scholarly journals Untargeted Fecal Metabolomics to Investigate the Role of the Microbiome and Nutrients in Osteoarthritis

2021 ◽  
Vol 5 (Supplement_2) ◽  
pp. 47-47
Author(s):  
Blake Rushing ◽  
Susan McRitchie ◽  
Liubov Arbeeva ◽  
Amanda Nelson ◽  
M. Andrea Azcarate-Peril ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Intestinal Inflammation ◽  
Stepwise Logistic Regression ◽  
Microbial Metabolites ◽  
Leaky Gut ◽  
Microbial Composition ◽  
Fecal Samples ◽  
Logistic Regression Models

Abstract Objectives The objective of this study was to determine if perturbations in gut microbial composition and the gut metabolome could be linked to individuals with obesity and osteoarthritis (OA). Methods Fecal samples were collected from 92 participants with obesity recruited from the Johnston County Osteoarthritis Project. OA cases (n = 59) had radiographic hand plus knee OA, defined as involvement of at least 3 joints across both hands, and a Kellgren-Lawrence (KL) grade 2–4 in at least one knee. Controls (n = 33) were without hand OA and with KL grade 0–1 knees. Fecal metabolomes were analyzed by a UHPLC/Q Exactive HFx mass spectrometer. Microbiome composition was determined in fecal samples by 16S ribosomal RNA amplicon sequencing (rRNA-seq). Stepwise logistic regression models were built to determine predictors of OA status. Spearman correlations were performed to determine associations between metabolites and microbiota in OA or healthy individuals. Results Untargeted metabolomics analysis indicated that OA cases had significantly higher levels of di- and tri-peptides (P < 0.05), and significant perturbations (P < 0.1) in microbial metabolites. Pathway analysis revealed several significantly perturbed pathways (P < 0.05) associated with OA, including leukotriene metabolism, amino acid metabolism and fatty acid utilization. Logistic regression models selected metabolites associated with the microbiota and leaky gut syndrome as significant predictors of OA status, particularly when combined with the 16S rRNA sequencing data. Omega-3/6 polyunsaturated fatty acids (PUFAs) levels were significantly correlated with the phyla Bacteriodetes and Firmicutes. Conclusions Adults with obesity and OA have distinct fecal metabolomes characterized by perturbations in microbial metabolites, PUFAs, and protein digestion compared with healthy controls. These metabolic perturbations suggest a role of intestinal inflammation and leaky gut in OA. Funding Sources Supported by the Arthritis Foundation, the National Center for Advancing Translational Sciences (NCATS) (UL1TR002489), and the National Institute of Arthritis and Musculoskeletal and Skin Diseases (P30AR072580).

scholarly journals Risk Assessment Models for Wheat Fusarium Head Blight Epidemics Based on Within-Season Weather Data

2003 ◽  
Vol 93 (4) ◽  
pp. 428-435 ◽  
Author(s):  
E. D. De Wolf ◽  
L. V. Madden ◽  
P. E. Lipps
Keyword(s):  
Logistic Regression ◽  
Relative Humidity ◽  
Fusarium Head Blight ◽  
Prediction Accuracy ◽  
Regression Models ◽  
Weather Conditions ◽  
Predictor Variables ◽  
Stepwise Logistic Regression ◽  
Head Blight ◽  
Logistic Regression Models

Logistic regression models for wheat Fusarium head blight were developed using information collected at 50 location-years, including four states, representing three different U.S. wheat-production regions. Non-parametric correlation analysis and stepwise logistic regression analysis identified combinations of temperature, relative humidity, and rainfall or durations of specified weather conditions, for 7 days prior to anthesis, and 10 days beginning at crop anthesis, as potential predictor variables. Prediction accuracy of developed logistic regression models ranged from 62 to 85%. Models suitable for application as a disease warning system were identified based on model prediction accuracy, sensitivity, specificity, and availability of weather variables at crop anthesis. Four of the identified models correctly classified 84% of the 50 location-years. A fifth model that used only pre-anthesis weather conditions correctly classified 70% of the location-years. The most useful predictor variables were the duration (h) of precipitation 7 days prior to anthesis, duration (h) that temperature was between 15 and 30°C 7 days prior to anthesis, and the duration (h) that temperature was between 15 and 30°C and relative humidity was greater than or equal to 90%. When model performance was evaluated with an independent validation set (n = 9), prediction accuracy was only 6% lower than the accuracy for the original data sets. These results indicate that narrow time periods around crop anthesis can be used to predict Fusarium head blight epidemics.

Surgical oncology outcomes: The role of nurse practice environments

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 6105-6105
Author(s):  
C. R. Friese ◽  
L. H. Aiken
Keyword(s):  
Logistic Regression ◽  
Patient Outcomes ◽  
Regression Models ◽  
Surgical Oncology ◽  
Cancer Center ◽  
Practice Environment ◽  
Failure To Rescue ◽  
Oncology Patient ◽  
Logistic Regression Models

6105 Background: Increased attention has focused on the role of hospital characteristics on cancer patient outcomes. We examined two cancer-specific credentials, as well registered nurse practice environments, on outcomes of care. Methods: Through secondary analysis of existing data from hospital claims, the tumor registry, and a statewide of survey of nurses (RNs), we studied 30-day mortality (D) and failure to rescue (death given a complication) (FTR) for surgical oncology patients treated in 164 Pennsylvania hospitals from 1998–1999 (N=24,618). We compared D and FTR rates by a hospital’s NCI cancer center designation, American College of Surgeon’s (ACoS) cancer program approval and categorized scores on the Practice Environment Scale of the Nursing Work Index (PES-NWI). The PES-NWI scales measure RN participation in hospital affairs, RN foundations for quality of care, nurse manager leadership/support, staffing/resource adequacy, and RN-physician relations. Multivariate logistic regression models examined predictors of D and FTR, controlling for 25 patient variables. Standard errors were corrected for patient clustering in hospitals. Results: NCI centers had lower D and FTR rates (p < .01). ACoS hospitals had lower D and FTR rates (ns). Hospitals with low scores on PES-NWI scales had the poorest outcomes (p < .01). In logistic regression models, significant predictors included unfavorable PES-NWI Scores for D (OR=1.32, 95% CI: 1.06–1.65) and FTR (OR=1.39, 95% CI:1.03–1.88), and NCI centers for D (OR=0.64, 95% CI: 0.50–0.83) and FTR (OR=0.67, 95% CI: 0.47–0.96). The NCI effect lost significance when environment was included. ACoS program effects were small (OR= 0.99, p = .90) for both outcomes. Conclusions: Favorable outcomes in NCI centers may be partly explained by practice environments. The practice environment of RNs significantly predicts surgical oncology patient outcomes, and should be a focus of quality improvement activities. No significant financial relationships to disclose.

scholarly journals Plasmatic Extracellular Vesicles in Acute Graft-Versus-Host Disease after Haplo-Identical Allografting with Post-Transplant Cyclophosphamide

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 598-598
Author(s):  
Giuseppe Lia ◽  
Clara Di Vito ◽  
Marta Tapparo ◽  
Stefania Bruno ◽  
Elisa Zaghi ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Extracellular Vesicles ◽  
Graft Versus Host Disease ◽  
Research Funding ◽  
Regression Models ◽  
Logistic Regression Models ◽  
Graft Versus Host ◽  
Increased Risk ◽  
Acute Graft

INTRODUCTION: Acute Graft-versus-Host-Disease (aGVHD) is a frequent complication where the endothelium may play a pivotal role. We recently investigated the potential role of extracellular vesicles (EVs) as novel biomarkers of aGVHD (Lia G. et al. Leukemia 2018). In this study we further investigated the correlation of plasma EVs and their content in miRNAs with the risk of developing aGVHD in the setting of post-transplant cyclophosphamide (PTCY) haploidentical-stem cell transplantation (Haplo-SCT). METHODS: Thirty-two patients who underwent a Haplo-SCT were included. Plasma samples were collected from peripheral blood at given time-points (pre-transplant, on day 0, 3, 7, 14, 21, 28, 35, 45, 60, 75 and 90 after transplant). EVs were extracted by a protamine-based precipitation method and were characterized by Nano-tracking Particle Analysis (Nanosight). EVs were then analyzed by flow-cytometry (Guava EasyCyte Flow Cytometer) with a panel of 14 antibodies (CD44, CD138, CD146, KRT18, CD120a, CD8, CD30, CD106, CD25, CD26, CD31, CD144, CD86, and CD140a). MiRNAs were extracted from EVs by miRNeasy Mini Kit (Qiagen) and retrotranscribed by miScript II RT Kit (Qiagen). Three miRNAs (miR100, miR194, miR155) were studied and quantified by qRT-PCR using the miScript SYBR Green PCR Kit (Qiagen). Concomitant plasma concentrations of human Tumor Necrosis Factor Receptor I (TNFR1) and human ST2 were also evaluated using a commercially available sandwich enzyme-linked immunosorbent assay (DualSET® ELISA R&D Systems). The risk of aGVHD was evaluated by logistic regression models and Odds Ratios (ORs) were estimated as absolute levels and as proportional changes compared with pre-transplant baseline levels of each marker. Moreover, among biomarkers significantly associated with a higher risk of aGVHD, a multivariable logistic regression model using Akaike's information criteria (AIC) was estimated to define a biomarker combination. Ors were reported for 1-unit increase of standardized variables. RESULTS: AGVHD (grade II-IV) was observed in 7/32 patients (22%) at a median of 41 (range 33-90) days after transplant. Logistic regression models showed that CD146 fluorescence was associated with a significantly increased risk of acute GVHD (OR 2.93 p&lt;0.001) as well as expression changes in miR100, miR155 and miR194 (OR 3.90 p&lt;0.001; OR 1.84 p=0.008; OR 2.68 p&lt;0.001, respectively). Concentrations of plasmatic hTNFR1 and ST2 were also confirmed to be associated with increased risk of aGVHD (OR 1.47 p=0.04; OR 1.55 p=0.05, respectively) as previously described. Of note, all biomarkers associated with risk of aGVHD showed a consensual change in signal levels before the onset of aGVHD (Figure 1). By applying a backward selection on a multivariable logistic model using the AICapproach, we found that the combination of CD146-miR100-TNFR1 with an individual AUROC of 0.858, 0.923, and 0.794, respectively, increased their discrimination ability to predict aGVHD (multivariable AUROC = 0.987). CONCLUSIONS: This study, in the setting of haplo-transplant, confirms the association of CD146, a cell adhesion molecule, and the risk of aGVHD suggesting an important role of endothelium damage in the pathogenesis of aGVHD. The association of miRNA100, miRNA155 and miRNA194, carried by EVs, and aGVHD was also significant. Interestingly, MiRNA100 was reported to regulate inflammatory neovascularization during GvHD while miR-155 plays a role in donor T cell expansion. We have also found that using three markers in combination (CD146-miR100-TNFR1) could greatly improve aGVHD predictivity. To translate our results into an in vivo model, we have recently designed preclinical mouse models to evaluate if a) antagomir (against miRNA100 and/or miRNA155) injections or b) pre-emptive treatments with endothelium protective agents such as defibrinotide or OMS721 (Anti-Masp2) may reduce the risk of aGVHD. Figure1 a) Signal variation from baseline level (preTx) of CD146 fluorescence, miR100 expression, and TNFR1 concentration before aGVHD onset. Disclosures Boccadoro: Sanofi: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; AbbVie: Honoraria; Mundipharma: Research Funding; Bristol-Myers Squibb: Honoraria, Research Funding.

scholarly journals Hypertension control and risk of colonic diverticulosis

2019 ◽  
Vol 12 ◽  
pp. 175628481985573
Author(s):  
Li-Xian Yeo ◽  
Tzu-Hsiang Tseng ◽  
Wei-Liang Chen ◽  
Tung-Wei Kao ◽  
Li-Wei Wu ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Logistic Regression ◽  
Regression Models ◽  
Antihypertensive Medication ◽  
Positive Association ◽  
Antihypertensive Drug Therapy ◽  
Logistic Regression Models ◽  
Epidemiologic Evidence ◽  
Asymptomatic Patients

Background: The prevalence of diverticulosis has increased in our aging population, but the risk factors for diverticulosis are not fully understood. The role of hypertension in the risk of diverticulosis remains uncertain. This study investigated whether hypertension is associated with asymptomatic colorectal diverticulosis. Methods: This study enrolled asymptomatic patients who received a colonoscopy as part of a health check. Hypertension was defined by actual measured blood pressure. Logistic regression models were used to examine the relationship between hypertension and diverticulosis. In addition, we established three logistic regression models for covariate adjustment, and further stratified patients with hypertension into three subgroups based on their type of hypertension. Results: The study group consisted of 2748 participants, including 141 participants with diverticulosis and 2607 participants without diverticulosis. After adjustments for potential covariates, the odds ratio (OR) for having diverticulosis was 1.83 (95% confidence interval, 1.21–2.75, p = 0.004) in the hypertension group compared with the group without hypertension. In subgroup analyses, hypertension without antihypertensive medication use, and hypertension despite the use of antihypertensive medication were also significantly associated with the occurrence of asymptomatic diverticulosis (OR = 1.73, p = 0.028; OR = 2.07, p = 0.013, respectively). Current normal blood pressure under antihypertensive drug therapy was not associated with diverticulosis (OR = 1.74, p = 0.092). Conclusions: Our findings suggest a positive association between hypertension and diverticulosis. Participants with poorly controlled blood pressure were found to have a higher risk of asymptomatic diverticulosis. Our study presents epidemiologic evidence for future prevention strategies against diverticulosis.

scholarly journals Sexual satisfaction among italian university students

Genus ◽  
2020 ◽  
Vol 76 (1) ◽  
Author(s):  
Laura Terzera ◽  
Stefania Maria Lorenza Rimoldi ◽  
Elisa Barbiano di Belgiojoso
Keyword(s):  
Logistic Regression ◽  
University Students ◽  
Sexual Satisfaction ◽  
Regression Models ◽  
Essential Role ◽  
Young Men ◽  
Men And Women ◽  
Logistic Regression Models ◽  
Positive Effect

Abstract This paper examines the determinants of sexual satisfaction among Italian young men and women at the beginning of their adulthood, taking into account the different stages of sentimental and sexual transitions. We based the analyses on the data collected in 2017 by the SELFY Survey on a sample of 7842 university students in Italy. Results of the logistic regression models highlight that, above all, sexual satisfaction is positively associated with the frequency of intercourse within a stable and exclusive relationship. Furthermore, results highlight the essential role of all transitions, sexual and sentimental, in enhancing sexual satisfaction, both in a positive and negative direction. Religion has a positive effect too, but only among students who have not yet had intercourse, expressing a protective effect of the adherence to beliefs. Significant differences between young men and women emerged mainly concerning performance, other conditions being equal.

Murder as Importation: An Empirical Study of the Continuity of Homicide Offending From Community to Confinement

2020 ◽  
Vol 24 (4) ◽  
pp. 398-416 ◽  
Author(s):  
Matt DeLisi ◽  
H. Daniel Butler
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Rare Events ◽  
Severe Form ◽  
Model Specification ◽  
Logistic Regression Models ◽  
Institutional Violence ◽  
Career Criminals ◽  
Low Prevalence

Prison murder is the most severe form of institutional violence but its exceedingly low prevalence has limited prior research. Recent studies of prison murders make clear that serious, violent, and chronic career criminals are most likely to perpetrate inmate murders with equivocal evidence of the role of prior homicide offending on prison murder. Using retrospective administrative data from 1,005 prisoners selected from the southwestern United States, the current study examined whether homicide offending in the community is itself an importation factor that is useful for understanding prison murder and thus can be used to understand continuity in homicidal offending from the community to confinement context. Rare events logistic regression models found that individuals sentenced for first-degree murder are more likely to perpetrate prison murder. A separate rare events logistic regression model with any type of homicide commitment offense as a predictor provided similar findings suggesting these effects are robust to model specification. Given its gravity and fundamental threat to prison safety and security, we encourage data collection and additional research on prison murder and the inmates that perpetrate it.

P–256 Time Lapse Imaging (TLI) acquired morphokinetic variables, nucleation errors and cleavage abnormalities are associated with live birth and may aid in de-selection of transfer embryos

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
S Sayed ◽  
M Reigstad ◽  
B M Petersen ◽  
A Schwennicke ◽  
J Wegne. Hausken ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Embryo Transfer ◽  
Live Birth ◽  
Clinical Setting ◽  
Regression Models ◽  
Explanatory Power ◽  
Study Cohort ◽  
Hormonal Stimulation ◽  
Logistic Regression Models

Abstract Study question May the observation by TLI of morphokinetics, nucleation errors and cleavage abnormalities assist in de-selecting embryos before embryo transfer? Summary answer The combine predictive power of the association between the three biomarkers and live birth may aid in embryo de-selection What is known already Morphokinetic parameters and cleavage biomarkers are associated with treatment outcomes following in vitro fertilization (IVF). Nucleation errors observed by TLI have also been associated with IVF outcomes. It is also shown that nucleation error self-repair in pre-implantation embryos occurs, resulting in euploid blastocysts and live births. Biomarkers identified by TLI have been incorporated in developing algorithms to be used in selecting “the embryo” with the best potential for a live birth. However, the few randomized control studies (RCT) have not shown convincingly that TLI significantly improves live birth rate. Study design, size, duration Analyses of TLI data from transferred embryos, cultured in the EmbryoScope TM between June 2012 and August 2018, in a single IVF clinical setting were included. 2082 treatment cycles with Known Implantation Data (KID) for implantation and live birth were included in the analyses. Nucleation errors such as micronucleation, binucleation, and multinucleation were systematically annotated. Cleavage abnormalities such as direct cleavages, rapid and reverse cleavages were annotated for a minimum of 44 hours post insemination. Participants/materials, setting, methods Annotations for cleavage abnormalities, morphokinetic variables and nucleation errors, during a minimum of 44 hours, for 2959 transferred embryos were obtained from the EmbryoScope. The potential negative association between day 2 KID embryo biomarkers and implantation as well as live birth was assessed. The analyses controlled for potential confounding by adjusting for maternal age, infertility diagnosis, BMI, hormonal stimulation regime and insemination method. Main results and the role of chance Preliminary results were obtained regarding biomarkers in the form of nucleation errors, cleavage abnormalities and early embryo morphological attributes. Several of these biomarkers were significantly associated with implantation and live birth. Nucleation errors were associated with substantial decrease in implantation and live birth, but contrary to findings from other studies, none of the recorded nucleation error types precluded live birth. Many morphokinetically defined cleavage abnormalities were also shown to be significantly associated with implantation and live birth, with timings to 2-cells (t2) and second cell cycle (cc2) displaying the most prominent predictions for live birth probability. Within each of the three biomarker groups, logistic regression models with implantation and live birth probability predictions displayed reasonable explanatory power regarding implantation and live birth. Combining all types of biomarkers lead to logistic regression models with substantially higher explanatory power than when the regression models only comprised a single biomarker group. With a study of this size and P values for the basic findings predominantly being highly significant, the role of chance is likely to be limited. The statistical uncertainty may therefore be subordinated to the confounding caused by embryo transfer selection and further by exclusive use of embryos with known implantation Limitations, reasons for caution Only transferred embryos with KID data were analysed and hence the outcome of other embryos is unknown. Our study used mostly day 2 embryos, therefore generalisation up to blastocyst stage is not possible. Our findings apply to our study cohort and may differ from findings in another clinical setting. Wider implications of the findings: Our study provides knowledge about the role of TLI biomarkers and their potential for deselecting embryos for transfer. This will avoid transfer of lower quality embryos with lower chances of live birth. Incorporating such non-invasive de-selection strategies, alongside morphology may contribute to improving IVF outcome. Trial registration number NA

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