On maps preserving isosceles orthogonality in normed linear spaces

EnWe show that a linear map from a normed linear space X to another normed linear space Y preserves isosceles orthogonality if and only if it is a scalar multiple of a linear isometry

Temporal Changes in Energy-Balance Behaviors and Home Factors in Adolescents with Normal Weight and Those with Overweight or Obesity

This study aimed to examine the temporal changes in energy-balance behaviors and home factors in adolescents with normal weight and those with overweight or obesity (OWOB). Adolescents or parent proxies completed survey assessments two to four years before (T0; n = 82), ≤ six months before (T1; n = 68), and ≤ three months after the COVID-19 pandemic outbreak (T2; n = 82), to capture energy-balance behaviors (i.e., physical activity [PA], screen time, sleep) and home factors (i.e., food environment, food worry, parent support for PA). At T0 and T1 (before pandemic), participants visited our laboratory for anthropometric measurements. At T2, parent proxies also completed a survey to report the COVID-19 pandemic exposure and impact. The participating families experienced moderate levels of pandemic exposure and impact, although exposure was higher in the OWOB group (F1,78= 5.50, p \u3c .05). Repeated-measure multivariate analyses of covariance (RM-MACOVAs) did not show significant time by weight status interaction effects (p \u3e 0.05; adjusted for race and sex). However, the models detected significant time (T0 vs. T2) by race (White vs. non-White) interaction effect (λ7,66=0.81, p \u3c 0.05), with greater increase in food worry (F1,72 = 4.36, p \u3c .05) but less increase in screen time (F1,72= 4.54, p \u3c .05) among the non-White group. Graphical visualization depicted some favorable change patterns in adolescents with normal weight (vs. those with OWOB) for certain behaviors and home factors (e.g., number of days per week ≥ 60 mins PA, food worry). These findings suggest that the COVID-19 pandemic exerted greater adverse effects on adolescents with OWOB and specifically on screen time and food worry among non-White adolescents

The nuclear receptor LXRα controls the functional specialization of splenic macrophages.

Macrophages are professional phagocytic cells that orchestrate innate immune responses and have considerable phenotypic diversity at different anatomical locations. However, the mechanisms that control the heterogeneity of tissue macrophages are not well characterized. Here we found that the nuclear receptor LXRα was essential for the differentiation of macrophages in the marginal zone (MZ) of the spleen. LXR-deficient mice were defective in the generation of MZ and metallophilic macrophages, which resulted in abnormal responses to blood-borne antigens. Myeloid-specific expression of LXRα or adoptive transfer of wild-type monocytes restored the MZ microenvironment in LXRα-deficient mice. Our results demonstrate that signaling via LXRα in myeloid cells is crucial for the generation of splenic MZ macrophages and identify an unprecedented role for a nuclear receptor in the generation of specialized macrophage subsets

Bone Marrow-Derived Microglia-Based Neurturin Delivery Protects Against Dopaminergic Neurodegeneration in a Mouse Model of Parkinson\u27s Disease

Although neurotrophic factors have long been recognized as potent agents for protecting against neuronal degeneration, clinical success in treating Parkinson\u27s disease and other neurodegenerative disorders has been hindered by difficulties in delivery of trophic factors across the blood brain barrier (BBB). Bone marrow hematopoietic stem cell-based gene therapy is emerging as a promising tool for overcoming drug delivery problems, as myeloid cells can cross the BBB and are recruited in large numbers to sites of neurodegeneration, where they become activated microglia that can secrete trophic factors. We tested the efficacy of bone marrow-derived microglial delivery of neurturin (NTN) in protecting dopaminergic neurons against neurotoxin-induced death in mice. Bone marrow cells were transduced ex vivo with lentivirus expressing the NTN gene driven by a synthetic macrophage-specific promoter. Infected bone marrow cells were then collected and transplanted into recipient animals. Eight weeks after transplantation, the mice were injected with the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropuridine (MPTP) for seven days to induce dopaminergic neurodegeneration. Microglia-mediated NTN delivery dramatically ameliorated MPTP-induced degeneration of tyrosine hydroxylase (TH)-positive neurons of the substantia nigra and their terminals in the striatum. Microglia-mediated NTN delivery also induced significant recovery of synaptic marker staining in the striatum of MPTP-treated animals. Functionally, NTN treatment restored MPTP-induced decline in general activity, rearing behavior, and food intake. Thus, bone marrow-derived microglia can serve as cellular vehicles for sustained delivery of neurotrophic factors capable of mitigating dopaminergic injury

Mapping of spatiotemporal auricular electrophysiological signals reveals human biometric clusters

Underneath the ear skin there are rich vascular network and sensory nerve branches. Hence, the 3D mapping of auricular electrophysiological signals can provide new biomedical perspectives. However, it is still extremely challenging for current sensing techniques to cover the entire ultra-curved auricle. Here, a 3D graphene-based ear-conformable sensing device with embedded and distributed 3D electrodes for full-auricle physiological monitoring is reported. As a proof-of-concept, spatiotemporal auricular electrical skin resistance (AESR) mapping is demonstrated for the first time, and human subject-specific AESR distributions are observed. From the data of more than 30 ears (both right and left ears), the auricular region-specific AESR changes after cycling exercise are observed in 98% of the tests and are clustered into four groups via machine learning-based data analyses. Correlations of AESR with heart rate and blood pressure are also studied. This 3D electronic platform and AESR-based biometrical findings show promising biomedical applications

Principal variable selection to explain grain yield variation in winter wheat from features extracted from UAV imagery

Background: Automated phenotyping technologies are continually advancing the breeding process. However, collecting various secondary traits throughout the growing season and processing massive amounts of data still take great efforts and time. Selecting a minimum number of secondary traits that have the maximum predictive power has the potential to reduce phenotyping efforts. The objective of this study was to select principal features extracted from UAV imagery and critical growth stages that contributed the most in explaining winter wheat grain yield. Five dates of multispectral images and seven dates of RGB images were collected by a UAV system during the spring growing season in 2018. Two classes of features (variables), totaling to 172 variables, were extracted for each plot from the vegetation index and plant height maps, including pixel statistics and dynamic growth rates. A parametric algorithm, LASSO regression (the least angle and shrinkage selection operator), and a non-parametric algorithm, random forest, were applied for variable selection. The regression coefficients estimated by LASSO and the permutation importance scores provided by random forest were used to determine the ten most important variables influencing grain yield from each algorithm. Results: Both selection algorithms assigned the highest importance score to the variables related with plant height around the grain filling stage. Some vegetation indices related variables were also selected by the algorithms mainly at earlier to mid growth stages and during the senescence. Compared with the yield prediction using all 172 variables derived from measured phenotypes, using the selected variables performed comparable or even better. We also noticed that the prediction accuracy on the adapted NE lines (r = 0.58–0.81) was higher than the other lines (r = 0.21–0.59) included in this study with different genetic backgrounds. Conclusions: With the ultra-high resolution plot imagery obtained by the UAS-based phenotyping we are now able to derive more features, such as the variation of plant height or vegetation indices within a plot other than just an averaged number, that are potentially very useful for the breeding purpose. However, too many features or variables can be derived in this way. The promising results from this study suggests that the selected set from those variables can have comparable prediction accuracies on the grain yield prediction than the full set of them but possibly resulting in a better allocation of efforts and resources on phenotypic data collection and processing

The characteristics of impaired fasting glucose associated with obesity and dyslipidaemia in a Chinese population

<p>Abstract</p> <p>Background</p> <p>Different populations have diverse patterns of relationships between Impaired Fasting Glucose (IFG) and obesity and lipid markers, it is important to investigate the characteristics of associations between IFG and other related risk factors including body mass index (BMI), waist circumstance (WC), serum lipids and blood pressure (BP) in a Chinese population.</p> <p>Methods</p> <p>This was a case-control study of 648 IFG subjects and 1,296 controls derived from a large-scale, community-based, cross-sectional survey of 10,867 participants. Each subject received a face-to-face interview, physical examination, and blood tests, including fasting blood glucose and lipids. Student's <it>t</it>-test, Chi-square test, Spearman correlation and multiple logistic regressions were used for the statistical analyses.</p> <p>Results</p> <p>Fasting plasma glucose (FPG) was positively correlated with BMI, WC, systolic blood pressure (SBP), diastolic blood pressure (DBP), triglyceride (TG), and total cholesterol (TC), and was negatively correlated with high density lipoprotein-cholesterol (HDL-C) (all p < 0.05). BMI was more strongly correlated with IFG than with WC. The correlation coefficient of FPG was remarkably higher with TG (0.244) than with TC (0.134) and HDL-C (-0.192). TG was an important predictor of IFG, with odds ratios of 1.76 (95%CI: 1.31-2.36) for subjects with borderline high TG level (1.70 mmol/l ≤ TG < 2.26 mmol/l) and 3.13 (95% CI: 2.50-3.91) for those with higher TG level (TG ≥ 2.26 mmol/l), when comparing to subjects with TG < 1.70 mmol/l. There was a significant dose-response relationship between the number of abnormal variables and increased risk of IFG.</p> <p>Conclusions</p> <p>In this Chinese population, both BMI and WC were important predictors of IFG. Abnormal TG as a lipid marker was more strongly associated with IFG than were TC and HDL-C. These factors should be taken into consideration simultaneously for prevention of IFG.</p