Predicting Space Radiation Single Ion Exposure in Rodents: A Machine Learning Approach.

This study presents a data-driven machine learning approach to predict individual Galactic Cosmic Radiation (GCR) ion exposure for 4He, 16O, 28Si, 48Ti, or 56Fe up to 150 mGy, based on Attentional Set-shifting (ATSET) experimental tests. The ATSET assay consists of a series of cognitive performance tasks on irradiated male Wistar rats. The GCR ion doses represent the expected cumulative radiation astronauts may receive during a Mars mission on an individual ion basis. The primary objective is to synthesize and assess predictive models on a per-subject level through Machine Learning (ML) classifiers. The raw cognitive performance data from individual rodent subjects are used as features to train the models and to explore the capabilities of three different ML techniques for elucidating a range of correlations between received radiation on rodents and their performance outcomes. The analysis employs scores of selected input features and different normalization approaches which yield varying degrees of model performance. The current study shows that support vector machine, Gaussian naive Bayes, and random forest models are capable of predicting individual ion exposure using ATSET scores where corresponding Matthews correlation coefficients and F1 scores reflect model performance exceeding random chance. The study suggests a decremental effect on cognitive performance in rodents due to ≤150 mGy of single ion exposure, inasmuch as the models can discriminate between 0 mGy and any exposure level in the performance score feature space. A number of observations about the utility and limitations in specific normalization routines and evaluation scores are examined as well as best practices for ML with imbalanced datasets observed.

Machine Learning Models to Predict Cognitive Impairment of Rodents Subjected to Space Radiation.

This research uses machine-learned computational analyses to predict the cognitive performance impairment of rats induced by irradiation. The experimental data in the analyses is from a rodent model exposed to ≤15 cGy of individual galactic cosmic radiation (GCR) ions: 4He, 16O, 28Si, 48Ti, or 56Fe, expected for a Lunar or Mars mission. This work investigates rats at a subject-based level and uses performance scores taken before irradiation to predict impairment in attentional set-shifting (ATSET) data post-irradiation. Here, the worst performing rats of the control group define the impairment thresholds based on population analyses via cumulative distribution functions, leading to the labeling of impairment for each subject. A significant finding is the exhibition of a dose-dependent increasing probability of impairment for 1 to 10 cGy of 28Si or 56Fe in the simple discrimination (SD) stage of the ATSET, and for 1 to 10 cGy of 56Fe in the compound discrimination (CD) stage. On a subject-based level, implementing machine learning (ML) classifiers such as the Gaussian naïve Bayes, support vector machine, and artificial neural networks identifies rats that have a higher tendency for impairment after GCR exposure. The algorithms employ the experimental prescreen performance scores as multidimensional input features to predict each rodent's susceptibility to cognitive impairment due to space radiation exposure. The receiver operating characteristic and the precision-recall curves of the ML models show a better prediction of impairment when 56Fe is the ion in question in both SD and CD stages. They, however, do not depict impairment due to 4He in SD and 28Si in CD, suggesting no dose-dependent impairment response in these cases. One key finding of our study is that prescreen performance scores can be used to predict the ATSET performance impairments. This result is significant to crewed space missions as it supports the potential of predicting an astronaut's impairment in a specific task before spaceflight through the implementation of appropriately trained ML tools. Future research can focus on constructing ML ensemble methods to integrate the findings from the methodologies implemented in this study for more robust predictions of cognitive decrements due to space radiation exposure.

Exposure to Low (≤10 cGy) Doses of 4He Particles Leads to Increased Social Withdrawal and Loss of Executive Function Performance.

Astronauts on the planned mission to Mars will be exposed to galactic cosmic radiation (GCR), with proton and He particles accounting (in approximately equal amounts) for ∼75% of the equivalent dose. Exposure to ≤15 cGy of space radiation ions with Z ≥ 15 particles has been shown to impair various executive functions, including attentional set shifting and creative problem-solving in rats. Executive functions also regulate social interactions and mood. Should space radiation exposure alter these executive functions as it does cognitive flexibility, there is the possibility of altered interactions among crew members and team cooperativity during prolonged space exploration. This study characterized the effects of ≤10 cGy 400 MeV/n of 4He particles on cognitive flexibility and social interaction (within freely interacting dyads) in male Wistar rats. Exposure to ≥1 cGy 4He ions induced deficits in the SD and/or CD stages of the attentional set shifting (ATSET) task, as reported after exposure to Z ≥ 15 space radiation ions. Should similar effects occur in astronauts, these data suggest that they would have a reduced ability to identify key events in a new situation and would be more easily distracted by extraneous variables. The irradiated rats were also screened for performance in a task for unconstrained cognitive flexibility (UCFlex), often referred to as creative problem-solving. There was a marked dose-dependent change in UCFlex performance with ∼30% of rats exposed to 10 cGy being unable to solve the problem, while the remaining rats took longer than the sham-irradiated animals to resolve the problem. Importantly, performance in the ATSET test was not indicative of UCFlex performance. From a risk assessment perspective, these findings suggest that a value based on a single behavioral end point may not fully represent the cognitive deficits induced by space radiation, even within the cognitive flexibility domain. Rats that received 5 cGy 4He ion irradiation had a significantly lower level of interaction toward their sham-irradiated partners in a non-anxiogenic (uncaged) dyad interactions study. This is consistent with the social withdrawal previously observed in space radiation-exposed male mice in a three-chamber test. 4He-irradiated rats exhibited a significantly higher incidence and duration of self-grooming, which is even more concerning, given that their dyad partners were able to physically interact with the irradiated rats (i.e., touching/climbing over them). This study has established that exposure of male rats to "light" ions such as He affects multiple executive functions resulting in deficits in both sociability and cognitive flexibility, and possibly affective behavior (reward valuation). Further studies are needed to determine if these space radiation-induced co-morbidities are concomitantly induced within individual rats.

Dot ELISA for measuring anti-Fasciola IgG isotypes among patients with fascioliasis.

Stool examination using modified Kato thick smear method was performed to detect Fasciola eggs and other parasites. Forty-five patients were proved to have Fasciola infection by passing eggs in their stool samples. Pallor was the major presenting symptom (95.5%) followed by abdominal pain (93.3%) and fever (15.5%). Hepatomegaly was recorded in 86.6% of patients compared to 33.3% with splenomegaly. Abdominal, ultrasonography revealed hepatomegaly in 38 cases (84.4%) and common bile duct dilatation in 35 patients (77.7%). Moreover, 4 cases showed Olympic game rings which are diagnostic. All of patients had positive IgG4 levels, 40 cases were found positives for specific total IgG and 42 cases for IgG1, whereas, only 30 cases had positive IgG2 levels (66.6%). Dot-ELISA showed that IgG2 and IgG4 giving the highest specificity (>99%), followed by IgG1 (90%) and the least specific test was obtained with detection of IgG (85%). From the present work, it was concluded that detection of anti-Fasciola isotypes especially IgG4 is very specific for accurate diagnosis of fascioliasis.