Integrated Signal Research Articles

Visualization of accessible cholesterol using a GRAM domain-based biosensor

Cholesterol is important for membrane integrity and cell signaling, and dysregulation of the distribution of cellular cholesterol is associated with numerous diseases, including neurodegenerative disorders. While regulated transport of a specific pool of cholesterol, known as “accessible cholesterol”, contributes to the maintenance of cellular cholesterol distribution and homeostasis, tools to monitor accessible cholesterol in live cells remain limited. Here, we engineer a highly sensitive accessible cholesterol biosensor by taking advantage of the cholesterol-sensing element (the GRAM domain) of an evolutionarily conserved lipid transfer protein, GRAMD1b. Using this cholesterol biosensor, which we call GRAM-W, we successfully visualize in real time the distribution of accessible cholesterol in many different cell types, including human keratinocytes and iPSC-derived neurons, and show differential dependencies on cholesterol biosynthesis and uptake for maintaining levels of accessible cholesterol. Furthermore, we combine GRAM-W with a dimerization-dependent fluorescent protein (ddFP) and establish a strategy for the ultrasensitive detection of accessible plasma membrane cholesterol. These tools will allow us to obtain important insights into the molecular mechanisms by which the distribution of cellular cholesterol is regulated.

Rapid Detection of SARS-CoV-2 in Clinical and Environmental Samples via a Resonant Cavity SERS Platform within 20 min.

The coronavirus disease 2019 (COVID-19) epidemic has given a warning that it is important to explore the rapid detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in clinical specimens or environmental samples for public health strategies and future variants. The surface-enhanced Raman spectroscopy (SERS) technique was demonstrated to achieve this goal. However, the consistency of signals originating from the poor compatibility of virions with SERS hotspots remains a key scientific challenge for the practical applications of SERS. Herein, we develop a SERS platform for the ultrasensitive and rapid detection of SARS-CoV-2 antigen within 20 min by the combination of a highly consistent SERS substrate and a supervised deep learning algorithm. A V-shaped resonant cavity array (VRC) substrate was fabricated to trap SARS-CoV-2 virions in the periodic V cavity array and stimulate the integral SERS signal of the virus via a resonance coupling effect. Benefiting from the unique architecture of the VRC substrate, we were able to directly detect the SARS-CoV-2 virus with high sensitivity and high consistency. These excellent performances enabled us to identify five different kinds of SARS-CoV-2 variants and detect SARS-CoV-2 from clinical and environmental samples with high accuracies.

Navigating a plethora of progesterone receptors: Comments on the safety/risk of progesterone supplementation in women with a history of breast cancer or at high-risk for developing breast cancer

Progesterone and progestin agonists are potent steroid hormones. There are at least three major types of progesterone receptor (PR) families that interact with and respond to progesterone or progestin ligands. These receptors include ligand-activated transcription factor isoforms (PR-A and PR-B) encoded by the PGR gene, often termed classical or nuclear progesterone receptor (nPR), membrane-spanning progesterone receptor membrane component proteins known as PGRMC1/2, and a large family of progestin/adipoQreceptors or PAQRs (also called membrane PRs or mPRs). Cross-talk between mPRs and nPRs has also been reported. The complexity of progesterone actions via a plethora of diverse receptors warrants careful consideration of the clinical applications of progesterone, which primarily include birth control formulations in young women and hormone replacement therapy following menopause. Herein, we focus on the benefits and risk of progesterone/progestin supplementation. We conclude that progesterone-only supplementation is considered safe for most reproductive-age women. However, women who currently have ER + breast cancer or have had such cancer in the past should not take sex hormones, including progesterone. Women at high-risk for developing breast or ovarian cancer, either due to their family history or known genetic factors (such as BRCA1/2 mutation) or hormonal conditions, should avoid exogenous sex hormones and proceed with caution when considering using natural hormones to mitigate menopausal symptoms and/or improve quality of life after menopause. These individuals are urged to consult with a qualified OB-GYN physician to thoroughly assess the risks and benefits of sex hormone supplementation. As new insights into the homeostatic roles and specificity of highly integrated rapid signaling and nPR actions are revealed, we are hopeful that the benefits of using progesterone use may be fully realized without an increased risk of women’s cancer.

Antifungal mechanism of Bacillus amyloliquefaciens SC-B15 and its application in cereal mildewproof and grape preservation

Microorganisms and their metabolites play vital roles in inhibiting the growth of toxic-producing fungi. Here, Bacillus amyloliquefaciens SC-B15 showed over 64% inhibition of six mycotoxin-producing fungi and the best inhibition of A. ochraceus (81%). Meanwhile, the supernatant fraction of >10 kDa showed the best inhibition against A. ochraceus and the antifungal proteins were probably cell wall hydrolytic enzymes. Our study showed that the antifungal components lead to the destruction of mycelium and spores of A. carbonarius, while also affecting gene expression of cell wall integrity signaling pathways and secondary metabolic processes, such as leading to substantial downregulation of pks genes and affecting the synthesis of OTA precursors. The antifungal fraction could markedly reduce the spot diameter (66.19%) and Ochratoxin A (OTA) accumulation (63.56%) of grape wounds, and reduce A. carbonarius growth (64.78%) and OTA accumulation (84.41%) during cereal storage. Our research indicates that the SC-B15 strain has a promising prospect in the control of Aspergillus and OTA contamination.

Adiposomes from Obese-Diabetic Individuals Promote Endothelial Dysfunction and Loss of Surface Caveolae.

Glycosphingolipids (GSLs) are products of lipid glycosylation that have been implicated in the development of cardiovascular diseases. In diabetes, the adipocyte microenvironment is characterized by hyperglycemia and inflammation, resulting in high levels of GSLs. Therefore, we sought to assess the GSL content in extracellular vesicles derived from the adipose tissues (adiposomes) of obese-diabetic (OB-T2D) subjects and their impact on endothelial cell function. To this end, endothelial cells were exposed to adiposomes isolated from OB-T2D versus healthy subjects. Cells were assessed for caveolar integrity and related signaling, such as Src-kinase and caveolin-1 (cav-1) phosphorylation, and functional pathways, such as endothelial nitric oxide synthase (eNOS) activity. Compared with adiposomes from healthy subjects, OB-T2D adiposomes had higher levels of GSLs, especially LacCer and GM3; they promoted cav-1 phosphorylation coupled to an obvious loss of endothelial surface caveolae and induced eNOS-uncoupling, peroxynitrite generation, and cav-1 nitrosylation. These effects were abolished by Src kinase inhibition and were not observed in GSL-depleted adiposomes. At the functional levels, OB-T2D adiposomes reduced nitric oxide production, shear response, and albumin intake in endothelial cells and impaired flow-induced dilation in healthy arterioles. In conclusion, OB-T2D adiposomes carried a detrimental GSL cargo that disturbed endothelial caveolae and the associated signaling.

Intelligent fiber optic integrated sensing system for human motion monitoring

In recent years, the development of flexible bend sensors and their detection devices has attracted great interest. In this paper, an intelligent wearable plastic optical fiber (POF) integrated sensing system for human motion detection is presented. The system consists of POF bend sensors and a wearable fiber bend detection meter (WFBDM). By capturing the POF array image from the video stream, it realizes a sampling frequency of 91.7 times/s. It also greatly increases the integration of multiple sensors, with an integrated sensing area of only 0.35*0.35 mm2 for a single sensor. POF bending sensors with a diameter of 0.25 mm were tested using this system with a linear range of −40° to 90°, an accuracy of up to 0.4°, and a response time of 26.2 ms. The system has been successfully applied to human joint and muscle motion monitoring, and combined with machine learning to realize the intelligent recognition of human motion state. The sensing system is small in size, large in sensing range, high in sensitivity and good in stability, and has the ability of intelligent recognition and highly integrated multi-channel bend signals sensing.

Modeling of integrated signal converters for biomedical sensor microsystems

The paper presents the results of computer modeling of the proposed functional-electrical circuit of integrated signal converters (ISC) from photosensitive elements based on CMOS operational amplifiers, which is intended for the construction of an element base of hybrid sensor microsystems for biomedical applications. A feature of this ISC is the regulation and filtering of the amplitude of the constant component in the amplified signal from the diode photosensitive element in the wave range of 400 - 1040 nm.
 Computer simulation of the functioning of the device was carried out, the constituent components were determined and their parametric optimization was carried out. The results of experimental studies and computer modeling agree well, which confirms the correct functioning of the proposed signal converter from photosensitive elements. The developed ISC is suitable for creating real devices, both on the basis of discrete components and in an integrated design, as an element of sensor microsystems-on-a-chip or intelligent sensors.

EHD2 regulates plasma membrane integrity and downstream insulin receptor signaling events.

Adipocyte dysfunction is a crucial driver of insulin resistance and type 2 diabetes. We identified EH domain-containing protein2(EHD2) as one of the most highly upregulated genes at the early stage of adipose-tissue expansion. EHD2 is a dynamin-related ATPase influencing several cellular processes, including membrane recycling, caveolae dynamics, and lipid metabolism. Here, we investigated the role of EHD2 in adipocyte insulin signaling and glucose transport. Using C57BL6/N EHD2 knockout mice under short-term high-fat diet conditions and 3T3-L1 adipocytes we demonstrate that EHD2 deficiency is associated with deterioration of insulin signal transduction and impaired insulin-stimulated GLUT4 translocation. Furthermore, we show that lack of EHD2 is linked with altered plasma membrane lipid and protein composition, reduced insulin receptor expression, and diminished insulin-dependent SNARE protein complex formation. In conclusion, these data highlight the importance of EHD2 for the integrity of the plasma membrane milieu, insulin receptor stability, and downstream insulin receptor signaling events, involved in glucose uptake and ultimately underscore its role in insulin resistance and obesity.

An insight into the temporal dynamics in the gut microbiome, metabolite signaling, immune response, and barrier function in suckling and weaned piglets under production conditions.

Little information is available on age- and creep-feeding-related microbial and immune development in neonatal piglets. Therefore, we explored age- and gut-site-specific alterations in the microbiome, metabolites, histo-morphology, and expression of genes for microbial signaling, as well as immune and barrier function in suckling and newly weaned piglets that were receiving sow milk only or were additionally offered creep feed from day of life (DoL) 10. The experiment was conducted in two replicate batches. Creep feed intake was estimated at the litter level. Piglets were weaned on day 28 of life. Gastric and cecal digesta and jejunal and cecal tissue were collected on DoL 7, 14, 21, 28, 31, and 35 for microbial and metabolite composition, histomorphology, and gene expression. In total, results for 10 piglets (n = 5/sex) per dietary group (sow milk only versus additional creep feed) were obtained for each DoL. The creep feed intake was low at the beginning and only increased in the fourth week of life. Piglets that were fed creep feed had less lactate and acetate in gastric digesta on DoL 28 compared to piglets fed sow milk only (p < 0.05). Age mainly influenced the gastric and cecal bacteriome and cecal mycobiome composition during the suckling phase, whereas the effect of creep feeding was small. Weaning largely altered the microbial communities. For instance, it reduced gastric Lactobacillaceae and cecal Bacteroidaceae abundances and lowered lactate and short-chain fatty acid concentrations on DoL 31 (p < 0.05). Jejunal and cecal expression of genes related to microbial and metabolite signaling, and innate immunity showed age-related patterns that were highest on DoL 7 and declined until DoL 35 (p < 0.05). Weaning impaired barrier function and enhanced antimicrobial secretion by lowering the expression of tight junction proteins and stimulating goblet cell recruitment in the jejunum and cecum (p < 0.05). Results indicated that age-dependent alterations, programmed genetically and by the continuously changing gut microbiome, had a strong impact on the expression of genes for gut barrier function, integrity, innate immunity, and SCFA signaling, whereas creep feeding had little influence on the microbial and host response dynamics at the investigated gut sites.

Island detection for grid connected photovoltaic distributed generations via integrated signal processing and machine learning approach

The applications of distributed generators in distribution networks have proven to be highly reliable and cost-effective. Accidental islanding is currently regarded as an undesirable operational mode in utility practice because it can harm individuals and connected systems. Therefore, the occurrence of islanding must be detected, and then distributed generators must be disconnected from the main network. In this article, a fast and accurate island detection method is proposed for photovoltaic distributed generations with a near-zero non-detection zone. A new island detection approach is developed by combining signal processing and machine learning techniques. Variational mode decomposition is used as a signal processing technique. Whereas the ensemble bagged-trees method is used as a machine learning technique. Variational mode decomposition is used to process positive- and negative-sequence component voltage signals along with power signal measurements acquired from the point of common coupling in order to identify intrinsic-mode functions. Next, the ensemble bagged-trees method is utilized to detect islanding during active and reactive power mismatch events and inconvenient quality factors. The results demonstrate that the suggested technique is able to discriminate between islanding and non-islanding events such as capacitive switching, fault emulation, and distribution generation cut-off. Besides, it has a minimum non-detection zone of less than 4% and a 4.8 ms detection time. Therefore, it is a reliable and reasonable solution for the distribution grid.

The mushroom body output encodes behavioral decision during sensory-motor transformation

Animals form a behavioral decision by evaluating sensory evidence on the background of past experiences and the momentary motivational state. In insects, we still lack understanding of how and at which stage of the recurrent sensory-motor pathway behavioral decisions are formed. The mushroom body (MB), a central brain structure in insects1 and crustaceans,2,3 integrates sensory input of different modalities4,5,6 with the internal state, the behavioral state, and external sensory context7,8,9,10 through a large number of recurrent, mostly neuromodulatory inputs,11,12 implicating a functional role for MBs in state-dependent sensory-motor transformation.13,14 A number of classical conditioning studies in honeybees15,16 and fruit flies17,18,19 have provided accumulated evidence that at its output, the MB encodes the valence of a sensory stimulus with respect to its behavioral relevance. Recent work has extended this notion of valence encoding to the context of innate behaviors.8,20,21,22 Here, we co-analyzed a defined feeding behavior and simultaneous extracellular single-unit recordings from MB output neurons (MBONs) in the cockroach in response to timed sensory stimulation with odors. We show that clear neuronal responses occurred almost exclusively during behaviorally responded trials. Early MBON responses to the sensory stimulus preceded the feeding behavior and predicted its occurrence or non-occurrence from the single-trial population activity. Our results therefore suggest that at its output, the MB does not merely encode sensory stimulus valence. We hypothesize instead that the MB output represents an integrated signal of internal state, momentary environmental conditions, and experience-dependent memory to encode a behavioral decision.

Target-Induced Stepwise Disintegration of Starlike Branched and Multiplex Embedded Systems for Amplified Detection of Serum MicroRNA.

DNA nanotechnology has shown great promise for biosensing and molecular recognition. However, the practical application of conventional DNA biosensors is constrained by inadequate target stimuli, intricate design schemes, multicomponent systems, and susceptibility to nuclease degradation. To overcome these limitations, we present a class of starlike branched and multiplex embedded system (SBES) with an integrated functional design and cascade exponential amplification for serum microRNA (miRNA) detection. The DNA arms can be integrated into an all-in-one system by surrounding a branch point, with each arm endowed with specific functionalities by embedding different DNA fragments. These fragments include a segment complementary to the target miRNA for the recognition element, palindromic tails for self-primed polymerization, and a region with the same sequences as the target serving as the target analogue. Upon exposure to a target miRNA, the DNA arms unwind in a stepwise manner through palindrome-mediated dimerization and polymerization. This enables target recycling for subsequent reactions while releasing the target analogue to generate a secondary response in a feedback manner. A comparative analysis illustrates that the signal-to-noise ratio (SNR) of a full SBES with a feedback strategy is approximately 250% higher than the system without a feedback design. We demonstrate that the four-arm 4pSBES has the benefits of multifunctional integration, enhanced sensitivity, and low false-positive signals, which makes this approach ideally suited for clinical diagnosis. Moreover, an upgraded SBES with additional DNA arms (e.g., 6pSBES) can be constructed to allow multifunctional extension, offering unprecedented opportunities to build versatile DNA nanostructures for biosensing.

Regulation of the RNA polymerase II pre-initiation complex by its associated coactivators.

The RNA polymerase II (Pol II) pre-initiation complex (PIC) is a critical node in eukaryotic transcription regulation, and its formation is the major rate-limiting step in transcriptional activation. Diverse cellular signals borne by transcriptional activators converge on this large, multiprotein assembly and are transduced via intermediary factors termed coactivators. Cryogenic electron microscopy, multi-omics and single-molecule approaches have recently offered unprecedented insights into both the structure and cellular functions of the PIC and two key PIC-associated coactivators, Mediator and TFIID. Here, we review advances in our understanding of how Mediator and TFIID interact with activators and affect PIC formation and function. We also discuss how their functions are influenced by their chromatin environment and selected cofactors. We consider how, through its multifarious interactions and functionalities, a Mediator-containing and TFIID-containing PIC can yield an integrated signal processing system with the flexibility to determine the unique temporal and spatial expression pattern of a given gene.

The Historic Built Environment As a Long-Term Geochemical Archive: Telling the Time on the Urban "Pollution Clock".

This study introduces a novel methodology for utilizing historic built environments as reliable long-term geochemical archives, addressing a gap in the reconstruction of past anthropogenic pollution levels in urban settings. For the first time, we employ high-resolution laser ablation mass spectrometry for lead isotope (206Pb/207Pb and 208Pb/206Pb) analysis on 350-year-old black crust stratigraphies found on historic built structures, providing insights into past air pollution signatures. Our findings reveal a gradual shift in the crust stratigraphy toward lower 206Pb/207Pb and higher 208Pb/206Pb isotope ratios from the older to the younger layers, indicating changes in lead sources over time. Mass balance analysis of the isotope data shows black crust layers formed since 1669 primarily contain over 90% Pb from coal burning, while other lead sources from a set of modern pollution including but not limited to leaded gasoline (introduced after 1920) become dominant (up to 60%) from 1875 onward. In contrast to global archives such as ice cores that provide integrated signals of long-distance pollution, our study contributes to a deeper understanding of localized pollution levels, specifically in urban settings. Our approach complements multiple sources of evidence, enhancing our understanding of air pollution dynamics and trends, and the impact of human activities on urban environments.

Condition Evaluation of Steam Turbine Generator Using Minute-Interval Integrated Vibration Signals

Vibration levels are a primary indicator for condition monitoring of Electrical Machine (EM) systems. This work employs Singular Spectrum Analysis (SSA) to analyze vibration time series of shaft and bearings of a real 250MW industrial power plant steam turbine Synchronous Generator (SG) in Greece. The SG operates under reduced power due to increased vibration conditions according to threshold guidelines. This work attempts to retrieve fault indications from the minute-interval integrated signal sample via its trend and periodicity components to predict vibrations under full load operation and establish correlations to discern whether the reduced output is justified. The successful application of this novel procedure is important due to ease of storing and handling low frequency signals, especially in remote environments. Rules are established using fuzzy logic due to the nature of the dataset and industrial application. The predictor employed is based on Sugeno-based Adaptive Neuro Fuzzy Inference System (ANFIS).

OPTICAL 4:1 MULTIPLEXER USING SAGNAC SWITCHES

This paper presents the design and implementation of an Optical 4:1 Multiplexer using Sagnac Switches as Terahertz Optical Asymmetric Demultiplexers (TOADs). Optical multiplexers play a crucial role in modern communication systems by combining multiple signals onto a single optical channel. The proposed multiplexer architecture leverages the benefits of Sagnac Switches, such as low insertion loss, high extinction ratio, and low crosstalk, along with TOADs to achieve efficient signal routing and demultiplexing. The design is evaluated through simulations, demonstrating its performance in terms of insertion loss, extinction ratio, and crosstalk. The experimental validation of the multiplexer verifies its effectiveness in real-world scenarios. The Optical 4:1 Multiplexer using Sagnac Switches as TOADs offers a promising solution for optical communication networks, enabling efficient signal multiplexing and demultiplexing while maintaining high data integrity and low signal degradation.

Adaptive approximated inverse control for a class of multi-agent systems with unknown control directions

An adaptive approximated inverse control scheme for a class of high-order nonlinear multi-agent systems with unknown control directions is proposed in this paper. The adaptive control problem under the case it is not required to be identical for the unknown control directions is solved by some novel Nussbaum functions and a monotonously increasing sequence, leading our multiple Nussbaum functions reinforce rather than counteract each other. Also, it is introduced in the design and analysis like some integrable auxiliary signals and a novel contradiction argument. Moreover, hysteresis nonlinearity is counteracted by constructing its approximated inverse compensator. With these efforts, stability analysis ensures that all the closed-loop system signals are uniformly bounded, and it is successfully achieved the asymptotic convergence of tracking error to zero, circumventing the obstacle caused by the unknown control directions. Experiment results illustrate the effectiveness of the proposed scheme.

A fractional-order visual neural model for small target motion detection

Detecting small moving targets consisting of one or few pixels is technically demanding due to their limited visual features. Motivated by nature, some bio-inspired models have been developed that simulate the behavior of small target motion detectors (STMDs), a class of specialized neurons found in insects’ visual neural systems dominating in detecting small moving targets during activities such as predation or courtship. However, the existing models’ high dependence on the sampling frequency of input videos becomes a bottleneck that seriously hinders their real-time applications in the physical world. This is because massive computational power is required to capture and process high-sampling-frequency videos. While model detection performance in low-sampling-frequency videos is plagued by significant spatial errors and weak responses. To address these issues, we propose an STMD-based visual neural model with a fractional-order difference operator for small target motion detection. The fractional-order operator captures instantaneous luminance change and integrates it with memory information, where the instantaneous information dominates the integrated signal. The STMD network further separates the rising and falling luminance components, which are aligned in the time domain and then multiplied to predict the location of moving small targets. Due to the rapid response of instantaneous information and the supplement of memory information, the proposed model locates the small moving targets accurately and robustly in low-sampling-frequencies. Numerical experiments show that the proposed model significantly improves the detection performance for low-sampling-frequency videos.

#4277 EGF, GDF-15 AND NEOPTERIN AS PREDICTORS OF CHRONIC KIDNEY DISEASE PROGRESSION IN CHILDREN BY MEANS OF ARTIFICIAL NEURAL NETWORK MODELS

Abstract Background and Aims Progression of chronic kidney disease (CKD) is a compound process, where activation of immunocompetent cells and subclinical inflammation play pivotal role. Enhanced atrophy of the tubular cells, and finally, gradual fibrosis of tubulointerstitial tissue, are responsible for irreversible character of the disease. Multiple molecules influence above-mentioned processes. Growth differentiation factor (GDF)15, a member of TGF-β cytokine superfamily, is a marker of inflammation and an integrative signal in both acute and chronic stress conditions. Elevated serum concentrations of GDF15 were associated with increased risk of development and progression of CKD in adults, as well as with mortality in this group of patients. Our previous investigation revealed increased serum GDF15 concentrations in children on chronic dialysis. Epidermal growth factor (EGF), a tubule-specific protein, promotes proliferation, differentiation and migration of epithelial cells, and therefore, modulates regeneration of injured renal tubules. Decreased concentrations of EGF in urine were observed in variety of kidney diseases, including diabetic nephropathy, lupus nephritis or CKD. Our previous analysis of EGF serum concentrations in CKD children confirmed their decreased values on chronic dialysis. Neopterin is a product of activated monocytes and macrophages and serves as a marker of cell-mediated immunity. Elevated serum concentrations of neopterin were observed in CKD adult patients, our investigation revealed its increased values in children on chronic dialysis. None of the above mentioned markers was analyzed in the population of CKD children treated conservatively. Therefore, the aim of study was to assess the serum concentrations of EGF, GDF-15 and neopterin in children with CKD on conservative treatment and verify the usefulness of these markers in predicting CKD progression by means of artificial intelligence tools. Method The study group consisted of 153 children with pre-dialysis CKD stages 1-5 (stage 1 – 27 patients, stage 2 – 26 patients, stage 3 – 51 patients, stage 4 - 28 patients, stage 5 – 21 patients). EGF, GDF-15 and neopterin serum concentrations were assessed by ELISA. The patient database was implemented into the artificial neural network. In detail, the recursively selected subsets of input variables constituted the input layer of an artificial neural network built of perceptrons (multi-layer perceptron). Anthropometric data, biochemical parameters, EGF, GDF15 and neopterin were included into the model, serum creatinine and eGFR, as direct classifiers of CKD stage, were excluded. Various models were tested, regarding their accuracy, AUROC and Matthews correlation coefficient (MCC) values. Results EGF serum concentrations decreased gradually, whereas GDF15 and neopterin values rose systematically with CKD progression, keeping statistically significant inter-stage differences. Moreover, the most precise ANN model, among the tested artificial neural networks, contained EGF, GDF15 and neopterin as input parameters and classified patients into either CKD 1-3 or CKD 4-5 groups. This model has put new patients into appropriate classes with excellent Accuracy of 96.77%, AUROC 0.9169 and Matthews correlation coefficient (MCC) of 0.9157. Conclusion The presented model of an artificial neural network, with serum concentrations of EGF, GDF15 and neopterin as input parameters, may serve as a useful predictor of CKD progression in the pediatric population. It suggests the essential role of inflammatory processes, defined by newly discovered markers, in the renal function decline towards advanced stages of CKD in children.

The STRIPAK complex orchestrates cell wall integrity signalling to govern the fungal development and virulence of Fusarium graminearum.

Striatin-interacting phosphatases and kinases (STRIPAKs) are evolutionarily conserved supramolecular complexes that control various important cellular processes such as signal transduction and development. However, the role of the STRIPAK complex in pathogenic fungi remains elusive. In this study, the components and function of the STRIPAK complex were investigated in Fusarium graminearum, an important plant-pathogenic fungus. The results obtained from bioinformatic analyses and the protein-protein interactome suggested that the fungal STRIPAK complex consisted of six proteins: Ham2, Ham3, Ham4, PP2Aa, Ppg1, and Mob3. Deletion mutations of individual components of the STRIPAK complex were created, and observed to causea significant reduction in fungal vegetative growth and sexual development, and dramatically attenuae virulence, excluding the essential gene PP2Aa. Further results revealed that the STRIPAK complex interacted with the mitogen-activated protein kinase Mgv1, a key component in the cell wall integrity pathway, subsequently regulating the phosphorylation level and nuclear accumulation of Mgv1 to control the fungal stress response and virulence. Our results also suggested that the STRIPAK complex was interconnected with the target of rapamycin pathway through Tap42-PP2A cascade. Taken together, our findings revealed that the STRIPAK complex orchestrates cell wall integrity signalling to govern the fungal development and virulence of F. graminearum and highlighted the importance of the STRIPAK complex in fungal virulence.