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BackgroundWebsites and phone apps are increasingly used to track weights during weight loss interventions, yet the longitudinal accuracy of these self-reported weights is uncertain. ObjectiveOur goal was to compare the longitudinal accuracy of self-reported weights entered online during the course of a randomized weight loss trial to measurements taken in the clinic. We aimed to determine if accuracy of self-reported weight is associated with weight loss and to determine the extent of misclassification in achieving 5% weight loss when using self-reported compared to clinic weights. MethodsThis study examined the accuracy of self-reported weights recorded online among intervention participants in the Hopkins Practice-Based Opportunities for Weight Reduction (POWER) trial, a randomized trial examining the effectiveness of two lifestyle-based weight loss interventions compared to a control group among obese adult patients with at least one cardiovascular risk factor. One treatment group was offered telephonic coaching and the other group was offered in-person individual coaching and group sessions. All intervention participants (n=277) received a digital scale and were asked to track their weight weekly on a study website. Research staff used a standard protocol to measure weight in the clinic. Differences (self-reported weight – clinic weight) indicate if self-report under (-) or over (+) estimated clinic weight using the self-reported weight that was closest in time to the clinic weight and was within a window ranging from the day of the clinic visit to 7 days before the 6-month (n=225) and 24-month (n=191) clinic visits. The absolute value of the differences (absolute difference) describes the overall accuracy. ResultsUnderestimation of self-reported weights increased significantly from 6 months (mean -0.5kg, SD 1.0kg) to 24 months (mean -1.1kg, SD 2.0kg; P=.002). The average absolute difference also increased from 6 months (mean 0.7kg, SD 0.8kg) to 24 months (mean 1.3, SD 1.8kg; P

The mechanical properties of single flax fibers are characterized here as a function of dew retting. The fibers are measured using micromechanical and nanomechanical techniques over a large retting period (91 days). Damage-free single flax fibers in various stages of dew retting were manually extracted from retted flax plant stems. The flexural modulus and strength of the flax fibers were determined using micromechanical methods. The effective modulus of the outer surface of the single fibers was measured using AFM-based nanoindentation. The micromechanical methods revealed that the flexural modulus and strength of the manually extracted single fibers does not vary significantly as the retting progresses. The micromechanical methods revealed two distinct values of flexural strength in the fibers attributed to different failure modes. The values of these strengths do not vary significantly with retting or over-retting. The nanomechanical methods revealed that the effective modulus of the outer surface of the single fibers does evolve with retting. The physical/chemical origin of these observations remains to be established and could be the objective of future work.

Microparticles play a role in cardiovascular disease pathology. The flavanol-like epicatechin is increasingly considered due to its cardioprotective effects. The aim of this study was to investigate the impact of epicatechin on microparticle generation, phenotype and procoagulant properties. Plasma samples from 15 healthy subjects were incubated with increasing concentrations of epicatechin (1 to 100 μM). Then, the expression of glycoprotein IIb, phosphatidylserine (PS), glycoprotein Ib (GPIb) and P-selectin was assessed by flow cytometry analysis after (or not) platelet stimulation. Microparticle procoagulant activity was determined using ZymuphenTM MP and ZymuphenTM MP-TF for phospholipid and tissue factor content, and with thrombin generation (TG) assays for procoagulant function. Platelet microparticles that express GPIb (/µL) decreased from 20,743 ± 24,985 (vehicle) to 14,939 ± 14,333 (p = 0.6), 21,366 ± 16,949 (p = 0.9) and 15,425 ± 9953 (p < 0.05) in samples incubated with 1, 10 and 100 µM epicatechin, respectively. Microparticle concentration (nM PS) decreased from 5.6 ± 2.0 (vehicle) to 5.1 ± 2.2 (p = 0.5), 4.5 ± 1.5 (p < 0.05) and 4.7 ± 2.0 (p < 0.05) in samples incubated with 1, 10 and 100µM epicatechin, respectively. Epicatechin had no impact on tissue factor-positive microparticle concentration. Epicatechin decreased TG (endogenous thrombin potential, nM.min) from 586 ± 302 to 509 ± 226 (p = 0.3), 512 ± 270 (p = 0.3) and 445 ± 283 (p < 0.05). These findings indicate that epicatechin affects microparticle release, phenotype and procoagulant properties.

Abstract Accumulation in target cells is an essential pharmacokinetic step of targeted therapies. Tyrosine Kinase Inhibitors (TKI) against the BCR-ABL fusion protein in Chronic Phase-Chronic Myeloid Leukaemia (CP-CML) cells constitute a unique model in terms of efficacy, specificity, and in vivo demonstration of response heterogeneity by target cells. The overall therapeutic response to nilotinib is heterogeneous with no satisfactory explanation. To better understand the patients’ response heterogeneity, we quantified nilotinib uptake by primary CP-CML cells in standardized conditions using flow cytometry, which allowed also distinguishing mature (polymorphonuclear cells) from immature (CD34+) cells. Nilotinib was undetectable in 13.3% of PMN and 40% of CD34+ cells. Moreover, in CD34+ cells, intracellular nilotinib did not completely abolish BCR-ABL activity (monitored by CrkL phosphorylation inhibition), although nilotinib accumulated well in most CD34+ cell samples. Intracellular nilotinib concentration was inversely correlated with disease burden parameters, Sokal score, and early haematologic response at day 6 ± 1 only in PMN, suggesting an intrinsic ability to limit nilotinib entry in the forms with higher tumor cell burdenat diagnosis. These findings suggest that nilotinib accumulation in CP-CML cells is influenced by individual characteristics and intra-clonal heterogeneity, and might be used for pharmacokinetic studies and to assess the therapeutic response.

Acoustical tweezers can exert forces several orders of magnitude greater than optical tweezers but the absence of spatial selectivity and their limited resolution has prevented their use for many applications in microbiology. Here the authors perform spatially selective contactless manipulation and positioning of human cells.

Purpose: To develop machine learning models to predict regional and/or distant recurrence in patients with early-stage non-small cell lung cancer (ES-NSCLC) after stereotactic body radiation therapy (SBRT) using [18F]FDG PET/CT and CT radiomics combined with clinical and dosimetric parameters. Methods: We retrospectively collected 464 patients (60% for training and 40% for testing) from University Hospital of Liège and 63 patients from University Hospital of Brest (external testing set) with ES-NSCLC treated with SBRT between 2010 and 2020 and who had undergone pretreatment [18F]FDG PET/CT and planning CT. Radiomic features were extracted using the PyRadiomics toolbox®. The ComBat harmonization method was applied to reduce the batch effect between centers. Clinical, radiomic, and combined models were trained and tested using a neural network approach to predict regional and/or distant recurrence. Results: In the training (n = 273) and testing sets (n = 191 and n = 63), the clinical model achieved moderate performances to predict regional and/or distant recurrence with C-statistics from 0.53 to 0.59 (95% CI, 0.41, 0.67). The radiomic (original_firstorder_Entropy, original_gldm_LowGrayLevelEmphasis and original_glcm_DifferenceAverage) model achieved higher predictive ability in the training set and kept the same performance in the testing sets, with C-statistics from 0.70 to 0.78 (95% CI, 0.63, 0.88) while the combined model performs moderately well with C-statistics from 0.50 to 0.62 (95% CI, 0.37, 0.69). Conclusion: Radiomic features extracted from pre-SBRT analog and digital [18F]FDG PET/CT outperform clinical parameters in the prediction of regional and/or distant recurrence and to discuss an adjuvant systemic treatment in ES-NSCLC. Prospective validation of our models should now be carried out. [ABSTRACT FROM AUTHOR]

Cancer-associated fibroblasts (CAFs) are key actors in modulating the progression of many solid tumors, such as breast cancer (BC). Herein, we identify an integrin [alpha]11/PDGFR[beta]-positive CAF subset displaying tumor-promoting features in BC. In the preclinical MMTV-PyMT mouse model, integrin [alpha]11 deficiency led to a drastic reduction of tumor progression and metastasis. A clear association between integrin [alpha]11 and PDGFR[beta] was found at both transcriptional and histological levels in BC specimens. High stromal integrin [alpha]11/PDGFR[beta] expression was associated with high grades and poorer clinical outcome in human BC patients. Functional assays using 5 CAF subpopulations (1 murine, 4 human) revealed that integrin [alpha]11 promotes CAF invasion and CAF-induced tumor cell invasion upon PDGF-BB stimulation. Mechanistically, the proinvasive activity of integrin [alpha]11 relies on its ability to interact with PDGFR[beta] in a ligand-dependent manner and to promote its downstream JNK activation, leading to the production of tenascin C, a proinvasive matricellular protein. Pharmacological inhibition of PDGFR[beta] and JNK impaired tumor cell invasion induced by integrin [alpha][11.sup.+] CAFs. Collectively, our study uncovers an integrin [alpha][11.sup.+] subset of protumoral CAFs that exploits the PDGFR[beta]/JNK signaling axis to promote tumor invasiveness in BC., Introduction Breast cancer (BC) is the most common type of cancer and the second leading cause of cancer-related death in women worldwide. Despite increasing knowledge of BC biology and huge [...]

Abstract Background The major marker utilized to monitor COPD patients is forced expiratory volume in one second (FEV1). However, asingle measurement of FEV1 cannot reliably predict subsequent decline. Recent studies indicate that T lymphocytes and eosinophils are important determinants of disease stability in COPD. We therefore measured cytokine levels in the lung lavage fluid and plasma of COPD patients in order to determine if the levels of T cell or eosinophil related cytokines were predictive of the future course of the disease. Methods Baseline lung lavage and plasma samples were collected from COPD subjects with moderately severe airway obstruction and emphysematous changes on chest CT. The study participants were former smokers who had not had a disease exacerbation within the past six months or used steroids within the past two months. Those subjects who demonstrated stable disease over the following six months (ΔFEV1 % predicted = 4.7 ± 7.2; N = 34) were retrospectively compared with study participants who experienced a rapid decline in lung function (ΔFEV1 % predicted = -16.0 ± 6.0; N = 16) during the same time period and with normal controls (N = 11). Plasma and lung lavage cytokines were measured from clinical samples using the Luminex multiplex kit which enabled the simultaneous measurement of several T cell and eosinophil related cytokines. Results and Discussion Stable COPD participants had significantly higher plasma IL-2 levels compared to participants with rapidly progressive COPD (p = 0.04). In contrast, plasma eotaxin-1 levels were significantly lower in stable COPD subjects compared to normal controls (p < 0.03). In addition, lung lavage eotaxin-1 levels were significantly higher in rapidly progressive COPD participants compared to both normal controls (p < 0.02) and stable COPD participants (p < 0.05). Conclusion These findings indicate that IL-2 and eotaxin-1 levels may be important markers of disease stability in advanced emphysema patients. Prospective studies will need to confirm whether measuring IL-2 or eotaxin-1 can identify patients at risk for rapid disease progression.

Shrinkage estimates of small domain parameters typically use a combination of a noisy "direct" estimate that only uses data from a specific small domain and a more stable regression estimate. When the regression model is misspecified, estimation performance for the noisier domains can suffer due to substantial shrinkage toward a poorly estimated regression surface. In this article, we introduce a new class of robust, empirically-driven regression weights that target estimation of the small domain means under potential misspecification of the global regression model. Our regression weights are a convex combination of the model-based weights associated with the best linear unbiased predictor (BLUP) and those associated with the observed best predictor (OBP). The mixing parameter in this convex combination is found by minimizing a novel, unbiased estimate of the mean-squared prediction error for the small domain means, and we label the associated small domain estimates the "compromise best predictor," or CBP. Using a data-adaptive mixture for the regression weights enables the CBP to preserve the robustness of the OBP while retaining the main advantages of the EBLUP whenever the regression model is correct. We demonstrate the use of the CBP in an application estimating gait speed in older adults. for this article are available online. [ABSTRACT FROM AUTHOR]