Validation of scientific topic models using graph analysis and corpus metadata

Probabilistic topic modeling algorithms like Latent Dirichlet Allocation (LDA) have become powerful tools for the analysis of large collections of documents (such as papers, projects, or funding applications) in science, technology an innovation (STI) policy design and monitoring. However, selecting an appropriate and stable topic model for a specific application (by adjusting the hyperparameters of the algorithm) is not a trivial problem. Common validation metrics like coherence or perplexity, which are focused on the quality of topics, are not a good fit in applications where the quality of the document similarity relations inferred from the topic model is especially relevant. Relying on graph analysis techniques, the aim of our work is to state a new methodology for the selection of hyperparameters which is specifically oriented to optimize the similarity metrics emanating from the topic model. In order to do this, we propose two graph metrics: the first measures the variability of the similarity graphs that result from different runs of the algorithm for a fixed value of the hyperparameters, while the second metric measures the alignment between the graph derived from the LDA model and another obtained using metadata available for the corresponding corpus. Through experiments on various corpora related to STI, it is shown that the proposed metrics provide relevant indicators to select the number of topics and build persistent topic models that are consistent with the metadata. Their use, which can be extended to other topic models beyond LDA, could facilitate the systematic adoption of this kind of techniques in STI policy analysis and design.

     

Fat Distribution and Lipid Profile of Young Adults with Congenital Adrenal Hyperplasia Due to 21-Hydroxylase Enzyme Deficiency

We aimed to compare detailed fat distribution and lipid profile between young adults with congenital adrenal hyperplasia due to 21-hydroxylase enzyme deficiency and a control group. We also verified independent associations of treatment duration and daily hydrocortisone dose equivalent (HDE) with lipid profile within patients. This case–control study included 23 patients (7 male and 16 female) matched by an age range of young adults (18–31 years) with 20 control subjects (8 male and 12 female). Dual energy X-ray absorptiometry was used to measure the fat distribution. Male patients demonstrated elevated indices of fat mass for total (7.7 ± 2.1 vs. 4.5 ± 1.3 kg/m², p = 0.003), trunk (4.0 ± 1.2 vs. 2.2 ± 0.8 kg/m², p = 0.005), android (0.63 ± 0.24 vs. 0.32 ± 0.15 kg/m², p = 0.008), gynoid (1.34 ± 0.43 vs. 0.74 ± 0.24 kg/m², p = 0.005), arm (0.65 ± 0.16 vs. 0.39 ± 0.10 kg/m², p = 0.009), and leg regions (2.7 ± 0.8 vs. 1.6 ± 0.4 kg/m², p = 0.005) than the control group, but not in females. However, female patients demonstrated elevated ratio of low-density lipoprotein cholesterol to high-density lipoprotein cholesterol (1.90 ± 0.46 vs. 1.39 ± 0.47, p = 0.009) than the control group, but not in males. Total fat mass was inversely correlated with total testosterone (r = −0.64, p = 0.014) and positively correlated with leptin in males (r = 0.75, p = 0.002). An elevated daily HDE (β = 0.43, p = 0.038 and β = 0.47, p = 0.033) and trunk to total fat mass ratio (β = 0.46, p = 0.025, and β = 0.45, p = 0.037) were independently correlated with impaired lipid profile markers. Although there is no altered lipid profile, male patients demonstrated an increased fat distribution. However, female patients presented with an impaired lipid profile marker but demonstrated close values of normal fat distribution. Interestingly, the dose of glucocorticoid therapy can have some role in the lipid mechanisms.     

超亲水毛细芯环路热管启动及热性能分析

为解决电子设备高热通量下的散热问题，采用H₂O₂氧化法对烧结毛细芯进行了超亲水改性，研究了毛细芯表面润湿性对吸液性能的影响。并将改性后的超亲水毛细芯应用到环路热管内，研究了倾斜角度及加热功率对超亲水毛细芯环路热管的换热特性的影响。实验结果表明：超亲水毛细芯的吸液速度增加，吸液时间较亲水毛细芯减小了3.52ms；与普通亲水毛细芯环路热管相比，在加热功率Q=200W时，超亲水毛细芯环路热管蒸发器中心温度降低了约6.0℃，在Q=20W时启动时间与温度分别降低了33s与2.5℃。同时发现超亲水毛细芯环路热管在正重力状态时的运行温度更低，热阻较小，最低热阻仅为0.084℃/W。     

A Fluorometric Enzymatic Assay for Quantification of Steryl Glucosides in Biodiesel

Steryl glucosides (SG) are common contaminants in biodiesel that form precipitates, which form and cause problems due to fouling during transport and storage. Therefore, their quantification is necessary to assess the quality of this fuel. The methods currently available for SG analysis require expensive instrumentation, need a previous concentration step by solid‐phase extraction (SPE) or are of limited use for the quantitative assessment. We developed an enzymatic method for SG quantification in biodiesel samples based on the hydrolysis of the glucoside catalyzed by a broadly specific beta glucosidase and the subsequent determination of the glucose released by the reaction. The method is non‐expensive, sensitive and was adapted to 96‐well format fluorescence plate reader, making it useful for the parallel assay of multiple samples. The enzymatic assay presented here represent a valuable tool for both quality control and the development of improved biodiesel production and purification procedures.     

The Gut Microbiota: A Potential Gateway to Improved Health Outcomes in Breast Cancer Treatment and Survivorship

Breast cancer is the most frequently diagnosed cancer in women worldwide. The disease and its treatments exert profound effects on an individual’s physical and mental health. There are many factors that impact an individual’s risk of developing breast cancer, their response to treatments, and their risk of recurrence. The community of microorganisms inhabiting the gastrointestinal tract, the gut microbiota, affects human health through metabolic, neural, and endocrine signaling, and immune activity. It is through these mechanisms that the gut microbiota appears to influence breast cancer risk, response to treatment, and recurrence. A disrupted gut microbiota or state of ‘dysbiosis’ can contribute to a biological environment associated with higher risk for cancer development as well as contribute to negative treatment side-effects. Many cancer treatments have been shown to shift the gut microbiota toward dysbiosis; however, the microbiota can also be positively manipulated through diet, prebiotic and probiotic supplementation, and exercise. The objective of this review is to provide an overview of the current understanding of the relationship between the gut microbiota and breast cancer and to highlight potential strategies for modulation of the gut microbiota that could lead to improved clinical outcomes and overall health in this population.