Performance of Reinforced Concrete Structures Subjected to Earthquake Motions

Two simplified methods for estimating the performance of reinforced concrete structures subjected to earthquake motions were evaluated. Both the Flat-Rate and Target Period methods characterize the expected level of performance in terms of the maximum estimated drift for a given intensity of ground motion. Drift estimates using the Flat-Rate method are based on the area of structural members, the total floor area of the structure, and the peak ground acceleration as a measure of earthquake intensity. The main parameters for the Target Period method are the initial period of the structures and the peak ground acceleration. The applicability of these methods to assess the expected level of performance of existing structures was investigated using experimental data. Drift values calculated with the Flat-Rate and Target Period methods were compared with measurements obtained from earthquake simulator tests performed on reduced-scale models of reinforced concrete structures. Results indicate that both methods provided an adequate assessment of performance

C-banding in sheep with balanced homolog interchromosomal translocation

International audienc

G-banding and fluorescent-banding in sheep with heterozygous and homozygous translocation

International audienc

Associations between exploratory dietary patterns and incident type 2 diabetes : a federated meta-analysis of individual participant data from 25 cohort studies

Purpose In several studies, exploratory dietary patterns (DP), derived by principal component analysis, were inversely or positively associated with incident type 2 diabetes (T2D). However, fndings remained study-specifc, inconsistent and rarely replicated. This study aimed to investigate the associations between DPs and T2D in multiple cohorts across the world. Methods This federated meta-analysis of individual participant data was based on 25 prospective cohort studies from 5 continents including a total of 390,664 participants with a follow-up for T2D (3.8–25.0 years). After data harmonization across cohorts we evaluated 15 previously identifed T2D-related DPs for association with incident T2D estimating pooled incidence rate ratios (IRR) and confdence intervals (CI) by Piecewise Poisson regression and random-efects meta-analysis. Results 29,386 participants developed T2D during follow-up. Five DPs, characterized by higher intake of red meat, processed meat, French fries and refned grains, were associated with higher incidence of T2D. The strongest association was observed for a DP comprising these food groups besides others (IRRpooled per 1 SD=1.104, 95% CI 1.059–1.151). Although heterogeneity was present (I 2=85%), IRR exceeded 1 in 18 of the 20 meta-analyzed studies. Original DPs associated with lower T2D risk were not confrmed. Instead, a healthy DP (HDP1) was associated with higher T2D risk (IRRpooled per 1 SD=1.057, 95% CI 1.027–1.088). Conclusion Our fndings from various cohorts revealed positive associations for several DPs, characterized by higher intake of red meat, processed meat, French fries and refned grains, adding to the evidence-base that links DPs to higher T2D risk. However, no inverse DP–T2D associations were confrmed

A Professional Development Program for Science Adjunct Faculty: The Mentoring-Learning Community (MLC)

Institutions of higher education have become increasingly dependent on adjunct faculty. These faculty members are often unfamiliar with current teaching strategies emphasizing an active learning approach. To support science adjunct faculty in learning about active learning, a professional development program was designed and implemented by the authors of this study, the Mentoring-Learning Community. The Mentoring-Learning Community program design was informed by literature regarding the use of professional development programs that focused on adjunct faculty. To determine the impact of this program, participants in the Mentoring-Learning Community were observed and interviewed over one semester. Mentoring-Learning Community participants transformed through all three Transformative Learning Theory dimensions, felt more empowered to utilize active learning approaches in their classrooms, and modified some aspects of their instruction

The case: chronic kidney disease unmasked by single-subject research

We present a 42-year-old man with a BMI of 32, who was referred because of proteinuria and decreased renal function. We were impressed by his markedly muscular physique. A renal biopsy was performed, which showed focal segmental glomerular sclerosis (FSGS). Is this patient merely an obese person with FSGS or is something else going on here? We performed extensive clinical and laboratory examinations, genetic testing, and anthropometric data monitoring over time. We transferred our methodology for routine FSGS mutation screening (Sanger sequencing) to the Ion Torrent PGM platform with a new custom-targeted NGS gene panel (Ion Ampliseq FSGS panel) and tested the performance of the system in two cohorts of patients with FSGS. We discuss FSGS in bodybuilders, including possible mechanisms, and review the literature

Effects of Circulating and Local Uteroplacental Angiotensin II in Rat Pregnancy.

The renin-angiotensin (Ang) system is important during placental development. Dysregulation of the renin-Ang system is important in preeclampsia (PE). Female rats transgenic for the human angiotensinogen gene crossed with males transgenic for the human renin gene develop the PE syndrome, whereas those of the opposite cross do not. We used this model to study the role of Ang II in trophoblast invasion, which is shallow in human PE but deeper in this model. We investigated the following groups: PE rats, opposite-cross rats, Ang II–infused rats (1000 ng/kg per day), and control rats. Ang II infusion increased only circulating Ang II levels (267.82 pg/mL), opposite cross influenced only uteroplacental Ang II (13.52 fmol/mg of protein), and PE increased both circulating (251.09 pg/mL) and uteroplacental (19.24 fmol/mg of protein) Ang II. Blood pressure and albuminuria occurred in the models with high circulating Ang II but not in the other models. Trophoblast invasion increased in PE and opposite-cross rats but not in Ang II–infused rats. Correspondingly, uterine artery resistance index increased in Ang II–infused rats but decreased in PE rats. We then studied human trophoblasts and villous explants from first-trimester pregnancies with time-lapse microscopy. Local Ang II dose-dependently increased migration by 75%, invasion by 58%, and motility by 282%. The data suggest that local tissue Ang II stimulates trophoblast invasion in vivo in the rat and in vitro in human cells, a hitherto fore unrecognized function. Conceivably, upregulation of tissue Ang II in the maternal part of the placenta represents an important growth factor for trophoblast invasion and migration

Classifying Cognitive Profiles Using Machine Learning with Privileged Information in Mild Cognitive Impairment

Early diagnosis of dementia is critical for assessing disease progression and potential treatment. State-or-the-art machine learning techniques have been increasingly employed to take on this diagnostic task. In this study, we employed Generalised Matrix Learning Vector Quantization (GMLVQ) classifiers to discriminate patients with Mild Cognitive Impairment (MCI) from healthy controls based on their cognitive skills. Further, we adopted a ``Learning with privileged information'' approach to combine cognitive and fMRI data for the classification task. The resulting classifier operates solely on the cognitive data while it incorporates the fMRI data as privileged information (PI) during training. This novel classifier is of practical use as the collection of brain imaging data is not always possible with patients and older participants.MCI patients and healthy age-matched controls were trained to extract structure from temporal sequences. We ask whether machine learning classifiers can be used to discriminate patients from controls based on the learning performance and whether differences between these groups relate to individual cognitive profiles. To this end, we tested participants in four cognitive tasks: working memory, cognitive inhibition, divided attention, and selective attention. We also collected fMRI data before and after training on the learning task and extracted fMRI responses and connectivity as features for machine learning classifiers. Our results show that the PI guided GMLVQ classifiers outperform the baseline classifier that only used the cognitive data. In addition, we found that for the baseline classifier, divided attention is the only relevant cognitive feature. When PI was incorporated, divided attention remained the most relevant feature while cognitive inhibition became also relevant for the task. Interestingly, this analysis for the fMRI GMLVQ classifier suggests that (1) when overall fMRI signal for structured stimuli is used as inputs to the classifier, the post-training session is most relevant; and (2) when the graph feature reflecting underlying spatiotemporal fMRI pattern is used, the pre-training session is most relevant. Taken together these results suggest that brain connectivity before training and overall fMRI signal after training are both diagnostic of cognitive skills in MCI