Biology subjects

Li, C.

Publications and source records attributed to Li, C..

At least 253 records · Page 14Linked to original sources

bioRxiv2025

Temporal Trends: Phase-shifted time-series analysis reveals highly correlated reproductive behaviors in the black soldier fly, Hermetia illucens (Diptera: Stratiomyidae)

ENGLISH ABSTRACTFor those researching reproduction of the black soldier fly (BSF), finding meaningful correlations between mating and downstream reproductive fitness metrics, owing to complex reproductive behavior and physiology, has been challenging. On the one hand, mating is not necessarily deterministic of fertile eggs being produced, since females might lay unfertile eggs both before and after mating. But conversely, the process is not random either, since fertility is predicated on the exchange of gametes during mating. To investigate the relationship between mating and other reproductive metrics, a cross-correlation analysis between lagged time series was conducted on data previously collected during a semi-outdoor greenhouse experiment. This process compared the average percent correlation between un-lagged mating with oviposition in traps, oviposition outside traps, total weight of eggs deposited, and hatch rate, which were lagged 0 to 6 days. This revealed that average mating was 97.54% correlated with oviposition in traps lagged by 2 days. For oviposition outside of traps, total egg weights, and hatch rate, these were also [~]71.63% correlated, 60.29% correlated, and 75.16% correlated with mating respectively, which were optimized when the time series were lagged n = 3 days. These trends likely have a biological basis since flies decrease their reproductive activity as they expend energy and senesce, aligning with temporal patterns consistently observed during BSF rearing.

ecology↗

bioRxiv2025

First Whole-Genome Chikungunya Virus Sequence Detected in Mosquitoes during the 2025 Foshan Outbreak: Evidence of Field Vector Infection and Transmission Potential in China

BackgroundSince July 2025, an outbreak of mosquito-borne chikungunya fever occurred in Foshan City, Guangdong Province, China. This was the second outbreak in China following the one that occurred in Dongguan City, Guangdong Province, in 2010. Moreover, the intensity of this outbreak was significantly greater than that of the previous one. Updates to 23 August, more than 10,000 human cases had been reported. Here, we present the first full genome sequence of the chikungunya virus (CHIKV) derived from field-trapped mosquitoes during the outbreak. MethodsAdult Aedes albopictus were BG-trap captured from residences and parklands in three hotspot towns with high density of confirmed human cases. Mosquitoes were morphologically identified and pooled by species, sex and environment types. RNA was extracted, screened by CHIKV RT-qPCR, then positive pools underwent sanger and whole-genome sequencing for complete sequences. Lineage and mutational profiles were inferred by maximum likelihood phylogenetic and comparison against human and mosquito genomes. The distribution of amino acid site mutations in different protein coding regions was also analyzed. ResultThrough 11 days of collection using 10 BG-traps, 2,803 mosquitoes were captured. 1569 (55.97%) female Ae. albopictus were divided into 77 pools and 9.09% (7/77) of the pools tested positive for CHIKV. The local Ae. albopictus minimum infection rate (MIR, per 1000 females) was 4.46, while the MIR for residences in Lecong Town was the highest at 9.17. The MIR for parklands was slight higher than for residences (4.60 vs. 4.30). All the 5 Ae. albopictus-derived complete CHIKV genome clustered within ECSA-Indian Ocean lineage genotype, closely related to human-derived genomes on 2025 Reunion Island. Amino-acid mutations E1-A226V/E2-L210Q were detected in the strains, which enhanced adaptability to Ae. albopictus and increased the transmission capacity. Novel mutation observed on E1 and E2 were totally consist to the patient-derived CHIKV in 2025 Reunion Island. ConclusionsIt was the first mosquito-derived CHIKV whole-genome during the 2025 Foshan outbreak, filling a critical gap between human case and entomological surveillance. Ae. albopictus was confirmed as the primary vector during the outbreak. The current outbreak CHIKV strain with particular amino-acid mutations had adapted to Ae. albopictus transmission. Compared to previous Chikungunya outbreaks over the past decade, the Foshan outbreak occurred earlier (early July), in a larger urban area (with a population of over 9.5 million), and with abundant breeding sites for the vector mosquito Ae. albopictus. However, the outbreak was quickly brought under control, with daily case numbers consistently decreasing, which is closely linked to the strong vector control measures implemented by the Chinese government in the early stages of the outbreak. Moreover, this event once again underscores the necessity of early monitoring of vector mosquitoes and the importance of implementing highly effective vector intervention measures as soon as possible after an outbreak occurs.

microbiology↗

bioRxiv2025

GASPS: A Multi-Omics Framework for Defining Genomic Aberration-Driven Signatures and Predicting Patient Outcomes in Lung Cancer

Lung cancer is the most common cause of cancer-related death worldwide. Recent advancements in targeted therapies and immunotherapies have achieved remarkable success. However, patient responses to treatments with lung cancer vary substantially. The mutation status of driver genes can direct personalized treatment, but their prognostic value and treatment efficacy are limited. In this study, we developed a statistical framework named Genomic Aberration-Derived Signature for Patient Stratification (GASPS) to characterize the transcriptomic deregulation of driver genomic aberrations and stratify patients. By applying GASPS to The Cancer Genome Atlas Lung Adenocarcinoma (TCGA-LUAD) data, we developed gene signatures for 38 driver genomic aberrations, including gene mutations, amplifications, and deletions. These signatures were applied to independent lung cancer transcriptomic datasets containing a total of 2,226 patient samples. Our results indicated that these driver gene signatures are much more prognostic than their corresponding genomic mutations. Interestingly, the two EGFR-related signatures characterizing EGFR mutation and amplification, respectively, exhibited contrasting associations with prognosis, treatment response, and immune infiltration in the tumor microenvironment. Moreover, the STK11 mutation signature, rather than the mutation status, was found to be predictive of the response and long-term benefit of patients treated with immune checkpoint blockade therapy in lung cancer. This framework is readily applicable to most cancer types using existing data to improve prognostic risk assessment and treatment efficacy by guiding personalized therapies.

bioinformatics↗

bioRxiv2025

A novel data filtering method resolves the controversy in the phylogeny of the Chondrichthyes

Phylogenomics, which uses genome-scale data for phylogenetic inference, has clarified many controversial nodes in the tree of life. Such extensive data improve tree resolution and better reflects organismal history compared to analyses based on single or a few genetic loci. However, some relationships within the tree of life remain unresolved, as increased data can yield high node support without ensuring accuracy due to systematic errors. For example, the order-level relationships among chondrichthyans are still contentious despite the use of phylogenomic data. To address systematic errors, complex models have been developed, and filtering for less erroneous data shows great promise. Current metric-based filtering methods rank loci based on overall tree statistics, but problematic signals are often local; and topology-based data filtering approaches struggle with circular assumptions. In this study, we introduced two novel metric-based data filtering methods based on the ratio of local branch length or GC content between problematic clades. We applied these methods to a dataset of 4,452 single-copy exons extracted from 98 chondrichthyan species. The results using all loci showed that the Hexanchiformes was positioned at the root of Elasmobranchii, pulling other squalomorphs to the basal position and rendering Squalomorphii paraphyletic. Contrastingly, filtering for loci with more even branch length, the branch ratio method (absRatioLen) strongly supported the monophyly of all superorders of the chondrichthyans as well as their higher classification grouping, such as Selachii and Batoidea. By concentrating on problematic nodes, our assumption-free filtering methods demonstrate significant potential in resolving contentious relationships in the tree of life.

evolutionary biology↗

bioRxiv2025

Small shifts, big ripples: multi-omics studies reveal how ambient temperatures govern Chlamydomonas cellular responses

Photosynthetic protists, known as microalgae, face increasing temperatures due to climate change. The green biflagellate alga Chlamydomonas reinhardtii serves as a model for thermoregulation. While responses to thermal stress are well characterized, much less is known about the impact of ambient temperature shifts. Understanding microalgal responses to environmental temperature changes is critical, as these primary producers drive ecosystem productivity and food web dynamics. Here, C. reinhardtii grew mixotrophically at ambient temperatures from 18 {degrees}C to 33 {degrees}C. Transcriptomic profiling revealed extensive reorganization, with over 5,000 transcripts significantly affected, including those involved in algal-bacterial interactions, photoreception, lipid metabolism, photosynthesis, cilia formation, and the secretome. CO2 transfer rates and acetate levels measured at 18 {degrees}C and 28 {degrees}C suggest decreased photoautotrophic algal growth at 28 {degrees}C at first. Antagonistic bacterial activity was sustained longer at lower temperatures. Proteomic analyses of isolated cilia and secreted proteins corroborate major abundance changes within these sub-proteomes, particularly in ciliary intraflagellar transport complexes and mating-related proteins in the secretome. Together, these molecular alterations resulted in pronounced changes in growth, the lengths of cells and cilia swimming behavior, mating ability and bacterial antagonism. These data reveal major cellular responses caused by ambient, even short-term temperature shifts.

cell biology↗

bioRxiv2025

UHRF1 restricts HCoV-229E infection through epigenetic silencing of the viral receptor APN

The emergence of SARS-CoV-2 has posed significant threats to global health, particularly for the older population. Similarly, common human coronaviruses, such as HCoV-229E, which typically cause mild cold-like symptoms, have also been linked to severe diseases, underscoring the need to understand virus-host interactions and identify host factors contributing to viral pathogenesis and disease progression. In this study, we performed a genome-wide CRISPR knockout screen using HCoV-229E and identified Ubiquitin-like with PHD and RING finger domain 1 (UHRF1) as a potent restriction factor. Mechanistically, UHRF1 suppressed HCoV-229E infection by downregulating the expression of its cell entry receptor, aminopeptidase N (APN), through promoter hypermethylation. Focused CRISPR activation screens of UHRF1-downregulated genes confirmed the critical role of APN in HCoV-229E infection and identified additional genes (e.g., SIGLEC1, PLAC8, and heparan sulfate biosynthesis genes) contributing to the restrictive functions of UHRF1. Transcriptomic and single-cell RNA sequencing analysis revealed that UHRF1 expression decreases with age, negatively correlating with increased APN expression. This age-related decline in UHRF1 was further validated in primary alveolar macrophages isolated from elderly individuals, which exhibited heightened susceptibility to HCoV-229E infection compared to those from younger individuals. Our findings highlight UHRF1 as a key age-related host defense factor against coronavirus infection and provide novel insights into the epigenetic regulation of viral entry receptors.

microbiology↗

bioRxiv2025

Force Propagation in Active Cytoskeletal Networks

Conventional materials science establishes clear structure-function relationships: grain boundaries modulate strength by blocking dislocations, and defect density limits conductivity through electron scattering. Active matter presents a fundamentally different challenge, components continuously consume energy to generate forces, creating a dual identity as both structural elements and force-generating machines. This material-machine duality raises a fundamental question: which structural parameters govern functional behavior in systems where constituents actively generate forces rather than merely responding to external inputs? Here we demonstrate that percolation is the critical mechanism that transforms active cytoskeletal networks from energy-dissipating materials into work-performing machines. Using light-controlled microtubule-kinesin networks, we show that increasing bundle length from 0.9 {micro}m to 5 {micro}m triggers a percolation transition that enables global force organization. Networks below the threshold remain incapable of performing coordinated work, while networks above it develop correlation lengths exceeding 240 {micro}m, generate 25-fold stronger forces, and extract 1000-fold more mechanical work, powering transport of live cells across 800 {micro}m distances. Network simulations reveal that introducing just 5-10% longer bundles creates a connected component containing 90% of microtubules, establishing the precise threshold that drives this material-to-machine transition. Our findings establish percolation as the fundamental mechanism governing whether active matter systems function as passive materials or as coordinated machines--providing design principles for both synthetic and biological systems. increasing bundle length from 0.9 {micro}m to 5 {micro}m increasing bundle length from 0.9 {micro}m to 5 {micro}m

biophysics↗

bioRxiv2025

Semaglutide drives weight loss through cAMP-dependent mechanisms in GLP1R-expressing hindbrain neurons

Glucagon-like peptide 1 receptor (GLP1R) agonists like semaglutide drive weight loss through the brain, but insights into their intracellular signaling mechanisms are lacking. Although canonically GLP1Rs signal through the stimulatory alpha Gs protein, we find that semaglutide utilizes both Gs- and Gq-signaling pathways in GLP1Rs in the area postrema (AP)--the primary site of semaglutide action in the brain--to differentially regulate neuronal activation across distinct neuronal clusters. Semaglutide also drives graded increases of the essential secondary messenger cyclic adenosine monophosphate (cAMP) in Glp1r-expressing AP neurons (APGlp1r) through Gs-dependent and -independent manners. Inhibition of the cAMP-degradation enzyme phosphodiesterase 4 (PDE4) can enhance and sustain these cAMP responses, whereas disruption of Gs or cAMP signaling in APGlp1r neurons abolishes semaglutide-induced weight loss and downstream brain-wide activation. Our systematic characterization of semaglutides signaling mechanisms in the brain provides avenues for improving the performance of obesity therapeutics.

neuroscience↗

bioRxiv2025

Spatial Transcriptomics Reveal Developmental Dynamics of the Human Cerebral Cortex and Striatum

The human fetal brain undergoes morphological changes that contribute to the development of regional functionalities. However, the features of structural development, the underlying molecular and cellular signatures in the fetal brain remain unclear. With spatial transcriptomics and snRNA-seq, we identified 25 forebrain regions and characterized the dynamic changes in the cortex and striatum during the late first and early second trimesters. In particular, we discovered that temporal lobe enriched NPY-expressing L2/3 EX neuron potentially interacted with L4 EX neurons during cortical expansion and arealization. Additionally, the gyrus and sulcus were developmental asynchronous, in which HOPX and SPARC genes were potentially involved. Further investigation on the striatum showed specific genes and cell types that enriched in patch and matrix compartments, and SST-positive interneurons potentially involved in the development of these structures. Together, our results give insights into the understanding of early fetal brain development.

bioinformatics↗

bioRxiv2025

ICEPIC: A Toolkit to Discover Ice Binding Proteins from Sequence

Ice binding proteins, such as antifreeze proteins (AFPs) and ice nucleation proteins (INPs), are critical for survival in subzero environments and have wide-ranging applications in biotechnology, agriculture, and materials science. Current discovery methods for these proteins are constrained by low throughput and limited datasets that are not conducive for engineering. Here, we present a high-throughput, sequence-based model that leverages contextual embeddings from protein language models to predict ice binding potential, as well as the expression and activity potential of candidate proteins. Using a curated data corpus of over 18,000 ice binding proteins -- far larger than previous datasets -- we fine-tuned a ProtBERT-based model, achieving 99% accuracy for prediction of ice binding potential. Sensitivity analyses through targeted mutagenesis (alanine and threonine substitutions) confirmed the models biological significance, revealing functionally important residues and sequence patterns. Additionally, we developed an expression prediction model that achieved an R2 score of 0.64 and low false-negative rates in identifying highly expressible candidates in Pichia pastoris. An additional regression model trained to predict ice activity as measured by thermal hysteresis achieved an R2 score of at least 0.79 with a clear difference in prediction between ice binding and non-ice binding proteins. Our toolkit advances the predictive accuracy, interpretability, and scalability of ice binding protein discovery, offering a powerful tool for protein engineering in cold-environment applications. Significance StatementIce binding proteins enable organisms to survive freezing temperatures and are essential for applications in cryopreservation, agriculture, and materials science. However, discovering and engineering these proteins has been limited by small datasets and inadequate predictive tools. We developed a machine learning model trained on over 18,000 ice binding protein sequences to predict not only ice binding potential but also protein activity and expression in engineered hosts. This approach integrates advanced protein language models with biological context, enabling faster, more reliable discovery of ice binding proteins. Our platform advances rational protein design for real-world applications in climate resilience, biotechnology, and beyond.

synthetic biology↗

bioRxiv2025

Evidence of Incoherent Fluid Flow in the Human Brain from Multidimensional MRI

PurposeThe human brain contains multiple fluids, including blood, cerebrospinal fluid (CSF), and tissue water. While compartmental models have been used to examine microvascular blood perfusion using intravoxel incoherent motion (IVIM), evidence on incoherent flows of CSF is emerging. This study aims to develop in vivo multi-dimensional MRI methods to investigate potential contributions of CSF in the IVIM regime. MethodT1-Diffusion (T1-D) and T2-Diffusion (T2-D) MRI data were acquired from 10 healthy subjects to investigate the relaxivity and diffusion signatures of incoherent fluid flows in the brain. Based on the T1-D and T2-D results, T1/T2 selective IVIM protocols were developed to map incoherent CSF flows in the human brains. ResultsT1-D and T2-D MRI suggested incoherent CSF flow in the human brain subarachnoid space. Results from four different relaxation selective IVIM methods further supported incoherent CSF flows in these regions. ConclusionWe have shown the feasibility of using T1-D and T2-D MRI within the low b-value regime to probe the heterogeneity of IVIM components. Designed based on the 2D MRI spectra, relaxation selective 1D IVIM acquisition can be obtained within clinically feasible timeframe.

neuroscience↗

bioRxiv2025

Construction of an engineered Escherichia coli with enhanced intestinal colonization and anti-inflammatory efficacy in colitis

Engineered probiotics are considered as effective and safe therapeutic strategies for the treatment of various diseases. Escherichia coli Nissle 1917 (EcN) has been widely used as a chassis strain for its safety and well-established genetic manipulation system. The limited intestinal colonization ability of EcN hampers its potential as a chassis for constructing synthetic probiotics in therapeutic applications. Here, an engineered EcN strain with high gastric acid and bile salts tolerance as well as enhanced intestinal adhesion ability was constructed by improving the expression of gastric acid and bile salts tolerance-associated genes and strengthening the expression of curli fiber formation genes, respectively. Meanwhile, oral administration of this engineered strain to colitis mice alleviated the disease severity and restored the disordered gut microbiome by decreasing the abundance of Escherichia-Shigella, whereas increasing norank_f_Muribaculaceae. We engineered EcN to improve its probiotic properties and anti-colitis efficacy, thereby establishing a platform for precision-designed synthetic probiotics.

microbiology↗

bioRxiv2025

Superresolution imaging of live samples by centroid reassignment microscopy

Superresolution imaging has become one of the most important recent advances in microscopy development. However, most superresolution methods are ill-adapted for live-sample imaging because they are unacceptably slow, susceptible to artifacts, or require the use of specialized fluorophores and labeling protocols. We introduce a superresolution method called centroid reassignment microscopy (CRM) that overcomes these limitations. CRM is a simple variation on confocal microscopy wherein the single-element detector and small pinhole are replaced by a centroid detector and larger pinhole. Superresolution is obtained by reassigning the detected fluorescence to its centroid location of as a function of the scanning excitation focus location. Our method bears resemblance to the method of image scanning microscopy, which involves the use of an array detector, with the advantage that CRM provides improved resolution for the same number of detected photons while being simpler to implement and less sensitive to noise. CRM is light-efficient, fast (single-frame), robust to defocus aberrations, and requires no changes whatsoever in standard fluorescence imaging protocols, making it uniquely attractive for superresolution imaging of live, dynamic samples.

bioengineering↗

bioRxiv2025

Structure-Guided Design of a Bioactive Covalent Small Molecule Targeting a Riboswitch

Small molecule ligands targeting structured RNA elements hold promise for modulating RNA function, serving as chemical probes and potential therapeutics. In this study, the characterization of phenylglyoxal-based covalent probe designed to target unpaired guanine residues in structured RNAs is reported. A structure-guided design strategy was employed to modify covalently unpaired guanines critical for flavin mononucleotide (FMN) binding to the FMN riboswitch. Covalent modification occurs at the designed site and modulates riboswitch function in a cellular reporter system, highlighting the potential of covalent mechanisms of action for bioactive RNA ligands.

biochemistry↗

bioRxiv2025

Aging-enhanced accumulation of fibroblasts excludes oligodendrocytes in demyelinated lesions

Fibroblast dysregulation contributes to pathological fibrosis and aberrant repair. Emerging evidence suggest that fibroblasts accumulate in lesions following central nervous system injury, but whether and how they influence oligodendrocyte repair responses, including in aging, is uncertain. Here we report that fibroblasts accumulate in the parenchyma of spinal cord white matter lesions of 6 - 10 week old young mice after lysolecithin-induced demyelination. This was first observed through immunofluorescence microscopy that employed several markers attributed to fibroblasts, including platelet-derived growth factor-{beta}, collagen type 11, -smooth muscle actin, periostin and fibronectin; and by the use of platelet-derived growth factor-{beta} TdTomato reporter transgenic mice. Single-nucleus and spatial transcriptomics of lysolecithin lesions established the presence of fibroblasts in lysolecithin lesions and delineated them from closely related pericytes. CellChat ligand - receptor analyses highlight fibroblasts in the lysolecithin environment as a major source of input of signals for microglia/macrophages and oligodendrocyte precursor cells, with numerous reciprocal interactions. The infiltration of fibroblasts was promoted by microglia/macrophages, as anticipated by their temporal representation in lysolecithin lesions, and by tissue culture experiments where the migration of fibroblasts was enhanced by macrophages. Of particular relevance to spontaneous regenerative events in lysolecithin demyelination, areas of fibroblast accumulation were devoid of oligodendrocyte precursor cells. In tissue culture, oligodendrocyte precursor cells were excluded from fibroblast domains. Moreover, fibroblast accumulation after lysolecithin injury was enhanced with increasing age, a known detriment to the capacity to remyelinate after injury, and exclusion of oligodendrocyte precursor cells from fibroblast areas of 48 - 52 week mice exceeds that occurring in younger 6 - 10 weeks animals. Finally, by mining a publicly available single-nucleus RNA database of multiple sclerosis, we found fibroblasts in the edge of chronic active and chronic inactive lesions and in lesion core, and fewer in periplaque or normal white matter. We identified several communication networks between fibroblasts, microglia/macrophages and oligodendrocyte precursor cells in these MS lesions. Our collective results demonstrate a role of fibroblasts in demyelination-associated neuropathology, which is exacerbated by aging, and highlight the importance of regulating fibroblasts to promote effective CNS repair.

neuroscience↗

bioRxiv2025

Engineering light robustness: Adaptive evolution uncovers new genetic determinants of HL tolerance in Synechocystis

Excess light absorption causes severe photo-oxidative damage and limits photosynthetic efficiency. Enhancing high-light (HL) tolerance and energy utilization in photosynthetic cyanobacteria holds great potential for sustainable biomanufacturing. Here, using Synechocystis sp. PCC 6803 (Syn6803) as a model, we generated eight independently evolved strains tolerant to hyper-HL (2000 mol photons/m2/s) through approximately two years of natural adaptive laboratory evolution (ALE). Remarkably, these strains circumvented common evolutionary trade-offs; all demonstrated markedly enhanced quantum yields and photosynthetic performance, with four strains exhibiting a 121.71%-168.36% increase in biomass accumulation under HL. When equipped with the heterologous sucrose transporter CscB, sucrose productivity under HL increased by up to 208.33%. Whole-genome resequencing unveiled a total of 77 mutations across the eight lineages, uncovering a diverse polygenic landscape for HL adaptation. Reverse genetics combined with structural modeling highlighted pivotal roles for regulatory and structural loci, including slr0758 (KaiC1) and slr1513 (SbtB), in modulating circadian rhythmicity and inorganic carbon uptake to prevent photo-oxidative overload. Overall, our findings uncover diverse evolutionary routes toward high-light acclimation and provide superior cyanobacterial chassis for photosynthetic biotechnology.

microbiology↗

bioRxiv2025

Study on physiological and ecological responses of alfalfa during the germination stage under drought, bicarbonate, and combined stress conditions

Alfalfa (Medicago sativa L.) is frequently constrained by drought and salinity during cultivation and production. This study aimed to investigate the differential response characteristics and underlying physiological and ecological mechanisms of alfalfa during the germination stage under drought stress, bicarbonate stress, and their combined effects. Twelve alfalfa varieties were subjected to germination tests using PEG-6000 to simulate drought stress (0-20%) and NaHCO{square} to simulate bicarbonate stress (0-30 mM). Based on the semi-inhibitory concentrations and phenotypic indices observed under single-stress conditions, a combined stress treatment was designed. The subordinate function method was employed to comprehensively evaluate the variations in stress responses among the twelve alfalfa varieties during the germination stage. Additionally, this study explored the physiological and ecological response mechanisms of drought-tolerant, salt-tolerant, and drought-salt-sensitive varieties. Among the 12 alfalfa varieties, WL363HQ has the strongest drought and salt tolerance, while WL319HQ is the most sensitive to drought and salt stress. Based on this, the varieties can be classified into drought-tolerant, salt-tolerant, and sensitive categories. At low concentrations, the drought-salt combination shows antagonism (salt alleviates drought inhibition); at high concentrations, it turns into synergy, and the inhibitory effect is amplified.WL363HQ adapts to the combined stress by maintaining stable SOD activity and gradually accumulating soluble sugar; WL319HQ shows sensitivity due to fluctuating SOD, membrane lipid peroxidation, and uncontrolled soluble sugar.

plant biology↗

bioRxiv2025

A PAM-CNN recognition approach to Muscle Fatigue of Special Operators by sEMG signals

Fatigue operation was the primary accident causes of large special equipment which could lead to serious economic loss and personnel injury or death, so the establishment of early fatigue warning methods was of great significance to reduce the accident rate. In view of the working environment and biomechanics properties of operators of special equipment, theoretical and experimental method was presented to analyze the fatigue mechanism and accumulate data samples, and then a new approach was proposed to recognize muscle fatigue by classifying these datasets. Firstly, in order to deduce fatigue mechanism, hidden Markov chain was adopted to build five-element theoretical model for studying interaction between machines and operators muscles during operation process, so that influence factors and tested points of muscles were approached; Surface electromyographic (sEMG) sensors were introduced to acquire muscle signals which were taken as sample data, and wavelet packet was adopted to extract features of these data. Subsequently, a convolutional neural network (CNN) classification model based on partial attention mechanism (PAM) was proposed to execute triple fatigue classification, moreover cross entropy-Adam algorithm was applied to train and optimize this model. Finally, large crane operators were taken as case studies to verify the proposed model. By comparison results indicated when the number of extracted features was 3 and the size of patch was [5,5], PAM-CNN model could approach the optimum solution of fatigue recognition, and the average accuracy could achieve 95.6% in test datasets, which showed a good potential in practical application.

bioengineering↗