The Bayesian Paradigm and Tree Diagrams with Applications in Genetics

Probability tree diagrams are developed for the calculation and interpretation of conditional probabilities. Their use in Bayesian calculations and, most importantly, for the correct interpretation of results is described. Key practical applications to linkage analysis and evaluation of evidentiary DNA material given.     

Responses to temperature and salinity by White Mullet Mugil curema: Possible explanation for the population decrease in Baja California Sur

The white mullet Mugil curema is distributed along the Gulf of Mexico and Pacific coasts and constitutes an important food resource in Mexico. However, during recent years the capture of this mugilid has decreased considerably, especially in Bahía and Ensenada de La Paz, Baja California Sur, Mexico. The effects of different levels of temperature (22, 26, and 30°C) and salinity (15, 25, and 35) on the instantaneous growth rate, energy content, and condition factor of early juveniles of Mugil curema were evaluated. Fish showed a lower growth rate, lower body energy content, and a less condition factor when exposed to high salinity and temperature. On the basis to the results obtained and considering the unusual extreme temperatures and salinity registered in Ensenada de La Paz, it is expected low functional performance of juvenile mullets beyond the overfishing might contribute to the population decrease of this resource.     

A comparative evaluation of neural network classifiers for stress level analysis of automotive drivers using physiological signals

Automotive driving under unacceptable levels of accumulated stress deteriorates their vehicle control and risk-assessment capabilities often inviting road accidents. Design of a safety-critical wearable driver assist system for continuous stress level monitoring requires development of an intelligent algorithm capable of recognizing the drivers’ affective state and cumulatively account for increasing stress level. Task induced modifications in rhythms of physiological signals acquired during a real-time driving are clinically proven hallmarks for quantitative analysis of stress and mental fatigue. The present work proposes a neural network driven based solution to learning driving-induced stress patterns and correlating it with statistical, structural and time-frequency changes observed in the recorded biosignals. Physiological signals like Galvanic Skin Response (GSR) and Photoplethysmography (PPG) were selected for the present work. A comprehensive performance analysis on the selected neural network configurations (both Feed forward and Recurrent) concluded that Layer Recurrent Neural Networks are most optimal for stress level detection. This evaluation achieved an average precision of 89.23%, sensitivity of 88.83% and specificity of 94.92% when tested over 19 automotive drivers. The biofeedback inferred about the driver's ongoing physiological state using this neural network based inference engine would provide crucial information to on-board safety embedded systems to activate accordingly. It is envisaged that such a driver-centric safety system will help save precious lives by way of providing fast and credible real-time alerts to drivers and their coupled cars.     

Model identification and physiological control of xylitol production using Debaryomyces hansenii

The control of xylitol production from xylose-grown Debaryomyces hansenii yeast, which is a very complex biological process, usually requires accurate and demanding analytical HPLC measurements. For this reason, estimating relationships of the main variables of the fermentation process-concentration of xylitol, biomass and xylose-are suggested and studied in this article. The volume of added base for maintaining pH at the prescribed level has been shown to be important for approximate assessment of the biomass concentration and, therefore, for all estimation relationships. Furthermore, replacement of expensive off-line HPLC analyses of xylose by an on-line determined respiratory quotient RQ for control purposes is discussed. On the basis of this, physiological control of xylitol production which takes advantage of on-line classification of the different metabolic states of the culture from easily and cheaply measured variables, has been developed. Data and knowledge obtained from several experiments were evaluated for this reason and results are presented.     

The hierarchical metaregression approach and learning from clinical evidence

The hierarchical metaregression (HMR) approach is a multiparameter Bayesian approach for meta‐analysis, which generalizes the standard mixed effects models by explicitly modeling the data collection process in the meta‐analysis. The HMR allows to investigate the potential external validity of experimental results as well as to assess the internal validity of the studies included in a systematic review. The HMR automatically identifies studies presenting conflicting evidence and it downweights their influence in the meta‐analysis. In addition, the HMR allows to perform cross‐evidence synthesis, which combines aggregated results from randomized controlled trials to predict effectiveness in a single‐arm observational study with individual participant data (IPD). In this paper, we evaluate the HMR approach using simulated data examples. We present a new real case study in diabetes research, along with a new R package called jarbes (just a rather Bayesian evidence synthesis), which automatizes the complex computations involved in the HMR.     

Three dimensional printing as an effective method of producing anatomically accurate models for studies in thermal ecology

Hollow copper models painted to match the reflectance of the animal subject are standard in thermal ecology research. While the copper electroplating process results in accurate models, it is relatively time consuming, uses caustic chemicals, and the models are often anatomically imprecise. Although the decreasing cost of 3D printing can potentially allow the reproduction of highly accurate models, the thermal performance of 3D printed models has not been evaluated. We compared the cost, accuracy, and performance of both copper and 3D printed lizard models and found that the performance of the models were statistically identical in both open and closed habitats. We also find that 3D models are more standard, lighter, durable, and inexpensive, than the copper electroformed models.     

Effects of oocyte vitrification on the behaviors and physiological indexes of aged first filial generation mice

To evaluate the long-term effects of oocyte cryopreservation on the health of the first filial generation (F1), we used B6D2F1 mice for oocyte collection, in vitro fertilization, and breeding. The female F1 mice born from the offspring of fresh mature oocytes (control group) and from the offspring of vitrified oocytes with traditional vitrification medium (VM group) and new improved vitrification medium (2P10E7D group) were maintained until 14–15 months of age for behavioral tests and 16–17 months of age for physiological analyses. Behavioral indexes, including anxiety-like status, discrimination ability, learning and memory ability, were investigated. Physiological indexes including body weight, body fat, heart rate, blood pressure, and blood lipids were also analyzed. In our results, the behavioral indexes, body weight, body fat, heart rate, blood pressure, total cholesterol (TC), high-density lipoprotein cholesterol (HDL), and low-density lipoprotein cholesterol (LDL) did not show significant differences among the three groups. However, the triglyceride (TG) level of the VM group was higher than that of the 2P10E7D group. Moreover, compared with the control group, both the VM group and the 2P10E7D group showed greatly increased diastolic blood pressure. This study is the first to report that oocyte vitrification might affect metabolic physiological indexes via transgenerational inheritance rather than behaviors related to anxiety-like status and cognitive ability. Furthermore, different vitrification media might have differential transgenerational effects.     

Physiological and biochemical response of different resistant alfalfa cultivars against thrips damage

To investigate physiological and biochemical changes of thrips-resistant alfalfa (Medicago sativa L. cv. Gan-nong No. 9), we aimed at clarifying the response mechanisms of alfalfa against thrips. Medicago sativa L. cv. including thrips-resistant Gan-nong No.9 (G9), thrips-susceptible Gan-nong No.3 (G3) and highly thrips-susceptible WL363HQ (363) were infested with different thrips densities (3, 5, 7 and 9-thrips per branch). The quantitative change in specific nutrients, secondary metabolites, defensive and antioxidant enzymes were measured at seedling stage of the three alfalfa cultivars. The results showed that with the increase of thrips densities, the damage indices, SS, Pro, flavonoids, tannin and H₂O₂ in G9, G3 and 363 were significantly increased, but PPO and SOD significantly reduced, compared with CK. Furthermore, the tannin and lignin contents of G9 were significantly higher compared to 363, but SP content was significantly lower than G3 and H₂O₂ content which was further significantly less compared to 363. Correlation analysis observed that the damage index of the three alfalfa cultivars showed a significant positive association with SS, Pro, flavone, tannin, and H₂O₂ (P < 0.01), while damage index and DW, Chl (a, b, a + b), PPO and SOD showed a significant negative correlation (P < 0.01). Based on principal component comprehensive evaluation, the 5-thrips adults per branch were the critical inoculation threshold for G9 against thrips injury because the score was – 0.048. These results revealed that thrips damage significantly increased the contents of SS, Pro, flavonoids, tannins and H₂O₂, as well as significantly declined the activities of PPO and SOD in the three cultivars (P < 0.05), moreover, thrips-resistant G9 markedly accumulated lignin content, POD and CAT activity, inhibited Chl (a + b, b) and SP biosynthesis to resist thrips damage.