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The goal of this work is to utilize the General Empirical Orthogonal Function (EOF) and Principal Component Analysis (PCA) to detect potential earthquake pre-cursory variations in Earth’s ionosphere-lithosphere geomagnetic system and observe their spatial-temporal signatures along seismotectonic fault lines. Two major earthquake episodes in China have been selected for this study: an M6.0 earthquake, which occurred on 19th January 2020 at ENE of Arzak, and another M6.3 earthquake, occurring on 22nd July 2020 in western Xizang. The spatial-temporal variability patterns in an ~ 800 km radius of earthquake epicentres were calculated from geomagnetic data recorded by SWARM satellites A, B and C. The results of EOF spatial components and associated time-series principal components (PCs) revealed anomalous patterns along and on borders of the local tectonic fault lines and around earthquake epicentres. The Planetary A and K geomagnetic storm indices did not show abnormal activities around the same time periods. This could suggest a pre-cursory connection between the detected geomagnetic anomalies and these earthquakes.

A polynomial chaos (PC) analysis with stochastic expansion coefficients is proposed for stochastic differential equations driven by additive or multiplicative Wiener noise. It is shown that for this setting, a Galerkin formalism naturally leads to the definition of a hierarchy of stochastic differential equations governing the evolution of the PC modes. Under the mild assumption that the Wiener and uncertain parameters can be treated as independent random variables, it is also shown that the Galerkin formalism naturally separates parametric uncertainty and stochastic forcing dependences. This enables us to perform an orthogonal decomposition of the process variance, and consequently identify contributions arising from the uncertainty in parameters, the stochastic forcing, and a coupled term. Insight gained from this decomposition is illustrated in light of implementation to simplified linear and non-linear problems; the case of a stochastic bifurcation is also considered.

Summary To further analyze the structural requirements responsible for the enhanced activity of the newly developed, highly active benzylpyrimidine K-130, a series of trimethoprim analogues with various 4-anilinoalkoxy moieties has been synthesized and tested against dihydrofolate reductase (DHFR) derived from various species (Mycobacterium lufu, Escherichia coli, Candida albicans and rats). The importance of the secondary amino group for binding affinity could be shown by varying the substituent in the para position to the sec-amino moiety. This finding could be supported by multiple linear regression and comparative molecular field analysis (CoMFA). The polarized SO2 group, which was thought to be responsible for the increased activity of K-130, seems not to be the only group important for receptor binding. Additionally, a high selectivity of the new compounds for DHFR derived from the various bacteria and C albicans compared with DHFR derived from rat liver is shown by PC analysis.

Taking as its starting point the category text (as opposed to clause, collocation span, sentence etc.) this paper proposes and illustrates a method of identifying key words in text, and leads from this to the notion of key key words (words that are key in many texts). A key key word is shown to have associates: words that are key in the same texts as a given key key word. Finally, these associates can be grouped together in clumps, which themselves are revealing about text schemata and stereotype. The number of clumps in which any key key word participates relates not to ambiguity but to a diversity of perceived roles; the members of the clump describe and illuminate these stereotypical roles.

The authors present a personal computer (PC)-based analysis tool to model the multiple access return (MAR) system of NASA's Second Tracking and Data Relay Satellite System (TDRSs) Ground Terminal (STGT). The MAR design, operational capabilities, and signal model are summarized. The STGT multiple access beamforming equipment (MABE) PC analysis system and its system objectives, modeling approach, functional operation and modeling, and overall operation are presented in detail. Example PC analysis results are presented. >

Standardized storage experiments with hashish and its isolated pure components have shown that for the judgement of hashish samples a comparison of total values of CBD/CBDA, CBN/CBNA and THC/THCA is important. The investigation is carried out by HPLC and is illustrated by a histogram obtained with the aid of a simple data processing program. Changes in the individual cannabinoid contents resulting through different storage conditions are largely compensated for. These results should be confirmed through an additional comparison with standardized HPLCs calculated on the basis of the same weight-in quantity. This is demonstrated on five different confiscated hashish samples. Untersuchung zur Chargengleichheit verschiedener Haschischproben mittels HPLC/PC-Kopplung Standardisierte Lagerungsversuche von Haschischproben und isolierten reinen Einzelsubstanzen zeigten, das ein Vergleich der Gesamtwerte an CBD/CBDA, CBN/CBNA und THC/THCA ein wichtiges Indiz fur die Beurteilung der Chargengleichheit verschiedener Haschischproben darstellt. Die Bestimmung erfolgt durch HPLC und wird uber ein einfaches Datenprogramm als Histogram visualisiert. Anderungen in den einzelnen Cannabinoid-Gehalten, die sich aus der unterschiedlichen Lagerung ergeben, werden dadurch weitgehend ausgeglichen. Das Ergebnis sollte durch zusatzliche Vergleiche mit normierten HPLC, die sich auf die gleiche Einwaage beziehen, gesichert werden. Dies wird am Beispiel von 5 konfiszierten Haschischproben verdeutlicht.

New personal computer (PC) software which performs interactive analysis of alpha spectra using enhanced graphics adapter graphics is described. Spectra are collected with a commercial MCA (multichannel pulse height analyzer) board and analyzed using the software described. The operator is required to approve each peak integration area before analysis proceeds. Sample analysis can use detector efficiencies or spike yields or both. Background corrections are made and upper limit values are calculated when specified. Nuclide identification uses a library of up to four nuclides with up to eight alpha lines for each nuclide. Any of 32 subset libraries can be used in an analysis. Analysis time is short and is limited by interaction with the operator, not only by calculation time. Utilities include nuclide library editing, library subset editing, energy calibration and background update. >

This paper describes a personal computer (PC) application for speech respiration analysis. Parameters that can be determined include lung volume changes, the relative contributions of the rib cage and abdomen to lung volume changes and the configuration of the chest wall during speech production. Data collected from two subjects fitted with Nucleus cochlear implant prostheses illustrate one application of this technique. The PC based kinematic analysis described provides previously inaccessible information about the effects of changes in the level of auditory feedback resulting from activation of a multiple channel cochlear prosthesis on the speech production mechanism.

Standardized storage experiments with hashish and its isolated pure components have shown that for the judgement of hashish samples a comparison of total values of CBD/CBDA, CBN/CBNA and THC/THCA is important. The investigation is carried out by HPLC and is illustrated by a histogram obtained with the aid of a simple data processing program. Changes in the individual cannabinoid contents resulting through different storage conditions are largely compensated for. These results should be confirmed through an additional comparison with standardized HPLCs calculated on the basis of the same weight-in quantity. This is demonstrated on five different confiscated hashish samples. Untersuchung zur Chargengleichheit verschiedener Haschischproben mittels HPLC/PC-Kopplung Standardisierte Lagerungsversuche von Haschischproben und isolierten reinen Einzelsubstanzen zeigten, das ein Vergleich der Gesamtwerte an CBD/CBDA, CBN/CBNA und THC/THCA ein wichtiges Indiz fur die Beurteilung der Chargengleichheit verschiedener Haschischproben darstellt. Die Bestimmung erfolgt durch HPLC und wird uber ein einfaches Datenprogramm als Histogram visualisiert. Anderungen in den einzelnen Cannabinoid-Gehalten, die sich aus der unterschiedlichen Lagerung ergeben, werden dadurch weitgehend ausgeglichen. Das Ergebnis sollte durch zusatzliche Vergleiche mit normierten HPLC, die sich auf die gleiche Einwaage beziehen, gesichert werden. Dies wird am Beispiel von 5 konfiszierten Haschischproben verdeutlicht.

[1] EOF/PC analysis is applied to low-pass filtered deseasonalized CO2 growth rates from a global observational network, and two statistically-significant modes of interannual variability are identified. The spatial structure of the 1st mode is characterized by an interhemispheric gradient, while the 2nd mode is characterized by a land-ocean dipole in the Northern Hemisphere midlatitudes. The gravest PC reflects ENSO-like variability, although the phase relationship to ENSO appears to change around 1990. However, the leading PC exhibits a statistically-significant, stationary phase relative to an index of the Pacific Decadal Oscillation (PDO) throughout the sampling period. The next-to-leading PC, on the other hand, shows little relation to any of the climate indices examined here. These relationships intimate that, while ENSO may play a substantial role in interannual CO2 growth rate variability, the ENSO-growth rate relationship is not stationary, and additional modes of interannual variability may significantly influence year-to-year changes in CO2.

Summary Kelly No. 1 was drilled on a footage basis in Escambia County, AL. Computer bit-record analysis provided summarized information in a format easily read and understood by field personneL With a PC used to compare surrounding bit records on a cost-per-foot basis, the best bit type, weight on bit (WOB), and bit speed for a given section of hole were identified. From the analysis, field personnel were able to improve bit selection, resulting in three bit runs having the lowest cost per foot in a given section of hole and an overall lower-cost-per-foot drilling operation.

The study was conducted in the period 2015-2017 in the experimental field of IRGR "K. Malkov” Sadovo. The elements of productivity of 24 varieties and lines of triticale (X. Triticosecale Wittmacks) were studied. The degree of variation of each of the indicators of productivity is determined by calculating a coefficient of variation. The results obtained show that the most variable indicator is the weight of grains in the central spike whereas the slightest variation is observed in the parameters of test weight and 1000 grains weight. Hierarchical cluster analysis and analysis of the main components (PC-analysis) are applied to assess the genetic similarity and distance between the different varieties. As a result of the clustering the studied samples were divided into six groups. The varieties Trit 32/6 and KS 60 are characterized with the greatest genetic proximity, followed by line BGR 30071 with the Bulgarian variety Rozhen. The largest genetic difference was reported between line BGR 30816 and variety KT 81. The applied analysis of the main components shows that the components PC 1, PC 2 and PC 3 explain 70.6% of the total variation of all traits by genotypes. The largest numbers of samples (9) belong to component 3, as four of them are located in the negative values of PC 3, and the other five genotypes are in the positive values of PC 3. Component 1 is represented by eight samples, and component 2 includes seven triticale genotypes.

Laser-induced fluorescence (LIF) is a powerful remote and non-invasive analysis technique that has been successfully applied to the real-time diagnosis of historical artworks. Hyperspectral images collection on fresco's and their false colours processing allowed to reveal features invisible to the naked eye and to obtain specific information on pigments composition and consolidants utilization, the latter also related to former restorations. This report presents the results obtained by ENEA LIF scanning system during a field campaign conducted in June 2010 on fresco's by Giusto de' Menabuoi in the Padua Baptistery. The data collected by LidArt allowed the detection of Paraloid B72 and Movilith/Primal AC33, guiding the restorers in their conservation actions. © 2013 Elsevier Masson SAS.

The onion is a widely distributed vegetable crop, which takes an important place in the vegetable production in Serbia. The traditional planting method is the one from sets. Old cultivars and populations and, in recent years, foreign cultivars are grown. The large variety of genotypes, including both domestic populations and cultivars, comprises the significant gene pool of this region. The onion collection of the Institute of Field and Vegetable Crops in Novi Sad is based on the populations and cultivars from the territory of the former Yugoslavia. This paper reviews 30 onion genotypes on the basic IPGRI descriptors (ANNEX I). Variability of the reviewed characteristics was determined by PC analysis. High variability values have been established for bulb skin color, bulb flesh color, bulb hearting and bulb skin thickness. The genotypes varied in bulb skin color as well as in bulb flesh color from white to dark violet. These two characteristics had the largest impact on clustering, with a single genotype being heterogeneous exactly for these two characteristics. Crni luk je široko rasprostranjena povrtarska vrsta, čija proizvodnja zauzima značajno mesto u setvenoj strukturi povrća u Srbiji. Tradicionalni način ove proizvodnje je iz arpadžika, gde su zastupljene stare sorte, populacije i sve prisutniji strani sortiment. Bogatstvo genotipova crnog luka, kako gajenih domaćih populacija tako i sorata, predstavlja značajan gen fond sa ovog područja. U Institutu za ratarstvo i povrtarstvo u Novom Sadu, osnovu kolekcije čine domaće populacije i sorte koje se gaje u širem region, sa prostora bivše Jugoslavije. U radu su prikazane osnovne osobine 30 genotipova crnog luka prema deskriptoru IPGRI (ANNEX I.). Varijabilnost ispitivanih osobina je utvrđena PC analizom, gde je ustanovljena visoka varijabilnost za boju lukovice, boju sočnih listova lukovice, broj gnezda i debljinu listova lukovice. Genotipovi su imali boju lukovice od bele do tamno ljubičaste, a takođe i boja sočnih listova. Ove dve osobine su imale najveći uticaj na grupisanje genotipova, tako su formirane dve grupe, uz izdvajanje jednog genotipa koji je heterogen upravo za ove osobine.

Temperatures and light intensities that deviate from optimum often affect maize (Zea mays L.) production in temperate regions. Objectives of the current study were (i) to investigate the effects of extreme temperatures and low light conditions on photosynthesis in maize hybrids, (ii) to test whether maize hybrids show distinctive reactions when subjected to different stresses, and (iii) to investigate informativeness of different fluorescence parameters in different stress conditions. Plants of five maize hybrids were subjected to: cold (Co), low light (LL), heat (H), and severe heat (SH) treatments and field (F) conditions along with control (C), and chlorophyll a fluo- rescence (ChlF) was measured. ChlF transients were shown to respond to different treatments by changing the appearance of OJIP band, mostly at steps J and I, while the appearance of the K step was confirmed as a good indicator of temperature stress. PC analysis revealed grouping of parameters with PCs according to their infor-mativeness. Parameter ψEo, was shown to be in most defined by the F treatment, probably due to higher light intensity compared to C. Variables regarding electron transport and dissipation showed specific reactions to H and SH treatments. Co and LL conditions caused specific changes in in parameters VJ and VI. Further research on usability of ChlF in maize breeding is needed, as it represents the data- rich, easy to measure method, providing the biological framework for explanation of reactions to different stresses.

Previous research regarding the intraseasonal variability of the wintertime Pacific jet has employed empirical orthogonal function (EOF)/principal component (PC) analysis to characterize two leading modes of variability: a zonal extension or retraction and a ∼20° meridional shift of the jet exit region. These leading modes are intimately tied to the large-scale structure, sensible weather phenomena, and forecast skill in and around the vast North Pacific basin. However, variability within the wintertime Pacific jet and the relative importance of tropical and extratropical processes in driving such variability, is poorly understood. Here, a self-organizing maps (SOM) analysis is applied to 73 Northern Hemisphere cold seasons of 250-hPa zonal winds from the NCEP–NCAR reanalysis data to identify 12 characteristic physical jet states, some of which resemble the leading EOF Pacific jet patterns and combinations of them. Examination of teleconnection patterns such as El Niño–Southern Oscillation (ENSO) and the Madden–Julian oscillation (MJO) provide insight into the varying nature of the 12 SOM nodes at inter- and intraseasonal time scales. These relationships suggest that the hitherto more common EOF/PC analysis of jet variability obscures important subtleties of jet structure, revealed by the SOM analysis, which bear on the underlying physical processes associated with Pacific jet variability as well as the nature of its downstream impacts.

Supplementary Figure S3. (A, B): Principal component (PC) analysis plot showing the distribution of the tumor and normal tissues in FFPE samples in the top two PC space before (A) and after (B) removal of 2 FFPE samples. (C, D): PC analysis plot showing the distribution of the tumor and normal tissues in fresh frozen samples in first and second PC (C) as well as first and third PC (D); whereby the analysis was conducted using the Spearman correlation between the tumor and normal samples on the 200 (A, B) and 536 (C, D) detected metabolites. FFPE, formalin-fixed paraffin-embedded; PC, principal component.

Background and Objectives: Perfluoroalkyl substances (PFASs) are known to disrupt the thyroid hormone system. However, no study has assessed the association between multiple exposure to PFASs and the thyroid hormone system. This study aimed to identify the singular effects of each PFAS and the effects of multiple exposure to PFASs on the thyroid hormone profile in a representative sample of the US population. Materials and Methods: We used data from the US National Health and Nutrition Examination Survey (NHANES) 2007-2008 and 2011-2012. To assess the effect of simultaneous exposure to multiple PFASs on thyroid function, principal component (PC) analysis with varimax rotation was performed. Multivariate linear regression analysis was conducted to identify the effect of each PFAS and PC on thyroid function. Results: In this study, perfluorooctanoate (PFOA) was associated with a decrease in total T4 and Free T4 levels. Perfluorooctane sulfonate (PFOS) was associated with a decrease in total T4 level and perfluorononanoate (PFNA) and perfluorodecanoate (PFDeA) were associated with decreases in TSH levels. In PC analysis, two PCs were identified. PC1 included PFOA, PFOS, perfluorohexane sulfonate (PFHxS), PFNA and 2-(N-methyl-perfluorooctane sulfonamido) acetic acid with high loading. PC2 included PFNA, PFDeA, and perfluoroundecanoate (PFUA). In the multivariate linear regression analysis, PC1 showed negative correlations with total T4 and Free T4 levels, whereas PC2 showed a negative correlation with TSH level. Conclusion: We found that singular and multiple exposure to PFASs was associated with a disruption in thyroid hormone system.

Additional file 2: Figure S1. A) The first two principal components (PC) from a PC analysis of genome-wide SNPs after removal of outliers (n=7). Isolates are color coded by the collection time point and wheat cultivar. B) SplitsTree phylogenetic network constructed from genome-wide single nucleotide polymorphism (SNP) data. Figure S2. Discriminant analysis of principal components (DAPC) results from the genome-wide SNP dataset. Cumulated variance explained by the eigenvalues of the PCs and scatter plot of the Bayesian Information Criterion (BIC) values. The lowest BIC value indicates the most parsimonious number of clusters. Figure S3. A) The first two principal components (PC) from a PC analysis of SNPs closest to biosynthetic gene clusters BGC. Isolates are color coded by the collection time point and wheat cultivar. B) Down sampling analysis to identify the proportion of 2633 metabolite markers detected in mapping population. Figure S4. Percentage leaf area covered by lesions and pycnidia during wheat infection for subset of Z. tritici strains included in the metabolome-GWAS analysis (n = 76). The isolates are grouped by their genotype at significant metabolome GWAS SNPs. Figure S5. Evolutionary history of the putative effector gene Zt09_00502. A) Alignment of the 3’UTR region of the gene. The box refers to the haplotypes found in the single Swiss field population. B) Phylogenetic tree of the 3’UTR region and (C) of the gene sequence. Names in bold black, blue and grey refer to the reference genomes of the species (IPO), isolates included in the metabolite GWAS and sister species, respectively. The phylogenetic tree was inferred by using maximum likelihood and the Tamura-Nei model. D) Pairwise linkage disequilibrium (LD) among all pairs of SNPs within the gene cluster. The red dotted line marks the r2=0.2. The blue dotted line represents distance where the LD drops to r2

Uncovering molecular basis with regard to the conformational change of two switches I and II in the GppNHp (GNP)-bound H-Ras is highly significant for the understanding of Ras signaling. For this purpose, accelerated molecular dynamics (aMD) simulations and principal component (PC) analysis are integrated to probe the effect of mutations G12V, T35S and Q61K on conformational transformation between two switches of the GNP-bound H-Ras. The RMSF and cross-correlation analyses suggest that three mutations exert a vital effect on the flexibility and internal dynamics of two switches in the GNP-bound H-Ras. The results stemming from PC analysis indicate that two switches in the GNP-bound WT H-Ras tend to form a closed state in most conformations, while those in the GNP-bound mutated H-Ras display transformation between different states. This conclusion is further supported by free energy landscapes constructed by using the distances of residues 12 away from 35 and 35 away from 61 as reaction coordinates and different experimental studies. Interaction scanning is performed on aMD trajectories and the information shows that conformational transformations of two switches I and II induced by mutations extremely affect the GNP-residue interactions. Meanwhile, the scanning results also signify that residues G15, A18, F28, K117, A146 and K147 form stable contacts with GNP, while residues D30, E31, Y32, D33, P34 and E62 in two switches I and II produce unstable contacts with GNP. This study not only reveals dynamic behavior changes of two switches in H-Ras induced by mutations, but also unveils general principles and mechanisms with regard to functional conformational changes of H-Ras.

Evidence is accumulating for the possibility to distinguish more than two distinct chronotypes, i.e., people would be neither morning nor intermediate nor evening types. We tried to establish four-type division into distinct chronotypes without implying any chronotypological questionnaire. A community-based online survey (n = 1305) included a visuo-verbal judgment task for evaluating how sleepy a survey participant thinks he/she would be at different randomly presented times. We predicted that principal component (PC) analysis of 24-h sleepiness curves would yield more than one PC. Consequently, only two types based on PC score would be sleepy in the evening but not in the morning (morning type) and in the morning but not in the evening (evening type), while two other types would be sleepy both in the morning and in the evening and neither in the morning nor in the evening. Results of PC analysis yielded four PCs with the predicted loading patterns. Four distinct patterns of sleepiness curves were identified by dividing participants in accord with scores PC > 1, −1 < PC < 1, and PC < −1. Only 396 participants were of intermediate chronotype (−1 < PC1–PC4 < 1) with a similar to the sample-averaged sleepiness curve, while, like morning and evening types, two further types (named “afternoon” and “napper”) were not uncommon.

Introduction: Neonatal heart surgery requiring cardiopulmonary bypass (CPB) is associated with significant morbidity and mortality. Methods to improve outcome prediction are lacking. Hypothesis: Targeted metabolic profiling can identify critical metabolites associated with important post-operative clinical outcomes. These in turn could be integrated into clinical prediction models. Methods: Secondary analysis of serum samples from the neonatal congenital cardiac surgery with CPB methylprednisolone trial, which evaluated effects of steroids on outcomes. Samples were from pre-op, immediate post-CPB, and 12 hrs post op. Outcomes were a cardiac dysfunction composite (death, ECMO, cardiac arrest and lactate) and low cardiac output syndrome (LCOS). Metabolite levels were determined with targeted mass spectrometry (LC/MS/MS). Principal component (PC) analysis and multivariable regression analysis with bootstrapping were used to assess the association between metabolic profiles and outcomes. Results: Total cohort had 149 patients. PC analysis identified 6 PCs (PC1-PC6) that explained 51% of variance. When PCs and metabolites were added to a base clinical model, model fit for the cardiac dysfunction composite outcome was significantly improved (c-stat 0.819 vs 0.902, p Conclusions: Combining metabolic profiles with patient characteristics revealed significant pre-op metabolites associated with important clinical outcomes. Given that the association held true for all time points, these observations could be used to design molecular signature for post-operative cardiac complications or, to create prediction models based on pre-operative metabolic profiles.

AimThe novel SARS-CoV-2 virus, which causes the COVID-19 disease, has infected more than 10 million people and caused 500K deaths worldwide. In Europe, over 2 million confirmed cases have been reported, while nearly 200K people have died from the disease. Despite strict containment measures in Spain and Italy after the first reported COVID-19 patient, these two countries have remained in the top five European nations with the highest mortality rate for over two months. We hypothesised that a genetic mechanism could partially explain the poor survival outcome observed in these two countries.MethodsAn extensive literature search to identify human candidate genes linked to SARS-CoV infection, host immune evasion and disease aggressiveness was carried out. Pathway analysis (IPA) was performed to select the most significantly associated canonical signalling pathways with the genes of interest. The genetic variants’ at these genes with ±1Mb flanking region was extracted (GRCh37/hg19 built). Over 80 million single nucleotide polymorphisms (SNPs) were analysed in genome-wide data of 2,504 individuals (1000 genomes, phase III, https://www.internationalgenome.org/). Principal component (PC) analysis was performed, ancestry by the whole genome was inferred and subsets of the regions of interest were extracted (PLINK v1.9b, http://pngu.mgh.harvard.edu/purcell/plink/). PC1 to PC20 values from five European ancestries, including the Spanish and Italian populations, were used for PC analysis. Gene function predictions were run with our genes of interest as a query to the GeneMANIA Cytoscape plugin (https://genemania.org/).ResultsA total of 437 candidate genes associated with SARS were identified, including 21 correlated with COVID-19 aggressiveness. The two most significant pathways associated with all 437 genes (Caveolar-mediated Endocytosis and MSP-RON Signalling) did not show any segregation at the population level. However, the most significant canonical pathway associated with genes linked to COVID-19 aggressiveness, the Hepatic Fibrosis and Hepatic Stellate Cell Activation, showed population-specific segregation. Both the Spanish and Italian populations clustered together from the rest of Europe. This was also observed for the Finnish population but in the opposite direction. These results suggest some of the severe COVID-19 cases reported in Spain and Italy could be partially explained by a pre-existing liver condition (especially liver cancer) and/or may lead to further COVID-19 related liver complications.

The β-amyloid cleaving enzyme 1 (BACE1) has been thought to be an efficient target for treatment of Alzheimer's disease (AD). Deep insight into inhibitor-BACE1 binding mechanism is of significance for design of potent drugs toward BACE1. In this work, multiple replica accelerated molecular dynamics (MR-aMD) simulations, principal component (PC) analysis, and free energy landscapes were integrated to decode the effect of disulfide bonds (SSBs) in BACE1 on bindings of three inhibitors 3KO, 3KT, and 779 to BACE1. The results from cross-correlation analysis suggest that the breaking of SSBs exerts significant influence on structural flexibility and internal dynamics of inhibitor-bound BACE1. PC analysis and free energy landscapes reveal that the breaking of SSBs not only evidently induces the conformational rearrangement of BACE1 but also highly changes binding poses of three inhibitors in BACE1 and leads to more disordered binding of three inhibitors to BACE1, which is further supported by the increase in binding entropy of inhibitors to BACE1 due to the breaking of SSBs. Residue-based free energy decomposition method was utilized to evaluate contributions of separate residues to inhibitor-BACE1 binding. The results suggest that although the breaking of SSBs in BACE1 does not destroy the interaction network of inhibitors with BACE1 it changes interaction strength of some residues with inhibitors. Meanwhile, the information from residue-based free energy decomposition indicates that residues L91, S96, V130, Y132, Q134, W137, F169, I171, and I179 can be used as efficient targets of drug design toward BACE1.

Purpose: To identify which combination metrics of external and internal training load (TL) capture similar or unique information for individual professional players during skills training in rugby union using principal-component (PC) analysis. Methods: TL data were collected from 21 male professional rugby union players across a competitive season. This included PlayerLoad™, total distance, and individualized high-speed distance (>61% maximal velocity; all external TL) obtained from a microtechnology device (OptimEye X4; Catapult Innovations, Melbourne, Australia) that was worn by each player and the session rating of perceived exertion (RPE) (internal TL). PC analysis was conducted on each individual to extract the underlying combinations of the 4 TL measures that best describe the total information (variance) provided by the measures. TL measures with PC loadings (PCL) above 0.7 were deemed to possess well-defined relationships with the extracted PC. Results: The findings show that from the 4 TL measures, the majority of an individual’s TL information (first PC: 55–70%) during skills training can be explained by session RPE (PCL: 0.72–0.95), total distance (PCL: 0.86–0.98), or PlayerLoad (PCL: 0.71–0.98). High-speed distance was the only variable to relate to the second PC (PCL: 0.72–1.00), which captured additional TL information (+19–28%). Conclusions: Findings suggest that practitioners could quantify the TL of rugby union skills training with one of PlayerLoad, total distance, or session RPE plus high-speed distance while limiting omitted information of the TL imposed during professional rugby union skills training.

Objectives: To clarify the relationship between tooth length and three-dimensional mandibular morphology in a healthy Japanese population. Materials and Methods: This study included 181 Japanese adults: 66 men and 115 women. Cone-beam computed tomography (CBCT) images were acquired with a dentofacial cone-beam x-ray CT scanner. Tooth length was measured with open-source OsiriX medical image processing software. Crown height and root length were measured in the maxillary and mandibular central incisors, lateral incisors, canines, first premolars, second premolars, first molars, and second molars. Based on these measurements, principal component (PC) analysis was performed. The following measurements were used to assess three-dimensional mandibular morphology: CD-GO, GO-GN, RCD-LCD, RGO-LGO, RCP-LCP, and the gonial angle. Stepwise multiple regression analysis was performed to examine the associations between three-dimensional mandibular morphology and the patterns of crown and root lengths using the mandibular measurements as explanatory variables and each PC as the dependent variable. Results: CD-GO was positively associated with PC1, which represented overall tooth length. RGO-LGO was positively associated with PC2, whereas GO-GN, RCP-LCP, and gonial angle were negatively associated with PC2, which was the axis denoting relatively longer root (+) vs higher crown (−). Being female was associated with PC3, which was the axis denoting relatively longer posterior tooth (+) vs anterior tooth (−). Conclusions: The present clinical study effectively used CBCT images and PC analysis to reveal significant correlations between tooth length and mandibular morphology in a modern human population, confirming in part the statement that “large teeth necessitate large jaws.”

Our goal was to verify the association between candidate polymorphisms and skeletal Class III malocclusion in a well-characterized homogeneous sample set.Thirty-five single-nucleotide polymorphisms were studied from 10 candidate loci in 54 Class III subjects and 120 controls. Skeletal Class III characteristics included ANB angle less than 0°, SNB angle greater than 83° (mandibular prognathism), SNA angle less than 79° (maxillary deficiency), Class III molar relationship, and negative overjet. Inclusion criteria for the controls were ANB angle between 0° and 4°, Class I molar relationship, and normal overjet. Chi-square and Fisher exact tests and principal component (PC) analysis were used to determine overrepresentation of marker alleles with alpha of 0.05. Odds ratios and 95% confidence intervals were calculated.MYO1H (rs10850110 AG) (P 0.01; odds ratio, 7.44 [4.02-13.77]) was associated with an increased risk for the mandibular prognathism phenotype. These results were confirmed by PC analysis, which showed 4 PCs representing the sample variations (PC1, 37.24%; PC2, 20.02%; PC3, 12.18%; and PC4, 11.40%), and PC1 was associated with MYO1H (P 0.001). We also found by PC analysis associations between MYO1H (P 0.001) and GHR (rs2973015 AG) (P = 0.001) with PC2 and between FGF10 (rs593307 AG) (P = 0.001) with PC4.Polymorphism in MYO1H could be used as a marker for genetic susceptibility to Class III malocclusion with mandibular prognathism, and polymorphisms in GHR and FGF were associated with maxillomandibular discrepancies. This study may contribute to improved diagnosis and further research assessing possible differences in treatment responses based on genetic polymorphisms.

It is well known that the interactions of p53 with murine double minute 2 and murine double minute X, namely MDM2 and MDMX, have been significant targets of efficient anti-cancer drug design. In this study, molecular dynamics (MD) simulations, principal component (PC) analysis and binding free energy calculations are combined to recognize binding selectivity of three ligands to MDM2 and MDMX. The binding free energies were estimated by using molecular mechanics generalized Born surface area (MM-GBSA) method and the obtained results display that the increase in the binding enthalpy of three ligands to MDM2 relative to MDMX mainly drives the binding selectivity of them toward MDM2 and MDMX. The information obtained from PC analysis shows that the associations of ligands exert important impacts on internal dynamics of MDM2 and MDMX. Meanwhile, the calculations of residue-based free energy decomposition not only identify the hot interaction spots of ligands with MDM2 and MDMX, but also show the residues (L54, M53), (Y67, Y66), (V93, V92), (H96, P95), (I99, I98) and (Y100, Y99) in (MDM2, MDMX) are responsible for most contributions to the binding selectivity of three ligands toward MDM2 and MDMX. It is believed that this work can provide useful information for design of highly selective and dual inhibitors targeting MDM2 and MDMX.Communicated by Ramaswamy H. Sarma.

This study is intended to explore the potential of silver (Ag) nanoparticle-based plasma surface-enhanced Raman spectroscopy (SERS) for providing a rapid and simple "Yes/No" assessment to detect acute myocardial infarction (AMI). A simple, rapid, and accurate method of diagnosing AMI is critical to reduce mortality and improve prognosis. Techniques such as electrocardiography examination and use of cardiac troponins have not yet met the current clinical need. Therefore, alternative approaches need to be developed. Plasma samples from 32 patients with AMI and 32 healthy control (Clt) subjects were assessed. Multivariate statistical techniques, including principal component (PC) analysis and linear discriminant analysis (PCA–LDA), were employed to develop a diagnostic algorithm for differentiating between patients with AMI and Clt subjects. Furthermore, the receiver operating characteristic was tested to evaluate the performance of the PCA–LDA algorithm for AMI detection. Each plasma sample was mixed with an equal volume of Ag colloidal solution, and the SERS measurement of each plasma sample was performed. The plasma SERS spectrum showed much stronger and sharper peaks compared with the normal Raman spectrum. Tentative assignments of Raman spectroscopy bands showed specific biomolecular (e.g., proteins, adenosine, adenine, and uric acid) changes. PC analysis and LDA were employed to discriminate patients with AMI from Clt subjects, yielding a sensitivity of 87.5% and a specificity of 93.8%. The findings of this study suggest that plasma SERS has a great potential for improving AMI in the future, and this will certainly reduce the difficulty, time to draw blood, and patients’ pain to a great extent.

Background: Orthodontic science centers primarily on the growth, development and advancement of the craniofacial structures. Geometric morphometrics (GMM) is a new approach for shape identification in forensic sciences. Purpose: The aim of this study was to examine the shape variation in the Indian sample in order to assess sexual dimorphism by application of two-dimensional GMM. Materials and Methods: The sample comprised a total of 105 lateral cephalograms (54 males–51 females) of Angle's Class I malocclusion patients that were later subjected to principal component (PC) analysis and discriminant analysis. Results: The PC analysis showed over 96% of shape variation. The initial three PCs were statistically significant that depicted as 58.37% of total shape variability, with PC1 represent for the most significant variance 28.48%, PC2 described 18.83% and PC3 11.06%. Conclusion: Sex of an individual was clearly associated with occlusion of teeth and showed considerable variation. GMM is an alternative research tool and can be utilized for diagnosing individual characterization and classification of malocclusion.

Insights into binding mechanism of inhibitors to targets are expected to provide a meaningfully theoretical guidance for design and development of effective inhibitors inhibiting of the activity of targets. It is well known that the bromodomain (BRD) family has been thought as a promising target utilized for treating various human diseases, such as inflammatory disorders, malignant tumors, acute myelogenous leukemia (AML), bone diseases, etc. In this work, we summarize the roles of integration of multiple simulation technologies in exploring atomic-level dynamics changes of the BRD family because of inhibitor bindings. Molecular dynamics (MD) simulations, binding free energy calculations, calculations of dynamics cross-correlation maps (DCCMs), and principal component (PC) analysis are integrated together to uncover binding modes of inhibitors to BRDs. The results obtained from binding free energy calculations can measure binding ability of inhibitors to BRDs, and explore the main driving forces of the binding of inhibitors to BRDs. The information stemming from PC analysis can reveal the changes in conformations, internal dynamics and movement patterns of BRDs due to inhibitor associations. Residue-based free energy decomposition method is wielded to unveil contributions of separate residues to inhibitor bindings, and explore the decisive factors that affect the bindings of inhibitors to BRDs.

Spin-coated MoO3 thin films were subsequently subjected to later thermal treatment (LTT) at different temperatures. The x-ray diffraction (XRD) results corroborated that the produced films crystallise in their α-phase with layer structure featured by preferential orientations along the (0k0) planes, and it was also revealed that the thermal energy gained by the later heat treatment plays a major role in enhancing crystallinity enlarging crystallite size. The optical spectroscopic analysis showed that in the visible and near-infrared regions, the average transmission of the film samples remarkably increases with increasing the LTT temperature, whereas the films prepared at 625 °C exhibits an average optical transmission of 79.92%. The optical bandgaps of the film samples were calculated to be of comparable values to the bulk one of α-MoO3 when increasing the LTT temperature from 375 to 525 °C, but it was found to be little greater than the bulk value by further increase in the LTT temperature. The DC electrical results revealed that raising the LTT temperature significantly enhances the electrical resistivity of the film samples, chiefly over the low working-temperatures. These results ascertained the realization of more than one conduction mechanism with different activation energies for the same film, and ramarkable upswings in activation energies were observed by increasing the LTT temperature. The photoconductivity (PC) analysis indicated the occurrence of various trapping processes associated with different photoexcitation energies. The PC analysis also corroborated that the highly resistive thin films exhibit much greater sensitivity to UV illumination compared with the remaining films, whereas the film prepared at the LTT temperature 625 °C presents the higher illumination current at the steady state condition exceeding the dark current value by a factor of 66.01.

Heat shock protein 90 (Hsp90) has been an attractive target of potential drug design for antitumor treatment. The current work integrates molecular dynamics (MD) simulations, calculations of binding free energy, and principal component (PC) analysis with scanning of inhibitor–residue interaction to probe the binding modes of inhibitors YK9, YKJ and YKI to Hsp90 and identify the hot spot of the inhibitor–Hsp90 binding. The results suggest that the introductions of two groups G1 and G2 into YKJ and YKI strengthen the binding ability of YKJ and YKI to Hsp90 compared to YK9. PC analysis based MD trajectories prove that inhibitor bindings exert significant effects on the conformational changes, internal dynamics and motion modes of Hsp90, especially for the helix α2 and the loops L1 and L2. The calculations of residue-based free energy decomposition and scanning of the inhibitor–Hsp90 interaction suggest that six residues L107, G108, F138, Y139, W162 and F170 construct the common hot spot of the inhibitor–residue interactions. Moreover the substitutions of the groups G1 and G2 in YKJ and YKI lead to two additional hydrogen bonding interactions and multiple hydrophobic interactions for bindings of YKJ and YKI to Hsp90. This work is also expected to contribute theoretical hints for the design of potent inhibitors toward Hsp90.

1. Comprehensive knowledge of innate fear in chickens has important implications for understanding the adaptation of native Japanese chickens in modern production and behavioural changes caused by modern breeding goals. Innate fear behaviour seen in chicks from six native Japanese chicken breeds;, Ingie (IG), Nagoya (NAG), Oh-Shamo (OSM), Tosa-Jidori (TJI), Tosa-Kukin (TKU) and Ukokkei (UK), were compared with those in two lines of White Leghorn (WL-G and WL-T) in tonic immobility (TI) and open field (OF) tests. 2. TI and OF tests were conducted for 267 chicks at 0-1 days of age in the eight breeds. Raw data for four TI traits and 13 OF traits were corrected for environmental factors. Breed differences were analysed by the Kruskal–Wallis test followed by the Steel Dwass post hoc test. Principal component (PC) analyses were conducted. 3. The results showed that OSM was the least sensitive to fear in both the TI and OF tests. The WL-G birds showed higher sensitivity to TI fear but lower sensitivity to OF fear. The PC analysis of OF traits classified the tested breeds into three groups: least (OSM and WL-G), moderate (IG, WL-T, NAG, TJI and TKU) and most sensitive (UK).

Introduction: Vascular risk factors (VRFs) and their net effects vary across ethnic populations. We hypothesized that use of DNA-based ancestry informative markers (AIMs), compared with self-reported race/ethnicity (SIRE), would result in better prediction of VRFs and thus improve risk modeling in intracerebral hemorrhage (ICH) across U.S. minority populations. Methods: Using data from the Ethnic/Racial Variations of Intracerebral Hemorrhage (ERICH) study (a multi-center case-control study of ICH in whites, blacks, and Hispanics), we utilized 15 AIMs to perform principal component (PC) analysis using variance-standardized relationship matrix dimension reduction. Multivariate logistic regression and tests for independent samples (X 2 and Mann-Whitney U tests) were used to compare PC-defined ancestry and SIRE in their association with VRFs, and to estimate effects within each SIRE. Finally, we compared models for ICH risk including AIMs vs. SIRE. Results: Among 4,935 subjects enrolled, 34.7% were blacks, 35.1% whites, and 30.2% Hispanic. PC analysis showed population structure not captured by SIRE [Figure]. Within each self-reported population, PCs values remained significantly associated with VRFs (p Conclusions: AIMs, particularly among Hispanics and blacks, provide a more detailed assessment of risk exposures in studies that include representative U.S. populations, compared with SIRE alone. This more inclusive ancestry modeling may be a useful tool to improve risk prediction accuracy across other phenotypes

Patterns of coordination result from the interaction between (at least) two oscillatory components. This interaction is typically understood by means of two variables: the mode that expresses the shape of the interaction, and the stability that is the robustness of the interaction in this mode. A potent method of investigating coordinated behaviors is to examine the extent to which patterns of coordination arise spontaneously. However, a prominent issue faced by researchers is that, to date, no standard methods exist to fairly assess the stability of spontaneous coordination. In the present study, we introduce a new method called the index-of-stability (IS) analysis. We developed this method from the phase-coupling (PC) analysis that has been traditionally used for examining locomotion–respiration coordinated systems. We compared the extents to which both methods estimate the stability of simulated coordinated behaviors. Computer-generated time series were used to simulate the coordination of two rhythmic components according to a selected mode m:n and a selected degree of stability. The IS analysis was superior to the PC analysis in estimating the stability of spontaneous coordinated behaviors, in three ways: First, the estimation of stability itself was found to be more accurate and more reliable with the IS analysis. Second, the IS analysis is not constrained by the limitations of the PC analysis. Third and last, the IS analysis offers more flexibility, and so can be adapted according to the user’s needs.

Wheat yields in Chile have increased significantly during the last four decades as a consequence of plant improvement and better crop husbandry. Central Chile is characterised by high-yield Mediterranean conditions, where precipitation received by the crop in most years does not represent a major limitation to productivity. This study assesses the changes in agronomic and physiological traits of spring cultivars released in the country between 1920 and 2000. A total of 95 spring bread wheat accessions, representing 20 old and 75 modern cultivars (released before and after 1960, respectively) were tested in a humid Mediterranean-type climate, with irrigation. Modern genotypes exhibited higher grain yield, harvest index, number of grains per ear and sedimentation values and lower height, test weight, wet gluten content and hardness index. No differences were found for days to heading, and ear length, whereas kernel weight decreased with the Green Revolution. Principal component (PC) analysis using ten agronomic traits clearly separated modern from old cultivars. Grain yield, a trait not included in PC analysis, was highly correlated with the first PC ( r = 0.80, P

This article presents and compares two approaches of principal component (PC) analysis for two-dimensional functional data on a possibly irregular domain. The first approach applies the singular value decomposition of the data matrix obtained from a fine discretization of the two-dimensional functions. When the functions are only observed at discrete points that are possibly sparse and may differ from function to function, this approach incorporates an initial smoothing step prior to the singular value decomposition. The second approach employs a mixed effects model that specifies the PC functions as bivariate splines on triangulations and the PC scores as random effects. We apply the thin-plate penalty for regularizing the function estimation and develop an effective expectation–maximization algorithm for calculating the penalized likelihood estimates of the parameters. The mixed effects model-based approach integrates scatterplot smoothing and functional PC analysis in a unified framework and is shown i...

Background Classical anthropometric traits may fail to fully represent the relationship of weight, adiposity, and height with cancer risk. We investigated the associations of body shape phenotypes with the risk of overall and site-specific cancers. Methods We derived four distinct body shape phenotypes from principal component (PC) analysis on height, weight, body mass index (BMI), waist (WC) and hip circumferences (HC), and waist-to-hip ratio (WHR). The study included 340,152 men and women from 9 European countries, aged mostly 35–65 years at recruitment (1990–2000) in the European Prospective Investigation into Cancer and Nutrition (EPIC) study. Cox proportional hazards regression was used to estimate multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs). Results After a median follow-up of 15.3 years, 47,110 incident cancer cases were recorded. PC1 (overall adiposity) was positively associated with the risk of overall cancer, with a HR per 1 standard deviation (SD) increment equal to 1.07 (95% confidence interval 1.05 to 1.08). Positive associations were observed with 10 cancer types, with HRs (per 1 SD) ranging from 1.36 (1.30–1.42) for endometrial cancer to 1.08 (1.03–1.13) for rectal cancer. PC2 (tall stature with low WHR) was positively associated with the risk of overall cancer (1.03; 1.02–1.04) and five cancer types which were not associated with PC1. PC3 (tall stature with high WHR) was positively associated with the risk of overall cancer (1.04; 1.03–1.05) and 12 cancer types. PC4 (high BMI and weight with low WC and HC) was not associated with overall risk of cancer (1.00; 0.99–1.01). Conclusions In this multi-national study, distinct body shape phenotypes were positively associated with the incidence of 17 different cancers and overall cancer.

Celosia (Celosia argentea), is an important tropical vegetable for households in sub-Saharan Africa. Despite the multifaceted usefulness, available genotypes are low-yielding, and the vegetable faces dangers of genetic erosion due to poor research attention. The magnitude and pattern of variability will guide the choice of breeding methods for improvement. Twenty-one celosia accessions were evaluated in 2018 and 2019 to determine study genetic variability and heterotic patterns among clusters. Accessions and clusters differed significantly (p ≤0.05/0.01) for plant height, number of leaves/plant, stem weight, harvest index and dry matter content. Genotypic coefficients of variation; ranging from 37.89 to 0.12, were lower than phenotypic coefficients of variation which ranged from 114.55 to 0.12, both for number of leaves/plant and harvest index respectively, indicating the importance of environment in the variability. Discriminant analysis indicated low (8.12%) classification error rate, indicating the possibility of heterotic patterns among clusters. Principal component (PC) analysis controlled 73% of the observed variability among accessions and identified all measured traits as important contributors with loadings ranging from 0.30 (in PC 1) to 0.63 (in PC 2) for harvest index and stem weight respectively. Useful levels of association were also observed among measured traits. The study concluded that there was sufficient genetic variability for effective selection. Discriminant and principal component analyses identified plant height, number of leaves/plant and dry matter content as major contributors to variation among accessions. Weight of edible parts of Celosia can be simultaneously improved with plant height and number of leaves/plants.

Many risk factors exist for chemotherapy-induced nausea and vomiting (CINV). This study utilized a multivariate projection technique to identify which risk factors were predictive of CINV in clinical practice. A single-centre, prospective, observational study was conducted from January 2007~July 2010 in Singapore. Patients were on highly (HECs) and moderately emetogenic chemotherapies with/without radiotherapy. Patient demographics and CINV risk factors were documented. Daily recording of CINV events was done using a standardized diary. Principal component (PC) analysis was performed to identify which risk factors could differentiate patients with and without CINV. A total of 710 patients were recruited. Majority were females (67%) and Chinese (84%). Five risk factors were potential CINV predictors: histories of alcohol drinking, chemotherapy-induced nausea, chemotherapy-induced vomiting, fatigue and gender. Period (ex-/current drinkers) and frequency of drinking (social/chronic drinkers) differentiated the CINV endpoints in patients on HECs and anthracycline-based, and XELOX regimens, respectively. Fatigue interference and severity were predictive of CINV in anthracycline-based populations, while the former was predictive in HEC and XELOX populations. PC analysis is a potential technique in analyzing clinical population data, and can provide clinicians with an insight as to what predictors to look out for in the clinical assessment of CINV. We hope that our results will increase the awareness among clinician-scientists regarding the usefulness of this technique in the analysis of clinical data, so that appropriate preventive measures can be taken to improve patients' quality of life.

Defined as the transient state between standing and walking, gait initiation is negatively affected in Parkinson's disease (PD), which often results in significant disability. Although deep brain stimulation (DBS) is the most common surgical procedure for PD, the long-term effects of DBS on gait initiation are not well studied. The present study evaluated the long-term effects of subthalamic nucleus (STN) DBS on the preparation phase of gait initiation using principal component (PC) analysis. Six patients with PD who had undergone STN DBS and 24 healthy control subjects were evaluated. PD subjects were assessed 11.3 ± 10.3 (P1) and 78.9 ± 10.6 (P2) months after surgery. PD subjects were tested with STN DBS in two conditions: without medication and with medication. PC analysis was applied separately for the vertical, anterior–posterior and medial–lateral components of ground reaction force (GRF) recorded during gait initiation. Three PC scores were chosen by the scree test for each GRF component and all these PC scores were used for calculating a standard distance between healthy controls and PD subjects. The Friedman test showed a significant difference in standard distance among conditions ( P = 0.004), with the post-hoc test recognizing differences among P1 conditions and P2 medication-on condition. The eigenvector loading factors pointed to major differences between PD conditions surrounding the maximum amplitude of vertical and anterior–posterior GRF. For the studied sample, all distances increased in the follow-up evaluation (P2) with and without medications, indicating a worsening in gait initiation after seven years.

Turkey has experienced major population movements. Population structure and genetic relatedness of samples from three regions of Turkey, using over 500,000 SNP genotypes, were compared together with Human Genome Diversity Panel (HGDP) data. To obtain a more representative sampling from Central Asia, Kyrgyz samples (Bishkek, Kyrgyzstan) were genotyped and analysed. Principal component (PC) analysis reveals a significant overlap between Turks and Middle Easterners and a relationship with Europeans and South and Central Asians; however, the Turkish genetic structure is unique. FRAPPE, STRUCTURE, and phylogenetic analyses support the PC analysis depending upon the number of parental ancestry components chosen. For example, supervised STRUCTURE (K=3) illustrates a genetic ancestry for the Turks of 45% Middle Eastern (95% CI, 42-49), 40% European (95% CI, 36-44) and 15% Central Asian (95% CI, 13-16), whereas at K=4 the genetic ancestry of the Turks was 38% European (95% CI, 35-42), 35% Middle Eastern (95% CI, 33-38), 18% South Asian (95% CI, 16-19) and 9% Central Asian (95% CI, 7-11). PC analysis and FRAPPE/STRUCTURE results from three regions in Turkey (Aydin, Istanbul and Kayseri) were superimposed, without clear subpopulation structure, suggesting sample homogeneity. Thus, this study demonstrates admixture of Turkish people reflecting the population migration patterns.

Breast parenchymal patterns on radiologic images are associated with breast cancer risk. Radiomic features have been proposed as quantitative measures of parenchymal patterns. We defined intrinsic imaging phenotypes of breast parenchymal patterns based on radiomic features extracted from full field digital mammography (FFDM) in breast screening populations and assessed whether these phenotypes are associated with breast cancer risk and masking. We selected 30,000 women with 4-view FFDM exams from Hologic machines from three institutions (Hospital of the University of Pennsylvania, Mayo Clinic, and San Francisco Mammography Registry), randomly split into a training (20,000 women) and test set (10,000 women). In total, 390 radiomic features were automatically extracted from each image using a validated software pipeline, standardized, and adjusted for site differences using ComBat. We used two methods, hierarchical clustering and Principal Components (PCs) analysis, to classify significant variation among the features in the training set and replicate among the test set. Next, we applied the replicated clusters and PCs to an independent nested case-control set [1082 invasive breast cancer (BC) cases (of which 151 were Black and 893 White women, 38 other race) matched to 2837 controls (411 Black and 2345 White women, 81 other race) on age, race, timing of images, and site]. We examined associations of the clusters and PCs with invasive breast cancer risk, as well as masking [defined as a false-negative (FN) screen (124 cases and 319 matched controls) and additionally the subset with symptomatic interval cancer (IC) within 12 months of negative screen (88 cases and 223 matched controls)] using conditional logistic regression. We evaluated their association with breast cancer alone, and with adjustment for age, body mass index (BMI) and breast density assessed by Breast Imaging Reporting and Data System (BI-RADS) using likelihood ratio tests. We estimated discrimination using area under the curve (AUC) and compared AUCs for models that included the radiomic clusters and PCs with the model that included only age, BMI and density. We also stratified analyses by race (Black/White). From hierarchical clustering, we defined six statistically significant phenotype clusters (each of at least 1000 women) in the training set which were replicated in the test set. For PC Analysis, we identified six PCs in the training set, explaining 85% of the variation in texture features and reproduced these in the test set. The six radiomic phenotype clusters (P< 0.001) and six PCs (P< 0.001) were both associated with invasive BC, including after adjusting for age, BMI, and density (cluster P=0.004; PCs P< 0.001). Improvements in discrimination of invasive BC with inclusion of PCs or clusters were more pronounced among Black women (Table). Further, the PCs (P< 0.001) and clusters (P< 0.001) were significantly associated with FN overall and for symptomatic IC (PCs P< 0.001; clusters P=0.001), but only PCs remained significant after adjusting for age, BMI and density (PCs P=0.004 for FN; PCs P=0.007 for symptomatic IC). Discrimination of masking also improved with inclusion of both clusters and PCs (Table). We identified reproducible radiomic phenotypes that are associated with invasive BC risk, above and beyond breast density with the strongest associations for invasive BC among Black women and symptomatic interval cancers. Citation Format: Stacey Winham, Anne Marie McCarthy, Aimilia Gastounioti, Christopher Scott, Aaron Norman, Walter C. Mankowski, Lauren Pantalone, Matthew Jensen, Eric A. Cohen, Hannah Horng, Kathleen Brandt, Emily F. Conant, Karla Kerlikowske, Despina Kontos, Celine Vachon. Radiomic phenotypes of breast texture and association with breast cancer risk and masking [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr GS4-06.