Experimental comparison of data transformation procedures for analysis of principal components

Sucrose rinse modulates the salivary behavior of carbonic anhydrase VI and its buffering capacity: a longitudinal study in 4 to 6.5-year-old children

Background

Carbonic anhydrase VI (CA VI) is crucial in regulating oral pH and predicting susceptibility to dental caries. The hypothesis posits that caries activity may alter the CA VI function, diminishing its capacity to regulate pH effectively and potentially exacerbating cariogenic challenges. This 1-year cohort study sought to investigate the enzymatic activity of salivary CA VI and buffering capacity following a 20% sucrose rinse in 4 to 6.5-year-old children.

Method

This research involved 46 volunteers categorized into three groups based on their caries status after follow-up: caries-free (CFee), arrested caries (CArrested), and caries active (CActive). Children underwent visible biofilm examination and saliva collection for salivary flow rate, buffering capacity, and CA VI analyses before and after a 20% sucrose rinse.

Results

A reduction in the buffering capacity was observed after sucrose rinse in all groups. The CA VI activity decreased significantly in CFee and CArrested groups after sucrose rinse, although it did not change in the CActive group. An improvement in the buffering capacity and salivary flow rate was found at follow-up when compared with the baseline. After 1-year follow-up, buffering capacity and salivary flow rate increased in all groups, whilst the CA VI activity reduced only in CFree and CArrested children.

Conclusion

Sucrose rinse universally reduces the salivary buffering capacity, while caries activity may disrupt CA VI activity response during a cariogenic challenge. After a year, increased salivary flow enhances buffering capacity but not CA VI activity in caries-active children.

The morphology and internal structure of dogwood (Cornus L.) endocarps in the taxonomy and phylogeny of the genus

The genus Cornus is known for its complicated taxonomy and extreme polymorphism. Currently, dogwoods are classified into four morphological groups reflected in four phylogenetic clades: blue- or white-fruited dogwoods (BW), cornelian cherries (CC), big-bracted dogwoods (BB), and dwarf dogwoods (DW). The present study is a continuation of a series of papers that started with the examination of the endocarp morphological diversity among BW species. The endocarps of 22 Cornus species were studied according to their morphology, internal structure, and sculpture; the aim was to evaluate the taxonomic importance of the examined characters and check whether endocarp differentiation supports the published phylogenies, according to which the relationships within the genus are indicated as (BW(CC(DW-BB))). Among the quantitative characters, the endocarp’s length, thickness, and width, its length/width ratio, and the number of vascular bundles on its surface were considered taxonomically important. Regarding the qualitative characters, the taxonomic significance of the stone shape, the endocarp apex and base outline, the position of vascular bundles on the endocarp surface, and the presence of the apical cavity and distinct furrow on the endocarp side walls was proved. Additionally, the uniform qualitative characters having a 100% share of a given character state were identified. Cornelian cherries and dwarf dogwoods were characterised by the presence of four uniform characters. In the big-bracted group, two uniform characters were found. Blue- or white-fruited species were the most heterogeneous, with no uniform characters. Regarding the endocarp’s internal structure, the presence of secretory cavities in the endocarp wall and in the septa, the presence of crystals in the outer endocarp, the number of cell layers in the transition sclereid zone, and the primary and secondary sculptures were found to be taxonomically significant. Additionally, the comparative analyses of dogwood endocarps found the following parameters to be useful: the germination valve thickness, the ratio of endocarp wall thickness to endocarp diameter, and the septum’s width and structure. Due to the great differentiation of the examined characters, it was difficult to verify the research hypothesis unambiguously. The calculated similarity coefficients of the endocarps’ qualitative and quantitative characters revealed the highest morphological similarity of endocarps between DW and BB groups, supporting the phylogenetic relationships based on molecular evidence. The number of vascular bundles on the endocarp surface was the character that supported this similarity the most. The similarity coefficients calculated separately for qualitative characters showed the closest similarity between groups CC-DW. However, these results do not directly reflect any of the published phylogenies.

Firmicutes Dysbiosis After Chlorhexidine Prophylaxis in Healthy Patients Submitted to Impacted Lower Third Molar Extraction

Prophylaxis with antiseptic and antibiotic therapy is common in impacted lower third molar surgeries, despite the lack of consensus among professionals and researchers in the indication for healthy patients. The aim of the present preliminary study was to verify the impact of prophylaxis therapy with antiseptic and antibiotic in healthy patients submitted to impacted lower third molar extraction, according to oral microorganism quantification. Eleven patients submitted to impacted lower third molar extraction, under prophylactic therapy with 0.12% chlorhexidine and amoxicillin in four experimental phases, were evaluated. Our results showed no significant reduction in total bacteria load, as well as in Bacteroidetes and C. albicans loads in the oral cavity, after prophylactic therapy with antiseptic and antibiotic. On the other hand, there was a significant difference between the Firmicutes levels across the follow-up, and this effect seems to be large (ηp²=0.94). Post-hoc test demonstrated that the levels of Firmicutes in T1 were higher than T0, T2, and T3, suggesting a microbiota dysbiosis, when 0.12% chlorhexidine use, which may be responsible for selection of antibiotic-resistant microorganisms. Our results alert for an overuse of antiseptic and antibiotics by dentists and for a better evaluation of the available protocols.

Firmicutes Levels in the Mouth Reflect the Gut Condition With Respect to Obesity and Early Childhood Caries

The present cross-sectional study investigated whether Firmicutes (F) and Bacteroidetes (B) levels in the mouth reflected the gut condition in obesity and early childhood caries (ECC). Eighty preschoolers (3-5 years) were equally assigned into four groups: 1. obese + ECC, 2. obese + caries-free (CF), 3. eutrophic + ECC, and 4. eutrophic + CF. Nutritional status and ECC were assessed based on the WHO criteria. Dental biofilm and fecal samples were collected for F and B quantification using RT-PCR analysis. Data were evaluated using three-way-ANOVA and Pearson’s correlation (α = 0.05). Regardless of the anatomical location effect (p = 0.22), there were higher values for F in the obese children + ECC compared with those in obese + caries-free (CF) in both mouth and gut (p < 0.05). The correlation for F at these sites was negative in obese children + ECC (r = −0.48; p = 0.03) and positive in obese children + CF (r=0.50; p = 0.03). Bacteroidetes were influenced by ECC (p = 0.03) and the anatomical location (p = 0.00), and the levels tended to be higher in the mouth of the obese children + ECC (p = 0.04). The F/B ratio was higher in the gut and was affected by the anatomical location (p = 0.00). This preliminary study suggested that modulated by ECC, counts of oral Firmicutes reflected corresponding condition in the gut of obese preschoolers. In addition, we first evidenced that the Firmicutes phylum behave differently according to the nutritional status and caries experience and that supragingival biofilm and gut could share levels of similarity.

Voxelwise Principal Component Analysis of Dynamic [S-Methyl-11C]Methionine PET Data in Glioma Patients

Recent works have demonstrated the added value of dynamic amino acid positron emission tomography (PET) for glioma grading and genotyping, biopsy targeting, and recurrence diagnosis. However, most of these studies are based on hand-crafted qualitative or semi-quantitative features extracted from the mean time activity curve within predefined volumes. Voxelwise dynamic PET data analysis could instead provide a better insight into intra-tumor heterogeneity of gliomas. In this work, we investigate the ability of principal component analysis (PCA) to extract relevant quantitative features from a large number of motion-corrected [S-methyl-¹¹C]methionine ([¹¹C]MET) PET frames. We first demonstrate the robustness of our methodology to noise by means of numerical simulations. We then build a PCA model from dynamic [¹¹C]MET acquisitions of 20 glioma patients. In a distinct cohort of 13 glioma patients, we compare the parametric maps derived from our PCA model to these provided by the classical one-compartment pharmacokinetic model (1TCM). We show that our PCA model outperforms the 1TCM to distinguish characteristic dynamic uptake behaviors within the tumor while being less computationally expensive and not requiring arterial sampling. Such methodology could be valuable to assess the tumor aggressiveness locally with applications for treatment planning and response evaluation. This work further supports the added value of dynamic over static [¹¹C]MET PET in gliomas.

Combined effect of starch and sucrose on carbonic anhydrase VI activity in saliva and biofilm of children with early childhood caries. Exposure to starch and sucrose alters carbonic anhydrase VI activity in saliva and biofilm

OBJECTIVES

This study aimed to investigate whether combined exposure to starch and sucrose modifies the activity of carbonic anhydrase VI (CA VI) in saliva (Study 1) and biofilm (Study 2) of children with early childhood caries (ECC).

MATERIAL AND METHODS

For Study 1 and Study 2, respectively, 54 and 46 preschoolers aged 4 to 5 were allocated into two groups: caries-free (CF) and with ECC. Children were exposed to rinses with sucrose, starch, and sucrose plus starch solutions. CA VI activity, pH, and buffering capacity (BC) were evaluated in saliva and biofilm.

RESULTS

In Study 1, a significant reduction in saliva pH was observed after sucrose and sucrose plus starch rinses. CA VI activity was influenced by ECC independently of the type of carbohydrate to which children were exposed. CA VI activity was higher in children with ECC; however, after rinses, CA VI activity was reduced. In Study 2, biofilm pH and BC were reduced after rinses with sucrose and sucrose plus starch. CA VI activity was significantly high before rinse in ECC group when compared with CF group; however, no difference was observed between groups after rinses.

CONCLUSIONS

In saliva, exposure to starch and sucrose (isolated or combined) induced a reduction in CA VI activity in children with ECC. In biofilm, the combination of starch and sucrose did not modify CA VI activity in ECC children.

CLINICAL RELEVANCE

The responsivity of the CA VI reflects directly in important parameters related to the pH maintenance on the oral cavity.

Combining PCA with DEA to Improve the Evaluation of Project Performance Data: A Taiwanese Bureau of Energy Case Study

This article proposes a new method of project performance evaluation, by which project performance data can be better understood. This article combines principal component analysis (PCA) and data envelopment analysis (DEA) to enhance the efficiency of decision-making units more accurately. The data used was based on energy projects promoted by the Bureau of Energy at the Ministry of Economic Affairs in Taiwan. The results of this article show that by combining PCA and DEA in evaluating the performance of energy projects, there was an improved evaluation of projects over simply using DEA data alone.

Performance of principal component analysis and independent component analysis with respect to signal extraction from noisy positron emission tomography data - a study on computer simulated images

Multivariate image analysis tools are used for analyzing dynamic or multidimensional Positron Emission Tomography, PET data with the aim of noise reduction, dimension reduction and signal separation. Principal Component Analysis is one of the most commonly used multivariate image analysis tools, applied on dynamic PET data. Independent Component Analysis is another multivariate image analysis tool used to extract and separate signals. Because of the presence of high and variable noise levels and correlation in the different PET images which may confound the multivariate analysis, it is essential to explore and investigate different types of pre-normalization (transformation) methods that need to be applied, prior to application of these tools. In this study, we explored the performance of Principal Component Analysis (PCA) and Independent Component Analysis (ICA) to extract signals and reduce noise, thereby increasing the Signal to Noise Ratio (SNR) in a dynamic sequence of PET images, where the features of the noise are different compared with some other medical imaging techniques. Applications on computer simulated PET images were explored and compared. Application of PCA generated relatively similar results, with some minor differences, on the images with different noise characteristics. However, clear differences were seen with respect to the type of pre-normalization. ICA on images normalized using two types of normalization methods also seemed to perform relatively well but did not reach the improvement in SNR as PCA. Furthermore ICA seems to have a tendency under some conditions to shift over information from IC1 to other independent components and to be more sensitive to the level of noise. PCA is a more stable technique than ICA and creates better results both qualitatively and quantitatively in the simulated PET images. PCA can extract the signals from the noise rather well and is not sensitive to type of noise, magnitude and correlation, when the input data are correctly handled by a proper pre-normalization. It is important to note that PCA as inherently a method to separate signal information into different components could still generate PC1 images with improved SNR as compared to mean images.

Analysis and interpretation of dynamic FDG PET oncological studies using data reduction techniques

Background

Dynamic positron emission tomography studies produce a large amount of image data, from which clinically useful parametric information can be extracted using tracer kinetic methods. Data reduction methods can facilitate the initial interpretation and visual analysis of these large image sequences and at the same time can preserve important information and allow for basic feature characterization.

Methods

We have applied principal component analysis to provide high-contrast parametric image sets of lower dimensions than the original data set separating structures based on their kinetic characteristics. Our method has the potential to constitute an alternative quantification method, independent of any kinetic model, and is particularly useful when the retrieval of the arterial input function is complicated. In independent component analysis images, structures that have different kinetic characteristics are assigned opposite values, and are readily discriminated. Furthermore, novel similarity mapping techniques are proposed, which can summarize in a single image the temporal properties of the entire image sequence according to a reference region.

Results

Using our new cubed sum coefficient similarity measure, we have shown that structures with similar time activity curves can be identified, thus facilitating the detection of lesions that are not easily discriminated using the conventional method employing standardized uptake values.

A new application of pre-normalized principal component analysis for improvement of image quality and clinical diagnosis in human brain PET studies—Clinical brain studies using [11C]-GR205171, [11C]-l-deuterium-deprenyl, [11C]-5-Hydroxy-l-Tryptophan, [11C]-l-DOPA and Pittsburgh Compound-B

Principal component analysis (PCA) is one of the most applied multivariate image analysis tool on dynamic Positron Emission Tomography (PET). Independent of used reconstruction methodologies, PET images contain correlation in-between pixels, correlations in-between frame and errors caused by the reconstruction algorithm including different corrections, which can affect the performance of the PCA. In this study, we have investigated a new approach of application of PCA on pre-normalized, dynamic human PET images. A range of different tracers have been used for this purpose to explore the performance of the new method as a way to improve detection and visualization of significant changes in tracer kinetics and to enhance the discrimination between pathological and healthy regions in the brain. We compare the new results with the results obtained using other methods. Images generated using the new approach contain more detailed anatomical information with higher quality, precision and visualization, compared with images generated using other methods.

Data weighting for principal component noise reduction in contrast enhanced ultrasound

Pulse inversion ultrasound is a mechanism for preferentially displaying contrast agent in blood vessels while suppressing signal from tissue. We seek a method for identifying and segmenting areas of the liver with similar statistically significant time intensity curves. As a first step in this process, a method of weighting Rayleigh distributed ultrasound image data before principal components analysis is presented. Simulation studies show that relative mean squared error can be reduced by 14% when the correct number of dimensions in selected. Our method is tested on an in vitro ultrasound phantom showing slightly increased error suppression, and is demonstrated on a clinical liver scan, showing decreased correlation between signals in the low intensity range.

Performance evaluation of principal component analysis in dynamic FDG-PET studies of recurrent colorectal cancer

Performance evaluation of principal component analysis (PCA) of dynamic F-18-FDG-PET studies of patients with recurrent colorectal cancer. Principal component images (PCI) of 17 iteratively reconstructed data sets were visually and quantitatively evaluated. The F-18-FDG compartment model parameters were estimated using polynomial regression. All structures were present in PCI1. PCI2 was correlated with the vascular component and PCI3 with the tumor. The vessel density in the tumor was estimated with a correlation coefficient equal to 0.834. PCA supports the visual interpretation of dynamic F-18-FDG-PET studies, facilitates the application of compartment modeling and is a promising quantification technique.