scholarly journals Biomarkers Associated with Physical Resilience After Hip Fracture

2020 ◽  
Vol 75 (10) ◽  
pp. e166-e172
Author(s):  
Daniel C Parker ◽  
Cathleen Colόn-Emeric ◽  
Janet L Huebner ◽  
Ching-Heng Chou ◽  
Virginia Byers Kraus ◽  
...  
Keyword(s):  
Older Adults ◽  
Hip Fracture ◽  
Canonical Correlation ◽  
Molecular Mechanisms ◽  
Principal Component ◽  
Lasso Regression ◽  
Circulating Micrornas ◽  
The Difference ◽  
Selection Operator ◽  
Better Than

Abstract Background Clinically similar older adults demonstrate variable responses to health stressors, heterogeneity attributable to differences in physical resilience. However, molecular mechanisms underlying physical resilience are unknown. We previously derived a measure of physical resilience after hip fracture—the expected recovery differential (ERD)—that captures the difference between actual recovery and predicted recovery. Starting with biomarkers associated with physical performance, morbidity, mortality, and hip fracture, we evaluated associations with the ERD to identify biomarkers of physical resilience after hip fracture. Methods In the Baltimore Hip Studies (N = 304) sera, we quantified biomarkers of inflammation (TNFR-I, TNFR-II, sVCAM-1, and IL-6), metabolic and mitochondrial function (non-esterified fatty acids, lactate, ketones, acylcarnitines, free amino acids, and IGF-1), and epigenetic dysregulation (circulating microRNAs). We used principal component analysis, canonical correlation, and least absolute shrinkage and selection operator regression (LASSO) to identify biomarker associations with better-than-expected recovery (greater ERD) after hip fracture. Results Participants with greater ERD were more likely to be women and less disabled at baseline. The complete biomarker set explained 37% of the variance in ERD (p < .001) by canonical correlation. LASSO regression identified a biomarker subset that accounted for 27% of the total variance in the ERD and included a metabolic factor (aspartate/asparagine, C22, C5:1, lactate, glutamate/mine), TNFR-I, miR-376a-3p, and miR-16-5p. Conclusions We identified a set of biomarkers that explained 27% of the variance in ERD—a measure of physical resilience after hip fracture. These ERD-associated biomarkers may be useful in predicting physical resilience in older adults facing hip fracture and other acute health stressors.

scholarly journals Advancing Cave Detection Using Terrain Analysis and Thermal Imagery

2021 ◽  
Vol 13 (18) ◽  
pp. 3578
Author(s):  
J. Judson Wynne ◽  
Jeff Jenness ◽  
Derek L. Sonderegger ◽  
Timothy N. Titus ◽  
Murzy D. Jhabvala ◽  
...  
Keyword(s):  
Mojave Desert ◽  
Analytical Techniques ◽  
Future Research ◽  
Terrain Analysis ◽  
Lasso Regression ◽  
Thermal Imagery ◽  
Cave Entrance ◽  
The Difference ◽  
Selection Operator ◽  
Cave Detection

Since the initial experiments nearly 50 years ago, techniques for detecting caves using airborne and spacecraft acquired thermal imagery have improved markedly. These advances are largely due to a combination of higher instrument sensitivity, modern computing systems, and processor-intensive analytical techniques. Through applying these advancements, our goals were to: (1) Determine the efficacy of methods designed for terrain analysis and applied to thermal imagery; (2) evaluate the usefulness of predawn and midday imagery for detecting caves; and (3) ascertain which imagery type (predawn, midday, or the difference between those two times) was most informative. Using forward stepwise logistic (FSL) and Least Absolute Shrinkage and Selection Operator (LASSO) regression analyses for model selection, and a thermal imagery dataset acquired from the Mojave Desert, California, we examined the efficacy of three well-known terrain descriptors (i.e., slope, topographic position index (TPI), and curvature) on thermal imagery for cave detection. We also included the actual, untransformed thermal DN values (hereafter “unenhanced thermal”) as a fourth dataset. Thereafter, we compared the thermal signatures of known cave entrances to all non-cave surface locations. We determined these terrain-based analytical methods, which described the “shape” of the thermal landscape, hold significant promise for cave detection. All imagery types produced similar results. Down-selected covariates per imagery type, based upon the FSL models, were: Predawn— slope, TPI, curvature at 0 m from cave entrance, as well as slope at 1 m from cave entrance; midday— slope, TPI, and unenhanced thermal at 0 m from cave entrance; and difference— TPI and slope at 0 m from cave entrance, as well as unenhanced thermal and TPI at 3.5 m from cave entrance. We provide recommendations for future research directions in terrestrial and planetary cave detection using thermal imagery.

Identification of Three Differentially Expressed miRNAs as Potential Biomarkers for Lung Adenocarcinoma Prognosis

2020 ◽  
Vol 23 (2) ◽  
pp. 148-156
Author(s):  
Wei Wang ◽  
Bin Liu ◽  
Xiaoran Duan ◽  
Xiaolei Feng ◽  
Tuanwei Wang ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Regression Model ◽  
Lupus Erythematosus ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Lasso Regression ◽  
Differentially Expressed Mirnas ◽  
Selection Operator

Objective: The aim of this study areto screen MicroRNAs (miRNAs) related to the prognosis of lung adenocarcinoma (LUAD) and to explore the possible molecular mechanisms. Methods: The data for a total of 535 patients with LUAD data were downloaded from The Cancer Genome Atlas (TCGA) database. The miRNAs for LUAD prognosis were screened by both Cox risk proportional regression model and Last Absolute Shrinkage and Selection Operator (LASSO) regression model. The performances of the models were verified by time-dependent Receiver Operating Characteristic (ROC) curve. The possible biological processes linked to the miRNAs’ target genes were analyzed by Gene Ontology (GO), Kyoto gene and genome encyclopedia (KEGG). Results: Among 127 differentially expressed miRNAs identified from the screening analysis, there are 111 up-regulated and 16 down-regulated miRNAs. Three of them, hsa-miR-1293, hsa-miR-490 and hsa-miR- 5571, were also significantly associated with the survival of the LUAD patients. The targets of the three miRNAs are significantly enriched in systemic lupus erythematosus pathways. Conclusion: Hsa-miR-1293, hsa-miR-490 and hsa-miR-5571 can be potentially used as novel biomarkers for the prognosis prediction of LUAD.

scholarly journals Image-Based Ultrasomics Classifiers: A Potential Method to Noninvasively Predict the Proliferation-Related Biomarker Ki67

2020 ◽  
Author(s):  
anna yuan ◽  
Guoze Xu ◽  
Guiting Fang ◽  
Tong Li ◽  
Xiaomin Lai ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Potential Method ◽  
3D Ultrasound ◽  
Lasso Regression ◽  
Diagnose Breast Cancer ◽  
Wavelet Features ◽  
Coronal Section ◽  
Selection Operator ◽  
Sensitivity Specificity ◽  
Better Than

Abstract Objectives: The proliferation-related biomarker Ki67 is excellent in predicting the prognosis of breast cancer. 3D ultrasound imaging can provide information about coronal section images that help diagnose breast cancer. Our study aims to develop an ultrasomics method that extracts information related to Ki67 by analyzing the maximum transverse/sagittal/coronal section images of breast cancer mass. Methods: Our study retrospectively collected data on patients who had finished 3D ultrasound examinations and were pathologically diagnosed with breast cancer. Images met the criteria were segmented, and then regions of interest (ROIs) were outlined for extracting ultrasomics features, such as statistical, morphological, texture, filter, and wavelet features.Results: The least absolute shrinkage and selection operator (LASSO) regression model selected 16 features that were closely related to the Ki67. The classification results of sensitivity, specificity, accuracy, and area under curve (AUC) of the transverse-sectional images were 0.6451, 0.8064, 0.7258, and 0.8065 (95% CI, 0.6915-0.9214), respectively; for sagittal-sectional images were 0.5806, 0.7741, 0.6774, and 0.6660 (95% CI, 0.5283-0.8037) respectively; for coronal-sectional images were 0.5806, 0.6774, 0.6290, and 0.7159 (95% CI, 0.5847-0.8471) respectively, and for a combination of three-section images were 0.7667, 0.7500, 0.7580, and 0.8510 (95% CI, 0.7537 -0.9483).Conclusions: The model classifier based on the transverse section images performed better than that based on the sagittal/coronal section images. The model classifier based on a combination of three-section images had a better outcome than that used only single section images. Image-based ultrasomics classifiers can noninvasively predict the Ki67 of breast cancer.

Comparison and Analysis of the Competitiveness of Two Groups of World Outstanding Male Professional Golfer

2011 ◽  
Vol 187 ◽  
pp. 210-215
Author(s):  
Zhi Yong Huang ◽  
Lie Bao Han ◽  
Gui Yan
Keyword(s):  
Comparison Group ◽  
Principal Component ◽  
The Other ◽  
The World ◽  
Comparison And Analysis ◽  
The Difference ◽  
World Ranking ◽  
Level Group ◽  
Different Levels ◽  
Better Than

In this article, the top 15 golfers are chosen for the top-level group and another 15 golfers ranking from 56 to 70 are chosen for the comparison group, according to the world ranking of PGA TOUR. The two groups are the main objects of study. This research aims to better understand the difference of competitiveness of the two groups, using mathematics statistics and comparative studies. First, average driving distance, driving accuracy percentage, greens in regulation percentage, putting average, birdie average, sand save percentage, scoring average, putts per round and par breakers are analyzed through principal component analysis. The result shows that they all can reveal the competitiveness of the golfers and they can also be used for analyzing the competitiveness of other golfers of different levels. Then, the competitiveness of the golfers in the top-level group is compared with that of the golfers in the comparison group. And the result shows that average driving distance、birdie average、scoring average and par breakers of golfers in the top-level group are much better than those of the golfers in the comparison group where Wenchong Liang belongs, but there is no obvious difference of the other 5 aspects.

scholarly journals Circulating IL-13 Is Associated with De Novo Development of HCC in HCV-Infected Patients Responding to Direct-Acting Antivirals

Cancers ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3820
Author(s):  
Zuzana Macek Jílková ◽  
Arnaud Seigneurin ◽  
Celine Coppard ◽  
Laurissa Ouaguia ◽  
Caroline Aspord ◽  
...  
Keyword(s):  
De Novo ◽  
Serum Levels ◽  
Lasso Regression ◽  
Direct Acting Antivirals ◽  
Immune Mediators ◽  
Luminex Technology ◽  
The Difference ◽  
Selection Operator ◽  
Direct Acting ◽  
Subsequent Time Point

Direct-acting antivirals (DAAs) are highly effective in targeting hepatitis C virus (HCV) infections, but the incidence of HCV-related hepatocellular carcinoma (HCC) remains still high. In this study, we investigated a cohort of HCV-infected patients treated with DAAs who were followed up for 4 years after sustained virological response (SVR) achievement. Patients who developed de novo HCC following DAA treatment were compared to matched controls who did not develop HCC. These control patients were selected based on DAA treatment, sex, age, fibrosis status, and platelet counts. We evaluated serum levels of 30 immune mediators before, during, at the end of, and three months after DAA treatment using Luminex technology. We identified the immune factors associated with de novo HCC occurrence following DAA treatment. Specifically, interleukin (IL)-4 and IL-13 levels were significantly higher before start of the DAA treatment in the serum of patients who later developed HCC than in controls and stayed higher at each subsequent time point. Least absolute shrinkage and selection operator (LASSO) regression revealed IL-13 as the only strong factor associated with HCC development in this cohort of HCV patients. The difference was observed already at baseline of DAA treatment, which confirms the existence of a specific immune profile in these patients who later develop HCC.

scholarly journals Modified Colon Leakage Score to Predict Anastomotic Leakage in Patients Who Underwent Left-Sided Colorectal Surgery

2019 ◽  
Vol 8 (9) ◽  
pp. 1450
Author(s):  
Seung Up Yang ◽  
Eun Jung Park ◽  
Seung Hyuk Baik ◽  
Kang Young Lee ◽  
Jeonghyun Kang
Keyword(s):  
Colorectal Surgery ◽  
Anastomotic Leakage ◽  
Operating Characteristic ◽  
Predictive Performance ◽  
Lasso Regression ◽  
Clinical Tool ◽  
Training Set ◽  
Validation Set ◽  
Selection Operator ◽  
Better Than

Colon leakage score (CLS) was introduced as a clinical tool to predict anastomotic leakage (AL) in patients who underwent left-sided colorectal surgery, but its clinical validity has not been widely studied. We evaluated the clinical utility of CLS and developed a modified CLS (m-CLS). In total, 566 patients who underwent left-sided colorectal surgery were enrolled and categorized into training (n = 396) and validation (n = 170) sets via random sampling. Using CLS variables, the least absolute shrinkage and selection operator (LASSO) regression model was applied for variable selection and predictive signature building in the training set. The model’s performance was validated in the validation set. The predictive powers of m-CLS and CLS were compared by the area under the receiver operating characteristic (AUROC) curve in the overall group. Twenty-three AL events (4.1%) were noted. The AL group had a significantly higher mean CLS than the No Leakage group (12.5 vs. 9.6, p = 0.001). Five clinical variables were selected and used to generate m-CLS. The predictive performance of m-CLS was similar in training and validation sets (AUROC 0.838 vs. 0.803, p = 0.724). In the overall set, m-CLS was significantly predictive of AL and performed better than CLS (AUROC 0.831 vs. 0.701, p = 0.008). In conclusion, LASSO-model-generated m-CLS could predict AL more accurately than CLS.

Removal of inelastically scattered electrons substantially increases phase contrast on frozen-hydrated molecules

1987 ◽  
Vol 45 ◽  
pp. 652-653
Author(s):  
John P. Langmore ◽  
Brian D. Athey
Keyword(s):  
Electron Diffraction ◽  
Phase Contrast ◽  
Low Dose ◽  
Dark Field ◽  
Biological Structure ◽  
Bright Field ◽  
Low Contrast ◽  
Negative Stain ◽  
The Difference ◽  
Better Than

Although electron diffraction indicates better than 0.3nm preservation of biological structure in vitreous ice, the imaging of molecules in ice is limited by low contrast. Thus, low-dose images of frozen-hydrated molecules have significantly more noise than images of air-dried or negatively-stained molecules. We have addressed the question of the origins of this loss of contrast. One unavoidable effect is the reduction in scattering contrast between a molecule and the background. In effect, the difference in scattering power between a molecule and its background is 2-5 times less in a layer of ice than in vacuum or negative stain. A second, previously unrecognized, effect is the large, incoherent background of inelastic scattering from the ice. This background reduces both scattering and phase contrast by an additional factor of about 3, as shown in this paper. We have used energy filtration on the Zeiss EM902 in order to eliminate this second effect, and also increase scattering contrast in bright-field and dark-field.

Slow Down You’re Moving Too Fast

2015 ◽  
Vol 27 (2) ◽  
pp. 53-63 ◽  
Author(s):  
Annie Lang ◽  
Nancy Schwartz ◽  
Sharon Mayell
Keyword(s):  
Older Adults ◽  
Cognitive Aging ◽  
Attention And Memory ◽  
Younger Adults ◽  
Media Messages ◽  
Two Factors ◽  
The Difference

The study reported here compared how younger and older adults processed the same set of media messages which were selected to vary on two factors, arousing content and valence. Results showed that older and younger adults had similar arousal responses but different patterns of attention and memory. Older adults paid more attention to all messages than did younger adults. However, this attention did not translate into greater memory. Older and younger adults had similar levels of memory for slow-paced messages, but younger adults outperformed older adults significantly as pacing increased, and the difference was larger for arousing compared with calm messages. The differences found are in line with predictions made based on the cognitive-aging literature.

PENERAPAN MODEL PEMBELAJARAN KOOPERATIF TIPE STAD DENGAN PENDEKATAN RME UNTUK MENINGKATKAN HASIL BELAJAR MATEMATIKA SISWA KELAS IX SMP MUHAMMADIYAH PADANG LUAS KECAMATAN TAMBANG KABUPATEN KAMPAR

2018 ◽  
Vol 2 (5) ◽  
pp. 744
Author(s):  
Zainur Zainur
Keyword(s):  
Action Research ◽  
Cooperative Learning ◽  
Student Learning ◽  
Learning Outcomes ◽  
Mathematics Learning ◽  
Student Learning Outcomes ◽  
Learning Model ◽  
Research Instrument ◽  
The Difference ◽  
Better Than

This research was motivated by the low learning outcomes of grade IX SMP Muhammadiyah Padang LuasKecamatan Tambang Kabupaten Kampar. This study aims to improve learning outcomes in mathematicslearning through STAD type cooperative learning with the RME approach in class IX SMP MuhammadiyahPadang Luas Kecamatan Tambang Kabupaten Kampar. The subjects of this study were all classes IX in SMPMuhammadiyah Padang Luas Kecamatan Tambang Kabupaten Kampar totaling 26 people. The form ofresearch is classroom action research. This research instrument consists of performance instruments and datacollection instruments in the form of teacher activity observation sheets and activities. The results of the studystated that there were significant differences between students' mathematics learning outcomes before applyingthe STAD type cooperative learning model with the RME approach with after applying the STAD typecooperative learning model with the RME approach. The difference shows student learning outcomes after theaction is better than before the action with completeness reaching 80.77% or 21 completed. Based on the resultsof the study and discussion it can be concluded that the application of STAD type learning model with RealisticMathematic Education (RME) approach can improve the learning outcomes of grade IX students of SMPMuhammadiyah Padang Luas Kecamatan Tambang Kabupaten Kampar on statistical material.

Sign in / Sign up

Export Citation Format

Share Document