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Povzetek: Background Ca2+ and H2O2 are second messengers that regulate a wide range of cellular events in response to different environmental and developmental cues. In plants, stress-induced H2O2 has been shown to initiate characteristic Ca2+ signatures; however, a clear picture of the molecular connection between H2O2-induced Ca2+ signals and H2O2-induced cellular responses is missing, particularly in cereal crops such as barley. Here, we employed RNA-seq analyses to identify transcriptome changes in roots and leaves of barley after H2O2 treatment under conditions that inhibited the formation of cytosolic Ca2+ transients. To that end, plasma membrane Ca2+ channels were blocked by LaCl3 application prior to stimulation of barley tissues with H2O2. Results We examined the expression patterns of 4246 genes that had previously been shown to be differentially expressed upon H2O2 application. Here, we further compared their expression between H2O2 and LaCl3 + H2O2 treatment. Genes showing expression patterns different to the previous study were considered to be Ca2+-dependent H2O2-responsive genes. These genes, numbering 331 in leaves and 1320 in roots, could be classified in five and four clusters, respectively. Expression patterns of several genes from each cluster were confirmed by RT-qPCR. We furthermore performed a network analysis to identify potential regulatory paths from known Ca2+-related genes to the newly identified Ca2+-dependent H2O2 responsive genes, using the recently described Stress Knowledge Map. This analysis indicated several transcription factors as key points of the responses mediated by the cross-talk between H2O2 and Ca2+. Conclusion Our study indicates that about 70% of the H2O2-responsive genes in barley roots require a transient increase in cytosolic Ca2+ concentrations for alteration in their transcript abundance, whereas in leaves, the Ca2+ dependency was much lower at about 33%. Targeted gene analysis and pathway modeling identified not only known components of the Ca2+ signaling cascade in plants but also genes that are not yet connected to stimuli-associated signaling. Potential key transcription factors identified in this study can be further analyzed in barley and other crops to ultimately disentangle the underlying mechanisms of H2O2-associated signal transduction mechanisms. This could aid breeding for improved stress resistance to optimize performance and productivity under increasing climate challenges.
Ključne besede: ROS, stress, RNA-Seq, Ca2+ signaling, crosstalk, Hordeum vulgare
Objavljeno v DiRROS: 03.04.2025; Ogledov: 16; Prenosov: 6
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Povzetek: The gut microbiome, a diverse community of microorganisms in the human body, plays an important role in maintaining health and influences various processes such as digestion, immunity, and protection against pathogens. A person's unique gut microbiome, shaped by factors such as birth method, diet, antibiotics, and lifestyle, contributes to bodily functions such as nutrient metabolism, drug processing, and im-mune regulation. Changes in the gut microbiome are associated with a predisposition to cancer and can influence the effectiveness of cancer treatments. Dysbiosis in the gut microbiome can lead to inflammation, tumor development, and metastasis, highlight-ing its importance in cancer research and prevention. The gut microbiota significantly influences cancer development and treatment outcomes. Certain bacteria enhance the effects of therapies such as cyclophosphamide and contribute to the body's im-mune response against tumors. Microbes produce anti-cancer molecules and probiotic compounds, making them potential tools in cancer prevention and treatment. Future research aims to develop targeted antibiotics and explore fecal microbiota transfer to selectively manipulate the microbiota for improved cancer treatment. Due to genetic and physiological similarities, mouse models are invaluable in biomedical research. However, because the gut microbiome of humans and mice and the composition of the tumor microenvironment differ, direct comparison between these two models can be challenging in research. Bridging these gaps is crucial for comparative medicine, especially in cancer research where the microbiome plays an important role in treat-ment outcomes. One important area where the gut microbiome could offer potential new treatment options is in primary brain tumors such as gliomas. To date, there are no long-lasting effective treatments for this type of cancer, but research in mouse models shows a link between tumor progression and response to treatment with changes in the gut microbiome. Overall, the gut microbiome and its modulation represent an opportu-nity for more efficient future cancer treatment.
Ključne besede: gut microbiome, cancer, treatment outcome, tumor models, glioma
Objavljeno v DiRROS: 03.04.2025; Ogledov: 15; Prenosov: 7
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Povzetek: Accurate modeling of sea level and storm surge dynamics with several days of temporal horizons is essential for effective coastal flood responses and the protection of coastal communities and economies. The classical approach to this challenge involves computationally intensive ocean models that typically calculate sea levels relative to the geoid, which must then be correlated with local tide gauge observations of sea surface height (SSH). A recently proposed deep-learning model, HIDRA2 (HIgh-performance Deep tidal Residual estimation method using Atmospheric data, version 2), avoids numerical simulations while delivering competitive forecasts. Its forecast accuracy depends on the availability of a sufficiently long history of recorded SSH observations used in training. This makes HIDRA2 less reliable for locations with less abundant SSH training data. Furthermore, since the inference requires immediate past SSH measurements as input, forecasts cannot be made during temporary tide gauge failures. We address the aforementioned issues using a new architecture, HIDRA3, that considers observations from multiple locations, shares the geophysical encoder across the locations, and constructs a joint latent state that is decoded into forecasts at individual locations. The new architecture brings several benefits: (i) it improves training at locations with scarce historical SSH data, (ii) it enables predictions even at locations with sensor failures, and (iii) it reliably estimates prediction uncertainties. HIDRA3 is evaluated by jointly training on 11 tide gauge locations along the Adriatic. Results show that HIDRA3 outperforms HIDRA2 and the Mediterranean basin Nucleus for European Modelling of the Ocean (NEMO) setup of the Copernicus Marine Environment Monitoring Service (CMEMS) by ∼ 15 % and ∼ 13 % mean absolute error (MAE) reductions at high SSH values, creating a solid new state of the art. The forecasting skill does not deteriorate even in the case of simultaneous failure of multiple sensors in the basin or when predicting solely from the tide gauges far outside the Rossby radius of a failed sensor. Furthermore, HIDRA3 shows remarkable performance with substantially smaller amounts of training data compared with HIDRA2, making it appropriate for sea level forecasting in basins with high regional variability in the available tide gauge data.
Ključne besede: sea level modeling, deep learning, storm surges
Objavljeno v DiRROS: 03.04.2025; Ogledov: 23; Prenosov: 8
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Ključne besede: bioobnovljivi viri, epoksidni temeljni premazi, poliuretanski pokrivni premaz, poliuretanski enoslojni premaz, trajnost, diplomsko delo
Objavljeno v DiRROS: 03.04.2025; Ogledov: 21; Prenosov: 0
Celotno besedilo (2,90 MB)

Ključne besede: recikliranje duroplastničnih kompozitov, kompavdiranje, brizganje, steklena vlakna, ogljikova vlakna, PA6GF50, karakterizacija, diplomsko delo
Objavljeno v DiRROS: 03.04.2025; Ogledov: 25; Prenosov: 4
Celotno besedilo (4,23 MB)