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Adaptive Multiclassification With Lung Cancer Types Using High-Dimensional Discriminant Analysis and Machine Learning Methods
(2025-01-01)
Araveeporn, Autcha
This research investigates adaptive multiclassification methods for classifying lung cancer types using both high-dimensional discriminant analysis (HDDA) and widely used machine learning (ML) approaches under challenging data conditions, including high dimensionality, multicollinearity, outliers, and imbalanced classes. The dataset consists of 1000 gene expressions as explanatory variables and four lung cancer types as response variables, categorizing the problem as high-dimensional and imbalanced. HDDA introduces a statistically principled parametrization of the covariance matrix tailored for high-dimensional data. At the same time, ML methods such as Naïve Bayes, K-Nearest Neighbors, Support Vector Machine, Artificial Neural Network, and Random Forest offer flexible, data-driven alternatives. While previous studies have separately investigated either discriminant analysis or ML, there is a lack of comparative studies that evaluate their performance simultaneously under such complex conditions. This study addresses this gap by systematically analyzing both approaches with balanced and imbalanced gene expression data. The central hypothesis of this study is that HDDA, despite being a classical statistical technique, can achieve performance comparable to or complementary with ML methods when applied to gene expression data. Experiments on both original and balanced datasets, across varying subsets of explanatory variables, show that data balancing consistently improves accuracy, precision, and recall. Among ML methods, Random Forest achieves the highest predictive performance on balanced data, while HDDA provides competitive and interpretable results across scenarios.
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Non-Pathogenic Pythium Induced the Resistance in Hydroponic Lettuce Against Root Rot Disease
(2024-05-01)
Talubnak, Chulalak
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Parinthawong, Nonglak
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Schoonbeek, Henk Jan
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Jaenaksorn, Tanimnun
Hydroponics is a common soilless type of culture. It is clean and gives high-yield crop production. Lettuce is the most widely grown leafy vegetable in hydroponics. The Pythium species causes root rot, a serious disease in lettuce. In this study, we investigated an effective elicitor to promote resistance in lettuce after pathogen infection. To evaluate the plant defense gene response profile, the expression stability of five candidate genes was studied using RT-qPCR. The LsPR1 and LsLTC2 gene expression were higher in lettuce leaves treated with non-pathogenic Pythium PyASR23 than in roots compared to untreated plants. To assess the disease, the rate of relative gene expression of LsLTC2, LsPR-1b like, LsERF, LsAOS, and LsDEF was associated with Pythium root rot pathogenesis. As a result, it was revealed that alterations in these gene expressions were a defense response to Pythium infection, which increased after pre-treatment with various elicitors for 24 hours. When the chemically stimulated lettuce was infected with pathogenic PySR31, the expression of these genes increased dramatically. These results suggested that non-pathogenic PyASR23 might be employed as an elicitor in lettuce roots and contribute to disease control by activating plant defense gene expression against the Pythium pathogen.
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Dark fermentative hydrogen production and transcriptional analysis of genes involved in the unicellular halotolerant cyanobacterium Aphanothece halophytica under nitrogen and potassium deprivation
(2023-01-06)
Chinchusak, Nattanon
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Incharoensakdi, Aran
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Phunpruch, Saranya
The unicellular halotolerant cyanobacterium Aphanothece halophytica is known as a potential hydrogen (H<inf>2</inf>) producer. This study aimed to investigate the enhancement of H<inf>2</inf> production under nutrient deprivation. The results showed that nitrogen and potassium deprivation induced dark fermentative H<inf>2</inf> production by A. halophytica, while no differences in H<inf>2</inf> production were found under sulfur and phosphorus deprivation. In addition, deprivation of nitrogen and potassium resulted in the highest H<inf>2</inf> production in A. halophytica due to the stimulation of hydrogenase activity. The effect of adaptation time under nitrogen and potassium deprivation on H<inf>2</inf> production was investigated. The results showed that the highest H<inf>2</inf> accumulation of 1,261.96 ± 96.99 µmol H<inf>2</inf> g dry wt−1 and maximum hydrogenase activity of 179.39 ± 8.18 µmol H<inf>2</inf> g dry wt−1 min−1 were obtained from A. halophytica cells adapted in the nitrogen- and potassium-deprived BG11 medium supplemented with Turk Island salt solution (BG11<inf>0</inf>-K) for 48 h. An increase in hydrogenase activity was attributed to the decreased O<inf>2</inf> concentration in the system, due to a reduction of photosynthetic O<inf>2</inf> evolution rate and a promotion of dark respiration rate. Moreover, nitrogen and potassium deprivation stimulated glycogen accumulation and decreased specific activity of pyruvate kinase. Transcriptional analysis of genes involved in H<inf>2</inf> metabolism using RNA-seq confirmed the above results. Several genes involved in glycogen biosynthesis (glgA, glgB, and glgP) were upregulated under both nitrogen and potassium deprivation, but genes regulating enzymes in the glycolytic pathway were downregulated, especially pyk encoding pyruvate kinase. Interestingly, genes involved in the oxidative pentose phosphate pathway (OPP) were upregulated. Thus, OPP became the favored pathway for glycogen catabolism and the generation of reduced nicotinamide adenine dinucleotide phosphate (NADPH), which resulted in an increase in H<inf>2</inf> production under dark anaerobic condition in both nitrogen- and potassium-deprived cells.
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Expression Analyses in the Rachis Hint towards Major Cell Wall Modifications in Grape Clusters Showing Berry Shrivel Symptoms
(2022-08-01)
Savoi, Stefania
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Supapvanich, Suriyan
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Hildebrand, Heinrich
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Stralis-Pavese, Nancy
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Forneck, Astrid
Berry shrivel (BS) is one of the prominent and still unresolved ripening physiological disorders in grapevine. The causes of BS are unclear, and previous studies focused on the berry metabolism or histological studies, including cell viability staining in the rachis and berries of BS clusters. Herein, we studied the transcriptional modulation induced by BS in the rachis of pre-symptomatic and symptomatic clusters with a custom-made microarray qPCR in relation to a previous RNASeq study of BS berries. Gene set analysis of transcript expression in symptomatic rachis tissue determined suppression of cell wall biosynthesis, which could also be confirmed already in pre-symptomatic BS rachis by CESA8 qPCR analyses, while in BS berries, a high number of SWITCH genes were suppressed at veraison. Additionally, genes associated with the cell wall were differently affected by BS in berries. A high percentage of hydrolytic enzymes were induced in BS grapes in rachis and berries, while other groups such as, e.g., xyloglucan endotransglucosylase/hydrolase, were suppressed in BS rachis. In conclusion, we propose that modulated cell wall biosynthesis and cell wall assembly in pre-symptomatic BS rachis have potential consequences for cell wall strength and lead to a forced degradation of cell walls in symptomatic grape clusters. The similarity to sugar starvation transcriptional profiles provides a link to BS berries, which are low in sugar accumulation. However, further studies remain necessary to investigate the temporal and spatial coordination in both tissues.

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