more effort be put into fighting crime, especially in areas where there are low-security formations, as they mostly have the highest record of crimes committed. Also, the patrol units should be equipped with GPS for better surveillance and real-time tracking of criminal activities.