免疫细胞浸润在非小细胞肺癌诊断与预后中的应用

免疫细胞浸润对癌症的诊断与预后有着重要意义。文中收集TCGA数据库已收录的非小细胞肺癌肿瘤与正常组织基因表达数据,利用CIBERSORT工具得到22种免疫细胞占比来评估免疫细胞浸润情况。以22种免疫细胞占比为特征,用机器学习方法构建了非小细胞肺癌肿瘤与正常组织的分类模型,其中随机森林方法构建的模型分类效果AUC=0.987、敏感性0.98及特异性0.84。并且用随机森林方法构建的肺腺癌和肺鳞癌肿瘤组织分类模型效果AUC=0.827、敏感性0.75及特异性0.77。用LASSO回归筛选22种免疫细胞特征,保留8种强相关特征组成的免疫细胞评分结合临床特征构建了非小细胞肺癌预后模型。经评估及验证,预后模型C-index=0.71并且3年和5年的校准曲线拟合良好,可以对预后风险度进行准确预测。本研究基于免疫细胞浸润所构建的分类模型与预后模型,旨在对非小细胞肺癌的诊断与预后研究提供新的策略。     

A single-spring model predicts the majority of variance in impact force during a fall onto the outstretched hand

The objective of this study was to validate a single-spring model in predicting measured impact forces during an outstretched arm falling scenario. Using an integrated force plate, impact forces were assessed from 10 young adults (5 males; 5 females), falling from planted knees onto outstretched arms, from a random order of drop heights: 3, 5, 7, 10, 15, 20, and 25 cm. A single-spring model incorporating body mass, drop height plus the estimated linear stiffness of the upper extremity (hand, wrist and arm) was used to predict impact force on the hand. We used an analysis of variance linearity test to test the validity of using a linear stiffness coefficient in the model. We used linear regression to assess variance (R²) in experimental impact force predicted by the single-spring model. We derived optimum linear stiffness coefficients for male, female and sex-combined. Our results indicated that the association between experimental and predicted impact forces was linear (P < 0.05). Explain variance in experimental impact force was R² = 0.82 for sex-combined, R² = 0.88 for males and R² = 0.84 for females. Optimum stiffness coefficients were 7436 N/m for sex-combined, 8989 N/m for males and 4527 N/m for females. In conclusion, a linear spring coefficient used in the single-spring model proved valid for predicting impact forces from fall heights up to 25 cm. Results also suggest the use of sex-specific spring coefficients when estimating impact force using the single-spring model. This model may improve impact force to bone strength ratios (factor-of-risk) and prediction of forearm and wrist fracture.     

The role of lipid second messengers in aldosterone synthesis and secretion

Second messengers are small rapidly diffusing molecules or ions that relay signals between receptors and effector proteins to produce a physiological effect. Lipid messengers constitute one of the four major classes of second messengers. The hydrolysis of two main classes of lipids, glycerophospholipids and sphingolipids, generate parallel profiles of lipid second messengers: phosphatidic acid (PA), diacylglycerol (DAG), and lysophosphatidic acid versus ceramide, ceramide-1-phosphate, sphingosine, and sphingosine-1-phosphate, respectively. In this review, we examine the mechanisms by which these lipid second messengers modulate aldosterone production at multiple levels. Aldosterone is a mineralocorticoid hormone responsible for maintaining fluid volume, electrolyte balance, and blood pressure homeostasis. Primary aldosteronism is a frequent endocrine cause of secondary hypertension. A thorough understanding of the signaling events regulating aldosterone biosynthesis may lead to the identification of novel therapeutic targets. The cumulative evidence in this literature emphasizes the critical roles of PA, DAG, and sphingolipid metabolites in aldosterone synthesis and secretion. However, it also highlights the gaps in our knowledge, such as the preference for phospholipase D-generated PA or DAG, as well as the need for further investigation to elucidate the precise mechanisms by which these lipid second messengers regulate optimal aldosterone production.     

An iterative learning strategy for the auto-tuning of the feedforward and feedback controller in type-1 diabetes

This paper proposes a scheme for the control of the blood glucose in subjects with type-1 diabetes mellitus based on the subcutaneous (s.c.) glucose measurement and s.c. insulin administration. The tuning of the controller is based on an iterative learning strategy that exploits the repetitiveness of the daily feeding habit of a patient. The control consists of a mixed feedback and feedforward contribution whose parameters are tuned through an iterative learning process that is based on the day-by-day automated analysis of the glucose response to the infusion of exogenous insulin. The scheme does not require any a priori information on the patient insulin/glucose response, on the meal times and on the amount of ingested carbohydrates (CHOs). Thanks to the learning mechanism the scheme is able to improve its performance over time. A specific logic is also introduced for the detection and prevention of possible hypoglycaemia events. The effectiveness of the methodology has been validated using long-term simulation studies applied to a set of nine in silico patients considering realistic uncertainties on the meal times and on the quantities of ingested CHOs.     

Can transposable element copy number distribution parameters be estimated from natural populations of Drosophila melanogaster?

The copy frequency distribution of a transposable element family in a Drosophila melanogaster natural population is generally characterised by the values of the Charlesworths' model parameters α and β (Charlesworth & Charlesworth, 1983). The estimation of these parameters is made using the observed distribution of the occupied sites in a population sample. Several results have been interpreted as due either to the influence of stochastic factors or to deterministic factors (transposition, excision, selection…). The accuracy of this method was tested by estimations performed on samples from simulated populations. The results show that with the sample size usually used for natural population studies, the confidence intervals are too large to reasonably deduce either the element copy number distribution or the values of transposition and excision rate and selective coefficients.     

Individual and simultaneous treatment with antipsychotic aripiprazole and antidepressant trazodone inhibit sterol biosynthesis in the adult brain

Polypharmacy, or the simultaneous use of multiple drugs to treat a single patient, is a common practice in psychiatry. Unfortunately, data on the health effects of commonly used combinations of medications are very limited. In this study, we therefore investigated the effects and interactions between two commonly prescribed psychotropic medications with sterol inhibiting side effects, trazodone (TRZ), an antidepressant, and aripiprazole (ARI), an antipsychotic. In vitro cell culture experiments revealed that both medications alone disrupted neuronal and astroglial sterol biosynthesis in dose-dependent manners. Furthermore, when ARI and TRZ were combined, exposure resulted in an additive 7-dehydrocholesterol (7-DHC) increase, as well as desmosterol (DES) and cholesterol decreases in both cell types. In adult mice, at baseline, we found that the three investigated sterols showed significant differences in distribution across the eight assessed brain regions. Furthermore, experimental mice treated with ARI or TRZ, or a combination of both medications for 8 days, showed strong sterol disruption across all brain regions. We show ARI or TRZ alone elevated 7-DHC and decreased DES levels in all brain regions, but with regional differences. However, the combined utilization of these two medications for 8 days did not lead to additive changes in sterol disturbances. Based on the complex roles of 7-DHC derived oxysterols, we conclude that individual and potentially simultaneous use of medications with sterol biosynthesis-inhibiting properties might have undesired side effects on the adult brain, with as yet unknown long-term consequences on mental or physical health.     

Identification of a four-gene metabolic signature predicting overall survival for hepatocellular carcinoma

While hundreds of consistently altered metabolic genes had been identified in hepatocellular carcinoma (HCC), the prognostic role of them remains to be further elucidated. Messenger RNA expression profiles and clinicopathological data were downloaded from The Cancer Genome Atlas—Liver Hepatocellular Carcinoma and GSE14520 data set from the Gene Expression Omnibus database. Univariate Cox regression analysis and lasso Cox regression model established a novel four-gene metabolic signature (including acetyl-CoA acetyltransferase 1, glutamic-oxaloacetic transaminase 2, phosphatidylserine synthase 2, and uridine-cytidine kinase 2) for HCC prognosis prediction. Patients in the high-risk group shown significantly poorer survival than patients in the low-risk group. The signature was significantly correlated with other negative prognostic factors such as higher α-fetoprotein. The signature was found to be an independent prognostic factor for HCC survival. Nomogram including the signature shown some clinical net benefit for overall survival prediction. Furthermore, gene set enrichment analyses revealed several significantly enriched pathways, which might help explain the underlying mechanisms. Our study identified a novel robust four-gene metabolic signature for HCC prognosis prediction. The signature might reflect the dysregulated metabolic microenvironment and provided potential biomarkers for metabolic therapy and treatment response prediction in HCC.     

Sinks and sources of methylmercury in a boreal catchment

A simple, catchment-scale, cascade model was used toassess the importance of sinks and sources ofmethylmercury (MeHg) in a boreal catchment thatcontains a forested upland, a lowland peatland and asmall lake. The three compartment model was run usingrealistic flow rates and atmospheric loading of MeHg,and the model was constrained by observedconcentrations of MeHg in each compartment. Assumingno internal sinks and sources of MeHg, modelledcatchment yields showed reasonable agreement withfield observation, but the predicted internal MeHgconcentrations in each compartment were implausible. Only when sources and sinks of MeHg are added to thethree compartments do MeHg-pool concentrations fallinto the range of those measured in the field. Tomaintain both catchment-scale and compartment-scalecontinuity, the upland and peatland were net sourcesof MeHg (0.0007 and 0.1065 mg ha^-1 d^-1respectively), and the lake a net sink (-0.2215 mgha^-1 d^-1). These source/sink rates are 1.73,259 and -539 times the input of MeHg via wetprecipitation input for the modelled ice-free season. Sensitivity analysis revealed that the volume ofrunoff delivered to the peatland by the upland area,peatland size and porewater MeHg concentration in thepeatland are important controls on catchment MeHgyield, and that contemporary atmospheric deposition ofMeHg is insignificant compared to the sources of MeHgwithin the catchment.     

Origins of regioselectivity in 1,3-dipolar cycloadditions of nitrile oxides with alkynylboronates

Density functional theory (M06-2X) studies of the regioselectivity of 1,3-dipolar cycloaddition reactions of benzo and mesitonitrile oxides with alkynyl pinacol and MIDA boronates are reported. Calculated relative free energies of activation reproduce the experimentally observed product ratios. The electronic energies of activation are found to be mainly controlled by distortion energies required to achieve the transition states. Both electronic and steric effects influence regioselectivities.