The oral microbiome and adverse pregnancy outcomes.

Significant evidence supports an association between periodontal pathogenic bacteria and preterm birth and preeclampsia. The virulence properties assigned to specific oral pathogenic bacteria, for example, Fusobacterium nucleatum, Porphyromonas gingivalis, Filifactor alocis, Campylobacter rectus, and others, render them as potential collaborators in adverse outcomes of pregnancy. Several pathways have been suggested for this association: 1) hematogenous spread (bacteremia) of periodontal pathogens; 2) hematogenous spread of multiple mediators of inflammation that are generated by the host and/or fetal immune response to pathogenic bacteria; and 3) the possibility of oral microbial pathogen transmission, with subsequent colonization, in the vaginal microbiome resulting from sexual practices. As periodontal disease is, for the most part, preventable, the medical and dental public health communities can address intervention strategies to control oral inflammatory disease, lessen the systemic inflammatory burden, and ultimately reduce the potential for adverse pregnancy outcomes. This article reviews the oral, vaginal, and placental microbiomes, considers their potential impact on preterm labor, and the future research needed to confirm or refute this relationship

Trustworthy Acceptance: A New Metric for Trustworthy Artificial Intelligence Used in Decision Making in Food–Energy–Water Sectors

We propose, for the first time, a trustworthy acceptance metric and its measurement methodology to evaluate the trustworthiness of AI-based systems used in decision making in Food Energy Water (FEW) management. The proposed metric is a significant step forward in the standardization process of AI systems. It is essential to standardize the AI systems’ trustworthiness, but until now, the standardization efforts remain at the level of high-level principles. The measurement methodology of the proposed includes human experts in the loop, and it is based on our trust management system. Our metric captures and quantifies the system’s transparent evaluation by field experts on as many control points as desirable by the users. We illustrate the trustworthy acceptance metric and its measurement methodology using AI in decision-making scenarios of Food-Energy-Water sectors. However, the proposed metric and its methodology can be easily adapted to other fields of AI applications. We show that our metric successfully captures the aggregated acceptance of any number of experts, can be used to do multiple measurements on various points of the system, and provides confidence values for the measured acceptance

Effective modeling for integrated water resource management: a guide to contextual practices by phases and steps and future opportunities

The effectiveness of Integrated Water Resource Management (IWRM) modeling hinges on the quality of practices employed through the process, starting from early problem definition all the way through to using the model in a way that serves its intended purpose. The adoption and implementation of effective modeling practices need to be guided by a practical understanding of the variety of decisions that modelers make, and the information considered in making these choices. There is still limited documented knowledge on the modeling workflow, and the role of contextual factors in determining this workflow and which practices to employ. This paper attempts to contribute to this knowledge gap by providing systematic guidance of the modeling practices through the phases (Planning, Development, Application, and Perpetuation) and steps that comprise the modeling process, positing questions that should be addressed. Practice-focused guidance helps explain the detailed process of conducting IWRM modeling, including the role of contextual factors in shaping practices. We draw on findings from literature and the authors’ collective experience to articulate what and how contextual factors play out in employing those practices. In order to accelerate our learning about how to improve IWRM modeling, the paper concludes with five key areas for future practice-related research: knowledge sharing, overcoming data limitations, informed stakeholder involvement, social equity and uncertainty management. © 2019 Elsevier Lt

Peroxisome proliferator-activated receptor gamma and spermidine/spermine N(1)-acetyltransferase gene expressions are significantly correlated in human colorectal cancer

BACKGROUND: The peroxisome proliferator-activated receptor γ (PPARγ) is a transcription factor that regulates adipogenic differentiation and glucose homeostasis. Spermidine/spermine N(1)-acetyltransferase (SSAT) and ornithine decarboxylase (ODC) are key enzymes involved in the metabolism of polyamines, compounds that play an important role in cell proliferation. While the PPARγ role in tumour growth has not been clearly defined, the involvement of the altered polyamine metabolism in colorectal carcinogenesis has been established. In this direction, we have evaluated the PPARγ expression and its relationship with polyamine metabolism in tissue samples from 40 patients operated because of colorectal carcinoma. Since it is known that the functional role of K-ras mutation in colorectal tumorigenesis is associated with cell growth and differentiation, polyamine metabolism and the PPARγ expression were also investigated in terms of K-ras mutation. METHODS: PPARγ, ODC and SSAT mRNA levels were evaluated by reverse transcriptase and real-time PCR. Polyamines were quantified by high performance liquid chromatography (HPLC). ODC and SSAT activity were measured by a radiometric technique. RESULTS: PPARγ expression, as well as SSAT and ODC mRNA levels were significantly higher in cancer as compared to normal mucosa. Tumour samples also showed significantly higher polyamine levels and ODC and SSAT activities in comparison to normal samples. A significant and positive correlation between PPARγ and the SSAT gene expression was observed in both normal and neoplastic tissue (r = 0.73, p < 0.0001; r = 0.65, p < 0.0001, respectively). Moreover, gene expression, polyamine levels and enzymatic activities were increased in colorectal carcinoma samples expressing K-ras mutation as compared to non mutated K-ras samples. CONCLUSION: In conclusion, our data demonstrated a close relationship between PPARγ and SSAT in human colorectal cancer and this could represent an attempt to decrease polyamine levels and to reduce cell growth and tumour development. Therefore, pharmacological activation of PPARγ and/or induction of SSAT may represent a therapeutic or preventive strategy for treating colorectal cancer

Reactive Oxygen Species Hydrogen Peroxide Mediates Kaposi's Sarcoma-Associated Herpesvirus Reactivation from Latency

Kaposi's sarcoma-associated herpesvirus (KSHV) establishes a latent infection in the host following an acute infection. Reactivation from latency contributes to the development of KSHV-induced malignancies, which include Kaposi's sarcoma (KS), the most common cancer in untreated AIDS patients, primary effusion lymphoma and multicentric Castleman's disease. However, the physiological cues that trigger KSHV reactivation remain unclear. Here, we show that the reactive oxygen species (ROS) hydrogen peroxide (H2O2) induces KSHV reactivation from latency through both autocrine and paracrine signaling. Furthermore, KSHV spontaneous lytic replication, and KSHV reactivation from latency induced by oxidative stress, hypoxia, and proinflammatory and proangiogenic cytokines are mediated by H2O2. Mechanistically, H2O2 induction of KSHV reactivation depends on the activation of mitogen-activated protein kinase ERK1/2, JNK, and p38 pathways. Significantly, H2O2 scavengers N-acetyl-L-cysteine (NAC), catalase and glutathione inhibit KSHV lytic replication in culture. In a mouse model of KSHV-induced lymphoma, NAC effectively inhibits KSHV lytic replication and significantly prolongs the lifespan of the mice. These results directly relate KSHV reactivation to oxidative stress and inflammation, which are physiological hallmarks of KS patients. The discovery of this novel mechanism of KSHV reactivation indicates that antioxidants and anti-inflammation drugs could be promising preventive and therapeutic agents for effectively targeting KSHV replication and KSHV-related malignancies

A review of gene-drug interactions for nonsteroidal anti-inflammatory drug use in preventing colorectal neoplasia.

Nonsteroidal anti-inflammatory drugs (NSAIDs) have been shown to be effective chemopreventive agents for colorectal neoplasia. Polymorphisms in NSAID targets or metabolizing enzymes may affect NSAID efficacy or toxicity. We conducted a literature review to summarize current evidence of gene-drug interactions between NSAID use and polymorphisms in COX1, COX2, ODC, UGT1A6 and CYP2C9 on risk of colorectal neoplasia by searching OVID and PubMed. Of 134 relevant search results, thirteen investigated an interaction. One study reported a significant interaction between NSAID use and the COX1 Pro17Leu polymorphism (P=0.03) whereby the risk reduction associated with NSAID use among homozygous wild-type genotypes was not observed among NSAID users with variant alleles. Recent pharmacodynamic data support the potential for gene-drug interactions for COX1 Pro17Leu. Statistically significant interactions have also been reported for ODC (315G>A), UGT1A6 (Thr181Ala+Arg184Ser or Arg184Ser alone), and CYP2C9 (*2/*3). No statistically significant interactions have been reported for polymorphisms in COX2; however, an interaction with COX2 -765G>C approached significance (P=0.07) in one study. Among seven remaining studies, reported interactions were not statistically significant for COX1, COX2 and ODC gene polymorphisms. Most studies were of limited sample size. Definitions of NSAID use differed substantially between studies. The literature on NSAID-gene interactions to date is limited. Reliable detection of gene-NSAID interactions will require greater sample sizes, consistent definitions of NSAID use and evaluation of clinical trial subjects of chemoprevention studies

CAD-based computer vision: the automatic generation of recognition stragtegies

Journal ArticleThree-dimensional model-based computer vision uses geometric models of objects and sensed data to recognize objects in a scene. Likewise, Computer Aided Design (CAD) systems are used to interactively generate three-dimensional models during these fields. Recently, the unification of CAD and vision systems has become the focus of research in the context of manufacturing automation. This paper explores the connection between CAD and computer vision. A method for the automatic generation of recognition strategies based on the geometric properties of shape has been devised and implemented. This uses a novel technique developed for quantifying the following properties of features which compose models used in computer vision: robustness, completeness, consistency, cost, and uniqueness. By utilizing this information, the automatic synthesis of a specialized recognition scheme, called a Strategy Tree, is accomplished. Strategy Trees describe, in a systematic and robust manner. the search process used for recognition and localization of particular objects in the given scene. They consist of selected features which satisfy system constraints and Corroborating Evidence Subtrees which are used in the formation of hypotheses. Verification techniques, used to substantiate or refute these hypotheses, are explored. Experiments utilizing 3-D data are presented

Triple-GEM discharge probability studies at CHARM: Simulations and experimental results

The CMS muon system in the region with 2.03<|η|<2.82 is characterized by a very harsh radiation environment which can generate hit rates up to 144 kHz/cm$^{2}$ and an integrated charge of 8 C/cm$^{2}$ over ten years of operation. In order to increase the detector performance and acceptance for physics events including muons, a new muon station (ME0) has been proposed for installation in that region. The technology proposed is Triple—Gas Electron Multiplier (Triple-GEM), which has already been qualified for the operation in the CMS muon system. However, an additional set of studies focused on the discharge probability is necessary for the ME0 station, because of the large radiation environment mentioned above. A test was carried out in 2017 at the Cern High energy AcceleRator Mixed (CHARM) facility, with the aim of giving an estimation of the discharge probability of Triple-GEM detectors in a very intense radiation field environment, similar to the one of the CMS muon system. A dedicated standalone Geant4 simulation was performed simultaneously, to evaluate the behavior expected in the detector exposed to the CHARM field. The geometry of the detector has been carefully reproduced, as well as the background field present in the facility. This paper presents the results obtained from the Geant4 simulation, in terms of sensitivity of the detector to the CHARM environment, together with the analysis of the energy deposited in the gaps and of the processes developed inside the detector. The discharge probability test performed at CHARM will be presented, with a complete discussion of the results obtained, which turn out to be consistent with measurements performed by other groups

Impact of magnetic field on the stability of the CMS GE1/1 GEM detector operation

The Gas Electron Multiplier (GEM) detectors of the GE1/1 station of the CMS experiment have been operated in the CMS magnetic field for the first time on the 7$^{th}$ of October 2021. During the magnetic field ramps, several discharge phenomena were observed, leading to instability in the GEM High Voltage (HV) power system. In order to reproduce the behavior, it was decided to conduct a dedicated test at the CERN North Area with the Goliath magnet, using four GE1/1 spare chambers. The test consisted in studying the characteristics of discharge events that occurred in different detector configurations and external conditions. Multiple magnetic field ramps were performed in sequence: patterns in the evolution of the discharge rates were observed with these data. The goal of this test is the understanding of the experimental conditions inducing discharges and short circuits in a GEM foil. The results of this test lead to the development of procedure for the optimal operation and performance of GEM detectors in the CMS experiment during the magnet ramps. Another important result is the estimation of the probability of short circuit generation, at 68 % confidence level, p$_{short}$$^{HV}$ $^{OFF}$ = 0.42$^{-0.35+0.94}$% with detector HV OFF and p$_{short}$$^{HV}$ $^{OFF}$ < 0.49% with the HV ON. These numbers are specific for the detectors used during this test, but they provide a first quantitative indication on the phenomenon, and a point of comparison for future studies adopting the same procedure