Integrated analysis of proteomics, epigenomics and metabolomics data revealed divergent pathway activation patterns in the recent versus chronic post-traumatic stress disorder.

Metabolomics, proteomics and DNA methylome assays, when done in tandem from the same blood sample and analyzed together, offer an opportunity to evaluate the molecular basis of post-traumatic stress disorder (PTSD) course and pathogenesis. We performed separate metabolomics, proteomics, and DNA methylome assays on blood samples from two well-characterized cohorts of 159 active duty male participants with relatively recent onset PTSD (<1.5 years) and 300 male veterans with chronic PTSD (>7 years). Analyses of the multi-omics datasets from these two independent cohorts were used to identify convergent and distinct molecular profiles that might constitute potential signatures of severity and progression of PTSD and its comorbid conditions. Molecular signatures indicative of homeostatic processes such as signaling and metabolic pathways involved in cellular remodeling, neurogenesis, molecular safeguards against oxidative stress, metabolism of polyunsaturated fatty acids, regulation of normal immune response, post-transcriptional regulation, cellular maintenance and markers of longevity were significantly activated in the active duty participants with recent PTSD. In contrast, we observed significantly altered multimodal molecular signatures associated with chronic inflammation, neurodegeneration, cardiovascular and metabolic disorders, and cellular attritions in the veterans with chronic PTSD. Activation status of signaling and metabolic pathways at the early and late timepoints of PTSD demonstrated the differential molecular changes related to homeostatic processes at its recent and multi-system syndromes at its chronic phase. Molecular alterations in the recent PTSD seem to indicate some sort of recalibration or compensatory response, possibly directed in mitigating the pathological trajectory of the disorder.

A DNA methylation clock associated with age-related illnesses and mortality is accelerated in men with combat PTSD.

DNA methylation patterns at specific cytosine-phosphate-guanine (CpG) sites predictably change with age and can be used to derive "epigenetic age", an indicator of biological age, as opposed to merely chronological age. A relatively new estimator, called "DNAm GrimAge", is notable for its superior predictive ability in older populations regarding numerous age-related metrics like time-to-death, time-to-coronary heart disease, and time-to-cancer. PTSD is associated with premature mortality and frequently has comorbid physical illnesses suggestive of accelerated biological aging. This is the first study to assess DNAm GrimAge in PTSD patients. We investigated the acceleration of GrimAge relative to chronological age, denoted "AgeAccelGrim" in combat trauma-exposed male veterans with and without PTSD using cross-sectional and longitudinal data from two independent well-characterized veteran cohorts. In both cohorts, AgeAccelGrim was significantly higher in the PTSD group compared to the control group (N = 162, 1.26 vs -0.57, p = 0.001 and N = 53, 0.93 vs -1.60 Years, p = 0.008), suggesting accelerated biological aging in both cohorts with PTSD. In 3-year follow-up study of individuals initially diagnosed with PTSD (N = 26), changes in PTSD symptom severity were correlated with AgeAccelGrim changes (r = 0.39, p = 0.049). In addition, the loss of CD28 cell surface markers on CD8 + T cells, an indicator of T-cell senescence/exhaustion that is associated with biological aging, was positively correlated with AgeAccelGrim, suggesting an immunological contribution to the accelerated biological aging. Overall, our findings delineate cellular correlates of biological aging in combat-related PTSD, which may help explain the increased medical morbidity and mortality seen in this disease.

Epigenetic biotypes of post-traumatic stress disorder in war-zone exposed veteran and active duty males.

Post-traumatic stress disorder (PTSD) is a heterogeneous condition evidenced by the absence of objective physiological measurements applicable to all who meet the criteria for the disorder as well as divergent responses to treatments. This study capitalized on biological diversity observed within the PTSD group observed following epigenome-wide analysis of a well-characterized Discovery cohort (N = 166) consisting of 83 male combat exposed veterans with PTSD, and 83 combat veterans without PTSD in order to identify patterns that might distinguish subtypes. Computational analysis of DNA methylation (DNAm) profiles identified two PTSD biotypes within the PTSD+ group, G1 and G2, associated with 34 clinical features that are associated with PTSD and PTSD comorbidities. The G2 biotype was associated with an increased PTSD risk and had higher polygenic risk scores and a greater methylation compared to the G1 biotype and healthy controls. The findings were validated at a 3-year follow-up (N = 59) of the same individuals as well as in two independent, veteran cohorts (N = 54 and N = 38), and an active duty cohort (N = 133). In some cases, for example Dopamine-PKA-CREB and GABA-PKC-CREB signaling pathways, the biotypes were oppositely dysregulated, suggesting that the biotypes were not simply a function of a dimensional relationship with symptom severity, but may represent distinct biological risk profiles underpinning PTSD. The identification of two novel distinct epigenetic biotypes for PTSD may have future utility in understanding biological and clinical heterogeneity in PTSD and potential applications in risk assessment for active duty military personnel under non-clinician-administered settings, and improvement of PTSD diagnostic markers.

Community structure, distribution pattern, and influencing factors of soil Archaea in the construction area of a large-scale photovoltaic power station.

The photovoltaic power station in Qinghai has been built for 8 years; however, its impact on the regional soil ecological environment has not been studied in depth. To reveal the structure and distribution pattern of archaeal communities in desert soil under the influence of a large photovoltaic power station, a comparative study was carried out between the soil affected by photovoltaic panels and the bare land samples outside the photovoltaic station in Gonghe, Qinghai Province. The abundance, community structure, diversity, and distribution characteristics of archaea were analyzed by quantitative PCR and Illumina-MiSeq high-throughput sequencing, and the main environmental factors affecting the variation in soil archaeal community were identified by RDA. The contribution rate of environmental factors and human factors to microbial community diversity was quantitatively evaluated by VPA. The results showed that there was no significant difference in soil nutrients and other physicochemical factors between the photovoltaic power station and bare land. Thaumarchaeota was the dominant archaeal phylum in the area, accounting for more than 99% of archaeal phylum, while at the level of genus, Nitrososphaera was the dominant archaeal genera. There was no significant difference in archaeal community structure between and under different types of PV panels. The analysis has shown that the construction of a photovoltaic station has little effect on the community structure of soil archaea in a desert area, and it was speculated that the selection of niche played a leading role in the distribution pattern of soil archaeal community. This study provides the basis for a scientific understanding of the characteristics and distribution patterns of soil archaeal communities affected by the construction of a photovoltaic power station.

The Genetic Basis for the Increased Prevalence of Metabolic Syndrome among Post-Traumatic Stress Disorder Patients.

Post-traumatic stress disorder (PTSD) is a highly debilitating psychiatric disorder that can be triggered by exposure to extreme trauma. Even if PTSD is primarily a psychiatric condition, it is also characterized by adverse somatic comorbidities. One illness commonly co-occurring with PTSD is Metabolic syndrome (MetS), which is defined by a set of health risk/resilience factors including obesity, elevated blood pressure, lower high-density lipoprotein cholesterol, higher low-density lipoprotein cholesterol, higher triglycerides, higher fasting blood glucose and insulin resistance. Here, phenotypic association between PTSD and components of MetS are tested on a military veteran cohort comprising chronic PTSD presentation (n = 310, 47% cases, 83% male). Consistent with previous observations, we found significant phenotypic correlation between the various components of MetS and PTSD severity scores. To examine if this observed symptom correlations stem from a shared genetic background, we conducted genetic correlation analysis using summary statistics data from large-scale genetic studies. Our results show robust positive genetic correlation between PTSD and MetS (rg[SE] = 0.33 [0.056], p = 4.74E-09), and obesity-related components of MetS (rg = 0.25, SE = 0.05, p = 6.4E-08). Prioritizing genomic regions with larger local genetic correlation implicate three significant loci. Overall, these findings show significant genetic overlap between PTSD and MetS, which may in part account for the markedly increased occurrence of MetS among PTSD patients.

PTSD is associated with increased DNA methylation across regions of HLA-DPB1 and SPATC1L.

Posttraumatic stress disorder (PTSD) is characterized by intrusive thoughts, avoidance, negative alterations in cognitions and mood, and arousal symptoms that adversely affect mental and physical health. Recent evidence links changes in DNA methylation of CpG cites to PTSD. Since clusters of proximal CpGs share similar methylation signatures, identification of PTSD-associated differentially methylated regions (DMRs) may elucidate the pathways defining differential risk and resilience of PTSD. Here we aimed to identify epigenetic differences associated with PTSD. DNA methylation data profiled from blood samples using the MethylationEPIC BeadChip were used to perform a DMR analysis in 187 PTSD cases and 367 trauma-exposed controls from the Grady Trauma Project (GTP). DMRs were assessed with R package bumphunter. We identified two regions that associate with PTSD after multiple test correction. These regions were in the gene body of HLA-DPB1 and in the promoter of SPATC1L. The DMR in HLA-DPB1 was associated with PTSD in an independent cohort. Both DMRs included CpGs whose methylation associated with nearby sequence variation (meQTL) and that associated with expression of their respective genes (eQTM). This study supports an emerging literature linking PTSD risk to genetic and epigenetic variation in the HLA region.

Multi-omic biomarker identification and validation for diagnosing warzone-related post-traumatic stress disorder.

Post-traumatic stress disorder (PTSD) impacts many veterans and active duty soldiers, but diagnosis can be problematic due to biases in self-disclosure of symptoms, stigma within military populations, and limitations identifying those at risk. Prior studies suggest that PTSD may be a systemic illness, affecting not just the brain, but the entire body. Therefore, disease signals likely span multiple biological domains, including genes, proteins, cells, tissues, and organism-level physiological changes. Identification of these signals could aid in diagnostics, treatment decision-making, and risk evaluation. In the search for PTSD diagnostic biomarkers, we ascertained over one million molecular, cellular, physiological, and clinical features from three cohorts of male veterans. In a discovery cohort of 83 warzone-related PTSD cases and 82 warzone-exposed controls, we identified a set of 343 candidate biomarkers. These candidate biomarkers were selected from an integrated approach using (1) data-driven methods, including Support Vector Machine with Recursive Feature Elimination and other standard or published methodologies, and (2) hypothesis-driven approaches, using previous genetic studies for polygenic risk, or other PTSD-related literature. After reassessment of ~30% of these participants, we refined this set of markers from 343 to 28, based on their performance and ability to track changes in phenotype over time. The final diagnostic panel of 28 features was validated in an independent cohort (26 cases, 26 controls) with good performance (AUC = 0.80, 81% accuracy, 85% sensitivity, and 77% specificity). The identification and validation of this diverse diagnostic panel represents a powerful and novel approach to improve accuracy and reduce bias in diagnosing combat-related PTSD.

Temporal analysis of mRNA expression profiles in Orientia infected C3HeB/FeJ mouse.

BACKGROUND: Scrub typhus causes up to 35% mortality if left untreated. One billion people living in the endemic regions are at risk. In spite of its heavy disease burden in some of the most populated areas in the world, there is no vaccine available. Although the disease can be effectively treated by proper antibiotics, timely and accurate diagnosis remains a challenge. Orientia tsutsugamushi infects a variety of mammalian cells in vitro and replicates in the cytoplasm of the infected cells. Microarray analysis has been used extensively to study host-pathogen interactions in in vitro models to understand pathogenesis. However there is a lack of in vivo studies. RESULTS: In this study, C3HeB/FeJ (C3H) mice were infected by O. tsutsugamushi via the intraperitoneal route and monitored gene expression at 10 different time points post infection. We observed two distinct types of expression profiles in the genes that we analyzed. There are two valleys (4-18 h and 2-4 days) with low number of differentially expressed genes (DEG) with three peaks with high number of DEG at 2 h, 1-day and 7-day post infection. Further analysis revealed that pathways like complement and coagulation cascade, and blood clotting cascade pathways showed significant global changes throughout entire time course. Real time quantitative Polymerase Chain Reaction (RT-qPCR) confirmed the change of expression for genes involved in complement and coagulation cascade. These results suggested dynamic regulation of the complement and coagulation cascades throughout most of the time post infection while some other specific pathways, such as fatty acid metabolism and tryptophan metabolism, are turned on or off at certain times post infection. CONCLUSIONS: The findings highlight the complex interconnection among all different biological pathways. It is conceivable that specific pathways such as cell growth control and cell development in the host are affected by Orientia in the initial phase of infection for Orientia to grow intracellularly. Once Orientia is replicating successfully inside the host as infection progresses, the infection could activate pathways involved in cellular immune responses to defend for host cell survival and try to eliminate the pathogen.

Functional Heatmap: an automated and interactive pattern recognition tool to integrate time with multi-omics assays.

BACKGROUND: Life science research is moving quickly towards large-scale experimental designs that are comprised of multiple tissues, time points, and samples. Omic time-series experiments offer answers to three big questions: what collective patterns do most analytes follow, which analytes follow an identical pattern or synchronize across multiple cohorts, and how do biological functions evolve over time. Existing tools fall short of robustly answering and visualizing all three questions in a unified interface. RESULTS: Functional Heatmap offers time-series data visualization through a Master Panel page, and Combined page to answer each of the three time-series questions. It dissects the complex multi-omics time-series readouts into patterned clusters with associated biological functions. It allows users to identify a cascade of functional changes over a time variable. Inversely, Functional Heatmap can compare a pattern with specific biology respond to multiple experimental conditions. All analyses are interactive, searchable, and exportable in a form of heatmap, line-chart, or text, and the results are easy to share, maintain, and reproduce on the web platform. CONCLUSIONS: Functional Heatmap is an automated and interactive tool that enables pattern recognition in time-series multi-omics assays. It significantly reduces the manual labour of pattern discovery and comparison by transferring statistical models into visual clues. The new pattern recognition feature will help researchers identify hidden trends driven by functional changes using multi-tissues/conditions on a time-series fashion from omic assays.

PanoromiX: a time-course network medicine platform integrating molecular assays and pathophenotypic data.

BACKGROUND: Network medicine aims to map molecular perturbations of any given diseases onto complex networks with functional interdependencies that underlie a pathological phenotype. Furthermore, investigating the time dimension of disease progression from a network perspective is key to gaining key insights to the disease process and to identify diagnostic or therapeutic targets. Existing platforms are ineffective to modularize the large complex systems into subgroups and consolidate heterogeneous data to web-based interactive animation. RESULTS: We have developed PanoromiX platform, a data-agnostic dynamic interactive visualization web application, enables the visualization of outputs from genome based molecular assays onto modular and interactive networks that are correlated with any pathophenotypic data (MRI, Xray, behavioral, etc.) over a time course all in one pane. As a result, PanoromiX reveals the complex organizing principles that orchestrate a disease-pathology from a gene regulatory network (nodes, edges, hubs, etc.) perspective instead of snap shots of assays. Without extensive programming experience, users can design, share, and interpret their dynamic networks through the PanoromiX platform with rich built-in functionalities. CONCLUSIONS: This emergent tool of network medicine is the first to visualize the interconnectedness of tailored genome assays to pathological networks and phenotypes for cells or organisms in a data-agnostic manner. As an advanced network medicine tool, PanoromiX allows monitoring of panel of biomarker perturbations over the progression of diseases, disease classification based on changing network modules that corresponds to specific patho-phenotype as opposed to clinical symptoms, systematic exploration of complex molecular interactions and distinct disease states via regulatory network changes, and the discovery of novel diagnostic and therapeutic targets.

A genome-wide identified risk variant for PTSD is a methylation quantitative trait locus and confers decreased cortical activation to fearful faces.

Genetic factors appear to be highly relevant to predicting differential risk for the development of post-traumatic stress disorder (PTSD). In a discovery sample, we conducted a genome-wide association study (GWAS) for PTSD using a small military cohort (Systems Biology PTSD Biomarkers Consortium; SBPBC, N = 147) that was designed as a case-controlled sample of highly exposed, recently returning veterans with and without combat-related PTSD. A genome-wide significant single nucleotide polymorphism (SNP), rs717947, at chromosome 4p15 (N = 147, ß = 31.34, P = 1.28 × 10(-8) ) was found to associate with the gold-standard diagnostic measure for PTSD (the Clinician Administered PTSD Scale). We conducted replication and follow-up studies in an external sample, a larger urban community cohort (Grady Trauma Project, GTP, N = 2006), to determine the robustness and putative functionality of this risk variant. In the GTP replication sample, SNP rs717947 associated with PTSD diagnosis in females (N = 2006, P = 0.005), but not males. SNP rs717947 was also found to be a methylation quantitative trait locus (meQTL) in the GTP replication sample (N = 157, P = 0.002). Further, the risk allele of rs717947 was associated with decreased medial and dorsolateral cortical activation to fearful faces (N = 53, P < 0.05) in the GTP replication sample. These data identify a genome-wide significant polymorphism conferring risk for PTSD, which was associated with differential epigenetic regulation and with differential cortical responses to fear in a replication sample. These results may provide new insight into understanding genetic and epigenetic regulation of PTSD and intermediate phenotypes that contribute to this disorder.

Inkjet printing assisted synthesis of multicomponent mesoporous metal oxides for ultrafast catalyst exploration.

We describe an inkjet printing assisted cooperative-assembly method for high-throughput generation of catalyst libraries (multicomponent mesoporous metal oxides) at a rate of 1,000,000-formulations/hour with up to eight-component compositions. The compositions and mesostructures of the libraries can be well-controlled and continuously varied. Fast identification of an inexpensive and efficient quaternary catalyst for photocatalytic hydrogen evolution is achieved via a multidimensional group testing strategy to reduce the number of performance validation experiments (25,000-fold reduction over an exhaustive one-by-one search).

Biomarker discovery process at binomial decision point (2BDP): Analytical pipeline to construct biomarker panel.

A clinical incident is typically manifested by several molecular events; therefore, it seems logical that a successful diagnosis, prognosis, or stratification of a clinical landmark require multiple biomarkers. In this report, we presented a machine learning pipeline, namely "Biomarker discovery process at binomial decision point" (2BDP) that took an integrative approach in systematically curating independent variables (e.g., multiple molecular markers) to explain an output variable (e.g., clinical landmark) of binary in nature. In a logical sequence, 2BDP includes feature selection, unsupervised model development and cross validation. In the present work, the efficiency of 2BDP was demonstrated by finding three biomarker panels that independently explained three stages of Alzheimer's disease (AD) marked as Braak stages I, II and III, respectively. We designed three assortments from the entire cohort based on these Braak stages; subsequently, each assortment was split into two populations at Braak score I, II or III. 2BDP systematically integrated random forest and logistic regression fitting model to find biomarker panels with minimum features that explained these three assortments, e.g., significantly differentiated two populations segregated by Braak stage I, II or III, respectively. Thereafter, the efficacies of these panels were measured by the area under the curve (AUC) values of the receiver operating characteristic (ROC) plot. The AUC-ROC was calculated by two cross-validation methods. Final set of gene markers was a mix of novel and a priori established AD signatures. These markers were weighted by unique coefficients and linearly connected in a group of 2-10 to explain Braak stage I, II or III by AUC ≥ 0.8. Small sample size and a lack of distinctly recruited Training and Test sets were the limitations of the present undertaking; yet 2BDP demonstrated its capability to curate a panel of optimum numbers of biomarkers to describe the outcome variable with high efficacy.

Changes in structural and functional properties of whey protein cross-linked by polyphenol oxidase.

The natural whey protein is unstable, to achieve more efficient utilization, the functional properties of whey protein were modified by changing its structure, and enzymatic cross-linking is one of the common methods in dairy products to change the functional characterization. This study was conducted with objective to evaluate the structural and functional of whey protein which was cross-linked by polyphenol oxidase from Agaricus bisporus. Whey protein was cross-linked by polyphenol oxidase, and the polymers and dimers were revealed by SDS-PAGE and LC-MS/MS, the structural alterations of the polymers were analyzed by UV-vis, fluorescence spectroscopy and SEM, and the effects of functional properties of whey protein after cross-linked were also explored. Results showed that dimer and high polymer of ß-lactoglobulin were formed, the secondary structure of whey protein was exhibited a significant variation, and the microstructure changed obviously. Moreover, the foaming and antioxidant activity of whey protein was enhanced although the emulsifying was reduced after cross-linked. These findings emphasize the feasible application of enzymatic cross-linking in improving the functional properties of whey protein, and provide a new direction for changing the traditional processing technology of whey protein and developing high-quality products.

High-Efficiency and Stable Long-Persistent Luminescence from Undoped Cesium Cadmium Chlorine Crystals Induced by Intrinsic Point Defects.

Application of long-persistent luminescence (LPL) materials in many technological fields is in the spotlight. However, the exploration of undoped persistent luminescent materials with high emission efficiency, robust stability, and long persistent duration remains challenging. Here, inorganic cesium cadmium chlorine (CsCdCl3 ) is developed, featuring remarkable LPL characteristics at room temperature, which is synthesized by a facile hydrothermal method. Excited by ultraviolet light, the CsCdCl3 crystals exhibit an intense yellow emission with a large photoluminescence quantum yield of ≈90%. Different from the reported systems with lanthanides or transition metals doping, the CsCdCl3 crystals without dopants perform yellow LPL with a long duration of 6000 s. Joint experiment-theory characterizations reveal the intrinsic point defects of CsCdCl3 act as the trap centers of excited electrons and the carrier de-trapping process from such trap sites to localized emission centers contributes to the LPL. Encouraged by the attractive fluorescence and persistent luminescence as well as good stability of CsCdCl3 against environment oxygen/moisture (75%), heat (100 °C for 10 h), and ultraviolet light irradiation, an effective dual-mode information storage-reading application is demonstrated. The results open up a new frontier for exploring LPL materials without dopants and provide an opportunity for advanced information storage compatible for practical applications.

Identifying Stress-Exacerbated Thermal-Injury Induced MicroRNAs.

Using a model of combat and operational stress reaction (COSR), our lab recently showed that exposure to an unpredictable combat stress (UPCS) procedure prior to a thermal injury increases pain sensitivity in male rats. Additionally, our lab has recently shown that circulating extracellular vesicle-microRNAs (EV-miRNAs), which normally function to suppress inflammation, were downregulated in a male rat model of neuropathic pain. In this current study, male and female rats exposed to UPCS, followed by thermal injury, were evaluated for changes in circulating EV-miRNAs. Adult female and male Sprague Dawley rats were exposed to a UPCS procedure for either 2 or 4 weeks. Groups consisted of the following: nonstress (NS), stress (S), NS + thermal injury (TI), and S + TI. Mechanical sensitivity was measured, and plasma was collected at baseline, throughout the UPCS exposure, and post-thermal injury. EV-miRNA isolation was performed, followed by small RNA sequencing and subsequent data analysis. UPCS exposure alone resulted in mechanical allodynia in both male and female rats at specific time points. Thermal-injury induction occurring at peak UPCS resulted in increased mechanical allodynia in the injured hind paw compared to thermal injury alone. Differential expression of the EV-miRNAs was observed between the NS and S groups as well as between NS + TI and S + TI groups. Consistent differences in EV-miRNAs are detectable in both COSR as well as during the development of mechanical sensitivity and potentially serve as key regulators, biomarkers, and targets in the treatment of COSR and thermal-injury induced mechanical sensitivity. PERSPECTIVE: This article presents the effects of unpredictable combat stress and thermal injury on EV-contained microRNAs in an animal model. These same mechanisms may exist in clinical patients and could be future prognostic and diagnostic biomarkers.

Molecular signatures of post-traumatic stress disorder in war-zone-exposed veteran and active-duty soldiers.

Post-traumatic stress disorder (PTSD) is a multisystem syndrome. Integration of systems-level multi-modal datasets can provide a molecular understanding of PTSD. Proteomic, metabolomic, and epigenomic assays are conducted on blood samples of two cohorts of well-characterized PTSD cases and controls: 340 veterans and 180 active-duty soldiers. All participants had been deployed to Iraq and/or Afghanistan and exposed to military-service-related criterion A trauma. Molecular signatures are identified from a discovery cohort of 218 veterans (109/109 PTSD+/-). Identified molecular signatures are tested in 122 separate veterans (62/60 PTSD+/-) and in 180 active-duty soldiers (PTSD+/-). Molecular profiles are computationally integrated with upstream regulators (genetic/methylation/microRNAs) and functional units (mRNAs/proteins/metabolites). Reproducible molecular features of PTSD are identified, including activated inflammation, oxidative stress, metabolic dysregulation, and impaired angiogenesis. These processes may play a role in psychiatric and physical comorbidities, including impaired repair/wound healing mechanisms and cardiovascular, metabolic, and psychiatric diseases.

Core module biomarker identification with network exploration for breast cancer metastasis.

BACKGROUND: In a complex disease, the expression of many genes can be significantly altered, leading to the appearance of a differentially expressed "disease module". Some of these genes directly correspond to the disease phenotype, (i.e. "driver" genes), while others represent closely-related first-degree neighbours in gene interaction space. The remaining genes consist of further removed "passenger" genes, which are often not directly related to the original cause of the disease. For prognostic and diagnostic purposes, it is crucial to be able to separate the group of "driver" genes and their first-degree neighbours, (i.e. "core module") from the general "disease module". RESULTS: We have developed COMBINER: COre Module Biomarker Identification with Network ExploRation. COMBINER is a novel pathway-based approach for selecting highly reproducible discriminative biomarkers. We applied COMBINER to three benchmark breast cancer datasets for identifying prognostic biomarkers. COMBINER-derived biomarkers exhibited 10-fold higher reproducibility than other methods, with up to 30-fold greater enrichment for known cancer-related genes, and 4-fold enrichment for known breast cancer susceptible genes. More than 50% and 40% of the resulting biomarkers were cancer and breast cancer specific, respectively. The identified modules were overlaid onto a map of intracellular pathways that comprehensively highlighted the hallmarks of cancer. Furthermore, we constructed a global regulatory network intertwining several functional clusters and uncovered 13 confident "driver" genes of breast cancer metastasis. CONCLUSIONS: COMBINER can efficiently and robustly identify disease core module genes and construct their associated regulatory network. In the same way, it is potentially applicable in the characterization of any disease that can be probed with microarrays.

Mn and Cu codoped Cs2ZnBr4metal halide with multiexcitonic emission toward anti-counterfeiting.

The growing demand for optical anti-counterfeiting technology requires the development of new environmentally-friendly smart materials with single-component, multimodal fluorescence. Herein, Cs2ZnBr4:0.3Mn2+&0.15Cu+, as an efficient multimodal luminescent material with excitation-wavelength-dependent emission is reported. Under 365 nm and 254 nm UV light excitation, Cs2ZnBr4:Mn2+&Cu+emits mutually independent green light at 525 nm and blue light at 470 nm, which origin from the emission of Mn2+and the Cu+enhanced self-trapped excitons of Cs2ZnBr4, respectively. Furthermore, the multiexcitonic emission is applied to anti-counterfeiting applications and information encryption and decryption engineering. This codoped strategy provides a colorful step to expand the new metal halide materials in fluorescent anti-counterfeiting and information encryption and decryption.