Visualizing Single-Molecule Protein Conformational Transitions and Free Energy Landscape.

Monitoring the conformational dynamics of individual proteins is essential to understand the relationship between structure and function in molecular regulatory mechanisms. However, the fast dynamics of single proteins remain poorly understood. Here, we construct a single-molecule sensing platform by introducing plasmonic imaging of single nanoparticles to sense and report the protein conformational changes at the single-molecule level. Tracking the fluctuations of individual nanoparticles with high resolution, we detect and characterize distinct conformational states of molecular chaperone heat shock protein 90 (Hsp90). We also explore the conformational changes of Hsp90 in situ under different nucleotide conditions. Analysis of the conformational fluctuations between the open and closed states of single Hsp90 provides important information on free energy profiles, effective spring constants, and multiphase behaviors. This method offers a strategy to visualize the conformational changes of single proteins in real-time and provides insights into the underlying molecular mechanisms.

Physicochemical and Rheological Properties of Degraded Konjac Gum by Abalone (Haliotis discus hannai) Viscera Enzyme.

In the present study, a new degraded konjac glucomannan (DKGM) was prepared using a crude enzyme from abalone (Haliotis discus hannai) viscera, and its physicochemical properties were investigated. After enzymatic hydrolysis, the viscosity of KGM obviously decreased from 15,500 mPa·s to 398 mPa·s. The rheological properties analysis of KGM and DKGMs revealed that they were pseudoplastic fluids, and pseudoplasticity, viscoelasticity, melting temperature, and gelling temperature significantly decreased after enzymatic hydrolysis, especially for KGM-180 and KGM-240. In addition, the molecular weight of KGM decreased from 1.80 × 106 Da, to 0.45 × 106 Da and the polydispersity index increased from 1.17 to 1.83 after 240 min of degradation time. Compared with natural KGM, the smaller particle size distribution of DKGM further suggests enzyme hydrolysis reduces the aggregation of molecular chains with low molecular weight. FT-IR and FESEM analyses showed that the fragmented KMG chain did not affect the structural characteristics of molecular monomers; however, the dense three-dimensional network microstructure formed by intermolecular interaction changed to fragment microstructure after enzyme hydrolysis. These results revealed that the viscosity and rheological properties of KGM could be controlled and effectively changed using crude enzymes from abalone viscera. This work provides theoretical guidance for the promising application of DKGM in the food industry.

DCX knockout ferret reveals a neurogenic mechanism in cortical development.

Lissencephaly is a rare brain malformation for which our understanding remains limited due to the absence of suitable animal models that accurately represent human phenotypes. Here, we establish doublecortin (DCX) knockout ferrets as a model that faithfully replicates key features of the disorder. We reveal the critical roles of DCX in neural progenitor cell proliferation and radial glial fiber extension, processes essential for normal cortical development. Utilizing single-nucleus RNA sequencing (snRNA-seq) and spatial transcriptomics, we provide a detailed atlas of the lissencephalic cortex, illustrating disrupted neuronal lamination and the specific interactions between inhibitory and excitatory neurons. These findings enhance our understanding of the cellular and molecular mechanisms underlying lissencephaly and highlight the potential of DCX knockout ferrets as a valuable tool for neurodevelopmental research, offering insights into both the pathology of lissencephaly and the general principles of brain development.

Widely targeted metabolomic analysis reveals effects of yellowing process time on the flavor of vine tea (Ampelopsis grossedentata).

The bitter and astringent taste and miscellaneous smell of vine tea prevent its further development. In this study, we used a processing technology that mimics yellow tea to improve the flavor of vine tea and revealed its internal reasons through metabolomics. Sensory evaluation showed the yellowing process for 6-12 h reduced the bitterness and astringency significantly, and enriched the aroma. The improvement of taste was mainly related to the down-regulation of anthocyanins (54.83-97.38%), the hydrolysis of gallated catechins (34.80-47.81%) and flavonol glycosides (18.56-44.96%), and the subsequent accumulation of d-glucose (33.68-78.04%) and gallic acid (220.96-252.09%). For aroma, increase of total volatile metabolite content (23.88-25.44%) and key compounds like geraniol (239.32-275.21%) induced the changes. These results identified the positive effects of yellowing process on improvements in vine tea flavor and the key compounds that contribute to these changes.

Energy-efficient dynamic sensor time series classification for edge health devices.

BACKGROUND AND OBJECTIVE: Time series data plays a crucial role in the realm of the Internet of Things Medical (IoMT). Through machine learning (ML) algorithms, online time series classification in IoMT systems enables reliable real-time disease detection. Deploying ML algorithms on edge health devices can reduce latency and safeguard patients' privacy. However, the limited computational resources of these devices underscore the need for more energy-efficient algorithms. Furthermore, online time series classification inevitably faces the challenges of concept drift (CD) and catastrophic forgetting (CF). To address these challenges, this study proposes an energy-efficient Online Time series classification algorithm that can solve CF and CD for health devices, called OTCD. METHODS: OTCD first detects the appearance of concept drift and performs prototype updates to mitigate its impact. Afterward, it standardizes the potential space distribution and selectively preserves key training parameters to address CF. This approach reduces the required memory and enhances energy efficiency. To evaluate the performance of the proposed model in real-time health monitoring tasks, we utilize electrocardiogram (ECG) and photoplethysmogram (PPG) data. By adopting various feature extractors, three arrhythmia classification models are compared. To assess the energy efficiency of OTCD, we conduct runtime tests on each dataset. Additionally, the OTCD is compared with state-of-the-art (SOTA) dynamic time series classification models for performance evaluation. RESULTS: The OTCD algorithm outperforms existing SOTA time series classification algorithms in IoMT. In particular, OTCD is on average 2.77% to 14.74% more accurate than other models on the MIT-BIH arrhythmia dataset. Additionally, it consumes low memory (1 KB) and performs computations at a rate of 0.004 GFLOPs per second, leading to energy savings and high time efficiency. CONCLUSION: Our proposed algorithm, OTCD, enables efficient real-time classification of medical time series on edge health devices. Experimental results demonstrate its significant competitiveness, offering promising prospects for safe and reliable healthcare.

Neurobehavioral toxicity induced by combined exposure of micro/nanoplastics and triphenyltin in marine medaka (Oryzias melastigma).

Microplastics/nanoplastics (MNPs) inevitably coexist with other pollutants in the natural environment, making it crucial to study the interactions between MNPs and other pollutants as well as their combined toxic effects. In this study, we investigated neurotoxicity in marine medaka (Oryzias melastigma) exposed to polystyrene micro/nanoplastics (PS-MNPs), triphenyltin (TPT), and PS-MNPs + TPT from physiological, behavioral, biochemical, and genetic perspectives. The results showed that marine medaka exposed to 200 ng/L TPT or 200 µg/L PS-NPs alone exhibited some degree of neurodevelopmental deficit, albeit with no significant behavioral abnormalities observed. However, in the PS-MP single exposure group, the average acceleration of short-term behavioral indices was significantly increased by 78.81%, indicating a highly stress-responsive locomotor pattern exhibited by marine medaka. After exposure to PS-MNPs + TPT, the swimming ability of marine medaka significantly decreased. In addition, PS-MNPs + TPT exposure disrupted normal neural excitability as well as activated detoxification processes in marine medaka larvae. Notably, changes in neural-related genes suggested that combined exposure to PS-MNPs and TPT significantly increased the neurotoxic effects observed with exposure to PS-MNPs or TPT alone. Furthermore, compared to the PS-MPs + TPT group, PS-NPs + TPT significantly inhibited swimming behavior and thus exacerbated the neurotoxicity. Interestingly, the neurotoxicity of PS-MPs was more pronounced than that of PS-NPs in the exposure group alone. However, the addition of TPT significantly enhanced the neurotoxicity of PS-NPs compared to PS-MPs + TPT. Overall, the study underscores the combined neurotoxic effects of MNPs and TPT, providing in-depth insights into the ecotoxicological implications of MNPs coexisting with pollutants and furnishing comprehensive data.

Development and validation of a prediction model for heart failure in patients with heart valvular regurgitation.

AIMS: Patients with heart valvular regurgitation is increasing; early screening of potential patients developing heart failure (HF) is crucial. METHODS: From 1 November 2019 to 31 October 2023, a total of 509 patients with heart valvular regurgitation hospitalized in the Department of Cardiovascular Disease of the First Affiliated Hospital of Guangzhou University of Traditional Medicine were enrolled. Three hundred fifty-six cases were selected as the training set for modelling, and 153 cases were selected as the validation set for the internal validation of the model. RESULTS: A predictive model of heart failure with the following nine risk factors was developed: atrial fibrillation (AF), pulmonary infection (PI), coronary artery disease (CAD), creatinine (CREA), low-density lipoprotein cholesterol (LDL-C), d-dimer (DDi), left ventricular end-diastolic diameter (LVEDd), mitral regurgitation (MR) and aortic regurgitation (AR). The model was evaluated by the C-index [the training set: area under curve (AUC) 0.937, 95% confidence interval (CI) 0.911-0.963; the validation set: AUC 0.928, 95% CI 0.890-0.967]. Hosmer-Lemeshow test (the training set: χ2 10.908, P = 0.207; the validation set: χ2 4.896, P = 0.769) revealed that both the training and validation sets performed well in terms of model differentiation and calibration. Decision curve analysis showed that both the training and validation sets have higher net benefits, indicating that the model has good utility. Ten-fold cross-validation showed that the training set has high similarities with the validation set, which means that the model has good stability. CONCLUSIONS: The occurrence of heart failure in patients with valvular regurgitation has a significant correlation with AF, PI, CAD, CREA, LDL-C, DDi, LVEDd, MR and AR. Based on these risk factors, a prediction model for heart failure was developed and validated, which showed good differentiation and utility, high accuracy and stability, providing a method for predicting heart failure.

Simulator Verification Is Potentially Beneficial for the Fitting of Softband Bone Conduction Hearing Devices in Young Children.

HYPOTHESIS: The current study employed a skull-simulator verification method to assess whether the output of softband bone conduction hearing devices (BCHDs) at the manufacturer's default settings deviated widely from the target determined by the fitting formula. BACKGROUND: Real ear analysis is utilized for the verification of the fitting of air conduction hearing devices (ACHDs) in a variety of institutions. This procedure, however, has not been used in the fitting of BCHDs, largely due to the difficulty of testing the output of these devices to temporal bones. Despite the availability of skull simulators, they have not been utilized clinically to measure BCHD output. MATERIALS AND METHODS: This prospective, single-center study enrolled 42 subjects, aged 3 months to 10 years, with microtia-atresia-associated mild-to-severe bilateral conductive hearing loss. Hearing sensitivity was evaluated behaviorally by pure tone audiometry (PTA) in 22 subjects 4 years or older (the PTA group), and by auditory brainstem response (ABR) in 20 subjects younger than 4 years (the ABR group). Following 6 months of subjects wearing the prescribed softband BCHDs, their dial level (DL) thresholds were reassessed while using their own BCHDs, configured with zero gain across all frequencies, functioning solely as a bone vibrator. These DL thresholds were inputted into the fitting formula, desired sensation level-bone conduction devices (DSL-BCD) for children, to obtain the target values of BCHD output. The simulator output of the BCHD programmed at the manufacturer's default setting was measured in response to speech presented at 55, 65, and 80 dB SPL, followed by gain adjustment based on the differences between the simulator output and the target. Aided speech intelligibility index (SII) was measured before and after the gain adjustment. RESULTS: The softband BCHDs at the manufacturer's settings generally had lower output than the prescribed target values. This difference was larger at low frequencies and low levels. Across the 12 points tested (four frequencies from 500 to 4000 Hz multiplied by three levels), 22 (52.3%) and 42 (100%) BCHDs had deviations of +7 and +5 dB, respectively, at one point or more. The gain adjustments reduced the deviation and improved the SII values at the two lower levels of speech presented. CONCLUSION: The simulator output of softband bone conduction hearing devices (BCHDs) with the manufacturer's settings may exhibit significant deviations from the formula. Objective output verification should be considered a beneficial step in BCHD fitting and is recommended when applicable.

A family perspective for the mechanism of parent-child conflict on maternal anxiety in Chinese children with autism.

BACKGROUND: Mothers of children with autism reported higher levels of anxiety than mothers of typical children. This study revealed the relationship between parent-child conflict, children's problem behavior, parenting stress, and maternal anxiety from the perspective of the relationship within the family. METHODS: The State-Trait Anxiety Inventory (STAI) and Caregiver Strain Questionnaire (CGSQ) were used to measure maternal anxiety and parenting stress respectively from 102 mothers of children with autism. We also collected information on parent-child relationships and children's problem behaviors by using the Child-Parent Relationship Scale (CPRS) and Conners Parent Symptom Questionnaire (PSQ). RESULTS: Parent-child conflict positively predicted state and trait anxiety in mothers of children with autism. The severity of children's psychosomatic disorders fully mediated the positive association between parent-child conflict and state-trait anxiety in mothers of children with autism. Parenting stress significantly moderated the impact of parent-child conflict on maternal state anxiety and trait anxiety. CONCLUSION: In the case of children with autism spectrum disorders, parent-child conflict can directly affect maternal anxiety levels, especially when mothers have low levels of parenting stress. Parent-child conflict can also affect children's problem behaviors and thus indirectly affect maternal anxiety. Therefore, this study is of great significance for the alleviation of anxiety of mothers of autistic children and the family intervention for the early rehabilitation of autistic children.

Ectopic expression of BmeryCA in Bombyx mori increases silk yield and mechanical properties by altering the pH of posterior silk gland.

The silk glands are the specialized tissue where silk protein synthesis, secretion, and conformational transitions take place, with pH playing a critical role in both silk protein synthesis and fiber formation. In the present study, we have identified erythrocyte carbonic anhydrase (BmeryCA) belonging to the α-CA class in the silk gland, which is a Zn2+ dependent metalloenzyme capable of efficiently and reversibly catalyzing the hydrated reaction of CO2 to HCO3-, thus participating in the regulation of acid-base balance. Multiple sequence alignments revealed that the active site of BmeryCA was highly conserved. Tissue expression profiling showed that BmeryCA had relatively high expression levels in hemolymph and epidermis but is barely expressed in the posterior silk gland (PSG). By specifically overexpressing BmeryCA in the PSG, we generated transgenic silkworms. Ion-selective microelectrode (ISM) measurements demonstrated that specifically overexpression of BmeryCA in the PSG led to a shift in pH from weakly alkaline to slightly neutral conditions. Moreover, the resultant PSG-specific BmeryCA overexpression mutant strain displayed a significant increase in both silk yield and silk fiber mechanical properties. Our research provided new insights into enhancing silk yield and improving the mechanical properties of silk fibers.

Neural mechanisms of social comparison in subthreshold depression.

Social comparison is a common phenomenon in our daily life, through which people get to know themselves, and plays an important role in depression. In this study, event-related potential (ERP) was used to explore the temporal course of social comparison processing in the subthreshold depression group. Electrophysiological recordings were acquired from 30 subthreshold depressed individuals and 31 healthy individuals while they conducted the adapted dot estimation task. The ERP results revealed that there was a significant difference of feedback-related negativity (FRN) in the process of social comparison. Especially only in the subthreshold depression, the FRN amplitudes of worse off than some, better off than many comparisons were larger than those of upward comparisons and downward comparisons. Our results suggested that the abnormal reward sensitivity for worse off than some, better off than many comparisons might be prodromal symptoms in the subthreshold depression.

Potential New Target for Dry Eye Disease-Oxidative Stress.

Dry eye disease (DED) is a multifactorial condition affecting the ocular surface. It is characterized by loss of tear film homeostasis and accompanied by ocular symptoms that may potentially result in damage to the ocular surface and even vision loss. Unmodifiable risk factors for DED mainly include aging, hormonal changes, and lifestyle issues such as reduced sleep duration, increased screen exposure, smoking, and ethanol consumption. As its prevalence continues to rise, DED has garnered considerable attention, prompting the exploration of potential new therapeutic targets. Recent studies have found that when the production of ROS exceeds the capacity of the antioxidant defense system on the ocular surface, oxidative stress ensues, leading to cellular apoptosis and further oxidative damage. These events can exacerbate inflammation and cellular stress responses, further increasing ROS levels and promoting a vicious cycle of oxidative stress in DED. Therefore, given the central role of reactive oxygen species in the vicious cycle of inflammation in DED, strategies involving antioxidants have emerged as a novel approach for its treatment. This review aims to enhance our understanding of the intricate relationship between oxidative stress and DED, thereby providing directions to explore innovative therapeutic approaches for this complex ocular disorder.

High-Throughput Screening of PAM-Flexible Cas9 Variants for Expanded Genome Editing in the Silkworm (Bombyx mori).

Genome editing provides novel opportunities for the precise genome engineering of diverse organisms. Significant progress has been made in the development of genome-editing tools for Bombyx mori (B. mori) in recent years. Among these, CRISPR/Cas9, which is currently the most commonly used system in lepidopteran insects, recognizes NGG protospacer adjacent motif (PAM) sequences within the target locus. However, Cas9 lacks the ability to target all gene loci in B. mori, indicating the need for Cas9 variants with a larger editing range. In this study, we developed a high-throughput screening platform to validate Cas9 variants at all possible recognizable and editable PAM sites for target sequences in B. mori. This platform enabled us to identify PAM sites that can be recognized by both xCas9 3.7 and SpCas9-NG variants in B. mori and to assess their editing efficiency. Cas9 shows PAM sites every 13 base pairs in the genome, whereas xCas9 3.7 and SpCas9-NG have an average distance of 3.4 and 3.6 base pairs, respectively, between two specific targeting sites. Combining the two Cas9 variants could significantly expand the targeting range of the genome, accelerate research on the B. mori genome, and extend the high-throughput rapid screening platform to other insects, particularly those lacking suitable NGG PAM sequences.

Incidence and characteristic of deep venous thrombosis in hospitalized chronic heart failure patients.

BACKGROUND: This study was conducted to investigate the incidence of deep venous thrombosis (DVT), outcomes and its characteristics in patients with chronic heart failure (CHF) in a retrospective setting. OUTCOMES: Patients died of cardiac shock or acute exacerbation of heart failure (HF), admitted to intensive care unit (ICU) due to acute exacerbation of HF, patients decided to withdraw treatment and return home due to acute exacerbation of HF. METHODS: From January 2015 to June 2022, we admitted 359 patients diagnosed with CHF, and lower limb ultrasonography was performed for the examination of DVT after admission. The incidence of DVT was recorded and patients with known risk factors of VTE were identified and excluded after incidence of DVT was calculated. Patients' clinical data were then collected. RESULTS: The occurrence of DVT was 10.0% (36/359), as calf intramuscular vein thrombosis was the main constitution (n = 28, 75%). DVT patients with other factors (carcinoma, surgery, stroke, previous history of DVT) constituted a considerable part (33.3%, 12/36). Age, history of Diabetes Mellitus (DM), levels of DDi (D-Dimer), levels of alanine transferase (ALT) and left ventricular end-diastolic diameter (LVEDd) were independent predictors or risk factors of DVT in CHF patients, while chronic kidney disease (CKD) stage 1-4, white blood cell (WBC) and direct oral anticoagulant (DOAC) were protective factors. Incidence of DVT was correlated with a poor outcome of CHF patients (Pearson Chi-Square test, Value 19.612, P < 0.001). CONCLUSIONS: In this retrospective study, incidence of DVT was found to be relatively high among hospitalized CHF patients, while patients with DVT was associated with a poor prognosis.

The disordered extracellular matrix landscape induced endometrial fibrosis of sheep: A multi-omics integrative analysis.

Endometrial fibrosis leads to the destruction of endometrial function and affects reproductive performance. However, mechanisms underlying the development of endometrial fibrosis in sheep remain unclear. We use transcriptomic, proteomic, and metabolomic studies to reveal the formation mechanisms of endometrial fibrosis. The results showed that the fibrotic endometrial tissue phenotype presented fewer glands, accompanied by collagen deposition. Transcriptomic results indicated alterations in genes associated with the synthesis and degradation of extracellular matrix components, which alter metabolite homeostasis, especially in glycerophospholipid metabolism. Moreover, differentially expressed metabolites may play regulatory roles in key metabolic processes during fibrogenesis, including protein digestion and absorption, and amino acid synthesis. Affected by the aberrant genes, protein levels related to the extracellular matrix components were altered. In addition, based on Kyoto Encyclopedia of Genes and Genomes analysis of differentially expressed genes, metabolites and proteins, amino acid biosynthesis, glutathione, glycerophospholipid, arginine and proline metabolism, and cell adhesion are closely associated with fibrogenesis. Finally, we analyzed the dynamic changes in serum differential metabolites at different time points during fibrosis. Taken together, fibrosis development is related to metabolic obstacles in extracellular matrix synthesis and degradation triggered by disturbed gene and protein levels.

Models for Meibomian gland dysfunction: In vivo and in vitro.

Meibomian gland dysfunction (MGD) is a chronic abnormality of the Meibomian glands (MGs) that is recognized as the leading cause of evaporative dry eye worldwide. Despite its prevalence, however, the pathophysiology of MGD remains elusive, and effective disease management continues to be a challenge. In the past 50 years, different models have been developed to illustrate the pathophysiological nature of MGD and the underlying disease mechanisms. An understanding of these models is crucial if researchers are to select an appropriate model to address specific questions related to MGD and to develop new treatments. Here, we summarize the various models of MGD, discuss their applications and limitations, and provide perspectives for future studies in the field.

Pathological Characteristics and Classification of Unstable Coronary Atherosclerotic Plaques.

Important forensic diagnostic indicators of sudden death in coronary atherosclerotic heart disease, such as acute or chronic myocardial ischemic changes, sometimes make it difficult to locate the ischemic site due to the short death process, the lack of tissue reaction time. In some cases, the deceased died of sudden death on the first-episode, resulting in difficulty for medical examiners to make an accurate diagnosis. However, clinical studies on coronary instability plaque revealed the key role of coronary spasm and thrombosis caused by their lesions in sudden coronary death process. This paper mainly summarizes the pathological characteristics of unstable coronary plaque based on clinical medical research, including plaque rupture, plaque erosion and calcified nodules, as well as the influencing factors leading to plaque instability, and briefly describes the research progress and technique of the atherosclerotic plaques, in order to improve the study on the mechanism of sudden coronary death and improve the accuracy of the forensic diagnosis of sudden coronary death by diagnosing different pathologic states of coronary atherosclerotic plaques.

Uncovering the potential of APOD as a biomarker in gastric cancer: A retrospective and multi-center study.

Gastric cancer (GC) poses a significant health challenge worldwide, necessitating the identification of predictive biomarkers to improve prognosis. Dysregulated lipid metabolism is a well-recognized hallmark of tumorigenesis, prompting investigation into apolipoproteins (APOs). In this study, we focused on apolipoprotein D (APOD) following comprehensive analyses of APOs in pan-cancer. Utilizing data from the TCGA-STAD and GSE62254 cohorts, we elucidated associations between APOD expression and multiple facets of GC, including prognosis, tumor microenvironment (TME), cancer biomarkers, mutations, and immunotherapy response, and identified potential anti-GC drugs. Single-cell analyses and immunohistochemical staining confirmed APOD expression in fibroblasts within the GC microenvironment. Additionally, we independently validated the prognostic significance of APOD in the ZN-GC cohort. Our comprehensive analyses revealed that high APOD expression in GC patients was notably associated with unfavorable clinical outcomes, reduced microsatellite instability and tumor mutation burden, alterations in the TME, and diminished response to immunotherapy. These findings provide valuable insights into the potential prognostic and therapeutic implications of APOD in GC.

The Effect of Social Support on the Mental Health Literacy of Parents Who Have Children with Special Needs: A Moderated Mediating Effect.

Background: It is well known that parents play an important role in the family, particularly the mental health literacy of parents is essential for the growth and development of children. As the parents of children with special needs, they are facing more difficulties and psychological pressure, resulted in more mental health problems. Purpose: The current study examined the effect of social support on mental health literacy, and its underlying mechanisms regarding the mediating role of coping styles and moderating role of social comparison. Methods: Using a cross-sectional design, 165 parents of children with special needs (22-67 years old, M=37.72, SD=8.78) participated in the study. The general information questionnaire, Mental Health Literacy Scale (MHLS), Social Support Rating Scale, Simplified Coping Style Questionnaire, and Social Comparison Orientation Scale were used. Results: We found that objective support positively predicted the mental health literacy, positive coping style played a mediating role between objective support and mental health literacy. In addition, the relationship between objective support and positive coping styles was moderated by social comparisons; for lower levels of opinion social comparison, the effect of objective support on positive coping styles was significantly stronger. Conclusion: We revealed the underlying mechanisms between social support and mental health literacy. The present study has profound implications for mental health literacy services for parents who have children with special needs.

A Multitask Dynamic Graph Attention Autoencoder for Imbalanced Multilabel Time Series Classification.

Graph learning is widely applied to process various complex data structures (e.g., time series) in different domains. Due to multidimensional observations and the requirement for accurate data representation, time series are usually represented in the form of multilabels. Accurately classifying multilabel time series can provide support for personalized predictions and risk assessments. It requires effectively capturing complex label relevance and overcoming imbalanced label distributions of multilabel time series. However, the existing methods are unable to model label relevance for multilabel time series or fail to fully exploit it. In addition, the existing multilabel classification balancing strategies suffer from limitations, such as disregarding label relevance, information loss, and sampling bias. This article proposes a dynamic graph attention autoencoder-based multitask (DGAAE-MT) learning framework for multilabel time series classification. It can fully and accurately model label relevance for each instance by using a dynamic graph attention-based graph autoencoder to improve multilabel classification accuracy. DGAAE-MT employs a dual-sampling strategy and cooperative training approach to improve the classification accuracy of low-frequency classes while maintaining the classification accuracy of high-frequency and mid-frequency classes. It avoids information loss and sampling bias. DGAAE-MT achieves a mean average precision (mAP) of 0.955 and an F1 score of 0.978 on a mixed medical time series dataset. It outperforms state-of-the-art works in the past two years.