Bio-degraded of sulfamethoxazole by microbial consortia without addition nutrients: Mineralization, nitrogen removal, and proteomic characterization.

Sulfamethoxazole (SMX) is widely employed as an antibiotic, while its residue in environment has become a common public concern. Using 100 mg/L SMX as the sole nutrient source, the acclimated sludge obtained by this study displayed an excellent SMX degradation performance. The addition of SMX resulted in significant microbiological differentiation within the acclimated sludge. Microbacterium (6.6%) was identified as the relatively dominant genera in metabolism group that used SMX as sole carbon source. Highly expressed proteins from this strain strongly suggested its essential role in SMX degradation, while the degradation of SMX by other strains (Thaurea 78%) in co-metabolism group appeared to also rely on this strain. The interactions of differentially expressed proteins were primarily involved in metabolic pathways including TCA cycle and nitrogen metabolism. It is concluded that the sulfonamides might serve not only as the carbon source but also as the nitrogen source in the reactor. A total of 24 intermediates were identified, 13 intermediates were newly reported. The constructed pathway suggested the mineralizing and nitrogen conversion ability towards SMX. Batch experiments also proved that the acclimated sludge displayed ability to biodegrade other sulfonamides, including SM2 and SDZ and SMX-N could be removed completely.

Combined health effects of PM2.5 components on respiratory mortality in short-term exposure using BKMR: A case study in Sichuan, China.

One of the major causes of global mortality is respiratory diseases. Fine particulate matter (PM2.5) increased the risk of respiratory death in short-term exposure. PM2.5 is the chemical mixture of components with different health effects. The combined health effects of PM2.5 are determined by the role of each component and the potential interaction between components, but they have not been studied in short-term exposure. Sichuan Province (SC), with high respiratory mortality and heavy PM2.5 pollution, had distinctive regional differences in four regions in sources and proportions of PM2.5, so it was divided into four regions to explore the combined health effects of PM2.5 components on respiratory mortality in short-term exposure and to identify the main hazardous components. Due to the multicollinear, interactive, and nonlinear characteristics of the associations between PM2.5 components and respiratory mortality, Bayesian kernel machine regression (BKMR) was used to characterize the combined health effects, along with quantile-based g-computation (QGC) as a reference. Positive combined effects of PM2.5 were found in all four regions of Sichuan using BKMR with excess risks (ER) of 0.0101-0.0132 (95 % CI: 0.0093-0.0158) and in the central basin and northwest basin using QGC with relative risks (RR) of 1.0064 (95 % CI: 1.0039, 1.0089) and 1.0044 (95 % CI: 1.0022, 1.0066), respectively. In addition, the adverse health effect was larger in cold seasons than that in warm seasons, so vulnerable people should reduce outdoor activities in heavily polluted days, especially in the cold season. For the components of PM2.5, the BC and OM mainly from traffic, dominated the adverse health effects on respiratory mortality. Furthermore, NO3- might aggravate the adverse health effects of BC/OM. Therefore, BC/OM and NO3- should be focused together in air pollution control.

Efficient degradation of hexabromocyclododecane using montmorillonite supported nano-zero-valent iron and Citrobacter sp. Y3.

The coupling of modified nanoscale zero-valent iron (nZVI) with organohalide-degrading bacteria provides a promising solution for the remediation of hexabromocyclododecane (HBCD)-contaminated environments. However, the interactions between modified nZVI and dehalogenase bacteria are intricate, and the mechanisms of synergistic action and electron transfer are not clear, and requires further specific investigation. In this study, HBCD was used as a model pollutant, and stable isotope analysis revealed that organic montmorillonite (OMt)-supported nZVI coupled with the degrading bacterial strain Citrobacter sp. Y3 (nZVI/OMt-Y3) can use [13C]HBCD as the sole carbon source and degrade or even mineralise it into 13CO2 with a maximum conversion rate of 100% within approximately 5 days. Analysis of the intermediates showed that the degradation of HBCD mainly involves three different pathways: dehydrobromination, hydroxylation, and debromination. The proteomics results showed that nZVI introduction promoted the transport of electrons and debromination. Combining the results from XPS, FTIR, and Raman spectroscopy with the analysis results of proteinomics and biodegradation products, we verified the process of electron transport and proposed a metabolic mechanism of HBCD degradation by the nZVI/OMt-Y3. Moreover, this study provides insightful avenues and models for the further remediation of HBCD and other similar pollutants in the environment.

Dimorphism of Candida tropicalis and its effect on nitrogen and phosphorus removal and sludge settleability.

Candida tropicalis PNY, a novel dimorphic strain with the capacity of simultaneous carbon, nitrogen and phosphorus removal in anaerobic and aerobic conditions, was isolated from activated sludge. Dimorphism of C. tropicalis PNY had effect on removing nitrogen and phosphorous and slightly affected COD removal under aerobic condition. Sample with high hypha formation rate (40 ± 5%) had more removal efficiencies of NH4+-N (50 mg/L) and PO43--P (10 mg/L), which could achieve 82.19% and 97.53%, respectively. High hypha cells dosage exhibited good settleability and filamentous overgrowth was not observed. According to label-free quantitative proteomics assays. Up-regulated proteins involved in the mitogen-activated protein kinase (MAPK) pathway indicated the active growth and metabolism process of sample with high hypha formation rate (40 ± 5%). And proteins concerning about glutamate synthetase and SPX domain-contain protein explain for the nutrient removal mechanism including assimilation of ammonia and polyphosphates synthesis.

Exploring the detailed spatiotemporal characteristics of PM2.5: Generating a full-coverage and hourly PM2.5 dataset in the Sichuan Basin, China.

Fine particulate matter (PM2.5) has received worldwide attention due to its threat to public health. In the Sichuan Basin (SCB), PM2.5 is causing heavy health burdens due to its high concentrations and population density. Compared with other heavily polluted areas, less effort has been made to generate a full-coverage PM2.5 dataset of the SCB, in which the detailed PM2.5 spatiotemporal characteristics remain unclear. Considering commonly existing spatiotemporal autocorrelations, the top-of-atmosphere reflectance (TOAR) with a high coverage rate and other auxiliary data were employed to build commonly used random forest (RF) models to generate accurate hourly PM2.5 concentration predictions with a 0.05° × 0.05° spatial resolution in the SCB in 2016. Specifically, with historical concentrations predicted from a spatial RF (S-RF) and observed at stations, an alternative spatiotemporal RF (AST-RF) and spatiotemporal RF (ST-RF) were built in grids with stations (type 1). The predictions from the AST-RF in grids without stations (type 2) and observations in type 1 formed the PM2.5 dataset. The LOOCV R2, RMSE and MAE were 0.94/0.94, 8.71/8.62 µg∕m3 and 5.58/5.57 µg∕m3 in the AST-RF/ST-RF, respectively. Using the produced dataset, spatiotemporal analysis was conducted for a detailed understanding of the spatiotemporal characteristics of PM2.5 in the SCB. The PM2.5 concentrations gradually increased from the edge to the center of the SCB in spatial distribution. Two high-concentration areas centered on Chengdu and Zigong were observed throughout the year, while another high-concentration area centered on Dazhou was only observed in winter. The diurnal variation had double peaks and double valleys in the SCB. The concentrations were high at night and low in daytime, which suggests that characterizing the relationship between PM2.5 and adverse health outcomes by daily means might be inaccurate with most human activities conducted in daytime.

Socio-demographic characteristics and inequality in exposure to PM2.5: A case study in the Sichuan basin, China.

The Chengyu Metropolitan Area (CYMA), located in the Sichuan Basin, is an unevenly developed region with high PM2.5 concentrations and a population of approximately 100 million. Although exposure inequality in air pollution has received increasing concern, no related research has been carried out in the CYMA to date. In this work, we used the concentration index to assess inequality of PM2.5 population-weighted exposure in the CYMA among different subgroups, including age, education, gender, occupation and GDP per capita in the city of residence. Our findings revealed that the non-disadvantaged subgroups (people aged 15-64, people with senior and higher education, people with high-income occupations and residents of cities with high GDP per capita) had a higher PM2.5 exposure in the CYMA, with the concentration indices of -0.03 (95% CI: 0.064, -0.001), -0.14 (95% CI: 0.221, -0.059), -0.15 (95% CI: 0.238, -0.056) and -0.27 (95% CI: 0.556, 0.012), opposite to previous studies in developed countries such as the United States and France. In addition, exposure differences among cities were much larger than those among populations in the CYMA. These findings may benefit the government in identifying disproportionately exposed subgroups in developing regions, and suggest that related measures should initially be carried out for cities exposed to high PM2.5 concentrations rather than for populations exposed to high PM2.5 concentrations.

System-level metabolic modeling facilitates unveiling metabolic signature in exceptional longevity.

Although it is well known that metabolic control plays a crucial role in regulating the health span and life span of various organisms, little is known for the systems metabolic profile of centenarians, the paradigm of human healthy aging and longevity. Meanwhile, how to well characterize the system-level metabolic states in an organism of interest remains to be a major challenge in systems metabolism research. To address this challenge and better understand the metabolic mechanisms of healthy aging, we developed a method of genome-wide precision metabolic modeling (GPMM) which is able to quantitatively integrate transcriptome, proteome and kinetome data in predictive modeling of metabolic networks. Benchmarking analysis showed that GPMM successfully characterized metabolic reprogramming in the NCI-60 cancer cell lines; it dramatically improved the performance of the modeling with an R2 of 0.86 between the predicted and experimental measurements over the performance of existing methods. Using this approach, we examined the metabolic networks of a Chinese centenarian cohort and identified the elevated fatty acid oxidation (FAO) as the most significant metabolic feature in these long-lived individuals. Evidence from serum metabolomics supports this observation. Given that FAO declines with normal aging and is impaired in many age-related diseases, our study suggests that the elevated FAO has potential to be a novel signature of healthy aging of humans.

Transcriptome integration analysis and specific diagnosis model construction for Hodgkin's lymphoma, diffuse large B-cell lymphoma, and mantle cell lymphoma.

Transcriptome differences between Hodgkin's lymphoma (HL), diffuse large B-cell lymphoma (DLBCL), and mantle cell lymphoma (MCL), which are all derived from B cell, remained unclear. This study aimed to construct lymphoma-specific diagnostic models by screening lymphoma marker genes. Transcriptome data of HL, DLBCL, and MCL were obtained from public databases. Lymphoma marker genes were screened by comparing cases and controls as well as the intergroup differences among lymphomas. A total of 9 HL marker genes, 7 DLBCL marker genes, and 4 MCL marker genes were screened in this study. Most HL marker genes were upregulated, whereas DLBCL and MCL marker genes were downregulated compared to controls. The optimal HL-specific diagnostic model contains one marker gene (MYH2) with an AUC of 0.901. The optimal DLBCL-specific diagnostic model contains 7 marker genes (LIPF, CCDC144B, PRO2964, PHF1, SFTPA2, NTS, and HP) with an AUC of 0.951. The optimal MCL-specific diagnostic model contains 3 marker genes (IGLV3-19, IGKV4-1, and PRB3) with an AUC of 0.843. The present study reveals the transcriptome data-based differences between HL, DLBCL, and MCL, when combined with other clinical markers, may help the clinical diagnosis and prognosis.

Identification of hub ubiquitin ligase genes affecting Alzheimer's disease by analyzing transcriptome data from multiple brain regions.

The ubiquitin-proteasome system (UPS) plays crucial roles in numerous cellular functions. Dysfunction of the UPS shows certain correlations with the pathological changes in Alzheimer's disease (AD). This study aimed to explore the different impairments of the UPS in multiple brain regions and identify hub ubiquitin ligase (E3) genes in AD. The brain transcriptome, blood transcriptome and proteome data of AD were downloaded from a public database. The UPS genes were collected from the Ubiquitin and Ubiquitin-like Conjugation Database. The hub E3 genes were defined as the differentially expressed E3 genes shared by more than three brain regions. E3Miner and UbiBrowser were used to predict the substrate of hub E3. This study shows varied impairment of the UPS in different brain regions in AD. Furthermore, we identify seven hub E3 genes (CUL1, CUL3, EIF3I, NSMCE1, PAFAH1B1, RNF175, and UCHL1) that are downregulated in more than three brain regions. Three of these genes (CUL1, EIF3I, and NSMCE1) showed consistent low expression in blood. Most of these genes have been reported to promote AD, whereas the impact of RNF175 on AD is not yet reported. Further analysis revealed a potential regulatory mechanism by which hub E3 and its substrate genes may affect transcription functions and then exacerbate AD. This study identified seven hub E3 genes and their substrate genes affect transcription functions and then exacerbate AD. These findings may be helpful for the development of diagnostic biomarkers and therapeutic targets for AD.

Correction to: FastMM: an efficient toolbox for personalized constraint-based metabolic modeling.

An amendment to this paper has been published and can be accessed via the original article.

Dietary antioxidant vitamin C influences the evolutionary path of insecticide resistance in Drosophila melanogaster.

Herbivorous insects encounter a variety of toxic environmental substances ranging from ingested plant defensive compounds to human-introduced insecticidal agents. Dietary antioxidants are known to reduce the negative physiological impacts of toxins in mammalian systems through amelioration of reactive oxygen-related cellular damage. The analogous impacts to insects caused by multigenerational exposure to pesticides and the effects on adaptive responses within insect populations, however, are currently unknown. To address these research gaps, we used Drosophila as a model system to explore adaptive phenotypic responses to acute dichlorodiphenyltrichloroethane (DDT) exposure in the presence of the dietary antioxidant vitamin C and to examine the structural genomic consequences of this exposure. DDT resistance increased significantly among four replicates exposed to a low concentration of DDT for 10 generations. In contrast, dietary intake of vitamin C significantly reduced DDT resistance after mutigenerational exposure to the same concentration of DDT. As to the genomic consequences, no significant differences were predicted in overall nucleotide substitution rates across the genome between any of the treatments. Despite this, replicates exposed to a low concentration of DDT without vitamin C showed the highest number of synonymous and non-synonymous variants (3196 in total), followed by the DDT plus vitamin C (1174 in total), and vitamin C alone (728 in total) treatments. This study demonstrates the potential role of diet (specifically, antioxidant intake) on adaptive genome responses, and thus on the evolution of pesticide resistance within insect populations.

Systematic metabolic analysis of potential target, therapeutic drug, diagnostic method and animal model applicability in three neurodegenerative diseases.

Considerable evidence suggests that metabolic abnormalities are associated with neurodegenerative diseases. This study aimed to conduct a systematic metabolic analysis of Alzheimer's disease (AD), Parkinson's disease (PD) and Huntington's disease (HD). Human and mouse model microarray datasets were downloaded from the Gene Expression Omnibus database. The metabolic genes and pathways were collected from the Recon 3D human metabolic model. Drug and target information was obtained from the DrugBank database. This study identified ATP1A1, ATP6V1G2, GOT1, HPRT1, MAP2K1, PCMT1 and PLK2 as key metabolic genes that were downregulated in AD, PD and HD. We screened 57 drugs that target these genes, such as digoxin, ouabain and diazoxide. This study constructed multigene diagnostic models for AD, PD and HD by using metabolic gene expression profiles in blood, all models showed high accuracy (AUC > 0.8) both in the experimental and validation sets. Furthermore, analysis of animal models showed that there was almost no consistency among the metabolic changes between mouse models and human diseases. This study systematically revealed the metabolic damage among AD, PD, and HD and uncovered the differences between animal models and human diseases. This information may be helpful for understanding the metabolic mechanisms and drug development for neurodegenerative diseases.

Effect of Treatment With 3-Octylthio-1,1,1-Trifluoropropan-2-One in the Diamondback Moth (Lepidoptera: Plutellidae) to the Toxicity of Diafenthiuron, Indoxacarb, and Bacillus thuringiensis.

The diamondback moth, Plutella xylostella (L.), is a worldwide insect pest of cruciferous crops. Although insecticides have long been used for its control, diamondback moth rapidly evolves resistance to almost any insecticide. In insects, juvenile hormone (JH) is critically involved in almost all biological processes. The correct activity of JH depends on the precise regulation of its titer, and juvenile hormone esterase (JHE) is the key regulator. Thus, JH and JHE have become important targets for new insecticide development. Trifluoromethyl ketones are specific JHE inhibitors, among which 3-octylthio-1,1,1-trifluoropropan-2-one (OTFP) has the highest activity. The interaction effects between pretreatment with or combination of OTFP and the insecticides diafenthiuron, indoxacarb, and Bacillus thuringiensis (Bt) were investigated in diamondback moth larvae to determine OTFP's potential as an insecticide synergist. In third-instar larvae, both pretreatment and combination treatment with OTFP decreased or antagonized the toxicities of diafenthiuron, indoxacarb, and Bt at all set concentrations. In fourth-instar larvae, combination treatment with OTFP decreased or antagonized the toxicities of diafenthiuron and indoxacarb at all set concentrations. However, it increased or synergized the toxicity of Bt at lower concentrations despite the limited effect at higher concentrations. Our results indicated that the effect of OTFP on the toxicities of insecticides varied with the type and concentration, larval stage, and treatment method. These findings contribute to the better use of OTFP in diamondback moth control.

FastMM: an efficient toolbox for personalized constraint-based metabolic modeling.

BACKGROUND: Constraint-based metabolic modeling has been applied to understand metabolism related disease mechanisms, to predict potential new drug targets and anti-metabolites, and to identify biomarkers of complex diseases. Although the state-of-art modeling toolbox, COBRA 3.0, is powerful, it requires substantial computing time conducting flux balance analysis, knockout analysis, and Markov Chain Monte Carlo (MCMC) sampling, which may limit its application in large scale genome-wide analysis. RESULTS: Here, we rewrote the underlying code of COBRA 3.0 using C/C++, and developed a toolbox, termed FastMM, to effectively conduct constraint-based metabolic modeling. The results showed that FastMM is 2~400 times faster than COBRA 3.0 in performing flux balance analysis and knockout analysis and returns consistent outputs. When applied to MCMC sampling, FastMM is 8 times faster than COBRA 3.0. FastMM is also faster than some efficient metabolic modeling applications, such as Cobrapy and Fast-SL. In addition, we developed a Matlab/Octave interface for fast metabolic modeling. This interface was fully compatible with COBRA 3.0, enabling users to easily perform complex applications for metabolic modeling. For example, users who do not have deep constraint-based metabolic model knowledge can just type one command in Matlab/Octave to perform personalized metabolic modeling. Users can also use the advance and multiple threading parameters for complex metabolic modeling. Thus, we provided an efficient and user-friendly solution to perform large scale genome-wide metabolic modeling. For example, FastMM can be applied to the modeling of individual cancer metabolic profiles of hundreds to thousands of samples in the Cancer Genome Atlas (TCGA). CONCLUSION: FastMM is an efficient and user-friendly toolbox for large-scale personalized constraint-based metabolic modeling. It can serve as a complementary and invaluable improvement to the existing functionalities in COBRA 3.0. FastMM is under GPL license and can be freely available at GitHub site: https://github.com/GonghuaLi/FastMM.

Gain and loss events in the evolution of the apolipoprotein family in vertebrata.

BACKGROUND: Various apolipoproteins widely distributed among vertebrata play key roles in lipid metabolism and have a direct correlation with human diseases as diagnostic markers. However, the evolutionary progress of apolipoproteins in species remains unclear. Nine human apolipoproteins and well-annotated genome data of 30 species were used to identify 210 apolipoprotein family members distributed among species from fish to humans. Our study focused on the evolution of nine exchangeable apolipoproteins (ApoA-I/II/IV/V, ApoC-I~IV and ApoE) from Chondrichthyes, Holostei, Teleostei, Amphibia, Sauria (including Aves), Prototheria, Marsupialia and Eutheria. RESULTS: In this study, we reported the overall distribution and the frequent gain and loss evolutionary events of apolipoprotein family members in vertebrata. Phylogenetic trees of orthologous apolipoproteins indicated evident divergence between species evolution and apolipoprotein phylogeny. Successive gain and loss events were found by evaluating the presence and absence of apolipoproteins in the context of species evolution. For example, only ApoA-I and ApoA-IV occurred in cartilaginous fish as ancient apolipoproteins. ApoA-II, ApoE, and ApoC-I/ApoC-II were found in Holostei, Coelacanthiformes, and Teleostei, respectively, but the latter three apolipoproteins were absent from Aves. ApoC-I was also absent from Cetartiodactyla. The apolipoprotein ApoC-III emerged in terrestrial animals, and ApoC-IV first arose in Eutheria. The results indicate that the order of the emergence of apolipoproteins is most likely ApoA-I/ApoA-IV, ApoE, ApoA-II, ApoC-I/ApoC-II, ApoA-V, ApoC-III, and ApoC-IV. CONCLUSIONS: This study reveals not only the phylogeny of apolipoprotein family members in species from Chondrichthyes to Eutheria but also the occurrence and origin of new apolipoproteins. The broad perspective of gain and loss events and the evolutionary scenario of apolipoproteins across vertebrata provide a significant reference for the research of apolipoprotein function and related diseases.

Molecular cloning, expression profiling, and functional analysis of a broad-complex isoform 2/3 (Br-Z2/Z3) transcription factor in the diamondback moth, Plutella xylostella (L.).

The diamondback moth, Plutella xylostella (L.) (Lepidoptera: Plutellidae), is a widespread and destructive pest of cruciferous crops. New strategies for controlling it are needed because it is rapidly developing resistance to conventional pesticides. In insects, transcription factors (TFs) including broad-complex (Br-C) are thought to be useful for insecticide development because they are able to regulate the transcription of functional genes involved in responses to external stimuli including insecticides. In the present study, we cloned and sequenced the open reading frames (ORFs) of three BTB-ZF encoding genes from the diamondback moth deposited in the National Center for Biotechnology Information (NCBI) database under accessions MG753773, MG288674, and MG753772. The lengths of these ORFs were 1,680, 1,428, and 1,647 bp, respectively. The phylogenetic analysis based on the predicted amino acid sequences of ZF domains showed that MG753773 and MG288674 belonged to Z2/Z3 and Z7 of Br-C while MG753772 belonged to Ttk types. In the agreement, the highest expression level of MG753773 occurred during the prepupal stage, MG288674 and MG753772 were expressed during all stages and peaked in the adult and egg stages, respectively. RNA interference silencing of MG753773 in the late third instar larvae significantly decreased survival and pupation of the insects. With precocene II, transcription of MG753773 increased (4×) in the fourth instar larva 24 hr later; 48 hr later the rate of prepupation and pupation was significantly higher. These findings will contribute to the development of new regulators of the growth and development for diamondback moth control.

Regulatory network reconstruction of five essential microRNAs for survival analysis in breast cancer by integrating miRNA and mRNA expression datasets.

Although many of the genetic loci associated with breast cancer risk have been reported, there is a lack of systematic analysis of regulatory networks composed of different miRNAs and mRNAs on survival analysis in breast cancer. To reconstruct the microRNAs-genes regulatory network in breast cancer, we employed the expression data from The Cancer Genome Atlas (TCGA) related to five essential miRNAs including miR-21, miR-22, miR-210, miR-221, and miR-222, and their associated functional genomics data from the GEO database. Then, we performed an integration analysis to identify the essential target factors and interactions for the next survival analysis in breast cancer. Based on the results of our integrated analysis, we have identified significant common regulatory signatures including differentially expressed genes, enriched pathways, and transcriptional regulation such as interferon regulatory factors (IRFs) and signal transducer and activator of transcription 1 (STAT1). Finally, a reconstructed regulatory network of five miRNAs and 34 target factors was established and then applied to survival analysis in breast cancer. When we used expression data for individual miRNAs, only miR-21 and miR-22 were significantly associated with a survival change. However, we identified 45 significant miRNA-gene pairs that predict overall survival in breast cancer out of 170 one-on-one interactions in our reconstructed network covering all of five miRNAs, and several essential factors such as PSMB9, HLA-C, RARRES3, UBE2L6, and NMI. In our study, we reconstructed regulatory network of five essential microRNAs for survival analysis in breast cancer by integrating miRNA and mRNA expression datasets. These results may provide new insights into regulatory network-based precision medicine for breast cancer.

Analysis of false-positive results of diatom test in the diagnosis of drowning-would not be an impediment.

Diatom test has been a significant tool for the diagnosis of drowning. The reliability of the diatom test is still in strong dispute in the field of forensic science because of the false-positive results. This study was designed to quantitatively compare the numbers of the diatoms in false-positive cases and true drowning cases. Diatom samples from 64 victims were used in this study: 32 cases are confirmed drowning victims and other 32 cases died from non-drowned death. Samples were subject for the diatom test those were analyzed by the microwave digestion-vacuum filtration-automated scanning electron microscopy method (MD-VF-Auto SEM method) that we developed before. The results did show that there are false-positive diatoms detected in the liver and kidney tissues of non-drowned bodies: 6/20 in liver tissues and 7/20 in kidney tissues. However, the quantitative studies showed that there are statistical differences with the numbers of diatoms in the false-positive cases and in the true drowning cases. Diatom test of single organ is difficult for us to distinguish the sources of the diatoms detected. Therefore, comprehensive analysis of multiple organs would be more useful for the diagnosis of drowning.

Low expression of aging-related NRXN3 is associated with Alzheimer disease: A systematic review and meta-analysis.

BACKGROUND: Alzheimer disease (AD) is a common neurodegenerative disorder with distinct pathological features, with aging considered the greatest risk factor. We explored how aging contributes to increased AD risk, and determined concurrent and coordinate changes (including genetic and phenotypic modifications) commonly exhibited in both normal aging and AD. METHODS: Using the Gene Expression Omnibus (GEO) database, we collected 1 healthy aging-related and 3 AD-related datasets of the hippocampal region. The normal aging dataset was divided into 3 age groups: young (20-40 years old), middle-aged (40-60 years old), and elderly (>60 years old). These datasets were used to analyze the differentially expressed genes (DEGs). The Gene Ontology (GO) terms, pathways, and function network analysis of these DEGs were analyzed. RESULTS: One thousand two hundred ninety-one DEGs were found to be shared in the natural aging groups and AD patients. Among the shared DEGs, ATP6V1E1, GNG3, NDUFV2, GOT1, USP14, and NAV2 have been previously found in both normal aging individuals and AD patients. Furthermore, using Java Enrichment of Pathways Extended to Topology (JEPETTO) analysis based on Kyoto Encyclopedia of Genes and Genomes (KEGG) database, we determined that changes in aging-related KEGG annotations may contribute to the aging-dependence of AD risk. Interestingly, NRXN3, the second most commonly deregulated gene identified in the present study, is known to carry a mutation in AD patients. According to functional network analysis, NRXN3 plays a critical role in synaptic functions involved in the cognitive decline associated with normal aging and AD. CONCLUSION: Our results indicate that the low expression of aging-related NRXN3 may increase AD risk, though the potential mechanism requires further clarification.

A new method of identifying glioblastoma subtypes and creation of corresponding animal models.

Glioblastoma (GBM) accounts for up to 50% of brain parenchymal tumors. It is the most malignant type of brain cancer with very poor survival and limited remedies. Cancer subtyping is important for cancer research and therapy. Here, we report a new subtyping method for GBM based on the genetic alterations of CDKN2A and TP53 genes. CDKN2A and TP53 are the most frequently mutated genes with mutation rates of 60 and 30%, respectively. We found that patients with deletion of CDKN2A possess worse survival than those with TP53 mutation. Interestingly, survival of patients with both TP53 mutation and CDKN2A deletion is no worse than for those with only one of these genetic alterations, but similar to those with TP53 mutation alone. Next, we investigated differences in the gene expression profile between TP53 and CDKN2A samples. Consistent with the survival data, the samples with both TP53 mutation and CDKN2A deletion showed a gene expression profile similar to those samples with TP53 mutation alone. Finally, we found that activation of RAS pathway plus Cdkn2a/b silencing can induce GBM, in a similar way to tumor induction by RAS activation plus TP53 silencing. In conclusion, we show that the genetic alterations of CDKN2A and TP53 may be used to stratify GBM, and the new animal models matching this stratification method were generated.