Maximin projection learning for optimal treatment decision with heterogeneous individualized treatment effects

A salient feature of data from clinical trials and medical studies is inhomogeneity. Patients not only differ in baseline characteristics, but also in the way that they respond to treatment. Optimal individualized treatment regimes are developed to select effective treatments based on patient's heterogeneity. However, the optimal treatment regime might also vary for patients across different subgroups. We mainly consider patients’ heterogeneity caused by groupwise individualized treatment effects assuming the same marginal treatment effects for all groups. We propose a new maximin projection learning method for estimating a single treatment decision rule that works reliably for a group of future patients from a possibly new subpopulation. Based on estimated optimal treatment regimes for all subgroups, the proposed maximin treatment regime is obtained by solving a quadratically constrained linear programming problem, which can be efficiently computed by interior point methods. Consistency and asymptotic normality of the estimator are established. Numerical examples show the reliability of the methodology proposed

Characterization of Laser-Resistant Port Wine Stain Blood Vessels Using In Vivo Reflectance Confocal Microscopy.

Background and objectivesPort wine stain (PWS) is a congenital vascular malformation of the human skin. Laser is the treatment of choice for PWS. Laser-resistant PWS is one crucial factor accounting for inadequate treatment outcome, which needs to be fully characterized. This study aims to quantitatively characterize the morphology of laser-resistant PWS blood vessels in the upper papillary dermis using in vivo reflectance confocal microscopy (RCM).Study design/materials and methodsA total of 42 PWS subjects receiving laser treatment from August 2016 through July 2018 were enrolled into this study. Thirty-three subjects had facial PWS; nine had extremity PWS. All subject's PWS received multiplex 585/1,064 nm laser treatment. RCM images were taken before and after treatment. The density, diameter, blood flow, and depth of PWS blood vessels were analyzed.ResultsWe found 44.4% PWS on the extremities (four out of nine subjects) were laser-resistant, which was significantly higher (P < 0.001) when compared with those PWS on the face (15.2%, 5 out of 33 subjects). The laser-resistant facial PWS blood vessels had significantly higher blood flow (1.35 ± 0.26 U vs. 0.89 ± 0.22 U, P < 0.001), larger blood vessel diameters (109.60 ± 18.24 µm vs. 84.36 ± 24.04 µm, P = 0.033) and were located deeper in the skin (106.01 ± 13.87 µm vs. 87.82 ± 12.57 µm, P < 0.001) in the skin when compared with laser-responsive PWS on the face. The average PWS blood vessel density (17.01 ± 4.63/mm2 vs. 16.61 ± 4.44/mm2 , P = 0.857) was not correlated to the laser resistance.ConclusionsLaser-resistant PWS blood vessels had significantly higher blood flow, larger diameters, and were located deeper in the skin. RCM can be a valuable tool for a prognostic evaluation on laser-resistant lesions before treatment, thereby providing guidance for tailored laser treatment protocols, which may improve the therapeutic outcome. The limitations for this study include relative small sample size and acquisitions of different blood vessels before and after 2 months of treatment. Lasers Surg. Med. © 2019 Wiley Periodicals, Inc

Climate change impact on China food security in 2050

Climate change is now affecting global agriculture and food production worldwide. Nonetheless the direct link between climate change and food security at the national scale is poorly understood. Here we simulated the effect of climate change on food security in China using the CERES crop models and the IPCC SRES A2 and B2 scenarios including CO2 fertilization effect. Models took into account population size, urbanization rate, cropland area, cropping intensity and technology development. Our results predict that food crop yield will increase +3-11 % under A2 scenario and +4 % under B2 scenario during 2030-2050, despite disparities among individual crops. As a consequence China will be able to achieve a production of 572 and 615 MT in 2030, then 635 and 646 MT in 2050 under A2 and B2 scenarios, respectively. In 2030 the food security index (FSI) will drop from +24 % in 2009 to -4.5 % and +10.2 % under A2 and B2 scenarios, respectively. In 2050, however, the FSI is predicted to increase to +7.1 % and +20.0 % under A2 and B2 scenarios, respectively, but this increase will be achieved only with the projected decrease of Chinese population. We conclude that 1) the proposed food security index is a simple yet powerful tool for food security analysis; (2) yield growth rate is a much better indicator of food security than yield per se; and (3) climate change only has a moderate positive effect on food security as compared to other factors such as cropland area, population growth, socio-economic pathway and technology development. Relevant policy options and research topics are suggested accordingly

Formation of nanoripples on ZnO flat substrates and nanorods by gas cluster ion bombardment

Funding Information: This work was supported by the National Natural Science Foundation of China under grant 11875210, the Science and Technology Planning Project of Guangdong Province under grant 2018A050506082, China Postdoctoral Science Foundation under grant 2019M652687, and by the grant RFBR No.19-05-00554 in the part of the development of advanced approach to analysis of geochemical objects.In the present study Ar+ cluster ions accelerated by voltages in the range of 5-10 kV are used to irradiate single crystal ZnO substrates and nanorods to fabricate self-assembled surface nanoripple arrays. The ripple formation is observed when the incidence angle of the cluster beam is in the range of 30-70°. The influence of incidence angle, accelerating voltage, and fluence on the ripple formation is studied. Wavelength and height of the nanoripples increase with increasing accelerating voltage and fluence for both targets. The nanoripples formed on the flat substrates remind of aeolian sand ripples. The ripples formed at high ion fluences on the nanorod facets resemble well-ordered parallel steps or ribs. The more ordered ripple formation on nanorods can be associated with the confinement of the nanorod facets in comparison with the quasi-infinite surface of the flat substrates.publishersversionpublishe

Ginkgo biloba’s footprint of dynamic Pleistocene history dates back only 390,000 years ago

Background: At the end of the Pliocene and the beginning of Pleistocene glaciation and deglaciation cycles Ginkgo biloba went extinct all over the world, and only few populations remained in China in relict areas serving as sanctuary for Tertiary relict trees. Yet the status of these regions as refuge areas with naturally existing populations has been proven not earlier than one decade ago. Herein we elaborated the hypothesis that during the Pleistocene cooling periods G. biloba expanded its distribution range in China repeatedly. Whole plastid genomes were sequenced, assembled and annotated, and sequence data was analyzed in a phylogenetic framework of the entire gymnosperms to establish a robust spatio-temporal framework for gymnosperms and in particular for G. biloba Pleistocene evolutionary history. Results: Using a phylogenetic approach, we identified that Ginkgoatae stem group age is about 325 million years, whereas crown group radiation of extant Ginkgo started not earlier than 390,000 years ago. During repeated warming phases, Gingko populations were separated and isolated by contraction of distribution range and retreated into mountainous regions serving as refuge for warm-temperate deciduous forests. Diversification and phylogenetic splits correlate with the onset of cooling phases when Ginkgo expanded its distribution range and gene pools merged. Conclusions: Analysis of whole plastid genome sequence data representing the entire spatio-temporal genetic variation of wild extant Ginkgo populations revealed the deepest temporal footprint dating back to approximately 390,000 years ago. Present-day directional West-East admixture of genetic diversity is shown to be the result of pronounced effects of the last cooling period. Our evolutionary framework will serve as a conceptual roadmap for forthcoming genomic sequence data, which can then provide deep insights into the demographic history of Ginkgo

KMT2A promotes melanoma cell growth by targeting hTERT signaling pathway.

Melanoma is an aggressive cutaneous malignancy, illuminating the exact mechanisms and finding novel therapeutic targets are urgently needed. In this study, we identified KMT2A as a potential target, which promoted the growth of human melanoma cells. KMT2A knockdown significantly inhibited cell viability and cell migration and induced apoptosis, whereas KMT2A overexpression effectively promoted cell proliferation in various melanoma cell lines. Further study showed that KMT2A regulated melanoma cell growth by targeting the hTERT-dependent signal pathway. Knockdown of KMT2A markedly inhibited the promoter activity and expression of hTERT, and hTERT overexpression rescued the viability inhibition caused by KMT2A knockdown. Moreover, KMT2A knockdown suppressed tumorsphere formation and the expression of cancer stem cell markers, which was also reversed by hTERT overexpression. In addition, the results from a xenograft mouse model confirmed that KMT2A promoted melanoma growth via hTERT signaling. Finally, analyses of clinical samples demonstrated that the expression of KMT2A and hTERT were positively correlated in melanoma tumor tissues, and KMT2A high expression predicted poor prognosis in melanoma patients. Collectively, our results indicate that KMT2A promotes melanoma growth by activating the hTERT signaling, suggesting that the KMT2A/hTERT signaling pathway may be a potential therapeutic target for melanoma

Smoking and coronary artery disease risk in patients with diabetes: A Mendelian randomization study

BackgroundPrevious observational studies have shown an association between smoking and coronary artery disease (CAD) in patients with diabetes. Whether this association reflects causality remains unestablished. This study aimed to explore the causal effect of smoking on CAD in patients with diabetes.MethodsGenetic signatures for smoking were extracted from a large genome-wide association study (GWAS), consisted of up to 1.2 million participants. Four smoking phenotypes were included: smoking initiation, cigarettes per day, age at initiation of regular smoking, and smoking cessation. Genetic associations with CAD in patients with diabetes were extracted from another GWAS, which included 15,666 participants (3,968 CAD cases and 11,696 controls). The analyses were performed using the univariable and multivariable Mendelian randomization (MR) method.ResultsMR analysis revealed that smoking initiation was positively related to CAD risk in patients with diabetes (OR = 1.322, 95% CI = 1.114 – 1.568, P = 0.001), but this association was attenuated when adjusted for cardiovascular risk factors (OR = 1.212, 95% CI = 1.008 – 1.457, P = 0.041). Age at initiation of regular smoking was negatively related to CAD in patients with diabetes (OR = 0.214, 95% CI = 0.070 – 0.656, P = 0.007), but this association became insignificant when adjusted for cardiovascular risk factors.ConclusionsThis study supported the effect of smoking initiation on the risk of CAD in patients with diabetes

Metformin promotes the survival of transplanted cardiosphere-derived cells thereby enhancing their therapeutic effect against myocardial infarction

The CDC differentiation at 4 weeks after transplantation analyzed by immunostaining. A–C: Sections of hearts were immunostained with antibodies to (A) the cardiomyocyte marker tropomyosin, (B) the endothelial cell marker von-Willebrand Factor (vWF), and (C) the smooth muscle cell marker α-smooth muscle actin (α-SMA). Antibody to GFP was used for identifying surviving CDC-derived cells and DAPI was used for identifying nuclei. Scale bars = 20 μm. DAPI 4′,6-diamidino-2-phenylindole. (PDF 178 kb

Nomogram for Predicting the Severity of Coronary Artery Disease in Young Adults ≤45 Years of Age with Acute Coronary Syndrome

Background: A non-invasive predictive model has not been established to identify the severity of coronary lesions in young adults with acute coronary syndrome (ACS). Methods: In this retrospective study, 1088 young adults (≤45 years of age) first diagnosed with ACS who underwent coronary angiography were enrolled and randomized 7:3 into training or testing datasets. To build the nomogram, we determined optimal predictors of coronary lesion severity with the Least Absolute Shrinkage and Selection Operator and Random Forest algorithm. The predictive accuracy of the nomogram was assessed with calibration plots, and performance was assessed with the receiver operating characteristic curve, decision curve analysis and the clinical impact curve. Results: Seven predictors were identified and integrated into the nomogram: age, hypertension, diabetes, body mass index, low-density lipoprotein cholesterol, mean platelet volume and C-reactive protein. Receiver operating characteristic analyses demonstrated the nomogram’s good discriminatory performance in predicting severe coronary artery disease in young patients with ACS in the training (area under the curve 0.683, 95% confidence interval [0.645–0.721]) and testing (area under the curve 0.670, 95% confidence interval [0.611–0.729]) datasets. The nomogram was also well-calibrated in both the training (P=0.961) and testing (P=0.302) datasets. Decision curve analysis and the clinical impact curve indicated the model’s good clinical utility. Conclusion: A simple and practical nomogram for predicting coronary artery disease severity in young adults≤45 years of age with ACS was established and validated