Multi-linear regression
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A new method of the chlorophyll (Chl) a fluorescence quenching analysis is described, which allows the calculation of values of (at least) three components of the non-photochemical quenching of the variable Chl a fluorescence (q (N)) using a non-linear regression of a multi-exponential function within experimental data. Formulae for coefficients of the "energy"-dependent (DeltapH-dependent) quenching (q (E)), the state-transition quenching (q (T)) and the photo/inhibitory quenching (q (I)) of Chl a fluorescence were found on the basis of three assumptions: (i) the dark relaxation kinetics of q (N), as well as of all its components, is of an exponential nature, (ii) the superposition principle is valid for individual Chl a fluorescence quenching processes and (iii) the same reference fluorescence level (namely the maximum variable Chl a fluorescence yield in the dark-adapted state, F (V)) is used to define both q (N) and its components. All definitions as well as the algorithms for analytical recognition of the q (N) components are theoretically clarified and experimentally tested. The described theory results in a rather simple equation allowing to compute values for all q (N) components (q (E), q (T), q (I)) as well as the half-times of relaxation (tau(1/2)) of corresponding quenching processes. It is demonstrated that under the above assumptions it holds: q (N) = q (E) + q (T) + q (I). The theoretically derived equations are tested, and the results obtained are discussed for non-stressed and stressed photosynthetically active samples. Semi-empirical formulae for a fast estimation of values of the q (N) components from experimental data are also given.
Texts in statistical science
2nd ed. vii, 225 s.
A sensitive assay for direct determination of intracellular level of daunorubicin (DRN) in resistant leukemia cells with overexpressed P-glycoprotein has been developed. This assay is based on a rapid separation of cells from media and fast cut-off of DRN transportation by centrifugation of cells through a layer of silicone oil. Cell pellets were extracted using 1% (v/v) formic acid in 50% (v/v) ethanol in water. The cell extracts were subsequently analysed by liquid chromatography (HPLC) coupled a low-energy collision tandem mass spectrometer equipped with an electrospray ionization source (ESI-CID-MS/MS) operated in the multiple-reaction monitoring (MRM) mode. Calibration curve was linear from 0.4 to 250nM with correlation coefficient (r²) better than 0.998. The limit of quantitation (LOQ) was 0.4 nM. The assay has been successfully applied to a determination of intracellular content of daunorubicin in sensitive K562 and resistant K562/Dox and K562/HHT300 cells.
- MeSH
- buňky K562 MeSH
- chemorezistence MeSH
- chronická myeloidní leukemie farmakoterapie metabolismus MeSH
- daunomycin analýza farmakokinetika MeSH
- DNA nádorová analýza MeSH
- fluorescence MeSH
- intracelulární prostor chemie metabolismus MeSH
- lidé MeSH
- lineární modely MeSH
- mnohočetná léková rezistence MeSH
- protinádorová antibiotika analýza farmakokinetika MeSH
- průtoková cytometrie MeSH
- senzitivita a specificita MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
BACKGROUND: Genomic selection (GS) can offer unprecedented gains, in terms of cost efficiency and generation turnover, to forest tree selective breeding; especially for late expressing and low heritability traits. Here, we used: 1) exome capture as a genotyping platform for 1372 Douglas-fir trees representing 37 full-sib families growing on three sites in British Columbia, Canada and 2) height growth and wood density (EBVs), and deregressed estimated breeding values (DEBVs) as phenotypes. Representing models with (EBVs) and without (DEBVs) pedigree structure. Ridge regression best linear unbiased predictor (RR-BLUP) and generalized ridge regression (GRR) were used to assess their predictive accuracies over space (within site, cross-sites, multi-site, and multi-site to single site) and time (age-age/ trait-trait). RESULTS: The RR-BLUP and GRR models produced similar predictive accuracies across the studied traits. Within-site GS prediction accuracies with models trained on EBVs were high (RR-BLUP: 0.79-0.91 and GRR: 0.80-0.91), and were generally similar to the multi-site (RR-BLUP: 0.83-0.91, GRR: 0.83-0.91) and multi-site to single-site predictive accuracies (RR-BLUP: 0.79-0.92, GRR: 0.79-0.92). Cross-site predictions were surprisingly high, with predictive accuracies within a similar range (RR-BLUP: 0.79-0.92, GRR: 0.78-0.91). Height at 12 years was deemed the earliest acceptable age at which accurate predictions can be made concerning future height (age-age) and wood density (trait-trait). Using DEBVs reduced the accuracies of all cross-validation procedures dramatically, indicating that the models were tracking pedigree (family means), rather than marker-QTL LD. CONCLUSIONS: While GS models' prediction accuracies were high, the main driving force was the pedigree tracking rather than LD. It is likely that many more markers are needed to increase the chance of capturing the LD between causal genes and markers.
- MeSH
- dřevo chemie genetika MeSH
- exom * MeSH
- genomika MeSH
- genotyp MeSH
- lineární modely MeSH
- lokus kvantitativního znaku MeSH
- modely genetické * MeSH
- Pseudotsuga genetika růst a vývoj MeSH
- selekce (genetika) * MeSH
- šlechtění rostlin * MeSH
- vysoce účinné nukleotidové sekvenování MeSH
- Publikační typ
- časopisecké články MeSH
OBJECTIVE: Age-at-death estimation is usually done manually by experts. As such, manual estimation is subjective and greatly depends on the past experience and proficiency of the expert. This becomes even more critical if experts need to evaluate individuals with unknown population affinity or with affinity that they are not familiar with. The purpose of this study is to design a novel age-at-death estimation method allowing for automatic evaluation on computers, thus eliminating the human factor. METHODS: We used a traditional machine-learning approach with explicit feature extraction. First, we identified and described the features that are relevant for age-at-death estimation. Then, we created a multi-linear regression model combining these features. Finally, we analysed the model performance in terms of Mean Absolute Error (MAE), Mean Bias Error (MBE), Slope of Residuals (SoR) and Root Mean Squared Error (RMSE). RESULTS: The main result of this study is a population-independent method of estimating an individual's age-at-death using the acetabulum of the pelvis. Apart from data acquisition, the whole procedure of pre-processing, feature extraction and age estimation is fully automated and implemented as a computer program. This program is a part of a freely available web-based software tool called CoxAGE3D, which is available at https://coxage3d.fit.cvut.cz/. Based on our dataset, the MAE of the presented method is about 10.7 years. In addition, five population-specific models for Thai, Lithuanian, Portuguese, Greek and Swiss populations are also given. The MAEs for these populations are 9.6, 9.8, 10.8, 10.5 and 9.2 years, respectively. Our age-at-death estimation method is suitable for individuals with unknown population affinity and provides acceptable accuracy. The age estimation error cannot be completely eliminated, because it is a consequence of the variability of the ageing process of different individuals not only across different populations but also within a certain population.
- MeSH
- acetabulum * diagnostické zobrazování MeSH
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- lineární modely MeSH
- mladý dospělý MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- software * MeSH
- soudní antropologie * metody MeSH
- strojové učení * MeSH
- určení kostního věku * metody MeSH
- zobrazování trojrozměrné * MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladý dospělý MeSH
- mužské pohlaví MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
BACKGROUND: In older adults, sedentary behaviors increase while physical activity decreases over time following the compositional nature of 24-h behaviors. These changes in movement-related behaviors (MRBs) might be associated with unhealthy weight gain and several health comorbidities. However, information is lacking on how obesity influences longitudinal changes in the composition of MRBs in older adults. Furthermore, the moderating effect of the built environment on prospective associations between obesity and MRBs in older adults is not fully understood. Therefore, using an integrated time-use approach, this study aims to identify prospective associations between obesity and MRBs together with an assessment of the moderating effect of the built environment in elderly women. METHODS: The study was designed as a prospective 7-year follow-up study. It is based on two previous cross-sectional studies that enable the use of participant data (women aged 60+ years, n = 409) as a baseline dataset in the current study. All methods designed for 7-year follow-up are based on previous studies. The data collection comprises device-based measurement of MRBs (ActiGraph GT1M accelerometer), objective assessment of body adiposity (multi-frequency bioelectrical impedance analysis), subjective assessment of the built environment (NEWS-A questionnaire), and other possible confounding factors. Time spent in sedentary behavior, light physical activity, and moderate-to-vigorous physical activity will be used as three components in a composition reflecting individual MRBs. In linear multiple compositional regression analysis assessing the prospective association between obesity and MRBs, the 7-year follow-up composition of the three mentioned components represents the dependent variable. The 7-year changes in the percentage of body fat (body adiposity), baseline composition of MRBs, and parameters of the built environment represent regressors. DISCUSSION: This study will use an integrated time-use approach to explore causality from obesity to device-measured behaviors in older women. The design and respective analysis consider the compositional nature of MRBs data and the potential moderating effects of various factors. A comprehensive assessment of causality may help to develop multilevel interventional models that enhance physical activity in older adults.
- MeSH
- adipozita * MeSH
- cvičení * MeSH
- hmotnostní přírůstek MeSH
- index tělesné hmotnosti MeSH
- lidé středního věku MeSH
- lidé MeSH
- lineární modely MeSH
- následné studie MeSH
- obezita komplikace MeSH
- prospektivní studie MeSH
- průřezové studie MeSH
- sedavý životní styl * MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- tuková tkáň metabolismus MeSH
- výzkumný projekt MeSH
- zdravé chování * MeSH
- životní prostředí - projekt * MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
The assessment of age-at-death is an important and challenging part of investigations of human skeletal remains. The main objective of the present study was to apply different mathematical approaches in order to reach more accurate and reliable results in age estimation. A multi-ethnic dataset (n=941) of evaluated age-related changes on the pubic symphysis and the auricular surface of the hip bone was used. Two research groups examined nine different mathematical approaches. The best results were reached by Multi-linear regression, followed by the Collapsed regression model, with MAE values of 9.7 and 9.9 years, respectively, and with RMSE values of 12.1 and 12.2, respectively. The mean accuracy of decision tree models ranged between 30.7% and 72.3%, with the model using only the PUSx indicator performing the best. Moreover, our results indicate that the limiting factor of age estimation can be the visual evaluation of age-related changes. Further research is required to objectify the proposed methods for estimating age.
- MeSH
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladý dospělý MeSH
- neuronové sítě MeSH
- os ilium anatomie a histologie MeSH
- rozhodovací stromy MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- statistické modely * MeSH
- symphysis pubica anatomie a histologie MeSH
- tělesné pozůstatky * MeSH
- určení kostního věku metody MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladý dospělý MeSH
- mužské pohlaví MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
STUDY QUESTION: Do genetic variations in the DNA damage response pathway modify the adverse effect of alkylating agents on ovarian function in female childhood cancer survivors (CCS)? SUMMARY ANSWER: Female CCS carrying a common BR serine/threonine kinase 1 (BRSK1) gene variant appear to be at 2.5-fold increased odds of reduced ovarian function after treatment with high doses of alkylating chemotherapy. WHAT IS KNOWN ALREADY: Female CCS show large inter-individual variability in the impact of DNA-damaging alkylating chemotherapy, given as treatment of childhood cancer, on adult ovarian function. Genetic variants in DNA repair genes affecting ovarian function might explain this variability. STUDY DESIGN, SIZE, DURATION: CCS for the discovery cohort were identified from the Dutch Childhood Oncology Group (DCOG) LATER VEVO-study, a multi-centre retrospective cohort study evaluating fertility, ovarian reserve and risk of premature menopause among adult female 5-year survivors of childhood cancer. Female 5-year CCS, diagnosed with cancer and treated with chemotherapy before the age of 25 years, and aged 18 years or older at time of study were enrolled in the current study. Results from the discovery Dutch DCOG-LATER VEVO cohort (n = 285) were validated in the pan-European PanCareLIFE (n = 465) and the USA-based St. Jude Lifetime Cohort (n = 391). PARTICIPANTS/MATERIALS, SETTING, METHODS: To evaluate ovarian function, anti-Müllerian hormone (AMH) levels were assessed in both the discovery cohort and the replication cohorts. Using additive genetic models in linear and logistic regression, five genetic variants involved in DNA damage response were analysed in relation to cyclophosphamide equivalent dose (CED) score and their impact on ovarian function. Results were then examined using fixed-effect meta-analysis. MAIN RESULTS AND THE ROLE OF CHANCE: Meta-analysis across the three independent cohorts showed a significant interaction effect (P = 3.0 × 10-4) between rs11668344 of BRSK1 (allele frequency = 0.34) among CCS treated with high-dose alkylating agents (CED score ≥8000 mg/m2), resulting in a 2.5-fold increased odds of a reduced ovarian function (lowest AMH tertile) for CCS carrying one G allele compared to CCS without this allele (odds ratio genotype AA: 2.01 vs AG: 5.00). LIMITATIONS, REASONS FOR CAUTION: While low AMH levels can also identify poor responders in assisted reproductive technology, it needs to be emphasized that AMH remains a surrogate marker of ovarian function. WIDER IMPLICATIONS OF THE FINDINGS: Further research, validating our findings and identifying additional risk-contributing genetic variants, may enable individualized counselling regarding treatment-related risks and necessity of fertility preservation procedures in girls with cancer. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by the PanCareLIFE project that has received funding from the European Union's Seventh Framework Programme for research, technological development and demonstration under grant agreement no 602030. In addition, the DCOG-LATER VEVO study was funded by the Dutch Cancer Society (Grant no. VU 2006-3622) and by the Children Cancer Free Foundation (Project no. 20) and the St Jude Lifetime cohort study by NCI U01 CA195547. The authors declare no competing interests. TRIAL REGISTRATION NUMBER: N/A.
- MeSH
- antimülleriánský hormon genetika MeSH
- dítě MeSH
- dospělí MeSH
- intracelulární signální peptidy a proteiny MeSH
- kohortové studie MeSH
- lidé MeSH
- mladiství MeSH
- ovariální rezerva * MeSH
- ovarium MeSH
- protein-serin-threoninkinasy MeSH
- retrospektivní studie MeSH
- Check Tag
- dítě MeSH
- dospělí MeSH
- lidé MeSH
- mladiství MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- metaanalýza MeSH
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
BACKGROUND: Genomic selection (GS) in forestry can substantially reduce the length of breeding cycle and increase gain per unit time through early selection and greater selection intensity, particularly for traits of low heritability and late expression. Affordable next-generation sequencing technologies made it possible to genotype large numbers of trees at a reasonable cost. RESULTS: Genotyping-by-sequencing was used to genotype 1,126 Interior spruce trees representing 25 open-pollinated families planted over three sites in British Columbia, Canada. Four imputation algorithms were compared (mean value (MI), singular value decomposition (SVD), expectation maximization (EM), and a newly derived, family-based k-nearest neighbor (kNN-Fam)). Trees were phenotyped for several yield and wood attributes. Single- and multi-site GS prediction models were developed using the Ridge Regression Best Linear Unbiased Predictor (RR-BLUP) and the Generalized Ridge Regression (GRR) to test different assumption about trait architecture. Finally, using PCA, multi-trait GS prediction models were developed. The EM and kNN-Fam imputation methods were superior for 30 and 60% missing data, respectively. The RR-BLUP GS prediction model produced better accuracies than the GRR indicating that the genetic architecture for these traits is complex. GS prediction accuracies for multi-site were high and better than those of single-sites while multi-site predictability produced the lowest accuracies reflecting type-b genetic correlations and deemed unreliable. The incorporation of genomic information in quantitative genetics analyses produced more realistic heritability estimates as half-sib pedigree tended to inflate the additive genetic variance and subsequently both heritability and gain estimates. Principle component scores as representatives of multi-trait GS prediction models produced surprising results where negatively correlated traits could be concurrently selected for using PCA2 and PCA3. CONCLUSIONS: The application of GS to open-pollinated family testing, the simplest form of tree improvement evaluation methods, was proven to be effective. Prediction accuracies obtained for all traits greatly support the integration of GS in tree breeding. While the within-site GS prediction accuracies were high, the results clearly indicate that single-site GS models ability to predict other sites are unreliable supporting the utilization of multi-site approach. Principle component scores provided an opportunity for the concurrent selection of traits with different phenotypic optima.
- MeSH
- algoritmy MeSH
- dřevo * MeSH
- genomika metody MeSH
- genotypizační techniky * MeSH
- modely genetické MeSH
- sekvenční analýza * MeSH
- šlechtění rostlin metody MeSH
- smrk genetika růst a vývoj MeSH
- vysoce účinné nukleotidové sekvenování MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Sum fraction terms can approximate multi-variable functions on the basis of discrete observations, replacing a partial differential equation definition with polynomial elementary data relation descriptions. Artificial neural networks commonly transform the weighted sum of inputs to describe overall similarity relationships of trained and new testing input patterns. Differential polynomial neural networks form a new class of neural networks, which construct and solve an unknown general partial differential equation of a function of interest with selected substitution relative terms using non-linear multi-variable composite polynomials. The layers of the network generate simple and composite relative substitution terms whose convergent series combinations can describe partial dependent derivative changes of the input variables. This regression is based on trained generalized partial derivative data relations, decomposed into a multi-layer polynomial network structure. The sigmoidal function, commonly used as a nonlinear activation of artificial neurons, may transform some polynomial items together with the parameters with the aim to improve the polynomial derivative term series ability to approximate complicated periodic functions, as simple low order polynomials are not able to fully make up for the complete cycles. The similarity analysis facilitates substitutions for differential equations or can form dimensional units from data samples to describe real-world problems.
