Environmental Signals Research Articles

Comparative Analysis of the Methods of Planning and Coordinating of Manipulator Robot Movement

This paper presents a comparative analysis of two methods for planning and coordinating the movement of robot manipulators in dynamic environments: a neural network-based approach for solving dynamic production scenarios and the rapidly exploring random trees algorithm. The study aims to enhance the trajectory planning of robot manipulators by leveraging the strengths of intelligent systems. The neural network method is designed to perceive the environment, generate accurate control commands, and adapt to changing conditions in real-time. The paper the processes involved in environmental analysis, collision avoidance, and control signal generation for actuators, with an emphasis on the neural network architecture tailored for these tasks. The results demonstrate that the neural network approach offers significant improvements in adaptability and efficiency, providing a robust solution for optimizing automated processes in dynamic production environments.

Plant sesquiterpene lactones.

Sesquiterpene lactones (STLs) are a prominent group of plant secondary metabolites predominantly found in the Asteraceae family and have multiple ecological roles and medicinal applications. This review describes the evolutionary and ecological significance of STLs, highlighting their roles in plant defence mechanisms against herbivory and as phytotoxins, alongside their function as environmental signalling molecules. We also cover the substantial role of STLs in medicine and their mode of action in health and disease. We discuss the biosynthetic pathways and the various modifications that make STLs one of the most diverse groups of metabolites. Finally, we discuss methods for identifying and predicting STL biosynthesis pathways. This article is part of the theme issue 'The evolution of plant metabolism'.

Fully Implantable Wireless Cardiac Pacing and Sensing System Integrated with Hydrogel Electrodes.

Cardiac pacemakers play a crucial role in arrhythmia treatment. Existing devices typically rely on rigid electrode components, leading to potential issues such as heart damage and detachment during prolonged cardiac motion due to the mechanical mismatch with cardiac tissue. Additionally, traditional pacemakers, with their batteries and percutaneous leads, introduce infection risks and limit freedom of movement. A wireless, battery-free multifunctional bioelectronic device for cardiac pacing is developed. This device integrates highly conductive (160Sm-1), flexible (Young's modulus of 80kPa is similar to that of mammalian heart tissue), and stretchable (270%) soft hydrogel electrodes, providing high signal-to-noise ratio (≈28dB) electrocardiogram (ECG)recordings and effective pacing of the beating heart. The versatile device detects physiological and biochemical signals in the cardiac environment and allows for adjustable pacing in vivo studies. Remarkably, it maintained recording and pacing capabilities 31 days post-implantation in rats. Additionally, the wireless bioelectronic device can be fully implanted in rabbits for pacing. By addressing a major shortcoming of conventional pacemakers, this device paves the way for implantable flexible bioelectronics, which offers promising opportunities for advanced cardiac therapies.

USF2 and TFEB compete in regulating lysosomal and autophagy genes

Autophagy, a highly conserved self-digestion process crucial for cellular homeostasis, is triggered by various environmental signals, including nutrient scarcity. The regulation of lysosomal and autophagy-related processes is pivotal to maintaining cellular homeostasis and basal metabolism. The consequences of disrupting or diminishing lysosomal and autophagy systems have been investigated; however, information on the implications of hyperactivating lysosomal and autophagy genes on homeostasis is limited. Here, we present a mechanism of transcriptional repression involving upstream stimulatory factor 2 (USF2), which inhibits lysosomal and autophagy genes under nutrient-rich conditions. We find that USF2, together with HDAC1, binds to the CLEAR motif within lysosomal genes, thereby diminishing histone H3K27 acetylation, restricting chromatin accessibility, and downregulating lysosomal gene expression. Under starvation, USF2 competes with transcription factor EB (TFEB), a master transcriptional activator of lysosomal and autophagy genes, to bind to target gene promoters in a phosphorylation-dependent manner. The GSK3β-mediated phosphorylation of the USF2 S155 site governs USF2 DNA-binding activity, which is involved in lysosomal gene repression. These findings have potential applications in the treatment of protein aggregation-associated diseases, including α1-antitrypsin deficiency. Notably, USF2 repression is a promising therapeutic strategy for lysosomal and autophagy-related diseases.

A denoising algorithm based on ARIMA and competitive K-SVD for the diagnosis of rolling bearing faults

Rolling bearings are extensively employed in industrial production as essential support components for rotating machinery. However, under conditions of high load and harsh operation, bearings are highly susceptible to failure. The weak vibration signals associated with these failures may be obscured by complex harmonic interference and strong noise, posing challenges for the accurate diagnosis of rolling bearing failures. In this paper, an autoregressive integrated moving average and competitive K-singular value decomposition (ARIMA-CK-SVD) algorithm is proposed to realize effective extraction of faulty pulse signals in a strong interference environment. First, the ARIMA model is used to preprocess the original signal to eliminate the interference of harmonic components. Second, a method is proposed for the adaptive selection of parameters in the ARIMA model, with consideration given to the characteristics of K-SVD. Subsequently, a competitive mechanism is introduced during the dictionary update phase of the algorithm to adjust the pattern of atomic updates and eliminate noise atoms. Finally, the effectiveness of the ARIMA-CK-SVD has been validated through simulation experiments and engineering tests.

Vibrio cholerae CsrA controls ToxR levels by increasing the stability and translation of toxR mRNA.

Vibrio cholerae is uniquely adapted to life in marine environments as well as in the human intestinal tract. Global regulators such as CsrA, which help translate environmental cues into an appropriate cellular response, are critical for switching between these distinct environments. Understanding the pathways involved in relaying environmental signals is essential for understanding both the environmental persistence and the intestinal pathogenesis of this devastating human pathogen. In this study, we demonstrate that CsrA directly regulates synthesis of ToxR, a key virulence factor of V. cholerae . Under conditions favoring high levels of active CsrA in the cell, such as in the presence of particular amino acids, CsrA increases ToxR protein levels by binding to the toxR transcript and enhancing both its stability and translation. By responding to nutrient availability, CsrA is perfectly poised to activate the virulence gene regulatory cascade at the preferred site of colonization, the nutrient-rich small intestinal mucosa.

Novel Carbohydrate Polymer-Based Systems for Precise Drug Delivery in Colon Cancer: Improving Treatment Effectiveness With Intelligent Biodegradable Materials.

Due to their biocompatibility, biodegradability, and controlled release, carbohydrates polymers are crucial to targeted drug delivery systems, notably for colon cancer treatment. This article examines how carbohydrate polymers like chitosan, pectin, guar gum, alginate, hyaluronic acid, dextran, and chondroitin sulfate are used in improved drug delivery. Modifying these polymers improves drug loading, stability, and release patterns, enhancing chemotherapeutic drugs' therapeutic index. Chitosan nanoparticles are pH-responsive, making them perfect for cancer treatment. Pectin's resistance to gastric enzymes and colonic bacteria makes it a promising colon-specific medication delivery agent. The combination of these polymers with nanotechnology, 3D printing, and AI allows the creation of stimuli-responsive systems that release drugs precisely in response to environmental signals like pH, redox potential, or colon enzymatic activity. The review highlights intelligent delivery system design advances that reduce systemic toxicity, improve treatment efficacy, and improve patient adherence. Carbohydrate polymers will revolutionize colon cancer treatment with personalized and accurate alternatives.

Mio-pliocene evolution of deep-water channels on the northeastern Bengal fan: Records of signals of Himalaya uplift and South Asian Monsoon from source areas

Submarine channels, acting as major conduits for delivering terrestrial sediments into the deep sea, are sensitive to source-region uplift and climate variations. Using new 3D seismic data, previously published paleoenvironmental data, and IODP/ODP data, we characterize stratigraphic time changes in deep-water channels on the northeastern Bengal Fan and suggest that their long-term evolution relates to contemporaneous changes of Himalaya uplift and South Asian Monsoon. Our results show that around the boundary between the Miocene and Pliocene Epochs, the sedimentary characteristics of deep-water channels were changing at about the same time as decreased rates of Himalaya uplift and changes in the monsoonal climate. It is strongly suggested that environmental signals could successfully propagate from the Himalaya to the deep sea and play a dominant control on the long-term evolution of deep-water channels. During the late Miocene, orogen-wide and substantial Himalaya uplift and humid monsoonal climates (dominance of summer monsoon) generated a sediment supply with high fluxes, which allowed coarser-grained sediments to reach further into the basin and thus caused the formation of larger-scale, non-leveed erosional channels that have avulsion and confluence phenomena. After the Miocene, local and limited Himalaya uplift and arid monsoonal climates (dominance of winter monsoon) led to a sediment supply with low fluxes, during which only finer-grained sediments reached deep water and gave rise to smaller-scale, leveed aggradational channels that mainly have splay deposits. Between the late-Miocene and post-Miocene periods, detrital zircon U-Pb ages of Bengal Fan samples from IODP cores reflect a sediment provenance change from the mixing of Brahmaputra and Ganges Rivers to the end-member of Brahmaputra River, broadly coeval with the variations of Himalaya uplift and South Asian Monsoon. Moreover, Bengal Fan cores record a Mio-Pliocene decrease in sedimentation rates and maximum grain sizes and an increase in mudstone contents, consistent with the variations of sediment yield in the source catchments. Observations and interpretations from the current study, therefore, contribute to a better understanding of how the long-term evolution of submarine channels respond to tectonic and climatic perturbations in source areas and may help recognizing similar process-response relationships in other areas.

Matrix Viscoelasticity Tunes the Mechanobiological Behavior of Chondrocytes.

In articular cartilage, the pericellular matrix acting as a specialized mechanical microenvironment modulates environmental signals to chondrocytes through mechanotransduction. Matrix viscoelastic alterations during cartilage development and osteoarthritis (OA) degeneration play an important role in regulating chondrocyte fate and cartilage matrix homeostasis. In recent years, scientists are gradually realizing the importance of matrix viscoelasticity in regulating chondrocyte function and phenotype. Notably, this is an emerging field, and this review summarizes the existing literatures to the best of our knowledge. This review provides an overview of the viscoelastic properties of hydrogels and the role of matrix viscoelasticity in directing chondrocyte behavior. In this review, we elaborated the mechanotransuction mechanisms by which cells sense and respond to the viscoelastic environment and also discussed the underlying signaling pathways. Moreover, emerging insights into the role of matrix viscoelasticity in regulating chondrocyte function and cartilage formation shed light into designing cell-instructive biomaterial. We also describe the potential use of viscoelastic biomaterials in cartilage tissue engineering and regenerative medicine. Future perspectives on mechanobiological comprehension of the viscoelastic behaviors involved in tissue homeostasis, cellular responses, and biomaterial design are highlighted. Finally, this review also highlights recent strategies utilizing viscoelastic hydrogels for designing cartilage-on-a-chip.

Enhancing hotel efficiency and environmental health with biosensors and big data analytics

The hospitality industry embraces digital technologies to enhance efficiency, guest satisfaction, and environmental sustainability. Integrating biosensors and big data analytics allows hotels to monitor operational processes while maintaining high ecological health standards. However, the impact on environmental health is not fully understood, leading to suboptimal decisions and missed opportunities. This research proposes a novel Tabu Search Drove-Extended Multi-Layer Perceptron (TSD-EMLP) to evaluate the effectiveness of digital operations in hotels through the use of biosensors and big data for predicting hotel environmental conditions. Initially, smart biosensors are deployed in key areas and heating, ventilation, and air conditioning denoted as HVAC systems in the hotel, then the water quality data, noise levels, lighting quality, waste management data, operational data, financial and operational effectiveness data are collected and transmitted to the Internet of Things (IoT) cloud for further process. Interquartile Range (IQR) utilizes the IoT cloud data to remove sensor errors and anomalous events to frame outlier data for the Wavelet Packet Transform (WPT) feature extraction process to decompose sensor data into detailed frequency bands, allowing for precise analysis of complex environmental signals, TSD-EMLP model predicts the environmental health in hotels using the decomposed data. The results demonstrate reducing energy consumption, ventilation systems, indoor environment control, and guest satisfaction, improving air quality, and adjusting environmental settings based on real-time environmental conditions through TSD-EMLP optimized settings. TSD-EMLP classification model achieved high accuracy in predicting hotel environmental health, with a low improvement in guest satisfaction metrics.

Targeting SHCBP1 Inhibits Tumor Progression by Restoring Ciliogenesis in Ductal Carcinoma

Abstract Primary cilia detect and transmit environmental signals into cells. Primary cilia are absent in a subset of ductal carcinomas characterized by distinctive biological activities, and recovery of cilia with normal functionality has been shown to have therapeutic potential in some cancer types. Therefore, elucidation of the underlying mechanism and clinical significance of ciliary loss in ductal carcinomas could help develop effective treatment strategies. Here, we identified a link between SHCBP1 and cilia in ductal carcinomas. Shcbp1 knockout in transgenic mice profoundly impeded tumor progression and metastasis, prolonging survival. Single-cell transcriptome analysis revealed a functional connection between SHCBP1 deficiency and increased tumor ciliogenesis. SHCBP1 ablation restored ciliogenesis in unciliated ductal carcinoma by promoting the proximity between the midbody remnant (MBR) and centrosome through enhanced Rab8 GTPase activity and Rab8GTP positioning within the MBR. Inhibition of tumor progression by SHCBP1 loss relied on the recovery of ciliogenesis. Analysis of a large cohort of patients with ductal carcinoma revealed a negative correlation between SHCBP1-induced ciliary loss and patient prognosis. Restoring ciliogenesis via SHCBP1 ablation elicited therapeutic effects in patient-derived xenograft models. Together, this study delineates that induction of MBR-centrosome proximity through SHCBP1-deficiency reactivates ciliogenesis, offering unique opportunities for the treatment of unciliated ductal carcinomas.

The green promotion back to digitization: Research on air quality, urban green coverage and digital innovation

We examine the relationship between air quality, urban green coverage, and the digital innovation of companies in this paper. Using a sample of Chinese A-share listed companies spanning from 2006 to 2016, we discover a positive effect of air quality on companies' digital innovation. Furthermore, urban green coverage enhances this positive relationship through the environmental effect and signaling effect. In mechanism analysis, we find that improved air quality correlates with digital investment attraction, digital human resource immigration, and digital R&D efficiency enhancement channels, subsequently contributing to the advancement of digital innovations among companies. The positive impact of air quality on digital innovation is particularly pronounced in non-state-owned enterprises and under stricter government air policy regulations. Additionally, our study shows that while air quality significantly boosts total innovation by enhancing digital innovation, it has a minimal effect on non-digital innovation. Our findings underscore the importance of paying attention to air quality and promoting green environmental initiatives in the digital era.

Circadian cilia transcriptome in mouse brain across physiological and pathological states

Primary cilia are dynamic sensory organelles that continuously undergo structural modifications in response to environmental and cellular signals, many of which exhibit rhythmic patterns. Building on our previous findings of rhythmic cilia-related gene expression in diurnal primates (baboon), this study extends the investigation to the nocturnal mouse brain to identify circadian patterns of cilia gene expression across brain regions. We used computational techniques and transcriptomic data from four publicly available databases, to examine the circadian expression of cilia-associated genes within six brain areas: brainstem, cerebellum, hippocampus, hypothalamus, striatum, and suprachiasmatic nucleus. Our analysis reveals that a substantial proportion of cilia transcripts exhibit circadian rhythmicity across the examined regions, with notable overrepresentation in the striatum, hippocampus, and cerebellum. We also demonstrate region-specific variations in the abundance and timing of circadian cilia genes’ peaks, indicating an adaptation to the distinct physiological roles of each brain region. Additionally, we show that the rhythmic patterns of cilia transcripts are shifted under various physiological and pathological conditions, including modulation of the dopamine system, high-fat diet, and epileptic conditions, indicating the adaptable nature of cilia transcripts’ oscillation. While limited to a few mouse brain regions, our study provides initial insights into the distinct circadian patterns of cilia transcripts and highlights the need for future research to expand the mapping across wider brain areas to fully understand the role of cilia’s spatiotemporal dynamics in brain functions.

Genome-wide identification of the OVATE family proteins and functional analysis of BhiOFP1, BhiOFP5, and BhiOFP18 during fruit development in wax gourd (Benincasa hispida)

OVATE family proteins (OFPs) are transcriptional regulators in plants. They have a common domain called the OVATE domain and control the development of leaves, fruits, and flowers in plants. Although the OFP gene family has been widely explored in the plant kingdom, the identification and characterization of this family have not yet been performed in wax gourd. In this study, we conducted a genome-wide investigation of the OFP gene family and identified 18 OFP (BhiOFP) genes in wax gourd. Next, we discovered their evolutionary relationships, conserved motifs, gene structures, cis-acting elements, and expression patterns. The BhiOFP genes were irregularly distributed on nine chromosomes, with only two BhiOFP genes containing introns. The BhiOFP gene promoters contained cis-acting elements in response to phytohormones and environmental signals. The majority of BhiOFP genes were derived from whole-genome duplication events. Expression analysis demonstrated that the BhiOFP genes showed disparate modes of expression and some of them were highly expressed in fruits. Overexpression of BhiOFP1, BhiOFP5, and BhiOFP18 in Arabidopsis resulted in dwarf plants, small rosette leaves, and shortened siliques, while the BhiOFP1 overexpression plants displayed a more severe phenotype. In summary, our study systematically analyzed the wax gourd OFP gene family, facilitated the functional research of BhiOFP1, BhiOFP5, and BhiOFP18, and offered a theoretical foundation for the improvement of wax gourd varieties with appropriate fruit length.

Automatic classification method for water entry sounds in multi-interference environments

Abstract In marine environments with strong pulse interference, distinguishing water entry sounds from pulse interference with high accuracy presents a challenge. Conventional algorithms that only utilize the singular values of intrinsic mode functions (IMFs) as the classification feature can have many misclassified signals in noisy environments. To identify the water entry sound more precisely, this study introduces a classifier based on selected singular value and correlation coefficient features. Specifically, the correlation coefficient between each IMF and the original signal are used to select crucial singular values and eliminate uninformative components. Furthermore, the correlation coefficient also combines with singular values as classification features for water entry sounds. The classification experiment results of 2460 groups of water entry sound and pulse interference indicate that the proposed classifier improves classification accuracy by approximately 11.5% compared to using singular values alone and by approximately 2.4% compared to classification accuracy without eliminating uninformative IMFs.

Machine learning based classification of presence utilizing psychophysiological signals in immersive virtual environments

In Virtual Reality (VR), a higher level of presence positively influences the experience and engagement of a user. There are several parameters that are responsible for generating different levels of presence in VR, including but not limited to, graphical fidelity, multi-sensory stimuli, and embodiment. However, standard methods of measuring presence, including self-reported questionnaires, are biased. This research focuses on developing a robust model, via machine learning, to detect different levels of presence in VR using multimodal neurological and physiological signals, including electroencephalography and electrodermal activity. An experiment has been undertaken whereby participants (N = 22) were each exposed to three different levels of presence (high, medium, and low) in a random order in VR. Four parameters within each level, including graphics fidelity, audio cues, latency, and embodiment with haptic feedback, were systematically manipulated to differentiate the levels. A number of multi-class classifiers were evaluated within a three-class classification problem, using a One-vs-Rest approach, including Support Vector Machine, k-Nearest Neighbour, Extra Gradient Boosting, Random Forest, Logistic Regression, and Multiple Layer Perceptron. Results demonstrated that the Multiple Layer Perceptron model obtained the highest macro average accuracy of 93±0.03%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$93\\pm 0.03\\%$$\\end{document}. Posthoc analysis revealed that relative band power, which is expressed as the ratio of power in a specific frequency band to the total baseline power, in both the frontal and parietal regions, including beta over theta and alpha ratio, and differential entropy were most significant in detecting different levels of presence.

A Multi-Omics, Machine Learning-Aware, Genome-Wide Metabolic Model of Bacillus Subtilis Refines the Gene Expression and Cell Growth Prediction.

Given the extensive heterogeneity and variability, understanding cellular functions and regulatory mechanisms through the analysis of multi-omics datasets becomes extremely challenging. Here, a comprehensive modeling framework of multi-omics machine learning and metabolic network models are proposed that covers various cellular biological processes across multiple scales. This model on an extensive normalized compendium of Bacillus subtilis is validated, which encompasses gene expression data from environmental perturbations, transcriptional regulation, signal transduction, protein translation, and growth measurements. Comparison with high-throughput experimental data shows that EM_iBsu1209-ME, constructed on this basis, can accurately predict the expression of 605 genes and the synthesis of 23 metabolites under different conditions. This study paves the way for the construction of comprehensive biological databases and high-performance multi-omics metabolic models to achieve accurate predictive analysis in exploring complex mechanisms of cell genotypes and phenotypes.

Regulation of bacterial virulence genes by PecS family transcription factors.

Bacterial plant pathogens adjust their gene expression programs in response to environmental signals and host-derived compounds. This ensures that virulence genes or genes encoding proteins, which promote bacterial fitness in a host environment, are expressed only when needed. Such regulation is in the purview of transcription factors, many of which belong to the ubiquitous multiple antibiotic resistance regulator (MarR) protein family. PecS proteins constitute a subset of this large protein family. PecS has likely been distributed by horizontal gene transfer, along with the divergently encoded efflux pump PecM, suggesting its integration into existing gene regulatory networks. Here, we discuss the roles of PecS in the regulation of genes associated with virulence and fitness of bacterial plant pathogens. A comparison of phenotypes and differential gene expression associated with the disruption of pecS shows that functional consequences of PecS integration into existing transcriptional networks are highly variable, resulting in distinct PecS regulons. Although PecS universally binds to the pecS-pecM intergenic region to repress the expression of both genes, binding modes differ. A particularly relaxed sequence preference appears to apply for Dickeya dadantii PecS, perhaps to optimize its integration as a global regulator and regulate genes ancestral to the acquisition of pecS-pecM. Even inducing ligands for PecS are not universally conserved. It appears that PecS function has been optimized to match the unique regulatory needs of individual bacterial species and that its roles must be appreciated in the context of the regulatory networks into which it was recruited.

Revisiting the role of light signaling in plant responses to salt stress

Abstract As one of the grave environmental hazards, soil salinization seriously limits crop productivity, growth and development. When plants are exposed to salt stress, they suffer a sequence of damage mainly caused by osmotic stress, ion toxicity and subsequently oxidative stress. As sessile organisms, plants have developed many physiological and biochemical strategies to mitigate the impact of salt stress. These strategies include altering root development direction, shortening the life cycle, accelerating dormancy, closing stomata to reduce transpiration and decreasing biomass. Apart from being a prime energy source, light is an environmental signal, which profoundly influences plant growth and development and also participates in plants’ response to salt stress. This review summarizes the regulatory network of salt tolerance by light signals in plants, which is vital to further understanding plants’ adaptation to high salinity. In addition, the review highlights potential future uses of genetic engineering and light supplement technology by light-emitting diode (LED) to improve crop growth in saline-alkali environments in order to make full use of the vast saline land.

Research Progress on Photoperiod Gene Regulation of Heading Date in Rice.

Heading date is a critical physiological process in rice that is influenced by both genetic and environmental factors. The photoperiodic pathway is a primary regulatory mechanism for rice heading, with key florigen genes Hd3a (Heading date 3a) and RFT1 (RICE FLOWERING LOCUS T1) playing central roles. Upstream regulatory pathways, including Hd1 and Ehd1, also significantly impact this process. This review aims to provide a comprehensive examination of the localization, cloning, and functional roles of photoperiodic pathway-related genes in rice, and to explore the interactions among these genes as well as their pleiotropic effects on heading date. We systematically review recent advancements in the identification and functional analysis of genes involved in the photoperiodic pathway. We also discuss the molecular mechanisms underlying rice heading date variation and highlight the intricate interactions between key regulatory genes. Significant progress has been made in understanding the molecular mechanisms of heading date regulation through the cloning and functional analysis of photoperiod-regulating genes. However, the regulation of heading date remains complex, and many underlying mechanisms are not yet fully elucidated. This review consolidates current knowledge on the photoperiodic regulation of heading date in rice, emphasizing novel findings and gaps in the research. It highlights the need for further exploration of the interactions among flowering-related genes and their response to environmental signals. Despite advances, the full regulatory network of heading date remains unclear. Further research is needed to elucidate the intricate gene interactions, transcriptional and post-transcriptional regulatory mechanisms, and the role of epigenetic factors such as histone methylation in flowering time regulation. This review provides a detailed overview of the current understanding of photoperiodic pathway genes in rice, setting the stage for future research to address existing gaps and improve our knowledge of rice flowering regulation.