The fungus Acremonium alternatum enhances salt stress tolerance by regulating host redox homeostasis and phytohormone signaling.

While endophytic fungi offer promising avenues for bolstering plant resilience against abiotic stressors, the molecular mechanisms behind this biofortification remain largely unknown. This study employed a multifaceted approach, combining plant physiology, proteomic, metabolomic, and targeted hormonal analyses to illuminate the early response of Brassica napus to Acremonium alternatum during the nascent stages of their interaction. Notably, under optimal growth conditions, the initial reaction to fungus was relatively subtle, with no visible alterations in plant phenotype and only minor impacts on the proteome and metabolome. Interestingly, the identified proteins associated with the Acremonium response included TUDOR 1, Annexin D4, and a plastidic K+ efflux antiporter, hinting at potential processes that could counter abiotic stressors, particularly salt stress. Subsequent experiments validated this hypothesis, showcasing significantly enhanced growth in Acremonium-inoculated plants under salt stress. Molecular analyses revealed a profound impact on the plant's proteome, with over 50% of salt stress response proteins remaining unaffected in inoculated plants. Acremonium modulated ribosomal proteins, increased abundance of photosynthetic proteins, enhanced ROS metabolism, accumulation of V-ATPase, altered abundances of various metabolic enzymes, and possibly promoted abscisic acid signaling. Subsequent analyses validated the accumulation of this hormone and its enhanced signaling. Collectively, these findings indicate that Acremonium promotes salt tolerance by orchestrating abscisic acid signaling, priming the plant's antioxidant system, as evidenced by the accumulation of ROS-scavenging metabolites and alterations in ROS metabolism, leading to lowered ROS levels and enhanced photosynthesis. Additionally, it modulates ion sequestration through V-ATPase accumulation, potentially contributing to the observed decrease in chloride content.

Utility of texture analysis for objective quantitative ex vivo assessment of meningioma consistency: method proposal and validation.

BACKGROUND: Tumor consistency is considered to be a critical factor for the surgical removal of meningiomas and its preoperative assessment is intensively studied. A significant drawback in the research of predictive methods is the lack of a clear shared definition of tumor consistency, with most authors resorting to subjective binary classification labeling the samples as "soft" and "hard." This classification is highly observer-dependent and its discrete nature fails to capture the fine nuances in tumor consistency. To compensate for these shortcomings, we examined the utility of texture analysis to provide an objective observer-independent continuous measure of meningioma consistency. METHODS: A total of 169 texturometric measurements were conducted using the Brookfield CT3 Texture Analyzer on meningioma samples from five patients immediately after the removal and on the first, second, and seventh postoperative day. The relationship between measured stiffness and time from sample extraction, subjectively assessed consistency grade and histopathological features (amount of collagen and reticulin fibers, presence of psammoma bodies, predominant microscopic morphology) was analyzed. RESULTS: The stiffness measurements exhibited significantly lower variance within a sample than among samples (p = 0.0225) and significant increase with a higher objectively assessed consistency grade (p = 0.0161, p = 0.0055). A significant negative correlation was found between the measured stiffness and the time from sample extraction (p < 0.01). A significant monotonic relationship was revealed between stiffness values and amount of collagen I and reticulin fibers; there were no statistically significant differences between histological phenotypes in regard to presence of psammoma bodies and predominant microscopic morphology. CONCLUSIONS: We conclude that the values yielded by texture analysis are highly representative of an intrinsic consistency-related quality of the sample despite the influence of intra-sample heterogeneity and that our proposed method can be used to conduct quantitative studies on the role of meningioma consistency.

Zinc effects on bacteria: insights from Escherichia coli by multi-omics approach.

IMPORTANCE: A long-term exposure of bacteria to zinc oxide and zinc oxide nanoparticles leads to major alterations in bacterial morphology and physiology. These included biochemical and physiological processes promoting the emergence of strains with multi-drug resistance and virulence traits. After the removal of zinc pressure, bacterial phenotype reversed back to the original state; however, certain changes at the genomic, transcriptomic, and proteomic level remained. Why is this important? The extensive and intensive use of supplements in animal feed effects the intestinal microbiota of livestock and this may negatively impact the health of animals and people. Therefore, it is crucial to understand and monitor the impact of feed supplements on intestinal microorganisms in order to adequately assess and prevent potential health risks.

Evaluation of Commercially Available Fall Detection Systems.

Falls are a serious problem in the hospital setting and home environments. However, this problem does not only affect the elderly, but also people who have had surgery, have disabling problems, have associated diagnoses (such as poor eyesight, confusion, etc.) or are dizzy or have walking aids. The aim of research was to find, compare and implement fall detectors especially for the hospital environment. This paper summarizes possible fall detectors. Various technological solutions were selected for testing, including wearable technologies as well as contactless technologies based on PIR detectors and mmWave technologies. The selected fall detectors were tested in living laboratory of HEALTHLab.vsb.cz and then in Hospital AGEL Trinec - Podlesí. The best result of the testing was the use of two Vayyar Home Care devices in one room, thus achieving a detection accuracy of 92.50 % and a sensitivity of 92.50 %.

Casein as protein and hydrolysate: Biostimulant or nitrogen source for Nicotiana tabacum plants grown in vitro?

In contrast to inorganic nitrogen (N) assimilation, the role of organic N forms, such as proteins and peptides, as sources of N and their impact on plant metabolism remains unclear. Simultaneously, organic biostimulants are used as priming agents to improve plant defense response. Here, we analysed the metabolic response of tobacco plants grown in vitro with casein hydrolysate or protein. As the sole source of N, casein hydrolysate enabled tobacco growth, while protein casein was used only to a limited extent. Free amino acids were detected in the roots of tobacco plants grown with protein casein but not in the plants grown with no source of N. Combining hydrolysate with inorganic N had beneficial effects on growth, root N uptake and protein content. The metabolism of casein-supplemented plants shifted to aromatic (Trp), branched-chain (Ile, Leu, Val) and basic (Arg, His, Lys) amino acids, suggesting their preferential uptake and/or alterations in their metabolic pathways. Complementarily, proteomic analysis of tobacco roots identified peptidase C1A and peptidase S10 families as potential key players in casein degradation and response to N starvation. Moreover, amidases were significantly upregulated, most likely for their role in ammonia release and impact on auxin synthesis. In phytohormonal analysis, both forms of casein influenced phenylacetic acid and cytokinin contents, suggesting a root system response to scarce N availability. In turn, metabolomics highlighted the stimulation of some plant defense mechanisms under such growth conditions, that is, the high concentrations of secondary metabolites (e.g., ferulic acid) and heat shock proteins.

Muddying the unexplored post-industrial waters: Biodiversity and conservation potential of freshwater habitats in fly ash sedimentation lagoons.

Deposits of fly ash and other coal combustion wastes are common remnants of the energy industry. Despite their environmental risks from heavy metals and trace elements, they have been revealed as refuges for threatened terrestrial biodiversity. Surprisingly, freshwater biodiversity of fly ash sedimentation lagoons remains unknown despite such lack of knowledge strongly limits the efficient restoration of fly ash deposits. We bring the first comprehensive survey of freshwater biodiversity, including nekton, benthos, zooplankton, phytoplankton, and macrophytes, in fly ash lagoons across industrial regions of the Czech Republic. To assess their conservation potential, we compared their biodiversity with abandoned post-mining ponds, the known strongholds of endangered aquatic species in the region with a shortage of natural ponds. Of 28 recorded threatened species, 15 occurred in the studied fly ash lagoons, some of which were less abundant or even absent in the post-mining ponds. These are often species of nutrient-poor, fishless waters with rich vegetation, although some are specialised extremophiles. Species richness and conservation value of most groups in the fly ash lagoons did not significantly differ from the post-mining ponds, except for species richness of benthos, zooplankton, and macrophytes, which were slightly lower in the fly ash lagoons. Although the concentrations of some heavy metals (mainly Se, V, and As) were significantly higher in the fly ash lagoons, they did not significantly affect species richness or conservation value of the local communities. The differences in species composition therefore does not seem to be caused by water chemistry. Altogether, we have shown that fly ash lagoons are refuges for threatened aquatic species, and we thus suggest maintaining water bodies during site restoration after the cessation of fly ash deposition. Based on our analyses of environmental variables, we discuss suitable restoration practices that efficiently combine biodiversity protection and environmental risk reduction.

Fully automated imaging protocol independent system for pituitary adenoma segmentation: a convolutional neural network-based model on sparsely annotated MRI.

This study aims to develop a fully automated imaging protocol independent system for pituitary adenoma segmentation from magnetic resonance imaging (MRI) scans that can work without user interaction and evaluate its accuracy and utility for clinical applications. We trained two independent artificial neural networks on MRI scans of 394 patients. The scans were acquired according to various imaging protocols over the course of 11 years on 1.5T and 3T MRI systems. The segmentation model assigned a class label to each input pixel (pituitary adenoma, internal carotid artery, normal pituitary gland, background). The slice segmentation model classified slices as clinically relevant (structures of interest in slice) or irrelevant (anterior or posterior to sella turcica). We used MRI data of another 99 patients to evaluate the performance of the model during training. We validated the model on a prospective cohort of 28 patients, Dice coefficients of 0.910, 0.719, and 0.240 for tumour, internal carotid artery, and normal gland labels, respectively, were achieved. The slice selection model achieved 82.5% accuracy, 88.7% sensitivity, 76.7% specificity, and an AUC of 0.904. A human expert rated 71.4% of the segmentation results as accurate, 21.4% as slightly inaccurate, and 7.1% as coarsely inaccurate. Our model achieved good results comparable with recent works of other authors on the largest dataset to date and generalized well for various imaging protocols. We discussed future clinical applications, and their considerations. Models and frameworks for clinical use have yet to be developed and evaluated.

Artificial Intelligence Can Generate Fraudulent but Authentic-Looking Scientific Medical Articles: Pandora's Box Has Been Opened.

BACKGROUND: Artificial intelligence (AI) has advanced substantially in recent years, transforming many industries and improving the way people live and work. In scientific research, AI can enhance the quality and efficiency of data analysis and publication. However, AI has also opened up the possibility of generating high-quality fraudulent papers that are difficult to detect, raising important questions about the integrity of scientific research and the trustworthiness of published papers. OBJECTIVE: The aim of this study was to investigate the capabilities of current AI language models in generating high-quality fraudulent medical articles. We hypothesized that modern AI models can create highly convincing fraudulent papers that can easily deceive readers and even experienced researchers. METHODS: This proof-of-concept study used ChatGPT (Chat Generative Pre-trained Transformer) powered by the GPT-3 (Generative Pre-trained Transformer 3) language model to generate a fraudulent scientific article related to neurosurgery. GPT-3 is a large language model developed by OpenAI that uses deep learning algorithms to generate human-like text in response to prompts given by users. The model was trained on a massive corpus of text from the internet and is capable of generating high-quality text in a variety of languages and on various topics. The authors posed questions and prompts to the model and refined them iteratively as the model generated the responses. The goal was to create a completely fabricated article including the abstract, introduction, material and methods, discussion, references, charts, etc. Once the article was generated, it was reviewed for accuracy and coherence by experts in the fields of neurosurgery, psychiatry, and statistics and compared to existing similar articles. RESULTS: The study found that the AI language model can create a highly convincing fraudulent article that resembled a genuine scientific paper in terms of word usage, sentence structure, and overall composition. The AI-generated article included standard sections such as introduction, material and methods, results, and discussion, as well a data sheet. It consisted of 1992 words and 17 citations, and the whole process of article creation took approximately 1 hour without any special training of the human user. However, there were some concerns and specific mistakes identified in the generated article, specifically in the references. CONCLUSIONS: The study demonstrates the potential of current AI language models to generate completely fabricated scientific articles. Although the papers look sophisticated and seemingly flawless, expert readers may identify semantic inaccuracies and errors upon closer inspection. We highlight the need for increased vigilance and better detection methods to combat the potential misuse of AI in scientific research. At the same time, it is important to recognize the potential benefits of using AI language models in genuine scientific writing and research, such as manuscript preparation and language editing.

Abiotic Stress in Crop Production.

The vast majority of agricultural land undergoes abiotic stress that can significantly reduce agricultural yields. Understanding the mechanisms of plant defenses against stresses and putting this knowledge into practice is, therefore, an integral part of sustainable agriculture. In this review, we focus on current findings in plant resistance to four cardinal abiotic stressors-drought, heat, salinity, and low temperatures. Apart from the description of the newly discovered mechanisms of signaling and resistance to abiotic stress, this review also focuses on the importance of primary and secondary metabolites, including carbohydrates, amino acids, phenolics, and phytohormones. A meta-analysis of transcriptomic studies concerning the model plant Arabidopsis demonstrates the long-observed phenomenon that abiotic stressors induce different signals and effects at the level of gene expression, but genes whose regulation is similar under most stressors can still be traced. The analysis further reveals the transcriptional modulation of Golgi-targeted proteins in response to heat stress. Our analysis also highlights several genes that are similarly regulated under all stress conditions. These genes support the central role of phytohormones in the abiotic stress response, and the importance of some of these in plant resistance has not yet been studied. Finally, this review provides information about the response to abiotic stress in major European crop plants-wheat, sugar beet, maize, potatoes, barley, sunflowers, grapes, rapeseed, tomatoes, and apples.

Salicylic Acid Treatment and Its Effect on Seed Yield and Seed Molecular Composition of Pisum sativum under Abiotic Stress.

The reproductive stage of plant development has the most critical impact on yield. Flowering is highly sensitive to abiotic stress, and increasing temperatures and drought harm crop yields. Salicylic acid is a phytohormone that regulates flowering and promotes stress resilience in plants. However, the exact molecular mechanisms and the level of protection are far from understood and seem to be species-specific. Here, the effect of salicylic acid was tested in a field experiment with Pisum sativum exposed to heat stress. Salicylic acid was administered at two different stages of flowering, and its effect on the yield and composition of the harvested seeds was followed. Plants treated with salicylic acid produced larger seed pods, and a significant increase in dry weight was found for the plants with a delayed application of salicylic acid. The analyses of the seed proteome, lipidome, and metabolome did not show any negative impact of salicylic treatment on seed composition. Identified processes that could be responsible for the observed improvement in seed yields included an increase in polyamine biosynthesis, accumulation of storage lipids and lysophosphatidylcholines, a higher abundance of components of chromatin regulation, calmodulin-like protein, and threonine synthase, and indicated a decrease in sensitivity to abscisic acid signaling.

Design of Proposed Software System for Prediction of Iliosacral Screw Placement for Iliosacral Joint Injuries Based on X-ray and CT Images.

One of the crucial tasks for the planning of surgery of the iliosacral joint is placing an iliosacral screw with the goal of fixing broken parts of the pelvis. Tracking of proper screw trajectory is usually done in the preoperative phase by the acquisition of X-ray images under different angles, which guide the surgeons to perform surgery. This approach is standardly complicated due to the investigation of 2D X-ray images not showing spatial perspective. Therefore, in this pilot study, we propose complex software tools which are aimed at making a simulation model of reconstructed CT (DDR) images with a virtual iliosacral screw to guide the surgery process. This pilot study presents the testing for two clinical cases to reveal the initial performance and usability of this software in clinical conditions. This model is consequently used for a multiregional registration with reference intraoperative X-ray images to select the slide from the 3D dataset which best fits with reference X-ray. The proposed software solution utilizes input CT slices of the pelvis area to create a segmentation model of individual bone components. Consequently, a model of an iliosacral screw is inserted into this model. In the next step, we propose the software CT2DDR which makes DDR projections with the iliosacral screw. In the last step, we propose a multimodal registration procedure, which performs registration of a selected number of slices with reference X-ray, and based on the Structural Similarity Index (SSIM) and index of correlation, the procedure finds the best match of DDR with X-ray images. In this pilot study, we also provide a comparative analysis of the computational costs of the multimodal registration upon various numbers of DDR slices to show the complex software performance. The proposed complex model has versatile usage for modeling and surgery planning of the pelvis area in fractures of iliosacral joints.

Environmental impacts on barley grain composition and longevity.

To counter projected reductions in yields of the major crop barley, it is essential to elucidate the mechanisms of its resilience. To assist such efforts, we collected grains from plants grown in fields at 12 testing stations, with suitable temperature and precipitation gradients for identifying environmentally induced changes in their protein and metabolite contents. We then subjected the grains to detailed molecular analysis. The results showed that numerous metabolites and at least a quarter of the grain protein content was modulated by the environment, and provided insights into barley seed production under abiotic stress, including alterations in ribosomal proteins, heatshock protein 70 family proteins, inhibitors, storage proteins, and lipid droplet formation. Potential positive and negative markers of yield were also identified, including the phenolic compound catechin and storage protein levels, respectively. Complementary analyses of barley seedlings and Arabidopsis seeds, respectively, confirmed the role of the identified proteins in abiotic stress responses and highlighted evolutionarily conserved mechanisms. In addition, accelerated ageing experiments revealed that variations in the environment had stronger effects on seed longevity than the genotype. Finally, seeds with the highest longevity differed from the others in gibberellin contents, H2O2 metabolism, and levels of >250 proteins, providing novel targets for improving resilience.

Bunyaviruses Affect Growth, Sporulation, and Elicitin Production in Phytophthora cactorum.

Phytophthora cactorum is an important oomycetous plant pathogen with numerous host plant species, including garden strawberry (Fragaria × ananassa) and silver birch (Betula pendula). P. cactorum also hosts mycoviruses, but their phenotypic effects on the host oomycete have not been studied earlier. In the present study, we tested polyethylene glycol (PEG)-induced water stress for virus curing and created an isogenic virus-free isolate for testing viral effects in pair with the original isolate. Phytophthora cactorum bunya-like viruses 1 and 2 (PcBV1 & 2) significantly reduced hyphal growth of the P. cactorum host isolate, as well as sporangia production and size. Transcriptomic and proteomic analyses revealed an increase in the production of elicitins due to bunyavirus infection. However, the presence of bunyaviruses did not seem to alter the pathogenicity of P. cactorum. Virus transmission through anastomosis was unsuccessful in vitro.

Methods of preoperative prediction of pituitary adenoma consistency: a systematic review.

This study aims to review the current literature on methods of preoperative prediction of pituitary adenoma consistency. Pituitary adenoma consistency may be a limiting factor for successful surgical removal of tumors. Efforts have been made to investigate the possibility of an accurate assessment of the preoperative consistency to allow for safer and more effective surgery planning. We searched major scientific databases and systematically analyzed the results. A total of 54 relevant articles were identified and selected for inclusion. These studies evaluated methods based on either MRI intensity, enhancement, radiomics, MR elastometry, or CT evaluation. The results of these studies varied widely. Most studies used the average intensity of either T2WI or ADC maps. Firm tumors appeared hyperintense on T2WI, although only 55% of the studies reported statistically significant results. There are mixed reports on ADC values in firm tumors with findings of increased values (28%), decreased values (22%), or no correlation (50%). Multiple contrast enhancement-based methods showed good results in distinguishing between soft and firm tumors. There were mixed reports on the utility of MR elastography. Attempts to develop radiomics and machine learning-based models have achieved high accuracy and AUC values; however, they are prone to overfitting and need further validation. Multiple methods of preoperative consistency assessment have been studied. None demonstrated sufficient accuracy and reliability in clinical use. Further efforts are needed to enable reliable surgical planning.

Phytochromes and Their Role in Diurnal Variations of ROS Metabolism and Plant Proteome.

Plants are sessile organisms forced to adapt to environmental variations recurring in a day-night cycle. Extensive research has uncovered the transcriptional control of plants' inner clock and has revealed at least some part of the intricate and elaborate regulatory mechanisms that govern plant diel responses and provide adaptation to the ever-changing environment. Here, we analyzed the proteome of the Arabidopsis thaliana mutant genotypes collected in the middle of the day and the middle of the night, including four mutants in the phytochrome (phyA, phyB, phyC, and phyD) and the circadian clock protein LHY. Our approach provided a novel insight into the diel regulations, identifying 640 significant changes in the night-day protein abundance. The comparison with previous studies confirmed that a large portion of identified proteins was a known target of diurnal regulation. However, more than 300 were novel oscillations hidden under standard growth chamber conditions or not manifested in the wild type. Our results indicated a prominent role for ROS metabolism and phytohormone cytokinin in the observed regulations, and the consecutive analyses confirmed that. The cytokinin signaling significantly increased at night, and in the mutants, the hydrogen peroxide content was lower, and the night-day variation seemed to be lost in the phyD genotype. Furthermore, regulations in the lhy and phyB mutants were partially similar to those found in the catalase mutant cat2, indicating shared ROS-mediated signaling pathways. Our data also shed light on the role of the relatively poorly characterized Phytochrome D, pointing to its connection to glutathione metabolism and the regulation of glutathione S-transferases.

Defense mechanisms promoting tolerance to aggressive Phytophthora species in hybrid poplar.

Poplars are among the fastest-growing trees and significant resources in agriculture and forestry. However, rapid growth requires a large water consumption, and irrigation water provides a natural means for pathogen spread. That includes members of Phytophthora spp. that have proven to be a global enemy to forests. With the known adaptability to new hosts, it is only a matter of time for more aggressive Phytophthora species to become a threat to poplar forests and plantations. Here, the effects of artificial inoculation with two different representatives of aggressive species (P. cactorum and P. plurivora) were analyzed in the proteome of the Phytophthora-tolerant hybrid poplar clone T-14 [Populus tremula L. 70 × (Populus × canescens (Ait.) Sm. 23)]. Wood microcore samples were collected at the active necrosis borders to provide insight into the molecular processes underlying the observed tolerance to Phytophthora. The analysis revealed the impact of Phytophthora on poplar primary and secondary metabolism, including carbohydrate-active enzymes, amino acid biosynthesis, phenolic metabolism, and lipid metabolism, all of which were confirmed by consecutive metabolome and lipidome profiling. Modulations of enzymes indicating systemic response were confirmed by the analysis of leaf proteome, and sampling of wood microcores in distal locations revealed proteins with abundance correlating with proximity to the infection, including germin-like proteins, components of proteosynthesis, glutamate carboxypeptidase, and an enzyme that likely promotes anthocyanin stability. Finally, the identified Phytophthora-responsive proteins were compared to those previously found in trees with compromised defense against Phytophthora, namely, Quercus spp. and Castanea sativa. That provided a subset of candidate markers of Phytophthora tolerance, including certain ribosomal proteins, auxin metabolism enzymes, dioxygenases, polyphenol oxidases, trehalose-phosphate synthase, mannose-1-phosphate guanylyltransferase, and rhamnose biosynthetic enzymes. In summary, this analysis provided the first insight into the molecular mechanisms of hybrid poplar defense against Phytophthora and identified prospective targets for improving Phytophthora tolerance in trees.

Molecular Mechanisms Underlying Flax (Linum usitatissimum L.) Tolerance to Cadmium: A Case Study of Proteome and Metabolome of Four Different Flax Genotypes.

Cadmium is one of the most toxic heavy metal pollutants, and its accumulation in the soil is harmful to agriculture. Plants have a higher cadmium tolerance than animals, and some species can be used for phytoremediation. Flax (Linum usitatissimum L.) can accumulate high amounts of cadmium, but the molecular mechanism behind its tolerance is unknown. Here, we employed four genotypes representing two fiber cultivars, an oilseed breeding line, and a transgenic line overexpressing the metallothionein domain for improved cadmium tolerance. We analyzed the proteome of suspensions and the proteome and metabolome of seedling roots in response to cadmium. We identified more than 1400 differentially abundant proteins representing putative mechanisms in cadmium tolerance, including metal-binding proteins and transporters, enzymes of flavonoid, jasmonate, polyamine, glutathione metabolism, and HSP70 proteins. Our data indicated the role of the phytohormone cytokinin in the observed responses. The metabolome profiling found that pipecolinic acid could be a part of the cadmium accumulation mechanism, and the observed accumulation of putrescine, coumaric acid, cinnamic acid, and coutaric acid confirmed the role of polyamines and flavonoids in tolerance to cadmium. In conclusion, our data provide new insight into cadmium tolerance and prospective targets for improving cadmium tolerance in other plants.

Cytokinin modulates the metabolic network of sulfur and glutathione.

The phytohormone cytokinin is implicated in a range of growth, developmental, and defense processes. A growing body of evidence supports a crosstalk between cytokinin and nutrient signaling pathways, such as nitrate availability. Cytokinin signaling regulates sulfur-responsive gene expression, but the underlying molecular mechanisms and their impact on sulfur-containing metabolites have not been systematically explored. Using a combination of genetic and pharmacological tools, we investigated the interplay between cytokinin signaling and sulfur homeostasis. Exogenous cytokinin triggered sulfur starvation-like gene expression accompanied by a decrease in sulfate and glutathione content. This process was uncoupled from the activity of the major transcriptional regulator of sulfate starvation signaling SULFUR LIMITATION 1 and an important glutathione-degrading enzyme, γ-glutamyl cyclotransferase 2;1, expression of which was robustly up-regulated by cytokinin. Conversely, glutathione accumulation was observed in mutants lacking the cytokinin receptor ARABIDOPSIS HISTIDINE KINASE 3 and in cytokinin-deficient plants. Cytokinin-deficient plants displayed improved root growth upon exposure to glutathione-depleting chemicals which was attributed to a higher capacity to maintain glutathione levels. These results shed new light on the interplay between cytokinin signaling and sulfur homeostasis. They position cytokinin as an important modulator of sulfur uptake, assimilation, and remobilization in plant defense against xenobiotics and root growth.

Type-A response regulators negatively mediate heat stress response by altering redox homeostasis in Arabidopsis.

Besides the long-standing role of cytokinins (CKs) as growth regulators, their current positioning at the interface of development and stress responses is coming into recognition. The current evidence suggests the notion that CKs are involved in heat stress response (HSR), however, the role of CK signaling components is still elusive. In this study, we have identified a role of the CK signaling components type-A Arabidopsis response regulators (ARRs) in HSR in Arabidopsis. The mutants of multiple type-A ARR genes exhibit improved basal and acquired thermotolerance and, altered response to oxidative stress in our physiological analyses. Through proteomics profiling, we show that the type-A arr mutants experience a 'stress-primed' state enabling them to respond more efficiently upon exposure to real stress stimuli. A substantial number of proteins that are involved in the heat-acclimatization process such as the proteins related to cellular redox status and heat shock, are already altered in the type-A arr mutants without a prior exposure to stress conditions. The metabolomics analyses further reveal that the mutants accumulate higher amounts of α-and γ-tocopherols, which are important antioxidants for protection against oxidative damage. Collectively, our results suggest that the type-A ARRs play an important role in heat stress response by affecting the redox homeostasis in Arabidopsis.

Performance and Robustness of Regional Image Segmentation Driven by Selected Evolutionary and Genetic Algorithms: Study on MR Articular Cartilage Images.

The analysis and segmentation of articular cartilage magnetic resonance (MR) images belongs to one of the most commonly routine tasks in diagnostics of the musculoskeletal system of the knee area. Conventional regional segmentation methods, which are based either on the histogram partitioning (e.g., Otsu method) or clustering methods (e.g., K-means), have been frequently used for the task of regional segmentation. Such methods are well known as fast and well working in the environment, where cartilage image features are reliably recognizable. The well-known fact is that the performance of these methods is prone to the image noise and artefacts. In this context, regional segmentation strategies, driven by either genetic algorithms or selected evolutionary computing strategies, have the potential to overcome these traditional methods such as Otsu thresholding or K-means in the context of their performance. These optimization strategies consecutively generate a pyramid of a possible set of histogram thresholds, of which the quality is evaluated by using the fitness function based on Kapur's entropy maximization to find the most optimal combination of thresholds for articular cartilage segmentation. On the other hand, such optimization strategies are often computationally demanding, which is a limitation of using such methods for a stack of MR images. In this study, we publish a comprehensive analysis of the optimization methods based on fuzzy soft segmentation, driven by artificial bee colony (ABC), particle swarm optimization (PSO), Darwinian particle swarm optimization (DPSO), and a genetic algorithm for an optimal thresholding selection against the routine segmentations Otsu and K-means for analysis and the features extraction of articular cartilage from MR images. This study objectively analyzes the performance of the segmentation strategies upon variable noise with dynamic intensities to report a segmentation's robustness in various image conditions for a various number of segmentation classes (4, 7, and 10), cartilage features (area, perimeter, and skeleton) extraction preciseness against the routine segmentation strategies, and lastly the computing time, which represents an important factor of segmentation performance. We use the same settings on individual optimization strategies: 100 iterations and 50 population. This study suggests that the combination of fuzzy thresholding with an ABC algorithm gives the best performance in the comparison with other methods as from the view of the segmentation influence of additive dynamic noise influence, also for cartilage features extraction. On the other hand, using genetic algorithms for cartilage segmentation in some cases does not give a good performance. In most cases, the analyzed optimization strategies significantly overcome the routine segmentation methods except for the computing time, which is normally lower for the routine algorithms. We also publish statistical tests of significance, showing differences in the performance of individual optimization strategies against Otsu and K-means method. Lastly, as a part of this study, we publish a software environment, integrating all the methods from this study.