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.

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.

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.

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.

COP1 destabilizes DELLA proteins in Arabidopsis.

DELLA transcriptional regulators are central components in the control of plant growth responses to the environment. This control is considered to be mediated by changes in the metabolism of the hormones gibberellins (GAs), which promote the degradation of DELLAs. However, here we show that warm temperature or shade reduced the stability of a GA-insensitive DELLA allele in Arabidopsis thaliana Furthermore, the degradation of DELLA induced by the warmth preceded changes in GA levels and depended on the E3 ubiquitin ligase CONSTITUTIVELY PHOTOMORPHOGENIC1 (COP1). COP1 enhanced the degradation of normal and GA-insensitive DELLA alleles when coexpressed in Nicotiana benthamiana. DELLA proteins physically interacted with COP1 in yeast, mammalian, and plant cells. This interaction was enhanced by the COP1 complex partner SUPRESSOR OF phyA-105 1 (SPA1). The level of ubiquitination of DELLA was enhanced by COP1 and COP1 ubiquitinated DELLA proteins in vitro. We propose that DELLAs are destabilized not only by the canonical GA-dependent pathway but also by COP1 and that this control is relevant for growth responses to shade and warm temperature.

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.

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.

Transcriptome, metabolome and suppressor analysis reveal an essential role for the ubiquitin-proteasome system in seedling chloroplast development.

BACKGROUND: Many regulatory circuits in plants contain steps of targeted proteolysis, with the ubiquitin proteasome system (UPS) as the mediator of these proteolytic events. In order to decrease ubiquitin-dependent proteolysis, we inducibly expressed a ubiquitin variant with Arg at position 48 instead of Lys (ubK48R). This variant acts as an inhibitor of proteolysis via the UPS, and allowed us to uncover processes that are particularly sensitive to UPS perturbation. RESULTS: Expression of ubK48R during germination leads to seedling death. We analyzed the seedling transcriptome, proteome and metabolome 24 h post ubK48R induction and confirmed defects in chloroplast development. We found that mutations in single genes can suppress seedling lethality, indicating that a single process in seedlings is critically sensitive to decreased performance of the UPS. Suppressor mutations in phototropin 2 (PHOT2) suggest that a contribution of PHOT2 to chloroplast protection is compromised by proteolysis inhibition. CONCLUSIONS: Overall, the results reveal protein turnover as an integral part of a signal transduction chain that protects chloroplasts during development.

Regulation of heat shock proteins 70 and their role in plant immunity.

Heat shock proteins 70 (HSP70s) are steadily gaining more attention in the field of plant biotic interactions. Though their regulation and activity in plants are much less well characterized than are those of their counterparts in mammals, accumulating evidence indicates that the role of HSP70-mediated defense mechanisms in plant cells is indispensable. In this review, we summarize current knowledge of HSP70 post-translational control in plants. We comment on the phytohormonal regulation of HSP70 expression and protein abundance, and identify a prominent role for cytokinin in HSP70 control. We outline HSP70s' subcellular localizations, chaperone activity, and chaperone-mediated protein degradation. We focus on the role of HSP70s in plant pathogen-associated molecular pattern-triggered immunity and effector-triggered immunity, and discuss the contribution of different HSP70 subfamilies to plant defense against pathogens.

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.

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.

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.

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.

Review: Development and Technical Design of Tangible User Interfaces in Wide-Field Areas of Application.

A tangible user interface or TUI connects physical objects and digital interfaces. It is more interactive and interesting for users than a classic graphic user interface. This article presents a descriptive overview of TUI's real-world applications sorted into ten main application areas-teaching of traditional subjects, medicine and psychology, programming, database development, music and arts, modeling of 3D objects, modeling in architecture, literature and storytelling, adjustable TUI solutions, and commercial TUI smart toys. The paper focuses on TUI's technical solutions and a description of technical constructions that influences the applicability of TUIs in the real world. Based on the review, the technical concept was divided into two main approaches: the sensory technical concept and technology based on a computer vision algorithm. The sensory technical concept is processed to use wireless technology, sensors, and feedback possibilities in TUI applications. The image processing approach is processed to a marker and markerless approach for object recognition, the use of cameras, and the use of computer vision platforms for TUI applications.

Quantitative and Comparative Analysis of Effectivity and Robustness for Enhanced and Optimized Non-Local Mean Filter Combining Pixel and Patch Information on MR Images of Musculoskeletal System.

In the area of musculoskeletal MR images analysis, the image denoising plays an important role in enhancing the spatial image area for further processing. Recent studies have shown that non-local means (NLM) methods appear to be more effective and robust when compared with conventional local statistical filters, including median or average filters, when Rician noise is presented. A significant limitation of NLM is the fact that thy have the tendency to suppress tiny objects, which may represent clinically important information. For this reason, we provide an extensive quantitative and objective analysis of a novel NLM algorithm, taking advantage of pixel and patch similarity information with the optimization procedure for optimal filter parameters selection to demonstrate a higher robustness and effectivity, when comparing with NLM and conventional local means methods, including average and median filters. We provide extensive testing on variable noise generators with dynamical noise intensity to objectively demonstrate the robustness of the method in a noisy environment, which simulates relevant, variable and real conditions. This work also objectively evaluates the potential and benefits of the application of NLM filters in contrast to conventional local-mean filters. The final part of the analysis is focused on the segmentation performance when an NLM filter is applied. This analysis demonstrates a better performance of tissue identification with the application of smoothing procedure under worsening image conditions.

Multifaceted activity of cytokinin in leaf development shapes its size and structure in Arabidopsis.

The phytohormone cytokinin has been shown to affect many aspects of plant development ranging from the regulation of the shoot apical meristem to leaf senescence. However, some studies have reported contradictory effects of cytokinin on leaf physiology. Therefore cytokinin treatments cause both chlorosis and increased greening and both lead to decrease or increase in cell size. To elucidate this multifaceted role of cytokinin in leaf development, we have employed a system of temporal controls over the cytokinin pool and investigated the consequences of modulated cytokinin levels in the third leaf of Arabidopsis. We show that, at the cell proliferation phase, cytokinin is needed to maintain cell proliferation by blocking the transition to cell expansion and the onset of photosynthesis. Transcriptome profiling revealed regulation by cytokinin of a gene suite previously shown to affect cell proliferation and expansion and thereby a molecular mechanism by which cytokinin modulates a molecular network underlying the cellular responses. During the cell expansion phase, cytokinin stimulates cell expansion and differentiation. Consequently, a cytokinin excess at the cell expansion phase results in an increased leaf and rosette size fueled by higher cell expansion rate, yielding higher shoot biomass. Proteome profiling revealed the stimulation of primary metabolism by cytokinin, in line with an increased sugar content that is expected to increase turgor pressure, representing the driving force of cell expansion. Therefore, the developmental timing of cytokinin content fluctuations, together with a tight control of primary metabolism, is a key factor mediating transitions from cell proliferation to cell expansion in leaves.

Control Methods for Transradial Prostheses Based on Remnant Muscle Activity and Its Relationship with Proprioceptive Feedback.

The loss of a hand can significantly affect one's work and social life. For many patients, an artificial limb can improve their mobility and ability to manage everyday activities, as well as provide the means to remain independent. This paper provides an extensive review of available biosensing methods to implement the control system for transradial prostheses based on the measured activity in remnant muscles. Covered techniques include electromyography, magnetomyography, electrical impedance tomography, capacitance sensing, near-infrared spectroscopy, sonomyography, optical myography, force myography, phonomyography, myokinetic control, and modern approaches to cineplasty. The paper also covers combinations of these approaches, which, in many cases, achieve better accuracy while mitigating the weaknesses of individual methods. The work is focused on the practical applicability of the approaches, and analyses present challenges associated with each technique along with their relationship with proprioceptive feedback, which is an important factor for intuitive control over the prosthetic device, especially for high dexterity prosthetic hands.

Towards to Optimal Wavelet Denoising Scheme-A Novel Spatial and Volumetric Mapping of Wavelet-Based Biomedical Data Smoothing.

Wavelet transformation is one of the most frequent procedures for data denoising, smoothing, decomposition, features extraction, and further related tasks. In order to perform such tasks, we need to select appropriate wavelet settings, including particular wavelet, decomposition level and other parameters, which form the wavelet transformation outputs. Selection of such parameters is a challenging area due to absence of versatile recommendation tools for suitable wavelet settings. In this paper, we propose a versatile recommendation system for prediction of suitable wavelet selection for data smoothing. The proposed system is aimed to generate spatial response matrix for selected wavelets and the decomposition levels. Such response enables the mapping of selected evaluation parameters, determining the efficacy of wavelet settings. The proposed system also enables tracking the dynamical noise influence in the context of Wavelet efficacy by using volumetric response. We provide testing on computed tomography (CT) and magnetic resonance (MR) image data and EMG signals mostly of musculoskeletal system to objectivise system usability for clinical data processing. The experimental testing is done by using evaluation parameters such is MSE (Mean Squared Error), ED (Euclidean distance) and Corr (Correlation index). We also provide the statistical analysis of the results based on Mann-Whitney test, which points out on statistically significant differences for individual Wavelets for the data corrupted with Salt and Pepper and Gaussian noise.