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Objective:To investigate the metabolic profile of fatty acids in elderly frail patients, and its value as a biomarker of frailty.Methods:Forty-nine older adults were recruited, of whom 19 were non-frail while 15 were in the pre-frail or frail phase.Targeted metabolomics was used to detect the serum levels of fatty acids, concerning 38 short-, medium-and long-chain fatty acids.Results:Metabolomics indicated elevated levels of 9 long-chain fatty acids in the serum of the elderly frail patients, with a 1.056-fold increase in the risk of fatigue for every 1 unit increase in the level of HOMO-γ-linolenic acid( OR=2.056, P=0.016). No metabolic differences were found between the pre-frail and non-frail groups.Three and seven long-chain fatty acids were negatively correlated with the grip strength and gait speed, respectively.The γ-linolenic acid was positively correlated with body mass index(BMI), percent body fat, visceral fat area and other indicators reflecting adipose tissue.However, no correlation was found between skeletal muscle, laboratory indicators or fatty acids.Five metabolic pathways were correlated with frailty, namely fatty acid biosynthesis, fatty acid metabolism, fatty acid elongation in mitochondria, linoleic acid metabolism and α-linolenic acid metabolism. Conclusions:Nine unsaturated fatty acids, including HOMO-γ-linolenic acid and γ-linolenic acid, may be potential biomarkers of frailty in the elderly.However, the value of fatty acid metabolomics for identifying pre-frail elderly people needs to be further investigated.
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Objective:To investigate changes in skin microecological structures and functions between acute and remission phases in adult patients with severe atopic dermatitis (AD) .Methods:From October 2019 to November 2020, skin scale specimens were collected from 5 body sites (cheeks, cubital fossa, back of the hand, abdomen, lower limbs) of 4 adult patients with severe AD in the acute and remission phases, who visited the outpatient clinic of Guangzhou Institute of Dermatology. The next-generation high-throughput sequencing was performed for metagenomic sequencing to construct the microbial gene catalogue of these specimens, followed by gene annotation and bioinformatics analysis for each sample.Results:A total of 18 phyla, 37 classes, 73 orders, 142 families, 237 genera, and 331 species were identified in the skin specimens from the 4 patients with severe AD. The patients with AD in the remission phase showed significantly increased diversity of skin microbiota and markedly different relative abundance of skin microorganisms compared with those in the acute phase (both P < 0.05). At the microbial species level, Staphylococcus aureus showed the highest impact on the acute phase of AD, while Staphylococcus epidermidis, Moraxella osloensis, Francisella sp., Staphylococcus cohnii, Staphylococcus warneri, Malassezia globosa and Malassezia restricta were enriched in the remission phase of AD with the absolute value of the common logarithm of the linear discriminant analysis score > 2 (Kruksal-Wallis test, all P < 0.05). As KEGG pathway enrichment analysis showed, the differentially abundant genes were annotated into a total of 355 functional pathways, of which 38 pathways were significantly enriched (all P < 0.05), mainly involving Staphylococcus aureus infection, tryptophan metabolism, histidine metabolism, nitrogen metabolism, metabolism of arginine and proline, biosynthesis and degradation of valine, leucine and isoleucine, fatty acid degradation, peroxisome proliferator-activated receptor signaling pathway, etc. Conclusion:The skin microecological structure significantly differed between the acute and remission phases among the patients with severe AD, which may be related to multiple functional pathways, such as Staphylococcus aureus infection, tryptophan metabolism, histidine metabolism and nitrogen metabolism.
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Objective@#To observe the alteration of brain glucose metabolic network in patients with somatoform disorders (SFD).@*Methods@#18F-fluorodeoxyglucose (FDG) PET images of 18 SFD patients (10 males, 8 females; age: (39.5±12.0) years; illness duration: (3.67±3.20) years) and 21 matched healthy controls (13 males, 8 females; age: (43.9±8.4) years) in Huashan Hospital of Fudan University from October 2011 to December 2012 were enrolled to construct the brain glucose metabolic networks for 2 groups (SFD group, control group) respectively. Then the global network properties (normalized clustering coefficient, normalized shortest path length, small-worldness and global efficiency) and local parameters (clustering coefficient and betweenness centrality of the node) were calculated using the graph theory. Differences between 2 groups were compared by permutation test with 1 000 permutations. The top 20% (18/90) were classified as Hub nodes based on the results of clustering coefficient and betweenness centrality of the node.@*Results@#Small-worldness of SFD patients was similar to that of healthy controls (σ>1). There were decreased tendency in normalized clustering coefficient and global efficiency, and increased tendency in normalized shortest path length in SFD patients, but without significant differences (P>0.05). Compared to healthy controls, the betweenness centrality of left pallidum, left amygdala, left precuneus and right angular gyrus increased (permutation test, P<0.05); the betweenness centrality of left middle temporal gyrus, right superior occipital gyrus decreased (permutation test, P<0.05); the clustering coefficients of bilateral pallidum, bilateral thalamus, and left amygdala decreased (permutation test, P<0.05). Most changed Hub nodes (16/24) belonged to limbic system.@*Conclusion@#The changes of topological properties of brain glucose metabolic network in SFD patients including the decreased tendency of small-worldness and global efficiency, as well as the altered Hub nodes, may provide valid imaging evidences for brain dysfunction of somatization symptoms.
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Objective To observe the alteration of brain glucose metabolic network in patients with somatoform disorders (SFD).Methods 18F-fluorodeoxyglucose (FDG) PET images of 18 SFD patients (10 males 8 females;age:(39.5±12.0) years;illness duration:(3.67±3.20) years) and 21 matched healthy controls (13 males,8 females;age:(43.9±8.4) years) in Huashan Hospital of Fudan University from October 2011 to December 2012 were enrolled to construct the brain glucose metabolic networks for 2 groups (SFD group,control group) respectively.Then the global network properties (normalized clustering coefficient,normalized shortest path length,small-worldness and global efficiency) and local parameters (clustering coefficient and betweenness centrality of the node) were calculated using the graph theory.Differences between 2 groups were compared by permutation test with 1000 permutations.The top 20％ (18/90) were classified as Hub nodes based on the results of clustering coefficient and betweenness centrality of the node.Results Small-worldness of SFD patients was similar to that of healthy controls (σ＞ 1).There were decreased tendency in normalized clustering coefficient and global efficiency,and increased tendency in normalized shortest path length in SFD patients,but without significant differences (P＞0.05).Compared to healthy controls,the betweenness centrality of left pallidum,left amygdala,left precuneus and right angular gyrus increased (permutation test,P＜0.05);the betweenness centrality of left middle temporal gyrus,right superior occipital gyrus decreased (permutation test,P＜0.05);the clustering coefficients of bilateral pallidum,bilateral thalamus,and left amygdala decreased (permutation test,P ＜ 0.05).Most changed Hub nodes (16/24) belonged to limbic system.Conclusion The changes of topological properties of brain glucose metabolic network in SFD patients including the decreased tendency of small-worldness and global efficiency,as well as the altered Hub nodes,may provide valid imaging evidences for brain dysfunction of somatization symptoms.
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BACKGROUND Carrion's disease (CD) is a neglected biphasic illness caused by Bartonella bacilliformis, a Gram-negative bacteria found in the Andean valleys. The spread of resistant strains underlines the need for novel antimicrobials against B. bacilliformis and related bacterial pathogens. OBJECTIVE The main aim of this study was to integrate genomic-scale data to shortlist a set of proteins that could serve as attractive targets for new antimicrobial discovery to combat B. bacilliformis. METHODS We performed a multidimensional genomic scale analysis of potential and relevant targets which includes structural druggability, metabolic analysis and essentiality criteria to select proteins with attractive features for drug discovery. FINDINGS We shortlisted seventeen relevant proteins to develop new drugs against the causative agent of Carrion's disease. Particularly, the protein products of fabI, folA, aroA, trmFO, uppP and murE genes, meet an important number of desirable features that make them attractive targets for new drug development. This data compendium is freely available as a web server (http://target.sbg.qb.fcen.uba.ar/). MAIN CONCLUSION This work represents an effort to reduce the costs in the first phases of B. bacilliformis drug discovery.
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Humans , Bartonella Infections/drug therapy , Bartonella bacilliformis/drug effects , Anti-Bacterial Agents/therapeutic use , DNA, Bacterial/isolation & purification , DNA, Bacterial/genetics , Polymerase Chain Reaction , Genomics , Bartonella bacilliformis/isolation & purification , Bartonella bacilliformis/geneticsABSTRACT
Objective@#To explore the topological abnormality of brain metabolic network in patients with idiopathic rapid eye movement sleep behavior disorder (iRBD) and compare it with the topology of brain metabolic network in patients with Parkinson′s disease (PD).@*Methods@#The 18F-fluorodeoxyglucose (FDG) PET brain images of 19 patients with iRBD diagnosed with polysomnography (PSG) (iRBD group; 15 males, 4 females, average age: 64.9 years), 19 patients with PD (PD group; 12 males, 7 females, average age: 62.2 years) and 19 gender and age-matched healthy controls (HC group; 15 males, 4 females, average age: 63.1 years) in Huashan Hospital from September 2014 to June 2015 were retrospectively analyzed. According to the complex brain network method based on graph theory, the brain metabolic networks of each group was constructed and the network parameters (clustering coefficient, characteristic path length, local efficiency, global efficiency and small-world property, etc) were evaluated quantitatively. The 500 times non-parametric permutation test was used to determine the differences in network parameters between groups.@*Results@#The brain metabolic networks of iRBD group and PD group both had abnormal topological structure, which showed that the characteristic path length (for example, when sparsity=34%, HC vs iRBD vs PD groups: 1.517 vs 1.552 vs 1.561) and local efficiency (for example, when sparsity=30%, HC vs iRBD vs PD groups: 0.802 vs 0.824 vs 0.831) were significantly increased (both P<0.05), the global efficiency (for example, when sparsity=36%, HC vs iRBD vs PD groups: 0.672 vs 0.658 vs 0.656) was significantly decreased (P<0.05). The topology was more aggravated in PD group compared with that in iRBD group.@*Conclusion@#The graph-based complex brain network analysis can reveal the abnormal topological structure of the brain metabolic network in which iRBD progresses to PD.
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Objective@#To explore the mechanism of Shengxian decoction in the treatment of heart failure by using metabolomic technology.@*Methods@#Rats were randomly divided into the control group, model group and administration group according to body weight, with 10 rats in each group. Rats in model group and administration group were induced by intraperitoneal injection of adriamycin to duplicate rat heart failure model. The rats in the treatment group were given Shengxian decoction 3.83 g/kg, while those in the control group and model group were given distilled water of equal volume once a day for 4 weeks. The levels of CK, AST, LDH and MDA in serum of rats were detected by ultraviolet spectrophotometer, and the metabolite profiles were collected by high resolution tandem mass spectrometry. The data were analyzed by principal component analysis and partial least squares discriminant analysis. Metabolic pathways were obtained by pathway enrichment analysis, focusing on key metabolic enzymes and metabolic pathways.@*Results@#Compared with the model group, the serum CK (1 015.44 ± 201.49 U/L vs. 1 301.89 ± 311.54 U/L), AST (210.59 ± 80.34 U/L vs. 421.56 ± 120.32 U/L), LDH (1 211.64 ± 416.61 U/L vs. 601.58 ± 311.74 U/L) in the administration group significantly decreased (P<0.05), and MDA (209.21 ± 151.15 nmol/ml vs. 1 251.15 ± 110.64 nmol/ml) levels significantly increased (P<0.05). The metabolic distribution of rats in the control group was significantly separated from that in the model group, and the administration group was between the two groups. After dimension reduction, blood biomarkers were obtained by partial least squares discriminant analysis, including citric acid, succinic acid, malic acid, arachidonic acid, canine uric acid, serine, sphingosine, Cer (d18:0/14:0), SM (d18:1/22:0), SM [d18:0/18:1 (11Z)], SM (d18:0/16:1). Metabo Analyst 4.0 analysis showed abnormal metabolism in heart failure rats, which mainly involved arachidonic acid metabolism, glycine, serine and threonine metabolism, sphingolipid metabolism, citric acid metabolism and aminoacyl-tRNA biosynthesis.@*Conclusions@#The Shengxian decoction has a good therapeutic effect on heart failure rats. Regulation of arachidonic acid metabolism, glycine, serine and threonine metabolism, sphingolipid metabolism, citric acid metabolism and aminoacyl-tRNA biosynthesis may be the key mechanisms for its treatment of heart failure.
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Objective To explore the topological abnormality of brain metabolic network in patients with idiopathic rapid eye movement sleep behavior disorder (iRBD) and compare it with the topology of brain metabolic network in patients with Parkinson's disease (PD).Methods The 18F-fluorodeoxyglucose (FDG) PET brain images of 19 patients with iRBD diagnosed with polysomnography (PSG) (iRBD group;15 males,4 females,average age:64.9 years),19 patients with PD (PD group;12 males,7 females,average age:62.2 years) and 19 gender and age-matched healthy controls (HC group;15 males,4 females,average age:63.1 years) in Huashan Hospital from September 2014 to June 2015 were retrospectively analyzed.According to the complex brain network method based on graph theory,the brain metabolic networks of each group was constructed and the network parameters (clustering coefficient,characteristic path length,local efficiency,global efficiency and small-world property,etc) were evaluated quantitatively.The 500 times non-parametric permutation test was used to determine the differences in network parameters between groups.Results The brain metabolic networks of iRBD group and PD group both had abnormal topological structure,which showed that the characteristic path length (for example,when sparsity =34％,HC vs iRBD vs PD groups:1.517 vs 1.552 vs 1.561) and local efficiency (for example,when sparsity=30％,HC vs iRBD vs PD groups:0.802 vs 0.824 vs 0.831) were significantly increased (both P＜0.05),the global efficiency (for example,when sparsity =36％,HC vs iRBD vs PD groups:0.672 vs 0.658 vs 0.656) was significantly decreased (P＜0.05).The topology was more aggravated in PD group compared with that in iRBD group.Conclusion The graph-based complex brain network analysis can reveal the abnormal topological structure of the brain metabolic network in which iRBD progresses to PD.
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Objective To explore the mechanism of Shengxian decoction in the treatment of heart failure by using metabolomic technology. Methods Rats were randomly divided into the control group, model group and administration group according to body weight, with 10 rats in each group. Rats in model group and administration group were induced by intraperitoneal injection of adriamycin to duplicate rat heart failure model. The rats in the treatment group were given Shengxian decoction 3.83 g/kg, while those in the control group and model group were given distilled water of equal volume once a day for 4 weeks. The levels of CK, AST, LDH and MDA in serum of rats were detected by ultraviolet spectrophotometer, and the metabolite profiles were collected by high resolution tandem mass spectrometry. The data were analyzed by principal component analysis and partial least squares discriminant analysis. Metabolic pathways were obtained by pathway enrichment analysis, focusing on key metabolic enzymes and metabolic pathways. Results Compared with the model group, the serum CK (1 015.44 ± 201.49 U/L vs. 1 301.89 ± 311.54 U/L), AST (210.59 ± 80.34 U/L vs. 421.56 ± 120.32 U/L), LDH (1 211.64 ± 416.61 U/L vs. 601.58 ± 311.74 U/L) in the administration group significantly decreased (P<0.05), and MDA (209.21 ± 151.15 nmol/ml vs. 1 251.15 ± 110.64 nmol/ml) levels significantly increased (P<0.05). The metabolic distribution of rats in the control group was significantly separated from that in the model group, and the administration group was between the two groups. After dimension reduction, blood biomarkers were obtained by partial least squares discriminant analysis, including citric acid, succinic acid, malic acid, arachidonic acid, canine uric acid, serine, sphingosine, Cer (d18:0/14:0), SM (d18:1/22:0), SM [d18:0/18:1 (11Z)], SM (d18:0/16:1). Metabo Analyst 4.0 analysis showed abnormal metabolism in heart failure rats, which mainly involved arachidonic acid metabolism, glycine, serine and threonine metabolism, sphingolipid metabolism, citric acid metabolism and aminoacyl-tRNA biosynthesis. Conclusions The Shengxian decoction has a good therapeutic effect on heart failure rats. Regulation of arachidonic acid metabolism, glycine, serine and threonine metabolism, sphingolipid metabolism, citric acid metabolism and aminoacyl-tRNA biosynthesis may be the key mechanisms for its treatment of heart failure.
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For the last decade,the incidence of kidney neoplasms has shown an obvious rising trend in the world. The most common histopathological type of kidney neoplasms is clear cell renal cell carcinoma (ccRCC),which has a poor prognosis. ccRCC is generally accompanied by reprogramming of glucose,fatty acid,glutamine,tryptophan and arginine metabolic networks and pathways. Reprogramming of metabolic net-works and pathways enables tumor cells to proliferate rapidly,survive in conditions of nutrient depletion and hy-poxia,and escape surveillance by epidemic systems. New strategies have been developed to the treatment of ccRCC by targeting key proteins or enzymes involved in metabolic reprogramming pathways.
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Actinobacillus pleuropneumoniae is a Gram-negative bacterium that resides in the respiratory tract of pigs and causes porcine respiratory disease complex, which leads to significant losses in the pig industry worldwide. The incidence of drug resistance in this bacterium is increasing; thus, identifying new protein/gene targets for drug and vaccine development is critical. In this study, we used an in silico approach, utilizing several databases including the Kyoto Encyclopedia of Genes and Genomes (KEGG), the Database of Essential Genes (DEG), DrugBank, and Swiss-Prot to identify non-homologous essential genes and prioritize these proteins for their druggability. The results showed 20 metabolic pathways that were unique and contained 273 non-homologous proteins, of which 122 were essential. Of the 122 essential proteins, there were 95 cytoplasmic proteins and 11 transmembrane proteins, which are potentially suitable for drug and vaccine targets, respectively. Among these, 25 had at least one hit in DrugBank, and three had similarity to metabolic proteins from Mycoplasma hyopneumoniae, another pathogen causing porcine respiratory disease complex; thus, they could serve as common therapeutic targets. In conclusion, we identified glyoxylate and dicarboxylate pathways as potential targets for antimicrobial therapy and tetra-acyldisaccharide 4′-kinase and 3-deoxy-D-manno-octulosonic-acid transferase as vaccine candidates against A. pleuropneumoniae.
Subject(s)
Actinobacillus pleuropneumoniae , Actinobacillus , Computer Simulation , Cytoplasm , Databases, Protein , Drug Resistance , Genes, Essential , Genome , Genomics , Incidence , Metabolic Networks and Pathways , Mycoplasma hyopneumoniae , Pleuropneumonia , Respiratory System , Swine , TransferasesABSTRACT
The central carbon metabolic system is the upstream energy source for microbial fermentation. In addition, it is a master switch for increasing the production of metabolites and an important part of the microbial metabolic network. Investigation into the relationship between genes, environmental factors, and metabolic networks is a main focus of systems biology, which significantly impacts research in biochemistry, metabolic engineering, and synthetic biology. To this end, the central carbon metabolic flux under a variety of growth conditions or using strains with various genetic modifications was previously measured in Saccharomyces cerevisiae using 13C tracer technology. However, the measured values were not integrated and investigated further. In this study, we collected and analyzed the metabolic flux rates of the central carbon metabolic system in S. cerevisiae measured in recent studies. We carried out preliminary analyses of flux values of each pathway, performed regression analyses on relationship between different fluxes, and extracted principal component factors of the flux variables. Based on the results, the general characteristics of pathway flux distribution were clustered and explored, and the effects of environmental and genetic factors on the flux distribution were analyzed. Furthermore, this study explored the relationship between similarity in the enzyme's transcriptional regulation and the correlations in the enzyme's reaction flux. Our results provide a foundation for further studies on the control of the central carbon metabolic flux and facilitate the search for targets in metabolic engineering research.
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Vitamin D is a molecule that is actively involved in multiple metabolic pathways. It is mostly known for its implications related to calcium metabolism. It has also been determined that it actively participates in the cardiovascular system, influencing blood pressure, coronary artery disease and other vascular diseases, such as heart failure and atrial fibrillation. Furthermore, it has been established that this vitamin is extensively involved in the regulation of both the renin angiotensin aldosterone system and the immune system. In this review, we present the different vitamin D metabolic pathways associated with the cardiovascular pathophysiology, and we include studies in animal and human models, as well as some of the controversies found in the literature. This review also incorporates an overview of the implications in the molecular biology and public health fields.
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Animals , Humans , Atrial Fibrillation , Blood Pressure , Calcium , Cardiovascular Diseases , Cardiovascular System , Coronary Artery Disease , Heart Failure , Immune System , Metabolic Networks and Pathways , Metabolism , Molecular Biology , Public Health , Renin-Angiotensin System , Vascular Diseases , Vitamin D , VitaminsABSTRACT
Many methods have been developed for finding the commonalities between different organisms in order to study their phylogeny. The structure of metabolic networks also reveals valuable insights into metabolic capacity of species as well as into the habitats where they have evolved. We constructed metabolic networks of 79 fully sequenced organisms and compared their architectures. We used spectral density of normalized Laplacian matrix for comparing the structure of networks. The eigenvalues of this matrix reflect not only the global architecture of a network but also the local topologies that are produced by different graph evolutionary processes like motif duplication or joining. A divergence measure on spectral densities is used to quantify the distances between various metabolic networks, and a split network is constructed to analyse the phylogeny from these distances. In our analysis, we focused on the species that belong to different classes, but appear more related to each other in the phylogeny. We tried to explore whether they have evolved under similar environmental conditions or have similar life histories. With this focus, we have obtained interesting insights into the phylogenetic commonality between different organisms.
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Metabolic syndrome (METS) is a disorder of energy utilization and storage and increases the risk of developing cardiovascular disease and diabetes. To identify the genetic risk factors of METS, we carried out a genome-wide association study (GWAS) for 2,657 cases and 5,917 controls in Korean populations. As a result, we could identify 2 single nucleotide polymorphisms (SNPs) with genome-wide significance level p-values (<5 x 10(-8)), 8 SNPs with genome-wide suggestive p-values (5 x 10(-8) < or = p < 1 x 10(-5)), and 2 SNPs of more functional variants with borderline p-values (5 x 10(-5) < or = p < 1 x 10(-4)). On the other hand, the multiple correction criteria of conventional GWASs exclude false-positive loci, but simultaneously, they discard many true-positive loci. To reconsider the discarded true-positive loci, we attempted to include the functional variants (nonsynonymous SNPs [nsSNPs] and expression quantitative trait loci [eQTL]) among the top 5,000 SNPs based on the proportion of phenotypic variance explained by genotypic variance. In total, 159 eQTLs and 18 nsSNPs were presented in the top 5,000 SNPs. Although they should be replicated in other independent populations, 6 eQTLs and 2 nsSNP loci were located in the molecular pathways of LPL, APOA5, and CHRM2, which were the significant or suggestive loci in the METS GWAS. Conclusively, our approach using the conventional GWAS, reconsidering functional variants and pathway-based interpretation, suggests a useful method to understand the GWAS results of complex traits and can be expanded in other genomewide association studies.
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Cardiovascular Diseases , Genome-Wide Association Study , Hand , Metabolic Networks and Pathways , Polymorphism, Single Nucleotide , Quantitative Trait Loci , Risk FactorsABSTRACT
The systematic study of the genetic fingerprint (genomics) and the biochemistry (metabolites) that goes with a specific cellular process requires the characterization of all the small molecules that form the profile of metabolites and the associated genes. The metabolome represents the collection of all the metabolites during certain process in an organism. The transcriptome represents the gene expression profile, all the messengers RNA in a defined condition. Then to understand the whole process, the studies of metabolites must be accompanied with studies of the gene expression, hence the metabolome must be accompanied by the transcriptome, so we can identify genes and metabolites whose synthesis is induced by a specific process, an infection or stress. Studies of metabolomics generate an enormous amount of data, then they need mathematical and computational tools to establish the correlations between the biochemical and genetic data, and to build up networks that represent the complex metabolic interactions that occur in each case, using tools like Graph and Networks Theory to elucidate the emergent properties inherent to the complex interactions of the metabolic maps. This paper describes the major mathematical tools that can be used for these studies, with emphasis on a semi-qualitative proposal known as the kinetic structural model.
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Humans , Models, Genetic , Metabolism/genetics , /methods , Metabolic Networks and Pathways/genetics , RNA, Messenger/genetics , RNA, Messenger/chemistry , DNA Fingerprinting/methods , /methodsABSTRACT
Though introduced recently, complex networks research has grown steadily because of its potential to represent, characterize and model a wide range of intricate natural systems and phenomena. Because of the intrinsic complexity and systemic organization of life, complex networks provide a specially promising framework for systems biology investigation. The current article is an up-to-date review of the major developments related to the application of complex networks in biology, with special attention focused on the more recent literature. The main concepts and models of complex networks are presented and illustrated in an accessible fashion. Three main types of networks are covered: transcriptional regulatory networks, protein-protein interaction networks and metabolic networks. The key role of complex networks for systems biology is extensively illustrated by several of the papers reviewed.