The deterioration of a bridge’s deck endangers its safety and serviceability. Ohio has approximately 45,000 bridges that need to be monitored to ensure their structural integrity. Adequate prediction ...of the deterioration of bridges at an early stage is critical to preventing failures. The objective of this research was to develop an accurate model for predicting bridge deck conditions in Ohio. A comprehensive literature review has revealed that past researchers have utilized different algorithms and features when developing models for predicting bridge deck deterioration. Since, there is no guarantee that the use of features and algorithms utilized by past researchers would lead to accurate results for Ohio’s bridges, this research proposes a framework for optimizing the use of machine learning (ML) algorithms to more accurately predict bridge deck deterioration. The framework aims to first determine “optimal” features that can be related to deck deterioration conditions, specifically in the case of Ohio’s bridges by using various feature-selection methods. Two feature-selection models used were XGboost and random forest, which have been confirmed by the Boruta algorithm, in order to determine the features most relevant to deck conditions. Different ML algorithms were then used, based on the “optimal” features, to select the most accurate algorithm. Seven machine learning algorithms, including single models such as decision tree (DT), artificial neural networks (ANNs), k-nearest neighbors (k-NNs), logistic regression (LR), and support vector machines (SVRs), as well as ensemble models such as Random Forest (RF) and eXtreme gradient boosting (XGboost), have been implemented to classify deck conditions. To validate the framework, results from the ML algorithms that used the “optimal” features as input were compared to results from the same ML algorithms that used the “most common” features that have been used in previous studies. On a dataset obtained from the Ohio Department of Transportation (ODOT), the results indicated that the ensemble ML algorithms were able to predict deck conditions significantly more accurately than single models when the “optimal” features were utilized. Although the framework was implemented using data obtained from ODOT, it can be successfully utilized by other transportation agencies to more accurately predict the deterioration of bridge components.
Disruptions to the gut microbiota have been associated with adverse outcomes including graft-versus-host disease, infections, and mortality after hematopoietic cell transplantation and cellular ...therapy. Evidence for causal links is accumulating, thus supporting therapeutic interventions targeting the microbiota with the goal of preventing and treating adverse outcomes. One such intervention is fecal microbiota transplantation (FMT) by which an entire community of gut microbiota is transferred to the patient with dysbiosis. As this approach in transplant and cellular therapy recipients is still in its infancy, no best approach has been defined and many open questions need to be addressed before FMT becomes a standard treatment. In this review, we highlight microbiota-outcome associations with the highest level of evidence, provide an overview of the main FMT trials, and suggest some paths forward.
Acute leukemia (AL) patients undergoing intensive induction chemotherapy develop severe gut dysbiosis, placing them at heightened risk for infectious complications. Some AL patients will undergo ..."repeat therapy" (re-induction or salvage) due to persistent or relapsed disease. We hypothesized that prior injury to the microbiome during induction may influence dysbiosis patterns during repeat therapy. To test this hypothesis, we analyzed the bacterial microbiome profiles of thrice-weekly stool samples from 20 intensively treated AL patients (first induction: 13, repeat therapy: 7) by 16S rRNA sequencing. In mixed-effects modeling, repeat therapy was a significant predictor of Enterococcus expansion (P = 0.006), independently of antibiotic exposure, disease type, feeding mode, and week of chemotherapy. Bayesian analysis of longitudinal data demonstrated larger departures of microbial communities from the pre-chemotherapy baseline during repeat therapy compared to induction. This increased ecosystem instability during repeat therapy possibly impairs colonization resistance and increases vulnerability to Enterococcus outgrowth. Microbiota restoration therapies at the end of induction or before starting subsequent therapy warrant investigation.
Neutropenic fever (NF) is a common complication of chemotherapy in patients with cancer which often prolongs hospitalization and worsens the quality of life. Although an empiric antimicrobial ...approach is used to prevent and treat NF, a clear etiology cannot be found in most cases. Emerging data suggest an altered microbiota-host crosstalk leading to NF. We profiled the serum metabolome and gut microbiome in longitudinal samples before and after NF in patients with acute myeloid leukemia, a prototype setting with a high incidence of NF. We identified a circulating metabolomic shift after NF, with a minimal signature containing 18 metabolites, 13 of which were associated with the gut microbiota. Among these metabolites were markers of intestinal epithelial health and bacterial metabolites of dietary tryptophan with known anti-inflammatory and gut-protective effects. The level of these metabolites decreased after NF, in parallel with biologically consistent changes in the abundance of mucolytic and butyrogenic bacteria with known effects on the intestinal epithelium. Together, our findings indicate a metabolomic shift with NF which is primarily characterized by a loss of microbiota-derived protective metabolites rather than an increase in detrimental metabolites. This analysis suggests that the current antimicrobial approach to NF may need a revision to protect the commensal microbiota.
The burden of non-communicable diseases is rising globally. This trend seems to be faster in developing countries of the Middle East. In this study, we presented the latest prevalence rates of a ...number of important non-communicable diseases and their risk factors in the Iranian population.
The results of this study are extracted from the third national Surveillance of Risk Factors of Non-Communicable Diseases (SuRFNCD-2007), conducted in 2007. A total of 5,287 Iranian citizens, aged 15-64 years, were included in this survey. Interviewer-administered questionnaires were applied to collect the data of participants including the demographics, diet, physical activity, smoking, history of hypertension, and history of diabetes. Anthropometric characteristics were measured and serum biochemistry profiles were determined on venous blood samples. Diabetes (fasting plasma glucose >or= 126 mg/dl), hypertension (systolic blood pressure >or= 140 mmHg, diastolic blood pressure >or= 90 mmHg, or use of anti-hypertensive drugs), dyslipidemia (hypertriglyceridemia: triglycerides >or= 150 mg/dl, hypercholesterolemia: total cholesterol >or= 200 mg/dl), obesity (body mass index >or= 30 kg/m2), and central obesity (waist circumference >or= 80 cm in females and >or= 94 cm in males) were identified and the national prevalence rates were estimated.
The prevalence of diabetes, hypertension, obesity, and central obesity was 8.7% (95%CI = 7.4-10.2%), 26.6% (95%CI = 24.4-28.9%), 22.3% (95%CI = 20.2-24.5%), and 53.6% (95%CI = 50.4-56.8%), respectively. The prevalence of hypertriglyceridemia and hypercholesterolemia was 36.4% (95%CI = 34.1-38.9%) and 42.9% (95%CI = 40.4-45.4%), respectively. All of the mentioned prevalence rates were higher among females (except hypertriglyceridemia) and urban residents.
We documented a strikingly high prevalence of a number of chronic non-communicable diseases and their risk factors among Iranian adults. Urgent preventive interventions should be implemented to combat the growing public health problems in Iran.
Oral activated charcoal (OAC), a potent adsorbent with no systemic absorption, has been used for centuries to treat poisoning. Recent studies have suggested its potential efficacy in protecting the ...colonic microbiota against detrimental effects of antibiotics. In a dose-finding safety and feasibility clinical trial, 12 healthy volunteers not receiving antibiotics drank 4 different preparations made of 2 possible OAC doses (12 or 25 grams) mixed in 2 possible solutions (water or apple juice), 3 days a week for 2 weeks. Pre- and post-OAC stool samples underwent 16S rRNA gene sequencing and exact amplicon sequence variants were used to characterize the colonic microbiota. The preferred preparation was 12 grams of OAC in apple juice, with excellent safety and tolerability. OAC did not influence the gut microbiota in our healthy volunteers. These findings provide the critical preliminary data for future trials of OAC in patients receiving antibiotics.
Introduction
Nodular skin lesions in patients with acute myeloid leukemia (AML) raise clinical suspicion for leukemia cutis versus fungal infections. Here, we report a rare case of treatment-related ...erythema nodosum (EN) in a patient with AML.
Case Report
Approximately 5 weeks after the initiation of sorafenib and one week after azacitidine initiation, a 32-year-old man with primary refractory AML presented with several painful red nodules on the lower extremities. Histological examination established a diagnosis of EN.
Management and Outcome
Treatment with topical and oral steroids led to complete resolution of the nodules. However, once the dose of steroids was reduced, the lesions rapidly recurred. Higher dose steroids were reinitiated, again with a resolution of the nodules, confirming steroid responsiveness of the underlying process.
Discussion
Given the onset of lesions one week after the initiation of azacitidine and 5 weeks after the initiation of sorafenib, azacitidine was considered the more likely culprit. Only 2 cases of EN-like eruption after azacitidine and 1 case after sorafenib have been reported. Although fungal infections and leukemia cutis are the top differentials considered for skin nodules in a patient with AML, EN should be considered as an alternative diagnosis. Correct diagnosis is critical because it will guide treatment.
X-ray computed tomography provides qualitative and quantitative structural and compositional information for a broad range of materials. Yet, its contribution to the field of advanced composites such ...as carbon fiber reinforced polymers is still limited by factors such as low imaging contrast, due to scarce X-ray attenuation features. This article, through a review of the state of the art, followed by an example case study on Micro-computed tomography (CT) analysis of low X-ray absorptive dry and prepreg carbon woven fabric composites, aims to highlight and address some challenges as well as best practices on performing scans that can capture key features of the material. In the case study, utilizing an Xradia Micro-CT-400, important aspects such as obtaining sufficient contrast, an examination of thin samples, sample size/resolution issues, and image-based modeling are discussed. The outcome of an optimized workflow in Micro-CT of composite fabrics can assist in further research efforts such as the generation of surface or volume meshes for the numerical modeling of underlying deformation mechanisms during their manufacturing processes.
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