太空生存太空生存太空生存 (45).pdf
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1、Contents lists available at ScienceDirectActa Astronauticajournal homepage: phenotypes and urinary metabolites associated with thepsychological changes of healthy human:A study in lunar palace 365”Zikai Haoa,b,Siyuan Fenga,b,Yinzhen Zhua,b,Jianlou Yanga,b,Chen Menga,b,Dawei Hua,b,d,Hui Liua,d,Hong L
2、iua,b,c,d,aBeijing Advanced Innovation Centre for Biomedical Engineering,Beihang University,Beijing,100083,ChinabInstitute of Environmental Biology and Life Support Technology,School of Biological Science and Medical Engineering,Beihang University,Beijing,100083,ChinacState Key Laboratory of Virtual
3、 Reality Technology and Systems,School of Computer Science and Engineering,Beihang University,Beijing,100083,ChinadInternational Joint Research Center of Aerospace Biotechnology&Medical Engineering,Beihang University,Beijing,100083,ChinaA R T I C L E I N F OKeywords:Lunar palace 365Psychological cha
4、ngesPhysiological phenotypesUrinary metabolitesCorrelation analysisBLSSLong-time isolationA B S T R A C TMental health of the crewmembers is crucial to the success of the task during long-duration space explorationmissions,especially in isolated and confined environments.The ability to recognize men
5、tal states is essential toeffectively help safeguard mental health.However,the current recognition of the mental status is still based onrelatively subjective assessment of symptoms as well as psychometric evaluations,lacking objective recognitionmethods.Fortunately,the“Lunar Palace 365”experiment o
6、ffers us a precious opportunity to study the objectiverecognition indicators such as physiological phenotypes and urinary metabolites associated with the psycholo-gical changes of crewmembers in isolated and confined environments.In this study,28 phenotypic measure-ments were recorded daily.Psycholo
7、gical measurements were completed 12 times per week with the symptomchecklist 90(SCL-90)and profile of mood states(POMS)questionnaires,while 24-h urine samples were collectedfor metabolomics analysis on the day of psychological measurement.Spearmans correlation analysis was per-formed to identify po
8、tential physiological phenotypes and urine metabolic markers associated with mentalchanges.In this study,all crewmembers showed neither behavioral disturbances nor reports of psychologicaldistress during the 370-day period of mission confinement.Psychological changes showed significant individualdif
9、ferences,but there were consistent and large fluctuations during the mission transitions and when en-countering critical events such as power failures and“covering windows”.Crewmembers had lower negativemood scores and higher positive mood scores when they performed their missions the second time th
10、an the first.Significant gender differences were found in psychological scores,physiological phenotypes,and urinary me-tabolites.Spearman correlation analysis showed 11 physiological phenotypes(|R|0.4,P 0.5,P 3 wereselected as the key urinary metabolites for Spearmans correlationanalysis.The predict
11、ability was also evaluated by the Spearmans cor-relation coefficient(R)and P-value between predicted and observedemotion subscales score.To analyze gender differences,we divided the samples into twogroups by gender and analyzed them using Principal component ana-lysis(PCA).PCA is the simplest of the
12、 true eigenvector-based multi-variate analyses.Often,its operation can be thought of as revealing theinternal structure of the data in a way that best explains the variance inthe data.If a multivariate dataset is visualised as a set of coordinates ina high-dimensional data space(1 axis per variable)
13、,PCA can supply theuser with a lower-dimensional picture,a projection of this object whenviewed from its most informative viewpoint 26.In the study,psy-chological data,phenotypic data,and urine metabolite data includemultiple factors,which are high-dimensional data.Using PCA analysiscan reduce the d
14、imensions and more easily see the individual andgender differences.The statistical significance of the separation amonggroupswasthenassessedbyMultivariateanalysisofvariance(MANOVA)based on Mahalanobis distances using the PCA scores.Theclusters are computed by applying the single linkage method to th
15、ematrix of Mahalanobis distances between group means.To analyzewhether there was a trend change of the crewmembers emotions fromthe normal stage into“covering windows”stage,we performed a Mann-Kendall trend test 27,28 using the psychological data from the 3weeks before and during the“covering window
16、s”stage.All the date wasnormalized through quotient transformation(x/mean)and log2-trans-formed before the analysis with MATLAB(version R2012b,The Math-Works Inc.,Natick,MA,USA).For each time series data,we performedrange scaling(mean-centered and divided by the range of each vari-able)to scale the
17、data.All PLS,PCA,Mann-Kendall trend test andcorrelation methods were performed with MATLAB.3.Results3.1.Individual psychological changeIn total,we obtained 476 profiles of SCL-90 questionnaires and 497profiles of POMS questionnaires from the eight crewmembers in thisstudy.Through the analysis of the
18、 questionnaire data and interviewrecords,we recognized the changes in the mental states of the crew-members,the results are shown in Fig.2.Eight crewmembers showedneither psychological disturbances nor reports of psychological distressduring the whole experiment.Crewmembers A,B,C and D of Group 1par
19、ticipated in the first phase(060th day)and the third phase(260370th day)experiment,and Crewmembers E,F,G and H of Group2 participated in the second phase of the experiment(60260th day).Ascan be seen from Fig.2,the psychological changes of each crewmembersuggested substantial inter-individual differe
20、nces.However,during themission transition(several weeks before and after entering and exitingthe LP1)the crewmembers showed consistent psychological fluctua-tions.A Total Mood Disturbance(TMD)score is also calculated by sum-ming the five negative mood scores and subtracting the two positivemood(vigo
21、r-activity and self-esteem)23.SUM-SCL score is the sum ofthe 11 subscales of the SCL-90.High TMD and SUM-SCL scores usuallyindicates high negative mood scores or lower positive mood scores.Thealterations of the TMD and SUM-SCL scores were also reflected in thesubscales scores(see Supplementary Figs.
22、S1 and S2).For example,theincrease in TMD scores of crewmember E and F during the 150200thday period was due to the increase in negative psychological scores andthe decrease in positive psychological scores,while the increase inSUM-SCL score was due to the increased in most subscales scores.Fig.2A a
23、nd B showed crewmember A had the highest TMD and SUM-SCL scores and crewmember D had the lowest scores in Group 1.Fig.2Cand D showed female crewmember E had the higher TMD and SUM-SCLscores than the rest crewmembers in Group 2.Interestingly,the psy-chological fluctuations of female crewmembers(E and
24、 F)were sig-nificant greater than male crewmembers(G and H),and male crew-members showed relatively stable mental states compared to femaleduring the isolation period.In order to further analyze the individualdifferences in psychological fluctuations,we performed a kruskal-wallisrank sum test on the
25、 psychological score changes of each crewmember,as shown in the Supplementary Table S3.Results suggested that onmost the subscale scores of the POMS and SCL90,the strength of theZ.Hao,et al.Acta Astronautica 176(2020)132316crewmembers psychological fluctuations was ranked as crewmemberE F G H.In ord
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