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1

Evaluation of changes caused by HR-HPV infection in squamous cell carcinoma of the head and neck using Raman microspectroscopy in combination with multivariate statistical analysis

Szurko Agnieszka, Zygadło Dorota, Student Sebastian, Śnietura Mirosław, Lorenc Zbigniew, Kiełboń Agnieszka, Waniczek Dariusz

Polish Journal of Medical Physics and Engineering

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2024

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Vol. 30, Iss. 2

69--78

EN

Introduction: Squamous cell carcinoma of the head and neck region (HNSCC), with a positive status for high oncogenic potential human papillomavirus (HR-HPV), represents a clinically distinct disease entity compared to HPV-independent cases. Patients exhibit variations in prognosis and proposed therapy regimens. A prompt and reliable diagnosis of the presence of HPV infection could optimize the treatment for these patients. Currently employed treatment methods are long-term, expensive, and lack specificity, especially when administered separately. Material and methods: The research objective of this study is to explore significant differences in the Raman spectra of biological samples taken from patients with HNSCC, facilitating the confirmation of HPV virus presence. Study groups were delineated based on histopathological diagnosis and molecular biology tests, confirming the biological activity of the virus and the presence of the HR-HPV form with a diagnosis of a specific subtype. Results: To identify high oncogenic potential human papillomavirus (HR-HPV) infection as a crucial factor in squamous cell carcinoma of the head and neck region, an effective automatic data analysis system was established, relying on Raman microspectroscopy and multivariate analysis. Our results showed clear ranges of the Raman spectrum that differentiated between HPV-associated and non-HPV-associated cancers. Conclusions: In conclusion, our experience shows a great diagnostic potential of Raman confocal microscopy with multidimensional statistical analysis. In the future, the use of this method may allow for the creation of an effective and automated HR-HPV detection system in neoplastic tissue.

2

Analysis of groundwater quality in the lower Soummam Valley, North-East of Algeria

Ghodbane Messaoud, Benaabidate Lahcen, Boudoukha Abderrahmane, Gaagai Aissam, Adjissi Omar, Chaib Warda, Aouissi Hani Amir

Journal of Water and Land Development

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2022

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no. 54

1--12

EN

Analysis of groundwater quality in the alluvial aquifer of the lower Soummam Valley, North-East of Algeria, was realised through the application of multivariate statistical methods: hierarchical cluster analysis (HCA) in Q and R modes, factorial correspondence analysis (FCA), and principal component analysis (PCA), to hydrochemical data from 51 groundwater samples, collected from 17 boreholes during periods of June, September 2016 and March 2017. The objectives of this approach are to characterise the water quality and to know the factors which govern its evolution by processes controlling its chemical composition. The Piper diagram shows two hydrochemical facies: calcium chloride and sodium bicarbonate. Statistical techniques HCA, PCA, and FCA reveal two groups of waters: the first (EC, Ca2+, Mg2+, Cl-, SO42- and NO3-) of evaporitic origin linked to the dissolution processes of limestone rocks, leaching of saliferous soils and anthropogenic processes, namely contamination wastewater and agricultural activity, as well marine intrusion; and the second group (Na+, K+, and HCO3-) of carbonated origin influenced by the dissolution of carbonate formations and the exchange of bases. The hermodynamic study has shown that all groundwater is undersaturated with respect to evaporitic minerals. On the other hand, it is supersaturated with respect to carbonate minerals, except for water from boreholes F9, F14, and F16, which possibly comes down to the lack of dissolution and arrival of these minerals. The results of this study clearly demonstrate the utility of multivariate statistical methods in the analysis of groundwater quality.

3

Analysis of Spatial-Temporal Variations of Surface Water Quality in the Southern Province of Vietnamese Mekong Delta Using Multivariate Statistical Analysis

Hong Tran Thi Kim, Viet Le Hoang, Giao Nguyen Thanh

Journal of Ecological Engineering

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2022

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Vol. 23, nr 7

1--9

EN

The study aimed to assess the variation in surface water quality in the Tien Giang province, Vietnam, and at the same time identify the main sources of water pollution. The surface water quality samples were collected at 34 locations (NM01-NM34) with 17 surface water quality indicators in March, June, September and November in canals and rivers in the Tien Giang province. Multivariate statistical analysis methods, including principal component analysis (PCA), cluster analysis (CA) and numerical discriminant analysis (DA), were used to analyze the variability and key indicators affecting the effect of multivariate statistical analysis. The analysis results show that the surface water quality in the study area is contaminated with organic (low DO, high BOD and COD) and nutrients (NH4+-N, NO2--N, PO43--P and TP), salinity (high Cl-). The PCA results showed that 14/17 surface water environmental parameters to be monitored are pH, temperature, TSS, BOD, COD, NH4+-N, NO2--N, PO43--P, TP, SO42-, Cl-, coliform and Fe. The PCA analysis showed that PC1-PC4 accounted for 79.70% of the variation in surface water quality in the study area. Potential surface water polluting sources include hydrological regime, domestic waste, agricultural production, industrial production activities. The CA results showed that 34 monitoring locations can be reduced to 27 locations, with a frequency of 4 times/year to ensure surface water quality representativeness. The DA indicated that the indicators of EC, SO42- and Cl- made the difference of the surface water quality between the wet and dry seasons. The current results provide important information on the current state of water quality for different uses and contribute to the improvement of the surface water quality monitoring system in the Tien Giang province.

4

Impact of the heated water discharge on the water quality in a shallow lowland dam reservoir

Mazierski Jerzy, Kostecki Maciej

Archives of Environmental Protection

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2021

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Vol. 47, no. 2

29--46

EN

The purpose of the work was to determine the relationship between the of the water quality parameters in an artificial reservoir used as cooling ponds. Factor analysis were applied to analyze eighteen physico- -chemical parameters such as air and water temperature, dissolved oxygen concentration, visibility of the Secchi disk, concentrations of total nitrogen, ammonium, nitrate, nitrite, total phosphorus, phosphate, concentrations of calcium, magnesium, chlorides, sulfates and total dissolved salts, pH, chemical oxygen demand and electric conductivity from 2002-2019 to investigated cooling water discharge. Exploratory factor analysis allowed identified four factors were obtained from 54.1% (in discharge zone) to 56.7% (in dam zone). In discharge and pelagic zones confirmatory factor analysis showed that four latent variables: salinity, temperature, nitrogen and phosphorus provide good fit, but in the dam zone the better fit was obtained for the latent variables salinity, temperature, nutrient and eutrophic. Correlations between latent variables temperature, nitrogen, phosphorus or nutrient and eutrophic show a significant effect of temperature on the transformation of nitrogen and phosphorus compounds.

5

Assessment of the possibility of implementing small retention reservoirs in terms of the need to increase water resources

Wiatkowski Mirosław, Wiatkowska Barbara, Gruss Łukasz, Rosik-Dulewska Czesława, Tomczyk Paweł, Chłopek Dawid

Archives of Environmental Protection

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2021

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Vol. 47, no. 1

80--100

EN

Currently, due to reduced water resources, there is a need to build reservoirs in Poland. Reservoirs perform important economic, natural and recreational functions in the environment, improve water balance and contribute to flood protection. In the construction of reservoirs, it is necessary to consider not only hydrological issues related to water quantity, but also its quality, silting, and many other factors. Therefore, the physiographic, hydrological, hydrochemical, and hydrogeological conditions of the projected reservoirs have to be taken into account to limit the potential negative effects of decisions to build them. In order to assess the suitability of eight projected small water retention reservoirs (to increase water resources in the Barycz River catchment in Lower Silesia and Greater Poland provinces, this article takes into account hydrological indicators (efficiency of the reservoir, operation time, dependence on the intensity of silting, and flood hazard indicator), water quality (phosphorus load and nitrogen load), hydrogeological conditions (type of geological substratum for the reservoir basin and filtration losses), and safety of the reservoir dam. To develop a theoretical model describing the regularities between the indicators, multivariate statistical techniques were used, including the Principal Component Analysis (PCA) and the Factor Analysis (FA). In order to assess the reservoirs, a synthetic indicator was developed to compare the reservoirs with each other in relation to the conditions. The Cluster Analysis (CA) was used for typological classification of homogeneous locations of projected small retention reservoirs. Own research procedure for identification of the most advantageous water reservoirs, with the use of multivariate statistical techniques, may be used as a tool supporting decision making in other facilities intended for implementation in provincial projects of small retention.

PL

Obecnie w Polsce z powodu zmniejszonych zasobów wodnych istnieje potrzeba budowy zbiorników wodnych. Pełnią one w środowisku ważne funkcje gospodarcze, przyrodnicze, rekreacyjne, poprawiają bilans wodny i przyczyniają się do ochrony przeciwpowodziowej. Budując zbiornik wodny, oprócz zagadnień hydrologicznych związanych z ilością wody, należy wziąć pod uwagę jakość wody, która będzie retencjonowana w zbiorniku, jego zamulenie oraz szereg innych aspektów. Bardzo ważna jest więc analiza uwarunkowań zbiorników planowanych, w tym fizjograficznych, hydrologicznych, hydrochemicznych i hydrogeologicznych, aby ograniczyć potencjalne negatywne skutki podejmowania decyzji o budowie takich obiektów. W celu oceny możliwości realizacji ośmiu planowanych zbiorników małej retencji wodnej w kontekście potrzeby zwiększania zasobów wodnych na obszarze zlewni Barycz w województwie dolnośląskim i wielkopolskim w niniejszym artykule uwzględniono wskaźniki hydrologiczne (sprawność zbiornika, czas eksploatacji ze względu na intensywność zamulania, wskaźnik potencjalnego zagrożenia powodzią), jakości wody (obciążenie ładunkiem fosforu i azotu), hydrogeologiczne (rodzaj podłoża geologicznego pod czaszę zbiornika wodnego i straty filtracyjne) oraz bezpieczeństwa zapory zbiornika. Do opracowania teoretycznego modelu, opisującego prawidłowości zachodzące pomiędzy tymi wskaźnikami, wykorzystano wielowymiarowe techniki statystyczne takie jak: Principal Component Analysis (PCA) i Factor Analysis (FA). W celu oceny planowanych zbiorników w aspekcie najbardziej korzystnych do realizacji opracowano syntetyczny wskaźnik, który umożliwił porównanie tych zbiorników w odniesieniu do rozpatrywanych uwarunkowań. Wykonano również z zastosowaniem Cluster Analysis (CA) typologiczną klasyfikację planowanych zbiorników małej retencji wodnej pod względem jednorodnych lokalizacji na analizowanym obszarze. Zaproponowana w niniejszej pracy autorska procedura badawcza identyfikacji najkorzystniejszych, spośród planowanych do realizacji, zbiorników wodnych z zastosowaniem wielowymiarowych technik statystycznych, może posłużyć jako narzędzie wspomagające podejmowanie decyzji przy innych obiektach planowanych do realizacji w wojewódzkich planach rozwoju małej retencji.

6

Phytochemical analysis of trifoliate orange during fermentation by HPLC–DAD–ESI–MS/MS coupled with multivariate statistical analysis

Gao Dan, Cho Chong Woon, Vinh Le Ba, Kim Jin Hyeok, Kim Young Ho, Kang Jong Seong

Acta Chromatographica

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2021

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Vol. 33, no. 4

371--377

EN

During the process of fermentation, the chemical compositions of trifoliate orange (Poncirus trifoliate (L). Raf) changed greatly. To provide a completely phytochemical profile, high-performance liquid chromatography-diode array detector-hyphenated with tandem mass spectrometry (HPLC–DAD–ESIMS/ MS) has been successfully applied to screen and identify the unknown constituents of trifoliate orange during fermentation, which make it available for the quality control of fermented products. Multivariate statistical analysis was performed to classify the trifoliate oranges based on the status of fermentation. A total of 8 components were identified among the samples. Hierarchical Clustering Analysis (HCA) and Principal Component Analysis (PCA) demonstrated the fermented and unfermented trifoliate oranges were obviously different, an effective and reliable Partial Least Square Discriminate Analysis (PLS-DA) technique was more suitable to provide accurate discrimination of test samples based their different chemical patterns. Furthermore, a permutation validated the reliability of PLS-DA and variable importance plot revealed that the characterized syringing, naringin, and poncirin showed the high ability to distinguish the trifoliate oranges during fermentation. The present investigation could provide detailed information for the quality control and evaluation of trifoliate oranges during the fermentation process.

7

Hydrochemistry and origin of principal major elements in the groundwater of the Béchar–Kénadsa basin in arid zone, South-West of Algeria

Lachache S., Nabou M., Merzouguui T., Amroune A.

Journal of Water and Land Development

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2018

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no. 36

77--87

EN

Béchar region is located in the southwest of Algeria, characterized by an arid climate with a Saharan tendency. It is subject to an increasing demand for water like all the great agglomerations due to the economic and demographic development. The groundwater of region is deteriorating because of the economic development, and the rapid growth of population. This article is devoted to the study of hydrochemistry and processes of mineralization of groundwater in this region. The results of physicochemicals analyses shows the same chemical facies of the chloride and sulphate-calcium and magnesium type, with high mineralization from North-East to South- -West to the outlet of Béchar–Kénadsa basin. The determination of the mineralization origin and the main major elements were approached by multivariate statistical treatment and geochemical. This method has identified the main chemical phenomena involved in the acquisition of mineralization of water in this aquifer. These phenomena are mainly related to the dissolution of evaporite formations, the infiltration of runoff water and direct ion exchange and mixing. However, the high mineralization anomaly is observed at the centre of Béchar–Kénadsa basin progressively by going to the outlet of this basin.

PL

Region Béchar w południowozachodniej Algierii charakteryzuje klimat suchy z wpływami saharyjskimi. Jak wszystkie duże aglomeracje, region ten wykazuje rosnące zapotrzebowanie na wodę w związku z rozwojem ekonomicznym i demograficznym. Rozwój gospodarczy i szybki przyrost populacji jest powodem pogarszania się jakości wód gruntowych. Niniejszy artykuł jest poświęcony badaniom właściwości hydrochemicznych i procesów mineralizacji wód gruntowych w regionie. Wyniki analiz wykazują występowanie podobnych facji chemicznych typu chlorkowego i siarczanowo-wapniowych lub magnezowych o wysokim stopniu mineralizacji od północnego wschodu do południowego zachodu basenu Béchar–Kénadsa. Źródła mineralizacji i główne pierwiastki zostały oznaczone metodami geochemicznymi z zastosowaniem wieloczynnikowej analizy statystycznej. Metody te dały podstawy do identyfikacji głównych zjawisk chemicznych wpływających na mineralizację wody, takie jak rozpuszczanie formacji ewaporytowych, infiltracja spływów powierzchniowych, bezpośrednia wymiana jonowa i mieszanie. Anomalię wysokiej mineralizacji malejącą w kierunku odpływu zaobserwowano w środkowej części basenu Béchar–Kénadsa.

8

Application of the spatial data mining module in analysis of mining ground deformation factors

Blachowski J., Stefaniak P.

Mining Science

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2013

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Vol. 20

5--17

EN

Spatial data mining methods for example those based on artificial neural networks (ANN) allow extraction of information from databases and detection of otherwise hidden patterns occurring in these data and in consequence acquiring new knowledge on the analysed phenomena or processes. One of these techniques is the multivariate statistical analysis, which facilitates identification of patterns otherwise difficult to observe. In the paper an attempt of applying self-organising maps (SOM) to explore and analyse spatial data related to studies of ground subsidence associated with underground mining has been described. The study has been carried out on a selected part of a former underground coal mining area in SW Poland with the aim to analyse the influence of particular ground deformation factors on the observed subsidence and the relationships between these factors. The research concerned the uppermost coal panels and the following factors: mining system, time of mining activity and inclination, thickness and depth below the ground of the exploited coal panels. It has been found that the exploratory spatial data analysis can be used to identify relationships in multidimensional data related to mining induced ground subsidence. The proposed approach may be found useful in identification of areas threatened by mining related subsidence and in creating scenarios of developing deformation zones and therefore aid spatial development of mining grounds.

PL

Metody eksploracji danych przestrzennych na przykład te oparte na sztucznych sieciach neuronowych (SSN) pozwalają na ekstrakcję informacji z baz danych i wykrywanie ukrytych relacji występujących w tych danych, a w konsekwencji pozyskiwanie nowej wiedzy o analizowanych zjawiskach i procesach. Jedną z grup technik eksploracji danych przestrzennych jest statystyczna analiza wielowymiarowa (ang. multivariate statistical analysis), która umożliwia identyfikację wzorców inaczej trudnych do wykrycia. W pracy przedstawiono próbę zastosowania metodyki samoorganizujacyh się map (SOM) w eksploracji i analizie danych przestrzennych na potrzeby wspomagania badań deformacji powierzchni spowodowanych podziemną działalnością górniczą. Badania przeprowadzono na wybranym fragmencie dawnego zagłębia węgla kamiennego w Polsce w celu analiz wpływu czynników deformacji górotworu na obserwowane osiadania powierzchni i związków między tymi czynnikami. Dotyczyły one dwóch górnych pokładów węgla i następujących czynników: system eksploatacji, okres eksploatacji, nachylenie, miąższość i głębokość eksploatowanych pokładów poniżej powierzchni terenu. W wyniku przeprowadzonych badań stwierdzono przydatność metody SOM do identyfikacji związków w danych wielowymiarowych dotyczących deformacji terenów górniczych Proponowane podejście może także znaleźć zastosowanie w identyfikacji obszarów zagrożonych osiadaniami oraz w budowaniu scenariuszy rozwoju stref deformacji, a przez to wspomaganie planowania zagospodarowania przestrzennego takich obszarów.

9

Identification of water quality and benthos characteristics in Daya Bay, China, from 2001 to 2004

Wang Y-S., Sun C-C., Lou Z-P., Wang H., Mitchell B.G., Wu M-L., Sun Z-X.

Oceanological and Hydrobiological Studies

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2011

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Vol. 40, No.1

82-95

EN

Physicochemical and benthos data were collected from 12 marine monitoring stations in Daya Bay, during 2001-2004. 12 stations in Daya Bay could be grouped into three clusters: cluster I consisted of stations in the southern part of Daya Bay (stations S1, S2 and S6); cluster II consisted of stations in the cage culture areas (stations S3, S4, S5 and S8); cluster III consisted of stations in the southwest, the middle and the northeast of the Bay (stations S7, S9, S10, S11 and S12). Calculation with bivariate correlations between benthos and major physicochemical factors showed that the density of benthos in all stations correlated positively with temperature, DO, pH, NH4-N, SiO3-Si, SiO3-Si /PO4-P and chlorophyll a and was negatively correlated with salinity, Secchi, COD, NO3-N, NO2-N, TIN, PO4-P, TIN/PO4-P and BOD5. Factor analysis showed that there were high positive loading salinity, Secchi and NH4-N of three clusters. Results revealed that temperature, DO, pH, SiO3-Si and SiO3-Si/PO4-P and chlorophyll a could also play an important role in determining the biomass of benthos in Daya Bay, especially near the Nuclear Power Plants, in the southern part and in the cage culture areas.

10

Demonstration of a new indicator for studying upwelling in the northern South China Sea

Lin L., Wang Y-S., Sun C-C., Li N., Wang H., Mitchell B.G., Wu M-L., Song H., Wu J-F.

Oceanologia

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2011

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No. 53 (2)

605-622

EN

In order to demonstrate that silicate can be used as an indicator to study upwelling in the northern South China Sea, hierarchical cluster analysis (CA) and principle component analysis (PCA) were applied to analyse the metrics of the data consisting of 14 physical-chemical-biological parameters at 32 stations. CA categorized the 32 stations into two groups (low and high nutrient groups). PCA was applied to identify five Principal Components (PCs) explaining 78.65% of the total variance of the original data. PCA found important factors that can describe nutrient sources in estuarine, upwelling, and non-upwelling areas. PC4, representing the upwelling source, is strongly correlated to silicate (SiO3-Si). The spatial distribution of silicate from the surface to 200 m depth clearly showed the upwelling regions, which is also supported by satellite observations of sea surface temperature.

11

Multivariate statistical analysis of water quality and phytoplankton characteristics in Daya Bay, China, from 1999 to 2002

Wang Y-S., Lou Z-P., Sun C-C., Wu M-L., Han S-H.

Oceanologia

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2006

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No. 48 (2)

193-211

EN

This study analyzed seasonal physicochemical and phytoplankton data collected at 12 marine monitoring stations in Daya Bay from 1999 to 2002. Cluster analysis based on water quality and phytoplankton parameters measured at the 12 stations could be grouped into three clusters: cluster I - stations S1, S2, S7 and S11 in the southern part and the north-eastern part of Daya Bay; cluster II - stations S5, S6, S9, S10 and S12 in the central and north-eastern parts of Daya Bay; cluster III - stations S3, S4 and S8 in the cage culture areas in the south-western part of Daya Bay and in the north-western part of the Bay near Aotou harbor. Bivariate correlations between phytoplankton density and the major physical and nutrient factors were calculated for all stations. Factor analysis shows that there were high positive loadings of pH, TIN and the ratio of TIN to PO4-P in the three clusters, which indicates that all the stations in the three clusters were primarily grouped according to their respective nutrient conditions.